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1 ANALYSIS OF PRICING DECISION OF FLORIDA WATER UTILITIES: COST, INST I UTIONAL AND DEMAND FACTORS By SHIRISH RAJBHANDARY A THESIS PRESENTED TO THE GRADUATE SCHOOL OF THE UNIVERSITY OF FLORIDA IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF SCIENCE UNIVERSITY OF FLORIDA 2010
2 2010 Shirish Rajbhandary
3 To my mom and d ad
4 ACKNOWLEDGMENTS It would not have been possible to write complete this thesis without the help and support from a lot of people. First and foremost, I would like to thank my advisor, Dr. Tatiana Borisova for providing me guidance through every aspect of this research. I a m also greatly indebted to my other committee members, Dr. Chuck Moss and Dr. Ronald Randles, who have offered me invaluable suggestions to my thesis. I would also like express my g ratitude to my peers in the Food and Resource Economics graduate program fo r providing a stimulating and fun learning environment. Finally, I would like to thank my parents Deepak and Rita, for being supportive in every decision I have made in my life. Without their encouragement, support and love, I would not have made it this f ar.
5 TABLE OF CONTENTS page ACKNOWLEDGMENTS ................................ ................................ ................................ .. 4 LIST OF TABLES ................................ ................................ ................................ ............ 8 LIST OF FIGURES ................................ ................................ ................................ .......... 9 LIST OF ABBREVIATIONS ................................ ................................ ........................... 11 ABSTRACT ................................ ................................ ................................ ................... 12 CHAPTER 1 INTRODUCTION ................................ ................................ ................................ .... 14 1.1 Motivation ................................ ................................ ................................ ......... 14 1.2 Water Uses in Florida ................................ ................................ ....................... 15 1.3 Water Markets ................................ ................................ ................................ .. 16 1.3.1 Public Goods ................................ ................................ ........................... 17 1.3.2 Natural Monopoly and Public Water Supply ................................ ............ 17 1.3.2 Externalities ................................ ................................ ............................. 18 1.3.3 Other Arguments Against Water Markets ................................ ................ 19 1.3.4 Implications ................................ ................................ ............................. 19 1.4 Water Regulation in Florida ................................ ................................ .............. 20 1.5 Water Demand and Supply Management Strategies ................................ ........ 22 1.6 Outline of the Chapters ................................ ................................ ..................... 23 2 LITERATURE REVIEW ................................ ................................ .......................... 25 2.1 Overview of Rate Structures ................................ ................................ ............. 25 2.2 Objectives of Rate Setting ................................ ................................ ................ 26 2.2.1 Financially Sustainability ................................ ................................ ......... 27 2.2.2 Fairness and Equity ................................ ................................ ................. 27 2. 2.3 Economic Efficiency ................................ ................................ ................ 28 2.2.4 Water Conservation ................................ ................................ ................. 29 2.2.5 Ease of Implementation and Administering ................................ ............. 30 2.3 Advantages and Disadvantages of the Common Rate Structures .................... 30 2.4 Rate Structures that do not Send a Conservation Price Signal ......................... 31 2.5 Conservation Rate Structures ................................ ................................ ........... 32 2.5.1 Uniform Block Rate Structure ................................ ................................ .. 32 2.5.2 Inclining Block Rate Structure ................................ ................................ 33 2.5.3 Seasonal Rate Structure ................................ ................................ ......... 34 2.6 Residential Water Demand and Effectiveness of Price Policy .......................... 34 2.7 Measuring Determinants of Water Rates and Rate Structure ........................... 37 2.8 Objective and Hypotheses of Thesis ................................ ................................ 48
6 3 DESCRIPTIVE STATISTICS ................................ ................................ .................. 52 3.1 Overview ................................ ................................ ................................ ........... 52 3.2 The Sample of Florida Drinking Water Systems ................................ ............... 52 3.3 Survey Instrument Development and Pre test ................................ .................. 53 3.4 Survey Distribution ................................ ................................ ............................ 54 3.5 Summary of Results ................................ ................................ .......................... 56 3.5.1 Water System Characteristics ................................ ................................ 56 3.5.2 Changes in Water Delivery ................................ ................................ ...... 57 2.5.3 Water Rates ................................ ................................ ............................ 60 3.5.4 Non Price Conservation Strategies ................................ ......................... 62 3.5.5 Information about Price and Non Price Conservation Programs ............. 63 Price Conservation Strategies .... 63 3.5.7 Perceived Barriers for Implementation of Conservation Programs .......... 65 4 MODEL SPECIFICATION ................................ ................................ ....................... 83 4.1 Overview ................................ ................................ ................................ ........... 83 4.2 Hypothesized Model 4 1 ................................ ................................ ................... 83 4.2.1 Dependent Variable ................................ ................................ ................. 84 4.2. 2 Independent Variables ................................ ................................ ............. 8 5 126.96.36.199 Supply factors that drive up cost of water systems ........................ 85 188.8.131.52 Institutional factors that influence water rates ................................ 87 4.2.3 Number of Observations ................................ ................................ .......... 90 4.3 Hypothesized Model 4 2 ................................ ................................ ................... 90 4. 3.1 Selection of Demand Proxies for Model 4 2 ................................ ............ 92 4.3.2 Number of Observations ................................ ................................ .......... 93 4.4 Summary of Definition of Variables and Descriptive Statistics .......................... 93 4.5 Data Sources ................................ ................................ ................................ ... 93 5 EMPIRICAL RESULTS ................................ ................................ ........................... 99 5.1 Over view ................................ ................................ ................................ ........... 99 5.2 Model 4 1: Cost and Institutional Factors ................................ .......................... 99 5.3 Model 4 2: Cost, Institutional, and Demand Factors ................................ ....... 103 5.4 OLS Assumptions ................................ ................................ ........................... 104 5.4.1 Tests for Normality of Residuals ................................ ............................ 104 5.4.2 Tests for Heteroskedasticity ................................ ................................ .. 104 5.4.4 Summary of Assumptions ................................ ................................ ...... 106 6 DISCUSSION AND CONCLUSIONS ................................ ................................ .... 111 6.1 Overview ................................ ................................ ................................ ......... 111 6.2 Discussion ................................ ................................ ................................ ...... 111 6.3 Study Limitations and Recommendations for further research ....................... 113
7 APPENDIX A CHARACTERISTICS OF FLORIDA DRINKING WATER SYSTEMS ................... 117 B WATER MANAGEMENT DISTRICT INFORMATION ................................ ........... 119 LIST OF REFERENCES ................................ ................................ ............................. 121 BIOGRAPHICAL SKETCH ................................ ................................ .......................... 125
8 LIST OF TABLES Table page 3 1 Sample of community water examined in this project ................................ ......... 66 3 2 Water system characteristics ................................ ................................ .............. 67 3 3 Number of gallons of metered water delivered per day during non drought periods ................................ ................................ ................................ ................ 68 3 4 Percen t of water delivered to customer classes ................................ ................. 68 3 5 Percentage of utilities planning to increase delivery capacity in the next five years ................................ ................................ ................................ ................... 68 3 6 Analysis of blocks for systems with inclining block rates ................................ .... 68 3 7 Changes in water rates ................................ ................................ ....................... 69 3 8 If residential water rates increased by 10%, what change in total gallons delivered would you expect? ................................ ................................ .............. 69 4 1 Summary of stepwis e selection of demand variables ................................ ......... 95 4 2 Summary of hypothesized coefficients ................................ ............................... 96 4 3 Descriptive statistics ................................ ................................ ........................... 97 5 1 Estimation of results ................................ ................................ ......................... 107 5 2 Comparison of interaction coefficients under Model 4 1and Model 4 1a .......... 107 5 3 Variation inflation factors ................................ ................................ .................. 108 A 1 Characteristics of Florida public drinking water systems ................................ .. 117
9 LIST OF FIGURES Figure page 1 1 Allocation of a good by the market ................................ ................................ ..... 24 2 1 Common rate structures for water services ................................ ........................ 50 2 2 General principles for full cost accounting ................................ .......................... 51 3 1 Source of water ................................ ................................ ................................ .. 70 3 2 Change of water delivery in the last five years ................................ ................... 70 3 3 Primary causes for change in water demand ................................ ..................... 71 3 4 ................................ ......... 71 3 5 ................................ ....................... 72 3 6 Do you believe that long run changes in weather patterns will seriously and ................................ ...... 72 3 7 Plans to adapt to long run changes in weather ................................ .................. 73 3 8 Projects in increase delivery capacity over next five years ................................ 73 3 9 Determinants of water rates ................................ ................................ ............... 74 3 10 Percentage of utilities that changed their rate structure in the last five years ..... 75 3 11 Change of rate structure in the last five years ................................ .................... 75 3 12 Reasons for changing rate structure ................................ ................................ ... 76 3 13 Decision making authority regarding rate changes ................................ ............. 76 3 14 Decision making authority regarding conservation programs ............................. 77 3 15 Conservation programs used by wat er systems ................................ ................. 78 3 16 Customer Information A) Notification channels regarding water rates and conservation programs, B) Sources for customers ................................ ............. 79 3 17 Effect of conservation pricing and programs. A) On total revenue, B) On revenue variability, C) On total budget ................................ ............................... 80 3 18 Effectiveness of conservation programs. A) Most efficient B) Least efficient. ..... 81
10 3 19 Barriers to successful conservation pricing and programs ................................ 82 4 1 Expected difference in slopes between utilities encouraging water ................................ ................................ ...... 98 5 1 Studentized residuals and predicted values. A) Model 4 1. B) Model 4 2 ........ 109 5 2 Plot of studentized residuals and predicted value ................................ ............. 110 5 3 Plot of Residuals an d all observations ................................ .............................. 110
11 LIST OF ABBREVIATION S AWE Alliance for Water Agency AWWA American Water Works Association BOD Bio oxygen demand CDWS Community drinking water systems CUP Conservation use permits FDEP Florida Department of Environmental Protection Gpd Gallons per day Mgpd Million gallons per day OLS Ordinary Least Squares PED P ri c e elasticity residential water demand RFC Ratfellis Financial Corpo ration SRCC Southeast Regional Climate Center SWAPP Source Water Assessment & Protection Program USDA United States Department of Agriculture USGS United States Geological Survey VIF Variation Inflation Factor NWFWMD North West Florida Water Management Dis trict SFWMD South Florida Water Management District SJRWMD St. Johns River Water Management District SRWMD Suwannee River Water Management District SWFWMD South West Florida Water Management District WMD Water Management District
12 Abstract of Thesis Presented to the Graduate School of the University of Florida in Partial Fulfillment of the Requirements for the Degree of Master of Science ANALYSIS OF PRICING DECISION OF FLORIDA WATER UTILITIES: COST, INSTIUTIONAL AND DEMAND FACTORS By Shirish Rajbhandary December 2010 Chair: Tatiana Borisova Major: Food and Resource Economics Interest in water conservation policies has increased as water demand has grown in Florida coupled with a decline in traditional freshwater sources and incre asing costs of water supply The objective of this study is to examine the use of pricing policies programs by Florida water utilities to promote water conservation in residential sector Specifically, the research focus es on the importance of the water c onservation goal in designing water rate structures, in comparison with other rate setting priorities (such as cost recovery, and water affordability). To achieve this objective a survey of Florida water utilities was conducted in 2009 2010 T he respondents were asked about 1) their water utility characteristics, 2) price and non price water conservation strategies and 3) barriers to implementation of conservation programs. Next, using an OLS regression technique marginal residential water prices were examined to test the importance of cost recovery, institutional, and demand factors on the marginal rates charged by water utilities. Model estimation results support the d by water supply costs. Specifically, larger utilities that rely on self supplied water and/or water from groundwater sources charge
13 lower rates than utilities using surface water sources, purchased water, or a mix of water sources. Furthermore, this stud y confirms the hypothesis that the utilities encouraging water conservation (as indicated by the implementation of non price conservation programs) charge higher water rates. Finally, utilities in the areas with high poverty rates charged lower rates, whic h support the hypothesis that water affordability is an important rate design objective.
14 CHAPTER 1 INTRODUCTION 1.1 Motivation Of all the natural resources essential for human survival and well being, water is one of the most important. Although the earth is covered with 70 % water, less than 2% T his small proportion of freshwater is steadily decrea sing as a consequence of excessive water use and water pollution, exacerbated by climate change and variations in climate conditions (such as prolonged droughts) In contrast, demand for water is steadily increasing due to population growth and rising stan dards of living. This mismatch between growing human wants and diminishing water resources, combined with failures of market mechanisms to regulate water use, n e cessitates decision makers to design policies to allocate this scarce water resource towards i ts best use s A variety of instruments can be used by the decision makers to achieve socially optimal water allocation, such as subsidizing or taxing water consumption, limiting the volume of water use in a particular economic sector, or designing market based mechanisms to re allocate water among competing uses (Griffin, Water resource economics: The analysis of scarcity, policies, and projects, 2006) In Florida, state and regional agencies are using a portfolio of strategie s to curb water withdrawals for public supply, and to increase the amount of water available for in stream / in ground uses. This change in water allocation from public supply to in stream / in ally, the Florida important action we can take to sustain our water supplies, meet future needs, and
15 dependent ecosystems such as lakes The set of strategies used to stimulate water conservation includes c ost share incentives to promote water conservation irrigation design and installation standards irrigation watering restrictions, incentives for water reuse and education and outreach programs (FDEP, 2002). Water conservation rates designed to promote more efficient use of water than the rate structure they replace by providing economic incentive for consumers to limit water use water utilities to implement a variety of water rate structures. F urther, water conservation can be at odds with other water rate setting priorities, such as cost recovery and water affordability to low income customers (AWWA, 2000) Hence, it is important to examine how Florida water utiliti meet one of the competing priorities of water rate design. 1.2 Water Uses in Florida In 2005, the total amount of water withdraw n in Florida was estimated at 18,354 Mgal/day, of which 37% total freshwater withdrawal in 2005, USGS estimates that 3,110 Mgal/d (45 % ) was maining 3,758 Mgal/d (55% the hydrologic system as wastewater or runoff (Marella, Water use in Florida, 2005 and trends 1950 2005, 2008) Agricultural irrigation accounted for the greatest consumption of freshwater i n Florida largely due to high evapotranspiration, fo llowed by public supply in 2005.
