The Impact of the Biomass Crop Assistance Program on the Forest Product Market

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Title:
The Impact of the Biomass Crop Assistance Program on the Forest Product Market an Application of the Global Forest Product Model
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english
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Jiang, Wei
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University of Florida
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Gainesville, Fla.
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Degree:
Master's ( M.S.)
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University of Florida
Degree Disciplines:
Forest Resources and Conservation
Committee Chair:
Carter, Douglas R
Committee Members:
Adams, Damian C
Gao, Zhifeng

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bcap -- bioenergy -- biomass -- gfpm
Forest Resources and Conservation -- Dissertations, Academic -- UF
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Forest Resources and Conservation thesis, M.S.
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theses   ( marcgt )
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Abstract:
With the concerns over energy security andgreenhouse gas emission, the United States is the leading country in producing bioenergy. Although the government has instituted various policies concentratingon bioenergy, the policies addressing the plantation of woody biomass are few.   Considering this deficiency, theBiomass Crop Assistance Program (BCAP) emerged in 2008 with the purpose of plantingenergy crops. However, its effects on forestproduct market, environmental sustainability and welfare economics aresuffering attacks from the congress. This study aims at quantifying itseffects on these three aspects by applying Global Forest Product Model (GFPM).   Three scenarios weredesigned to simulate payments in BCAP. In the first scenario, the matchingpayments were simulated by adjusting themanufacturing cost of fuelwood and particleboard. In the second scenario, theestablishment payments were simulated byadjusting the supply rate of industrial roundwood. The third scenario employed theannual payments by linking the supply change ratewith soil rental rate.   The increasing productionsfrom the establishment payments and the annual paymentsfor fuelwood and industrial roundwood are the main findings. A decrease couldbe found in particleboard under the matching payments,while modest increases happen in woodpulp and paper under the establishmentpayments and annual payments. Few changes were found in forest area but aslight decrease happens in forest stock under the establishment payment. Allof three payments will lead to decreasesin domestic producer surplus and consumer surplus but the exporters of woodpulp and paper arethe biggest winners in this program.
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In the series University of Florida Digital Collections.
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Includes vita.
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by Wei Jiang.
Thesis:
Thesis (M.S.)--University of Florida, 2012.
Local:
Adviser: Carter, Douglas R.
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RESTRICTED TO UF STUDENTS, STAFF, FACULTY, AND ON-CAMPUS USE UNTIL 2014-08-31

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1 THE IMPACT OF THE BIOMASS CROP ASSISTANCE PROGRAM ON THE FOREST PRODUCT MARKET: AN APPLICATION OF THE GLOBAL FOREST PRODUCT MODEL By WEI JIANG A THESIS PRESENTED TO THE GRADUATE SCHOOL OF THE UNIVERSITY OF FLORIDA IN PARTIA L FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF SCIENCE UNIVERSITY OF FLORIDA 2012

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2 2012 Wei Jiang

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3 To Mom and Dad your encouragement is my eternal drive to progress

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4 ACKNOWLEDGMENTS I thank my parents for instilling discipline in me and making me who I am today. I thank my supervisor Dr. Douglas R Carter H e had a lot of things to handle but great honor to work with him and I am thankful for his willingness to accept me as his graduate student. I also acknowledge Dr. Damian C. Adams and Dr Zhifeng Gao who are the members of my committee. They contribute a lot in my research. My heartfelt appr eciation goes to Dr. Marian Marinescu. Without him, I cannot chase my dream for being in the United States I also extend my thanks to Charles Nettleman who provides me with the fresh views of life and expert opinions on academic research. Besides, I appre ciate the help from Xi Liang who always blames me but is always concerned about me. I am thankful to College of Agricultural and Life Science and Department of Forest Resources and Conservation for providing me with assistantship to support me to complete my thesis and study at University of Florida. Ultimately, I must thank to my boyfriend, Jiang Jin. Without him hardly can I finish my thesis.

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5 TABLE OF CONTENTS page ACKNOWLEDGMENTS ................................ ................................ ................................ .. 4 LIST OF TABLES ................................ ................................ ................................ ............ 7 LIST OF FIGURES ................................ ................................ ................................ .......... 8 ABSTRACT ................................ ................................ ................................ ................... 10 CHAPTER 1 INTRODUCTION ................................ ................................ ................................ .... 12 Background ................................ ................................ ................................ ............. 12 The Supply of Woody Biomass in the United States ................................ ............... 13 Biomass Assistance Program ................................ ................................ ................. 19 2 LITERATURE REVIEW ................................ ................................ .......................... 26 Overview Policies Supporting Woody Biomass in the United States ...................... 26 Overview Economic Analysis for Biomass Policies ................................ ................. 30 Overview of the Applications of GFPM ................................ ................................ ... 34 3 METHODOLOGY ................................ ................................ ................................ ... 3 7 Model Instruction ................................ ................................ ................................ .... 37 Country Classification ................................ ................................ ............................. 37 Commodity Coverage ................................ ................................ ............................. 37 Six Exogenous Variables ................................ ................................ ........................ 40 Primary Product Sup pl y ................................ ................................ .................... 40 End Product Demand ................................ ................................ ....................... 41 Manufacture Capacity ................................ ................................ ...................... 42 Forest Reso urce ................................ ................................ ............................... 43 Recycle ................................ ................................ ................................ ............. 43 Transport ................................ ................................ ................................ .......... 43 Objective Function ................................ ................................ ................................ .. 44 Constraint Function ................................ ................................ ................................ 45 4 SCENARIO DESIGNED ................................ ................................ ......................... 46 Baseline Scenario ................................ ................................ ................................ ... 46 The Matching Payments ................................ ................................ ......................... 46 The E stablishment P ayments ................................ ................................ ................. 48 The A nnual P ayme nts ................................ ................................ ............................. 49

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6 5 RESULT ................................ ................................ ................................ .................. 51 The Matching Payments ................................ ................................ ......................... 51 Production and Price Change for Fuelwood ................................ ..................... 51 Production and Price Change for Industrial Roundwood and Particleboard ..... 52 Welfare Economics Change Under the Matching Payments for the United States ................................ ................................ ................................ ............ 53 The Establishment Payments ................................ ................................ ................. 54 Production and Price Change for Fuelwood ................................ ..................... 54 Production and Price Change for Industrial Roundwood, Woodpulp and Paper ................................ ................................ ................................ ............ 58 Welfare Economics Change Under the Establishment Payments in the United States ................................ ................................ ................................ 59 The Annual Payments ................................ ................................ ............................. 62 Production and Price Change for Fuelwood ................................ ..................... 62 Production and Price Change for Industrial Roundwood, Woodpulp and Paper ................................ ................................ ................................ ............ 63 Welfare Economics Change Under the Annual Payments in the United States ................................ ................................ ................................ ............ 63 Effects on Forest Area and Forest Stock ................................ ................................ 67 6 DISCUSSION AND CONCLUSION ................................ ................................ ........ 69 Disc ussion ................................ ................................ ................................ .............. 69 Conclusion ................................ ................................ ................................ .............. 70 APPENDIX. PARAMETERS USED IN GFPM ................................ .............................. 72 LI ST OF REFERENCES ................................ ................................ ............................... 79 BIOGRAPHICAL SKETCH ................................ ................................ ............................ 85

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7 LIST OF TABLES Table page 1 1 C lassification of biomass based on technology ................................ .................. 17 1 2 Qualified eligible mate rials for the matching payments ................................ ....... 21 6 1 T he absolute change in production for industrial roundwood in the United States under the matching payments ................................ ................................ 55 6 2 The absolute price change of particleboard and industrial roundwood under the matching payments ................................ ................................ ...................... 56 6 3 The absolute added value for the United States under the matching payments. ................................ ................................ ................................ ........... 57 6 4 The absolute change in production of industrial roundwood, woodpulp and paper under the establishment payments ................................ ........................... 60 6 5 The absolute change in prices of industrial roundwood, woodpulp and paper under the establishment payments ................................ ................................ ..... 61 6 6 The absolute added value in the United States under the establishment payments ................................ ................................ ................................ ............ 61 6 7 The absolute change in production of industrial roundwood, woodpulp and paper in the United States under the annual payments ................................ ...... 65 6 8 The absolute change in prices of industrial roundwood, woodpulp and paper under the annual payments ................................ ................................ ................ 66 6 9 The absolute change in added value under the annual payments ...................... 66 A 1 Commodity codes in GFPM ................................ ................................ ................ 72 A 2 Count ry codes in GFPM ................................ ................................ ..................... 73 A 3 GFPM demand table for the United States in base year 2006 ............................ 75 A 4 GFPM supply table in the United States in base year 2006 ............................... 76 A 5 GFPM manufacturing cost table for the United States in base year of 2006 ...... 77 A 6 I O coefficient in GFPM for the United States ................................ ..................... 78

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8 LIST OF FIGURES Figure page 1 1 Primary Energy Consumpti on by Source and Sector, 2010. .............................. 14 1 2 The share of renewable energy in the energy consumption in the United States. ................................ ................................ ................................ ................ 15 1 3 Sources of biomass ................................ ................................ ........................... 15 1 4 The d istribution of the matching payments among biomass resources in 2010. ................................ ................................ ................................ .................. 22 1 5 The d istribution of the matching payments among woody biomass in 2010. ...... 22 1 6 The state matching payments reimbursement in 2010. ................................ ...... 23 3 1 Forest product transformation in GFPM. ................................ ............................ 38 6 1 T he change of fuelwood under the matching payments. ................................ .... 55 6 2 The production change s of industrial roundwood and particle. ........................... 55 6 3 The percentage changes in prices of particleboard and industrial roundwood under the matching payments. ................................ ................................ ........... 56 6 4 The percentage change of welfare economics under the matching payments. .. 57 6 5 The percentage change of fuelwood production and consumption under the establishment payments. ................................ ................................ .................... 60 6 6 The percentage change in production of industrial roundwood, woodpulp and paper under the establishment payments. ................................ .......................... 60 6 7 The percentage change in price of industrial roundwood, woodpulp and paper under the establishment payments. ................................ .......................... 61 6 8 The percentage change of welfare economics in the United States under the establishment payments. ................................ ................................ .................... 62 6 9 The production change of fuelwood under the annual payments ....................... 65 6 10 The percentage change of industrial roundwood, woodpulp and paper under the annual payments. ................................ ................................ ......................... 65 6 11 The percentage change in prices of industrial roundwood, woodpulp and paper under the annual payments. ................................ ................................ ..... 66

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9 6 12 The percentage change in welfare economics under the annual payments ...... 66

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10 Abstract of Dissertation Presented to the Graduate School of the University of Florida in Partial Fulfillment of the Requirements for the Degree of Mast er of Science THE IMPACT OF THE BIOMASS CROP ASSISTANCE PROGRAM ON THE FOREST PRODUCT MARKET: AN APPLICATION OF THE GLOBAL FOREST PRODUCT MODEL By Wei Jiang August 2012 Chair: Douglas R. Carter Major: Forest Resources and Conservation With the concerns over energy security and greenhouse gas emission, the United States is the leading country in producing bioenergy. Although the government has instituted various policies concentrating on bioenerg y, the policies addressing the plantation of woody biomass are few. Considering this deficiency, the Biomass Crop Assistance Program ( BCAP) emerged in 2008 with the purpose of plant ing energy crops. However its effects on forest product market, environmental sustainability and welfare economics are suffering atta cks from the congress. This study aims at quantifying its effects on these three aspects by applying Global Forest Product Model ( GFPM). Three scenarios were designed to simulate payments in BCAP. In the first scenario, the matching payment s were simulated by adjusting the manufacturing cost of fu elwood and particle board. In the second scenario the establishment payment s were simulated by adjusting the supply rate of industrial roundwood. The third scenario employed the annual payment s by linking the suppl y change rate with soil rental rate.

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11 The increasing production s from the establishment payment s and the annual payment s for fuelwood and industrial roundwood are the main findings. A decrease could be found in particleboard under the matching payments whi le modest increases happen in woodpulp and paper under the establishment payments and annual payments Few changes were found in forest area but a slight decrease happens in forest stock under the establishment payment A ll of three payments will lead to d ecrease s in domestic producer surplus and consumer surplus but the exporters of woodpulp and paper are the biggest winners in this program.

