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Forecasting Jobs in the Supply Chain for Investments in Residential Energy Efficiency Retrofits in Florida

Permanent Link: http://ufdc.ufl.edu/UFE0043916/00001

Material Information

Title: Forecasting Jobs in the Supply Chain for Investments in Residential Energy Efficiency Retrofits in Florida
Physical Description: 1 online resource (147 p.)
Language: english
Creator: Fobair, Richard C, Ii
Publisher: University of Florida
Place of Publication: Gainesville, Fla.
Publication Date: 2012

Subjects

Subjects / Keywords: chain -- construction -- doors -- efficiency -- energy -- estimating -- factors -- forecasting -- fte -- hvac -- insulation -- job -- jobs -- manufacturing -- mining -- residential -- retrofit -- supply -- windows
Design, Construction and Planning -- Dissertations, Academic -- UF
Genre: Design, Construction, and Planning Doctorate thesis, Ph.D.
bibliography   ( marcgt )
theses   ( marcgt )
government publication (state, provincial, terriorial, dependent)   ( marcgt )
born-digital   ( sobekcm )
Electronic Thesis or Dissertation

Notes

Abstract: This research presents a model for forecasting the numbers of jobs created in the energy efficiency retrofit (EER) supply chain resulting from an investment in upgrading residential buildings in Florida. This investigation examined material supply chains stretching from mining to project installation for three product types: insulation, windows/doors, and heating, ventilating, and air conditioning (HVAC) systems. Outputs from the model are provided for the project, sales, manufacturing, and mining level. The model utilizes reverse-estimation to forecast the numbers of jobs that result from an investment. Reverse-estimation is a process that deconstructs a total investment into its constituent parts. In this research, an investment is deconstructed into profit, overhead, and hard costs for each level of the supply chain and over multiple iterations of inter-industry exchanges. The model processes an investment amount, the type of work and method of contracting into a prediction of the number of jobs created. The deconstruction process utilizes data from the U.S. Economic Census. At each supply chain level, the cost of labor is reconfigured into full-time equivalent (FTE) jobs (i.e. equivalent to 40 hours per week for 52 weeks) utilizing loaded labor rates and a typical employee mix. The model is sensitive to adjustable variables, such as percentage of work performed per type of product, allocation of worker time per skill level, annual hours for FTE calculations, wage rate, and benefits. This research provides several new insights into job creation. First, it provides definitions that can be used for future research on jobs in supply chains related to energy efficiency. Second, it provides a methodology for future investigators to calculate jobs in a supply chain resulting from an investment in energy efficiency upgrades to a building. The methodology used in this research is unique because it examines gross employment at the sub-industry level for specific commodities. Most research on employment examines the net employment change (job creation less job destruction) at levels for regions, industries, and the aggregate economy. Third, it provides a forecast of the numbers of jobs for an investment in energy efficiency over the entire supply chain for the selected industries and the job factors for major levels of the supply chain.
General Note: In the series University of Florida Digital Collections.
General Note: Includes vita.
Bibliography: Includes bibliographical references.
Source of Description: Description based on online resource; title from PDF title page.
Source of Description: This bibliographic record is available under the Creative Commons CC0 public domain dedication. The University of Florida Libraries, as creator of this bibliographic record, has waived all rights to it worldwide under copyright law, including all related and neighboring rights, to the extent allowed by law.
Statement of Responsibility: by Richard C Fobair.
Thesis: Thesis (Ph.D.)--University of Florida, 2012.
Local: Adviser: Kibert, Charles J.

Record Information

Source Institution: UFRGP
Rights Management: Applicable rights reserved.
Classification: lcc - LD1780 2012
System ID: UFE0043916:00001

Permanent Link: http://ufdc.ufl.edu/UFE0043916/00001

Material Information

Title: Forecasting Jobs in the Supply Chain for Investments in Residential Energy Efficiency Retrofits in Florida
Physical Description: 1 online resource (147 p.)
Language: english
Creator: Fobair, Richard C, Ii
Publisher: University of Florida
Place of Publication: Gainesville, Fla.
Publication Date: 2012

Subjects

Subjects / Keywords: chain -- construction -- doors -- efficiency -- energy -- estimating -- factors -- forecasting -- fte -- hvac -- insulation -- job -- jobs -- manufacturing -- mining -- residential -- retrofit -- supply -- windows
Design, Construction and Planning -- Dissertations, Academic -- UF
Genre: Design, Construction, and Planning Doctorate thesis, Ph.D.
bibliography   ( marcgt )
theses   ( marcgt )
government publication (state, provincial, terriorial, dependent)   ( marcgt )
born-digital   ( sobekcm )
Electronic Thesis or Dissertation

Notes

Abstract: This research presents a model for forecasting the numbers of jobs created in the energy efficiency retrofit (EER) supply chain resulting from an investment in upgrading residential buildings in Florida. This investigation examined material supply chains stretching from mining to project installation for three product types: insulation, windows/doors, and heating, ventilating, and air conditioning (HVAC) systems. Outputs from the model are provided for the project, sales, manufacturing, and mining level. The model utilizes reverse-estimation to forecast the numbers of jobs that result from an investment. Reverse-estimation is a process that deconstructs a total investment into its constituent parts. In this research, an investment is deconstructed into profit, overhead, and hard costs for each level of the supply chain and over multiple iterations of inter-industry exchanges. The model processes an investment amount, the type of work and method of contracting into a prediction of the number of jobs created. The deconstruction process utilizes data from the U.S. Economic Census. At each supply chain level, the cost of labor is reconfigured into full-time equivalent (FTE) jobs (i.e. equivalent to 40 hours per week for 52 weeks) utilizing loaded labor rates and a typical employee mix. The model is sensitive to adjustable variables, such as percentage of work performed per type of product, allocation of worker time per skill level, annual hours for FTE calculations, wage rate, and benefits. This research provides several new insights into job creation. First, it provides definitions that can be used for future research on jobs in supply chains related to energy efficiency. Second, it provides a methodology for future investigators to calculate jobs in a supply chain resulting from an investment in energy efficiency upgrades to a building. The methodology used in this research is unique because it examines gross employment at the sub-industry level for specific commodities. Most research on employment examines the net employment change (job creation less job destruction) at levels for regions, industries, and the aggregate economy. Third, it provides a forecast of the numbers of jobs for an investment in energy efficiency over the entire supply chain for the selected industries and the job factors for major levels of the supply chain.
General Note: In the series University of Florida Digital Collections.
General Note: Includes vita.
Bibliography: Includes bibliographical references.
Source of Description: Description based on online resource; title from PDF title page.
Source of Description: This bibliographic record is available under the Creative Commons CC0 public domain dedication. The University of Florida Libraries, as creator of this bibliographic record, has waived all rights to it worldwide under copyright law, including all related and neighboring rights, to the extent allowed by law.
Statement of Responsibility: by Richard C Fobair.
Thesis: Thesis (Ph.D.)--University of Florida, 2012.
Local: Adviser: Kibert, Charles J.

Record Information

Source Institution: UFRGP
Rights Management: Applicable rights reserved.
Classification: lcc - LD1780 2012
System ID: UFE0043916:00001


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1 FORECASTING JOB S IN THE SUPPLY CHAIN FOR INVESTMENTS IN RESIDENTIAL ENERGY EFFICIENCY RETROFITS IN FLORIDA By RICHARD C. FOBAIR II A DISSERTATION PRESENTED TO THE GRADUATE SCHOOL OF THE UNIVERSITY OF FLORIDA IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY UNIVERSITY OF FLORIDA 20 12

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2 20 12 Richard C. Fobair II

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3 For my g rand parents Curtis and Lavon Fobair, who said I could do anything!

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4 ACKNOWLEDGMENTS I thank Dr. Charles J. Kibert, Dr. Paul Oppenheim, Dr. James G. Sullivan, and Dr. Herbert Ingley III for their support, guidance and advice on conducting this research I n addition, I thank Dr. Kibert Dr. Sullivan, and Dr. Abd o l Chini for the employment opportunities that made this educational milestone a reality. Finally, I thank Dr. Mark Russell for his advice on navigating the rough waters encountered in the doctoral program.

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5 TABLE OF CONTENTS page ACKNO WLEDGMENTS ................................ ................................ ................................ .. 4 LIST OF FIGURES ................................ ................................ ................................ .......... 8 ABSTRACT ................................ ................................ ................................ ................... 12 CHAPTER 1 INTRODUCTION ................................ ................................ ................................ .... 14 Problem Statement ................................ ................................ ................................ 14 Research Quest ion ................................ ................................ ................................ 14 Objectives ................................ ................................ ................................ ......... 15 Assumptions ................................ ................................ ................................ ..... 15 Limitations ................................ ................................ ................................ ........ 15 Contributions ................................ ................................ ................................ ........... 16 Benefits ................................ ................................ ................................ ................... 16 Target Audience ................................ ................................ ................................ ..... 17 Organization of the Research ................................ ................................ ................. 17 Summary ................................ ................................ ................................ ................ 18 2 LITERATURE REVIEW ................................ ................................ .......................... 19 Background Information ................................ ................................ .......................... 19 Related Studies and Research on Job Creation ................................ ............... 19 Energy Dollars ................................ ................................ ........................... 20 Non Energy Benefit s ................................ ................................ .................. 20 Non Monetary Benefits ................................ ................................ .............. 20 Job Creation Input Output Models ................................ .......................... 21 Job Creation Louisiana Energy Fund ................................ ...................... 22 Job Creation Energy Saving Trust ................................ .......................... 23 U.S. Weatherization Assistance Program ................................ .................. 23 U.S. Bureau of Economic Analysis ................................ ............................ 24 Development and Construction Contributions to the US Economy ............ 24 Job Creation National Association of Home Builders (NAHB) ................. 24 Jobs and Renewable Energy ................................ ................................ ..... 24 Sustainable Construction and Economic Development ............................. 25 Calculating Job Creation ................................ ................................ ............ 26 Job Fore casting in Policy Making and Evaluations ................................ .... 27 Contextual Information ................................ ................................ ..................... 28 Non Energy Benefits ................................ ................................ .................. 28 Job Characteristics ................................ ................................ .................... 29 Construction Supply Chains ................................ ................................ ....... 30 Definitions: Jobs and Energy Efficiency Retrofits ................................ ............. 32

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6 Defining Jobs ................................ ................................ ............................. 32 Defining Energy Efficiency Retrofits ................................ ........................... 33 Data Classification and Sets ................................ ................................ ............. 34 2007 Economic Census ................................ ................................ ............. 35 2007 Census of Governments ................................ ................................ ... 35 2007 Census of Agriculture ................................ ................................ ........ 36 2009 S ervice Annual Survey ................................ ................................ ...... 36 Occupational Employment Statistics Survey ................................ .............. 36 National Compensation Survey ................................ ................................ .. 36 Davis Bacon Weatherization Wage Rates ................................ ................. 37 NAICS Codes ................................ ................................ ............................. 37 Literature Analysis ................................ ................................ ................................ .. 38 Recommendations ................................ ................................ ................................ .. 39 Summary ................................ ................................ ................................ ................ 41 3 METHODOLOGY ................................ ................................ ................................ ... 43 Description of Methodology ................................ ................................ .................... 43 Research Design ................................ ................................ ................................ .... 44 Step I: Literature Review ................................ ................................ .................. 44 Step II: Develop a Methodology ................................ ................................ ....... 45 Step III: Data Collection ................................ ................................ .................... 45 Step IV: Data Analysis ................................ ................................ ...................... 46 Step V: Develop a Prototype Model ................................ ................................ 47 Step VI: Test the Model ................................ ................................ .................... 48 Step VII: Develop the Final Model ................................ ................................ .... 49 Summary ................................ ................................ ................................ ................ 49 4 RESULTS ................................ ................................ ................................ ............... 55 Model Inputs ................................ ................................ ................................ ........... 55 Model Outputs ................................ ................................ ................................ ........ 55 Insulation ................................ ................................ ................................ .......... 56 Openings ................................ ................................ ................................ .......... 57 HVAC Systems ................................ ................................ ................................ 59 Summary ................................ ................................ ................................ ................ 60 5 ANALYSIS ................................ ................................ ................................ .............. 74 Sample Outputs ................................ ................................ ................................ ...... 74 Insulation ................................ ................................ ................................ .......... 74 Openings ................................ ................................ ................................ .......... 77 HVAC Systems ................................ ................................ ................................ 80 Summary of the Sample Outputs ................................ ................................ ..... 84 Job Factors ................................ ................................ ................................ ............. 85 Employment Multipliers ................................ ................................ ........................... 87 Average Wage Rates ................................ ................................ .............................. 87

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7 Average Hourly Cost ................................ ................................ ............................... 88 Time Job Rel ationships ................................ ................................ .......................... 89 Economic Impact Analysis ................................ ................................ ...................... 91 Summary ................................ ................................ ................................ ................ 91 6 SUMMARY AND CONCLUSIONS ................................ ................................ ........ 111 Resear ch Summary ................................ ................................ .............................. 111 Conclusions ................................ ................................ ................................ .......... 1 11 7 RECOMMENDATIONS FOR FUTURE RESEARCH ................................ ............ 117 Introduction ................................ ................................ ................................ ........... 117 Enhancements ................................ ................................ ................................ ...... 117 Mergers ................................ ................................ ................................ ................. 117 New Places ................................ ................................ ................................ ........... 118 Summary ................................ ................................ ................................ .............. 119 APPENDIX A PROCEDURES FO R CREATING AND USING THE MODEL .............................. 120 B DOLLAR BREAKDOWN TEMPLATE ................................ ................................ ... 123 C NAICS CODES FOR SUPPLY CHAINS ................................ ............................... 125 LIST OF REFERENCES ................................ ................................ ............................. 142 BIOGRAPHICAL SKETCH ................................ ................................ .......................... 146

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8 LIST OF FIGURES Figure page 2 1 Range of jobs per $1 million investment ................................ ............................. 42 3 1 Model process ................................ ................................ ................................ .... 50 3 2 Research design ................................ ................................ ................................ 50 3 3 HCM supp ly chain ................................ ................................ .............................. 51 3 4 OHM, OHE, HCM and HCE supply chains ................................ ......................... 52 3 5 Profit and OHO supply chains ................................ ................................ ............ 53 3 6 Model flowchart ................................ ................................ ................................ .. 54 4 1 Insulati on jobs by money source, contractor self performs all work .................... 62 4 2 Insulation jobs by sector, contractor self performs all work ................................ 62 4 3 Insulation jobs by pass thru, contractor self performs all work ........................... 63 4 4 Insulation jobs by money source, contractor subcontracts all work .................... 64 4 5 Insulation jobs by sector, contractor subcontracts all work ................................ 64 4 6 Insulation jobs by pass thru, contractor subcontracts all work ............................ 65 4 7 Openings jobs by money source, contractor self performs all work .................... 66 4 8 Openings jobs by sector, contractor self performs all work ................................ 66 4 9 Openings jobs by pass thru, contractor self performs all work ........................... 67 4 10 Openings jobs by money source, contractor subcontracts all work .................... 68 4 11 Openings jobs by sector, contractor subcontracts all work ................................ 68 4 12 Openings jobs by pass thr u, contractor subcontracts all work ............................ 69 4 13 HVAC systems jobs by money source, contractor self performs all work ........... 70 4 14 HVAC systems jobs by sector, contractor self performs all work ........................ 70 4 15 HVAC systems jobs by pass thru, contractor self performs all work ................... 71 4 16 HVAC systems jobs by money source, contractor subcontracts all work ........... 72

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9 4 17 HVAC systems jobs by sector, contractor subcontracts all work ........................ 72 4 18 HVAC systems jobs by pass thru, contractor subcontracts all work ................... 73 5 1 Insulation jobs by m oney source, contractor self performs all work .................... 93 5 2 Insulation jobs by sector, contractor self performs all work ................................ 93 5 3 Insulation jobs comparison of money source vs. sector, contractor self performs all work ................................ ................................ ................................ 93 5 4 Insulation jobs by pass thru, contractor self performs all work ........................... 94 5 5 Percent of total insulation jobs by pass thru, contractor self performs all work .. 94 5 7 Insulation jobs by sector, contractor subcontracts all work ................................ 95 5 8 Insulation jobs comparison of money source vs. sector, contractor subcontracts all work ................................ ................................ .......................... 95 5 9 Insulation jobs by pass thru, contractor subcontracts all work ............................ 96 5 10 Percent of total insulation jobs by pass thru, contractor subcontracts all work ... 96 5 11 Openings jobs by money source, contractor self performs all work .................... 97 5 12 Openings jobs by sector, contractor self performs all work ................................ 97 5 13 Openings jobs comparison of money source vs. sector, contractor self performs all work ................................ ................................ ................................ 97 5 14 Openings jobs by pass thru, contractor self performs all work ........................... 98 5 15 Percent of total openings jobs by pass thru, contractor self performs all work ... 98 5 16 Openi ngs jobs by money source, contractor subcontracts all work .................... 99 5 17 Openings jobs by sector, contractor subcontracts all work ................................ 99 5 18 Openings jobs comparison of money source vs. sector, contractor subcontracts all work ................................ ................................ .......................... 99 5 19 Openings jobs by pass thru, contractor subcontracts all work .......................... 100 5 20 Percent of total openings jobs by pass thru, contractor subcontracts all work .. 100 5 21 HVAC systems jobs by money source, contractor self performs all work ......... 101 5 22 HVAC systems jobs by sector, contractor self performs all work ...................... 101

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10 5 23 HVAC systems jobs comparison of money source vs. sector, contractor self performs all work ................................ ................................ .............................. 101 5 24 HVAC systems jobs by pass thru, contractor self performs all work ................. 102 5 25 Percent of total HVAC systems jobs by pass thru, contractor self performs all work ................................ ................................ ................................ .................. 102 5 26 HVAC systems jobs by money source, contractor subcontracts all work ......... 103 5 27 HVAC systems jobs by sector, contractor subcontracts all work ...................... 103 5 28 HVAC systems jobs comparison of money source vs. sector, contractor subcontracts all work ................................ ................................ ........................ 103 5 29 HVAC systems jobs by pass thru, contractor subcontracts all work ................. 104 5 30 Percent of total HVAC systems jobs by pass thru, contractor subcontracts all work ................................ ................................ ................................ .................. 104 5 31 Summary of the numbers of jobs created ................................ ......................... 105 5 32 Percent of total for the numbers of jobs created ................................ ............... 105 5 33 Percent of total for the hard cost and overhead cost categories ....................... 105 5 34 ................................ ................................ ................................ .................. 105 5 35 Job factors for insulation by money source ................................ ...................... 106 5 36 Job factors for openings by money source ................................ ....................... 106 5 37 Job factors for HVAC systems by money source ................................ .............. 106 5 38 Job factors for insulation by sector ................................ ................................ ... 107 5 39 Job factors for openings by sector ................................ ................................ .... 107 5 40 Job factors for HVAC systems by sector ................................ .......................... 107 5 41 Energy efficiency retrofit (EER) employment multipliers ................................ ... 108 5 42 Investment equation (AWR) ................................ ................................ ............. 108 5 43 Average wage rate equation ................................ ................................ ............. 108 5 44 Average wage rate comparison for all jobs ................................ ....................... 108

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11 5 45 Investment equation (AHC) ................................ ................................ .............. 108 5 46 Average hourly cost equation ................................ ................................ ........... 109 5 47 Average hourly cost comparison for energy efficiency retrofit jobs ................... 109 5 48 Time job relationship in the supply chain ................................ .......................... 109 5 49 FTE vs. actual jobs, insulation subcontracted ................................ .................. 110 5 50 Graph of time job occurrence ................................ ................................ ........... 110 B 1 Dollar breakdown template ................................ ................................ ............... 124 C 1 Insulation ................................ ................................ ................................ .......... 126 C 2 Doors/windows ................................ ................................ ................................ 128 C 3 HVAC systems ................................ ................................ ................................ 130 C 4 Hard cost equipment ................................ ................................ ........................ 133 C 5 Overhead equipment ................................ ................................ ........................ 138 C 6 Over head material ................................ ................................ ............................ 140 C 7 Overhead other ................................ ................................ ................................ 141 C 8 Profit ................................ ................................ ................................ ................. 141

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12 Abstract of Dissertation Presented to the Graduate School of the University of Florida in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy FORECASTING JOBS IN THE SUPPLY CHAIN FOR INVESTMENTS IN RESIDENTIAL ENERGY EFFICIENCY RETROFITS IN FLORIDA By Richard C. Fobair II May 20 12 Chair man : Charles J. Kibert Major: Design, Construction and Planning This research presents a model for forecast ing the number s of jobs created in the energy efficiency retrofit (EER) supply chain resulting from an investment in upgrad ing residential building s in Florida. Th is investigation examined material supply chains stretching from mining to project installation for three product types : insulation, windows/doors, and heating, ventilating, and air conditioning ( HVAC ) systems Outputs from the model are provided for the project sales, manufacturing, and mining level Th e model utilizes reverse estimation to forecast the number s of jobs that result from an investment. Reverse estimation is a process that deconstructs a total investment into its constituent parts. In this research, an investment is deconstructed into p rofit, overhead and hard costs for each level of the supply chain and over multiple iterations of inter industry exchanges. The model processes an investment amount, the type of work and method of contracting into a prediction of the number of jobs creat ed The deconstruction process utiliz es data from the U.S. Economic Census. At each supply chain level, the cost of labor is reconfigured into full time equivalent (FTE) jobs (i.e. equivalent to 40 hours per week for 52 weeks) utilizing loaded labor rate s and a typical employee mix The model is sensitive to adjustable variables, such as