16 distributed by a publicly or privately (Marella, 2008) According to 2008 estimates compiled by USGS, withdrawals for public supply in Florida totaled 2,541 mgpd of which groundwater sources supplied 87% and surface water supplied 13%. USGS estimates showed an increa se in total pu blic supply by 32% in the period between 1990 and 2005, and a 4% increase in the 5 years between 2000 and 2005. The population served by public supp ly increased by 4.9 million (44% ) between 1990 and 2005 and 2.1 million (15 % ) between 2000 and 2005. Both the gross statewide per capita water use and the domestic per capita water use have shown a decline since 1980, with the exception of 2000, which was a drought year According to Marella (2008), this trend can be attributed to water conservation efforts and restrictions imposed during this period, as well as the use of reclaimed wastewater for lawn irrigation in conjunction with other Florida Friendly Landscaping techniques. 1. 3 Water Markets The benefits of allowing the perfectly competitive market to alloca te goods are well established. A well functioning market will allocate a good among alternative uses so that the total value of the good across all uses is maximized. The market has a built in tendency to reach equilibrium where the quantity of goods dema nded is equal to the quantity of goods supplied, market price for the goods are established, and the sum of producer and consumer surplus es is maximized (Randall, 1987) Looking at the market from the marginal theory perspective, at equilibrium the marginal benefit of consuming a good is exactly equal to the marginal cost o f supplying that good (Figure 1 1 )
17 However, efficient allocation of water resources among competing uses cannot be achieved by free, unregulated mar kets due to the three main types of markets failures: in public water supply. 1.3.1 Public Goods Public goods are defined as being non rival and non excludable. A good is non agents. A good is nonexclusive if it is prohibitively expensive to exclude someone from using it (Griffin, Water resource economics : The analysis of scarcity, policies, and projects, 2006) While it is economically incorrect to label water resources in their entirety as a public good, some water uses do constitute public goods. For example, derives from it does not diminish the amount of resource available to others; further, it is generally difficult to exclude somebody from stream based recreation. Non excludability resource without paying a full price for it. Free riders expect others to pay for the provision of the public resource. As a result of the free rider problem, free markets lead to the production of public goods below the socially optimal level. To correct this market failure, government usually regulates production of public goods, and finances it through taxes. 1.3.2 Natural M onopoly and P ublic W ater S upply Natural monopoly is the situation when firms fac e declining long run average costs due to economies of scale. As a result, it is more efficient for one firm to supply the entire market output, and economic efficiency is injured, not aided by, marketplace
18 competition (Griffin, Water resource economics: The analysis of scarcity, policies, and projects, 2006) A natural monopoly is common for water suppliers. Once investments into the water supply infrastructure are made, costs of increasing water supply by one unit are small, and hence, average water supply costs decrease with the water supply expansion. At competitive market equilibrium, prices of goods are equal to the marginal production cost. For a natural monopoly, as a consequence of declining average costs, however, marginal costs of supplying an additional unit of water are lower than the (Griffin, Water resource economics: The ana lysis of scarcity, policies, and projects, 2006) On the other hand, since the average costs are declining, the monopolist can prevent new firms from entering the market by charging lower rates and producing economic losses for the new entrants (Waldman, 2004) Without the threat of competition, a natural monopolist can set high prices, supply less water than it is economically optimal, and derive economic profits. Government regulation of water suppliers attempts to set th e water prices to the levels equal to the long run average cost (Waldman 2004). For this level of prices, the water supply monopolists cover the water supply costs (including the opportunity costs), supply more water, and receive zero economic profits. 1 .3.2 Externalities A negative externality refers to situations where not all interactions among parties are reflected in market prices (Randall, 1987) For example, any diversion from a stream by a water utility or an industri al enterprise can reduce downstream flows and can potentially affect the state of aquatic ecosystems, impacting recreational water
19 users. There is no market for the services provided by the aquatic ecosystems, and hence this potential impact on downstream users is not accounted for in the prices of be overused by the up stream users. To correct this market failure to allocated water resources efficiently, governmen t regulations can either limit water withdrawals (through a cap or a standard), or establish taxes to internalize the cost of the negative externality. 1.3.3 Other A rguments A gainst W ater M arkets M any argue that the market should not allocate water res ources on the grounds that markets may further distort the distribution of resources from the poor to higher income users (Hadjigeorgalis, 2009) Further, unique hydrological and physical characteristics of water make it dif ficult to define property rights and to establish a market for water. Water is mobile, its flow tends to be variable; it evaporates, seeps, and flows. Mobility of water presents problems in identifying and measuring specific units of the resource. Since gr oundwater, surface water and the oceanic water are all connected through a complex network of rivers, groundwater, seas and evaporation, it is difficult to assign property rights to an arbitrary unit of water. Without property rights, or in the case of wat er, water rights, regular markets fail to allocate water and reveal its value for the users. 1.3.4 Implications Since water resources are plagued with issues of negative externalities, public nature of some uses of water, property rights, equity, and natural monopoly, markets tend to fail in the efficient allocation of water, calling for government interventions.
20 1 .4 Water Regulation in Florida law and long established practices, provided a basis for water use rights (Carriker, 2008) In 1972, the Water Resources Act (Chapter 373, Florida Statutes) established general supervision of the Florida Department of Environmental Protection (FDEP) (Marella, Water use in Florida, 2005 and trends 1950 2005, 2008) The five Water Management Districts are South Florida Water Management District (SFWMD), the Southwest Florida Water Management District (SWFWMD), the St. Johns River Water Management District (SJRWMD), the Suwannee Water Management District (SRWMD), programs delegated to the districts include programs to manage the consumptive use of water, aqui Department of Environmental Protection [FDEP], 2010). The water management districts fund their projects mostly via the ad valorem tax (Carriker, 2008) T h e type of permit which authorizes water use is called a consumptive use permit (CUP). This permit allows water to be withdrawn from surface and groundwater supplies for reasonable and beneficial uses such as public supply (drinking water), agricultural and landscape irrigation, and industry and power generation. In accordance with the are issued by the water management districts. When determined threshold levels, the party needs to acquire a CUP from its respective water management district. The threshold levels vary and are set by each of the five water management districts (Olexa, D'Lserinia, Minton, Miller, & Corbett, 2005) ed period of time, with an
21 expiration date and must be renewed prior to the expiration date in order to continue using water (FlWaterPermits, 2010) These permits prevent detrimental use of water able uses and promotes natural resource, fish, and (Olexa et al., 2005). For the case of public supply, these permits set limits on the amount of water that utilities can withdraw from the ground and/or surface water sources, and hen ce, control the amount of water that the utilities can supply. Public water systems seeking water permits must adhere to their respective WMDs conservation plan requirements. Specifically, SWF W MD requires the following: adopt a water conserving rate structure no later than two years from the date of permit issuance and shall submit the rate ordinances or tariff sheets for both potable and irrigation water, and submit a report describing the potable water rate structure an (SWFWMD, 2010) Similarly, according to Conditions for Issuance of Permits ( Rule 40B 2.301 Florida Administrative Code ) SRWMD requires that applicants for water permits must provide reasonable assurances that the proposed use of water is used for reasonable beneficial use, will not interfere with any presently existing legal use of water, and is consistent with the public interest. Among many conditions, wa ter use must promote efficient and economic use should not degrade the source from which it is withdrawn, and will not contribute to flooding (SRWMD, 2010) In turn, SJ R WMD in Rule 40C 2.301 Conditions for Issuance of Permits list all the requirements stated by SRWMD, along with the need for applicants to take conservation measures, and reduce the harm caused by consumptive use to the environment (SJWMD, 2009) Similar conditions for water use
22 pe rmits are required by NWFWMD (NWFWMD, 2010) .In essence, to secure a consumptive use permit, public supply systems must keep in mind the need for conservation, ensure that water use does not harm the economy or the environment, and guarantee that water is used for beneficial uses. 1.5 Water Demand and Supply Management Strategies Whenever water demand approaches the limits of available water resources, two general methods for addressing potential water shortage can be taken. I n the case of residential water (public supply), utilities can either focus on enhancing water supply or pursue approaches to manage water demand. The first, often referred to as supply side measures, involve increasing the water supply, thereby shifting t he supply curve of water outwards. Some supply enhancement measures are: drilling / improving wells, repairing leaky infrastructure, building desalination plants, and reprogramming reservoir operations (Griffin 2006). The second method, referred to as dema nd side measures, focuses on managing water demand and operating within the limits of current water supplies. Demand side measures can be divided into 1) Non price demand management tools, and 2) pricing policy. Examples of non price tools include install ing water conserving fixtures through retro fit programs, developing drought contingency plans, rationing water, implementing water use restriction programs, and educating water users about conservation options. Pricing policies essentially involve raisin g water rates and hence, creating economic stimulus to reduce water use. Although supply side measures in the developing world are still popular (for example, large scale diversion projects in China and India, (Hadjigeorgalis, 2009) these approaches are losing momentum in the United States. Supply side enhancements in Unites States are no longer economically feasible, because most of the finite freshwater
23 sources have already been exploited, and further exploitation of this r esource is becoming increasingly more expensive. For example, the desalination plant at Tampa Bay, Florida is currently desalinating water at the cost of $650 per acre foot (or $1.99 per thousand gallons) compared to about $200 per acre foot ($0.61 per th ousand gallons) for water from traditional supply sources (1992 cost basis). (USGS, 2010) side policies (Hadjigeorgalis, 2009) Demand management strategies can be powerful tools to equate demand and supply. M uch research has focused on reducing water demand through a mix of pricing policy and non price tools such as use restricti ons, retro fit programs and education. For example, Corral, Fisher & Hatch (1999) show that pricing policy and conservation programs proved effective in lowering water demand during droughts and the summer season in three water districts in the San Francis co Bay Area. A conservation rate structure study by Jordan and Albani (1999) showed that rates used as part of a conservation program were most effective at reducing peak demands, while other non price programs (e.g., low flow fixtures, education) were mor e successful at reducing the base demand. Additional results from existing literature will be presented in Chapter 3 below. 1.6 Outline of the Chapters The objective of this study is to examine the use of pricing policies programs by Florida water utilitie s to promote water conservation. Specifically, the research focus es on the importance of the water conservation goal in designing water rate structures, in comparison with other rate setting priorities (such as cost recovery, and water affordab ility).
24 I summarized. Next, a detailed description of the data used in th is study is presented in Chapter 3. Methodology is presented in Chapter 4 Results and Conclusion fo llow thereafter in Chapter 5 and Chapter 6 respectively. Price ($/unit) S=MC of production PS P eq E sum of producer and consumer surplus is maximized CS D=MB of consumption =marginal willingness to pay Q eq Quantity per time period Figure 1 1 Allocation of a good by the market
25 CHAPTER 2 LITERATURE REVIEW 2.1 Overview of Rate Structures This chapter provides an overview of the literature related to the subject of the For water utilities, s electing the appropriate rate structure is an important undertaking for two determined by water rates necessary to maintain vital infrastructure, 2) rate structures reflect the philosophy and objectives of the utility. The AWWA manual of water supply practices defines a wat er rate structure (AWWA Manual, 2000) A water rate structure usually includes a fixed monthly fee (also referred to as base, minimum monthly, or meter fee) and a variable charge. The fixed fee is usually tied to the size of the wide survey of water utilities conducted in 2008 shows that the monthly fi xed fee for the median residential customer ($7.03) comprises 30.2% of the total water bill (1,000 cubic feet of 7,480 gallons of water usage) (AWWA & RFC, 2008) The monthly fixed fee for the median water customer using 1,000 cf (7,480 gallons) is reported to be $7. 03 (AWWA & RFC, 2008) Since the fixed fee is constant, discussions about conservation water rate structures are usually focused on variable charges that depend on the household water use. Based on the variable charge schedules, the three most common rate structures increasing block block ates (Figure 2 1). In a uniform rate structure, the per unit variable charge does not change as the customer uses more
26 water. In an inclining block structure, the per unit variable charge increases with greater water use. Conversely, in a declining block s tructure, per unit variable water charge decreases as water use increases. Additionally, in a seasonal rate structure, different rate structures are applied at different times of the year. There is considerable variation in rate structures among utilities, with each structure giving rise to definite differences in their design and impact. A nation wide survey of water utilities conducted in 2008 indicate that declining and uniform rate structure s are losing popularity, especially in those areas where water supplies are more scarce The percentage of utilities using declining block rates and uniform b lock rates have decreased by 20% and 11 % since 2000, while inclining block rates hav e increased in popularity by 38% since 2000 (AWWA & RFC, 2008) However, about one third of water utilities that participated in the national survey (28%) still employ declining rate structures for res idential customers. Further, 32% of utilities in the United States have uniform rate structures, an d 4 0% of utilities have inclining block rates (AWWA & RFC, 2008) For those water utilities that employ block rate structures for residential water service, the most common number of blocks is 3, with average number of declining blocks being 3.7 and the average number of inclining blocks being 3 .5 (AWWA & RFC, 2008) 2.2 Objectives of Rate Setting There is no single rate structure that is best for all utilities. The most appropriate rate struc ture for each utility differ s based on the local conditions and policy objectives. R ates can be structured to encourage water conservation, attract industry customers meet revenue requirements, or meet other goals (Ernst and Young, 1992, Rogers Silva
27 & Bh atia 2002, Griffin 2002, AWWA & RFC 2008, AWWA Manual 2000, Gaur 2007). F ive main objectives of rate design are discussed in detail below. 2.2.1 Financially S ustainability The first objective of a water utility is to design a rate structure to generate investments, that is, a high percentage of water supply cost are fixed costs that do not vary with the quantity of water consumed (Reynaud, Renzetti, & Villeneuve, 2005) Sufficient r evenue is necessary to cover this high fixed cost, maintain the quality of service and invest in system expansion and improvements (AWWA Manual, 2000) While discussing residential water consumption and revenue stability, it is also important to distinguish between the two types of water consumption. First is indoor water consumption, which is typically consistent from year to year. For instance, the number of showers taken in a year, water used for cooking, cleaning, and other household uses is generally constant However, outdoor water use is more volatile, fluctuating in response to weather and time of year. For instance, in the summer, more outdoo r activity such as swimming is done, and lawns need more watering than the winter. An increase in the proportions of the outdoor water use s leads to the increase in the volatility of total water use, and hence, higher revenue volatility (Gaur, 2007) Different rate structures can either magnify or reduce this volatility as discussed below. 2.2.2 Fairness and Equity reflects a reasonable share of utilit the value of service to the customer (Rubin, 2010) Classes are groups of customers that share common characteristics. Typical water utility customers include singl e family
28 residential, multifamily residential, commercial, industrial, and irrigation (Teodoro, 2002) R ate setting should focus on distribut ing utility costs equitably to each class of customers. Some rate structures fail to achieve the fairness and equity objective, and may penalize or reward certain groups of customers without much justification. For example inclining block rate s can potential ly penalize large users of water, as they are charged a higher per unit co st than smaller users. Gaur (2007) illustrates this objective through an example using two families under an inclining block rate structure The author assumes that one family consists of two people and the other consists of six people. Although each indi vidual in a family consumes the same amount of water, the per capita cost for the latter family is higher because of th e nature of the inclining block rate structure. 2.2.3 Economic E fficiency Economic e fficiency is achieved when the welfare of the commun ity utilizing a water resource is maximized and when the marginal price of water faced by consumers equal the marginal social cost of supplying water to these customers. Such pricing strategy, if implemented in practice, should allow for transfers from w asteful water uses to more efficient and higher value uses that should account for environmental externalities and opportunity cost of water and all other inputs involved in supplying water (Renzetti & Kushner, 2004) (Rogers, Silva, & Bhatia, 2002) (Figure 2 2 ). Full cost pricing has a set of advantages. H igher rates discourage wasteful water use leading to re allo cation of water resources from low value to high value uses. F unds become available for water resource protection, as well as for regular maintenance of water supply system Finally consumers develop an
29 awareness of the scarcity of water supply, which reit erates the goal of water conservation (Goldstein, 1986) However, several factors preclude widespread use of full cost pricing. Water utility managers tend to adhere to historical pricing methods (Goldstein, 1986) Most water ratemaking is based on principles and rate designs established decades ago by (AWWA Manual, 2000) Although this document describes different types of rate stru ctures and provides guidelines in implementing them, this document falls short in full cost pricing rate structures. Secondly, in most cases, those responsible for water rates are elected officials. These officials are subject to political pressure and may be reluctant to support higher rates associated with full cost pricing (Goldstein, 1986) Finally, data needed to estimate some of the cost components and environmental externalities are difficult to collect (Griffin, Water resource economics: The analysis of scarcity, policies, and projects, 2006; Renzetti & Kushner, 2004) 2.2.4 Water Conservation R egulatory agencies and utilities focus on designing water rates to create incentives f or the customers to reduce level of water use in low value discretionary Since utilities do not have complete information about the full cost of water supplied to the customers (as discussed above) the goal of conservation water pricing is not to achieve the economically efficient water use level, but to bring the customers closer to this level. Specifically, conservation water rates are designed to increase the tota l payment for water for the high volume customers, thereby reducing or eliminating low
30 value water uses (such as, for example, frequent lawn irrigation that does not improve the quality of the turf). Water conservation objective requires the rate design t o pass to the consumer information about the scarcity of water resources and the rising opportunity cost of withdrawing increasingly large volumes of water for residential consumption. As discussed below inclining block rates can promote water conservati on. On the other hand, a declining block rate structure does not reflect water scarcity, because each unit of water becomes less expensive as the water use increases (Gaur, 2007) 2.2.5 Ease of Implementation and A dministerin g I t is important for the utility to minimize the costs of designing and implement ing water rates Costs associated with water rate design include personnel time required for data collection and analysis, demand forecasting, customer information campaign, management of customer complaints, etc. Some rate structures are more difficult for the utilities t o design and convey to the customers. For example, it is more difficult for the customers to understand their water rates given a block rate structures, compared with uniform rates (AWWA & RFC, 2008) 2.3 Advantages and Disad vantages of the Common Rate S tructures Each rate structure type (uniform, inclining, and declining block rates) presents utilities with a tradeoff in reaching some objectives but failing to satisfy others (AWWA & RFC, 2008) T he key issue for utilities is to prioritize their rate objectives and ensure that their rate structure is consistent with their needs. Recently attention of researchers and water industry professionals has focused on challenges of achieving conservation, e quity and financial sustainability (Goldstein, 1986) Water utilities often find it difficult
31 to strike a balance among the three objectives because greater equity and especially conservation price signals often c ause increased revenue volatility. Based on the degree to which a specific rate structure achieves the conservation objective, the rate structures can be categorized into conservation oriented rates, and the rates that do not send a conservation price sig nal. Pros and cons of these rate structure types are discussed below. 2.4 Rate S tructures that do not S end a C onservation Price S ignal Declining block rate structures fall under this category. Such rate structure s are ine with inclining water use (i.e., economies of scale ), given that the opportunity cost of using water is very low. Such rate structures are also favorable when it is important to encourage large scale consumers to remain in the system (AWWA Manual, 2000) Hence, declining rate structure is often employed by utilities that focus on encourag ing economic development. Declining block rate structures can allow a utility to reduce volatility of revenue and hence, meet the revenue stability objective of the rate design. If designed properly, the first price blocks would cover indoor water use, and the higher blocks would capture outdoor water use. Under a declining block rate structure, lower blocks are charged the highest water rates, with rates decreasing for subsequent higher blocks. The lower blocks tend to be more stable as it typically includes everyday use (indoor use), providing a reliable and stable revenue stream. With respect to the ease of i mplementation, d eclining rate structures and inclining rate structures may be more difficult to implement compared with uniform rates, because it is necessary to estimate how much water is consumed in each price block.