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12 CHAPTER 1 INTRODUCTION Background World energy markets are in transition and a general consensus has emerged that bi omass energy could expand in the next decades (Ince, 2011). At present, biomass energy accounts for 10 % of primary energy consumed globally, which is more than the produced from all other renewable and nuclear power combined and, among those, woody source s account for 87 % of all biomass used g lobally for energy (FAO, 2009) The share of utilization of biomass varies across the countries or regions generally correlated with the level economic development and industrialization (FAO, 2009) In developing coun tries, biomass is a primary energy source for home heating and electricity but its share in energy structure is declining because of the strong demand arising in fossil fuel. F or the developed countries, growing conce rns about climate change and energy sec urity are the basic drive s for increasing utilization of biomass energy. As the largest gasoline consumer, the United States imports half of its consumption from foreign countries. The biggest industry consuming petroleum is transportation which digests 7 1% of petroleum product ( F igure 1 1). As a consequence, it also becomes a big producer for the greenhouse gas which contributes to 3 4 % of carbon dioxide emissions ( EIA, 2010 a ) The newly released Annual Energy Outlook 2012 energy consumption in the transportation sector will grow from 27.6 quadrillion British Thermal Unit (BTU) in 2010 to 28.8 quadrillion B TU in Electricity is another producer for greenhouse gas. Though only consum ing about 1% of petroleum ( Figure 1 1 ) the electricity industry deploys about 92 % of coal

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13 ( F igure 1 1) which is regarded as another main source generating carbon dioxide In 2009, electricity emitted 41% of the carbon dioxide from fossil fuel combustion (Hodges 2011) which is more than th at from transportation. Therefore how to decrease the energy consumption and how to reduce the carbon dioxide from these two industries are the top two priorities for policy makers. Two types of renewable energy are prominent in relieving the concerns ove r transportation and electricity: biofuel and biopower. Estimated by the International Energy Agency, biofuel has the potential to meet more than a quarter of demand for transportation fuels by 2050 for the United States. With the technology of combined he at and power (CHP) by substituting parts of coals by woody biomass, biopower is also effective in reducing the emission of carbon dioxide. Both of biofuel and biopo wer are generated from biomass. What is biomass? What is the current status of biomass in th e United States ? And how much biomass could be supplied to produce biofuel and bioenergy ? The answer s would be found in the next section with the special attention on woody biomass. The Supply of Woody Biomass in the United States I n 20 09 renewable energy accounted for 8 percent of the U.S. energy consumption or 7.745 q uadrillion BTU (E I A 2010c) Among renewable energy market, biomass accounts for 53% of the total renewabl e energy consumption market ( F igure 1 2) and the trend is expected to continue in th e next two decades with the U.S. Department of Energy (DOE) and the U.S. Department of Agricult ure (USDA) requirements that 30 % of current the U.S. petroleum consumption be replaced wi th biofuel by 2030 (Perlack et al. 2005)

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14 Figure 1 1 Primary E nergy Consumption by Source and Sector, 2010 [ Source : U.S. Energy I nformation Administration, Annual Energy Review 2010, http://www.eia.gov/totalenerg y/data/annual/pecss_diagram.cfm ]

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15 Biomass is the organic materi al made from plants and animals and most of them are from forestry (woody) and agriculture ( F igure 1 3 ) : Figure 1 2 The share of renewable energy in the e nergy consumption in the United States [Data source: the environmental information agency, 2011, Renewable Energy Production and Consumptio n by Primary Energy Source, 1949 2010 .] Figure 1 3 Sources of biomass [ Adaptive based on the U.S. Department of Energy, 2011. U.S. Billion Ton Update: Biomass Supply for a Bioenergy and Bioproducts Industry. R.D. Perlack and B.J. Stokes (Leads), ORN L/TM 2011/224. Oak Ridge National Laboratory, Oak Ridge, TN. 227p]

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16 Biomass energy has certain advantages over other renewable energies For example biomass is stored energy. It can be drawn on at any time, unlike daily or seasonally intermittent solar, wi nd, wave and small hydro sources whose contributions are all constrained by the high costs of energy storage (FAO, 2009). Biomass energy systems can produce energy in several different carriers at the same facility or implementation platform, thereby enhan cing economic feasibility and reducing the environmental impact (FAO, 2009). Typically, the utilization s of woody biomass mainly concentrate on two aspects: Solid Bioenergy --biopower for electricity generating by combustion or gasification processes, c o firing along with coal, or for CHP system in industrial facilities; highly compact wood pellet used for heating purpose (Aguilar and Saunders, 2011) Liquid Bioenergy --biofuel (bioethanol, biomethanol and biodiesel) which can be blended with conventi onal transportation fuels and bioproduct (Alavalapati, 2009). Based on the utilizations, woody biomass could be divided into two categories ( T able 1 1) From Table 1 2 we are able to conclude that woody biomass was categorized into second generation bioma ss to generate second generation biofuel in the long term period. Especially for Short Rotation Wood Crop (SRWC ), it is able to meet all the requirements from biofuel, biopower and bioproduct. Therefore, developing the woody biomass seems to be promising w ith a long term perspective. Currently, i n the United States, the supply of wood feedback for bioenergy is from the following resources (Perlack et al. 2005): The recovered residues generated by traditional logging activities and residues generated from f orest cultural operations or clearing of timberlands.

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17 Table 1 1 C lassification of biomass based on technology Liquid Bioenergy Solid Bioenergy Feedback First generation fuels Second generation fuels Biopower Bioproduct Ethanol Biodiesel Methane C ellulosic Ethanol Thermos Fuels Stand along Co firing Second generation(short term) Forest Biomass Logging residues Fuel treatment Conventional wood X X X X X X X X X X X X X X X Urban woody waste and landfills Primary wood product Secondary mill residues Municipal solid waste Construction demolition wood landfills X X X X X X X X X X X X X X X X X Second generation (long term) Herbaceous energy crops Switch grass Miscanthus Reed canary grass Sweet sorghum Alfalfa X X X X X X X X X X X X X X X X X Short rotation woody crops Willow H ybrid poplar C ottonwood pines Sycamore pines Eucalyptus X X X X X X X X X X X X X X X X X X X X X X X X X Source : adaptive based on the U.S.Department of Energy, Biomass Research and Deve lopment Board, 2008. Increasing feedstock production for biofuels: economic drivers, environmental implications, and the role of research.

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18 The recovered residues generated from fuel treatment operations on timberland and other forestland. The direct con versio n of round wood to energy (fuel wood) in the residential, commercial, and electric utility sectors. Forest products industry residues and urban wood residues. Forest growth and increase in the demand for forest products. The estimated supply of woo dy biomass totally is 368 million dry tons annually (Perlack et al., 2005) Among these resources, the residues from primary logging, thinning or processing treatment currently take the larger share to produce bioenergy with the supply amount of 243 millio n dry tons while the fuelwood and other forest growth (SRWC) with long term perspective combined only occupy a small amount of 124 million dry tons. W hy the supply for those dedicated energy crops is small ? The concerns over market price and risks existin g in biomass markets are the main reasons. In the woody biomass market, the price should be higher fairly to compete with woodpulp and paper purchas ing price for raw materials and also be lower enough to compete with other fossil fuel to generate energy T hese two constrains make the price of woody biomass instable and exacerbate the market risks for farmers and landowners. In addition to this, numerous public policies aiming at subsidizing bioenergy instead of biomass also distort the new market mechanism. Th erefore, this research picks up Biomass Crops Assistance Program (BCAP) as the research target to examine its effects on traditional forest product Compared with other policies, BCAP is standing out with several features : The payment s are directly issu ed to biomass instead of bioenergy.

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19 It is the program that aim s to encourage the plantation of the long term energy crops. It initially puts two types of payments for short term residues and long term energy crops into one program. It focuses on subsidizin g transport and har vest cost of eligible materials, which are regarded as the big two obstacles hindering the development of biomass ( Becker, 2009) Therefore, a detailed introduction for BCAP is needed Biomass Assistance Program BCAP was authorized by t he Food, Conservation, and Energy Act of 2008 to provide financial assistance to owners and operators of agricultural and non industrial private forest land owners who wish to establish, produce, and deliver biomass feedstock (BCAP, 2011) It was fully impl emented as of October 27, 2010 and administered by USDA through the Commodity Credit Corporation (CCC) and the Farm Service Agency (FSA). Funding is currently authorized through September 30, 2012. The cap for fiscal year 2010 is $512 million and for 2011 is $432 million (10/1/10 9/30/11) and meanwhile no limit for fiscal year 2012 (10/1/11 9/30/12). BCAP is comprised of two The matching payments : they intended to assist agricultural and fo rest land owners and operators with the collection, harvest, storage, and transportation (CHST) of eligible materials for use in a biomass conversion facility. The matching payment s are authorized to be made at a rate of $1 for each $1 per dry ton paid by a Qualified Biomass Conversion Facility (QBCF) for the sale and delivery of eligible materials. Payments are capped at $45 per dry ton. These payments are mad e directly to e ligible m aterial o wners. P ayments are authorized to be made for a 2 year period, be ginning on the date the first payment is issued to the eligible material owner (BCAP, 2011)

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20 The e sta blishment payments and t he annual payment s: they intended to support the establishment and production of eligible crops for conversion to bioenergy in selec ting BCAP project area s. The establishment payment s cover up to 75% of the actual or average cost (whichever is lower) of establishing an eligible perennial crop (either woody or non woody). The annual payment s intended to offset the lost opportunity costs associated with cultivating a biomass crop as opposed to a traditional crop. Payments will be similar to Conservation Reserve Program (CRP) payments and it The tim e period for the annual payments would be up to 5 years for annual and perennial non woody crops and up to 15 years for perennial woody crops. Several requirements for eligible materials and eligible area need to be noticed. In the mat ching payment s, the r equirements for eligible material s could be summarized into the Table 1 2 From Table 1 2 we could find that most of the eligible materials are residues including logging residues, thinning residues as well as pro cessing residues. As a result, the matchin g payments are regarded as the part addressing the utilization of short term residues. The rules for eligible area in the matching payments are not strict. Regard the establishment payments and the annual payments the requirements for eligible materials a re not strict. Any organic matter that is available on a renewable or recurring basis from non federal land could be qualified as eligible materials. However, the rules for eligible area is relatively strict compared with the matching payments. The area sh ould be agricultural land and nonindustrial private forest land Land that is native sod or simultaneously enrolled in the: Conservation Reserve

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21 Program ( CRP); Wetlands Reserve Program; Grassland Re serve Program are not included. Table 1 2 Qualified elig ible materials for the matching payments Eligible Material If collected or harvested directly from the land before transport and delivery to the biomass conversion facility If collected or harvested by separation from a higher value product collected or harvested directly from the land b efore transport and delivery to the biomass conversion facility after transport and delivery to the biomass conversion facility Forest thinning Y Y N Post disaster debris Y Y N Hardwood chips Y Y N Softwood chips Y Y N Cutoffs Y Y N Bark Y Y N Trees and shrubs without timber lumber or wood pulp value Y Y N Trees and shrubs with timber, lumber or wood pulp value Y non federal land N N Source: the U.S. Department of Agriculture/ Farm Service Agency, BCAP 2011. Th e biomass crop assistance program (BCAP) Final Rule Provision On June 11, 2009, the first phase of the BCAP as authorized by the 2008 Farm Bill was implemented through the publication of a Notice of Funding Availability (NOFA). This NOFA provided the m atching payment s for the collection, harvest, storage and transportation (CHST) of biomass material to approved energy conversion facilities. On October 27, 2010, a final rule was published implementing all phases of BCAP including financial assistance for the establishment and maintenance of crops for bioenergy production as well as the CHST payments previously funded through the NOFA ( BCAP 2011 )

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22 Figure 1 4 T he d istribution of the matching payments among biomass resources in 2010 [ Data source: the U .S. Department of Agriculture/ Farm Service Agency, BCAP, 2010, Report of BCAP CHST payments by biomass type .] Figure 1 5 T he d istribution of the matching payments among woody biomass in 2010 .[Data source: the U.S. Department of Agriculture/ Farm Ser vice Agency, BCAP, 2010 Report of BCAP CHST payments by biomass type .]

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23 Figure 1 6 T he state matching payments reimbursement in 2010 [Data source: the U.S. Department of Agriculture/ Farm Service Agency, BCAP, 2010, Summary Report of BCAP CHST payme nts .]

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24 Based on one year statistics ( F igure 1 4 and F igure 1 5), we could clearly determine that the majority of BCAP subsidies are distributed to woody biomass and among woody biomass, fuelwood and chips combined occupy a very important position in the mat ching payments In 2010, 30 states ( Figure 1 6) had jointed in this program and the expense for BCAP from each state is not small. It seems that BCAP would attract more participants with further implementation. However, initial implementing the matching pa yment s raised questions and concerns about the BCAP program as a whole which subsequently brought attention to other aspects of the BCAP program. These questions are : Competition with traditional forest product: g iven the large production capacity of fores ts product, the forest industry still holds an important position in the United States In 2009, the industrial roundwood produced and exported from the United States occupy 20.7% in the world market and the share for woodpulp is even higher reaching to 3 5% ( Oel, 2010) However, the matching payment s pulp and paper manufacturing and nursery industries that use industrial roundwood noticed an increase in price for their raw materials. This increase was linked, by some, to the BC AP payments which offered a federal payment match for the same materials (Stubbs, 2010). Sustainability: a lthough biomass was considered as a tool to protect environment, negative impacts on the forest system such as wildlife habitat destruction, soil eros ion and deforestation would still happen (Buongiorn o et al 2011). BCAP has a dual purpose on establishing new dedicated biomass crops for bioenergy production (annual and the establishment payment s) and increasing the collection of exist ed and underutili zed biomass for bioenergy production ( the matching payment s). The latter purpose for biomass removal in areas where it is possible but not currently profitable is a key factor for the forestry recovery. Efficiency: BCAP initially picked up the concept enco uraging the plantation of energy crop for bi o energy production. However, a new market might weak the substituted market such as pulp industry. Whether this program could finally enhance the welfare economics in the whole forestry industry in the United Sta tes is still a misery Since BCAP was only implemented completely for one year and data correlated to the problems mentioned above is not consistent this res earch aiming to quantifying the

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25 BCAP s effects on these three problems will be conducted based on numerous assumption with an application of Global Forest Product Model (GFPM).