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13 percentage of work performed per type of product, allocation of worker time per skill level, annual hours for FTE calculations, wage rate, and benefits. This research provides several new insight s in to job creation First, it provides definitions that can be used for future research on jobs in supply chains related to energy efficiency. Second, it provides a methodology for future investigators to calcul ate jobs in a supply chain resulting from an investment in energy efficiency upgrades to a building. The methodology used in this research is unique because it examines gross employment at the sub industry level for specific commodities. Most research on employment examines the net employment change (job creation less job destruction) at levels for regions, industries, and the aggregate economy. Third, it provides a forecast of the numbers of jobs for an investment in energy efficiency over the entire su pply chain for the selected industries and the job factors for major levels of the supply chain

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14 CHAPTER 1 INTRODUCTION This research will present a model for forecasting the numbers of jobs created in the energy efficiency retrofit (EER) supply chain resulting from an investment in upgrading residential buildings in Florida. EER activities include installing or upgrading mineral wool insula tion, glass doors/ windows, and heating, ventilating, and air conditioning ( HVAC ) systems. Th is research will provide new job definitions, a method to calculate the numbers of jobs and the job factors in the EER supply chain The results of this research may be used to forecast the employment effect before an investment will have been made. Problem Statement There has been no study found with an established and transparent methodology to forecast job creation for investments in EER activities or other typ es of construction activities. Previous research ha d reported job creation in numbers that are unclear and incomparable did not define jobs by FTEs or compensable hours worked n or explain ed how jobs were categorized Additionally, most had not explaine d the method utilized to calculate the results and none provide d the factors of job creation. Research Question The research question is written: H ow many direct indirect and induced jobs are created in the EER supply chain for an investment in residential structures in Florida ? The scope of this question is clarified by the following objectives, assumptions and limitations

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15 Objectives This research will have three objectives. First, d efine the job related terms specific to this research Second, d evelop a methodology that will standardize how jobs in the EER supply chain are categorized and calculated. The methodology should convert dollars invested in residenti al EER activities into jobs. Third, c reate a working model that will demons trate the methodology. The model should be flexible for various assumptions, allowing for changes in wage rates, benefits, number of annual compensable hours, and worker mix. The option of a contractor self performing versus subcontracting the work shoul d be available. Assumptions This research will make four assumptions. First, t he investment can be public, private or a combination of both types of dollars. Second, a reasonably accurate representation of the EER supply chain can be modeled. Third, a r easonably accurate dollar breakdown of the costs can be made for materials consumed at each level of the supply chain. Fourth, e nergy efficiency activities are very similar to construction activities because th e worker skills are identical. Limitations This research will have four limitations. First, t he 2007 U.S. Economic Census data w ill be used Second, t he model will use data for three EER supply chains (i.e. mineral wool insulation, glass doors / windows, and HVAC systems ). Third, t he model will us e state level (i.e. Florida) data for the project level of the supply chain. County level statistics exist; however, they are less complete than the state level statistics. Data for other states could be added. Fourth, t he model will be designed for res idential structures but can be modified to examine commercial construction

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16 Contribution s This research will contribute to the body of knowledge on EER activities in five ways. First, jobs in the EER supply chain will be defined T he new definitions will place the jobs into context and make distinctions between the categories of jobs that are necessary for performing the calculations. Second, a methodology will be developed that utilizes empirical data in a standardized fashion to forecast jobs in the EE R supply chain for investments made in residential structures. The methodology will be unique because it examines gross employment at the sub industry project and regional level s for specific categories of commodities. Most research on employment only examines the net employment change (job creation less job destruction) at levels for regions, industries, and /or the aggregate economy. Third, a working model of the methodology will be created. T he model will provide e stimates of the direct, indirect an d induced jobs in the EER supply chain for a given level of investment. C ontributions four and five will be the results of the model Fourth, the numbers of jobs for each product category will be displayed in a variety of formats Fifth, the factors of job creation for the four major levels of the supply chain (i.e. construction, sales, manufacturing and mining) will be provided. Benefits This research will have two major benefits. First, the numbers of jobs c ould be used in metrics for comparability an d decision making. For example, a $1 million investment c ould be compared to the number of jobs created in the EER supply chain. This investment to jobs comparison would be a form of cost to benefit analysis that c ould be used when comparing policy proposals Second, the factors of job creation will provide a better understanding of the employment structure of EER supply chains and

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17 c ould be used to calculate changes in employment on a regional level due to changes in magnitude of investment For ex ample, if the factors of jobs were based on a $1 million investment, then multiplying the manufacturing job factor by five would calculate the number of jobs at the same level for a $5 million investment. Knowing the number s of jobs and the factors of job creation will be an important development in understanding the economic effects that policy oriented towards energy efficiency has on economic development. Furthermore, t his new information will improve decision making when comparing and choosing between policy proposals Target Audience The primary target audience for using this model will be state level government agencies that are attempting to quantify the economic development impact of energy efficiency policy focused on the built environment. The s econdary target audience will be local economic development agencies that require a convenient method to compare and evaluate policy proposals whe n the metric of importance is number of job s created. Organization of the Research This research will be arranged in chapters. Chapter 1 will be the introduction of the research, including the problem statement and research question. Chapter 2 will be the literature review. This review will present previous studies and research relevant to the topic of th is research Terminology specific to this research will be explained. Chapter 3 will be the methodology. The process of deconstructing an investment in EER activities will be explained and an Excel model to demonstrate the process will be developed Ch apter 4 will be the results Sample outputs for each product category will be provided. Chapter 5 will be the analysis of the results. The sample outputs will be used to find the factors of job creation employment multipliers, average wage rates

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18 and a verage hourly costs The time relationship of jobs in the supply chain will be discussed, as well as the overall economic impact of a $1 million investment. Chapter 6 will be the summary and conclusion of the research Chapter 7 will be recommendations for fu ture research. The appendices will provide instructions for the working model an example of a template used in the model, and a complete list of census data used for each supply chain. Summary This chapter has introduced research that will invest igate the employment effect of investments in EER activities for residential use properties. The problem statement, research question, c ontributions benefits and target audience have been presented. The organization of the research has been outline d in to chapters.

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19 CHAPTER 2 LITERATURE REVIEW This chapter will be divided into three sections : Background Information, Literature Analysis, and Recommendations. Background Information will present p revious studies research and publications relevant to the topic of this research Literature A nalysis will analyze the previous literature for utility to this research and for shortcomings Recommendations will present improvements for the shortcomings Background Information Background Informa tion will be divided into four categories: Related Studies and Research on Job Creation, Contextual Information Definitions : Jobs and Energy Efficiency Retrofits and Data Classification and Sets Related Studies on Job Creation will summarize the avai lable studies and research that discuss the economic or employment effect of several types of investments Contextual Information will present literature that gives this research perspective. D efin itions : Jobs and Energy Efficiency Retrofits will review the terminology used to describe jobs and retrofits. Data Classification and Sets will provide information on the methods of classifying data and the sources of data used in this research. Related Studies and Research on Job Creation The topic of j ob creation can be typically found in literature that discuss es topics such as labor economics, employment, and economic development Occasionally, job creation had been mentioned tangentially as an effect of some activity; however, the act ivity had bee n the focus of the research, not the job creation. The s tudies and research related to the topic of this research are presented below. When applicable and for ease of comparison, the job creation numbers were presented per $1 million.

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20 Energy Dollars The U.S. Department of Energy looked at the stimulus effect of energy dollars on a community (Laitner 1996). Assuming energy wa s generated outside a community, reducing energy consumption would cause fewer energy dollars to flow out of the local economy; henc purchases. In general, each $1.00 used to purchase local consumer goods produced $1.90 of economic activity in the local economy because the store paid its employees who in turn purc hased more goods using the same $1.00. The economic activity of energy conservation policy are a significant benefit to local economies, but they inherently lack the abilit y to be tracked and measured for comparison of results. Although jobs are certainly created from the additional spending, quantifying the jobs created would be impossible. Non Energy Benefits Schweitzer and Tonn (2002) presented substantial energy and non energy benefits from weatherization. Analyzing federal funding invested in weatherization, they predicted $1.83 worth of energy benefits and $1.88 worth of non energy benefits. The non energy benefits included societal benefits, such as job creation, bu t the number and typ e of jobs had not been quantified. Non Monetary Benefits Tonn and Peretz (2007) discussed state level energy efficiency programs. They identified numerous non monetary benefits, including the creation of jobs and avoidance of job destr uction. The results of model programs indicated energy efficiency initiatives create jobs; however, neither a methodology for calculating jobs nor the characteristics

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21 of the jobs created (e.g. industry sector, skill level, full time, or part time) were gi ven. Consequently, the number of jobs created per level of investment could not be determine d throughout the supply chain Job Creation Input Output Models Input output models can analyze job creation through interdependencies between industry sectors a nd provide geographically based results. For example, Berry (1997) summarized an Iowa Study (The Statewide Low Income Collaborative Evaluation (SLICE) of Iowa 1994 ; found in Berry 1997 ) that used input output analysis to measure economic activity and job creation benefits. The SLICE investigators concluded $240,000 worth of additional economic activity was produced for each million dollars of program spending and determined 5.6 additional jobs were supported from the additional economic activity. This tr anslates to about 23 jobs per $1 million invested. Specific dollar values were not assigned to the non energy benefits; therefore, it was not possible to determine if the additional economic activity supporting the additional jobs was fully or only p artia lly funding the jobs. The SAVE Employment project ( Jeeninga et al. 1999) addresse d the employment impacts of energy conservation retrofits as a function of financing schemes (e.g., loans, subsidies, grants), based on case studies conducted in France, Germa ny, the Netherlands, Spain, the United Kingdom, and Finland. It use d an input output model as well, although it discusse d only residential retrofits, and it measure d the output in labor years generated. However, the study note d that the positive effect o n jobs due to energy efficiency programs wa s small compared to the large investment necessary. T he National Renewable Energy Laboratory (NREL) created the Job and Economic Development Impact Model (JEDI), a spreadsheet based approach for

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22 calculating employ ment and economic increases achieved by the construction of wind farms (Goldberg et al. 2004) The spreadsheet gather ed data on the size and location of the wind farm and include d regional considerations of spending patterns within local economies in orde r to determine the cost and employment benefits of wind farms and the stre ngth of the multiplier effect The multiplier effect is the economic effect from reinvestments back into the economy after an initial investment is made For example, after an init ial investment had been made to build a wind farm, the wages paid to employees of the farm will be spent in the local economy. Regional Economic Models, Inc. (REMI) is well known commercially for creating policy models that utilize an input output approach ; however, REMI models integrate input output techniques with other modeling approaches, including General Equilibrium (a balanced economy), Econometrics (estimating structural relationships with statistics), and New Economic Geography (spatial analysis of the economy) (REMI 2011). REMI models are powerful tools at the macro econometric level of analysis, but their predictive power does not transla te over to the micro level. Job Creation Louisiana Energy Fund Kaiser et al. (2004) reviewed, among other th ings, the employment that had been created by The Louisiana Energy Fund, a public private endeavor designed to provide publicly funded institutions with low cost, tax exempt financing to implement energy and water conservation projects in Louisiana. The y stated that for a total investment of $13.7 million by the Fund in projects across seven parishes, the associated employment increase was 297 jobs, or about 22 jobs per $1 million invested. They also predicted the creation of 16.2 jobs for ongoing mainte nance of the systems, costing approximately $490,000 annually, which approximates to 33 jobs per million dollars. The report d id not

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23 describe the methodology em ployed in this research and did not describe the types of energy conservation activities, types of jobs, nor how the job creation numbers had been determined. Job Creation Energy Saving Trust Wiltshire et al. (1998) reported on the Standards of Performance program run by the United Kingdom Energy Saving Trust (EST). It was designed to stimulate t he provision of cost effective energy saving measures throughout all sectors of the electricity franchise market. The scheme was funded via a customer levy of up to £1 per year for each customer, amounting to a total of £25 million over a four year period (1994 1998). The Public Electricity Suppliers (PESs) were required to give priority to schemes likely to exert general downward pressure on the charge per kWh to consumers in order to encourage demand side management measures. The report calculated that the program had generated 394 full time jobs per year over the four years, of which approximately half were in installation and half are in project management and administration. This corresponds to approximately 10 direct and indirect jobs per $1 million invested. The report also calculated that a total 67 in duced jobs have been generated which is about 1.68 jobs per $1 million U.S. Weatherization Assistance Program The U.S. Weatherization Assistance Program (WAP) is a D epartment of Energy venture that offers energy efficiency upgrades such as insulation and storm windows to low income families. The WAP Technical Assistance Center (TAC) website reports that the weatherization programs create 52 direct jobs and 23 indirect jobs for every $1 million inve sted (WAPTAC 2009).

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24 U.S. Bureau of Economic Analysis Construction sector modeling from the U.S. Bureau of Economic Analysis (BEA) predicts 26.67 direct, indirect and induced jobs per $1 million of spending in the construction industry (EOSI 2009). Home remodeling and bridge construction have been included with general construction. The average wage rate in the BEA model is about $19.00, which includes employer benefits. Development and Construction Contributions to the US Economy Fuller (2007) exam ined the ripple effect of construction spending across the life cycle of development, from the initial idea creation of a development project, through construction, and forward during ongoing maintenance and operations. He concluded that $1 million in new construction spending supported 28.5 annual full time jobs. He further state d the multiplier effect of a dollar inv ested in construction wa s 3.42. Job Creation National Association of Home Builders (NAHB) Fei Liu and Emrath (2008) report ed that the NAH B estimated 1.11 (FTE) jobs had been created per $100,000 spent on residential remodeling or 11.1 jobs per $1 million. Of the 11.1 jobs created per $1 million, construction jobs equal ed 5.4, manufacturing jobs equal ed 1.8, and other jobs equal ed 3.9. Thi s estimate wa s based on nat ional averages of home values. Jobs and Renewable Energy Sterzinger (2006) reported on enhancements to the Renewable Energy Policy Project (REPP) Jobs Calculator model that included a jobs locator feature. The original REPP Jobs Calculator only calculated direct jobs resulting from renewable energy development. The new model expanded to include multiple renewable technologies and the capability to locate where new economic activity may occur related to each type

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25 of renewable tec hnology. The Jobs Calculator produced three results: 1) Potential skill gaps, 2) Jobs created per MW of installed capacity per technology, and 3) Type of jobs by manufacturing, installation, and operation and maintenance. Labor was calculated as a functi on of [potentially] installed capacity, where the actual installation depend ed upon the enactment of a Renewable Portfolio Standard or other legislation or program. The marginal labor quantities per level of capacity used to calculate the final output was based on a survey of current industry practices. The jobs locator was based on a four step methodology that began with a review of the U.S. Census of Manufacturing data and utilized the six digit NAICS (North American Industrial Classification System) co des. After components of renewable energy equipment had been identified and linked with a NAICS code, cost was allocated by industry and allocated geographically by census data. Results of the calculator can be found in various REPP reports. For example the substantial number of jobs for developing wind energy will result from manufactur ing the equipment. Sustainable Construction and Economic Development Fobair (2009) discussed the increase in job opportunities related to sustainable building activities resulting from the 2008 09 federal stimulus funds. In response to sustainability becoming mainstream in the pol icy arena in the United States, Fobair reco mmended local planners critically examine economic development initiatives in search of sustainable job creation opportunities. He summarized the practice of urban planning has been criticized for its lack of identifying a definitive measurement procedure for sustainable policy. Furthermore, urban planning does not have a clear cut method to calculate the number of jobs created by an economic development program focused on ene rgy conservation in buildings.

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26 Fobair believed investments in energy conservatio n for existing buildings was a good path to sustainable economic development. He proposed the measurement of project level jobs created due to energy conservation investments would be a good predictor of success for a sustainable economic development poli cy, and presented a calculator to measure the number of jobs that could be created by energy conservation investments in exist ing buildings. The calculator wa s flexible and could be applied to commercial and/or residential buildings; however, some inputs into the calculator require d the opinion of experienc ed construction professionals. Calculating Job Creation Kibert, Fobair and Sullivan (2011) believed weatherization and construction worker skills are cross functional and proposed calculating these jobs using a full time equivalent (FTE) method. They presented a model for calculating jobs based on investments in energy conservation retrofits. The model was flexible. It considered multiple variables, provided three calculation methods based on user pref erences, and forecast direct jobs at the project level and indirect jobs at the manufacturing level. Based on national cost averages, Methods 1 and 2 indicate d approximately 10 direct jobs and 3 6 indirect jobs were created per $1 million. Method 3 indic ate d approximately 13 direct jobs and 3 5 indirect jobs were created per $1 milli on. The difference in results wa s due to Method 3 allow ing user defined material and labor splits that were more accurate than the default 50% 50% spli t utilized in Methods 1 and 2. The model used a reverse estimating technique to deconstruct an energy and then the cost of materials. Next, the model allocate d the labor portion of the inve stment based on loaded labor rates and typical crew make up. The input variables

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27 included worker skill level, allocation of worker time per skill level, regional effects on job creation, rate of pay, and worker benefits. The model did not consider taxes, administrative jobs embedded in overhead costs, or indirect jobs that could be created in other industry sectors from the profit markups. Additionally, jobs created in the supply chain before the project level up through and including the manufacturing l evel were calculated based on construction pricing schemes instead of retailer, wholesaler, and manufacturer pricing schemes. Job Forecasting in Policy Making and Evaluations Fobair and Kibert (2011) proposed calculating jobs from an investment in energy e fficiency retrofits for the project level through mining The retrofit work evaluated had been limited to energy efficient roofing systems/accessories (e.g. roof/ridge vents and radiant barriers); energy efficient doors and windows; window blinds and ther mal shades; additional insulation; weatherization (e.g. air sealing, low flow devices, and hot water tank insulation); heating and air conditioning system retrofits; and, upgrades to lighting systems. A preliminary estimate of direct and indirect jobs from the project through mining was provided. This estimate was used to demonstrate two new calculations: the Savings to Jobs Ratio (SJR) and Jobs from Energy Efficiency Retrofit Savings (JEERS) The SJR wa s the e stimated energy savings per year per job created from an investment in energy efficient retrofits. The JEER S wa s the e stimated number of indirect jobs created in the first year from energy savings. An example using a standard 150 m 2 home as the basis of design demonstrate d the calculations.

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28 C on textual I nformation Various studies and research question ed the accuracy of knowledge surrounding job creation from energy efficiency activities and in supply chains Arguments have been made that past efforts were not performed systematically, fallacies exist ed in measurements, and research approaches were oversimplified. The following s tudies and research provide a setting for this research. Non Energy Benefits Mills and Rosenfeld (1996) argued that non energy benefits deserve more emphasis when assessi ng energy efficiency technology and evaluating marketing and program activities for energy efficiency. The b enefits accrue d at the national, local and consumer levels; however, non energy benefits create d the most motivation to adopt energy efficient tech nologies at the consumer level. The consumer motivation stem med from the added value associated with non energy benefits, which is contrasted to the common approach of emphasizing energy services at lower co decision making had reflect ed that non energy costs have been typically emphasized over non energy benefits. The authors had summarized past research on non ene rgy benefits, which focus ed through reduced oil imports, job creation, local economic development induced by large scale efficiency programs, enhanced international competitiveness and reduced ld 1996, p. 708). They found that other authors had concluded knowledge of consumer non energy benefits was undeveloped, past efforts have not been performed systematically, and that data gaps exist in the literature on non energy e conomic benefits in bui ldings.