32 With respect to water conservation objective, declining water rate structures are viewed negatively, as they are perceived to promote rather than discourage water consumption (AWWA Manual, 2000) 2.5 Conservation R ate S tructures Rate structures that encourage wa ter customers to save water are referred to as According to the Alliance for Water Efficiency (AWE), the most important aspect of conservation rates is designing the rate structure so that a large portion (two thirds or mor e) of the water rates are based on the volumetric consumption of customers (Efficiencey, 2009) There are three types of conservation rate structures: uniform, inclining block and seasonal block rates. The latter two send stro nger conservation signals than uniform block rates (AWWA Manual, 2000; Gaur, 2007; Goldstein, 1986) 2.5.1 Uniform B lock R ate S tructure The chief advantage of a uniform rate structure is that it is relatively simple to administer and easy for customers to comprehend. Further, it is generally accepted that i n comparison with in c l in ing block rate structure s uniform rates provide utilities with more revenue stability. With respect to the equity criteria, uniform rates are usually considered equitable as all customers pay the same unit price for general water service. However, large consumers may consider uniform rate structures as unfair since their higher consumption levels can be associated with lower water sup ply costs compared with other customers. W hile uniform rates provide incentives to conserve water (because the total water bill increases with water consumption), conservation experts believe that more complex
33 rate structures such as inclining block rates send a stronger conservation oriented price signal to consumers (AWWA Manual, 2000; Glennon, 2004). 2.5.2 Inclining B lock R ate S tructure Inclining block rates essentially penalizes the customer for greater water consumption providing a larger disincentiv e for the customer to use large quantities of water (compared to uniform and declining rate structures). The intent of this type of rate is to encourage customers to conserve water. A properly designed inclining rate structure can reduce daily and seasonal peak uses, and reduce peak demand, which lowers the capital investment needed to supply water. (Agthe & Billings, 1987) The main advantage of this rate structure is that it transmits water scarcity information to consumers, which is increasingly one of the major objectives water utilities seek to accomplish. To balance the goal of conservation, price equity, and revenue stability, the AWE recommends that the first tier of a residential inclining block rate structure provides minimal water usage for a typical household at the minimum reasonable price. Subsequent blocks should then be priced significantly higher (i.e. greater than 50 percent higher than the prior block) (Efficiencey, 2009) Further, the number of blocks necessary for an effective residential rate design, according to the AWE is 3 to 4 blocks, where more than half of residential customers exceed t he first block, and at least 30% and 10 % of customers using water in the third and fourth blocks respectively (Efficiencey, 2009) Compared to the uniform rate structure inclining block rate structure is more complex and more difficult to design and administer as it is necessary to know the amount of water consum ed in each price block With respect to the revenue stability objective, s tudies suggest that utilities implementing inclining rate structure are prone to
34 larger revenue variability because reductions in water use occur at the highest rate block (AWWA Man ual, 2000; Beecher & Laubach, 1989; McLarty & Heaney, 2008). Given an inclining rate structure, a large portion of the revenue is generated on higher price blocks At the same time, water use on the higher price blocks is typically for outdoor needs and i s more volatile. Furthermore, as consumers face higher prices, they have incentives to reduce their consumption to smaller prices set for the lower price blocks This can further exacerbate revenue instability. With respect to equity, inclining block rate s can have adverse effects on large users, who can argue that this rate structure is inequitable. 2.5.3 Seasonal R ate S tructure Seasonal block rates involve higher rates for water during periods of peak demand (such as the end of dry period in Florida Ma rch to May), when a large portion of water is used for outdoor and discretionary activity. The higher rates reflect the large investments in capital investment required to satisfy higher water demand during those peak periods (AWWA Manual, 2000; Goldstein, 1986) Peak rates can be used to promote conservation by providing incentives for customers to reduce their water consumption during peak use periods. Administering seasonal rate structure can be challenging because it requires to differentiate rates during different time periods and know the consumption of water during each respective season (Gaur, 2007) 2.6 Residential Water Demand and Effectiveness of Price Policy For a price policy to successfully manage demand and encourage water conservation the key is to design water rates based on the sensitivity of water use to the price changes, i.e. based on the price elasticity of water demand (PED). PED is defined as the percen tage change in the volume of water demanded that occurs due to
35 a percentage change in price. For example, if the price elasticity of residen tial water demand is 0.2, a 10% inc rease in price will lead to a 2% decrease in water consumption. PED information should guide water utilities in their decision to encourage water use reduction by increasing water rates, replacing uniform rates with inclining block rate structures, and increasing water rates from one price block to the next (AWWA M1 manual). E lasticit ies may vary along demand curve and any estimate represents elasticity at a specific price. On average, in the United States, the water demand is relatively inelastic (i.e., PED is less than one in absolute value) (O lmstead & Stavins, 2008) For example, (Espey, Espey, & Shaw, 1997) used a meta analysis of 124 nationwide PED estimates generated between 1963 and 1993 and showed that the overall residential PED (indoor and outdoor) estima tes ranged from .02 to 3.33, with an average PED of 0.51. More recently, Dalhuisen et al. (2003) performed meta analysis of 314 estimates of PED for residential customers. The estimates were compiled from 64 studies conducted in the United States betwe en 1963 and 1998. The results of the analysis are comparable with findings from Epsey et al (1997): the distribution of PED estimates had a sample mean of 0.41, a median of 0.35, and a standard deviation of 0.86 (Dalhuisen, F lorax, Groot, & Nijkamp, 2003) Similarly, a recent study of residential water demand in eleven urban areas in the United States and Canada found that the PED of residential water demand was approximately 0.33 (Olmstead, Hanemann & Stavins, 2007) P rice elasticity depends on many factors. First, p rice elasticity depends on the proportion of income spent on water bill. Literature
36 reports contradicting results about the elasticity of high versus low i ncome customers. For example, a price elasticity study conducted in Tucson, Arizona, between 1974 1980 showed a steady decrease in the PED as income increases, from 0.565 for the low income group to only 0.397 for the high income group (Agthe & Billings, 1987) In contrast, in a Florida study, Whitcomb (2004) found that PED first increases with Second, consumers are relatively more sensitive to water prices in the long run than they are in the short run In the long run, capital investments are not fixed (e.g., households might change appliances, or alter landscaping to reduce water use ) which make water demand to be more elastic in the long run (Olmstead & Stavins, 2008) Third, p rice elasticity differs for indoor (non discretionary) water use and outdoor ( discretionary ) use. Indoor water use is usually inelastic because it includes necessary water use such as drinking, cleaning, cooking, and laundry. However discretionary water uses (such as lawn watering, swimming pools) are more responsive to price changes. Discretiona ry water use is the main driver of seasonal variations in residential water consumption because the volume of water used for discretionary purposes increases as the outdoor temperature goes up. Due to the higher proportion of discretionary water use in sum mer months, people are more responsive to changes in water price in summer (Corral et al ., 1999; Espey et al ., 1997; Glennon, 2004). Since price elasticity is affected by many factors, it is necessary to incorporate price elasticity studies in the rate set ting process. Furthermore, since elasticities differ size fit which necessitates study of elasticities specific to customer classes
37 2.7 Measuring Det erminants of Water Rates and Rate Structure Given that water rate structures differ significantly among water utilities, several studies have Based on the main research question, existing studies can be divided into two groups: 1 ) studies that examine the effects of various factors on the average price charged by water utilities, and 2 ) studies that examine choice s among the types of rate structures (i.e., inclining block, uniform, or declining block structures). Thosten, Eskaf & Hughes (2008) and Garcia, Schneider, & Fauquert (2005) belong to the first group of studies. Thosten, Eskaf & Hughes (2008) used hedonic technique to test if utility cost, customer demand characteristics and institu tional and geographic factors influence the size of the average monthly bills consumers pay for water and sewer services in North Carolina. Their data included rates and rate structures used by 333 North Carolina public utilities in 2005 2006. The authors used three models to examine the average water and wastewater bills. T he first model (Model 2 1) presumes that the bill set by utility i for service j at quantity q can be described as a function of cost characteristics and an error term; that is, P i,j,q = + 1 C i,j,q + i ( 2 1) in which, the hedonic price P i,j,q is the total monthly bill charged to residential customers (including fixed and volumetric charges ) and C i,j,q is a vector of fa ctors that drive the cost of service j at quantity q for utility i Seven cost determinants are considered in this analysis including: a) utility size, b) total long term debt (an indicator of capacity and repayment), c) water source (groundwater or surfac e water), d) purchased water system (or self treating water system), e) a water source and purchased water system interaction term, f) treated wastewater system (or contracting
38 wastewater treatment by another utility), and g) population density of the muni cipality or county. With an adjusted R 2 of 0.043, this cost model explains 4.3% of the total variation in the monthly bill. Results show that larger utilities charge lower bills possibly, due to lower water supply costs. Utilities with higher debt pass o n debt funding costs onto their customers and charge higher rates Furthermore, u tilities that purchase their water from a wholesaler also charge higher rates, that is, they pass additional transaction cost and premium they pay for obtaining this water onto their customers. Although the interaction term for surface water and purchase water system s is negative and statistically significant, the net effect of relying on purchased surface water is positive That is, utilities that rely on surface water sources charge higher rates which reflects the increased cost of treating surface water (compared with groundwater) Two other cost factors w hether utility treats its own wastewater and population density, were not statistically signif icant in this model. Overall, the results show that utilities that incur higher water supply costs charge higher water rates. The second model introduces a set of demand factors into the monthly bill model ; that is, P i,j,q = + 1 C i,j,q + 2 D i,j,q + i (2 2) where D i,j,q is a vector of demand factors considered to influence the monthly bill, P i,j,q Seven demand factors are considered including a) median household income of the community, b) percent of residents service area, d) percent of elderly residents, e) percent of owner occupied homes, f) 30 year normal mean temperature, and g) 30 year normal annual precipitation.
39 Results show that utilities in areas with higher temperatures, and communities with higher median income charge higher rates at the average level of consumption, although the magnitude of the effects are very small. This result can imply that in the areas with higher water demand (associated with warmer climate and wealthier customers), utilities charge higher rates Such strategy makes economic sense, since rise in demand should increase market price s In addition, in the areas with higher discretionary water use, utilities charge higher rates to encourage water conservation. Percent of residents in poverty is also statistically significant but with an unexpected positive coefficient. However, this effect of the poverty rate on the average bill becomes insignificant once institutional factors are incorporated in to Model 2 2 ( see model 2 3 ). The remaining four coefficients (median age of homes, percent of elderly residents, percent of owner occupied homes, and precipitation) are not statistically significant. Introduction of demand proxies into the equation barely changes the strength or significance of the cost factors. Overall, inclusion of demand factors increased the explanatory power of the model measured by the improved adjusted R 2 of 0.119. The final model (Model 2 3) includes cost and significant demand factors as well as institutional factors ( I i,j,q ): P i,j,q = + 1 C i,j,q + 2 D i,j,q + 3 I i,j,q + i ( 2 3) Institutional factors include a) utility ownership type, b) whether the utility uses different rates for residential customers living outside city limits, c) whether utility has different rates for nonresidential customer groups, d) whether utility received state grant funding, the operating ratio, and f
40 recovery, affordability, economic development, or conservation based on responses of a survey ). Adding institutional factors raises the adjusted R 2 of the model to 0.206. T he cost drivers and median household income (to a lesser extent) retain their significance in Model 2 3 whereas temperature and percent of residents in poverty are no longer significant. perating ratio s are positively correlated with monthly b ills, and the presence of the rate differential for the residents outside city limits is very strongly associated with lower monthly bills. Utilities where managers place the highest priority on affordability report a 12.7% lower monthly bill. The remaining institutional factors (i.e., rates for non residential customers and state grant fun ding) were not statistically significant. Overall, this study provides empirical evidence that cost factors are not the only determinant s of the rate s chosen by water utilities. Demand characteristics and institutional factors are also considered by utili ty managers in the rate design process. Specifically, in the areas with higher income levels (and hence, higher use of water for discretionary activities), utilities charge higher water rates, possibly, in order to encourage water conservation. Further, u tilities that rank water availability as their most important rate design objective charge lower rates perhaps indicating the tradeoff between water affordability and water conservation objectives of rate design Similarly, Garcia, Schneider, & Fauquert (2005) group potential determinants of rate is computed as the reven ue received by the private operator (water utility) divided
41 by the water delivered to the customers. Two cost variables were included in the regression to capture the level of operator cost: variable CONS denotes the total water delivery of the supplier, w hile variable CONNECTS represents the number of connections. Both variables are intended to capture the reduction in water supply costs with the increase in utility size s and the resulting impacts on the water rates The other two group s of factors that i nfluence water rates the competition for the water supply market are used to test the theory that as the level of competition for the water supply market increases, rates tend to decrease. O priorities strategies, and are assumed to differ among new entrants ( who strive to enter the market and are expected to propose lower prices ) and more established operators. All three models were est imated using OLS log log specification. Estimation results match the results of Thorsten et al ., 2008 and support the hypothesis that utilities with lower supply costs charge lower rates. Specifically, the authors show that a 1% increase in water delivery decreases the average rate by about 0.46%, and a one percent increase in the number of connections results in 0.006% decrease in the average rates The authors were not able to show a clear relationship between the level of competition and w ater rates In turn, three existing studies examine d rate structures: Reynaud, Renzetti & Villeneuve (2005) Hewitt (2000), and Neiswiadomy and Cobb (1993). Specifically, using a sample of 899 communities in Can ada, Reynaud, Renzetti & Villeneuve (2005) develop a multinomial logit pricing model to examine the reasons why local communities (that own and/or manage local
42 water utilities) chose specific residential water rate structures. F our rate structure s are exam ined : uniform rates, inclining block rates, declining block rates, and flat rates (i.e., rates that are independent from water use level, the reference category in the model) choices are considered : cost recovery, equity /affordability price discrimination among customers and stability of revenues S everal cost proxies were included into the model. Based on the assumption that utility costs increase with the complexity of service provided, several variables are included in the model. The average biochemical oxygen demand (BOD) of effluents ( bod_inflow ), an indicator of quality of raw water, is a proxy variable for the level of treatment costs (with higher BOD associated wit h higher treatment costs). Another proxy cost variable is the source of water. Specifically, the authors assume that the increase in the share of groundwater in the total water supply ( groundwater) lower s the supply costs. Other variables used to proxy the complexity of service are no_sewage, no_teatment and no_disinfection. Water suppliers without a sewage facility ( no_sewage ), and/or without water treatment prior to supply ( no_teatment ) and water disinfection ( no_disinfection ) are expected to have lower costs. F urther, equity and water affordability objectives of the local communities were captured through the variables measuring the unemployment rate ( umemployment ), and the share of population without any earned income ( income2). The authors hypothesize that in the areas with high unemployment rate and large proportion of population without earned income, water affordability will be the primary objective of water utilities.