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26 CHAPTER 2 LITERATURE REVIEW The future of bioenergy and wood energy development is largely dependent on the effectiveness of policies and the consistency with which they are i mplemented Therefore, an overview for the public policies is the first step to research. Overview Policies Supporting Woody Biomass in the United States T he classification of public polices with respect to woody biomass could be viewed from different pers pectives Here, we adopted the classification from Aguilar (2011) that the policies from 1970 to 2009 are discussed under two categories: biopower and vehicle liquid fuels which are compiled with the two utilizations of woody biomass. Aguilar and Saunders (2011) pointed out that fiscal incentives are the most popular policy instruments in favoring biopower market Tax credits were regarded as the top frequently used financial tool. For example, the federal renewable electricity production tax credit (PTC) was a per kilowatt hour tax credit for electricity generated by qualified energy resources and sold by the taxpayer to the unrelated person during the taxable year (DSIRE, 2009). Originally enacted in 1992, the PTC had been renewed and expanded numerous ti mes. The extension from closed loop biomass to open loop biomass began to include forest related resources such as mill and harvesting residues, pre commercial thinning, slash, brush and solid wood waste materials used to power electricity plants (e.g. was te pallets, crates, manufacturing and construction wood wastes and landscape or right of way tree trimmings). As the subsequent policy to PTC, Business Energy Investment Tax Credit (ITC) allowed taxpayers eligible for PTC to take the federal ITC to receiv e a grant from the U.S Treasury Department instead of taking the PTC for new installation. For biopower,

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27 it typically concentrated on CHP technology requiring that CHP plant might get 10% of credits of the total expenditures without maximum limit stated. Although there was a requirement for the capacity of CHP system, it did not apply to the systems using State governments also focus on activating local biopower market by issuing public policies. The Renewable Portfolio Standard (RPS) is the most commonly adopted. It is a state policy that requires electricity providers to obtain a minimum percentage of their power from renewable energy resources by a certain date. As of March 2009, RPS requirements or goals had been established in 33 states plus the District of Columbia (EPA, 2009) Becker (2008) summarized detailed policies supporting biomass for each state by using Database of State Incentives for Renewable Energy (DSIRE) and the Reuters Find Law sea rch engine. T ax incentives were also widely adopted in state RPS For example, in Florida, the renewab le energy production tax credit was equal to $0.01/kWh of electricity produced and sold by the taxpayer to an unrelated party during a given tax year (Bec ker and Lee, 2008). The Minnesota Power Grant Program offered grants up to $50,000 to its commercial, industrial, and agricultural customers who use innovative technologies, improve manufacturing processes, undertake renewable electric energy projects or w ho need project design assistance. Eligible projects include renewab le energy products, new electro technologies that lower energy costs per unit of production in a manufacturing process, innovative technologies that are new and underutilized in the regio nal marketplace, and the inclusion of energy efficient options in the design phase of a project (Be cker and Lee, 2008).

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28 Detailed policy summary for liquid vehicle fuel is providing by Guo and Sun (2007). After viewing policies from 1970s, they concluded th at financial incentives were also the main method subsidizing biofuel. M ost of subsidies were awarded to the first generation biofuel. Much success of the corn ethanol industry in the United States could be attributed to governmental incentive polices star ting in the 1970s (Duffield and Collins, 2006). One of the earliest energy statutes was the Energy Tax Act of 1978 It initially exempted the federal gasoline excise tax of $0.40 per gallon through 1984 on gasoline blended with at least 10 % ethanol produce d from biomass. In recent years, increasing federal policies have addressed the utilization of forest biomass for biofuel production. First of all, the Biomass Research and Development Act of 2000 (Title III of the Agricultural Risk Protection Act) address es the utilization of trees, wood, wood wastes and residues as feedstock for bioproducts. The grants are awarded to improve cellulosic biomass conversion, biomass technologies to biobased fuel and product. The Farm Security and Rural Investment Act, common ly referred to as the Farm Bill, was first developed in the 1920s and had been reviewed approximately every six years. The 2002 Farm Bill included an energy title for the first time in history (Na zzar, 2005). It establishes bio refinery grants to assist th e emerging technologies for the use of biomass, including lingo cellulosic biomass to diversify markets for agricultural and forestry products. The Energy Policy Act of 2005 reflected the energy policy of increasing and diversifying domestic energy product ion (Nazzar, 2005; Duffield and Collins, 2006). It established various programs to foster research and development of woody biomass conversion technologies and biofuel production. In particular, it included stipulations

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29 specific to forest biomass utilizati on to prevent hazardous fires, reduce disease and insect infestation, and restore forest health. The Energy Independence and Security Act of 2007 further the emphasis on bioenergy. Section 202 creates the Renewable Fuel Standard ( RFS) calling for transport ation fuel sold or introduced into commerce in the United States, on an annual average basis, containing at least the applicable volume of renewable fuel, advanced bio fuel, cellulosic bio fuel, and biomass based diesel. BCAP was authorized by the Food, Co nservation, and Energy Act of 2008 to provide financial assistance to owners and operators of agricultural and non industrial private forest land owners who wish to establish, produce, and deliver biomass feedstock. BCAP provided (a) the matching payment s f or no more than two years to eligible material owners, at a rate of 1$ for each 1$ paid by a qualified biomass conversion facility up to $45 per moisture free metric ton of delivered biomass to produce heat, power, biobased products, or advanced bio fuels; (b) the establishment payment s up to 75 percent of the cost of establishing a bio energy perennial crop and (c) and up to 15 years of the annual payment s for woody crops. There is no doubt that government is actively participating in the bioenergy market with various polices. However, with respect to the big two problems associated with woody biomass transport cost (Aguilar and Saunders, 2011, Becker and Lee, 2011 Perlack, 2005) and competition for raw materials with traditional forest product, there are few policies aiming on emphasizing them solely Except BCAP, there were only two state level policies for subsidizing transportation cost. T he Oregon RFS provides a $9 per green ton income tax credit for the removal and use for energy of biomass directly from the forest. The Arizona Healthy Forest Enterprise Incentives Program was to offset

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30 the high cost of transportation due to distant processing facilities (Becker and Lee, 2011). To address the competition for raw materials between forest product and bio energy market, there are no specific policies. Even in BCAP, only some words are found that the products with a higher market value could not be qualified as eligible material but did not explain the standard to justify the higher market value. Therefore, the research is needed to examine the effect of the federal program aiming at subsidizing transport cost and addressing the competition between forest product market and bioenergy market Overview Economic Analysis for Biomass Policies The economic analysi s for woody biomass production is extensive. Most of these studies are concentrating on the analysis of production cost with consideration of feedback, technology and miscellaneous other procurement, transaction as well as opportunity costs. However, the e conomic studies on policy driven supply change and projection for woody biomass market are limited Therefore, we first introduce a study in Norway with the projection of woody biomass supply. Trogmbor and Bolkesjo (2007) applied NTMII, a model belonging to the same class of models as the GFPM, the European Forest Institute Global Trade Model (EFI GTM) and NTM, to simulated three policies in Northway: subsidies reducing 50% of the investment costs of district heating installations; deposit grant for repla cing of oil burners with burners based on bioenergy with the accordance to 50% subsidies; feed in supporting energy production in district heating based on bioenergy. Four alternative scenarios were designed so as to simulate these polices and firewood, ch ips and pellets were regarded as the representatives of woody biomass. The results provide us with medium term projections for bioenergy use in Norway.

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31 Abt (2010) conducted research measuring the competition between woody biomass and traditional forest pr oduct market. A higher demand for woody residuals or pulpwood driven by RPS in North Carolina was added to the existing forest product demand with Sub Regional Timber Supply Model (SRTS). The results indicated that logging residue alon e could not meet the bioenergy demand required in RPS and pulpwood should be used as an option. Thus, there was an increase in price as well as removals of pulpwood and displacement of traditional product would also be intensified. A relatively completed examination of the s tate RPS policy is conducted by Hodges (2010). In their reports, three programs including Renewable Electricity Standard, renewable electricity production tax credit and biomass feedstock subsidy (BCAP) were simulated by Computable General Equilibrium (CGE ) model, Input Output analysis and Social Accounting M atrices (I O/SAM). Accordingly ; three scenarios were deigned to finish the simulation: the modifications of Leontief coefficient for the intermediate inputs in CGE model, the negative excise tax rate fo r electric power and a negative sales tax on purchases of biomass by the electric power sector from the forestry sector in the CGE. The results indicated that various polices and incentives f or bioenergy development would bring a relatively small increase in Gross Domestic Product (GDP), overall employment and state government revenues of Florida with a modest decreas e of fossil fuels imports However, the forest product manufacturing sector would be adversely affected by competition for wood resources resu lting in higher prices for material inputs.

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32 In summary, the economic analysis implied that the higher demand driven by public policies might have a negative effect on forest product market from the biopower market perspectives. Beach and McCarl (2010) ut ilized the Forest and Agricultural Sector Optimization Model (FASOM) to simulate the economic effect of EISA in biofuel market In this study, milling residues and logging residue s were regarded as t he input source to generate bio fuel and the results indic ated the prices for hardwood as well as softwood would rise up under the control case and it also might decrease the competitiveness of forest product for the United States. Wu (2011) in her dissertation wrote that, based on the analysis of EISA with Agric ultural Policy Simulation Model (POLYSIS) and SRTS, the softwood pulpwood inventory and price were more sensitive than other forest products to changes in biofuel production which mean s that a small increase in biofuel production would induce a bigger cha nge of pulpwood price and that delaying meeting mandated biofuel targets to future years could maintain a sustainable pulpwood forest inventory. These researches implied that the competition for raw materials also existed in the biofuel market Since polic ies aiming to subsidize transport cost are few, there are few economic analyses about transport cost Becker (2009) simulated two transportation incentives: the transportation costs of waiving a federal excise tax of $0.2 gallon and a subsidy in which each ton of woody biomass collected from a qualifying source and transported to a bioenergy or bio fuel facility is eligible for an offset payment to the contractor. He pointed out that the transport of raw materia l was the single greatest cost. Transportation subsidies would have to be substantial to result in a significant change

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33 T he offsets achieved through the new federal BCAP which offers a dollar for dollar transportation cost share up to $45/dry ton, is notable. Based on the literatures discussed above we could find that the competition for raw materials between forest product and bioenergy market is existing in both biopower market and biofuel market. However, most of these researches only examined the short term supply change of woody biomass to meet the extra demand for raw materials driven by public policy. It means that these studies regarded most of residues (logging residues, thinning residues, milling residues and other wastes) as the materials to receive subsides but ignore the long term woody biomass such as the plantation of SRWC. If the extra supply was achieved the competition for raw material is still existed or not? In addition transportation cost is a big concern in the development of biomass. A substantial subsidy for it is required. BCAP is outstanding in favoring transport cost. Whether it w orsens the competition or not? The subsidy for transport cost is effective? We need to measure its effects in details. Furthermore policy simulation for current bioenergy market is typically divi ded into two steps: first, identifying the subsidies for biopower or biofuel; then, based on a series of assumptions, transfer these subsides to the input sources woody biomass. The transferring might complicate the simulation process and might result in i naccurate results. A call for examining direct subsidy for woody biomass is emerging. BCAP, as a federal program awarding direct subsidies for woody biomass and focusing on transport cost, naturally is picked up as the research target.