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29 Job Characteristics Davis et al. (1996) performed insightful research on the manufacturing industry and s pecifically focused on the establishments that employ workers. They used the Longitudinal Research Database (LRD) to perform the research. Th e LRD had been populated with data from Census Bureau economic surveys, namely Census of Manufacturers and the Annual Survey of Manufacturers. The Davis et al. (1996 ) research described the relationship between changes in employment and establishment chara cteristics such as size, industry, geographical location, level of wages, etc. It inferred restructuring and change in the economy are the rule and suggest ed large scale employment change will be part of every sector of the U.S. economy. When employment change will be occurring, creation and destruction in manufacturing will typically be associated with the startup or closing of a large plant. In o rder to avoid long term unemployment, the research advise d workers to stay flexible in terms of location and skill requirements of jobs. Davis et al. (1996) provide d explanations of terms commonly used in employment analysis. Job reallocation and worker r eallocation were n ot the same. Job reallocation was the job opportunity had been moved to a new location. Worker reallocation was a person entering or exiting the labor force or switching jobs. Although the concepts are distinct, overlap will exist betw een the two when calculating jobs. One third to one half of total worker reallocation will be due to job reallocation. Davis et al. (1996) foun d jobs that require greater human capital command higher wages and tend ed to be more stable. Human capital referred to the capacity of the worker to produce valuable goods or services. Jobs characterized by higher wages and

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30 greater human capital exhibit ed lower job reallocation. For example, jobs that pa id more for better skills were less l ikely to go oversea s. Davis et al. (1996) shed light on the common belief that small business create d most new jobs. In the manufacturing sector, this belief ha d been incorrectly promoted by statistical fallacies. Measurements of job creation have typically been performed by grouping companies that are similar in siz e. The fallacy of this method wa s that over time companies migrate between size categories. Based on SBA and government definitions of a small business, small employers create d approximately twenty percent of all new manufacturing jobs; however, small businesses in nonmanufacturing industries account ed for a larger percentage of job creation and destruction. The in depth analysis conclude d strong or sim Construction Supply Chains London (2008) developed the concept of describe the charact (London 2008; p. 2) London summarized that construction supply chain research of the past decade has taken three paths: 1) transactions at the project level, 2) transactions at the industry level, and 3) performance at a market level. These approaches have had weaknesses. They fail ed to emphasize the importance of the complex and varied connections between the supply chain levels, actors, markets and commodities. Firm firm procurement relationships have connect ed the project to many firms, industry markets, project markets and commodities These relationships form ed the which ties these

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31 London (2008) believed project performance depend ed on firm firm relationships thro ughout the chain of contracts. Firm firm procurement relationships have been based on contracts which were relationships, demand, sourcing strategies, supplier response and current market (Lon don 2008; p. 7). Most research has been on clients, contractors London (2008; p. 7) believed t he remaining chain of fi rm firm connections, also known as the supply chain, must be associated London (2008) discussed government economic models of performance, including input output analysis and industrial organization economic theory which ha s been but has not include d o f commodities and their markets London 2008; p. 8 9) Governments have play ed as controller of the regulatory framework, as a major client, and as policymaker have affec t ed the character of the industry ( Cox and Townsend 1998) in three ways: 1) Encourag ing competition or restrict ing practices (Warren 1993) ; 2) Allocat ing of budgets and capital works programs ; and, 3) Altering procedural systems and practices of suppliers with purchasing power Supply chains will begin with the clients who originate the design and construction process. Different clients for example the government, will impact suppliers differently.

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32 The degree of impact will depend on leverage. A client with leverage will manage resources in a supply chain in a manner that will appropriate value to oneself. Managing supply chai n resources has been difficult because the c onstruction industry has a fragmented structure and fragmented p rocesses. Fragmenta tion has lead to positive and negative benefits. For example, specialization of work has produce d a better product, but multiple layers of contracts in a delivery process will compound markups resulting in higher cost. Due to this fragmentation, t he auth or referenced work by Groak (1994) who suggested construction will be best represented by a multi industry model made of s everal overlapping industries. Firms in construction have provide d commodities, whether it wa s a service, p roduct, or product and serv ice. Supply chain behavior in construction has been influenced by the way the industry operates as a p roject based industry. It wa s unknown if the project based influence extend ed to the materials and manufacturer level, but it has influence d the subcont ractor and supplier level. Definitions : Jobs and Energy Efficiency Retrofits Definitions is divided into two categories: Jobs and Energy Efficiency Retrofits. Jobs will present existing terms and definitions that define a job. Energy Efficiency Retrofits will present existing terms and definitions that describe an energy efficiency retrofit. Defining Job s task. In many instances, it was defined by the number of hours worked per week, such as full time (40 hrs) or less than full time. In other cases, the benefits associated with the job determine d if it wa art ed on a person working a

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33 certain day of the week or time period (US DOL 2009). For example, a job wa s counted if a person work ed on the third Thursday of a month. The following terms provide a starting point for defining jobs in this research. described in the National Compensation Survey (USBLS 2011a) are classified as full time, versus a part time classification, based on how the employer defines the terms. described in the Current Population Survey (USCB 2006) and American Time Use Survey (USCB 2011) are p ersons who work 35 hours or more per week. is described as time hours (i.e ., not including overtime or holiday hours) worked by employees divided by the number of compensable hours applicable to each fiscal year. Annual leave, sick leave, and compensatory time off and other approved leave categories are considered to be for purposes of defining FTE employment (USGAO are associated with energy efficiency and are measured either by the output or process approach (USBLS 2010). They preserve or restore the environment either by producing green goods and providing green services or by using environmentally friendly production processes. are job s created for a project by an investment (White House 2009 a) are jobs created at the supplier who makes materials used in the project (White House 2009a) are job s created elsewhere in the economy when increased incomes from investment in the project lead to increased spending by w orkers and firms (White House 2009a). Defining Energy Efficiency Retrofits id not have a universal definition. Possible synonyms for the phrase include d: green retrofit home energy retrofit home retrofit deep energy retrofit home energy improvements and home performance retrofit The following examples provide a few of the definitions. Lovins (2004) of the R ocky Mountain Institute provided a taxonomic overview of en is d efined as (Lovins 2004, p. 383) : of function, service, or value provided to the energy converted to provide it. Herein,

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34 energy efficiency and its components all use (a) physical rather than economic metrics and (b) engineering, not eco nomic, definitions (this physical convention can, however, become awkward with multiple inputs or outputs). Energy efficiency may or may not count thermodynamic quality of energy (ability to do work); see the distinction between First Law and Second Law e Lovins (2004, p. 385) clarified that the term d to technical improvements in energy efficiency in stalled in existing buildings. An energy efficiency retrofit involve d changes that reduce home energy use, typically by up to 40% (White House 2009b) wa s a 50% reduction in energy consumption in an existing home compared to a newly built efficient home (Scanla 2010). The Environmental Energy Technologies Division of Lawrence Berkley Nat ional Laboratory pre ferred residential energy efficiency retrofits home performance retrofits The y re port ed consumer s have react ed which wa s often associated with the t home energy improvements wa s not explicitly defined; however, it implie d the improvements were to reduce energy consumption. D ata C lassification and S ets Government surveys provide large population, highly standardized data sets free for download from the Internet. Data sets of this nature will be necessary when analyzing supply chains. The following data sets and classification system will be utilized in this research.

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35 2007 Economic Census The federal government performs an economic census every five years, and the most recent data av ailable is for the year 2007. It is free for download and searchable search engine. For exam ple, contracting business data wa s available by geographic location, percentage of specialization in a type of construction (TOC), and kind of busines s activity (KOB) (USCB 2007 a ). As the largest and most comprehensive economic cen sus performed in the United States, t he data has been w idely used to formulate public policy on economic development. The 2007 Economic Census surveyed large and medium size firms using mailed report forms. Some small employers also received the mailed fo rms; however, gaps had been filled using administrative records of federal agencies. The collected data had been organized by North American Industry Classification System (NAICS) codes based on self reporting by the business establishments which effecti vely group ed the establishments into industries with similar production processes. Each data set ha d been itemized into defined categories. The categories represent ed a variety of statistics, including number of establishments, number of employees, payro ll, sales, receipts, revenue, expenses, value of shipments and value of construction work done. The statistics provided are for within the U.S. borders; therefore, the work product and labor is American. 2007 Census of Governments The Census of Governments prepared by the U.S. Census Bureau (USCB 2007b) provides information on government employment and finances. Revenue,

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36 expenditures, payroll, benefits and other data are routinely collected and reported every five years. This data is frequent ly used for public policy research. 2007 Census of Agriculture The Census of Agriculture, prepared by the U.S. Department of Agriculture (USDA 2007) provides information on farms and ranches providing agricultural products. Revenue, expenditures, payroll farm numbers, and other data are reported every five years. This is the only source of agricultural information for the entire nation. Data is arranged by North American Industry Classification System codes. 2009 Service Annual Survey The 2009 Service Annual Survey, prepared by the U.S. Census Bureau (USCB 2009) includes data for 2007. Estimates of revenues and expenses including payroll and benefits, are provide d for select service sectors. Sectors are arranged by North American Industry Classifica tion System codes. Occupational Employment Statistics Survey The Occupational Employment Statistics (OES) Survey provide d employment and wage estimates for specific occu pations. The mean annual wage wa s provided for occupations identified by Standard Occu pational Classification (SOC) c odes and by NAICS codes in t he OES data sets (USBLS 2007). National Compensation Survey The National Compensation Survey (NCS) provide d comprehensive data on occupational wages, benefits and employment co st trends. Part of t he survey wa s the Employer Costs for Employee Compensation (ECEC) publ ication. The ECEC measured the average cost to employers for wages and salaries and benefits per employee hour worked. The percent of total compensation was provided by industry

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37 and oc cupational group in the ECEC Historical Listing March 2004 March 2011 (USBLS 2011b). Davis Bacon Weatherization Wage Rates The Wage and Hour Division of the U.S. Department of Labor conducted a survey for the American Recovery and Reinvestment Act (ARRA) of 2009 to determine the prevailing wage rates for weatherization services (USDOL 2009). This survey was necessary for compliance with the Davis Bacon Act that requires contractors and subcontractors performing work on federally funded or assisted contra cts in excess of $2,000 to pay prevailing wages and fringe benefits equivalent to corresponding work on similar projects in the area. The survey was for all fifty states, and wages were reported for each county in each state. The data were reported in a tabular format Windows Replacement Worker Cooling Repair, Insta were provided for NAICS Codes The standard utilized by federal statistical agencies to classify business establishments by type of economic activity in the United States has been the North American Industry Classification System (NAICS) (OMB 2007). The NAICS is organized by a six digi t numbering system. Reading from left to right, the first two digits identify the business sector, the third digit identifies the subsector, the fourth digit identifies the industry group, the fifth digit identifies specific industries, and the sixth digi t

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38 identifies national industries. Appendix C has the complete list of NAICS codes for each product supply chain that will be used in this research. Literature Analysis The l iterature has been a naly zed to find shortcomings in the current body of knowledge. Several have been identified and the details will be provided below. Few studies and research related to j ob creation in the EER supply chain exist. Of the sources that are related, the results on numbers of jobs create d range d from about five to fifty two See Figure 2 1 for a summary of the range of jobs reported in other literature for a n equivalent $1 million dollar investment. This wide r ange i s unexplainable because most of the sources did not prov ide a methodology of how the jobs were calculated. Other deficiencies exist as well. Job definitions are ambiguous or not given, and the types of jobs counted are unclear. None of the studies addressed jobs throughout the entire supply chain. The topic of this research merge d three areas of knowledge together: job creation, energy efficiency retrofits, and supply chains. Authors (Mills and Rosenfeld 1996; Davis et al. 1996; London 2008) have writ ten about these individual subjects using language similar to the following: undeveloped, not performed systematically, gaps exist, statistical fallacies, fail to emphasize, have weaknesses, and must be better studied. The se individual subjects have been understudied, which partially explains the disconnect in n ot finding the topic of this research extensively written about in the literature while conducting this study Definitions depend ed on the usage and source. Several commonly used definitions for jobs and energy efficiency retrofits have been provided ; how ever, s ome disconnects exist ed between these definitions and this research T he following

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39 corrected in order to establish new definitions for this research. 1. The number of hours equaling a full year of work is not de finitive 2. The supply chain is not emphasized. 3. Green jobs addressing energy eff icien cy is a very broad subject. 4. Induced jobs from business to business exchanges outside of the supply chain and from utility savings reinvested in the economy are not addressed 5. Energy efficiency retrofit does not have a universally agreed upon definition. In summary, t he literature that has been analyzed supports a conclusion more research will be needed on job creation, energy efficiency retrofits, and supply chains, each as individual subjects and in combination. Two primary shortcomings have been identified. First, t he method of calculating jobs typically has not been provided Second, defini tions typically have not been provided explained or universal. Recommendations P roviding and explaining methodologies and definitions specific to job creation in EER supply chains would clarify which jobs will be counted and how. A new methodology will b e presented in the next chapter that utilizes data in a similar fashion to Sterzinger (2006). Changes have to be made to the old definitions in order to make new definitions specific to this research. Specifically, terms need to be accurately defined wit h measurable inputs/outputs. The new definitions are provided below. Direct Job : A job installing or managing the installation of finished products at the project level. Direct jobs occur at the end of the supply chain. Indirect Job : A job caused by in tra supply chain industry exchanges (i.e. raw materials or parts for manufacturing work in process), which includes administrative office jobs at the project level. Induced Job : A job caused by one of three sources: 1) inter industry exchanges outside of the product supply chain; 2) reinvestment of wages into the marketplace; and/or 3) reinvestment of utility savings into the marketplace. Full time Equivalent (FTE) : The total number of regular straight time hours (i.e., not including overtime or holiday ho urs) worked by employees divided by 2,080 hours per fiscal year. Annual leave, sick leave, and compensatory time off and other

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40 defining FTE employment; however, approved leave categories shall reflect a minimum of at least ten paid holidays and two weeks paid vacation pro rated evenly on an annual basis over the time of employment. Energy Efficiency Retrofit ( EER ) Job : A full time equivalent direct or indire ct green job found in the supply chain of an investment to retrofit a building for energy efficiency. EER jobs can be classified as created, retained, or reallocated. Energy Efficiency Retrofit ( EER ) Supported Job : A full time equivalent indu ced job found outside the supply c hain of an investment to retrofit a building for energy efficiency. EER supported jobs benefit from the retrofit investment. Energy Efficiency Retrofit (EER) [general] : C hanges made to an existing, functional, structure for reducing energy consumption. Energy Efficiency Retrofit (EER) [specific] : C hanges made to an existing, functional that the residential structure has previously received a certificate of occupancy fro m the local building department and/ or there is documented proof the structure has s peaking, are in working order and that the structure serves its intended purpose as triplex, town homes, cottages, mother in law suites and multifamily of three story or les condominiums or any other structure intended for residency that is over three stories or utilizes building systems design ed for commercial applications. Energy Efficiency Retrofit ( E ER ) Supply Chain : E nterprises connected by relationships that facilitate the flow of energy efficiency goods and services to an end. This research proposes ten levels exist in an EER supply chain. The levels are listed in reverse order, meaning the first level is actually the end of the supply chain. The ten levels are as follows: 1. Contractor 2. Subcontractor 3. Retailer 4. Wholesaler 5. Manufacturing Finished Product 6. Manufacturing Assembly Parts 7. Manufacturing Intermediate Parts 8. Manufacturing Beginning Parts 9. Mining Raw Materials 10. Mining Exploration and Development

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41 Levels one and two, contractor and subcontractor respectively, are the project phase of the supply chain. At these levels, EER products are installed in the residence. Levels three and four, retailer and wholesaler respectively, are the sales levels. Levels one, two and three can purchase materials from level four. Levels five through eight are for manufacturing. Level five is the finished product, which i s where the final assembly of a product takes place. Level six is the assembly parts. At this level, major sub parts are made, such as motors and compressors. Level seven is the intermediate parts, where wire, fuses, nuts and bolts are made. Level eigh t is the beginning parts. Beginning parts is the final processing of raw materials into billets, blooms, rod, plate, etc. Level nine is the mining of raw materials, which includes the extraction of material from the earth. Level ten is the exploration a nd development of land for mining, which includes surveying and land clearing. Summary This chapter has sum marized literature relevant to this research. First, background information has been provided on job creation, the context of t his research, definitions, and data sets. Next, it has been analyzed to find shortcomings in the existing body of knowledge. Finally, recommendations to correct the definitional shortcomings have been made. Recommendations to correct the methodological shortcomings will be made in the next chapter.

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42 Figure 2 1. Range of jobs per $1 million investment

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43 CHAPTER 3 METHODOLOGY The chapter will be divided into t wo sections : Description of Methodology and Research Design Description of Methodology will be the method of calculating job creation in the EER supply chain. Research Design will be the steps taken to conduct this research. Description of Methodology This methodology will utilize construction estimating and budgeting techniques to forecast jobs i n the EER supply chain for a given level of investment in residential structures. Specifically, a reverse estimation technique will be utilized to deconstruct an energy efficiency investment into profit, overhead and hard costs. Overhead and hard costs w ill be further broken down into the elemental pieces of an estimate, which are labor, materials, equipment, and other. The deconstructive process will be performed over the ten levels of the EER supply chain and repeated thirty five times for the multipli er effect. The methodology will be demonstrated in the form of an economic input output model. The basic process of the model is shown in Figure 3 1 The primary user input will be the amount of the investment; however, other adjust able variables will include the wage rate, allocation by percent of worker time per skill level, mix by percent of self performed versus subcontracted work (i.e. method of contracting) and type of supply chain (i.e. EER activity) The primary model outpu ts will be the numbers of jobs at each level of the EER supply chain. Division of the investment will be based on percentages extrapolated from survey data primarily found in the U.S. Economic Census The percentages are calculated

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44 using a dollar breakdown template made for this research The dollar breakdown template will distribute the survey data for each business establishment, identified by a NAICS code into eight accounts (i.e. Profit, Overhead Labor (OHL), Overhead Material (OHM), Over head Equipment (OHE), Overhead Other (OHO), Hard Cost Labor (HCL), Hard Cost Material (HCM), and Hard Cost Equipment (HCE)) in order to find the percent of total for each account The eight accounts will be explained later in Research Design, Ph ase IV: Data Analysis. The types of labor to be counted will include, but not be limited to, on site installers, manufacturing assemblers, administrative management, and administrative assistants. The labor portion of the investment will be converted int o full time equivalent (FTE) jobs utilizing loaded labor rates (i.e. the hourly wage rate plus benefits) and a reasonable management/crew mix. The FTE jobs will be displayed as direct, indirect and induced jobs. The material portion will cascade down to the next supply chain level where the division process will be repeated. The profit, equipment and other portions will form new supply chains for materials or services not associated with EER activities. These supply chains will follow a similar deconstr uction process. Th is dual process will continue for thirty five iterations until the entire initial investment has been converted into labor. Research Design The design process for this research had seven steps. The steps are shown in Figure 3 2 and will be described below. Step I: Literature Review Chapter 2 discussed the literature review Shortcomings in the existing body of knowledge have been identified, and new definitions have been provided for use in this re search.

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45 Step II: Develop a Methodology Input output models have been commonly used in the modeling of economic activity, such as the economic activity that occurs in a supply chain. For this research, t he flow of goods through a supply chain has been base d on transactions between many enterprises and a standard method of pricing the goods and services. The pricing method was to add a profit markup to the total cost. Profit markups typically were different for each industry and c osts include d some arrang ement of labor, materials, equipment, and overhead. E ach subsequent level downstream depend ed on the goods or services from the upstream level. Consequently, the inputs of each lower level would be th e outputs of the upstream level Complicating this cha in structure was the number of enterpr ises at any given level. M ultiple enterprises typically act ed as feeder chains that fl ow ed together to the next level. The problem in modeling supply chains for this research has been deciding how to unbundle the dollars systematically over the multiple levels and iterations. These iterations consist ed of passing material costs through a dollar breakdown to determine the distribution of profit, overhead and hard costs for each product and/or service. The goal has been to group monies into accounts that are similar across all levels of the supply chain and through all material pass thru iterations The accounts w ould become their own supply chains in subsequent iterations. Step I I I: Data Collection D ata collection involved searchi ng for existing data sets that w ould be applied to this research. Using the American FactFinder by the U.S. Census Bureau, data sets from the 2007 Economic Census were chosen These data sets have been arranged by

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46 North Ame rican Industry Classification System ( NAICS ) codes and provide d detailed information on the costs and materials consumed. The benefits to using the government collected data sets are larger populations and standardized data presentation. Step IV : Data Analysis For each of the three product categories (mineral wool insulation, glass doors / windows, and HVAC systems), files have been arranged in the ten levels of the EER supply chain. For each level, the appropriate data set had been downloaded from the 2 007 Economic Census and saved in a separate file. Each data set ha s been organized into defined categories with the units expressed in dollars. A template had been created in a format similar to an income sheet in order to standardize the format of the data for use in the model A copy of this template has been saved in each file and linked to its data set. This template provide s a breakdown of dollars that flow through each enterprise in the EER supply chain. For all data sets, the breakdown of dollars will be made into the following eight accounts: 1. Profit 2. Overhead Labor (OHL) 3. Overhead Material (OHM) 4. Overhead Equipment (OHE) 5. Overhead Other (OHO) 6. Hard Cost Labor (HCL) 7. Hard Cost Material (HCM) 8. Hard Cost Equipment (HCE) These accounts comply with standard industry defi n itions and practices. Profit i s the remaining m oney after all other costs have been covered. Overhead labor (OHL) i s the administrative personnel performing day to day business activities, e.g. company officer, manager, secretary and receptionist. Overhead materials (OHM) are basic