43 Price discrimination ( to encourage water conservation or to increase utilities r eturns) To capture the degree of income heterogeneity among the customers, tw o variables were included into the model: a) t he ratio of the difference between median and average incomes to the average income ( income3 ) in the community and b) the standard error of the average income ( income4 ) in the community The assumption is that t he greater the heterogeneity among customers, the more successful the price discrimination can be. In addition to the income variables the percentage of households residing in rural area s as opposed to urban area s ( rural ) aims at captur ing the geographic heterogeneity across consumers. Further, dwelling characteristics, such as proportion of single family ho m es ( dwelling_ind ), proportion of dwellings built after 1991(dwelling_new), and the average number of rooms per dwelling ( dwelling_room ) were included to account for possible differences in water use among communities Specifically, dwellings built afte r 1991 tend to have more rooms bathrooms and swimming pool s leading to higher water use. The proportion of single family homes in a community is also positively correlated with the average water consumption per household which can be explained by a larg er outdoor water use associated with individual houses compared to apartment complexes Finally, to reflect the revenue stability objective in the water rate design, the authors included a categorical variable representing the size of the municipality ( size ). The argument is that revenue stability criterion may be more important for smaller utilities (that may be unable to diversify risk s ) compared with larger utilities.
44 Estimation results show that pricing choice s by local communities is significantly influenced by the following three considerations. First, the probability of implementing inclining block structures increases with the cost of water services, as utilities try to reflect their increasing cost s of water supply through the increasing rate s Second, choice of pricing structure is also affected by social goals of the local communities That is, the probability of implementing inclining block structures decreases with the proportion of the population without earned income, and with higher unempl oyment rates. Inclining block rate structures are usually promoted as the structures designed to encourage water conservation, and hence, s imilar to Thosten, Eskaf & Hughes (2008) such result indicates that water conservation and water affordability objec tives can be at conflict in low income communities Finally, price discrimination among consumers is also an important determinant of the price structure choice. The results show that the probability of using an inclining block rate structure increases with the community water use levels, as captured through such variables as : a) the proportion of dwellings built after 1991, b) average number of rooms in a household in a community c) proportion of single family homes and d) income differentiation in the community This result water pricing as a tool to encourage water conservation in the communities where water consumption is high thus, brining water use level closer to the economically efficient outcome Similarly, u Water system survey, Hewitt (2000) shows that utilities are more likely to adopt inclining block rate structures if they are located in climates characterized by some combination
45 of hot, dry, sunny, and lengthy sunny season s (i.e., in the areas where water resources are likely to be more scarce, and demand for water is likely to be higher) In contrast, utilities that are concerned with revenue stability and meeting their debt obliga tions are less likely to adopt inclining block rates. Smaller utilities and private utilities are also less likely to adopt inclining block structures because such utilities lack the human capital to develop, track and administer these more complex rate s tructures Finally, since surface storage typically implies greater infrastructure expenditures than either purchased water or groundwater, utilities that rely on surface water (and are concerned with cost recovery) are more likely to adopt inclining block rate structures. In another study, using the 1984 AWWA survey of several hundred of the largest U.S. water utilities, Neiswiadomy & Cobb (1993) show that cities that implement conservation programs, and have lower annual rainfall, have a greater probabil ity of implementing conservation oriented inclining block rates. Additionally, the more water a city purchases from outside sources, the greater the probability that the utility will choose and inclining block rate (potentially, to recover the cost of wate r purchase from a wholesale supplier). Overall, literature shows that utilities with higher water treatment and delivery cost s are more likely to implement inclining block rate structures and /or charge higher rates. The costs are measured in the existing literature using a similar set of variables, including : a) utility size (measured in terms of total water delivery and/or total number of connections) b) total long term debt, c) water source (groundwater or surface water), d) the quality of water in the source and the need to conduct additional treatment; d) purchased water system (or self treating water system), e) wastewater treatment and
46 g) population density of the municipality or county Hence, based on the existing literature, a comparable set of variables is used in this thesis to examine impact of supply costs on the rates of Florida water utilities. Further, existing literature shows that utilities institutional characteristics are tes. The following institutional factors are examined in literature: a) utility ownership type, b) whether the utility uses different rates for residential customers living outside city limits, c) whether utility has different rates for nonresidential cust omer groups, d) whether utility received state grant funding, e) the operating ratio, and f ) utilit ies rate setting priorit ies The studies consistently show that u tilities where managers place a high priority on affordability charge lower rate s and/or less likely to adopt inclining block rate structures Further, existing studies show empirically that the water demand characteristics are also considered by water utilities in their rate decisions. Demand characteristics are measured using such variables as a) median household income of the community and income heterogeneity b) percent of residents in poverty and unemployment rate c) percent of elderly residents and the percentage of households residing in a rural area d ) percent of owner occupied homes and the proportion of single family houses, e ) proportion of new built houses and the average number of rooms per dwelling and f ) 30 year normal mean temperature and 30 year normal annual precipitation. T hese variables allow the researchers to differentiate utilities serving high and low demand service areas. Economic theory suggests that markets with high er demand s are characterized by higher prices In addition, in the high income/high water use communities, large proportion of the total water consumption is used for low value
47 discretionary uses. If opportunity costs of water are high (i.e., water resources are limited), higher rates may also indicate that water utilities are focused on encouraging water conservation ( to bring residential water consumption closer to the economically efficient level). The studies consistently show that high level s of water consumption are associated with a higher probability of using increasing block rates and/or higher rates. rarely available. As a result, all existing studies use proxy variables to capture important characteristics of the water supply and demand. S ince information captured throug h the proxy variables is imperfect interpretation of the coefficients of such variables in the estimated water rate models is often complicated and is based on a set of assumptions. For example, utility size can affect both water supply cost and the rat e setting priorities. S tudies show that larger utilities are more likely to implement inclining block rate structure s than smaller utilities. One explanation is that smaller utilities lack the funding resources and staff to implement and monitor the more c omplex inclining block rate structure Alternatively, this result may imply that smaller utilities have a different set of rate setting priorities, compared with larger utilities, and are more concerned with revenue stability (s variable). Similarly, climate variables (i.e., average temperature and precipitation) may reflect both the demand for the discretionary uses (that increases in hotter and drier climates) and the scarcity of water resources (hence higher opportunity costs of water use in residential sector). Since perfect information about water supply and demand in Florida is not available, this thesis also employs a set of proxy variables. However, one
48 recommendation for the future studies on this topic is to collect and use more accurate 2. 8 Objective and H ypotheses of Thesis The goal of my thesis is to identify factors that help explain the difference s amo ng the residential water rates charged by Florida water utilities, and to examine if water conservation is among the top priorities for water rate design of the utilities. Similar to existing literature, I examine if cost, demand, and institutional factors influence water rates. However, in contrast to the existing studies ( Thosten et al. (2008), Garcia, Schneider, & Fauquert (2005), Reynaud et al. (2005), Hewitt (2000), and Neiswiadomy & Cobb (1993)), that focused on the decision about rate structure type or water rates charged by water utilities. Large majority of water utilities in Florida use inclining block setting priorities can be revealed through the analysis of rate structure type (similar to Reynaud et al. (2005) or Hewitt (2000)). In turn, average bill analysis used by Thosten et al (2008) does not allow evaluation of the differences between rates faced by low use / low income and high use / high income customers of the same utilities. Accordingly several hypotheses are tested in this study: 1) Water utilities design their water rates to mimic their cost structure. Utilities that have hi gher costs charge higher rates. 2) I nstitutional factors are important determinants of water rate s: a. Utilities owned by municipalities are expected to charge lower prices than privately owned utilities Privately owned utilities often incorporate a small percentage of returns into their rates. b. Water rates will significantly differ among the jurisdictions of the five
49 cies related to consumptive water use permits. 3) Rate setting priorities influence water rate structures adopted by water utilities. Specifically, u tilities that focus on water conservation are expected to have higher / steeper water rate structures. 4) Cust demand characteristics are considered by water utilities in water rate design. a. Higher income, lower poverty rate and higher temperatures are associated with larger water consumption due to higher outdoor use. In response to higher water demand such areas, I expect water utilities to charge higher prices. b. In the areas with high poverty rate utilities rate setting objective s shift towards water affordability and hence water rates will be lower in areas with high poverty rates. In the next chapter I describe responses to a survey of Florida water utilities that are used in my analysis. Next, a complete methodology is discussed in Chapter 4
50 Price/unit of water Price/unit of water Consumption Consumption Uniform Block Rate Declining Block Rate Price/unit of water Price/unit of water C onsumption Winter Summer Winter Inclining Block Rate Seasonal Block Rate Figure 2 1. Common rate structures for water services
51 Figure 2 2 General principles for full cost accounting
52 CHAPTER 3 DESCRIPTIVE STATISTI CS 3.1 Overview My analysis is based on the results of 2009 2010 survey of Florida drinking water systems. The objective of the survey was to identify price and non price conservation strategies used by Florida water utilities. Below, I discuss the survey sam pling and administration procedures and summarize survey results. 3.2 The Sample of Florida Drinking Water Systems The study focuses on a subset of 742 community water systems that serve at least 501 people in Florida counties, municipalities, cities, mo bile home parks, subdivision, and apartments. This section describes the selection procedure for the subset of Florida drinking water systems. According to US EPA criteria, public drinking water systems are the systems that serve at least 25 people or 15 service connections for at least 60 days per year (US EPA 2008). The database of Florida drinking water systems that are subject to the Federal Safe Drinking Water act requirements is maintained by the Florida Department of Environmental Protection (FDEP ) and is up dated quarterly (FDEP 2009). The database was downloaded for the use in the current project in April 2009. Characteristics of public water systems provided in the FDEP database are summarized in Appendix A. The FDEP database contains informat ion about 5,698 public drinking water systems in Florida. Out of them, 1,766 water systems are classified as community systems i.e. systems that serve at least 15 service connections used by year round residents or at least 25 year round residents (FDEP 2007) (note that two water systems
53 since the database also indicated that they served less than 25 people). Public drinking water systems are further sub divided into fi ve categories according to the size of the population they serve. The population served is the number of permanent residents plus the number of additional non transient persons (such as school children, office and commercial employees, and seasonal residen ts) to whom the system is available (FDEP, date not found). Out of 1,766 community water systems, we selected 799 systems that serve at least 501 people (i.e., the systems that were Finally, us ing information from FDEP Source Water Assessment & Protection Program (SWAPP), only the water systems with the following types of service areas were selected lso included systems for which the service areas were not systems that we included in the survey sample (Table 3 1). 3.3 Survey Instrument Development and Pre test T he survey instrument was developed by the team of faculty from the land grant universities in Oklahoma, Florida, Tennessee, and Arkansas participating in the Water Economics and Policy Team, Southern Regional Water Program (USDA). The team followed the re commendations for survey instrument design from Dillman (2009). The survey included the sections about: 1) characteristics of the water systems; 2) changes in water delivery and strategies used to respond to these changes; 3) water rates; and 4) non price conservation programs. Survey instrument is available in the Appendix B.
54 To pre test the Florida survey instrument, seven field expert (including water utility representatives and faculty in two academic institutions) were contacted. In addition, 34 comm unity water systems were randomly selected from the database of Florida drinking water systems. Each of the 34 systems was contacted by phone in three consecutive days, using the contact phone numbers provided in the FDEP database. Phone numbers for eight water systems were found to be disconnected or erroneous (24% of the sample). After the three attempted contacts, managers from 15 utilities responded to the phone call (44%), and 13 of them agreed to participate in the survey pre test (38%). Survey pre t est was implemented on line. Participants had the opportunity to provide comments and suggestions for each survey question. Responses were received from 12 out of 20 field experts and community water system managers who agreed to pre test the survey. The survey instrument was then revised according to the suggestions received during the pre test. The names of the managers who participated in the pre test (and the water systems they were affiliated with) were removed from the sample of water systems. Since some of the pre test participants managed more than one water system, twenty water systems were removed from the final list of water systems used for the survey distribution (i.e., remaining sample included 722 water systems). 3.4 Survey Distribution Five hundred eighty four contacts were identified for the 722 community water systems in the sample. Graduate students from the University of Florida and the Oklahoma State University made four attempts to reach every contact by phone. The calling script included a brief description of the survey, a question about the best person
55 in the water system to respond to the survey, and a question about the willingness to participate in the on line survey. Overall, 317 water system managers were willin g to participate in the survey, and provided their e mail addresses (54.2% of 584 contacts identified, or 43.9% of 722 water systems in the sample). At introductory e mail was sent to the water managers on August 20, 2009. The e mail described the study and emphasized the importance of responses from individual water systems On August 24, 2009 participants received an e mail with the link to the on line survey. On August 31 st an e mail message was sent reminding the participants about the survey. As of October 20, 152 responses were received, and 1 30 of them provided responses complete enough to be used in further analysis ( 4 1. 0 % of 317 contacts used to distribute the on line survey, or 1 8 .0% of 722 systems in the sample). Next, 621 systems were survey ed by mail (th e s e were the systems that did not reply to the on line survey, systems provided incomplete responses, and systems that were not included in the on were taken from the FDEP database The s urvey was administered in four steps: (1) a survey booklet with a cover letter was mailed to the water systems on Jan. 7 (first class mailing), followed by (2) a reminding postcard (Jan. 13), (3) the second survey booklet with a more urgent cover letter (J an. 15, bulk mailing), and (4) the last reminding postcard (Jan. 21, 2010). About one third of the surveys (27.2%) were returned as undeliverable due to incomplete or incorrect mailing addresses or missing mail receptacles. For the remaining 452 systems, as of March 16, 67 complete responses were received ( 14.8 % of 452 systems that received mail survey, or 9.3 % of 722 water systems in the sample).