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34 Overview of the Appl ications of GFPM The Global Forest Products Model (GFPM) is an economic model of production, consumption, and trade in forest products at the global level. It uses historical information and exogenous assumptions in a market equilibrium model to produce fo recasts of global forest products market developments to 2060. The history of this model could be dated back to the development of PAPYRUS model for U.S pulp and paper industry (Buongiorno and Gilless 1983). The PAPYRUS was built with a general structure and software to model any economic sector with spatial and dynamic elements, the Price Endogenous Linear Programming System (PELPS). The PELPS software became PELPS II Plus and PELPS III. The latest version, PELPS IV, forms the structure of the GFPM. The first connection between GFPM and energy happened after energy crisis. Buongiorno and Chang (1986) tested if there had been systematic changes in the income and price elasticity of demand for forest products after the first oil embargo of 1973. Though this research mainly focused on price change for forest product, it was a good try to link demand change from energy to forest resources. Raunikar and Buongiorno (2010) exa mined the competition between high demand for bioenergy set Intergovernmental Panel on Climate Change (IPCC) and future demand for timber and forestry by manipulating GFPM. In this paper, they took two scenarios designed by IPCC as research objectives. Via modifying GFPM by an assumption that the industrial wo od would be converted into fuel w ood when the prices of these two products are equ al, they demonstrated that fuel wood would increase by 5.4 percent from 2006 to 2060 and, on the contrary, industrial wood production will be affected negatively. In additi on, Buongiorno and Raunikar (2011) a lso m easured the

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35 consequences for the global forest sector of doubling the rate of growth of bioenergy demand relative to a base scenario, keeping other drivers constant with GFPM. A more detailed model USFPM/GFPM was introduced by Ince and Kramp (2011). It provided a detailed picture of the U.S. regional timber supply and wood residue markets. Scenarios were designed with USFPM/GFPM ranging from baseline of 48% incr ease to 173% increase in annual consumption of fuel wood for energy from 2006 to 2030 in the United States while consumption of fuel wood in other countries was assumed to incre ase by around 65% in aggregate. Except energy market, traditionally, GFPM was widely adopted in analyzing the change driven by policy in forest product market Zhu and Buo ngiorno (2001) applied GFPM to assess the impact of the U.S. paper recycling policies and pointed out further paper recycling in the United States would affect the pulp and paper markets in other countries. Buongiorno (2003) also applied GFPM to present a simulation of the impact of the U.S. timber harvest policies on Pacific Rim timber markets and forest resources. Economic change and trade change could also be simulated with GFPM by linking the change with forest product market. Whiteman (2000) manipulate d GFPM with Food and Agriculture Organization(FAO) predicted data for GDP and population in New Zealand to finish a prediction for forest product existing in GFPM with respect to demand, supply in New Zealand. Compared with the sub regional model such as S RTS and NTM II, GFPM is more suitable for the federal program analysis. C ompared with the general equilibrium model like CGE and agricultural forestry combination mo del POLYSIS, GFPM could conduct detailed analysis for the competition between traditional f orest product and bioenergy

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36 market. Furthermore, the GFPM also includes the variable s of forest area and forest stocks, which are generally accepted as the index measuring environmen tal sustainability Therefore, a completed introduction of GFPM is needed.

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37 CHAPTER 3 METHODOLOGY Model Instruction BCAP effects are modeled using GFPM Global Forest Product Model. GFPM is an economic model of global production, consumption and trade of forest products (Bu ongiorno et al. 2003). GFPM 201 0 has data and parameter s to produce and forecasts of forest resources and markets for 180 countries, and 14 forest product ( commodity) categories, from 200 6 to 20 60 (Buongiorno et al. 2010). F o r each product in each country in each year, consumption production, export, import, manufacturing cost price and value added could be calculated based on the input data for six variables and equations listed below. For dynamic changes, part of parameters in six variable s could be adjusted exogenously with the aim to simulate policy Cou ntry Classification GFPM includes 180 countries (Table A 2 ) and it could be divided into 7 regions: Africa, South America, North/Central America, Asia, Oceania, Europe and Former USSR. In this research, the United States is the focus since BCAP is the U.S. policy instead of an i nternational policy. Also, we concentrate on the North America, which might be influenced by the U.S. policy. Commodity Coverage There ar e 14 forestry commodities: fuel wood and charcoal i ndustrial round wood, other industrial round w ood, sawn wood veneer and plywood particleboard fiberboard mechanical wood pulp chemical and semi chemical wood pulp other fiber pulp waste

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38 paper newsprint printing and writing paper other paper and paperboard. The production transformation could be concluded as Figure 3 1 Figure 3 1 F orest product transformation in GFPM [ Source: Raunikar, R., Buongiorno, J., Turner, J.A., Zhu, S., 2010. Global outlook for wood and forests with the bioenergy demand implied by scenarios of the Intergovernmen tal Panel on Climate Change. Forest Policy and Economics 12, 48 56 ] In this research, three products in GFPM are picked up as subsidized targets : fuelwood, chips and in dustrial roundwood and three final products are targeted as the competitors being exami ned the BCAP influences on their productions: particleboard, woodpulp and paper. F uelwood and chips combined take half of subsidies from the matching payments for woody biomass ( Figure 1 4 and Figure 1 5 ). Therefore, these two products are the subsidized p r oducts for the matching payments, which aim to deduce the costs of collecting, harvesting, storage and transportation of woody biomass We transform these payments to a decrease in manufacturing cost s We will introduce how to adjust

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39 the parameters in GFP M for these two products i n the next parts Regard chips since it is not listed separately in GFPM, we classify it into the industrial roundwood, which is also fittin g in the definition set by FAO: the industrial roundwood included saw logs or veneer logs pulpwood, other industrial roundwood and, also chips and particles and wood residues The final product, p articleboard is the competitor for raw materials in the matching payments since it greatly depends o n the chip A change in manufacturing cost of c hips will influence the production of par ticleboard. In the establishment payments and the annual payments industrial roundwood is pick ed up to receive the subsidies. The change in industrial roundwood is from the extra plantation of short rotation wood c rops ( SRWC) In the United States, SRWC are regarded as the promising energy crops to meet future demand fo r bioenergy with its quick growing and high yield advantages. Rotation lengths for SRWC range from about 6 to 12 years, although they can be shorter (3 years, e.g., Adegbidi et al. 2001) if the material is sold for bioenergy feedstock or longer (up to 15 years, e.g. Stanton et al., 2002) i f sold for saw n timber As we see from the last citation SRWC could be used to produce not only bioenergy but al so saw n timber. Besides, woodpulp and paper s production also highly depend on SRWC. Therefore, if BCAP subsidies are attributed to SRWC, in another word, to industrial roundwood in GFPM there must have a change in production s of woodpulp and paper since, industrial roundwood is the main raw material to produce other forest final products ( Figure 3 1) We link the establishment payments and the annual payments to the price elasticity for industrial roundwood in GFPM so as to calculate the supply expand rate We will introduce the parameters in details in the next section and Chapter 5.

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40 Six Exogenous Variables Primary Product Suppl y In GFPM, supply was divided into two pa rts: supply for primary product and recycled product and supply for end product and inter mediate product. The former is represented in econometric equation which could be adjusted exogenously and the latter is presented in input output (I O) coefficient which was calculated based on previous studies and research Generally, the change in su pply for primary product and recycled product is determined by price, forest resource inventory and other variables influencing the sup ply (Binkely and Dykstra 1987). We are able to express it in Cobb Douglas productions function which is static equation for each product in one year (Buongiorno et al., 2003 ) : [ 3 1 ] Where : i j = country, k = product = price elasticity of supply. For the dynamic change, S* depend s on last p and on exogenous or endogenous supply shifters ( Equation 3 2) which could be adjusted based on the policy In the base year, S* is equal to the base year supply, and is equal to the observed base year price Shifts of supply: t he wood supply (fuel wood, industrial round wood, or other industrial round wood) can be shifted exogenously [ 3 2 ]

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41 Where: = adjustable supply change rate, = periodic rate of c hange of GDP The variable driving supply change is which is adjust abl e based on policy requirements (Buongiorno et al., 2003 ) Total wood drain from the forest: [ 3 3 ] Where: r = industrial roundwood, n = other industrial roundwood, f = fuelwood, from the forest and harvest (Buongiorno et al., 2003 ) End Product Demand In GFPM, demand also was divide d into 2 parts: demand for end product intermediate product and recycled product. The former is presented by the econometric equation and the latter is expressed by an I O coefficient. Generally speaking, demand for each end product is decided by real GDP and price of that product (Buongiorno and Chang 1986 ). W e transformed it into the equation which is the static equation for each product in one year : [ 3 4 ] 1 rice, and For dynamic change, demand, and the growth of GDP in the country (E quation 3 5) which is adjustable based on the policy In the base year, D is equal to the observed base year consumpti on, and is equal to the observed base year price

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42 Shifts of Demand : [ 3 5 ] Where = GDP periodic growth rate, = elasticity with respect to GDP and =periodic trend As the changeable rate could be adjusted exogenously The parameters driving the demand change is f rom GDP with the assumption that higher GDP growth will lead to a higher consumption of forest product (Buongiorno et al., 2003). Manufacture Capacity In this part, manufacture is divided into 2 parts: I O coefficient and manufacture cost. GFPM simulates the process of transforming raw materials into final product and i ntermediate produc t (Buongior no 2003). This proces s is represented by I O coefficient ( Table A 6 ) Each product in each country is expressed by one matrix and reflects technology level. Using data from 1992 to 2006 I O coefficients are estimated by minimizing the deviation of calcul ated from observed production for all products given a priori bounds on the I O coefficients. The manufacturing cost is the marginal cost of the inputs not recognized explicitly by the model (labor, energy, capital, etc.) We could express it in the stati c equation for each product in one year: [ 3 6 ] Where: m* = current manufacturing cost, s= elasticity of manufacturing cost with respect to output and Y=the amount of output For dynamic change, m* depend s on last peri ( E quation 3 7) and on the exogenous rate of change of

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43 manufacturing cost. In the base year, m* is equal to the observed base year manufacturing cost and is equal to the observed base year quantity manufactur ed. The manufacturing cost function shifts exogenously ov er time: [ 3 7] Where = the exogenous change rate in manufacturing cost I n this research, forest resources, recycle and transportation we re not closely linked to the research aims. T here is only a brief introduction for these three variables. Forest Resource This section contains data for forest area, forest resource stock and GDP per capita which are related to production, consumption and other parts closely. Recycle The wastepaper recovery rate is the ratio of wastepaper production in the current recycled policy in each country. The change in wastepaper r ecycle rate is projected by GFPM (Buongiorno et al., 2003). Transport This part includes: quantity of international trade, trade tariff (export and import tariff), freight cost and trade inertia. Among them, we need to explain freight cost and trade inerti a. Regarding freight cost, generally, we could obtain it from the difference between world export and import unit value from product. I t keeps constant in the projection period. Trade inertia plays a restriction condition in the model. Trade (export and im port) could not exceed its lower bound and upper bound). The transport cost per unit of volume for commodity k from country i to country j is given by :

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44 [ 3 8 ] Where: c*=current transport co nd T =elasticity of transport transport cost, and on the exogenous chang es of freight rates and taxes (Buongiorno et al., 2003). In the base year, c* is computed as: [ 3 9 ] Where: c = transport cost per un it of volume, f = freight cost per unit of volume, =export tax, = import ad valorem tariff, and is equal to the observed base year world export price (Buongiorno et al., 2003). Objective Function The objective for the model i s to maximize welfare which means to maximize consumer surplus and producer surplus which means the valued of end product minus the cost of raw material, the cost of transforming raw materials into the end product and cost of transport. We could specify the objective function as: [ 3 10 ] Where : z= consumer surplus and produce r surplus i j =country, k=product, p=price in US dollar of the constant value in the given year, Y= production quantity, m=manufacture cost efficient, c=transport cost and t = transport quantity (Buongiorno et al., 2003).

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45 The first term could be explained as the consumer surplus which is the area under the demand curve and the last three terms could be explained as producer surplus which is the area under supply curve. Constraint Function The constraint condition could be summarized by this equation: [ 3 11 ] Where: T = import /export S =domestic supply, Y=manufacture qu antity and D= domestic demand. The subscripts have the same meaning with objective function. The coefficient indicates how mu ch of product k is used to make product n in country i and it represents the technology level in that country. Constraint equation means domestic production with the consideration of import and manufacture quantity should equal to domestic demand plus expo rt and manufacture needed for other product s With objective equation and constraint condition, after inputting data for 6 parts discussed above, we could get equilibrium price, production, demand, trade and transport quantity (Buongiorno et al., 2003).