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47 office supplies required by administration. Overhead equipment (OHE) i s basic equipment required by administration, e.g. copiers and computers. Overhead other (OHO) i s a category for small miscellaneous company expenses, e.g. rent, communication services, data processing, insurance, professional/technical services, repair/maintenance, taxes/license fees, training, trash collection, utilities and travel. Hard cost labor (HCL) i s the producti on personnel from foreman to labor and described as skilled, semi skilled and unskilled. Hard cost material (HCM) i s the products, materials and equipment incorporated into a more complete or finished product. Hard cost equipment (HCE) i s the equipment u tilized in the processing, transportation or install ation of products or materials. Step V : Develop a Prototype Model The model i s an Excel spreadsheet with over a thousand tabs. The first tab i s an index with hyperlinks to other tabs. The next few tabs are for user defined inputs and model outputs (i.e. results). The i nputs include the magnitu d e of investment, whether work will be self performed or subcontracted, contractor mark up on subcontracted work, number of compensable hours for FTE calculations, employee mix, and wage rates. Outputs include the number of jobs produced for a given investment. The job numbers will be displayed in a variety of ways, including an economic format (e.g. direct, indirect and induced) and a construction estimating/budg et format (e.g. profit, overhead and hard cost, where overhead and hard cost will be subdivided into labor, materials, equipment and other). The remaining tabs are the working model. The procedure for using the model is fully described in Appendix A The model operate s by a user entering an investment amount and selecting a path for the EER supply chains. Selecting a path require s choosing the product category

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48 (i.e. mineral wool insulation, glass doors / windows, or HVAC systems) and who perform ed the installation (i.e. contractor self perform s or subcontracts) Other variables exist (e.g. wage rates and benefits), but it is recommended the u ser accept the default values. After inputs ha ve been made, the investment dollars initially cascad e through the ten levels of the H CM supply chain See Figure 3 3 for a diagram of the HCM supply cha in. T he HCM balance at one level bec omes the starting amount at the next level. At each level, th e labor account will be reconfigured into full time equivalent jobs utilizing loaded labor rates and a typical employee mix The remaining accounts will be grouped in like kind fashion to creat e two types of new supply chains For example, o ne will be for OHM, OHE, HCM, and HCE supply chains diagrammed in Figure 3 4 T he other w ill be for profit and OHO supply chains diagrammed in Figure 3 5 The diagram in Figure 3 6 illustrate s how dollars flow ed through these supply chains as part of the overall model. This initial flow of investment dollars through the HCM account will create direct and indirect jobs. Employment from the newly created supply chains will make induced jobs which result from the invested dollars turning over in the market from economic activity. The economic churn will be a repeating process; therefore, the dollars will in iterations convert ing the entire investment into labor Step V I : Test the Model The model had been tested and checked for mistakes After the mistakes had been corrected, t ables and graphs have been made to display the output from the model. The tables display the information in various formats, including by category of

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49 jo b (i.e. direct, indirect and induced), by level of the supply chain, and by iteration of the model. The graphs display the jobs created by level of the supply chain and by iteration of the model. A second iterative graph display s the cumulative number of jobs created over the supply chain. Step V I I : Develop the Final Model One final change had been made to the model after testing it. The number of iterations for the economic churn had been increased to thirty five from originally twenty This change all ow s more induced jobs to be counted when the initial investment i s a large dollar amount. S ample output from the model will be included in the next chapter. Summary This chapter has presented a new methodology to forecast jobs in the EER supply chain for residential structures in Florida. A working model demonstrating the methodology has been explained. The steps taken in the design of this research have been enumerated and discusse d

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50 Figure 3 1 Model process Figure 3 2 Research d esign

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51 Figure 3 3 HCM supply chain

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52 Figure 3 4 OHM, OHE, HCM and HCE supply chains

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53 Figure 3 5 Profit and OHO supply chains

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54 Figure 3 6 Model flowchart

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55 CHAPTER 4 RESULTS This chapter will present the results of the model First, the user inputs will be summarized. Second, the model outputs will be provided for three energy efficiency product categories: mineral wool insulation, glass doors / windows (i.e. openings) and HVAC systems. Model Inputs The primary user input is investment dollars, which represent ed the magnitude of the work to be performed. Additional inputs include d : 1. T he division of the investment by percentage over the three products: insulati on, openings, and HVAC systems; 2. T he division of each product by percentage between the contractor and subcontractor levels of the supply chain (i.e. an indication by percentage of the amount of work self performed by the contractor versus the amoun t of work subcontracted); 3. T and Performed and/or Sub acr oss multiple worker categories; 4. T he amo 5. T he Economic Census data sets relevant to the supply chain for the type of retrofit work to be performed. Model Outputs The primary outputs are the numbers of jobs as a function of the initial investment. Jobs are based on FTE calculations and have been organized by money source or sector For the money source, a job has been counted in the level the money origin a ted. For the sector, the job has been counted in the industrial sector where it occurred Jobs have been calculated by the method of contract ing, which c ould have been the contractor self perform ing or subcontract ing the work. Jobs have been arranged in two categories. The categories are t ype of job (i.e. direct, indirect or

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56 induced ) and c ost category (i.e. overhead or hard cost ). The number s of jobs have been presented i n four formats The formats are the following : 1. T en level s of the supply chain; 2. F our major levels of the supply chain (i.e. project, sales, manufacturing and mining); 3. P ass thru, which is dollars passing through th e model in multiple iterations (i.e. economic turnover or multiplier effect) ; and, 4. A ggregate The following are sample outputs for mineral wool insulation, glass doors / windows (i.e. openings) and HVAC systems. For th ese outputs the user input for EER investment h ad been set to $1 million. All other inputs had been set at the default levels discussed in Appendix A Insulation The results for mineral wool insulation have been displayed in Figures 4 1 through 4 6. Figures 4 1 4 2 and 4 3 display the results when the contractor i s self perform ing all of the installation work. Figure s 4 4 4 5 and 4 6 display the results when the contractor i s provid ing only management and coordination because all of the insta llation work has been subcontracted. Figure 4 1 displays the job results by the money source. Figure 4 2 displays the job results by the sector. For th ese formats 29.60 total jobs are forecast per one million dollars. The numbers of direct, indirect and induced jobs are 6.52 4.15 and 18.94 respectively. The numbers of hard cost and overhead jobs are 1 8.14 and 11.46 respectively. Jobs are also shown at each of the ten levels of the supply chain. Additionally, the ten levels have been grouped to indicate the subtotals of jobs at the project, sales, manufacturing, and mining levels. The results in Figure 4 1 for each of these four subtotals are 13.42 9.50 6.48 and 0.2 0 respectively. The results in Figure

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57 4 2 for each of these four subtotals are 10.71 12.84 5.84 and 0.2 1 respectively. Figure 4 3 displays the job results by the number of times money passe d through the ten levels of the supply chain. For this display, t hirty five iterations are shown, and each iteration i s 12.65 jobs. Additionally, the job numbers have been arranged by direct, indirect, ind uced, hard cost and overhead. Figure 4 4 displays the job results by the money source. Figure 4 5 displays the job results by the sector. For th ese formats 30.78 total jobs are created per one million dollars. The numbers of direct, indirect and induced jobs are 9.34 4. 39 and 1 7.05 respectively. The numbers of hard cost and overhead jobs are 19.85 and 10.93 respectively. Jobs are also shown at each of the ten levels of the supply chain. Additionally, the ten levels have been grouped to indicate the subtotals of jobs at the project, sales, manufacturing, and mining levels. The results in Figure 4 4 for each of these four subtotals are 16.82 8.30 5.49 and 0. 1 7 respectively. The results in Figure 4 5 for each of these four subtotals are 14.00 11.47 5. 12 and 0. 18 respectively. Figure 4 6 displays the job result s by the number of times money passe d through the ten levels of the supply chain. For this display, t hirty five iterations are shown, and each iterati on has been Additionally, the j ob numbers have been arranged by direct, indirect, ind uced, hard cost and overhead. Openings The results for openings, which include d windows and doors, have been displayed in Figure s 4 7 through 4 12. Figures 4 7 4 8 and 4 9 display the results when the contractor i s self perform ing all of the installation work. Figures 4 10 4 11 and 4 12

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58 display the r esults when the contractor i s provid ing only management and coordination because all of the insta llation work has been subcontracted. Figure 4 7 displays the job results by the money source. Figure 4 8 displays the job results by the sector. For these formats, 29.25 total jobs are forecast per one million dollars. The numbers of direct, indirect and induced jobs are 6.52 4.66 and 1 8.08 respectively. The numbers of hard cost and overhead jobs are 1 7 .94 and 1 1.31 respectively. Jobs are also shown at each of the ten levels of the supply chain. Additionally, the ten levels have been grouped to indicate the subtotals of jobs at the project, sales, manufacturing, and mining levels. The results in Figure 4 7 for each of these four subtotals are 13.46 9.14 6. 36 and 0. 3 0 respectively. The results in Figure 4 8 for each of these four subtotals are 10.73 1 2.30 5.96 and 0.2 6 respectively. Figure 4 9 displays the job results by the number of times money passes through the ten levels of the supply chain. For this display, thirty five iterations are shown, and each iteration i Additionally, the job numbers have been arranged by direct, indirect, induced, hard cost and overhead. Figure 4 10 displays the job results by the money source. Figure 4 11 displays the job results by the sector. For these fo rmats, 31.31 total jobs are forecast per one million dollars. The numbers of direct, indirect and induced jobs are 6.52 4.80 and 19.99 respectively. The numbers of hard cost and overhead jobs are 19.06 and 1 2.25 respectively. Jobs are also shown at e ach of the ten levels of the supply chain. Additionally, the ten levels have been grouped to indicate the subtotals of jobs at the project, sales, manufacturing, and mining levels. The results in Figure 4 10 for each of

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59 these four subtotals are 15.65 9.31 6.08 and 0. 27 respectively. The results in Figure 4 11 for each of these four subtotals are 1 1.88 1 3.16 6. 0 2 and 0.2 6 respectively. Figure 4 12 displays the job resul ts by the number of times money passe d through the ten levels of the supply chain. For this display, t hirty five iterations are shown, and each iteration i Additionally, the job nu mbers have been arranged by direct, indirect, induced, hard cost and overhead. HVAC Systems The results for HVAC Systems have been displayed in Figures 4 13 through 4 18. Figures 4 13 4 14 and 4 15 display the results when the contractor i s self perform ing all of the installation work. Figures 4 16 4 17 and 4 18 display the results when the contractor i s provid ing only management and coordination because all of the insta llation work has been subcontracted. Figure 4 1 3 displays the job results by the money source. Figure 4 14 displays the job results by the sector. For these formats, 29.06 total jobs are forecast per one million dollars. The numbers of direct, indirect and induced jobs are 6.52 4.56 and 17.98 respectively. The numbers of hard cost and overhead jobs are 17.73 and 11.33 respectively. Jobs are also shown at each of the ten levels of the supply chain. Additionally, the ten levels have been grouped to indicate the subtotals of jobs at the project, sales, manufacturing, and mining levels. The results in Figure 4 1 3 for each of these four subtotals are 13.41 9.4 8 5.87 and 0. 3 0 respectively. The results in Figure 4 14 for each of these four subtotals are 10.72 1 2.51 5. 53 and 0. 29 respectively. Figure 4 15 displays the job results by the number of times money passe d through the ten levels of the supply chain. For this display, thirty five iterations are shown, and each

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60 iteration i A dditionally, the job numbers have been arranged by direct, indirect, induced, hard cost and overhead. Figure 4 16 displays the job results by the money source. Figure 4 17 displays the job results by the sector. For these formats, 28.47 total jobs are fo recast per one million dollars. The numbers of direct, indirect and induced jobs are 5.95 5. 39 and 1 7.13 respectively. The numbers of hard cost and overhead jobs are 1 6.67 and 1 1.80 respectively. Jobs are also shown at each of the ten levels of the s upply chain. Additionally, the ten levels have been grouped to indicate the subtotals of jobs at the project, sales, manufacturing, and mining levels. The results in Figure 4 16 for each of these four subtotals are 11.87 9.88 6. 3 9 and 0. 3 3 respectively. The results in Figure 4 17 for each of these four subtotals are 10.12 12.38 5.67 and 0. 3 0 respectively. Figure 4 18 displays the job results by the number of times money passe d through the ten levels of the supply chain. For this display, t hirty five iterations are shown, and each it eration i Additionally, the job numbers have been arranged by direct, in direct, induced, hard cost and overhead. Summary An input output model ha d been developed to demonstrate the methodology in the prev ious chapter. The objective has been to forecast job creation in the supply chain for specific EER activities. Fir st, the user inputs have been summarized. Then, sample output results have been provided for three investment scenarios, which include installing mineral wool insulation, glass doors / windows, and HVAC systems. Results have been provided for different contracting methods (i.e. self perform vs.

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61 subcontracting), types of jobs (i.e. direct, indirect and induced), and cost categories (i.e. hard costs vs. soft costs). In addition, the numbers of jobs have been provided at the four ma jor levels of the supply chain (i.e. project, sales, manufacturing and mining).

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62 Figure 4 1. Insulation jobs by money source, contractor self performs all work Figure 4 2. Insulation jobs by sector, contractor self performs all work

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63 Figure 4 3. Insulation jobs by pass thru, contractor self performs all work

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64 Figure 4 4. Insulation jobs by money source, contractor subcontracts all work Figure 4 5. Insulation jobs by sector, contractor subcontracts all work

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65 Figure 4 6. Insulation jobs by pass thru, contractor subcontracts all work

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66 Figure 4 7. Openings jobs by money source, contractor self performs all work Figure 4 8. Openings jobs by sector, contractor self performs all work

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67 Figure 4 9. Openings jobs by pass thru, contractor s elf performs all work

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68 Figure 4 10. Openings jobs by money source, contractor subcontracts all work Figure 4 11. Openings jobs by sector, contractor subcontracts all work

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69 Figure 4 12. Openings jobs by pass thru, contractor subcontracts all work

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70 Figure 4 13. HVAC systems jobs by money source, contractor self performs all work Figure 4 14. HVAC systems jobs by sector, contractor self performs all work

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71 Figure 4 15. HVAC systems jobs by pass thru, contractor self performs all work

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72 Figure 4 16. HVAC systems jobs by money source, contractor subcontracts all work Figure 4 17. HVAC systems jobs by sector, contractor subcontracts all work

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73 Figure 4 18. HVAC systems jobs by pass thru, contractor subcontracts all work

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74 CHAPTER 5 ANALYSIS This chapter will analyze the results of the model. First, the sample outputs will be analyzed. Second, the job factors for the major supply chain levels will be discussed. Third, the average wage rates for the supply chains will be calculated. Fourth the time relationship between the investment and when jobs occur will be developed. Finally, the previous analyses will be brought together into an economic impact analysis Sample Output s In the previous chapter, sample outputs ha ve been provided for t hree product categories: mineral wool insulation, glass doors / windows, and HVAC systems. The outputs are the numbers of jobs The model ha s organized the jobs by money source or sector and ha s calculated by the method of contracting Additionally, the jobs ha ve been displayed in various formats and categories. The analysis considers all of these options. Insulation The analysis for mineral woo l insulation includes Figures 5 1 through 5 10. Figures 5 1 5 2 5 3 5 4 and 5 5 display the results when the contractor i s self perform ing all of th e installation work. Figures 5 6 5 7 5 8 5 9 and 5 10 display the results when the contractor i s providing only management and coordination and subcontract ing all of the installation work The job results displayed in Figure 5 1 are by the money source and in Figure 5 2 by the sector Figure 5 3 combines Figures 5 1 and 5 2 into a single chart for easy comparison. More jobs occur red at level one by money source than by sector, 1 3.42 versus 1 0.71 respectively. The opposite happen ed at lev els three and four. More jobs

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75 occur red by sector than by money source. At level five the lead change d again. The explanation is based on how the jobs are organized. Jobs organized by money source attribute the jobs to the level spending the money, wher eas the sector counts j obs at the level where the job is performed. Therefore, induced jobs are higher for the contractor and manufacturer of finished products because those levels provide more dollars being spent in the marketplace. Consequently, the sector jobs increase d at the retailer and wholesaler levels due to the increased spending. Very l ittle difference exist s in the numbers of jobs from level six through ten. The chart indicates no jobs are created in level two of the supply chain because the contractor is s elf perform ing all of the work. The jo b results displayed in Figure 5 4 are by p ass thru. Each pass thru represent s an iteration of the economic turnover in the marketplace. Figure 5 5 presents the cumulative total as a percentage of the numbers of jobs being cr eated for each pass thru. The f igures show 1 2.65 jobs, which i s 42.74%, are created in the first pass thru. Of the 1 2.65 jobs, the types of jobs (i.e. direct, indirect and induced) are about 51 %, 33 % and 16 %, respectively See Figure 4 3 in the previous chapter for details on the types of jobs More than 90% of all jobs had been created by the twelfth pass thru, and o ver 95% of all jobs had been created by the sixteenth pass thru; however all jobs created after the first pass thru are induced jobs. Direct and indirect jobs only occur red in the first pass thru, which i s the EER supply chain Induced jobs are EER supported. The jo b results displayed in Figure 5 6 are by t he money source and in Figure 5 7 by the sector. Figure 5 8 combines Figures 5 6 and 5 7 into a single chart for easy comparison. The chart indicates the same number of jobs 0.8 2 for each method, have

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76 been created in level one of the supply chain These jobs represent the management provided by contractors to oversee the work performed by subcontractors. Level two ha d a sharp increase in the numbers of jobs because of subcontracting. More jobs occur red at level two by money source than by sector, 16.00 versus 1 3.18 respectively. The opposite happen ed at levels three and four. More jobs occur red by sector than by money source. At level five the lead changed again. The explanation i s the same as before. The differences depend on how the jobs are organized. Jobs organized by money source attribute the jobs to the level spending the money, where as the sector counts j o bs at the level where the job i s performed. Therefore, induced jobs are higher for the contractor and manufacturer of finished products because those levels provide more dollars being spent in the marketplace. Consequently, the sec tor jobs increase at the retailer and wholesaler levels due to the increased spending. Very little difference exists in the numbers of jo bs from level six through ten. The jo b results displayed in Figure 5 9 are by pass thru. Each pass thru represent s an iteration of the economic turnove r in the marketplace. Figure 5 10 present s the cumulative total as a percentage of the numbers of jobs being cr eated for each pass thru. The f igures show 15.56 jobs, which i s 50.54 %, are created in the first pass thru. Of the 1 5.56 jobs, the types of jobs (i.e. direct, indirect and induced) are about 60 %, 28 % and 1 2 %, respectively. See Figure 4 6 in the previous chapter for details on the types of jobs. More than 90% of all jobs had been created by the eleventh pass thru, and over 95% of all jobs had been created by the fifteenth pass thru; however, all jobs created after the first pass thru are induced jobs. Direct and indirect

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77 jobs only occur red in the first pass thru, which i s the EER supply chain. Induced jobs are EER supported. When the contractor has been self perform ing or subcontract ing the work, the numbers of jobs d o not change regardless of the money source or sector. Of the total 29.60 jobs from the self perform calculation m ethod the types of jobs (i.e. d irect, indirect and induced) are about 22% 14% and 64%, respectively, and the cost categories (i.e. overhead and hard cost) are about 39% and 61%, respectively. Of the total 30.78 jobs from the subcontracting calculation m ethod, the types of jobs (i.e. di rect, indirect and induced) are about 31%, 14% and 55%, respectively, and the cost categories (i .e. overhead and hard cost) are about 3 5 % and 6 5 %, respectively. Openings The analysis for glass doors / windows (i. e. openings) includes Figures 5 11 through 5 20 Figures 5 11 5 12 5 13 5 14 and 5 15 display the results when the contractor i s self perform ing all of th e installation work. Figures 5 1 6 5 17 5 18 5 19 and 5 20 display the results when the contractor i s providing only management and coordination and subcontract ing all of the installation work. The jo b results displayed in Figure 5 1 1 are by t he money source and in Figure 5 1 2 by the sector. Figure 5 1 3 combi nes Figures 5 1 1 and 5 1 2 into a single chart for easy c omparison. More jobs occur red at level one by money source than by sector, 13.46 versus 1 0.73 respectively. The opposite happen ed at levels three and four. More jobs occur red by sector than by money source. At level five the lead change d again. The e xplanation i s based on how the jobs are organized. Jobs organized by money source attribute the jobs to the level spending the money, whereas the sector counts jobs at the level where the job i s performed. Therefore, induced jobs are higher

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78 for the contr actor and manufacturer of finished products because those levels provide d more dollars being spent in the marketplace. Consequently, the sector jobs increase d at the retailer and wholesaler levels due to the increased spending. For levels six through nine, the money source indicate d higher numbers than the sector. The explanation is based on the products being sold in those levels. Although much of the glass, aluminum extrusions and other products flow through the supply chain to become a door or win dow assembly, some of the assembly parts intermediate parts beginning parts and raw materials will be sold as parts or raw materials at the retailer and wholesaler level. At level ten, no difference exists in the numbers of jobs. The chart indicates no jobs are created in level two of the supply chain because the contractor i s self perform ing all of the work. The jo b results displayed in Figure 5 1 4 are by pass thru. Each pass thru represent s an iteration of the economic turnove r in the marketplace. F igure 5 1 5 present s the cumulative total as a percentage of the numbers of jobs being cr eated for each pass thru. The f igures show 1 3.06 jobs, which i s 44.66%, are created in the first pass thru. Of the 1 3.06 jobs, the types of jobs (i.e. direct, indirec t and induced) are about 5 0 %, 3 6 % and 1 4 %, respectively. See Figure 4 9 in the previous chapter for details on the types of jobs. More than 90% of all jobs had been created by the twelfth pass thru, and over 95% of all jobs had been created by the sixteenth pass thru; however, all jobs created after the first pass thru are induced jobs. Direct and indirect jobs only occur red in the first pass thru, which i s the EER supply chain. Induced jobs are EER supported.