56 To summarize, the o verall survey response rate (for both on line and mail survey) was 27 3 % (1 97 completed surveys for the sample of 722 water systems). 3 .5 Summary of Results 3.5.1 Water System Characteristics Survey respondents were asked about the size of their water systems ownership type customer base Water Management District jurisdiction, sources of w ater, and distribution capacity. Three quarters of responses (74.6%) were received from the systems located in the jurisdiction s of three largest water management districts: Southwest Florida, South Flo rida and St Johns River (Table 3 2 ). In comparison wi th the original sample of 722 water systems, there were fewer respondents from the South Florida Water Management District, and more respondents from Northwest Florida Water Management District. Eighty seven percent of responses were received from municipal, county, state or customer owned systems. Only 7. 6% of responses were from representatives of privately owned systems, which is significantly lower than the share of such systems in the initial sample of water systems (Table 3 2 ) M ore than ha lf of responses (53.2%) were received from the representatives of large or very large water systems (Table 3 2). Response rate among medium and small water systems was smaller. Finally, majority of the survey respondents (89%) indicated that their systems primarily relied on self supply or purchased ground w ater. Only 11% of system used surface water as the primary water source (Figure 3 1). Combining this information into the water use categories used by FDEP (2009), almost 80% of responses were
57 received from the systems that relied solely on groundwater for their w ater supply (79.8%), while 14.2% used both groundwater and surface water sources. In comparison with the original sample of 722 water systems used in this study, the response rate of systems t hat relied solely on groundwater was lower, while systems that used surface water only or a combination of groundwater and surface water seem to be overrepresented. According to the survey responses, t he volume of water delivered by the systems during no n drought period varied from about 12 thousand gallon per day to 346 thousand gallons per day (with the mean of 9.5 million gallons per day) (Table 3 4 ). On average, 74.5% of water was delivered to the residential customers (ranging from 3% to 100% for the individual systems), and 13.5% to commercial and institutional customers (ranging from 0% to 75%) (Table 3 4 ). On average, unaccounted water losses comprised 5% of total water delivery (with the range of 0% 22% ). Water uses also included industrial (4.1 % on average), wholesale and sale to other utilities (1.5% on average), and agricultural, oil and gas, and other uses (0.4%, 0.1%, and 0.8% on average, respectively). 3.5.2 Changes in Water Delivery A large number of respondents (42%) reported a decrease i n total water delivery of their water systems over the last 5 years (Figure 3 2 ). Twenty two percent reported an increase, and the remaining 36% reported no change in total water delivery. When asked about changes in per capita water delivery over the las t 5 years, 44% of respondents reported a decline, while only 12% of responde nts reported an increase in per capita delivery of their systems ( 44% of responded reported no changes )
58 Changes in regional economic activity were mentioned as the primary cause for the variations in the total water delivery by 50% of the respondents (Figure 3 3 ). Many systems reported economic growth, commercial development, and population growth in the last five years as the primary causes for water delivery increase. Other systems blamed the reduction in regional economic activit ies, population decrease, loss of major industries, and foreclosures for the reduction in water delivery The second m ost frequently mentioned cause for the changes in water delivery over the last five years were irrigation restrictions (combined with enforcement measures and fines for non compliance) (2 8 % of the respondents ). Water conservation by the customers, as well as changes in water rates and education and awareness programs were also mentioned by more than 10% of water systems. 56 % of respondents plan to improve infrastructure (includin g reduction in water loss). Half the respondents indicated that they will secure more water from the traditional ground and surface water sources, while 40% plan to secure new water supply from alternative sources (Figure 3 4 ). About 45% of the respondent s indicated that their systems plan on increasing water or sewer rates. Forty percent of respondents indicated that their systems will use (non price) demand side measures to meet future water demand. Forty five respondents plan to improve infrastructure ( including reduction in water loss). When asked about the factors that will significantly impact their meet future water demand, two factors were selected by more than half of the inefficient water use or waste by customer s (54% of systems ) and
59 ncreasing cost to treat water (Figure 3 5 ). Over 45% of the respondents also mentioned the need to meet regulatory requirements and increasing population. O nly 14% of the systems indicated that they expect difficulties in maintaining access to supply. O nly 28% of the respondents believed that long run changes in weather patterns (including regional climate change) would seriously affect water supply ( Figure 3 6 ). Forty All the responses to the open adapt to these long ure 3 7 ). One third of systems responded that they do not have a plan. Plans of the 36% of the systems include supply side measures (such as increase in utilization of traditional and alternative sources, increased recovery rate for the reverse osmosis systems, reuse systems, and deeper wells). Eighteen percent of systems plan to cope with long run changes in weather by promoting water conservation (for example, through education programs, drought ordinances, or inclining block rate structures). Note that the overall response rate to this question was very low (N = 55). This survey section about c hanges in w ater d elivery by water utilities concludes with two questions regarding whether the water utilities plan to increase capacity in the next five years. According to survey res pondents, 40% of the systems plan on doing so (Table 3 5 ). Further, thirty eight respondents provided description of specific projects their systems plan to implement to increase capacity. These projects can be integrated into five general categories (Fi gure 3 8). Over half of the respondents (53%) described
60 treatment and filtration projects. Forty three percent plan on tapping more groundwater by increasing the number and /or depth of the wells. Others are planning to increase surface/groundwater storag e systems and/or upgrade their distribution systems 2.5.3 Water R ates In addition to charging a fixed monthly fee, t wo types of volumetric water rate structures were used by the water systems for residential customers : uniform (when a constant per gallon water rate is charged for any volume of water used) and inclining block (when per gallon rate increases with the amount of water used). One hundred eighty systems shared their water pric e information. Approximately 85% of these systems had an inclining bl ock ra te structures; the remaining 15% had uniform rate structures. For the systems that have an inclining block rate structure, the number of blocks ranged from two to twenty one. The mean number of price blocks was 4.25 (Table 3 6) Rates ranged from $0/thousand gallon for the first block (i.e., customers paid only the base monthly rates) to $45.24/ thousand gallons (rate set by one of the systems for the water use above 20,000 gallons per month). For the systems that used uniform rate structures, uni t rates ranged from $0.69 /thousand gallon to $5.75 / thousand gallons, with the mean of $2.44 / thousand gallons. R espondents were asked to rate the importance of the factors consider ed in their water rate decisions (with 1 being the lowest impo rtance, and 4 being the highest) Cost of delivery was very important or to 83% of respondents (Figure 3 9 ). Repair and maintenance of infrastructure, future capital and infrastructure re investments, and regulat ory requirements were also very important or important to about 80% of respondents (
61 wasteful water use and customer satisfaction & attitudes were ranked very important or d of respondents. Only 21% of respondents ranked r evenue or profit requirements as very important or important Fifty one percent of the systems changed their water rate structure and 60% changed their average rates in the la st five years (Table 3 7 ) However, o nly 30% of the utilities have estimated how a change in water rates will impact water use. Of the 197 utility systems in the survey, 94 (52%) indicated that their utility changed their water rate structure in the last five years (Figure 3 10). Of these 94 utilities, 77 utility managers shared additional information on how water rate structure changed during the last five years. Sixty five percent of these 77 utility systems indicated that their systems changed their ra te structures to inclining block structures or introduced additional blocks to existing inclining block structures (Figure 3 11 A). Further, 2 3 % indicated that they increased rates for some of the blocks. The major reasons for changing rate structure are aggregated into four categories (Figure 3 11 B ). Fifty seven percent of the utilities changed their rate structure to meet financial needs. Financial needs incorporate a broad category including the need to meet operational costs, pay back loans, boost dec lining revenues and, keep up with inflation. Thirty six percent changed rate structure to promote water conservation, while 9% changed rates to adhere to requirements of CUP. Of the 197 utility systems in the survey, 184 responded to the question whether t heir utility changed their average rates in over the last five years. Sixty percent of the 184 (110 utility systems) of the utilities increased their average rates over the last five
62 years. Of these 110 utility systems, only 91 provided reasons for changin g their average rates. About 81% of these 91 utilities increased their average rates to meet financial needs, and another 5% to promote water conservation (Figure 3 1 2 ). Price elasticity of water demand (PED) is a measure of the responsiveness of the quant ity of a good demanded to a change in its price. It is calculated as the percentage change in quantity demanded by the percentage change in the price. Forty percent of respondents indicated that water is perfectly inelastic (Table 3 8 ). This means that a w ater rate increase will have no effect on the volume of water used. Approximately 50% of the respondents indicated that the demand is relatively inelastic to unitary elastic. O nly about 4% of respondents believed that residential water demand is relatively elastic or very elastic. Figure (3 13) summarizes responses to the question about the decision making authority related to water rate changes In over half of the systems responded to the survey, the utility/district manager recommends rate changes. Appr oximately 60% of the systems indicated that the city/county/state government makes the final decision regarding rate changes. 3.5.4 Non Price Conservation S trategies The survey responses suggest that in the majority (55%) of water systems responded to the survey the utility/district manager s recommend new conservation programs (Figure 3 14 ). The final approval for new conservation programs is decided by city, county, or the state government (49% of respondents), or by the utility board of directors (14% or respondents). Very few systems involve customers into recommending or approving conservation programs. Mandatory watering restrictions, education & awareness programs are the most widely used non price conservation
63 programs whereas rebates and retrofits and voluntary watering restrictions are used by relatively few systems (Figure 3 15 ). 3.5.5 Information about Price and Non Price Conservation Programs According to the survey respondents, attachment in water bill, public meeting, notice in loc al newspap er(s) were used by 75% 67 % and 53 % of the utilities to spread the word of rate changes and conservation programs to its customers (Figure 3 16 ). In turn, customers can learn about their water rates by contacting the utility, reading their water bills, or contacting their municipality (74%, 45%, 45% and 44% of the responses, respectively). Furthermore, 44% of the utilities have their own website where customers can access rate and conservation programs information. 3.5.6 Perceptions of P rice and N on P rice C onservation S trategies Several questions of the survey focused on how conservation pricing and programs affected system Economic theory suggests that charging a higher price lead s to an increase in revenue if the demand for a commodity is inelastic. On the other hand, i f the commodity demand is elastic, an increase in price would lead to a decrease in revenue. In the earlier section, over 70% of the respondents indicated that water was pe rfectly inelastic or relatively inelastic. Hence charging conservation prices ( that usually means higher rates) should increase revenue s However, only 23% of respondents indicated that conservation rates would increase revenue. On the contrary one third (34%) of the respondents indicated that there would be no change in revenue; and about 35 % indicated that revenue would decrease (Figure 3 1 7 A). In turn, 61% of respondents believed that conservation programs will decrease total revenue of the ir utility companies. This makes economic sense as conservation
64 revenue. Thirty percent of respondents indicated that revenue would not change and only 3% indicated that revenue would actually increase (Figure 3 1 7 A). Over one third of the respondents (37% and 34%) indicated that the revenue will not fluctuate with the introduction of conservation pricing and conservation programs (Figure 3 1 7 B). Thirty five percen t of utility managers indicated that conservation pricing increases revenue variability, while 13% indicated lower variation in revenue. In turn, 27% of utility managers indicated that conservation programs increases revenue variability, while 20% indicate d lower variation in revenue. A budget is an estimation of the revenue and expenses over a specified future period of time. A budget surplus means profits are anticipated, while a balanced budget means that revenues are expected to equal expenses. A defic it budget means expenses will exceed revenues. Eleven percent of respondents indicated that conservation rates would cause a budget surplus (Figure 3 1 7 C). This percent is slightly smaller than the percent of respondents who associated conservation rates with respondents anticipate an increase in operating and management expenses associated with implementation of conservation rates. Almost half of the respondents (46%) beli than a quarter of respondents (27%) indicated that conservation pricing would lead to budget deficit. In contrast, conservation programs are believed t o create a budget def icit by 44% of the respondents. Further, 41% indicated no change, and only 1% suggested a budget surplus as a result of conservation programs (Figure 3 1 7 C).
65 The next set of open ended questions in the survey pertain ed to comparative efficiency of price and non price conservation programs. Efficiency in the survey was least) water per dollar spent on the program. Twenty e ight percent of the 61 respondents indicated that use restrictions were the most efficient conservation measures (Figure 3 1 8 A). Only 6% suggested that conservation prices were most efficient in reducing water consumption. Only 40 respondents provided answers to the question about the least efficient co nservation program s. Among these respondents, 28% gave examples of various rebate a nd retrofit programs, and 18% referred to education and awareness programs (Figure 3 1 8 B). 3.5.7 Perceived B arriers for I mplementation of C onservation P rograms The final section of the survey asked about the factors that might prevent utilities from implementing conservation programs or conservation pricing. Out of the 150 system managers that responded to this question, a lmost half of respondents (45%) cited lim ited staff, and 42% indicated that they do not currently face water shortage (Figure 3 19 ). Revenue requirements were mentioned by 38% of respondents. This result suggests that a large percentage of systems do not adopt conservation programs and pricing pr ograms due to resource constraints. This concludes the section on rate making decisions and test the hypotheses detailed in the previous chapter. Model 4 1 includes only Model 4 2 incorporates cost, institutional, and demand factors.
66 Table 3 1. Sample of community water examined in this project Description Number Percent Community Water Systems by Water Source Ground Water Only 692 93.23 Surface Water Only 1 0.1 Combination of surface and ground water 49 6.6 Total 742 100 Community Water Systems by Owner Type Municipal, county, or state owned 413 56 Private investor 239 32 Investor / licensed public utility 45 6 Subdivision 14 2 Cooperative 8 1 Water association 18 2 Other / unknown 5 1 Total 742 100 Community Water Systems by WMD Northwest Florida 103 13.9 South Florida 249 33.6 Southwest Florida 175 23.6 St. Johns River 176 23.7 Suwannee River 39 5.3 Total 742 100 Community Water Systems by Population Served Small 367 49.5 Medium 141 19.0 Large 195 26.3 Very large 39 5.3 Total 742 100 Community Water Systems by Primary Service Area Apartments 9 1.2 County 24 3.1 Mobile home park 91 12.3 Municipality / city 353 47.6 Not identified 18 2.4 Other 4 0.5 Subdivision 242 32.6 Unincorporated 1 0.1 Total 742 100 jurisdictions (see Appendix A ).
67 Table 3 2. Water s ystem c haracteristics Description Sample of Water Systems (%) Survey Respondents (%) What water management district(s) is your utility in? (circle all that apply) Northwest Florida 13.9 18.5 South Florida 33.6 24.3 Southwest Florida 23.6 24.9 St. Johns River 23.7 25.4 Suwannee River 5.3 6.9 Total 100 100 (N=189) ownership structured? (circle one answer) Municipal, county, or state owned 56 76.2 Private investor owned* 38 7.6 Other private (subdivision, water association) 4 2.1 Customer owned nonprofit or cooperative 1 10.8 Other / unknown 1 3.2 Total 100 100 (N=185) Please, indicate the approximate population size served by your system (select one) Very small 0 1.1 Small 49.5 22.6 Medium 19.0 23.1 Large 26.3 36.0 Very large 5.3 17.2 Total 100 100 (N = 186) In a typical year, what are primary and secondary sources of water for your utility? (circle all that apply) Ground Water Only 93.23 84.7 Surface Water Only 0.1 6.4 Combination of surface and ground water 6.6 8.5 Total 100 100 (N = 189)
68 Table 3 3 Number of gallons of metered water delivered per day during non drought periods Number of Respondents Minimum Maximum Mean Standard Deviation 157 12 346,000 9,504 30,745 Table 3 4 P ercent of w ater delivered to customer classes Sectors Mean (%) Standard Deviation (%) Minimum (%) Maximum (%) Residential 74.5 17.8 3.0 100.0 Industrial 4.1 10.0 0.0 82.0 Commercial and institutional 13.7 13.5 0.0 75.0 Oil & Gas 0.1 0.5 0.0 5.0 Agricultural 0.4 1.4 0.0 10.0 Wholesale and sale to other systems 1.5 8.2 0.0 97.0 Unaccounted water loss 5.0 5.3 0.0 22.0 Other 0.8 2.5 0.0 18.0 Table 3 5 Percentage of utilities planning to increase delivery capacity in the next five years Response Percent No 60.3 Yes N = 184 39.7 Table 3 6. Analysis of b locks for systems with inclining block rates Statistic Number of systems with inclining block rate structure 15 3 Mean number of price blocks 4.2 5 Standard deviation 2.1 Minimum number of blocks 2 Maximum number of blocks 21
69 Table 3 7 Changes in w ater r ates Description Percent Has your utility changed its water rate structure in the last five years? No 48.1 Yes N 51.9 181 Has your utility's AVERAGE rates changed in the last five years? No 40.2 Yes N 59.8 184 Has your utility estimated how a change in water rates will impact water use? No 32.8 Not Sure 37.7 Yes N 29.5 183 Table 3 8 If residential water rates increased by 10%, what change in total gallons delivered would you expect? Percentage change in water demand Response PED Interpretation Increase <5% 1. 9% N/A erroneous answer Increase 5 10% 2. 5% N/A erroneous answer No Change 4 0 1% 0 perfectly inelastic Decrease <5% 3 2 1 0 0.5 relatively Inelastic Decrease 5 10% 19.1 0.5 1 unitary elastic Decrease 10 15% 3. 7% 1 1.5 relatively elastic Decrease >20% 0. 6% >2 very elastic N=162
70 Figure 3 1. Source of w ater Figure 3 2 Change of water delivery in the last five years 5% 6% 83% 6% 2% 3% 8% 13% Surface water, selfsupply Surface water, purchased from other utility Ground water, selfsupply Ground water purchased Primary Secondary Dec >10% Dec 5%10% Same Inc 5%-10% Inc>10% Total Delivery Change(N=173) 14% 28% 36% 17% 5% Per-Capita Change(N=161) 12% 32% 44% 9% 3% 0% 5% 10% 15% 20% 25% 30% 35% 40% 45% 50%
71 Figure 3 3 Primary causes for change in water demand Figure 3 4 Water systems s to meet future water demands 40% 40% 45% 50% 56% Secure new water supply from alternative sources Demand-side programs to promote water-use efficiency and conservation Increase water or sewer rates Secure new water supply from traditional ground and surface water sources Replace or improve infrastructure
Figure 3 Figure 3 Ina b Inabi L e Increasi n Inef f 3 -5. Utilitie s 3 -6. Do yo u negative b ility to maint a lity to maintai n e akages/loss i n n g cost to me e regulatory re q in c Increasing f icient use or w s plan to m u believe th ly impact y o O a in access to s u n withdrawal l e n old infrastru c e t testing and o q uirements c reasing popul a cost to treat w w aste by custo Yes, m eet future w at long-run o ur utilitys O ther u pply e vels c ture o ther a tion w ater mers Not Sure, 4 28% 72 w ater dem a changes i n available w 6% 14% No, 30% 4 2% a nds n weather p w ater suppl 24% 32 % p atterns wi l y? % 45% 47 % l l seriously % 52% 54% and