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46 CHAPTER 4 SCENARIO DESIGNED In order to explore the impacts of BCAP on forest products market, several scenarios are designed to simulate its effect. As described in methodology framework, the supply and manufacturing cost for forest product in GFPM could be adjusted exogenously. Four scenarios are designed to simulate the three payments in BCAP, which are the baseline scenario, matching payments scenario the establish payment scenario and the annual payments scenario Baseline Scenario In the baseline sce nario, there is no change in the exogenous variable. The change rate is as set in GFPM 2010 by the author The Matching P ayments Based on the rules in BCAP, the matching payments (CHST) are authorized at a rate of $1 fo r each $1 per dry ton paid by a quali fied biomass conversion facility for the payments are made directly to eligible landowners or farmers for 2 year period, beginning on the date the first payment is issue d to the eligible owners For research aim, we manually extend the eligible period to 15 years as of the establishment payments and the annual payments Scenario description: 100 percent deduct ion in manufacture cost of fuel wood and chips are simulated. In GFP M, the manufacture costs are costs not computed endogenously by the GFPM such as labor, capital, energy and other non wood or fiber input. Therefore, the matching payments should be transformed into a decre ase in manufacture cost for fuel wood and an in crease in that of particleboard which uses the

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47 chips as the raw materials The maximum amount in this payment is $45/ MT. We need to transform this amount as the exogenous change rate in manuf acturing cost required in GFPM. Firstly, u nify the units based on the requirements in FAO: using a factor of 6.0 to convert from weight (MT) to solid volume units (CUM) $45/ MT ---$45/6= $7.5/CUM Identify th e manufacture cost for fuelwood : in GFPM the manufacturing cost of fuelwood is zero in its database which might ignore the lost opportunity to do mo re productive or important work such as generating bioenergy Therefore, in this study we exert the base year market price for fuelwood as the manufacturing cost which is $50/CUM For the base year 2 006, fuel wood production is 44 .7 million CUM (FAO 2006) T he manufacturing cost is 50/CUM. We assume that the manufacturing cost did not change until the year 2010 the beginning of BCAP Based on the estimation made by Perlack (2005), the national annual supply for fue lwood is 51 millio n dry ton (the sum of currently used and potentially used) which is transferred into cubic meter is 8.5 million CUM. We assume that all the supply were eligible in the BCAP program to receive the matching payments Therefore, the manufact uring cost for t his new part is 50 7.5=42.5/CUM, and the matching payments for fuelwood are $63.75 million. T he new manufacturing cost, taking the consideration of the amount of fuelwood used to produce bioenergy is: {8,500,000*42.5 + ( 44,701,000 8,500,000 )*50}/44,701,000=48.57/ CUM The change rate for the fuelwood is : ( 48.57 50)/50= 0.0286 We also apply the same method to the woodchips. Since there is no separately list for woodchips and wood particles in the GFPM, we assume that there was an increase in the manufacturing cost for the particleboard which depends on the woodchips and wood particles intensely. Perlack (2005) e stimated that, in 2006, harvest residues amount to about 64 million dry tons of cut or killed materials left on harvest sit e We ass ume all this 64 million dry tons could be qualified as eligible material. Transform ing the amount into cubic meters is 10.6 million CUM. The total production of particleboard from the supply of chips is 11.16 million CUM calculated by the I O coefficient i n GFPM ( Table A 6 ) In 2006, the supply for particleboard was 21.98 million CUM. The matching payments for particleboard are 79.5 million. The manufacturing cost of particleboard is $108.5241/cum in base year.

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48 Therefore, the rate should be (10.6*(108.5241+ 7.5 ) + 11.38*108.5241)/21.98= 112.141 Therefore, there is an increase of manufacturing cost for particleboard with the rate of (112.141 108.5241)/108.5241= 0. 0 333 The E stablishment P ayments Based on the rules in BCAP: the establishment payments are authoriz ed to cover perennial crop (either woody or non woody) In order to simpli fy the simulation procedure, we assume that the establishment payments were based on the ave rage cost of the national average level. Scenario d escription: the aim of the establishment payments is to encourage the plantation of dedicated energy crops. Currently, in the United States, energy wood mainly means SRWC (White, 2010). Gen erally, willow, poplar, cottonwood, sycamore, and southern pine are widely planted across the nation to be used as SRWC. We do not specify the species but just assign the SRWC as the eligible materials to receive the establishment payments In additi on to the potential us e for biopower and bio fuel, SRWC can als o be used to produce woodpulp, paper and sawnwood (Stanton et al. 2002). Therefore, we classify the SRWC into the category of industrial roundwood in the GFPM, which extend its supply from the extra plantation of SR WC. Currently, in the United States, the average production cost for SWRC is 39 58 dollars/ acre (Tharakan et al., 2005; Eaton, 2007) and general yield for SRWC using contemporary planting stock under current management systems ranges from 5 to 12 dry tons per acre per year of woody material (Adegbidi et al. 2001 ; BRDB 2008 ; Volk et al. 2006).

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49 Assume the national average establishment cost was (39+58)/2=$48.5/ acre and the average harvest tons was (5+12)/2= $ 8.5 t on /acre. Therefore the production cost would be 48.5/8.5=$5.7059 / ton Transfer the production cost into CUM. I t is 5.7059/6=$0.951/CUM Get ting the subsidy from the government the new establishment cost is 0.951*0.25=$0.2377/CUM The establishment payments are ( 0.951 0.2377 )* (23.8/6)*15 = $ 42.44 milli on We assume that the ratio of establishment cost and price did not change. The ratio of establishment cost and price in the base year 2006 is 0.951/50=0.0190 2 Therefore, the newer price should be 0.2377/0.01902=$12.49737 The price change is $50 $12.497 37=$37.50263 The price elasticity is 0.64( Table A 4 ) The supply change should be 0.64* (37.50263/50)=0.48 The A nnual P ayments Based on the rules in BCAP the annual payments are intended to offset the lost opportunity costs associated with cultivating a biomass crop as opposed to a traditional crop. T he payments will be similar to CRP payments based on all or a percentage of a weighted average soil rental rate for cropland In order to calculate the revenue used for the annual payments the first step is to identify the area that is suitable for planting SRWC. The number of acres currently planted in SRWC is not definitively know n (Tuskan 1998). Ince (2009) estimated that less than 0.1 % of the privately owned agriculture an d forest land is currently dedi cated to SRWC popl ar plantations Zalesny (2008) citing the work of Eaton (2007) reports approximately 132,000 acres of hybrid poplar currently planted in the United States. Hybrid poplar is planted on approximately 50,000 ac res in the Pacific Northwest fo r pulpwood and saw n timber production (Stanton et al., 2002) and on about 6,000 ac res

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50 in Minnesota for both pulpwood and energy production. Short rotation woody crops have also been planted in the South (Tuskan 1998) and the Northeast (including willow for bioelectricity production) (Adegbidi et al. 2001). We adopt the estimation for eligible area from Alig (2000) with the consideration of budget, transformation from cropland to fo rest land and BCAP main function encourage the extra plantation for dedicat ed energy crop. Alig et al. ( 2000) pointed out that about 2.8 million acres of cropla nd was suitable for planting SRWC, mostly in the Corn Belt, Lake States, and South Central states. General yield figures for SRWC using contemporary planting stock under c urrent management systems range from 5 to 12 dry tons per acre per year of woody material (Adegbidi et al. 2001 ; BRDB 2008 ; Volk et al. 2006). Scenario d escription: based on the rule s in BCAP, the rate for the annual payments is closely attached to anot her program Cons ervative Reserve Program (CRP). Therefore, the rate we used is based on the CRP data got from USDA in 2009 (USDA, 2009) : Soil Rental Rate (national average ): $51.52/ acr e. Base year market price for fuel wood: $50/CUM Therefore, in GFPM, we ado pted the average harvest level mentio ned in the establishment payments For one year, the total yield of SRWC is 2.8 8.5= 23.8 /million dry tons. Total expense for the annual payments is 2.8 *51.52= 1 44 26 million dollars Average dry ton subsidy: 1 44 2 6 / 23.8 = 6 .06 /dry ton which is transformed in to cubic meters: 6.0 6 /6=$1.0 1 /CUM Here, since the annual payments were directly linked to the opportunity cost of fuel wood which was reflected in the market price, we assume the subsidy would influence its market pri ce The price change would be( based on the base year market price) 1.0 1 /50=0.02. The supply price elasticity is 0.64 ( Table A 4 ) Therefore the supply change rate would be 0.02*0.64=0.0128

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51 CHAPTER 5 RESULT For each scenario, a set of results are generated to examine the BCAP impacts on forest product s, forest area and welfare economics We pay attention to five products as stated in chapter 2. They are two main input raw materials: fuelwood and industrial rou ndw ood, which are subsidies by the matching paym ents and the establishment payments as well as the annual payments separately Besides, t here are also three closely related forest products: particleboard, woodpulp and paper which are picked up as the competitors to biomass market We will demonstrate p roduction change, price change and welfare economics change for each product from these three scenarios. The Matching P ayments Production and Price Change for Fuelwood Traditionally, North America wa s not the main producer of fuel wood compared with Africa and South Africa. Therefore, few changes happen in the North America ( Figure 6 1) Specifically, there has been no change in fuelwood production in the United States under the matching payments and Canada s production of fuelwood will decrease by 0.1% by the year 2025. While Africa seems to face a relatively modest increase, its percentage change rate is still around 0.1 % In summary, the change in the production of fuelwood under the matching payments is not significant. In BCAP the maximum cap of $45 f or the matching payments is not enough to influence the total production of fuelwood. Naturally, t he fuelwood price in the Unite d States did not change either.

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52 Production and Price Change for Industrial Roundwood and Particleboard Compared with fuelwood t he change in the industrial roundwood is relatively significant in the United States ( Figure 6 2). From 2010 to 202 5, there is a continuous decrease in the production of industrial roundwood. The decreasing rate is from 1.7% to 3.0%. Higher manufacturing cost for particleboard is the main reason for the red uction in industrial roundwood. The increase in manufacturing cost reduces the production of particleboard, which decreases the production of industrial roundwood indirectly. For the particleboard, we c ould s ee that the decreasing rate is even higher compared with industrial roundwood but the absolute amount is smaller ( Figure 6 2 and T able 6 1). The decreasing rate begins from 19.3% in 2015 to 44.2% in 2025 and the abs olute amount decreases from 5.41 million CUM to 14.68 million CUM. The matching payments will encourage more chips to be used as bioenergy instead of traditional particleboard Companying with the changes of production prices for industrial roundwood and particleboard also vary ( Figure 6 3 and T able 6 2). We find that the price of particleboard increase s faster in both percentage value and absolute value. Higher manufacturing cost is the dir ect drive to the raising price. T he increasing rate for manufacturing cost is only 3.3% annually but the particleboard price will increase 14% annually. We conclude that the matching payments will force the competition between particleboard and bioenergy based on the projection of particleboar s higher market price and lower production. While there is a decrease in the production of industrial roundwood, its price does not increase but decrease The main reason is the other products such as sawntimber and wood panel ( Figure 3 1) also decrease their productions. Therefore, the

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53 demand for industrial roundw ood is relatively lower. In addition, higher import for particleboard from foreign countries also lowers its dependence on industrial roundwood. As a consequence, the price for industrial roundwood did not increase For the rest of world, as the second lar gest producer of industrial roundwood, Europe experiences a slightly increase in industrial roundwood production with an annual average increasing rate of 0.2% and the absolute increasing amount is around 1.018 million CUM. Also, in the particleboard marke t, Europe also face s increasing production with the annual increasing rate of 1.9% and the absolute amount of 794 thousand CUM. Asia follows the Europe s step with an annual increasing rate of 2.6% and absolute amount of 556 thousand CUM. These two produce rs of particleboard grasp the chance to expand their exports to the United States, which directly drives the expansion of domestic particleboard production. For the world prices for industrial roundwood and particleboard, both of them experience the increa sing tendencies but not too much. The higher price for particleboard in the United States stimulates its world price to increase Welfare Economics Change Under the Matching Payments for the United States As mentioned in chapter 3 the objective function i n GFPM is to maximize the consumer surplus and producer surplus which also take the consideration of net trade change ( Equation 3 11) (Buongiorno et al. 2003). Naturally, the standard measuring welfare economics in the United States is the changes of con sumer surplus and producer surplus as well as net trade for the whole forestry industry From Figure 6 4, we could see there is an increase in the welfare economics in the forestry industry in the United States. The increasing rate expands from 1.1% to 2.5 % at the end of year 2025 The absolute value in 2015 is reaching to 678.5 million dollars. However, this value

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54 does not include government cost which is 716.25 million based on the calculation in chapter 3. Compared with total gains from the matching pay ments there is a net dead loss for the whole welfare economics. From the producer aspect, the winner is the particleboard Higher market price deduces a higher producer surplus. However, the increasing prices do not cover the loss from decreasing product ions of other forest products. Therefore, the whole producer surplus is negative. From the consumer surplus, the biggest loser is also from particleboard. Higher manufacturing cost drives the market price to rise, which decreases the consumer surplus. How e ver, by importing cheap particleboard, the loss might be lessened to consumers but the whole consumer surplus is still negative. From the net trade aspect, the winner is the importer of particleboard. Since its price is higher than the world price, particl eboard is highly imported from Europe and Asia. T he average importing rate is reaching to 120%. However, for the rest of forest products, the net trade value declines. The Establishment Payments Production and Price Change for Fuelwood Under this scenario, we are able to see the fuelwood production experience s a sharp increase in the United States (Figure 6 5). From the beginning of BCAP, the fuelwood production increases with a rapid rate and at the end of the year 2025 the rate has reached to 15.4%. T h e absolute increase also reaches to 7.97 million CUM. Why the fuelwood production increases so fast under this scenario?