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79 The jo b results displ ayed in Figure 5 1 6 are by t he money source and in Figure 5 1 7 by the sector. Figure 5 1 8 combines Figures 5 1 6 and 5 1 7 into a single chart for easy comparison. The chart indicates the same number of jobs, 0.8 2 for each method, are created in level one of the supply chain. These jobs represent the management provided by contractors to oversee the work performed by subcontractors. Level two ha d a sharp increase in the numbers of jobs because of subcontracting. More jobs occur red at level two by money s ource than by sector, 14.83 versus 1 1. 05 respectively. The opposite happen ed at levels three and four. More jobs occur red by sector than by money source. At level five the lead change d again. The explanation i s the same as before. The difference depe nd s on how the jobs are organized. Jobs organized by money source attribute the jobs to the level spending the money, whereas the sector counts jobs at the level where the job i s performed. Therefore, induced jobs are higher for the contractor and manufa cturer of finished products because those levels provide more dollars being spent in the marketplace. Consequently, the sector jobs increase at the retailer and wholesaler levels due to the increased spending. Level six had more jobs by sector than by mo ney source. The explanation is the jobs by money source have been included in the sales levels. Levels seven through nine ha d higher numbers of jobs by money source than sector. The explanation is the spending in these levels support more jobs than exist in these levels The jobs supported by spending in levels seven through nine on the money source chart have been included in the numbers for other levels on the sector chart. At level ten, no difference exists in the numbers of jobs

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80 The jo b results displayed in Figure 5 1 9 are by pass thru. Each pass thru represent s an iteration of the economic turnove r in the marketplace. Figure 5 2 0 present s the cumulative total as a perce ntage of the numbers of jobs being created for each pass thru. The Figures show 1 3.47 jobs, which i s 43.01 %, are created in the first pass thru. Of the 1 3.47 jobs, the types of jobs (i.e. direct, indirect and induced) are about 48 %, 36 % and 1 6 %, respecti vely. See Figure 4 12 in the previous chapter for details on the types of jobs. More than 90% of all jobs had been created by the twelfth pass thru, and over 95% of all jobs had been created by the six teenth pass thru; however, all jobs created after the first pass thru are induced jobs. Direct and indirect jobs only occur red in the first pass thru, which i s the EER supply chain. Induced jobs are EER supported. When the contractor has been self perform ing or subcontrac t ing the work, the numbers of jobs d o not change regardless of the money source or sector. Of the total 29.25 jobs from the self perform calculation method, the types of jobs (i.e. di rect, indirect and induced) are about 22%, 16% and 62%, respectively, an d the cost categories (i.e. overhead and hard cost) were about 39% and 61%, respectively. Of the total 31.31 jobs from the subcontracting calculation method the types of jobs (i.e. di rect, indirect and induced) are about 2 1 %, 1 5 % and 64 %, respectively, a nd the cost categories (i .e. overhead and hard cost) are about 3 9 % and 6 1 %, respectively. HVAC Systems The analysis for HVAC Systems includes Figures 5 21 through 5 30. Figures 5 21 5 22 5 23 5 24 and 5 25 display the results when the contractor i s self performing all of th e installation work. Figures 5 26 5 27 5 28 5 29 and 5 30 display the results

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81 when the contractor i s providing only management and coordination and subcontracting all of the installation work. The job results displayed in Figure 5 2 1 ar e by t he money source and in Figure 5 2 2 by the sector. Figure 5 23 combines Figures 5 2 1 and 5 2 2 into a single chart for easy comparison. More jobs occur red at level one by money source than by sector, 1 3.41 versus 1 0.72 respectively. The opposite happen ed at levels three and four. More jobs occur red by sector than by money source. At level five the lead change d again. The explanation i s based on how the jobs are organized. Jobs organized by money source attribute the jobs to the level spending the money, whereas the sector counts j o bs at the level where the job is performed. Therefore, induced jobs are higher for the contractor and manufacturer of finished products because those levels provide more dollars being spent in the marketplace. Conse quently, the sector jobs increase at the retailer and wholesaler levels due to the increased spending. For levels six through nine, the money source indicate d higher numbers than the sector. The explanation is based on the products being sold in those le vels. Although much of the fittings, connectors and other products flow through the supply chain to become a n HVAC system some of the assembly parts, intermediate parts, beginning parts and raw materials will be sold as parts or raw materials at the reta iler and wholesaler level. At level ten, no difference exists in the numbers of jobs. The chart indicates no jobs are created in level two of the supply chain because the contractor i s self performing all of the work. The jo b results displayed in Figure 5 2 4 are by pass thru. Each pass thru represent s an iteration of the economic turnover in the marketplace. Figure 5 2 5

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82 present s the cumulative total as a percentage of the numbers of jobs being cr eated for each pass thru. The f igures show 1 2.97 jobs, wh ich is 4 4.64 %, are created in the first pass thru. Of the 1 2.97 jobs, the types of jobs (i.e. direct, indirect and induced) are about 5 0 %, 3 5 % and 1 5 %, respectively. See Figure 4 15 in the previous chapter for details on the types of jobs. More than 90% of all jobs had been created by the twelfth pass thru, and over 95% of all jobs had been created by the sixteenth pass thru; however, all jobs created after the first pass thru are i nduced jobs. Direct and indirect jobs only occur red in the first pass thru, which i s the EER supply chain. Induced jobs are EER supported. The job results displa yed in Figure 5 2 6 are by t he money source and in Figure 5 2 7 by the sector. Figure 5 2 8 com bines Figures 5 2 6 and 5 2 7 into a single chart for easy comparison. The chart indicate s the same number of jobs, 0.8 2 for each method, are created in level one of the supply chain. These jobs represent the management provided by contractors to oversee t he work performed b y subcontractors. Level two had a sharp increase in the numbers of jobs because of subcontracting. More jobs occur red at level two by money source than by sector, 1 1. 05 versus 9.30 respectively. The opposite happen ed at levels three and four. More jobs occur red by sector than by money source. At level five the lead change d again. The explanation i s the same as before. The difference depend s on how the jobs are organized. Jobs organized by money source attribute the jobs to the level spending the money, whereas the sector counts jobs at the level where the job i s performed. Therefore, induced jobs are higher for the contractor and manufacturer of finished prod ucts because those levels provide more dollars being spent in the marketplace. Consequently, the sector jobs increase at

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83 the retailer and wholesaler levels due to the increased spending. Levels s ix through nine ha d higher numbers of jobs by money source than sector. The explanation is the spending in these levels support more jobs than exist in these levels. The jobs supported by spending in levels s ix through nine on the money source chart have been included in the numbers for other levels on the secto r chart. At level ten, no difference exists in the numbers of jobs. The jo b results displayed in Figure 5 2 9 are by pass thru. Each pass thru represent s an iteration of the economic turnove r in the marketplace. Figure 5 3 0 presents the cumulative total as a percentage of the numbers of jobs being cr eated for each pass thru. The f igures show 1 3.05 jobs, which i s 4 5 84 %, are created in the first pass thru. Of the 1 3.05 jobs, the types of jobs (i.e. direct, indirect and induced) are about 4 6 %, 41 % and 1 3 % respectively. See Figure 4 1 8 in the previous chapter for details on the types of jobs. More than 90% of all jobs had been created by the twelfth pass thru, and over 95% of all jobs had been created by the six teenth pass thru; however, all jobs created after the first pass thru are induced jobs. Direct and indirect jobs only occur in the first pass thru, which i s the EER supply chain. Induced jobs are EER supported. When the contractor ha s self perform ing or subcontract ing the work, the numbers of jobs d o not change regardless of the money source or sector. Of the total 29.06 jobs from the self perform calculation method the types of jobs (i.e. direct, indirect and induced) are about 22%, 1 6 % and 6 2 %, respec tively, and the cost categories (i .e. overhead and hard cost) are about 39% and 61%, respectively. Of the total 28.47 jobs from the subcontracting calculation method the types of jobs (i.e. direct, indirect and

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84 induced) are about 21 %, 1 9 % and 60 %, respec tively, and the cost categories (i .e. overhead and hard cost) are about 41 % and 59 %, respectively. Summary of the Sample Outputs The sample outputs have been analyzed for the various options offered by the model. Level one had the great est number of jobs when work had been self performed. Conversely, level two had the great est number of jobs when work had been subcontracted. Comparing the jobs organized by money source to those by sector provides a n insight into which level is supporting the jobs with ec onomic activity. For example, the economic activity in levels one, two and five support the jobs at level three and four. Figure 5 3 1 summarizes the results for all three product categories and both methods of contracting. Figure 5 3 2 provides the percent of total for the results. The results are the same for money source and sector. The numbers of direct jobs 6.52 at 22%, is the same for all categories of products w hen the contractor has been self perform i ng the work The exp lanation is the same data set had been used for the contractor regardless of the type of work performed. The number s of direct jobs are different when the work has been subcontracted because a different subcontractor perform ed each category of work Subcontracting create d 9.34, 6.52 and 5.95 direct jobs for insulation, openings, and HVAC systems, respectively. Self performing insulation installations create d the least amount of indirect jobs (4.15). Subcontracting door / windo w installations (i.e. openings) create d the greatest number of total jobs (31.31) and induced jobs (19.99) Subcontracting HVAC systems create d the least number of total jobs (28.47) and direct jobs (5.95), but it create d the greatest number of indirect j obs (5.39) Subcontracting insulation create d the greatest number of direct jobs (9.34) and the least number of induced jobs (17.05).

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85 The average total number of jobs for self performing work wa s 29.30. The average percent of direct and indirect jobs fo r self performing work wa s about 37%. The average total number o f jobs for subcontracting work wa s 30.19. The average percent of direct and indirec t jobs for subcontracting work wa s about 40%. Figure 5 3 3 provides the percent of total for the hard cost and overhead cost categories. Hard costs account ed for 61% of the jobs when work wa s self performed. For subcontracting, the percentage wa s about the same if the average is taken. Figure 5 3 4 On average, performing work. For all scenarios, obs ; however, subcontracting insulation made it by the fifteenth. Job Factors The EER supply chain has ten levels, which can be reduced to four by combining the levels based on commonality of industries. The four levels are project, sales, manufacturing a nd mining. The number of jobs at each of these four levels can be thought of as a factor. The project level factor is 1.0. When the number of project level jobs is known, it can be multiplied by the factor for any other level to find the number of jobs. Essentially, t he factors represent a structure to the relationship of job creation in the EER supply chain. Figures 5 35 5 36 and 5 37 provide t he job creation factors by money source for each of the product categor ies The money source indicates the level of supply chain spending the dollars that create economic activity and ultimately jobs. The EER supply chain flows from the mining to project level; however, interpreting the results requires analyzing the supply chain in reverse order from the project to mining level. For the results organized by money source, t he factors decreasing at a

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86 gr eater rate translates to more jobs at the end of the supply chain. Subcontracting insulation ha d the greatest factor decay between the project and sales levels, making it the best option for maximizing project level jobs. Subcontracting openings wa s a cl ose second. The manufacturing level create d less than half as many jobs as the project level. The mining level create d about two hundredths of as many jobs as the project level. The average job factors of the three product categories for self performing work wa s 1.00, 0.70, 0.46 and 0.02, respectively for project, sales, manufacturing, and mining. The average job factors of the three product cate gories for subcontracting work wa s 1.00, 0.64, 0.42 and 0.02, respectively for project, sales, manufacturing, and mining. Figures 5 38 5 39 and 5 40 provide t he job creation factors by sector for each of the product categories The results organized by sector indicate where the jobs actually o ccur. Sales level job factors were greater than 1.0 for all scenarios except for subcontracting insulation, which decrease d to 0.82 The g reatest sales level job factor wa s 1.22 for subcontracting HVAC systems. The manufacturing level create d about half as many jobs as the project level except for subcontracting insulation, which ma de about one third of the jobs. The mining level create d about two hundredths of as many jobs as the project level. The average job factors of the three product categ ories for self performing work wa s 1.00, 1.17, 0.54 and 0.02, respectively for project, sales, manufacturing, and mining. The average job factors of the three product cate gories for subcontracting work wa s 1.00, 1.05, 0.48 and 0.02, respectively for project, sa les, manufacturing, and mining.

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87 Employment Multipliers Employment multipliers measure how job creation or destruction in one or more industries results in employment changes throughout the broader economy. In this research, the employment multipliers indi cate how many EER supported jobs, i.e. induced jobs could be created from EER jobs, i.e. direct and indirect jobs Figure 5 41 shows the EER employment multipliers based on sector results for the three EER supply chain categories. The results are for self performed and subcontracted work Self performed insulation and subcontracted openings have the highest employment multiplier at 2.77. Subcontracted insulation has the lowest employment multiplier at 2.24. The average employment multiplier of the three product categories for self performing work is 2.67. The average employment multiplier of the three product categories for subcontracting work is about 2.51. Average Wage Rate s The average wage rate (AWR) per hour for jobs created in and supported by the EER supply chain can be easily calculated from the model by equating the inputs to outputs. See Figure 5 42 for the investment equation. For this research the primary input wa s a $1 million i nvestment. The primary output wa s the numbers of jobs. Therefore, the AWR for jobs resulting from the EER supply chain can be calculated by dividing the total investment by the product of the number of jobs times the number of compensable hours per year. For this resea rch the default number of compensable hours per year wa s 2,080. The AWR equation is shown in Figure 5 43 Figure 5 44 shows the AWR for the three EER supply chain categories. The results are for self perfor med and subcontracted work.

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88 The AWR and the total number of jobs is inversely correlated. T he highest AWR i s $16.89 for subcontracting HVAC system work, which had the fewest number of jobs at 28.47 The lowest AWR i s $15.36 for subcontracting openings, which had the greatest number of jobs at 31.31. The a v erage of the self perform AWR i s $16.40. The a verage of the subcontract AWR i s $15.96. When interpreting the AWR, remember the amount is the average for all types of workers (e.g. administrative offi cers, managers, secretaries, receptionists, skilled workers, semi skilled workers and unskilled workers) over various types of industries (e.g. construction, retail, wholesale, manufacturing, and mining). Calculating the AWR for the total number of jobs had a weakness worth mentioning. The total number of jobs represent ed all three types of jobs (i.e. direct, indirect and induced); thus, it include d EER jobs and EER supported jobs. Consequently, the AWR calculated from the total number of jobs wa s low d ue to the heavy weighting of induced jobs (i.e. EER supported jobs). Average Hourly Cost In comparison to the AWR, a better measurement for EER jobs, i.e. direct and indirect jobs, would be the average hourly cost (AHC) The AHC is similar in concept to the cost of work in place or cost of goods sold. It demonstrates the cost of work that must be performed on an hourly basis to maintain a job. The AHC for EER jobs can be explained by equating inputs to outputs from the model as sho wn in Figure 5 45 Calculating t he AHC is shown in Figure 5 46 Figure 5 47 shows the A HC for EER jobs for the three EER supply chain categories. The results are for self performed and subcontracted work.

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89 Similar to the AWR, the A HC and the total number of jobs i s inversely correlated. The highest A HC i s $45.06 for self performing insulation work, which had the fewest number of jobs at 10.67. The lowest A HC i s $35.02 for subcontracting insulation, which h ad the greatest number of jobs at 13.73. The a verage of the self perform A HC i s $43.82. The average of the subcontract A HC i s $39.96. When interpretin g the A HC remember it is similar to the average cost of work in place, which can also be described as the average amount of spending, and expresses the hourly equivalent of activity required to create a FTE job. The difference between AWR and AHC is that AHC includes costs other than compensation costs. The other costs in AHC represent the spending that will create the EER supported jobs. Time Job Relationship s The time relationship of jobs to the investment is important. It must be understood before predicting when an economic impact will affect the four main levels of the supply chain or forecasting how long the effect will last Figure 5 48 illustrates the general time job relationship in the supply chain. The time of investment wa s considered time zero (t 0 ) Logically, s ome jobs occur before time zero and others after time zero. The model in this research produce d full time equivalent (FTE) number s of direct, indirect and induced jobs from an investment in EER activities. The EER jobs (i.e. direct and indirect jobs ) can be analyzed on a time scale basis for each type of in vestment and scenario to determine a hypothetical schedule of work. For an example, Figure 5 49 is the monthly schedule of EER jobs for insulation installed by a subcontractor It shows the number of FTE jobs in comparison to the possible number of actual jobs. Similar analyses could be performed for glass doors / windows and HVAC systems.

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90 The analysis indicates that 1 3.73 direct and indirect FTE jobs in the insulation supply chain could make about 1 8.31 actual jobs In the three m ont hs prior to investment (between t 3 and t 0 ), 0.1 6 jobs would be retained in mining and manufacturing ; however, in the nine months after the investment (between t 0 and t +9 ), 1 8.15 jobs would be created, retained or reallocated from activity in all fo ur of the major supply chain levels. Figure 5 50 is the graph of actual insulation jobs over a twelve month period. The negative time jobs represent the small bump on the left hand side of the graph. At t ime zero a larger number of jobs will be immediately created. At the end of the investment period, jobs associated with the investment in the mining and manufacturing levels begin to taper off. These hypothetical schedules facilitate performing calculations to determine the actual number of persons required to perform the direct and indirect work on a monthly basis. Because the FTE is a summation calculation of part time jobs for a twelve month period, the actual number of workers for any level of the supply chain would be greater if the period of employment for a specific level of the supply chai n was less than twelve months. The actual jobs represents a more accurate picture of the number of pe ople employed over the course of a year due to an investment in EER activities; however, the emplo yment for some of those people will be less than one full year. This makes sense because some workers are part time employees. It is also possible that part of the difference between the FTE and actual job numbers will be due to employees who work over time to meet demand. Overtime hours would count towards the number of

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91 hours required to perform the work. The model cannot predict this nuance; therefore, it cannot recognize overtime in its calculations. Economic Impact Analysis Economic impact i s the effect a policy has on local and regional economies. Economic impact analysis can examine the effect by measuring different metrics, including levels of emplo yment and worker income. The result of this research provides the numbers of jobs in the EER supply chain for a given level of investment T he analysis provides the average wage rate per hour of th ese jobs the job factors per level of the supply chain f or various scenarios and explains the time job relationship Considering this newly available information the economic impact of a proposed policy can be better understood before a decision to invest is made. The following example demonstrates how to us e this new information. I f creating local jobs is a priority, then selecting to invest in insulation activities performed by subcontractors produces the greatest number of project level jobs ( 1 4.00 ). The AWR and A HC for this EER supply chain would be $15 .62 and $35.02 respectively The impact on the sales, manufacturing and mining levels of the supply chain c ould be forecast using the job factors 0.82, 0.37 and 0.01, respectively. Understanding the time job relationship, the forecast of actual number s of people employed full or part time would be 18.31. Summary This chapter has analyzed the sample output results of the model. The samp l e output results are forecasts of the numbers of jobs that occur in the supply chain from EER activities. First, the result s for each product category have been analyzed by supply chain level and iteration for the various scenarios. Second, the job factors at the

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92 four major levels of the supply chain have been discussed. Third, the EER employment multipliers have been determined. Fourth, the average wage rates per ho ur for the EER supply chain have been calculated. Fifth, the average h ourly cost for the EER jobs have been calculated. Sixth, the time job relationship to the EER investment has been exp lained. Finally, an example has been provided to demonstrate how this new knowledge can be used to perform an economic impact analysis.