Figure 3 Figure 3 Lea k Conser v Surface / 3 -7. Plans t 3 -8. Projec t k age / mainte n v ation Progra m Supply mea s Distributi / Ground/Aqui f New Gr o Treatmen t t o adapt to t s in increa n ance of infras Planni m s / demand re No plan a s ures (includi n on System f er storage Other o undwater t /Filtrationlong-run c h se delivery tructure ng stage Other duction a vailable n g reuse) 11% 73 h anges in w capacity o 2% 7% 9 % 21% 24% w eathe r o ver next fi v % 18% 42% v e years 53% 33% 36%
74 Figure 3 9 Determinants of water rates 7% 5% 3% 35% 2% 1% 1% 1% 24% 12% 9% 21% 11% 8% 8% 8% 21% 20% 20% 15% 11% 13% 12% 8% 15% 39% 37% 6% 32% 34% 33% 32% 6% 24% 31% 35% 44% 45% 46% 51% Revenue or profit requirements Consumers expectations & attitudes Reduce wasteful water use Subsidies for non-water utility operations Future capital and infrastructure reinvestment Repair and Maintenance of infrastructure Regulatory requirements Cost of delivery (other than regulatory requirements) 4 3 2 1 N/A
Figure 3 Figure 3 3 -10. Perc e years 3 -11. Chan e ntage of u t ge of rate s Yes 52% t ilities that c s tructure in 75 c hanged t h the last fiv e No, 8 h eir rate str u e years 7 u cture in th e last five
Figure 3 Figure 3 Regulat o Utility's C City / 3 -12. Reas 3 -13. Deci s o ry requireme Encourage co n Meet fina n C ustomers (by Corpor a / county/state g Utility's boar d Utility/dist r R e ons for ch a s ion makin g nt for CUP Other n servation n cial needs direct vote) a te decision Other g overnment of directors r ict Manager e commen d a nging rate g authority r 4% 4% 5% 1% 9% 7% 1 1% 2% 4% 4% 10% 11 % d s Change 76 structure r egarding r a 3% % Final a te chang e Approval e s 81% 59% 54%
77 Figure 3 1 4 Decision making authority regarding conservation programs 1% 1% 3% 14% 49% 6% 2% 4% 5% 6% 12% 55% Utility's Customers (by direct vote) Corporate decision Other Utility Board of Directors City/county/state government Utility/district Manager Recommends Change Final Approval
78 Figure 3 1 5 C onservation programs used by water systems 1% 16% 21% 10% 3% 2% 4% 2% 4% 9% 1% 6% 6% 6% 5% 5% 6% 6% 16% 10% 7% 16% 18% 22% 26% 28% 31% 46% 61% 69% Other Rebates and Retrofits Voluntary watering restrictions Water budgets and/or audits Florida friendly landscaping Efficient irrigation systems Leak detection at homes New water meters Education/Awareness Programs Mandatory watering restrictions Currently Using ONLY Currently Using & Have used in past Have used in Past ONLY
79 A B Figure 3 16. Customer Information A) Notification channels regarding water rates and conservation programs, B) Sources for customers 8% 18% 41% 43% 53% 67% 75% Other Local TV and radio stations Posting on utility's webpage Special mail out Notice in local newspaper(s) Public Meeting Attachment in water bill 12% 22% 24% 39% 44% 45% 45% 74% Utilty newsletter Utility's website Annual Report available to public Visit the municipal website Visit the utility's website Contact the municipality Water bill Contact the utility
80 A B Figure 3 17 Effect of c onserv ation pricing and programs. A) On total revenue, B) O n revenue variability, C) O n total budget 23% 34% 35% 3% 30% 61% Generally Increase No Effect Generally Decrease 35% 34% 13% 27% 37% 20% More Variable No effect Less Variable 27% 46% 11% 44% 41% 1% Creates a deficit No Effect Creates a surplus Conservation pricing Conservation programs C
Figure 3 Lea k Conser v N Irrig Reclai m Rebat e d e Use r 3 -18. Effec t efficient. k detection ation rates ew meters ation audit m ed / reuse Education Other e / low flow e vices r estrictions t iveness of 5% 6% 8% 9% 9% 11% 11% 12 % A conservati % 28% 81 A on progra m L e U s Education Re b m s. A) Mos t e ak detection s e restriction / awareness Other b ate / retrofit t efficient B 3% 10% 1 B ) Least 1 8% 20% 28%
Figure 3 3 -19. Barri e C No t C Conser v Decision mak p o e rs to succ e C urrently no s h Reven u t enough fund i C ost effective n v ation rates im custom e Not enough Regulat o e rs have little o licies effectiv e e ssful con s Limited st a h ortage of wat e u e requireme n i ng for progra m n ess of progra m pact low inco m e rs political supp o o ry requireme n awareness of t e ness Ot h 82 s ervation p r a ff e r n ts m s m s m e o rt n ts t he h er r icing and p 19 % 12% 9% p rograms 3 28% 25% 25% % 45% 42% 38% 3 7%
83 CHAPTER 4 MODEL SPECIFICATION 4.1 Overview As discussed in the literature review (Chapter 2), existing studies identify the cific residential water rate structures: a) cost of water utility; b) water demand characteristics; and c) institutional factors. In this thesis, a linear regression technique (OLS) is used to determine the relative importance of various factors that influ ence characteristics of the rate structure s adopted by Florida utilities. Accordingly, two models have been used to 4 1 includes and i nstitutional factors. Model 4 2 incorporates cost, institutional, and demand factors. 4.2 Hypothesized Model 4 1 M odel 4 1 incorporates a set of cost and institutional factors considered by Florida utilities in determining their water rates. L og p i j 1 q j + 2 F i 3 S i + 4 IN i j + ij ( 4 1) where i indexes water utilities, p i j is the marginal rate (per thousand gallon) charged by utility i to residential customers inside city limits for the water use level j q j is the water use level; F i is the fixed monthly fee charged by the utility i ; S i is a vector of cost factors ; and IN i j is a vector of institutional factors The specification of Model 4 1 takes the form of log level ( since the dependent variable is represented by a natural logarithm of the marginal water rate ) In a log level model, the coefficients are respect to an independent variable (Wooldridge, 2009) For example, if a n independent
84 variable has a n estimated coefficient of .2153, it is interpreted as follows: a one unit increase in the variable will increase marginal water rates by 21.53%. A log level specification was used to make the distribution of the model residuals, ij match more closely the normal distribution and to reduce possible heterogeneity (which is required by the OLS estimation technique, as discussed in detail in Chapter 6) 4.2.1 Dependent Variable The dependent variable in the model is the natural logarithm of marginal water rate (per thousand gallon) charged to residential customers (inside city limits) for the water use level q j Marginal rates are defined as the rate paid by the customers for the last thousand gallon of water they used. For the inclining block rate structures, marginal rates are increasing with the water use, while for the uniform rate structures the marginal rates are constant. These marginal rates were collected from the survey of Florida water utilities (described in chapter 3) Complete rate schedule is available for 180 water systems These systems used inclining or uniform rate structure s. Log of the dependent variable Price is taken to reduce possible heterogeneity and multicollinearity problems. Moreover, such definition of the dependent variable makes it possible to directly interpret the model coefficients as elasticities. By definition, water rate structure is a schedule of fees charged by water utilities for different water use levels. T o approximate the entire water rate schedule, marginal water rates p ij were evaluated for five water use levels, q j The water use levels considered in this study are the same for all u tilities in the sample, and are equal to 4000, 8000, 12000, 16000, and 20000 gallons, and are intended to represent the range of water consumption levels for low income / low use to high income / high use
85 customers Since five marginal quantities for each of the 180 water systems are considered, a total of 900 price observations, log p i j are included into the model. 4.2.2 Independent Variables The vector of five water use level s q j is described above. A s discussed in the Chapter 2, each rate structure includes a fixed monthly fee and a schedule of variable fees that vary The variable fees are captured in the model through the marginal prices, p ij To examine if margina l rates charged by water utilities are correlated with the fixed minimum fees the minimum fee variable F i is included in to the model. The other independent variables are categorized into three groups. The first group consists of a set of supply factors that drive the cost of water utilities. The second group includes institutional factors that drive decisions to select specific water rates. The third group contains a set of demand factors that are e xpected to influence the prices set by water utilities. 4.2 2. 1 Supply f actors t hat d rive up c ost of w ater s ystems Economic theory suggests that for a firm to remain operational, it must at least cover its cost of supplying water. All cost variables are expected to have positive coefficients, that is, as costs incurred by a utility increase, I expect the utility to charge higher water rates. Cost factors would ideally include actual fixed, operating, maintenance and capital expenses for providing service s Further, to reflect water resource scarcity and possible negative externalities associated with water supply service, an ideal model would include opportunity cost variable s and economic value of the externalities. However, th e data on the actual cost of water supply for the Florida
86 water systems are difficult to obtain Instead, five proxies obtained from the survey of Florida water utilities are used to estimate the supply side cost. Past resear ch indicates that utilities that rely on surface water often incur higher costs of water treatment and higher infrastructure costs than a comparable utility relying on ground water sources (Thorsten, Eskaf, & Hughes, 20 08; Reynaud, Renzetti, & Villeneuve, 2005) In this study, survey responses about their water source s were categorized into three categories: 1) groundwater only, 2) surface water only, and 3) combination of groundwater and surface water. Thre e dummy variables are coded as dummyGW, DummySW, and DummyMW We expect a negative coefficient for dummyGW The second variable related to the utility cost is whether a utility has its own supply of water and treatment facility (self supplied) or whether it purchase s water from other utilities (purchased) The hypothesis is that purchased water costs the utility more than self supplied water (Thorsten, Eskaf, & Hughes, 2008) Survey responses used to define this variable were 1) self supplied ( DumwaterS ), 2) purchased ( DumwaterP ) or 3) a combination of both ( DumwaterM ). I expect to have a negative coefficient for DumWaterS and DumwaterM ( given that DumWaterP is the reference category) A water source and purchased water system interaction term is also added to the model ( Self_Ground ). I expect to find the highest water rates for among the utilities that rely on purchased surface water. The third proxy of cost is the average per day delivery ( in million gallons) ( Deli vPerDay ). Due to the economies of scale, the average cost of water delivery is expected to decrease as the water supply volume increases. That is, I expect that larger
87 utilities will have lower average cost and hence, lower prices. Hence, I expect DelivPerDay variable to have a negative coefficient in the model Further, t o test if the economy of scale changes to a diseconomy at a certain delivery level ( that is, average cost start to rise with the increase in delivery volume ), a squared delivery p er day variable ( DelivPerDaySq ) is also included into the model I expect a positive coefficient for DelivPerdaySq The fifth proxy of cost is the size of population served by water system (referred to as Q5pop ) Similarly to DelivPerDay this variable is expected to reflect the economy of scale, when larger utilities incur lower distribution costs and hence, charge lower prices In addition, smaller utilities may have different rate setting objectives than larger utilities. The survey r esponse choices used to define this variable are as follows: (a) 500 people or less (very small), (b) 501 3,300 people (small), (c) 3,301 10,000 people (medium), (d) 10,001 100,000 people (large), and (e) more than 100,000 people (very large). Very small and small utilities are aggregated and coded as one variable CapDumSmall, whereas large and very large utilities have been aggregated as CapDumLarge Medium size utilities are coded as CapDumMed The expectation is that larger utilities will charge lower prices and therefore variables CapDumMed and CapDumLarge will have negative coefficients 4. 2 2.2 Institutional f actors that influence w ater r ates Three institutional factors are incorporated into the model: ( a) utility ownership type (b) Water Manageme nt District (WMD) jurisdiction and c) water conservation as a rate setting priority Although revenues of all water utilities are regulated, I expect municipally (or state) owned utilities to charge the lowest water rates. This is because according to the AWWA M1 Manual, private ly owned utilities can incorporate a small
88 percentage of return s into their rates. Hence, it is expected that municipality county or state owne d utilities will have lower prices compared with utilities of other ownership types In the utilities survey, the ownership of utilities are classified as: 1) city, county or municipally owned, 2) customer / privately owned, 3) owned by water association or cooperative, 4) other public, and 5) other private Utilities owned by city, county or municipality are coded as DumMuni while all other forms of ownership (2 5) were aggregated as DumOther Accordingly, I expect the coefficient of DumMuni to be negative when DumOther is the reference category. Florida WMDs differ in their requirements related to permits and residential water rates (as discussed in Chapter 1), and hence, it is assumed that WMD jurisdiction will play a role in how utilities price their water. Jurisdictions of the five WMDs Northwes t Florida, South Florida, Southwest Florida, St. Johns River, and Suwannee River are referred to as dummy variables CapDumNF, CapDumSF, CapDumSWF, CapDumSJR and CapDumSR respectively. South Florida is used as the reference WMD. Finally, utilities can pursue different objectives in their water rate design including water conservation, water affordability ease of implementation, etc. ( see Chapter 2). Water utilities aimed at encouraging water conservation are hypothesized to use higher rates to incent ivize their customers to reduce water use. It is expected that such utilities will be located in the areas with limited water supply (and hence, high opportunity costs of water) and high discretionary water use levels. In such areas, to achieve economicall y efficient level of residential water consumption, utilities need to charge higher rates to reflect high opportunity cost of water and to discourage low value
89 discretionary uses. It is hypothesized that utilities focused on water conservation goal will use both price and non price conservation programs. Hence, implementation of non price conservation programs (such as mandates, education awareness programs, rebates and retrofits, landscaping projects, leak detection and new toilet appliances) is used in the model to reflect water conservation objective of water utilities. Based on the survey of water systems, dummy variable DumConsv is equal to one if utilities report current and/or past use of non price conservation programs (and zero otherwise). It is DumConsv will have a positive coefficient in the price model Further, a n interaction term DumConsv_Qty ij ( defined as a product of DumConsv and q j ) has been included to test whether the rates are higher (and/or increase faster) for the w ater utilities aimed at encouraging water conservation To understand the dynamics of the interaction variable, for simplicity, assume for a moment that all other cost and institutional variables are excluded from the model Then, Model 4 1 can be present ed as: Log (Prices) ij = + 1 DumConsv i + 2 Quantity1 j + 3 DumConsv_Qty ij + ij ( 2 ) When utilities do not have any conservation efforts, ( DumConsv i = 0) t hen the intercept for the model is equal to and the slope is 2 In turn, w hen a utilit y employ s conservation efforts ( DumConsv i =1); then the model intercept is equal to ( + 1 ) and the slope is ( 2 + 3 ) In other words the coefficient 1 measures the difference in the intercepts between the utilities with and without conservation programs, while 3 measures the difference in the slope s (Fig. 4 3). The null hypothes i s tested is that a) there is no difference in intercept for utilities encouraging water conservation and those that do not (i.e. H o : 1 = 0 ) and b) that the
90 relationship between marginal water rates ( log p ij ) and water use quantities ( q j ) is independent from the water conservation objectives of the water utilities ( H o : 3 = 0 ). If the null hypothesis is rejected, then it can be concluded that water rates depend on priorities 4. 2 .3 Number of O bservations As mentioned above, 180 water systems provided complete rate inf ormation as a part of the survey of water utilities Five rates are included in the analysis, corresponding to the five quantities, resulting in a total of 900 observations. Of these, 220 observations had missing information for at least one of the indepen dent variables and were deleted from M odel 4 1. Hence the total number of observations in Model 4 1 is 680. 4. 3 Hypothesized Model 4 2 In addition to cost and institution variables introduced in Model 4 1, Model 4 2 is used to test the hypothesis that dema nd factors also play a role in deciding the rates charged by water utilities. Specifically, it is expected that the rates will be higher in the areas with higher demand Accordingly the Model 4 2 is estimated as follows: Log p i j 1 q j + 2 F i 3 S i + 4 I N i j + 5 D i + i j ( 4 2) where i indexes water utilities, p i j is the marginal rate (per thousand gallon) charged by utility i to residential customers inside city limits q j is the water use level; F i is the minimum fixed fee; S i is a vector of supply factors that drive the cost for utility i; IN i j is a vector of institutional factors ; D i is a set of demand variables, and i j is the error term. The dependent variable and all cost and institutional variables are the same as in Model 4 1. In addition, Model 4 2 incorporates several demand factors that are
91 expected to influence how water utilities set their water rates. Since the data on water use level for individual groups of customers were not available, d emand factors are estimated on the aggregate ( city ) level. Several demand factors were considered for the level of the cities in which the utilities are located, and include (a) log median household income, (b) percentage of population over sixty five years old, (c) percent of resid ents in poverty, ( d ) logged annual mean temperature, and ( e ) logged annual mean logIncome perc65 povrate ln temp ln precip Variable logincome i s expected to have a positive coefficient in M odel 4 2 Higher income households are more likely to consume more water and to use a large portion of their total water consumption for discretionary uses ( e.g., irrigating larger gardens and washing cars ) Si nce utilities in high income areas can be facing higher water demand, they are expected to charge higher prices. In addition, utilities serving high income customer s with large discretionary water uses may be more interested in water conservation, and hen ce, they are expected to set higher prices. pay for water also increases with income, and hence, water affordability concern will not constrain the water rate level s in high income service areas A log specification allows me to inte rpret the relationship between income and water rates in terms of elasticity In contrast, high poverty rates in the service area imply low ability to pay for water. Variable povrate refers to the poverty rate (in percent of total population ) and is expected to have negative coefficients in M odel 4 2 Likewise, communities with an older population are expected to resist high water rate s as their ability to pay decreases. If this perc65 should be negative Li terature suggests
92 that (Thorsten, Eskaf, & Hughes, 2008) On the demand side, all else constant, higher t emperatures often mean higher demand for discretionary use s (such as water ing lawns and filling up swimming pools). To stimulate water conservation in such high use areas utilities are expected to set higher rates. On the water supply side, higher tempera tures can lead to more evaporation (that is important for utiliti es relying on surface water sources ) and is expected to increase service. Both supply side and demand sid e effects should result in a positive coefficient in the price model In turn, high precipitation could mean more abundant supply of surface water (supply side effect) and a lower water demand (demand side effect). Basic economics suggests that water rates will be lower if surface water is abundant in supply, all else equa l. Based on this theory, I expect a negative coefficient for precip 4. 3 .1 Selection of D emand P roxies for Model 4 2 Using an OLS regression model with the five demand variables it was identified that t he five demand proxies were jointly significant at 99 % significance level with an adjusted R 2 of 0.0336. Next, a independent variables out of the five to be used in complete Model 4 2. The selection criteria used was statistical significance at the 85% level. Three out of five variables were significant at the 85% level (Table 4 1). Based on this selection criterion, three demand factors were selected for M odel 4 2: a) lnTemp b) povrate and c) lnincome The remaining two demand variables lnPrecip and Perc65 were dropped from Model 4 2.