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55 Figure 6 1 T he change of fuelwood under the matching payments Figure 6 2 The production change s of industrial roundwood and particle Table 6 1 T he absolute change in production for ind ustrial roundwood in the United States under the matching payments Year 2010 2015 2020 2025 Total Average Industrial roundwood 0.0 7396 .3 11663.7 13014.5 32074.5 5345.8 Particleboard 0.0 5451.6 9818.0 14683.3 29952.9 4992.2 Unit: thousand CUM

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56 Figure 6 3 The percentage changes in prices of particleboard and industrial roundwood under the matching payments Table 6 2 T he absolute price change of particleboard and industrial roundwood under the matching payments Year 2010 2015 2020 2025 Total Average Industrial roundwood 0.0 2.1 3.1 3.4 8.6 1.4 Particleboard 0.0 35.4 35.0 35.0 105.4 17.6 Unit: US dollar In GFPM, the I O coefficient between industrial roundwood and fuelwood is 1 ( Table A 6 ) which means inputting one unit industrial roundwood will produce 1 unit fuelwood. The establishment payments attribute to the industrial roundwood and there is an increase in it s production. Naturally, the fuelwood production will rise as well. Compared with the increasing rate of industrial roundwood, the fuelwood increasing rate is not faster. Higher production does not bring a lower price for fuelwood. The c onsumption for fuelwood increases as well with almost the same rate

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57 Figure 6 4 The percentage change of welfare economics under the matching paymen ts Table 6 3 The a bsolute added value for the United States under the matching payments Year 2010 2015 2020 2025 Total Average Total value 0.0 678473.1 868596.3 1172949.3 2720018.6 544003.7 Unit: thousand dollar s Therefore, the price for fuelwood does not change too much with only an absolute amount of 0.1 dollars at the end of year 2025. North America also experien ces a similar tendency From the beginning of BCAP 2010, there is an inc rease in the production of fuel wood and the increase lasts until 2015 with a rate of 5.4% annually and then a further increase emerges from 2015 to 2025. The rate is reaching to 16% at the end of 2025. For the rest of the world, the change s in fuelwood production and price are still insignificant. Howe ver, as the main player in fuel wood production, Africa undergoes an absolute increase with the amount of 22.5 t housand CUM.

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58 Production an d Price Change for Industrial Roundwood, Woodpulp and Paper Under the establishment payments industrial roundwood was picked as the representative to receive subsidies W o odpulp and paper were targeted as the heir productions. From the Figure 6 6 and Table 6 4 we could conclude that all of industrial roundwood and woodpulp as well as paper increase sharply compared with the matching payments Industrial roundwood begins to expand its production from 2010 with a rapid rate of 142.3%, and then a relatively modest increasing rate of 49.4% is found since 2020. Woodpulp and paper also follows the increasing tendency with the rate s around 10% and 8%. Compared with the matching payments the establishment payments are larger and its effects on industrial roundwood production are more significant. However, we could find that, after experi ences a strong increa se, it will take a modest increase The reason is the price of industrial roundwood continues to fall ( Figure 6 7 ) Woodpulp s and paper s prices also follow the same decreasing tendency. Unlike fuelwood, these three products consumptions do not catch up their supplies. As a consequen ce the prices will decline In summary, the establishment payments could strongly simulate the supply of industrial roundwood to rise up but the prices will go through the decreasing tendency. Compared with woodpulp and paper, fewer fuelwood are transformed from industrial roundwood b ecause its price is still lower than those of woodpul p and paper. For the rest of the world, as the second largest pulpwood and paper producer, Europe will experience a strong decrease i n the production s of wood pulp and paper. The deduction rates are projected to be 2.8% and 0.9%. Another producer of

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59 woodp ulp and paper Canada will also face a decrease in its productions with the decreasing rates of 1.0% and 1.6% W elfare Economics Change Under the Establishment Payments in the United States From the Figure 6 8 we could find that there is an increase in the total welfare economics in the forestry industry in the United States. The increasing rate is 13 % from the beginning of BCAP. Taking into the consideration of government budget for the establishment payments 44.8 million dollars the total gain is far more than the government payments. However, we could also find that both producer surplus and consumer surplus decrease, while the net trade value increase rapidly. The increasing net trade is the main reason for the increase in the welfare economics. Fro m the producer aspect, the biggest loser is the industrial roundwood producer. Due to the establishment payments the price of industrial roundwood falls down too much, which directly decrease the producer surplus. The next two losers are woodpulp and pape r, whose prices fall down as well with the rate s of 17% and 3.8% From the consumer aspect, the biggest loser is from paper. Due to the lower price of paper, its ex port increase proportionally, Therefore, the extra benefit from the establishment payments is transferred to the foreign consumers and the domestic consumer surplus decrease. From the net trade aspect, the biggest winner is the paper exporter. The United State is originally the big country in exporting paper and woodpulp. Lower domestic price directly stimulate s the strong export for paper with an amazing rate of 92%

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60 Figure 6 5 T he percentage change of fuelwood production and consumption under the establishment payments Figure 6 6 T he percentage change in production of industrial roundwood, woodpulp and paper under the establishment payments Table 6 4 The absolute change in production of industrial roundwood, woodpulp and paper under the establishment payments Year 2010 2015 2020 2025 Total Average Industrial roundwood 0.0 612961.4 214328.7 214871.1 1042161.2 173693.5 Woodpulp 0.0 5698.7 9009.6 12389.1 27097.4 4516.2 Paper 0.0 5981.1 8436.3 10864.8 25282.2 4213.7 Unit: thousand CUM s /ton s

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61 Figure 6 7 The percentage change in price of industria l roundwood, woodpulp and paper under the establishment payments Table 6 5 T he absolute change in prices of industrial roundwood, woodpulp and paper under the establishment payments Year 2010 2015 2020 2025 Total Average Industrial roundwood 0.0 74.5 72.8 70.1 217.4 54.4 Woodpulp 0.0 391.3 372.4 346.0 1109.7 277.4 Paper 0.0 376.3 342.0 296.5 1014.8 203.0 Unit: US dollar Table 6 6 The absolute added value in the United States under the establishment payments Year 2010 2015 2020 2035 Total Average Value Added 0.0 5915848.0 5904760.7 6318487.6 18139096.2 3627819.2 Unit: thousand dollar s

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62 Figure 6 8 T h e percentage change of welfare economics in the United States under the establishment payments The A nnual P ayments P roduction and Price Change for Fuelwood For the change of fue l wood production with the annual payments the total percentage change is not significant. The absolute change for fuel wood in world m arket is decreasing around 2.2 t housand CUM, a relatively small change. In the Uni ted States, there is an annual increasing 0.1% of production for fuel wood until the ending projection while there is annual decrease 0.3% of fuel wood production in Canada. Therefore, the curve for North America is a re verse V shape ( Figure 6 9 ) Compared with the establishment payments the annual payments is not higher enough to encourage more industrial round wood to be transform ed to fuel wood. Also, al though the price for fuel wood is projected to increase to $55.6 per unit, it is still lower than woodpulp and paper, which are projected to undergo a decreasing tendency. Therefore, this low price of fuelwood is not enough to attract more dedicated energy crops from the traditional woodpulp and paper industry.

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63 Production and Price Change for Industrial Roundwood, Woodpulp and Paper From the Figure 6 10 and Table 6 7 we could find that all of industrial roundwood, woodpulp and paper will increase their productions under the annual payments However, we firstly find that th ere are decreases from the year 2010 to the ye ar 2015, and then an increase is followed by the year 2025 When we check the price change ( Figure 6 11 ), we find that the price change tendency is opposite to the production change. The reason is that the annu al payments unlike the establishment payments are issued annually, which means that the landowners or farmers could not get relatively large subsidy at the beginning of the BCAP and that it might not be enough to enhance the producer willingness to pla nt SRWC. However the cumulat ive effects will come into play at the end of BCAP with the increasing productions As a result, the production changes will witness an increase at the end of BCAP. F o r the rest of the world, Europe and Canada are projected to face the decr eases in the production of wood pulp and paper. Comparatively speaking, the negative impacts on those two countries are smaller than the establishment payments Europe will meet 0.2% of the decrease s in pulpwood and 0.1% in paper industry. C anada will not suffer the loss in pulpwood and undertake around 0.1% loss in paper. In summary, the changes caused by the annual payments for the rest of world are not significant. However, in the United States the subsidies for opportunity cost are inef fective at the initial time due to small amount but function well at the end of the program. W elfare Economics Change Under the Annual Payments in the United States From Figure 6 12 and Table 6 9 while there is an increase in the percentage change in the year 2020 and 2025 for the total welfare economics, the total absolute

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64 value will decrease which means tha t a loss is founded in the welfare economics. We could find enhanced trade value is the m ain reason driving the welfare economics to rise. Regarding domestic producer and consumer, both of them suffer the loss from the annual payments From the supply aspects, the biggest loser is the industrial roundwood producer. Due to the annual payments the price of industrial roundwood falls with an annual rate of 1.1% which directly decrease s the producer surplus. The next two losers are woodpu lp and paper, whose prices decline as well with the rates of 0.3 % and 0.1 %. From the consumer aspect, the biggest loser is pulpwood which undertake s around 0.5% of t he loss es caused by the annual payments Similar to the establishment payments most benefits from lower price brought by BCAP were transfer red t o foreign consumer via export From the trade aspect, the winners are still from woodpulp and paper exporter. J ust like the establishment payments, lower domestic prices enhance the competitiveness for these two products and speed up their exports. In summary, except the matching payments the establishment payments and the annual payments are effective in enhancin g the production of fuelwood which verifies the statement that establishment cost and annual revenue are the big two concerns Compared with the annual payments the establishment cost is more effective in raising willingness to plant energy crops. For t he matching payments, t he cap for $45/dry ton is not enough to decrease the manufacturing cost of fuelwood so as to boost the fuelwood production.

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65 Figure 6 9 T he producti on change of fuelwood under the annual payments Figure 6 10 The percenta ge change of industrial roundwood, woodpulp and paper under the annual payments Table 6 7 The absolute change in production of industrial roundwood, woodpulp and paper in the United States under the annual payments Year 2010 2015 2020 2025 Total Average Industrial roundwood 0.0 3185.2 306.7 7022.4 4143.9 1036.0 Woodpulp 0.0 819.6 87.9 1825.7 918.2 229.6 Paper 0.0 1673.7 219.2 1260.4 632.5 158.1 Unit: thousand CUM / ton

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66 Figure 6 1 1 The percentage change in prices of industrial roundwood, wo odpulp and paper under the annual payments Table 6 8 T he absolute change in prices of industrial roundwood, woodpulp and paper under the annual payments Year 2010 2015 2020 2025 Total Average Industrial roundwood 0.0 1.9 1.9 4.4 4.4 0.9 Woodpulp 0.0 9.2 9.0 20.7 20.5 4.1 Paper 0.0 6.3 5.6 15.5 14.8 3.0 Unit: US dollar Table 6 9 The absolute change in added value under the annual payments Year 2010 2015 2020 2025 Total Average Value Added 0.0 814347.5 37343.3 760473.8 16530.4 3306. 1 Unite: thousand dollars Figure 6 1 2 T he percentage change in welfare economics under the annual payments

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67 With res pect to competition between bio energy and traditional forest product, products such as particleboard which intensively used woodchip s and other residues suffer a lot in the matching payments due to a higher input price Products with higher market value such as paper and pulpwood do get an enhancement in production. F armers and landowners would like to sell the product to pulp and pap er industries instead of bio energy companies who will pay for less money for the raw materials For the welfare economics analysis we find that the matching payments and the establishment payments did increase the valued increases. However, the estimated valued did not include the considerations of government cost. When we take i t into calculation, the added valued become negative in the matching payments while the net gain in the establishment payments is still positive. For all of the payments, the dom e stic producers and consumers suffer the loss caused by the BCAP Lower prices for industrial roundwood woodpulp and paper directly reduce the profit for producers and increas e the profit for exporter which makes the exporter become the biggest winner in this program and decrease s the s benefits. Effects on Forest Area and Forest Stock The ch ange for forest area is little. As estimated by Perlack (2005), current exploration for woody biomass is far less than the potential storage in the f orest system. Therefore, these three payments with limited funding could not make the forest area change. However, forest stock from the establishment payments will decrease under the establishment payments with an annual rate of 3.7% For the matching pa yments and the annual payments few changes are found. From the analysis above, we find that, compared with the other two payments, the establishment payments would augment the

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68 supply of industrial roundwood and fuelwood. The basic raw materials are di rect ly extracted from forestry. Therefore the forest stock will decrease in the United States.