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93 Figure 5 1. Insulation jobs by mone y source, contractor s elf performs all work Figure 5 2 Insulation jobs by sector, contractor s elf performs all work Figure 5 3 Insulation jobs comparison of money source vs. sector, contractor s elf performs all work

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94 Figure 5 4 Insulation jobs by pass thru, contractor s elf performs all work Figure 5 5 Percent of total insulation jobs by pass thru, contractor s elf performs all work

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95 Figure 5 6 Insulation jobs by money source, contractor s ubcontracts all work Figure 5 7 Insulation jobs by sector, contractor subcontract s all work Figure 5 8 Insulation jobs comparison of money source vs. sector, contractor subcontract s all work

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96 Figure 5 9 Insulation j obs by pass thru, contractor subcontracts all work Figure 5 10 Percent of total insulation jobs by pass thru, contractor subcontract s all work

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97 Figure 5 11 Openings jobs by money source, contractor s elf performs all work Figure 5 12 Openings jobs by sector, contractor s elf performs all work Figure 5 13 Openings jobs comparison of money source vs. sector, contractor s elf performs all work

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98 Figure 5 14 Openings jobs by pass thru, contractor s elf performs all work Figure 5 15 Percent o f total openings jobs by pass thru, contractor s elf performs all work

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99 Figure 5 16 Openings jobs by money source, contractor s ubcontracts all work Figure 5 17 Openings jobs by sector, contractor subcontract s all work Figure 5 18 Openings jobs comparison of money source vs. sector, contractor subcontract s all work

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100 Figure 5 19 Openings jobs by pass thru, contractor subcontracts all work Figure 5 20 Percent of total openings jobs by pass thru, contractor subcontract s all work

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101 Figure 5 21 HVAC systems jobs by money source, contractor s elf performs all work Figure 5 22 HVAC systems jobs by sector, contractor s elf performs all work Figure 5 23 HVAC systems jobs comparison of money source vs. sector, contractor s elf performs all work

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102 Figure 5 24 HVAC systems jobs by pass thru, contractor s elf performs all work Figure 5 25 Percent of t otal HVAC systems jobs by pass thru, contractor s elf performs all work

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103 Figure 5 26 HVAC systems jobs by money source, contractor s ubcontracts all work Figure 5 27 HVAC systems jobs by sector, contractor subcontract s all work Figure 5 28 HVAC systems jobs comparison of money source vs. sector, contractor subcontract s all work

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104 Figure 5 29 HVAC systems jobs by pass thru, contractor subcontracts all work Figure 5 30 Percent of t otal HVAC systems jobs by pass thru, contractor subcontract s all work

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105 Figure 5 31. Summary of the numbers of jobs created Figure 5 3 2 Percent of total for the numbers of jobs created Figure 5 33. Percent of total for the hard cost and overhead cost categories Figure 5 34. Summary of the number of jobs created and percent of total for the first

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106 Figure 5 35. Job factors for insulation by money source Figure 5 36. Job factors for openings by money source Figure 5 37. Job factors for HVAC systems by money source

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107 Figure 5 38. Job factors for insulation by sector Figure 5 39. Job factors for openings by sector Figure 5 40. Job f actors for HVAC systems by sector

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108 Figure 5 41. E nergy efficiency retrofit (EER) employment multipliers Figure 5 42 Investment e quation (AWR) Figure 5 43 Average wage rate equation Figure 5 44. Average wage rate comparison for all jobs Figure 5 45 Investment e quation (AHC)

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109 Figure 5 46 Average hourly cost equation Figure 5 47. Average hourly cost comparison for e nergy efficiency r etrofit jobs Figure 5 48 Time job relationship in the supply chain

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110 Figure 5 49 FTE vs. actual jobs, insulation subcontracted Figure 5 50 Graph of time job occurrence

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111 CHAPTER 6 SUMMARY AND CONCLUSIONS This chapter will be a recap of the research and final word about the findings. First, the research effort will be summarized. Then, conclusions based on the research will be made. Research Summary This research has addressed job creation in the EER supply chain for investments in residential structures. A review had been made of existing literature addressing jobs created from investm ents to reduce energy consumption or raise levels of energy efficiency. Noticeable deficiencies were found in the existing literature. Terminology had been undefined and job calculations lacked uniformity. In response, terminology has been defined speci fically for this research and a new methodology has been developed. A working model has been created and tested for a $1 million investment. The results are the numbers of jobs in the EER supply chain. Analyzing the results provides the average wage rat e per hour of these jobs, the job factors per level of the supply chain for various scenarios, and explains the time job relationship. This information can be used as metrics in economi c impact analysis. Conclusions After concluding this research, the fol lowing new information has been discovered about a $1 million dollar investment in EER activities. Self performed insulation produce s 6.52 direct, 4.15 indirect, and 18.94 induced jobs for a total of 29.60. The numbers of hard cost and overhead jobs are 18.14 and 11.46, respectively. These results remained the same regardless of organization; however, the results grouped by project, sales, manufacturing, and mining levels are different. For these levels, money

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112 source results are 13.42, 9.50, 6.48 and 0 .20, respectively, and sector results are 10.71, s 12.65 jobs. Subcontract ing insulation produce s 9.34 direct, 4.39 indirect, and 17.05 induced jobs for a total of 30.78. The numbers of hard cost and overhead jobs are 19.85 and 10.93, respectively. These results remained the same regardless of organization; however, the results grouped by project, s ales, manufacturing, and mining levels are different. For these levels, money source results are 16.82, 8.30, 5.49 and 0.17, respectively, and sector results are 14.00, 11.47, 5.12 and 0.18, respectively. The first s 15.56 jobs. Self pe rform ing glass doors / windows (i.e. openings) produce s 6.52 direct, 4.66 indirect, and 18.08 induced jobs for a total of 29.25. The numbers of hard cost and overhead jobs are 17.94 and 11.31, respectively. These results remained the same regardless of org anization; however, the results grouped by project, sales, manufacturing, and mining levels are different. For these levels, money source results are 13.46, 9.14, 6.36 and 0.30, respectively, and sector results are 10.73, 12.30, 5.96 and 0.26, respectivel s 13.06 jobs. Subcontracted glass doors / windows (i.e. openings) produce 6.52 direct, 4.80 indirect, and 19.99 induced jobs for a total of 31.31. The numbers of hard cost and overhead jobs are 19.06 and 12.25, respectively. These results remained the same regardless of organization; however, the results grouped by project, sales, manufacturing, and mining levels are different. For these levels, money source results are 15.65, 9.31, 6.08 and 0.27, respectively, and sector re sults are 11.88, 13.16, 6.02 s 13.47 jobs.

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113 Self performing HVAC systems produce s 6.52 direct, 4.56 indirect, and 17.98 induced jobs for a total of 29.06. The numbers of hard cost and overhead jobs are 1 7.73 and 11.33, respectively. These results remained the same regardless of organization; however, the results grouped by project, sales, manufacturing, and mining levels are different. For these levels, money source results are 13.41, 9.48, 5.87 and 0.3 0, respectively, and sector results are 10.72, 12.51, 5.53 and 0.29, respectively. The s 12.97 jobs. Subcontracted HVAC systems produce 5.95 direct, 5.39 indirect, and 17.13 induced jobs for a total of 28.47. The numbers of hard c ost and overhead jobs are 16.67 and 11.80, respectively. These results remained the same regardless of organization; however, the results grouped by project, sales, manuf acturing, and mining levels are different. For these levels, money source results ar e 11.87, 9.88, 6.39 and 0.33, respectively, and sector results are 10.12, 12.38, 5.67 and 0.30, respectively. The s 13.05 jobs. For the sample outputs, level one or two had the greatest numbers of jo bs depending on whether work had been self performed or subcontracted. Comparing the jobs organized by money source to those by sector, the economic activity in levels one, two and five support ed the jobs at level three and four. The numbers of direct jobs (6.52) were the same for all categories of products when the contractor was self perform ing the work; however, th e y are different when the work i s subcontracted A different subcontractor perform ed each category of work; therefore, s ubcontracting create d 9.34, 6.52 and 5.95 direct jo bs for insulation, openings, and HVAC systems, respectively. Self performing insulation installations create d the least amount of indirect

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114 jobs (4.15). Subcontracting door / window installations (i.e. openings) create d the greatest number of total jobs (31 .31) and induced jobs (19.99). Subcontracting HVAC systems create d the least number of total jobs (28.47) and direct jobs (5.95), but it create d the greatest number of indirect jobs (5.39). Subcontracting insulation create d the greatest number of direct jobs (9.34) and the least number of induced jobs (17.05). The average total number of jobs for self performing work wa s 29.30. The average percent of direct and indirect jobs for self performing work wa s about 37%. The average total number o f jobs for s ubcontracting work wa s 30.19. The average percent of direct and indirec t jobs for subcontracting work wa s about 40%. Hard costs account ed for 61% of the jobs when work wa s self performed. For subcontracting, the percentage wa s about the same if the aver age wa performing work. For all scenarios, the the fifteenth. Job factors var ied by the method of organization. The average job factors by money source of the three product categories for self performing work were 1.00, 0.70, 0.46 and 0.02, respectively for project, sales, manufacturing, and mining. The average job factors by mon ey source of the three product categories for subcontracting work were 1.00, 0.64, 0.42 and 0.02, respectively for project, sales, manufacturing, and mining. The average job factors by sector of the three product categories for self performing work were 1 .00, 1.17, 0.54 and 0.02, respectively for project, sales, manufacturing, and mining. The average job factors by sector of the three product

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115 categories for subcontracting work were 1.00, 1.05, 0.48 and 0.02, respectively for project, sales, manufacturing, and mining. The highest average wage rate (AWR) per hour for total jobs created in the EER supply chain was $16.89 for subcontracting HVAC system work, which had the fewest number of jobs at 28.47. The lowest AWR was $15.36 for subcontracting openings, w hich had the greatest number of jobs at 31.31. The average of the self perform AWR wa s $16.40. The average of the subcontract AWR wa s $15.96. Using only direct and indirect jobs (i.e. EER jobs) the highest A HC was $45.06 for self performing insulation work, which had the fewest number of jobs at 10.67. The lowest A HC was $35.02 for subcontracting insulation, which had the greatest number of jobs at 13.73. The average of the self perform A HC wa s $43.82. The a verage of the subcontract A HC wa s $39.96. The time jobs relationship of an investment in subcontracted insulation indicated 13.73 direct and indirect FTE jobs in the supply chain could make about 18.31 actual jobs In the three mont hs prior to investment (between t 3 and t 0 ), 0.16 jobs were retained in mining and manufacturing; but, in the nine months after the investment (between t 0 and t +9 ), 18.15 jobs were created, retained or reallocated from activity in all four of the major supply chain levels. T his research effort has lead to new metrics that can be used in economic impact analysis studies. Economic impact analysis examines the effect a policy has on an economy. For example, if creating local jobs is a priority, then the best policy option woul d be to invest $1 million in subcontracted insulation activities that produce 1 4.00 project level jobs. The average wage rate per hour for this EER supply chain would be $15.62. The average hourly cost for EER jobs would be $35.02. The impact on the

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116 sal es, manufacturing and mining levels of the supply chain could be forecast using the job factors 0.82, 0.37 and 0.01, respectively. Understanding the time job relationship, the forecast of actual numbers of people employed full or part time would be about 18.31.

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117 CHAPTER 7 RECOMMENDATIONS FOR FU TURE RESEARCH Introduction This chapter will make recommendations for future research. First, enhancements to the model will be suggested. Second, ways to merge the results with other existing research will be proposed. Finally, new places to take the research will be explored. Enhancements Th e working model could provide several new metrics with minor modifications. First, the profit in the EER supply chain for all thirty five iterations could be calculated. This profit could be compared to jobs, or vice versa, to determine the relationships between profitability and the numbers of jobs created in a specific supply chain. Synergies may be found that maximize profit and the numbers of jobs. New light may be shed on the long running profit maximizing versus profit satisficing debate. Perhaps corporations can promote social good without settling for less. Second the numbers of jobs from reinvested wages could be calculated. Assumptions would be made that t he reinvested wages equal the initial investment and are reinvested into the general economy for all iterations. Mergers The results of several existing studies could be merged with the results of this research to form comparisons and new metrics. First, carbon production in the EER supply chain could be calculated and compared to the jobs in the EER supply chain. The outcome would be carbon production per job for each $1 million investment. Additionally, the carbon production per job for non EER supply chains of similar products could be calculated and compared to the EER supply chain results. Second, a

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118 more complete forecast of induced jobs can be explored. There are three sources of induced jobs. T he model in this research forecasts induced jobs fro m business to business spending. A recommendation was made to calculate induced jobs from reinvested wages. The final source is induced jobs from energy dollars. Energy dollars are the dollars saved by avoiding higher utility payments (because lower uti lity payments result from the installation of energy efficient products ) Fobair and Kibert (2011) proposed a method to calculate the induced jobs from energy dollars. Their results could be combined with the results of this rese arch to provide a more co mplete understanding of the induced jobs created from investments in EER activities O nce the induced jobs are fully known, results from the studies could be combined to provide a complete number of di re ct, indirect and induced jobs. New Places This model could have many applications. First, i t can be expanded to other products, such as lighting and thermal shading. The progression would initially be to round out the examination of commonly implemented retrofit options; however, other products of a non r etrofit nature could be examined. Second, t he concept of the research could change to examine the job creation in supply chains for other forms of construction sustainability. For example, the model could be adapted to forecast the jobs resulting from deconstruction. The goal is to compare the jobs created from a building deconstruction to a building demolition. The comparison to be made is the number of jobs created versus the cost of the work. The assumpt ion is when the cost of work is the same, deconstruction is more sustainable than demolition because more jobs are created and less waste is hauled to a landfill. Third, this research can be adapted for new sustainable buildings. Specifically, the resear ch question would be:

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119 How much do sustainable buildings contribute to job creation when viewed in terms of credits from a rating system? D oes achieving certain LEED credits, or a combination of credits, result in a greater number of local jobs? If in fac t buildings having a higher rating (by achieving more credits) or better performance in a design criteria (e.g. energy efficiency) produce more local jobs, then local governments and municipalities may choose to offer economic development incentives that p romote certain credits for buildings pursuing higher performance ratings. The practical benefit would be more for employment. Summary This research has focused on calculating jobs for investments in three specific construction activities in Florida residences Future research will make enhancements to the model, merge results with other studies, and take the concept into new places Enhancements could have the mod el calculate profit and reinvested wages. Mergers could be with carbon production or induced jobs from energy dollars. New places could expand into new construction, deconstruction and waste management. F or new construction, LEED credits could be examin ed for their job creation impact.

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120 APPENDIX A PROCEDURES FOR CREATING AND USING THE MODEL T he procedure for using the model in this research will be described in the following steps. The primary function of the model is to forecast the number of jobs tha t result from an investment in energy efficiency retrofit work on residential use buildings. The inputs and outputs shown in this Appendix are based on default settings. M odel Setup 1) The model is data intensive and requires the use of macros, data connections and links. Therefore, the file must be saved in a macro enabled format and data connections and links should be checked and/or refreshed prior to use. 2) Data sets can be downloaded from the relevant government websites. See the sources for the data sets utilized. 3) Dollar templates. See Appendix B for an example of the template. 4) Dat a sets should be organized by supply chain and saved in a logical file order. File names should be unique for each data set and template. 5) The data sets for the model in this research are for mineral wool insulation, openings (wood, vinyl and metal doors o r windows), and HVAC systems. STEP 1 U ser Inputs 1) a. The model calculates jobs either for the material supply chain (direct, indirect and induced jobs) or for reinvested wages (induced jobs). Selec t or reinvested wages. The default setting is b. c. d. openings (windows and/or doors), or HVAC systems. The sum of percentages for all three materials should equal 100 percent. If the number of jobs for only one material is the desired answer, then 100 pe for one material. e. must be entered for each material. The percentage range is from zero percent to 100 percent. Based on the percentage entered, the calculator divides the amount between work that is self performed by the contractor and work that is subcontracted to others. Enter 100 percent to calculate the jobs created when the contractor self performs all of t he installation work. Enter zero percent to calculate the jobs created when the contractor

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121 hires a subcontractor to perform the installation. The default setting is either zero percent or 100 percent depending on the desired answer. f. percentage must be entered for each material. The percentage range is from zero percent to 100 percent. Based on the percentage entered, the calculator allocates the amount to the contractor as compensat ion for the labor to oversee the work performed by a subcontractor. The default setting is 5 percent. g. Project Management Mix % The mix is assumed based on the following question: Of the payroll for administration and project management, how much is allocated to each category of worker? The worker options are officer, secretary, and manager. The sum of percentages for all three options should equal 100 percent. The default settings for officer, secretary, and manager are 10 percent, 30 percent, and 60 percent, respectively. h. and assumed based on the following question: Of the payroll for temporary and leased employees, how much is allocated to each category of worker? The worker option is receptionist. The percentage must be 100 percent if temporary or leased employees are hired. The d efault setting is 100 percent. i. Performed and/or Sub assumed based on the fo llowing question: Of the payroll for the each category of worker? The worker options are skilled, semi skilled, and unskilled. The sum of percentages for all three options should equal 100 percent. The default settings for skilled, semi skilled and unskilled are 10 percent, 60 percent, and 30 percent, respectively. 2) a. worker category in a material supply chain for any level of the supply chain. The table wage rate is always used unless a user defined wage rate is entered to override the default. b. work er category in a material supply chain for any level of the supply chain. The table multiplier rate is always used unless a user defined multiplier rate is entered to override the default. STEP 2 M odel O utputs 1) v Output Results ides the number of jobs calculated by where the money originates. Jobs are provided for each of the seven worker categories: officer, secretary, manager, receptionist, skilled, semi skilled and unskilled. These jobs are divided into six categories: Mater ials (HC), Profit, Materials (OH), Equipment (OH), Other (OH), and Equipment (HC). Each

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122 category is divided into three subcategories: Direct Jobs, Indirect Jobs, and Induced Jobs. Each subcategory is divided into three additional sub subcategories: Profi t, Overhead and Hard Cost. Jobs are reflected in the table at the sub subcategory level. The table provides results for thirty five iterations of money turn over. In other words, the flow of money passing through the supply chain was calculated thirty f 2) vi Output Results By Industrial Sector by where the job will occur in the ten levels of the supply chain See the chapter for a description of the ten levels of the supply chain. Jobs are provided for each of the seven worker categories: officer, secretary, manager, receptionist, skilled, semi skilled and unskilled. These jobs are divid ed into six categories: Materials (HC), Profit, Materials (OH), Equipment (OH), Other (OH), and Equipment (HC). Each category is divided into three subcategories: Direct Jobs, Indirect Jobs, and Induced Jobs. Each subcategory is divided into three additi onal sub subcategories: Profit, Overhead and Hard Cost. Jobs are reflected in the table at the sub subcategory level. The table provides results for thirty five iterations of money turn over. In other words, the flow of money passing through the supply chain was calculated thirty five times, where each from the previous 3) summarizes the results into an easy to read table for the ten levels of the supply chain. In addition, the results are summarized in a format that displays the jobs grouped by Project, Sales and Manufacturing and Mining l evels. This summary format can be described as the job factors between the three maj or lev els of the supply chain. 4) to read table for the ten levels of the supply chain. In addition, the results are summarized in a format that displays the jobs grouped by Project, Sales and Manufacturing, and Mining levels. This summary format can be described as the job factors between the three maj or levels of the supply chain. 5) summarize the results into an eas y to read table for the thirty iterations In addition, the cumulative totals and the cumulative percent of totals are provided Th e number of iterations necessary to achieve a certain percentage of the total number of jobs is found usin g th ese table s 6) profit earned by all levels of the supply chain over all thirty iterations. This sheet summarizes the results into an easy to read table for th e ten levels of the supply chain. In addition, the results are summarized in a format that displays the pr ofit grouped by Project, Sales and Manufacturing, and Mining levels. This summary format can be described as the profit factors between the three ma j or levels of the supply chain.