93 4. 3 .2 Number of O bservations Model 4 2 uses the same 900 observations used in Model 4 1. Of the se 900 observations, 250 had missing observations for at least one of the independent variables These missing observations w ere removed. Hence, the total number of observations used in Model 4 2 is 650. 4.4 Summary of D efinition of Variables and D escriptive S tatistics This section defines the independent variables used in the two models. Table 4 2 summarizes the independent variables, their categories, the expected sign of the predicted coefficients, and hypotheses tested Table 3 summarizes key descriptive statistics of independent variables. Finally, all the sources of data are provided below. 4.5 Data Sources Data used in this study is amassed from various sources. Water utility characteristics are collected using a survey of utility systems in Florida (see Chapter 3). City level demand characteristics are collected from the 2000 U.S Census (Census, 2000) While 2010 figures would add more accuracy to the model, these recent figures are not yet available. Annual temperature and rainfall data is derived from the Southeast Regional Climate Center (SRCC) (Center, 2010) and the National Oceanic and Atmospheric Administration (NOAA) (Administration, 2010) The climate variables are 30 year (1971 2000) normal mean annual temperature ( temp ) and precipitation ( pr ecip ) obtained for 137 weather stations located across the state of Florida (Center, 2010) The 30 year normal mean temperatures and precipitation data are matched against the 180 utility systems. For cities that did not have their own weather station, the data from the closest
94 weather station was used. Temperature is measured in degrees Fahrenheit and precipitation is measured in inches.
95 Table 4 1. Summary of s tepwise s election of demand v ariables Step Variable Included Par tial R2 Model R2 C(p) F Value Pr>F 1 lnTemp 0.0227 0.0227 9.5954 16.08 <.0001 2 Povrate 0.0056 0.0282 7.6073 3.96 0.0469 3 lnIncome 0.0089 0.0371 3.2303 6.38 0.0117
96 Table 4 2. Summary of h ypothesized c oefficients Parameter Data Source Variable Explanation Factor Category Predicted Coefficient Coefficient Explanation Quantity 1 Survey Quantity used Positive Prices increase with quantity DumConsv Survey Non price c onservation programs used Institutional Positive If Conservation programs used, higher prices Water source Survey Primary source is ground, surface or mixed Cost Varies Surface water use implies higher water treatment cost and rates Water Survey Is water self supplied, purchased or mixed Cost Varies Purchased water results in higher cost and rates Size Survey Size of utility Cost Varies Larger systems benefit from lower costs Location Survey 5 WMDs Institutional Varies V ary due to difference s in policies Ownership Survey Ownership type of utility Institutional Varies Municipality might charge lower prices D elivPerD ay Survey Delivery Per Day in mgd Cost Negative Economies of scale DelivPerDay Sq Survey Squared DelivPerday Cost Positive Reflects Diseconomies of large scale logIncome Census Log median household income of city Demand Positive Ability to pay increases Perc65 Census % of residents over 65 Demand Negative Elderly residents oppose high rates Povrate Census Poverty rate Demand Negative Ability to pay decreases Pop_CAGR Census Annual Growth rate of county Demand Positive Increase in demand drives prices up LogTemp SRCC* Log Annual Temperature Demand Positive Higher water demand logPrecip SRCC Log Annual Precipitation Demand Negative Lower water demand Southeast Regional Climate Center
97 Table 4 3. Descriptive s tatistics Variable Mean Std Dev Minimum Maximum BaseFee ($) 11.85 5.41 3.00 28.94 Quantity1 (thousand gallon) 12.00 5.66 4.00 20.00 DumConsv (% utilities) 60% 49% 0.00 1.00 dummyGW (% utilities) 90% 30% 0.00 1.00 dummySW(% utilities) 3% 17% 0.00 1.00 dummyMW (% utilities) 7% 26% 0.00 1.00 DumWaterS (% utilities) 77% 42% 0.00 1.00 DumWaterM (% utilities) 18% 38% 0.00 1.00 DumWaterP (% utilities) 5% 22% 0.00 1.00 DumSmall (% utilities) 17% 37% 0.00 1.00 DumMed (% utilities) 26% 44% 0.00 1.00 DumLarge (% utilities) 57% 50% 0.00 1.00 DumDeliveryYes (% utilities) 23% 42% 0.00 1.00 DumNWF (% utilities) 14% 34% 0.00 1.00 DumSR (% utilities) 8% 27% 0.00 1.00 DumSJR (% utilities) 28% 45% 0.00 1.00 DumSWF (% utilities) 25% 43% 0.00 1.00 DumSF (% utilities) 25% 43% 0.00 1.00 DumMuni (% utilities) 81% 39% 0.00 1.00 DelivPerDay (million gallon) 105.15 324.42 0.12 3460.00 DelivPerDaySq (million gallon) 116155 1019611 0.01 11971600 LogTemp (F) 71.68 2.86 65.90 76.70 LogPrecip (inches) 55.09 6.52 44.58 69.48 perc65 (% of customers) 21% 11% 6% 61% logIncome (thousand dollars) 37.15 12.83 17.33 90.25 Povrate (% of customers) 15% 9% 2% 40% Pop_CAGR (Annaual population growth) 2% 1% 0% 7%
98 Water Rate C onservation Efforts Slope = ( 2 + 3 ) 1 ) Diff in slope = 3 No Conservation Efforts 1 2 Quantity Figure 4 1. Expected difference in slopes between utilities encouraging water
99 CHAPTER 5 EMPIRICAL RESULTS 5.1 Overview As indicated in the methodology chapter, Model 4 1 includes cost and institutional variables. Cost variables reflect water supply characteristics only as utilities evaluate their rate structures to ensure that their rates meet their costs. Institutional variables reflect institutional characteristics hypothesized to influence water rates. In turn, Model 4 2 includes variables de scribing water supply co st, institutional drivers as well as water demand characteristics. The next sections will discuss the results of the two models. 5.2 Model 4 1 : Cost and Institutional Factors For Model 4 1 an adjusted R 2 is .2125 indicating that the model explains 21.25 % of the variation in log prices. All of the cost factors have the correct expected sign and are statistically significant. In turn, the institutional variables are also important for explaining the differences in water rates (Table 5 1). The overall model is significant with 99% confidence indicated by an F value of 12.45. The coefficient of variable dummyGW is negative and statistically significant (at an alpha value of 1%), indicating that utilities relying on ground water sources charge 16.88% lower rates. This is similar to findings from Thorsten et al (2008) and Renaud et al (2005), who linked the lower rates with low costs incurred by water utilities that rely on ground water sources. Further, utilities that have their own supply of water ( DumWaterS ) charge lower rates compared with the utilities that purchase all or a part of their water ( DumWaterP and DumwaterM ). Taking purchased water as the reference category, the coefficients of DumWaterS and DumWaterM are .2152 and .1343
100 indicating t hat utilities that supply their own water charge 21.52% lower rates, while utilities that rely on both self supplied and purchased water charge 13.43% lower rates Compared with small size utilities, medium size utilities charge 9. 8 % lower rates (variable is statistically significant at 10% conf idence level only ). Although t he coefficient of the dummy variable indicating large utilities ( DumLarge ) has the correct expected negative sign, it is not statistically significant This result provides a partial su pport to hypothesis (2a) that larger utilities benefit from the economy of scale, and hence, can charge lower rates. This partial significance disappears, however, once demand factors are added in Model 4 2. According to the estimation results, the relati onship between the log of water rates linear. The coefficient of the variable DumDelivPerDay is negative and statistically significant at alpha level of 1%. In turn, the coefficient of the squared delivery level (DumDeleliPerDaySq) is positive and statistically significant at alpha level of 1%. This difference in the signs implies that an increase in the total water delivery levels results in reduction in water rates; howe ver, this reduction becomes smaller and smaller as delivery becomes larger and larger. At some point, the effect of the increase in the total water delivery on the water rate becomes positive Following (Wooldridge, 2009) to estimate the effect of the total water delivery on the water rates, I differentiated Model 4 1 with respect to DelivPerDay Using the estimated values of the coefficients for DelivPerDay and DelivPerDaySq change in log rates can be estimated as: and
101 For example, an increase in delivery per day from 10 million gpd to 20 million gpd decreases price by about 0.5%. These results confirm hyp othesis (1) that water utilities design their water rates to reflect their cost structure. This result is similar to Thosten et al. (2008) who showed that utilities that rely on purchased water need to pay a price premium to the wholesale water supplier. As a result, the cost of such utilities can be higher compared with the utilities that have their own source of water. Addition of demand variables in Model 4 2 does not change the significance or value of coefficients by much. The institutional variables seem to be less relevant than the cost variables. First, I hypothesized in (2a) that utilities owned by municipalities charge lower rates than privately owned utilities. Results indicate that utilities owned by municipality or county ( DumMuni ) charge 7.9% lower rates compared utilities of other forms of ownership, with 90% confidence level. Next, results show that the location variables (WMD jurisdictions) are significant at confidence level of 95%. The reference WMD is South Florida. Coefficients of all t he remaining WMDs are negative. This supports my hypothesis (2b) that water rates vary significantly among the 5 WMDs Specifically, all WMDs charge lower rates than South Florida. However, this effect becomes less significant (in statistical sense) with t he addition of demand variables in Model 4 2. Interpretation of the final two variables DumConsv and DumConsv_Qty is tricky and the associated hypothesis ( 3 ) that utilities focusing on water conservation are expected to have higher / steeper water rates structures is tricky. Under Model 4 1 both
102 these variables do not pass the significance test, indicated by the high p values However, variables DumConsv_Qty and DumConsv are highly correlated ( correlation coefficient of 0.92). As a result, the estimated coefficients for the variables may not be accurate. To correct for the multicollinearity I changed the definition of the interaction term DumConsv_Qty and evaluated the variable using the consumption of approximately 8000 gal lons per month (or 8 thousand g allon s ) Specifically I replace d the interaction term DumConsv_Qty = DumConsv Qty by the variable DumConsv_Qty 1 = DumConsv ( Qty 8 ) M odel 4 1 with the new interaction variable (referred to as Model 4 1 A ) performs better In Model 4 1 A the variable DumConsv is positive and significant with 95% confidence level (Table 5 2) This implies that utilities that encourage water conservation charge 10.78% higher rates than those that do not. That is, we can reject the null hypot hesis ( H o : 1 = 0 ) that there is no difference in the intercept for utilities encouraging water conservation and those that do not (refer back to Figure 4 1). In turn the modified interaction variable DumConsv_ Qty 1 is still not statistically significant with a p value of 0.2585. However, since the variable DumConsv is correlated with the marginal water rates, we reject ed the null hypothesis that marginal water rates ( log p ij ) are not affected by non price conservation programs us ed by water utilities ( H o : 3 = 0 ). That is there is no evidence to suggest difference in slopes for utilities encouraging water conservation and those that do not. Overall, Model 4 1 perform s well and is consistent with economic theory and existing liter ature All the
103 aforementioned cost and institutional variables are jointly significant at the 1% alpha level indicated by the F test. 5.3 Model 4 2: Cost, Institutional, and Demand Factors Introducing demand proxies into the Model 4 1 barely changes the values or the level of significance for the cost factors. However, two of the three institutional factors utility ownership and WMD jurisdiction lose their significance. In hypothesis (3a), I hypothesized that areas with higher income, lower poverty and h igher temperatures are associated with larger water consumption due to higher outdoor use, and hence higher water demand. Therefore, I expect utilities in such areas to charge higher water rates. T he coefficient of lnIncome is 0.7841 and is statistically s ignificant at the 10% rejection level. We can say that for any 10% increase in median income we expect about a 7.84% increase in water rates, with 90% confidence, cetaris paribus. This matches my expectation that utilities in richer communities charge hig her rates. However, my model failed to provide any statistical evidence that utilities in hotter areas charge higher rates. The coefficient of povrate ( .8298) is statistically significant at the 95 % significance level. It implies that as the poverty rate increases by 10% the water rates decrease by approximately 8.29% cetaris paribus This supports my hypothesis (3b) that affordability is an important objective of utilities and as results indicate, may override the objective of water conservation in are as of poorer population. The study by Thosten et al. (2008) had included povrate as an explanatory variable, but it was not significant in their model. In summary, addition of demand variables in Model 4 2 passes the overall significance test at 1% rejection level based on the F test ; however, fails to add any explanatory power to the original Model 4 1. On the contrary, the a djusted R 2 decreases
104 from 0.21 25 in Model 4 1 to 0.2 103 in Model 2 indicating that the Model 2 has a lower explanatory power that Model 1 This result may be explained by the fact that introduction of the demand variables into the Model 4 2 made the effects of several cost and institutional variables not statistically significant (compared with Model 4 1). In other words, Mode l 4 2 includes more variables than Model 4 1, while the number of variables with statistically significant effects on the dependent variable is smaller. 5.4 OLS Assumptions To ensure correct interpretation of regression results, tests were conducted to ensure that no OLS assumptions were violated. Specifically, I tested for normality of residuals, heteroskedasticity and multicollinearity. All these tests provide validity to the regression results. 5.4.1 Tests for N ormality of R esiduals One of the assumptions of linear regression analysis is that the model residuals are normally distributed. This assumption assures that the p values for the t tests are valid (Wooldridge, 2009; UCLA, 2010) To test the normality of residuals, I have generated the histogram of the studentized residuals for both Model 4 1 and Model 4 2 (Figure 5 1). Studentized residual is the residual divided by its standard error. T he histogram s show that the distribution of the mode l residuals is close to a normal distribution. 5.4.2 Tests for Heteroskedasticity Another important assumption for the ordinary least squares regression is the homogeneity of vari ance of the residuals. The error or residual denoted by should have the sa me variance given any value of the independent variables. Mathematically, Var( /x 1 k 2 (Wooldridge, 2009) In other words, if the model is well fitted, there should
105 be no pattern to the residuals plotted against the fitted values. If the variance of the residuals is non constant, then the residual variance is said to be "heterosckedastic." A graphical method is used to detecting heterosekedasticity in Model 4 1 and Model 4 2. Below, I use a plot statement in proc reg (SAS) to calculate the studentized residuals and predicted values f or use in the plot (Figure 5 2). Additionally, Figure (5 3) plots the residuals and t he number of residuals. Figure 5 2 shows some signs of slight heteroskedasticity. To account for this all estimates reported in Table 5 1 were generated using the consistent option in proc reg to generate heteroskedastic consistent t statistics and p values 5.4.3 Tests for Multicollinearity Another assumption of OLS regression is that there is n o perfect linear relationship among independent variables (Wooldridge, 2009) When there is a perfect linear relationship among independent variables, the estimates for a regression model cannot be uniquely computed. The term multicollinearity describes two variables that are highly correlated with each other. As the degree of multicollinearity increases, estimates of the coefficients become erratic and the standard errors for the coefficients can become highly inflated. In tha t case, the test of the hypothesis that the coefficient is equal to zero against the alternative that it is not equal to zero leads to a failure to reject the null hypothesis. To check for multicollinearity, I used the option in SAS to generate the v ariance inflation factor (VIF). VIF is defined as considered to indicate multicollinearity and warrants further investigation. All have any s evere case of multicollinearity (Table 5 3 ). Clearly DelivPerDay and
106 DelivPerDaySq have high correlation and high VIF combination of each other. 5.4.4 Summary of Assumptions All major assumptions have been tested for Tests have been conducted to ensure that no significant violation s of these OLS assumptions were made Residual plots a nd histogram above confirm that the assumption of independence, homogeneity and normality are satisfied, assuring reliability of the predicted coefficients.