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69 CHAPTER 7 DISCUSSION AND CONCL USION Discussion BCAP will stimulate the production of fuel wood and industrial roundwood under the establishment payments and the annu al payments Besides, BCAP emphasizes the development of wood biomass market should be with a minimum cost for environment. Otherwise, for the whole forestry industry, BCAP might lead to a net loss for domestic producers and consumers surplus In this game the biggest winner is the exporters of woodpulp and paper However, there are some doubts emerge on the collapse of producer surplus and consumer surplus in the forestry industry. Most of them are concentrating on the ignorance of environmental benefit b rought by woody biomass such as reducing carbon dioxide emission. However, how to quantity the benefits are still a problem needed further exploration. In addition, one of the recorded impacts of BCAP is to create blue, white and green color jobs (BCAP Fac t Sheet, 2010). W ith a forestry partial equilibrium model, it is impossible in a general equilibrium framework. F rom these two aspects, the welfare economics estimated in this research is not completed. In GFPM, there is no fi nal product directly related to bio energy such as bio electricity or biodiesel. Therefore, the amount of subsidized products is based on previous research which might overestimate the amount of qualified materials in this program. A call to construct the b ioenergy part in GFPM is needed to further explore Furthermore, lack of examination of land transfer is another shortcoming for this research. In GFPM, there is no specific part related to land use. The land qualified in

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70 this program is estimated from th e Alig ( 2000), whic h might exaggerate the effect of BCAP on welfare economics. A detailed examination on land is needed Conclusion This study aims to examine the effects of Biomass Crop Assistances Program on traditional forest product market, forest stock forest area and the whole welfare economics. Three scenarios were designed to simulate the three payments in BCAP. One is with 100% subsidy on fuelwood and chips based on the regulation listed in BCAP: FSA will provide the matching payments at the rate of $1 for each $1 per dry ton paid by the qualified biomass conversion facility to the eligible material owner for delivery of eligible material that qualify for payment to the facility in an amount not to exceed $45 per dry ton. Alternately, the second sc enario is about the establishment payments : cover up to 75% of the actual or average cost (whichever is lower) of establishing an eligible perennial crop (either woody or non woody) pursuant to a BCAP contract. Comparatively, the third scenarios is designe d to simulate the annual payments that offset the lost opportunity costs associated with cultivating a biomass crop as opposed all or a percentage of: a weighted avera ge soil rental rate for cropland. The time period for the annual payments would be up to 5 years for annual and perennial non woody crops and up to 15 years for perennial woody crop s ( BCAP 2010). The main findings concern th e increasing production of fuel wood, industrial roundwood, particleboard, wood pulp and paper under the establishment payments and the annual payments Few changes were found in forest stock and forest area with prerequisite in BCAP to stimulate sustainable development of woody biomass.

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71 However, when examined the welfare economics in forestry sector, the competition between woody biomass and traditional forest product emerges as a problem. Except the establishment payments, t he traditional forest product market will experience a decline w hich i s outweighed the gains with the consideration of government cost. Exporters for woodpulp and paper are the biggest winners in this game, while domestic producers and consumers for industrial roundwood will embrace the loss. This study has shortcoming s that are a source for future work: the incomplete examination for this program, lack of studies for land, and the absence of constructing the final product for bio energy in GFPM

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72 APPENDIX PARAMETERS USED IN G FPM Table A 1 Commodity codes in GFPM Cod e Commodities Units 80 81 82 83 84 85 86 87 88 89 90 91 92 93 Fuelwood and charcoal Industrial roundwood Other industrial roundwood Sawnwood Veneer and p lywood Particleboard Fiberboard Mechanical wood pulp Chemical and semi chemical wood pulp Other fiber pulp Waste paper Newsprint Printing and writing paper Other paper and paperboard 10 3 m 3 10 3 m 3 10 3 m 3 10 3 m 3 10 3 m 3 10 3 m 3 10 3 m 3 10 3 t 10 3 t 10 3 t 10 3 t 10 3 t 10 3 t 10 3 t Source: Buongiorno, J., 2012. Using the Global Forest Products Model (GFPM version 2012). Staff paper series #74.

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73 Table A 2 Country codes in GFPM Code Country Code Country Code Country Code Country AFRICA N/C AMERICA ASIA EUROPE A0 A lgeria F0 Bahamas I5 Afghanistan N5 Albania A1 Angola F1 Barbados I6 Bahrain N6 Austria A2 Benin F2 Belize I7 Bangladesh N7 Belgium A3 Botswana F3 Canada I8 Bhutan N8 Bosnia and Herzegovina A4 Burkina Faso F4 Cayman Islands I9 Brunei Darussalam N9 Bulg aria A5 Burundi F5 Costa Rica J0 Cambodia O0 Croatia A6 Cameroon F6 Cuba J1 China O1 Czech Republic A7 Cape Verde F7 Dominica J2 Cyprus O2 Denmark A8 Central African Republic F8 Dominican Republic J3 Hong Kong O3 Finland A9 Chad F9 El Salvador J4 Indi a O4 France B0 Congo, Republic of G0 Guatemala J5 Indonesia O5 Germany B1 Cte d'Ivoire G1 Haiti J6 Iran, Islamic Rep of O6 Greece B2 Djibouti G2 Honduras J7 Iraq O7 Hungary B3 Egypt G3 Jamaica J8 Israel O8 Iceland B4 Equatorial Guinea G4 Martinique J 9 Japan O9 Ireland B5 Ethiopia G5 Mexico K0 Jordan P0 Italy B6 Gabon G6 Netherlands Antilles K1 Korea, Dem People's Rep P1 Macedonia, The Fmr Yug Rp B7 Gambia G7 Nicaragua K2 Korea, Republic of P2 Malta B8 Ghana G8 Panama K3 Kuwait P3 Netherlands B9 G uinea G9 Saint Vincent/Grenadines K4 Laos P4 Norway C0 Guinea Bissau H0 Trinidad and Tobago K5 Lebanon P5 Poland C1 Kenya H1 United States of America K6 Macau P6 Portugal C2 Lesotho SOUTH AMERICA K7 Malaysia P7 Romania C3 Liberia H2 Argentina K8 Mongo lia P8 Slovakia C4 Libyan Arab Jamahiriya H3 Bolivia K9 Myanmar P9 Slovenia C5 Madagascar H4 Brazil L0 Nepal Q0 Spain C6 Malawi H5 Chile L1 Oman Q1 Sweden

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74 Table A 2. Continued Code Country Code Country Code Country Code Country C7 Mali H6 Colombia L2 Pakistan Q2 Switzerland C8 Mauritania H7 Ecuador L3 Philippines Q3 United Kingdom C9 Mauritius H8 French Guiana L4 Qatar Q4 Serbia and Montenegro D0 Morocco H9 Guyana L5 Saudi Arabia FORMER USSR D1 Mozambique I0 Paraguay L6 Singapore Q5 Armenia D2 N iger I1 Peru L7 Sri Lanka Q6 Azerbaijan, Republic of D3 Nigeria I2 Suriname L8 Syrian Arab Republic Q7 Belarus D4 Runion I3 Uruguay L9 Thailand Q8 Estonia D5 Rwanda I4 Venezuela, Boliv Rep of M0 Turkey Q9 Georgia D6 Sao Tome and Principe M1 United A rab Emirates R0 Kazakhstan D7 Senegal M2 Viet Nam R1 Kyrgyzstan D8 Sierra Leone M3 Yemen R2 Latvia D9 Somalia OCEANIA R3 Lithuania E0 South Africa M4 Australia R4 Moldova, Republic of E1 Sudan M5 Cook Islands R5 Russian Federation E2 Swazi land M6 Fiji Islands R6 Tajikistan E3 Tanzania, United Rep of M7 French Polynesia R7 Turkmenistan E4 Togo M8 New Caledonia R8 Ukraine E5 T unisia M9 New Zealand R9 Uzbekistan E6 Uganda N0 Papua New Guinea E7 Congo, Dem Republic of N1 Samo a ZY Dummy Region E8 Zambia N2 Solomon Islands ZZ World E9 Zimbabwe N3 Tonga Source: Buongiorno, J., 2012. Using the Global Forest Products Model (GFPM version 2012). Staff paper series #74.

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75 Table A 3 GFPM demand t able for the United States in base year 2006 1 A B C D E F G h1 80 50.00 44740.000 0.10 0.22 0.00 h1 82 80 9040.000 0.05 0.58 0.00 h1 83 259.00 129157.000 0.10 0.22 1.00 h1 84 437.84 19552.000 0.29 0.41 1.00 h1 85 258.56 31303.000 0.29 0.54 1.00 h1 86 356.53 10063.000 0.4 6 0.35 1.00 h1 91 587.00 9621.000 0.25 0.58 1.00 h1 92 908.00 27523.000 0.37 0.45 1.00 h1 93 805 53176.000 0.23 0.43 1.00 Data source: FAO(Food and Agricultural Organization), 2006, http://faostat.fao.org/default.aspx?lang=en A: Region number (01 to 99, in ascending order) B: Commodity number (01 to 99, in ascending order within each region) C: Base period price in common currency (US dollars/unit) D: Base per iod quantity demanded at price ( thousand CUM or thousand ton) E: Price elasticity (<0, enter 0.00 for horizontal demand) F: Elasticity of demand with respect to the first shift variable (optional, enter 0.00 if omitted) G: Elasticity of demand with respect to the second shift variable (optional, enter 0.00 if omitted) 1

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76 Table A 4 GFPM supp ly table in the United States in base year 200 6 2 A B C D E F G h1 80 50 44701.000 0.64 1.00 0.00 h1 81 80 405393.000 0.64 1.00 0.00 h1 82 80 9040.000 0.64 1.00 0.00 h1 89 982 245.000 0.75 0.40 0.00 h1 90 123 44401.000 1.00 0.50 0.00 Data source: FAO ( Food and Agricultural Organization), 2006, http://faostat.fao.org/default.aspx?lang=en 2 A: Region number ( 01 to 99, in ascending order) B: Commodity number (01 to 99, in ascending order within each region) C: Base period price in common currency (US dollars/unit) D: Base per iod quantity demanded at price ( thousand CUM or thousand ton) E: Price elasticity (<0, enter 0.00 for horizontal demand) F: Elasticity of demand with respect to the first shift variable (optional, enter 0.00 if omitted) G: Elasticity of demand with respect to the second shift variable (optional, enter 0.00 if omitted) 2

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77 Table A 5 GFPM manufacturing cost table for the United States in base year of 2006 3 A B C D E F G h1 80 10 1 0.1000 0.000 0.01 h1 83 10 1 136.4729 92613.667 0.10 h1 84 10 1 236.4648 14180.000 0.10 h1 85 10 1 108.5241 21873.000 0.10 h1 86 10 1 229.1648 7540.000 0.10 h1 87 10 1 224.8572 4080.667 0.10 h1 88 10 1 255.0000 45820.667 0.10 h1 91 10 1 253.4447 4885.000 0.10 h1 92 10 1 474.6265 21081.667 0.10 h1 93 10 1 462.2305 57192.667 0.10 Data source: FAO ( Food and Agricultural Organization), 2006, http://faostat.fao.org/default.aspx?lang=en 3 A Region number (0 1 to 99, in ascending order) B Commodity (primary) number (01 to 99, in ascending order within each region) C Process number(01 to 99, in ascending order within each commodity) D Input mix number(1 to 9, in ascending order with each process) E Net manufacturing cost in common currency ( US dollars)) F Base period manufactured quantity ( thousand CUM or thousand ton) G Output elasticity of manufacturing cost, >=0, enter 0.00 for constant manufacturing cost

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78 Table A 6 I O coefficient in GFPM for the United States 4 A B C D F G h1 81 83 10 1 1.5218988 h1 81 84 10 1 2.5128 571 h1 81 85 10 1 1.8557996 h1 81 86 10 1 1.5878571 h1 81 87 10 1 2.1476190 h1 81 88 10 1 3.5000000 h1 87 91 10 1 0.0434920 h1 88 91 10 1 0.4757937 h1 89 91 10 1 0.0000000 h1 90 91 10 1 0.5007143 h1 87 92 10 1 0.1477672 h1 88 92 10 1 0.6695238 h 1 89 92 10 1 0.0072890 h1 90 92 10 1 0.0768254 h1 87 93 10 1 0.0135714 h1 88 93 10 1 0.5254861 h1 89 93 10 1 0.0000000 h1 90 93 10 1 0.4579985 Data source: FAO ( Food and Agricultural Organization), 2006, http://faostat.fao.org/default.aspx?lang=en 4 A Region number (01 to 99, in ascending order) B Input commodity number (01 to 99, in ascending order within each output commodity) C Output commodity number (01 to 99, in ascending order within each region) D Process number(01 to 99, in ascending order within each commodity) F Input mix n umber(1 to 9, in ascending order with each process) G Amount of input commodity per unit of output commodity