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123 APPENDIX B DOLLAR BREAKDOWN TEMPLATE The dollar breakdown template demonstrates how dollars from the survey data have been categorized. Dollars could be placed in one of the following eight accounts: profit, overhead labo r, overhead material, overhead equipment, overhead other, hard cost labor, hard cost material, and hard cost equipment. An example of the template has been provided in Figure B 1

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124 Figure B 1. Dollar breakdown template

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125 APPENDIX C NAICS CODES FOR SUPP LY CHAINS The following f igures will show tables that provide the NAICS codes used in each supply chain. Figures C 1 C 2 and C 3 are for the hard cost mater ials used in insulation, doors / windows, and HVAC systems respectively. Figures C 4 C 5 C 6 C 7 and C 8 are for Hard Cost Equipment, Overhead Equipment, Overhead Material, Overhead Other, and Profit. Supply Chain Level 2007 NAICS Code Meaning of 2007 NAICS C ode 1 236118 Residential Remodelers 2 238310 Drywall and Insulation Contractors 3 444100 Building Materials and Supplies Dealers 4 423330 Roofing, Siding and Insulation Material Merchant Wholesalers 5 327993 Mineral Wool Manufacturing 6 212311 Dimension Stone Mining and Quarrying 6 212312 Crushed and Broken Limestone Mining and Quarrying 6 212319 Other Crushed and Broken Stone Mining and Quarrying 6 212391 Potash, Soda and Borate Mineral Mining 6 212322 Industrial Sand Mining 6 212393 Other Chemical and Fertilizer Mineral Mining 6 322121 Paper (except newsprint) Mills 6 322211 Corrugated and Solid Fiber Box Manufacturing 6 322222 Coated and Laminated Paper Manufacturing 6 322224 Uncoated Paper and Multiwall Bag Manufacturing 6 322226 Surface coated Paperboard Manufacturing 6 325131 Inorganic Dye and Pigment Manufacturing 6 325211 Plastics Material and Resin Manufacturing 6 325520 Adhesive Manufacturing 6 326111 Plastics Bag and Pouch Manufacturing 6 326113 Non packaging Plastics Film and Sheet Manufacturing 6 327212 Other Pressed and Blown Glass and Glassware Manufacturing 6 327310 Cement Manufacturing 6 331111 Iron and Steel Mills 7 100 Agriculture (except livestock) 7 211 Oil and Gas Extraction

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126 7 212 Mining (except oil and gas) 7 311 Food Manufacturing 7 313 Textile Mills 7 321 Wood Product Manufacturing 7 322 Paper Manufacturing 7 324 Petroleum and Coal Products Manufacturing 7 325 Chemical Manufacturing 7 326 Plastics and Rubber Products Manufacturing 7 327 Nonmetallic Mineral Product Manufacturing 7 331 Primary Metal Manufacturing 7 332 Fabricated Metal Product Manufacturing 7 333 Machinery Manufacturing 7 335 Electrical Equipment, Appliance and Component Manufacturing 8 10 11 Agriculture 8 21 Mining, Quarrying, and Oil and Gas Extraction (Including Support Activities of Exploration and Development) 8 31 33 Manufacturing 9 100 Agriculture (except livestock) 9 211 Oil and Gas Extraction 9 212 Mining (except oil and gas) 10 213 Support Activities for Mining Figure C 1. Insulation Supply Chain Level 2007 NAICS Code Meaning of 2007 NAICS C ode 1 236118 Residential Remodelers 2 238350 Finish Carpentry Contractors 3 444100 Building Materials and Supplies Dealers 4 423310 Lumber, Plywood, Millwork and Wood Panel Merchant Wholesalers 5 332321 Metal Window and Door Manufacturing 5 326199 All Other Plastics Product Manufacturing 5 321911 Wood Window and Door Manufacturing 6 313210 Broad woven Fabric Mills 6 321113 Sawmills 6 321211 Hardwood Veneer and Plywood Manufacturing 6 321212 Softwood Veneer and Plywood Manufacturing 6 321219 Reconstituted Wood Product Manufacturing 6 321911 Wood Window and Door Manufacturing 6 321912 Cut Stock, Re sawing Lumber and Planing

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127 6 322110 Pulp Mills 6 322121 Paper (except newsprint) Mills 6 322130 Paperboard Mills 6 322211 Corrugated and Solid Fiber Box Manufacturing 6 322214 Fiber Can, Tube, Drum and Similar Products Manufacturing 6 325110 Petrochemical Manufacturing 6 325120 Industrial Gas Manufacturing 6 325131 Inorganic Dye and Pigment Manufacturing 6 325132 Synthetic Organic Dye and Pigment Manufacturing 6 325181 Alkalies and Chlorine Manufacturing 6 325188 All Other Basic Inorganic Chemical Manufacturing 6 325211 Plastics material and resin manufacturing 6 325212 Synthetic Rubber Manufacturing 6 325520 Adhesive Manufacturing 6 325991 Custom Compounding of Purchased Resins 6 326112 Plastics Packaging Film and Sheet Manufacturing 6 326121 Un laminated Plastics Profile Shape Manufacturing 6 326199 All Other Plastics Product Manufacturing 6 327211 Flat Glass Manufacturing 6 327212 Other Pressed and Blown Glass and Glassware Manufacturing 6 331221 Rolled Steel Shape Manufacturing 6 331315 Aluminum Sheet, Plate and Foil Manufacturing 6 331316 Aluminum Extruded Product Manufacturing 6 331421 Copper Rolling, Drawing and Extruding 6 331511 Iron Foundries 6 331512 Steel Investment Foundries 6 331513 Steel Foundries (except investment) 6 331521 Aluminum Die casting Foundries 6 331522 Nonferrous (except aluminum) Die casting Foundries 6 331524 Aluminum Foundries (except die casting) 6 331525 Copper Foundries (except die casting) 6 331528 Other Nonferrous Foundries (except die casting) 6 332111 Iron and Steel Forging 6 332112 Nonferrous Forging 6 332116 Metal Stamping 6 332510 Hardware Manufacturing 6 332722 Bolt, Nut, Screw, Rivet and Washer Manufacturing 6 332997 Industrial Pattern Manufacturing 6 332999 All Other Miscellaneous Fabricated Metal Product Manufacturing 6 333220 Plastics and Rubber Industry Machinery Manufacturing 6 333515 Cutting Tool and Machine Tool Accessory Manufacturing

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128 6 334413 Semiconductor and Related Device Manufacturing 6 334417 Electronic Connector Manufacturing 6 334513 Industrial Process Variable Instruments 6 335314 Relay and Industrial Control Manufacturing 7 100 Agriculture (except livestock) 7 211 Oil and Gas Extraction 7 212 Mining (except oil and gas) 7 221 Utilities 7 311 Food Manufacturing 7 313 Textile Mills 7 321 Wood Product Manufacturing 7 322 Paper Manufacturing 7 324 Petroleum and Coal Products Manufacturing 7 325 Chemical Manufacturing 7 326 Plastics and Rubber Products Manufacturing 7 327 Nonmetallic Mineral Product Manufacturing 7 331 Primary Metal Manufacturing 7 332 Fabricated Metal Product Manufacturing 7 333 Machinery Manufacturing 7 334 Computer and Electronic Product Manufacturing 7 335 Electrical Equipment, Appliance and Component Manufacturing 8 10 11 Agriculture 8 21 Mining, Quarrying, and Oil and Gas Extraction (Including Support Activities of Exploration and Development) 8 22 Utilities 8 31 33 Manufacturing 9 100 Agriculture (except livestock) 9 211 Oil and Gas Extraction 9 212 Mining (except oil and gas) 10 213 Support Activities for Mining Figure C 2. D oors / w indows Supply Chain Level 2007 NAICS Code Meaning of 2007 NAICS C ode 1 236118 Residential Remodelers 2 238220 Plumbing, Heating, and Air conditioning Contractors 3 444100 Building Materials and Supplies Dealers 4 423730 HVAC Equipment Merchant Wholesalers 5 333415 AC, Refrigeration, and Forced Air Heating

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129 6 322211 Corrugated and Solid Fiber Box Manufacturing 6 326100 Plastics Packaging Film/Sheet and Un laminated Plastics Profile Shape Manufacturing 6 326199 All Other Plastics Product Manufacturing 6 326220 Rubber and Plastics Hoses and Belting Manufacturing 6 331221 Rolled Steel Shape Manufacturing 6 331315 Aluminum Sheet, Plate and Foil Manufacturing 6 331421 Copper Rolling, Drawing and Extruding 6 331510 Iron and Steel Foundries 6 331520 Aluminum, Copper and Non ferrous Foundries Including Aluminum and Non ferrous Die Casting 6 332000 Metal Stamping, Industrial Pattern, and Other Miscellaneous Fabricated Metal Product Manufacturing 6 332110 Iron, Steel, and Nonferrous Forging 6 332510 Hardware manufacturing 6 332722 Bolt, Nut, Screw, Rivet and Washer Manufacturing 6 332919 Other Metal Valve and Pipe Fitting Manufacturing 6 332991 Ball and Roller Bearing Manufacturing 6 334512 Automatic Environmental Control Manufacturing 6 335311 Power, Distribution and Specialty Transformer Manufacturing 6 335312 Motor and Generator Manufacturing 6 335931 Current carrying Wiring Device Manufacturing 6 339991 Gasket, Packing and Sealing Device Manufacturing 7 100 Agriculture (except livestock) 7 212 Mining (except oil and gas) 7 313 Textile Mills 7 321 Wood Product Manufacturing 7 322 Paper Manufacturing 7 324 Petroleum and Coal Products Manufacturing 7 325 Chemical Manufacturing 7 326 Plastics and Rubber Products Manufacturing 7 327 Nonmetallic Mineral Product Manufacturing 7 331 Primary Metal Manufacturing 7 332 Fabricated Metal Product Manufacturing 7 333 Machinery Manufacturing 7 334 Computer and Electronic Product Manufacturing 7 335 Electrical Equipment, Appliance and Component Manufacturing 7 339 Miscellaneous Manufacturing 8 10 11 Agriculture 8 21 Mining, Quarrying, and Oil and Gas Extraction (Including Support Activities of Exploration and Development)

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130 8 31 33 Manufacturing 9 100 Agriculture (except livestock) 9 212 Mining (except oil and gas) 10 213 Support Activities for Mining Figure C 3. HVAC s ystems Supply Chain Level 2007 NAICS Code Meaning of 2007 NAICS C ode 1 NA NA 2 NA NA 3 447000 Gasoline Stations 3 532000 Rental and Leasing Services 4 423800 Machinery, Equipment and Supplies Merchant Wholesalers 5 324110 Petroleum Refineries 5 324191 Petroleum Lubricating Oil and Grease Manufacturing 5 333120 Construction Machinery Manufacturing 5 333131 Mining Machinery and Equipment Manufacturing 5 333132 Oil and Gas Field Machinery and Equipment Manufacturing 5 333210 Sawmill and Woodworking Machinery Manufacturing 5 333220 Plastics and Rubber Industry Machinery Manufacturing 5 333295 Semiconductor Machinery Manufacturing 5 333511 Industrial Mold Manufacturing 5 333512 Machine Tool (metal cutting types) Manufacturing 5 333513 Machine Tool (metal forming types) Manufacturing 5 333514 Special Die and Tool, Die Set, Jig and Fixture Manufacturing 5 333515 Cutting Tool and Machine Tool Accessory Manufacturing 5 333516 Rolling Mill Machinery and Equipment Manufacturing 5 333518 Other Metalworking Machinery Manufacturing 5 333912 Air and Gas Compressor Manufacturing 5 333922 Conveyor and Conveying Equipment Manufacturing 5 333923 Overhead Cranes, Hoists and Monorail Systems 5 333924 Industrial Truck, Trailer and Stacker Manufacturing 5 333992 Welding and Soldering Equipment Manufacturing 5 333993 Packaging Machinery Manufacturing 5 333994 Industrial Process Furnace and Oven Manufacturing 6 211111 Crude Petroleum and Natural Gas Extraction 6 211112 Natural Gas Liquid Extraction 6 311222 Soybean Processing 6 311223 Other Oilseed Processing

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131 6 311225 Fats and Oils Refining and Blending 6 322211 Corrugated and Solid Fiber Box Manufacturing 6 322212 Folding Paperboard Box Manufacturing 6 322213 Setup Paperboard Box Manufacturing 6 322214 Fiber Can, Tube, Drum and Similar Products Manufacturing 6 324110 Petroleum Refineries 6 324191 Petroleum Lubricating Oil and Grease Manufacturing 6 325110 Petrochemical Manufacturing 6 325120 Industrial Gas Manufacturing 6 325131 Inorganic Dye and Pigment Manufacturing 6 325132 Synthetic Organic Dye and Pigment Manufacturing 6 325181 Alkalies and Chlorine Manufacturing 6 325188 All Other Basic Inorganic Chemical Manufacturing 6 325211 Plastics Material and Resin Manufacturing 6 325212 Synthetic Rubber Manufacturing 6 325520 Adhesive Manufacturing 6 325991 Custom Compounding of Purchased Resins 6 325510 Paint and Coating Manufacturing 6 325998 Other Miscellaneous Chemical Product Manufacturing 6 326199 All Other Plastics Product Manufacturing 6 326211 Tire Manufacturing (except retreading) 6 326220 Rubber and Plastics Hoses and Belting Manufacturing 6 327999 Miscellaneous Nonmetallic Mineral Products 6 331221 Rolled Steel Shape Manufacturing 6 331311 Alumina Refining 6 331312 Primary Aluminum Production 6 331314 Secondary Smelting and Alloying of Aluminum 6 331315 Aluminum Sheet, Plate and Foil Manufacturing 6 331316 Aluminum Extruded Product Manufacturing 6 331319 Other Aluminum Rolling and Drawing 6 331421 Copper Rolling, Drawing and Extruding 6 331492 Secondary Processing of Other Nonferrous 6 331511 Iron Foundries 6 331512 Steel Investment Foundries 6 331513 Steel Foundries (except investment) 6 331521 Aluminum Die casting Foundries 6 331522 Nonferrous (except aluminum) Die casting Foundries 6 331524 Aluminum Foundries (except die casting) 6 331525 Copper Foundries (except die casting) 6 331528 Other Nonferrous Foundries (except die casting) 6 332111 Iron and Steel Forging

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132 6 332112 Nonferrous Forging 6 332116 Metal Stamping 6 332420 Metal Tank (heavy gauge) Manufacturing 6 332431 Metal Can Manufacturing 6 332439 Other Metal Container Manufacturing 6 332510 Hardware Manufacturing 6 332722 Bolt, Nut, Screw, Rivet and Washer Manufacturing 6 332911 Industrial Valve Manufacturing 6 332912 Fluid Power Valve and Hose Fitting Manufacturing 6 332919 Other Metal Valve and Pipe Fitting Manufacturing 6 332991 Ball and Roller Bearing Manufacturing 6 332997 Industrial Pattern Manufacturing 6 332999 All Other Miscellaneous Fabricated Metal Product Manufacturing 6 333515 Cutting Tool and Machine Tool Accessory Manufacturing 6 333612 Speed Changer, Drive, and Gear Manufacturing 6 333613 Mechanical Power Transmission Equipment Manufacturing 6 333618 Other Engine Equipment Manufacturing 6 333911 Pump and Pumping Equipment Manufacturing 6 333993 Packaging Machinery Manufacturing 6 333994 Industrial Process Furnace and Oven Manufacturing 6 333995 Fluid Power Cylinder and Actuator Manufacturing 6 333996 Fluid Power Pump and Motor Manufacturing 6 333999 All Other Miscellaneous General Purpose Machinery Manufacturing 6 334413 Semiconductor and Related Device Manufacturing 6 334418 Printed Circuit Assembly (electronic assembly) Manufacturing 6 335110 Electric Lamp Bulb and Part Manufacturing 6 335121 Residential Electric Lighting Fixture Manufacturing 6 335122 Nonresidential Electric Lighting Fixture Manufacturing 6 335129 Other Lighting Equipment Manufacturing 6 335222 Household Refrigerator and Home Freezer Manufacturing 6 335311 Power, Distribution and Specialty Transformer Manufacturing 6 335312 Motor and Generator Manufacturing 6 335313 Switchgear and Switchboard Apparatus Manufacturing 6 335314 Relay and Industrial Control Manufacturing 6 335911 Storage Battery Manufacturing 6 335912 Primary Battery Manufacturing 6 335921 Fiber Optic Cable Manufacturing 6 335929 Other Communication and Energy Wire Manufacturing 6 335931 Current carrying Wiring Device Manufacturing 6 335932 Noncurrent carrying Wiring Device Manufacturing 6 335991 Carbon and Graphite Product Manufacturing

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133 6 335999 Miscellaneous Electrical Equipment Manufacturing 6 336111 Automobile Manufacturing 6 336322 Other Motor Vehicle Electric Equipment Manufacturing 6 336350 Motor Vehicle Transmission and Power Train Parts Manufacturing 6 339991 Gasket, Packing, and Sealing Device Manufacturing 7 100 Agriculture (except livestock) 7 211 Oil and Gas Extraction 7 212 Mining (except oil and gas) 7 221 Utilities 7 311 Food Manufacturing 7 313 Textile Mills 7 314 Textile Product Mills 7 321 Wood Product Manufacturing 7 322 Paper Manufacturing 7 324 Petroleum and Coal Products Manufacturing 7 325 Chemical Manufacturing 7 326 Plastics and Rubber Products Manufacturing 7 327 Nonmetallic Mineral Product Manufacturing 7 331 Primary Metal Manufacturing 7 332 Fabricated Metal Product Manufacturing 7 333 Machinery Manufacturing 7 334 Computer and Electronic Product Manufacturing 7 335 Electrical Equipment, Appliance and Component Manufacturing 7 336 Transportation Equipment Manufacturing 7 339 Miscellaneous Manufacturing 8 10 11 Agriculture 8 21 Mining, Quarrying, and Oil and Gas Extraction (Including Support Activities of Exploration and Development) 8 22 Utilities 8 31 33 Manufacturing 9 100 Agriculture (except livestock) 9 211 Oil and Gas Extraction 9 212 Mining (except oil and gas) 10 213 Support Activities for Mining Figure C 4. Hard cost e quipment Supply Chain Level 2007 NAICS Code Meaning of 2007 NAICS C ode 1 NA NA

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134 2 NA NA 3 447000 Gasoline Stations 3 453000 Miscellaneous Store Retailers 3 532000 Rental and Leasing Services 4 423200 Furniture and Home Furnishing Merchant Wholesalers 4 423400 Commercial Equipment Merchant Wholesalers 4 423800 Machinery, Equipment and Supplies Merchant Wholesalers 5 324110 Petroleum Refineries 5 324191 Petroleum Lubricating Oil and Grease Manufacturing 5 333120 Construction Machinery Manufacturing 5 333131 Mining Machinery and Equipment Manufacturing 5 333132 Oil and Gas Field Machinery and Equipment Manufacturing 5 333210 Sawmill and Woodworking Machinery Manufacturing 5 333220 Plastics and Rubber Industry Machinery Manufacturing 5 333295 Semiconductor Machinery Manufacturing 5 333511 Industrial Mold Manufacturing 5 333512 Machine Tool (metal cutting types) Manufacturing 5 333513 Machine Tool (metal forming types) Manufacturing 5 333514 Special Die and Tool, Die Set, Jig and Fixture Manufacturing 5 333515 Cutting Tool and Machine Tool Accessory Manufacturing 5 333516 Rolling Mill Machinery and Equipment Manufacturing 5 333518 Other Metalworking Machinery Manufacturing 5 333912 Air and Gas Compressor Manufacturing 5 333922 Conveyor and Conveying Equipment Manufacturing 5 333923 Overhead Cranes, Hoists and Monorail Systems 5 333924 Industrial Truck, Trailer and Stacker Manufacturing 5 333992 Welding and Soldering Equipment Manufacturing 5 333993 Packaging Machinery Manufacturing 5 333994 Industrial Process Furnace and Oven Manufacturing 5 334111 Electronic Computer Manufacturing 5 334112 Computer Storage Device Manufacturing 5 334113 Computer Terminal Manufacturing 5 334119 Other Computer Peripheral Equipment Manufacturing 5 334210 Telephone Apparatus Manufacturing 5 334220 Broadcast and Wireless Communications Equipment 5 334310 Audio and Video Equipment Manufacturing 5 337211 Wood Office Furniture Manufacturing 5 337214 Office Furniture (except wood) Manufacturing 5 337215 Showcase, Partition, Shelving and Locker Manufacturing 6 211111 Crude Petroleum and Natural Gas Extraction 6 211112 Natural Gas Liquid Extraction

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135 6 311222 Soybean Processing 6 311223 Other Oilseed Processing 6 311225 Fats and Oils Refining and Blending 6 313210 Broad woven Fabric Mills 6 313320 Fabric Coating Mills 6 314999 All Other Miscellaneous Textile Product Mills 6 321000 Aggregate of Sawmills, Hard/Soft Wood Veneer/Plywood, Reconstituted Wood Product, Wood Window/Door, Cut Stock, Re sawing Lumber, and Planing Manufacturing 6 321211 Hardwood Veneer and Plywood Manufacturing 6 321219 Reconstituted Wood Product Manufacturing 6 321912 Cut Stock, Re sawing Lumber, and Planing 6 321920 Wood Container and Pallet Manufacturing 6 322211 Corrugated and Solid Fiber Box Manufacturing 6 322212 Folding Paperboard Box Manufacturing 6 322213 Setup Paperboard Box Manufacturing 6 322214 Fiber Can, Tube, Drum and Similar Products Manufacturing 6 324110 Petroleum Refineries 6 324191 Petroleum Lubricating Oil and Grease Manufacturing 6 325110 Petrochemical Manufacturing 6 325120 Industrial Gas Manufacturing 6 325131 Inorganic Dye and Pigment Manufacturing 6 325132 Synthetic Organic Dye and Pigment Manufacturing 6 325181 Alkalies and Chlorine Manufacturing 6 325188 All Other Basic Inorganic Chemical Manufacturing 6 325211 Plastics Material and Resin Manufacturing 6 325212 Synthetic Rubber Manufacturing 6 325520 Adhesive Manufacturing 6 325991 Custom Compounding of Purchased Resins 6 325510 Paint and Coating Manufacturing 6 325520 Adhesive Manufacturing 6 325991 Custom Compounding of Purchased Resins 6 325998 Other Miscellaneous Chemical Product Manufacturing 6 326111 Plastics Bag and Pouch Manufacturing 6 326112 Plastics Packaging Film and Sheet Manufacturing 6 326113 Non packaging Plastics Film and Sheet Manufacturing 6 326130 Laminated Plastics Plate, Sheet and Shapes 6 326150 Urethane and Other Foam Product Manufacturing 6 326199 All Other Plastics Product Manufacturing 6 326211 Tire Manufacturing (except retreading) 6 326220 Rubber and Plastics Hoses and Belting Manufacturing