107 Table 5 1. Estimation of r esults Dependent Variable Log (Prices) Model 4 1 Model 4 2 Factor Coefficient SE Coefficient SE Intercept 1.407 *** 0.105 0.830 ** 0.384 Quantity1 0.020 *** 0.005 0.020 *** 0.005 BaseFee 0.008 *** 0.003 0.007 *** 0.003 dummyGW Cost 0.167 *** 0.049 0.173 *** 0.050 DumWaterS Cost 0.215 *** 0.053 0.223 *** 0.057 DumWaterM Cost 0.134 ** 0.059 0.148 ** 0.066 DelivPerDay Cost 0.005 *** 0.001 0.005 *** 0.001 DelivPerDaySq Cost 0.000 14 *** 0.000 0.000 0.000 DumMed Cost 0.098 0.050 0.067 0.052 DumLarge Cost 0.008 0.053 0.007 0.056 DumNWF Institution 0.032 0.046 0.013 0.103 DumSR Institution 0.140 ** 0.046 0.033 0.089 DumSJR Institution 0.106 ** 0.039 0.082 0.062 DumSWF Institution 0.016 ** 0.045 0.027 0.051 DumMuni Institution 0.079 0.045 0.082 0.052 DumConsv Institution 0.057 0.079 0.034 0.080 DumConsv_Qty Institution 0.006 0.006 0.007 0.006 lnTemp Demand 0.097 0.905 lnIncome Demand 0.784 0.095 povrate Demand 0.164 0.384 Adjusted R2 .2125 .2103 F Value 12.45 *** 10.1 *** Number of Obs 680 650 All estimates are heteroskedasicity consistent. SE is the standard error; *** significant at 1%; ** significant at 5%; significant at 10% Table 5 2. Comparison of interaction coefficients under Model 4 1 and Model 4 1a Model 4 1 Model 4 1a Variable Coefficient SD P Value Coefficient SD P Value DumConsv 0.057 0.079 0.471 DumConsv_Qty 0.006 0.006 0.259 DumConsv 0.1078 0.0452 0.0173 DumConsv_Qty1 0.0063 0.0056 0.2585
108 Table 5 3 Variation inflation factors Independent Variables Model 4 1 Model 4 2 Quantity1 2.34 2.45 BaseFee 1.24 1.26 DumConsv 6.18 6.21 DumConsv_Qty 6.84 6.95 dummyGW 1.39 1.39 DumWaterS 4.10 4.38 DumWaterM 3.81 4.17 DumMed 2.15 2.38 DumLarge 2.97 3.18 DumNWF 1.64 5.46 DumSR 1.40 2.97 DumSJR 1.72 3.28 DumSWF 1.98 2.44 DumMuni 1.33 1.39 DelivPerDay 12.31 12.85 DelivPerDaySq 11.56 12.17 lnTemp 5.70 lnIncome 4.87 Povrate 5.00
109 A B Figure 5 1. S tudentized residuals and predicted value s A) Model 4 1. B) Model 4 2
110 Figure 5 2 Plot of studentized residuals and predicted value Figure 5 3 Plot of Residuals and all observations
111 CHAPTER 6 DISCUSSION AND CONCL USIONS 6.1 Overview This chapter presents a summary, findings and implications of the study. Also discussed in this Chapter are some of the limitations of this study. Finally, the chapter concludes with recommendations for further research 6.2 Discussion This study investigates the relevance of cost, institution and demand factors for s First, t his study summarizes the results of the survey of Florida water utilities (the first such survey in Florida ), and rate setting objectives, and water conservation programs that were considered by utilities as the most effective. Sixty percent of water utilities that respo nded to the survey increased their water rates in the last five years. Interestingly, approximately 73 % of the survey respondents regard ed residential water demand as perfectly o r relatively inelastic This result is contrary to the existing literature th at suggests that residential water can be relatively elastic. Hence, such result implies that more data should be A better understanding of consumers responses to changing water rate s would allow utility managers to better forecast their returns, and for the Florida state and regional agencies to develop more accurate projections of future water consumption to be used in regional water supply plans. Next, t hypothesis that water suppliers design their rates to cover the supply costs. Specifically,
112 utilities that supply a larger amount of water are able to charge lower prices due to decreasing per unit delivery costs associated with economies of scale. Additionally, utilities that purchase their water (and hence, pay a price premium to the wholesale supplier) and/or rely on surface water (and hence, incur high treatment costs ) char ge higher prices These results are consistent with findings from previous literature that link higher rates to higher costs of service. This reiterates the fact that cost recovery and financial sustainability is among the most important rate setting objec tives of a utility. Further, results indicate that some of the institutional factors have an impact on the rates charged by Florida water utilities. Specifically, results support the hypothesis that utilities that include water conservation into the list (as indicated by the implementation of non price conservation programs) charge higher water rates. In contrast, for other institutional variables, no statistically significant effects on the water rates were found. Particula rly, a lthough ownership type was statistically significant in Model 4 1 (at 90% confidence level) the variables describing ownership type s are not statistically significant in Model 4 2 Such result corresponds to the result from previous stud ies that did not find statistically significant effect s of the ownership on structure s (Thorsten, Eskaf, & Hughes, 2008) Similarly, while the estimation result for Model 4 1 supports the hypothesis that water rates differ among the five WMD jurisdictions this effect is not statistically significant in Model 4 2 Previous studies estimated the effect of location via different proxies. For example, Thorsten et al. (2008) incorporated the effect of location by including 16 dummy variables for river basins; however they were not able to show any statistically significant relationship
113 between the location variables and logged combined bills. Renaud et al. (2005) on the other hand were able to show that the ave rage household water consumption increases with longitude and decreases with latitude of the local community. Further they showed that higher level of water consumption is associated with higher probability of using an inclining rate structure. Similar t o Hewitt et al. (1993), and Thorsten et al (2008), my results show that median household income rate in the service areas influence the water rates charged by utilities. Contrary to Thorsten et al. (2008), Model 4 2 results demonstrate that in the areas with higher poverty rates water rates are l ower suggesting that in poor neighborhoods This relat ionship is significant at the 95 % confidence level. The negative correlation between the poverty rates and water rates suggest s the conflict between the two major objectives of water utilities charging higher conservation rates vs. charging affordable rates Unlike the existing studies that focus on average water rates or on the choice of th e rate structures by utilities this study examines the whole schedule of marginal prices. This approach allowed me to examine the effect of water conservation objectives on the prices faced by high use customers compared with the lo w use customers Estimation results show that u tilities for which water conservation is a top priority ( that is indicated by the implementation of non price conservation strategies) steep rates that grow faster as water use increases ) ; however this effect is not statistically significant. 6.3 Study Limitations and Recommendations for further research This study has some important limitations. First, econometric estimation results are affected by the lack of data available. In the water rate models, cost factors should
114 ideally include the actual operating, maintenance, and capital expenses of water utilities However, such actual cost data were not available for Florida utilities. Instead, this research focuses on cost proxies obtained from the water utilities survey. While I believe that the proxies used in this study do just in accounting for the differences in costs among utilities proxies are yet just an approximation to the true costs and more accurate data c ould potentially improve the explanatory power of the model Furthermore, it is difficult to classify proxy variables into cost, institutional, or demand factors, which complicates the interpretation of the model coefficients. For example, the size of a ut ility could either be a cost factor, an institutional factor, or both. Similarly, the use of non price conservation programs can signal that water conservation is a top priority for a water utility (an institutional variable), and/or it can imply higher c osts associated with customer education and rebates of water efficient fixtures ( a cost variable). Finally, climate variables can characterize water demand ( since water use increases in hot and dry climate s ) opportunity costs of water ( since in drier climates, since utilities may rely on more expensive water supply sources in areas with limited water resources ) Further more poor data quality can also partially explain the low explanatory power of the demand factors in the econometric model P overty rate and income data were collected from the 2000 Census and can be outdated It is probable that current (Census 2010) data can change the significance of demand variables in Model 4 2 More variab les may also be required to accurately reflect the difference in water As discussed in the literature review chapter, previous studies have included demand proxies such as proportion of new built houses,
115 average numbe r of rooms per dwelling and the percentage of households residing in a rural area These variables were not included in to my model ( because of the data collection issues ) It is possible that inclusion of these omitted variables would better approximate w ater demand, which in turn would better explain the variation in water rates. There is a larger body of literature on estimating residential water demand. These studies frequently estimate demand functions by learning how customers react to dif ferent marginal water prices and/or pricing blocks. This approach usually requires a survey of individual customers or households regarding their demand functions. Specifically, questions would include demand variables such as income level, household size, size/age of house, monthly consumption, etc. Information on how consumers actually respond to price changes in practice can be better understood with individual data. Clearly, demand variables collected from individuals (through a survey) would be more precise than collecting them from secondary sources such as the U.S. Census. Future research could survey both the individual customers, as well as water suppliers to generate the most current and accurate data. The advantage of surve ys is that data can be collected on the individual level ( e.g. individual customers and individual water utilities), whereas secondary sources such as the U.S. Census can only provide city or county level average data. Additionally, since the water rate i nformation is collected from a survey, the estimation results may be influenced by the non response bias (when utilities that responded to the survey may be different from those that did not). Finally, the econometric model only examines the effect of one institutional variable on the increase
116 DumConsv_Qty ) Future studies should examine if other cost, demand, or institutional factors influence the increase in p rices for high use customers, as compared with the low use customers.
117 APPENDIX A CHARACTERISTICS OF F LORIDA DRINKING WATE R SYSTEMS Table A 1. Characteristics of F lorida p ublic d rinking w ater s ystems System Characteristic Categories FDEP District 6 FDEP districts County counties are alphabetized and numbered from 1 to 67 FDEP Office North West District (NWD) North East District (NED) Central District (CD) South West Polk (SWPO) Source Water Protection Area (SWPA) Central District Volusia (CDVO) South East Broward (SEBR) South East Dade (SEDA) South East District (SED) South East Palm Beach (SEPB) South District (SD) South District Lee(SDLE) South West District (SWD) South West Hillsborough (SWHI) South West Manatee (SWMA) South West Polk (SWP) South West Sarasota (SWSA) Email Email of the contact listed PWS ID This refers to the 7 digit DEP Public Water System ID number. Type Community Serves at least 15 service connections used by year round residents or regularly serves at least 25 year round residents. This group provides water to residences and includes a range of sizes from small mobile home courts to large city utilitie s. Transient Non Community serves at least twenty five people or fifteen connections, but the population is characterized as flow through traffic, such as with stores, RV parks, hotels or churches that are open at least 60 days a year. Non Transient No n Community Provides water to the same 25 individuals for six months or more each year. These systems include schools, factories or large businesses with their own drinking water supplies. (see FDEP 2007) Surface Source Refers to sources above ground. Ground Source Refers to sources below ground Mailing name, address, contact, and contact phone Mailing name, address, contact, and contact phone Owner, owner address, and phone number Owner, owner address, and phone number
118 Table A 1. Continued System Characteristic Categories Owner type The various types of owners ranging from investors, trusts and cooperatives to county, state and municipalities. Population Served The population served is the sum of the number of permanent residents and the number of additional non transient persons to whom the system is available, such as school children, office and commercial employees, and seasonal residents (FDEP, date not found). Sells to pop This means how may systems were sold to that population. Design capacity This refers to gallons per day. Service connect Describes how many connections there are. For example, it could be the number of houses in a neighborhood; or, if referring to a business, then each building may count as a service connection Last inspection This maybe basic one year or a more detailed compliance inspection Last sanitary survey The last time a sanitary survey was completed. # bact required how many samples FDEP inspectors have to take Bact frequency The number of days. Bact date When FDEP sampled the system. Secondary contaminates These include checking things like sulfate, color and odor Inorganic date Last time checked for inorganic materials like nitrate, nitrite, arsenic etc A more comprehensive list will be compi led if need. Synthetic organic contaminate date Last time checked for anything man made such as pesticides. Radio nuclides date Last time checked for radioactive materials such as Uranium. Volatile organic carbon date Last time checked for volatile mate rials such as benzene. Sources: FDEP 2007, FDEP date not found, Harmon 2009
119 APPENDIX B WATER MANAGEMENT DIS TRICT INFORMATION The 67 counties in Florida are distributed among the jurisdictions of five Water Management Districts (WMDs): Northwest Florida WMD (NWFWMD) Suwannee River WMD (SRWMD) St. Johns River WMD (SJRWMD) Southwest Florida WMD (SWFWMD) South Florida WMD (SFWMD) County is in the NWFWMD while the Easter n (and majority) part of county is in the Suwannee River WMD. For survey pre test, all community water systems in the Jefferson County are assumed to be in SR WMDs jurisdiction. Further, Alachua County is split almost equally (by area) between Suwannee and St Johns River WMD. City information was used to allocate community water systems in Alachua County between these WMDs. Baker County crosses the border between Suwannee and St. Johns WMDs; however, almost all territory of the county is in St. Johns WMD. It was assumed that all community water systems in Baker County are in St. Johns WMD. Levy County crosses the border between Suwannee and SWFWMD, and for the survey pre test, community water systems were allocated to specific WMD based on the informatio n about the city they are in. Lake County crosses the border between St. Johns and SWFWMD. Since the majority of the county (by area) is in St. Johns River WMD, it was assumed that all community water systems are in St. Johns River WMD jurisdiction. Mos t of the Marion County is in St. Johns River WMD jurisdiction, with a small portion (by area) in SWFWMD. It was assumed that all community water systems in Marion County belong to St. Johns River WMDs jurisdiction. It was assumed that all community water systems in Okeechobee County are under SFWMD jurisdiction, although a small portion of the county (by area) is in St. Johns River WMD. Almost all Orange County is in St. Johns River WMD, with a small portion (by area) in SFWMD. It was assumed that all community water systems in the county are in St. Johns River WMD. While graphically, Osceola, Charlotte, and Highlands counties may seem to have equal portions (by area) in two different WMDs, the majority of the cities in these counties
120 reside in the spe cified WMD. For example, many of the Charlotte County water systems are concentrated in the SWFWMD even though looking at a WMD map would suggest a greater area allotted towards SFWMD. It was assumed that all community water systems in Osceola and Highlan ds Counties are in SFWMD; while all community water systems in Charlotte County are assumed to belong to SWFWMD. Majority of Polk County is located in SFWMD, with a little area in SWFWMD. It was assumed that all community water systems in Polk County are located in SFWMD.
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125 BIOGRAPHICAL SKETCH Shirish Rajbhandary was born in Kathmandu, Nepal. After spending most of his childhood in Nepal, he was awarded the Hanover Scholar Merit Scholarship to continue his Bachelor of Liberal Arts in Hanover College, Indiana. After graduation in 2006, he worked at Deutschebank, New York, for s ix months as a Financial Data Analyst In August 2008, he joined the Master of Science program of the Food and Resource Economics Department at the University of Florida with full graduate assistantship. He specialized in water ec onomics and water conserva tion. He received his Master of Science degree from the University of Florida in the fall of 2010