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79 L IST OF REFERENCES Abt, R.C., Abt, K.L., Cubbage, F.W., Henderson, J.D., 2010. Effect of policy based bioenergy demand on southern timber markets: A case study of North Carolina. Biomass Bioenergy 34, 1679 1686 Adegbidi, H.G., Volk, T.A., White, E.H., Abra hamson, L.P., Briggs, R.D., Bickelhaupt, D.H., 2001. Biomass and nutrient removal by willow clones in experimental bioenergy plantations in New York State. Biomass Bioenergy 20, 399 411. Aguilar, F.X., Saunders, A.M., 2011. Attitudes toward Policy Instrume nts Promoting Wood To Energy Initiatives in the United States. South. J. Appl. For. 35, 73 79. Aguilar, F.X., Song, N., Shifley, S., 2011. Review of consumption trends and public policies promoting woody biomass as an energy feedstock in the US. Biomass Bi oenergy. Aguilar, F.X., Saunders, A., 2010. Policy instruments promoting wood to energy uses in the continental United States. J. For. 108, 132 140. Alavalapati, J., Hodges, A., Lal, P., Dwivedi, P., Rahmani, M., Kaufer, L., Matta, J., Susaeta, A., Kukrety S., Stephens, T., 2009. Bioenergy roadmap for southern United States. Southeast Agriculture and Forestry Energy Resources Alliance (SAFER), Southern Growth Policies Board, North Carolina 130. Alig, R.J., Adams, D.M., McCarl, B.A., Ince, P.J., 2000. Econo mic potential of short rotation woody crops on agricultural land for pulp fiber production in the United States. For. Prod. J. 50, 67 74. Beach, R.H., McCarl, B.A., 2010. US Agricultural and forestry impacts of the energy independence and security act: FAS OM results and model description. Research Triang le Park, NC: RTI International. Becker, D.R., Lee, C., 2008. State woody biomass utilization policies. University of Minnesota, Dept.of Forest Resources, St.Paul, MN.Staff Paper 199, 183. Becker, D.R., Mosel ey, C., Lee, C., 2011. A supply chain analysis framework for assessing state level forest biomass utilization policies in the United States. Biomass Bioenergy 35, 1429 1439. Becker, D.R., Larson, D., Lowell, E.C., 2009. Financial considerations of policy o ptions to enhance biomass utilization for reducing wildfire hazards. Forest Policy and Economics 11, 628 635. BCAP 2011. The biomass crop assistance program (BCAP) Final R ule Provision, http://www.fsa.usda.gov/FSA/newsReleases?area=newsroom%26subject=landing %26topic=pfs%26newstype=prfactsheet%26type=detail%26item=pf_20101 021_co nsv_en_bcap.html

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80 Binkley, C., 1987. Economic models of timber supply. The global forest sector: An analytical perspective, 109 136. BRDB ( Biomass Research and Development Board ) 2008 Increasing feedstock production for biofuels: economic drivers, environmental implications, and the role of research. http://www.brdisolutions.com/Site%20Docs/Increasing%20Feedstock_revised.pdf. (last accessed June 3 0,2012) Blouin, J., Krull, L., 2009. Bringing it home: A study of the incentives surrounding the repatriation of foreign earnings under the American Jobs Creation Act of 2004. Journal of Accounting Research 47, 1027 1059. Buchanan, G., 2010. Increasing Fe edstock Production for Biofuels: Economic Drivers, Environmental Implications, and the Role of Research, DIANE Publishing, Buongiorno, J., 2003. The global forest products model: structure, estimation, and applications, Academic Press,. Buongiorno, J., 2 012. Using the Global Forest Products Model (GFPM version 2012). Staff paper series #74 Buongiorno, J., Chang, H.S., 1986. Effect of the energy crisis on the elasticities of demand for forest products in OECD countries. Can.J.For.Res 16, 968 974. Buongiorn o, J., Gilless, J., 1984. A model of international trade of forest products, with an application to newsprint. J. World Forest Resour. Manage. 1, 65 80. Buongiorno, J., Gilless, J.K., 1983. Concepts used in a regionalized model of pulp and paper production and trade. Forest sector models.Berkhamsted, England: AB Academic Publishers, 57 90. Buongiorno, J., Raunikar, R., Zhu, S., 2011. Consequences of increasing bioenergy demand on wood and forests: An application of the Global Forest Products Model. J. For. Econ. 17, 214 229. Congress, U., 2008. Food, Conservation, and Energy Act of 2008. Washington, DC: Public Law, 110 234. Cook, J., Beyea, J., 2000. Bioenergy in the United States: progress and possibilities. Biomass Bioenergy 18, 441 455. DSIRE (Database of State Incentives for Renewable Energy and Efficiency), 2009. Financial incentives for renewable energy http://www.dsireusa.org/summarytables/finre.cfm; Duffield, J.A., Collins, K., 2006. Evolution of renewable energy policy.

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81 EIA ( U.S. Energy Information Administration ) 2010 a Monthly Energy Review Table 12.2 12.5, http://c1cleantechnicacom.wpengine.netdnacdn.com/files/2012/06/energy_related _carbon_dioxide_emissions_sector large.jpg EIA ( U.S. Energy Information Administration ) 2010 b Annual Energy Review 2010 http://www.eia.gov/totalenergy/data /annual/pecss_diagram.cfm. EIA ( U.S. Energy Information Administration ) 2010 c Renewable Energy Consumption and Electricity Preliminary Statistics 2009, ftp://ftp.eia.doe.gov/renewables/pretrend s09.pdf EIA ( U.S. Energy Information Administration ) 2012. Annual Energy Outlook 20 12, http://205.254.135.7/forecasts/aeo/pdf/0383(2012).pdf EPA ( U.S. Environmental Protecti on Agency ) 2009. Renewable Portfolio Standards: An Effective Policy to Support Clean Energy Supply. 2009 http://www.epa.gov/chp/state policy/renewable_fs.html Food and Agriculture Organ ization of the United Nations, 2006. FAOSTA ,http://faostat.fao.org/default.aspx?lang=en. F AO( Food and Agriculture Organization of the United Nations ) 2009. Wood energy http://www.fao.org/f orestry/energy/en/; Guo, Z., Sun, C., Grebner, D., 2007. Utilization of forest derived biomass for energy production in the USA: status, challenges, and public policies. International Forestry Review 9, 748 758. Harris, W.L., Lubben, B., Novak, J.L., Sa nders, L.D., 2008. The Food, Conservation, and Energy Act of 2008 Summary and Possible Consequences. Heinimo, J., Junginger, M., 2009. Production and trading of biomass for energy An overview of the global status. Biomass Bioenerg. 33, 1310 1320. Hillrin g, B., 2006. World trade in forest products and wood fuel. Biomass Bioenerg. 30, 815 825. Hodges, A.W., Stevens, T.J., Rahmani, M. 2010. Economic Impacts of Expanded Woody Biomass Utilization on the Bioenergy and Forest Products Industries in Florida, Un iversity of Florida, Institute of Food and Agricultural Sciences, Food and Resource Economics Dept., Hodges, A.W., Rahmani, M., 2011. Fuel Sources and Carbon Dioxide Emissions by Electric Power Plants in the United States.

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82 Ince, P.J., Kramp, A.D., Skog, K.E., Yoo, D., Sample, V.A., 2011. Modeling future US forest sector market and trade impacts of expansion in wood energy consumption. Journal of Forest Economics. Ince, P.J., 1998. Long range outlook for US paper and paperboard demand, technology, and fibe r supply demand equilibria. 330 343. Joseph Buongiorno, Shushuai Zhu, Dali Zhang, James Turner, David Tomberlin, 2010. The Global Forest Product, http://forest.wisc.edu/staticsites/buongiorno/book/GFPM.html. 2010. Jake Eaton, Opportunities for Poplar Bio energy Farms in North America, http://www.shortrotationcrops.org/pdfs/eaton_jake.pdf 2007. Kroeger, T., 2007. Economic Impacts of Live Wild Animal Imports in the United States Economic impacts of live wild animal imports in the United States. Larson, E.D., UN Energy. 2007. Sustainable bioenergy: A framework for decision makers, UN Energy, Meghan Gordon, IEA says biofuels can displace 27% of transportation fuels by 2050 http://www.platts.com/RSSFeedDetailedNews/RSSFeed/Oil/6017103 2011. Nazzaro, R.M. 2005. Natural resources: federal agencies are engaged in various efforts to promote the utilization of woody biomass, but significant obstacles to its use remain, DIANE Publishing, Nerurkar, N., Library of Congress. Congressional Research Service, 2011. US Oil Imports: Context and Considerations. Oel, P., Hoekstra, A., 2010. The green a nd blue water footprint of paper products: Methodological considerations and quantification. Peter J. Ince, Scientific uncertainty about bioenergy from a forestry perspective, http://webcache.googleusercontent.com/search?q=cache:EcLqMGufz cAJ:foragforum.rti.org/documents/2.3_ 4_Ince%2520slides Final%2520 %2520GHG%2520Modeling%2520 %2520Shepherdstown%25202009.ppt+&cd=1&hl=en&ct=clnk&gl=us 2009. Pimentel, D., Patzek, T.W., 2005. Ethanol production using corn, switchgrass, and wood; biodiesel production using soybean and sunflow er. Natural resources research 14, 65 76. Raunikar, R., Buongiorno, J., Turner, J.A., Zhu, S., 2010. Global outlook for wood and forests with the bioenergy demand implied by scenarios of the Intergovernmental Panel on Climate Change. Forest Policy and Econ omics 12, 48 56.

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83 Robert D. Perlack, Lynn L. Wright, Anthony F. Turhollow, Robin L. Graham, Bryce J. Stokes, Donald C. Erbach, 2005. Biomass As Feedstock for A Bioenergy And Bioproducts Industry: The Technical Feasibility of A Billion Ton Annual Supply. Ron ald S. Zalesny Jr., Woody Energy Crop Production, http://www.corrim.org/presentations/video/2008/CORRIM_Workshop/p df/06_Zalesny.pdf 2008. Rossi, F .J., Carter, D.R., Abt, R.C. 2010. Woody Biomass for Electricity Generation in Florida: Bioeconomic Impacts Under a Proposed Renewable Portfolio Standard (RPS) Mandate: Final Report, Florida Dept. of Agri culture and Consumer Services, Rummer, B., Preste mon, J., May, D., Miles, P., Vissage, J., McRoberts, R., Liknes, G., Shepperd, W.D., Ferguson, D., Elliot, W., 2003. A strategic assessment of forest biomass and fuel reduction treatments in western states. RMRS GTR 149. Sedjo, R.A., 2010. The Biomass Crop Assistance Program (BCAP): some implications for the forest industry. Discussion Paper Resources for the Future (RFF), 15. Smith, W.B. 2004. Forest resources of the United States, 2002, US Department of Agriculture, Forest Service, North Central Resea rch Station St. Paul, MN, Solar, D., 2009. Incentives for energy efficiency. Stanton, B., Eaton, J., Johnson, J., Rice, D., Schuette, B., Moser, B., 2002. Hybrid poplar in the Pacific Northwest: the effects of market driven management. J. For. 100, 28 33 Stubbs, M., 2010. Biomass crop assistance program (BCAP): Status and issues. Tharakan, P.J., Volk, T.A., Lindsey, C.A., Abrahamson, L.P., White, E.H., 2005. Evaluating the impact of three incentive programs on the economics of cofiring willow biomass wit h coal in New York State. Energy Policy 33, 337 347. use of forest based bioenergy in Norway -A spatial partial equilibrium analysis. Energy Policy 35, 5980 5990. Tuskan, G., 1998. Short rotation woody crop supply systems in the United States: what do we know and what do we need to know? Biomass Bioenergy 14, 307 315. USDA (U.S. Department of Agriculture), 2009. CRP enrollment as of September 2009 and October 2009 rental payment. http://www.fsa.usda.gov/Internet/FSA_File/apportstate.pdf USDA (U.S. Department of Agriculture) 2010. Report of BCAP CHST payments by biomass type. http://www.fsa.usda.gov/Internet/FSA_File/bcap_chst_component_report.pdf

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84 USDA (U.S. Department of Agriculture), 2010. Summary Report of BCAP CHST payments http://www.fsa.usda.gov/FSA/webapp?area=home&subject=ener&topic=bcap USDE( U.S. Depar tment of Energy ), 2011. U.S. Billion Ton Update: Biomass Supply for a Bioenergy and Bioproducts Industry. R.D. Perlack and B.J. Stokes (Leads), ORNL/TM 2011/224. Oak Ridge National Laboratory, Oak Ridge, TN. 227p. Volk, T., Abrahamson, L., Nowak, C., Smart L., Tharakan, P., White, E., 2006. The development of short rotation willow in the northeastern United States for bioenergy and bioproducts, agroforestry and phytoremediation. Biomass Bioenergy 30, 715 727. White, E.M. 2010. Woody biomass for bioenergy and biofuels in the United States: a briefing paper, DIANE Publishing, Whiteman, A., Brown, C., 2000. Modelling global forest products supply and demand: recent results from FAO and their potential implications for New Zealand. New Zealand Journal of Fo restry 44, 6 9. Wu, Y., 2012. An Integrated Multi Feedstock Modeling Approach towards Assessing Forest Resource Sustainability. Zhu, S., Buongiorno, J., Brooks, D., 2001. Effects of accelerated tariff liberalization on the forest products sector: a global modeling approach. Forest Policy Econ. 2, 57 78 Zhu, S., Buongiorno, J., Tomberlin, D., Food and Agriculture Organization of the United Nations. 1998. Global forest products consumption, production, trade and prices: global forest products model projecti ons to 2010, Food and Agriculture Organization of the United Nations,

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85 BIOGRAPHICAL SKETCH Wei Jiang is a young lady born and raised in Hebei the northern province of China She did her primary, secondary and undergraduate studies in China She holds a B achelor of Economics which was obtained from the Beijing Forestry University in 200 6 Based on her background, she decided to pursue a Master of Science in Forest Resources and Conservation with a concentration on woody biomass economics.