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136 6 327211 Flat Glass Manufacturing 6 327215 Glass Product Manufacturing Made of Purchased Glass 6 327999 Miscellaneous Nonmetallic Mineral Products 6 331221 Rolled Steel Shape Manufacturing 6 331311 Alumina Refining 6 331312 Primary Aluminum Production 6 331314 Secondary Smelting and Alloying of Aluminum 6 331315 Aluminum Sheet, Plate and Foil Manufacturing 6 331316 Aluminum Extruded Product Manufacturing 6 331319 Other Aluminum Rolling and Drawing 6 331421 Copper Rolling, Drawing and Extruding 6 331422 Copper Wire (except mechanical) Drawing 6 331492 Secondary Processing of Other Nonferrous 6 331511 Iron Foundries 6 331512 Steel Investment Foundries 6 331513 Steel Foundries (except investment) 6 331521 Aluminum Die casting Foundries 6 331522 Nonferrous (except aluminum) Die casting Foundries 6 331524 Aluminum Foundries (except die casting) 6 331525 Copper Foundries (except die casting) 6 331528 Other Nonferrous Foundries (except die casting) 6 332111 Iron and Steel Forging 6 332112 Nonferrous Forging 6 332116 Metal Stamping 6 332117 Powder Metallurgy Part Manufacturing 6 332322 Sheet Metal Work Manufacturing 6 332420 Metal Tank (heavy gauge) Manufacturing 6 332431 Metal Can Manufacturing 6 332439 Other Metal Container Manufacturing 6 332510 Hardware Manufacturing 6 332722 Bolt, Nut, Screw, Rivet and Washer Manufacturing 6 332911 Industrial Valve Manufacturing 6 332912 Fluid Power Valve and Hose Fitting Manufacturing 6 332919 Other Metal Valve and Pipe Fitting Manufacturing 6 332991 Ball and Roller Bearing Manufacturing 6 332997 Industrial Pattern Manufacturing 6 332999 All Other Miscellaneous Fabricated Metal Product Manufacturing 6 333515 Cutting Tool and Machine Tool Accessory Manufacturing 6 333612 Speed Changer, Drive, and Gear Manufacturing 6 333613 Mechanical Power Transmission Equipment Manufacturing 6 333618 Other Engine Equipment Manufacturing

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137 6 333911 Pump and Pumping Equipment Manufacturing 6 333993 Packaging Machinery Manufacturing 6 333994 Industrial Process Furnace and Oven Manufacturing 6 333995 Fluid Power Cylinder and Actuator Manufacturing 6 333996 Fluid Power Pump and Motor Manufacturing 6 333999 All Other Miscellaneous General Purpose Machinery Manufacturing 6 334111 Electronic Computer Manufacturing 6 334112 Computer Storage Device Manufacturing 6 334119 Other Computer Peripheral Equipment Manufacturing 6 334210 Telephone Apparatus Manufacturing 6 334220 Broadcast and Wireless Communications Equipment 6 334310 Audio and Video Equipment Manufacturing 6 334411 Electron Tube Manufacturing 6 334412 Bare Printed Circuit Board Manufacturing 6 334413 Semiconductor and Related Device Manufacturing 6 334414 Electronic Capacitor Manufacturing 6 334415 Electronic Resistor Manufacturing 6 334417 Electronic Connector Manufacturing 6 334418 Printed Circuit Assembly (electronic assembly) Manufacturing 6 334419 Other Electronic Component Manufacturing 6 334515 Electricity and Signal Testing Instruments 6 334611 Software Reproducing 6 335110 Electric Lamp Bulb and Part Manufacturing 6 335121 Residential Electric Lighting Fixture Manufacturing 6 335122 Nonresidential Electric Lighting Fixture Manufacturing 6 335129 Other Lighting Equipment Manufacturing 6 335222 Household Refrigerator and Home Freezer Manufacturing 6 335311 Power, Distribution and Specialty Transformer Manufacturing 6 335312 Motor and Generator Manufacturing 6 335313 Switchgear and Switchboard Apparatus Manufacturing 6 335314 Relay and Industrial Control Manufacturing 6 335911 Storage Battery Manufacturing 6 335912 Primary Battery Manufacturing 6 335921 Fiber Optic Cable Manufacturing 6 335929 Other Communication and Energy Wire Manufacturing 6 335931 Current carrying Wiring Device Manufacturing 6 335932 Noncurrent carrying Wiring Device Manufacturing 6 335991 Carbon and Graphite Product Manufacturing 6 335999 Miscellaneous Electrical Equipment Manufacturing 6 336111 Automobile Manufacturing 6 336322 Other Motor Vehicle Electric Equipment Manufacturing

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138 6 336350 Motor Vehicle Transmission and Power Train Parts Manufacturing 6 337129 Wood Television, Radio, and Sewing Machine Cabinet Manufacturing 6 337215 Showcase, Partition, Shelving, and Locker Manufacturing 6 339991 Gasket, Packing, and Sealing Device Manufacturing 7 100 Agriculture (except livestock) 7 211 Oil and Gas Extraction 7 212 Mining (except oil and gas) 7 221 Utilities 7 311 Food Manufacturing 7 313 Textile Mills 7 314 Textile Product Mills 7 315 Apparel Manufacturing 7 321 Wood Product Manufacturing 7 322 Paper Manufacturing 7 324 Petroleum and Coal Products Manufacturing 7 325 Chemical Manufacturing 7 326 Plastics and Rubber Products Manufacturing 7 327 Nonmetallic Mineral Product Manufacturing 7 331 Primary Metal Manufacturing 7 332 Fabricated Metal Product Manufacturing 7 333 Machinery Manufacturing 7 334 Computer and Electronic Product Manufacturing 7 335 Electrical Equipment, Appliance and Component Manufacturing 7 336 Transportation Equipment Manufacturing 7 337 Furniture and Related Product Manufacturing 7 339 Miscellaneous Manufacturing 8 10 11 Agriculture 8 21 Mining, Quarrying, and Oil and Gas Extraction (Including Support Activities of Exploration and Development) 8 22 Utilities 8 31 33 Manufacturing 9 100 Agriculture (except livestock) 9 211 Oil and Gas Extraction 9 212 Mining (except oil and gas) 10 213 Support Activities for Mining Figure C 5. Overhead e quipment

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139 Supply Chain Level 2007 NAICS Code Meaning of 2007 NAICS C ode 1 NA NA 2 NA NA 3 453000 Miscellaneous Store Retailers 4 424100 Paper and Paper Product Merchant Wholesalers 5 322231 Die cut Paper and Paperboard Office Supplies Manufacturing 5 322232 Envelope Manufacturing 5 322233 Stationery, Tablet and Related Product Manufacturing 5 339941 Pen and Mechanical Pencil Manufacturing 5 339942 Lead Pencil and Art Good Manufacturing 5 339943 Marking Device Manufacturing 5 339944 Carbon Paper and Inked Ribbon Manufacturing 6 313210 Broad woven Fabric Mills 6 313320 Fabric Coating Mills 6 314999 All Other Miscellaneous Textile Product Mills 6 321000 Aggregate of Sawmills, Hard/Soft Wood Veneer/Plywood, Reconstituted Wood Product, Wood Window/Door, Cut Stock, Re sawing Lumber, and Planing Manufacturing 6 322100 Aggregate of Pulp Mills, Paper, and Paperboard Mills 6 322120 Aggregate of Paper and Newsprint Mills 6 322210 Aggregate of Corrugated/Solid Fiber Box and Fiber Can, Tube, Drum, and Similar Products Manufacturing 6 324100 Aggregate of Petroleum Refineries, Lubricating Oil/Grease, and All Other Petroleum/Coal Products Manufacturing 6 325000 Aggregate of Inorganic Dye and Pigment Manufacturing 6 325130 Aggregate of Inorganic and Synthetic Organic Dye and Pigment Manufacturing 6 325520 Adhesive Manufacturing 6 325910 Printing Ink Manufacturing 6 326100 Aggregate of Plastics Bag/Pouch and Non packaging Plastics Film and Sheet Manufacturing 6 332000 Iron/Steel/Nonferrous Forging, Metal Stamping, Hardware, Bolt/Nut/Screw/Rivet/Washer, Industrial Pattern, and Other Miscellaneous Fabricated Metal Product Manufacturing 6 339941 Pen and Mechanical Pencil Manufacturing 7 100 Agriculture (except livestock) 7 211 Oil and Gas Extraction 7 212 Mining (except oil and gas) 7 311 Food Manufacturing 7 313 Textile Mills

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140 7 321 Wood Product Manufacturing 7 322 Paper Manufacturing 7 324 Petroleum and Coal Products Manufacturing 7 325 Chemical Manufacturing 7 326 Plastics and Rubber Products Manufacturing 7 327 Nonmetallic Mineral Product Manufacturing 7 331 Primary Metal Manufacturing 7 332 Fabricated Metal Product Manufacturing 7 333 Machinery Manufacturing 7 335 Electrical Equipment, Appliance and Component Manufacturing 7 339 Miscellaneous Manufacturing 8 10 11 Agriculture 8 21 Mining, Quarrying, and Oil and Gas Extraction (Including Support Activities of Exploration and Development) 8 31 33 Manufacturing 9 100 Agriculture (except livestock) 9 211 Oil and Gas Extraction 9 212 Mining (except oil and gas) 10 213 Support Activities for Mining Figure C 6 Overhead m aterial Supply Chain Level 2007 NAICS Code Meaning of 2007 NA ICS C ode ALL 22 Utilities (22) ALL 48 49 Transportation and Warehousing (48 and 49) ALL 517 Telecommunications (517) ALL 518 Internet Service Providers, Web Search Portals, and Data Processing Services (518) ALL 521 Monetary Authorities (e.g. Central Banks) (521) ALL 522 Credit Intermediation and Related Activities (522) ALL 524 Insurance Carriers and Related Activities (524) ALL 531 Real Estate (i.e. Building Rentals) (531) ALL 532 Rental and Leasing Services (e.g. Machinery Rentals) (532) ALL 54 Professional, Scientific, and Technical Services (54) ALL 561 Administrative and Support Services (e.g. Travel Agency) (561) ALL 562 Waste Management and Remediation Services (562) ALL 61 Educational Services (61) ALL 81 Other Services (i.e. Repair and Maintenance) (81)

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141 ALL NA Aggregate of Florida State and Local Governments (N/A) Figure C 7. Overhead o ther Supply Chain Level 2007 NAICS Code Meaning of 2007 NAICS C ode ALL 10 11 Agriculture (crops and livestock) ALL 21 Mining, Quarrying, and Oil and Gas Extraction (Including Support Activities of Exploration and Development) ALL 22 Utilities ALL 23 Construction ALL 31 33 Manufacturing ALL 42 Wholesale Trade ALL 44 Retail Trade ALL 48 49 Transportation and Warehousing ALL 51 Information Services ALL 52 Finance and Insurance ALL 53 Real Estate and Rental Leasing Services ALL 54 Professional, Scientific, and Technical Services ALL 56 Administrative and Support and Waste Management and Remediation Services ALL 61 Educational Services ALL 62 Health Care and Social Assistance ALL 71 Arts, Entertainment, and Recreation ALL 72 Accommodation and Food Services ALL 81 Other Services (i.e. Repair and Maintenance) Figure C 8. Profit

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142 LIST OF REFERENCES Berry, L. (1997). State level Evaluations of the Weatherization Assistance Program in 1990 1994: A Metaevaluation that Estimates National Savings, ORNL/CON 435 Oak Ridge National L aboratory, Department of Energy, Oak Ridge, Tenn. Cox A. and Townsend, M. (1998). Strategic Procurement in Construction: Towards Better Practice in the Management of Construction Supply Chains Vol. 1, 1 st ed. Thomas Telford Publishing, London. In: L ondon, K. (2008). Construction Supply Chain Economics Taylor and Francis Group, London and New York. Davis, S., Haltiwang er, J., and Schub, S. (1996). Job Creation and Destruction The MIT Press, Cambridge, Massachus etts pp. xviii 62. Economic Oppo rtunity Studies, Inc. (2009). How many workers does the weatherization assistance program employ now? What jobs will the Recovery Act offer? < h ttp://www.opportunitystudies.org/repository/File/weatherization/WAP_Workforce_Sc enarios.pdf > (Jan. 20, 2011). Fei L iu, H. and Emrath, P. (2008). The Direct Impact of Home Building an d Remodeling on the U.S.Economy National Association of Home Builders Washington, D.C. Fobair, R. (2009). Job Creation Calculator: Assessing the Potential of Energy Conservation Investments M.S. Thesis, University of Florida, Gainesville, Fla. Fob air, R. and Kibert, C. (2011). monetized Benefits of an Ener gy Efficiency Retrofit: A Job Forecasting Methodology for Use in Policy Making and SB11 Helsinki World Sustainable Building Conference Helsinki, Finland, October 17 21, 2011. Fuller, S. (2007). The Contribution of Office, Industr ial and Retail Development and Construction on the U.S. Economy National Association of Industrial and Office Properties Research Foundation, Herndon, Va. Fuller, M., Kunkel, C., Zimring, M., Hoffman, I., Soroye, K., and Goldman, C. (2010). Driving Demand for Home Improvements: Motivating residential customers to invest in comprehensive upgrades that eliminate energy waste, avoid high bills, and spur the economy LBNL 3960E Lawrence Berkeley National Laboratory, Environmental Energy Technologies Di vision < http://eetd.lbl.gov/EAP/EMP/reports/lbnl 3960e print.pdf > (Jan. 20, 2011). Goldberg, M., Sinclair, K., and Milligan, M. ( 2004). Job and Economic Development Impact Model (J EDI): A User Friendly Tool to Calculate Economic Impacts from Wind Projects NREL/CP 500 35953 National Renewable Energy Laboratory, Golden, Co <

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143 http://www.ee re.energy.gov/windandhydro/windpoweringamerica/pdfs/35953_jedi.pd f > (Jan 20,2011). Groak, S. (1994). Is construction an industry? Notes towards a greater analytic emphasis on external linkages. Journal of Construction Management and Economics, 12, 287 293. In: London, K. (2008). Construction Supply Chain Economics Taylor and Francis Group, London and New York. Jeeninga, H., et al. ( 1999). Employment Impacts of Energy Conservation in the Residential Sector ECN C 99 082 SAVE Employment Pro ject for the Commission of the European Communities, Directorate General for Energy Netherlands Kaiser, M., Olatubi, W., and Pulsipher, A. (2004). The Projected Impact of Energy Conservation Legislation : The Louisiana Fund Center for Energy Studies, Louisiana State University, Baton Rouge, La. Kibert, C., Fobair R., and Sullivan, J. (2011). Journal of Green Building 6 (2), 156 169. Laitner, S. (1996). The Jobs Connection: Energy Use and Local Economic Development DOE/GO 10096 342 American Council for an Energy Efficient Economy, National Renewable Energy Laboratory Golden, Co London, K. (2008). Construction Supply Chain Economics Taylor and Francis Group, London and New York. Lovins, A. (2004). "Energy Efficiency, Taxonomic Overview Encyclopedia of Energy Vol 2, San Diego and Oxford (UK) pp. 383 401. In : Rocky Mountain Institute, Publication #E04 02. < http://www.rmi.org/Knowledge Center/Library/E04 02_EnergyEfficiencyTaxonomicOverview > (Jan 20, 2011). Mills, E. and Rosenfeld, A. (1996). Consumer Non Ener gy Benefits as a Motivation for Making Energy Efficiency Improvements. Energy The International Journal 21, 7 /8 707 720. Office of Management and Budget (OMB). (2007 ). North American Industry Classification System (NAICS) Executive Office of the Pr esident Washington, D.C. Regional Economic Models, Inc. (REMI). (2011). The REMI Model. < http://www.remi.com/index.php?page=model&hl=en_US > (Jan 17, 2011). Scanla, V. (2010). Energy Circle Pro March 11, 2010. < http://www.energycircle. com/blog/2010/03/11/what deep energy retrofit experts nesea conference respond > (Jan 20, 2011).

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144 Schweitzer, M. and Tonn, B. (2002). Nonenergy Benefits from the Weatherization Assistance Program: A Summary of Findings from the Recent Literature ORNL/CON 484 Oak Ridge National Labo ratory, Department of Energy Oak Ridge, Tenn. Sterzinger, G. (2006). Jobs and Renewable Energy Project Renewable Energy Policy Proje ct (REPP), Washington, D.C. The Statewide Low Income Collaborative Evalua tion (SLICE) of Iowa. (1994). An income Weatherization Efforts Wisconsin Energy Conservation Corporation. I n: Berry, L. (1997). State level Evaluations of the Weatherization Assistance Program in 1990 1994: A Metaevaluation th at Estimates National Savings ORNL/CON 435 Oak Ridge National Laboratory, Department of Energy Oak Ridge, Tenn. To nn, B. and Peretz, J. (2007). State level benefits of energy efficiency. Energy Policy 35, 3665 3674. U.S. Bureau of Labor Statistics (USBLS) (2007). May 2007 OES Estimates. < http://www.bls.gov/oes/oes_dl.htm > (June 24, 2011). U.S. Bureau of Labor Statistics (USBLS) (2010). Green Jobs. < http://www.bls.gov/green/ > (Dec. 29, 2011) U.S. Bureau of Labor Statistics (USBLS) (2011 a ). National Compensation Survey. < http://www.bls.gov/ncs/ncswage201 0.htm > (Dec. 29, 2011). U.S. Bureau of Labor Statistics (USBLS) (2011b). National Compensation Survey Employer Costs for Employee Compensation Historical Listing March 2004 March 2011 Washington, D.C. U.S. Census Bureau (USCB). (2006). Curren t Population Survey Design and Methodology Technical Paper 66, Washington, D.C < http://www.census.gov/prod/2006pubs/tp 66.pdf > (Dec. 29, 2011). U.S. Census Bureau (USCB). (2007 a ). 2007 Economic Census Washington, D.C. < http://factfinder.census.gov/servlet/DatasetMainPageServlet?_program=ECN &_tabId =ECN1&_submenuId=datasets_4&_lang=en&_ts=246366688395 > (Jan. 20, 2011). U.S. Census Bureau (USCB). (2007b). 2007 Census of Governments Washington, D.C. < http://www.census.gov/govs/cog/ > (June 15, 2011). U.S. Census Bureau (USCB). (2009). 2009 Service Annual Survey Washington, D.C. < http://www.census.gov/services/sas/historic_data.html > (June 21, 2011).

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145 U.S. Census Bureau (USCB). (2011). American Time Use Survey Understanding ATUS 2003 to 2010 Washington, D.C. < http://www.bls.gov/tus/atususersguide.pdf > (Dec. 29, 2011). U.S. Depar tment of Agriculture (USDA). (2007). 2007 Census of Agriculture Washington, D.C. < http://www.agcensus.usda.gov/Publications/2007/Full_Report/index.asp > (June 21, 2011). U.S. Department of Labor (USDOL). (2009). WHD Information Related to the American Recovery and Reinvestment Act of 2009. Washington, D.C. < http://www.dol.gov/whd/recovery/#Survey > (Jan. 20 2011). U.S. Government Accountability Office (USGAO). (2005). A Glossary of Terms Used in the Federal Budget Process. GAO 05 734SP Washington, D.C. < http://www.gao.gov/new.items/d05734sp.pdf > (Dec. 29, 2011). Warren, M. (1993). Economics for the Built Environment Butterworth Heinnemann, Oxford, UK. In: London, K. (2008). Construction Supply Chain Economics Taylor and Francis Group, London and New York. Weatherization Assistance Program Technical Assistance Center (WAPTAC). (2009). Weatherizat ion Assistance Program Overview Website u pdated: July 7, 2009. < http://www.waptac.org/sp.asp ?mc=what_overview_program > (Oct. 11, 2009) White House. (2009 a ). Estimates of Job Creation from the American Recovery and Reinvestment Act of 2009. Executive Office of the President Council of Economic Advisors Washington, D.C. < http://www.whitehouse.gov/administration/eop/cea/Estimate of Job Creation/ > (Dec. 29, 2011). White House. (2009b). Recovery through Retrofit Middle Class Task Force, Council on Environmental Quality Washington, D.C. < http://www.whitehouse.gov/assets/documents/Recovery_Through_Retrofit_Final_Re port.pdf > (Dec. 29, 2011). Wiltshi re, V., Jones, E., King, C., Jenkins, T., and Barry, R. (1998). Green Job Creation in the UK London. In: Creation in the European Union European Commission DGXI Unit A2 p roject no: 306/68/24.4.96 London.

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146 B IOGRAPHICAL SKETCH Richard Fobair II studied for his Doctor of Philosophy degree in the M.E. Rinker, Sr. School of Building Construction at the University of Florida. His committee included chairman Charles Kibert, Ph.D., P.E. and members James Sullivan, Ph.D., Paul Oppenheim, Ph.D P.E., and Herbert Ingley, Ph.D., P.E. He has been published in the Journal of Green Building and presented his research at the SB 11 Helsinki World Sustainable Building Confere nce. research interests include sustain able construction, sustainable material selection, building rating systems, effects of buildi ng rating systems on real estate valuation, and job creation throughout supply chains from investments in energy efficiency. He teaches at the University of Flori da and Santa Fe College, where his courses include Construction Estimating I, Construction Mechanics, Structural Design, Construction Materials and Building Codes and Regulations. Additionally, he has been a lecturer in the following courses: Leadership and Management High Performance Building Systems, and Sustainable Construction. Richard holds a Master of Science in Building Construction, Master of Arts in Real Estate and Urban Analysis and B achelor of Arts in Political Science degree from the Univer sity of Florida. His concentrations were sustainable construction and urban planning. Professional work experience includes eight years of commercial construction experience managing hospital, school, jail and courthouse projects, and two years of residen tial construction experience as the owner of a small contracting business. Currently, Richard teaches courses on green building and Leadership in Energy and Environmental Design (LEED) to building industry professionals throughout Florida.

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147 Richard is a li censed certified general contractor and real estate sales person. Additionally, he is a U.S. Green Building Council (USGBC) LEED Accredited Professional (LEED AP, BD&C).