Consequences of the Clean Water Act and the Demand for Water Quality. (2018). Keiser, David A ; Shapiro, Joseph K.
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Paper not yet in RePEc: Add citation now - Appendix Figure 1. Densities of Raw Pollution Readings Panel A. Biochemical Oxygen Demand Panel B. Dissolved Oxygen Deficit Panel C. Fecal Coliforms Panel D. Total Suspended Solids Panel E: Log Fecal Coliforms Panel F. Log Total Suspended Solids Notes: Data include years 1962-2001. 0 .005 .01 .015 Density 0 200 400 600 800 1000 mg/L 0 .1 .2 .3 Density 0 10 20 30 40 mg/L 0 .005 .01 .015 .02 .025 Density -200-100 0 100 mg/L 0 .001 .002 .003 .004 Density 0 20000 40000 60000 MPN/100mL 0 .05 .1 .15 .2 .25 Density -10-5 0 5 10 ln(MPN/100mL) 0 .1 .2 .3 Density -10-5 0 5 10 ln(mg/L) Appendix Figure 2a. Pollution by River Basin, 1992-2001 Panel A. Biochemical Oxygen Demand Panel B. Dissolved Oxygen Deficit Panel C. Fecal Coliforms Panel D. TSS Notes: Data are mean by river basin. Darker colors represent worse pollution, white areas have no data.
Paper not yet in RePEc: Add citation now - Appendix Figure 2b. Fecal Coliforms, by River Basin and Decade, 1962-2001 Panel A. 1962-1971 Panel B. 1972-1981 Panel C. 1982-1991 Panel D. 1992-2001 Notes: Data are mean by river basin. Darker colors represent worse pollution. Color cutoffs are same in each year. White areas have no data. Colors are as follows, with values in logs: No data (white), <250 (light blue), 250 to 750 (moderate blue), 750 to 1750 (darker blue), >1750 (darkest blue). Panel A. Month Panel B. Hour Panel C. Air Temperature Appendix Figure 3. Patterns in Dissolved Oxygen Deficits Notes: Figures show coefficients from a regression of dissolved oxygen deficit on monitoring station fixed effects and on dummy variables for the indicated controls. Data use only dissolved oxygen measured in mg/L. Dissolved oxygen deficit measured as 15 minus the reported level of dissolved oxygen in mg/L.
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Paper not yet in RePEc: Add citation now - Connected dots show yearly values, dashed lines show 95% confidence interval, and 1962 is reference category. Standard errors are clustered by watershed.
Paper not yet in RePEc: Add citation now - Control for Stream Gauge Flow includes only stations which report instantaneous stream flow at the same time they report pollution, and it controls for streamflow. Include Monitors on Other Rivers includes monitors on rivers different than the treatment plant, but that eventually flow into or out of the treatment plant's river. Decennial sample includes averaged periods 1965-1974, 1975-1984, 1985-1994, 1995-2004. Cumulative Grants rows use trends sample. Data cover years 19622001. Standard errors are clustered by watershed. Asterisks denote p-value < 0.10 (*), < 0.05 (**), or < 0.01 (***).
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Paper not yet in RePEc: Add citation now - Dependent variable mean describes upstream mean. Standard errors are clustered by watershed. Asterisks Table 1. Water Pollution Trends, 1962-2001 Main Pollution Measures Other Pollution Measures Notes: Each observation in the data is a pollution reading. Data includes years 1962-2001. Dissolved oxygen deficit equals 100 minus dissolved oxygen saturation, measured in percentage points. Season controls are a cubic polynomial in day of year. Time of Day controls are a cubic polynomial in hour of day. In Panel B, the year variables are recentered around the year 1972. The 1972 to 2001 change equals the fitted value Year*39 + Year*1[Year≥1972]*39. Dependent variable mean refers to years 1962-1971. Standard errors are clustered by watershed. Asterisks denote p-value < 0.10 (*), < 0.05 (**), or < 0.01 (***).
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Paper not yet in RePEc: Add citation now - Each row describes different analyses. Row 2 excludes all housing units within a 1-mile radius in any direction of the treatment plant, to address the possibility that grants change local disamenities 66 Overall, 57 percent of the plants we analyze have at least one other plant within 25 miles upstream or 25 miles downstream, and the mean plant in our data has 1.7 other plants within 25 miles upstream or 25 miles downstream. The two additional controls included in Row 20 both have small and statistically insignificant coefficients. 67 Because the Census RDC industrial water pollution data are only observed in 1972, they are interacted with a full set of year indicators, in addition to the interaction with downstream indicators. like noise or odor. Row 3 allows two-way clustering of standard errors by watershed and also by year.
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Paper not yet in RePEc: Add citation now - Figure 1. National Maps of Water Pollution Data Panel A. The River and Stream Network Panel B. Wastewater Treatment Plants Panel C. Water Pollution Monitoring Sites Notes: In Panel A, rivers are colored by Stream Level from the National Hydrography Dataset. Streams that flow into oceans, Great Lakes, Canada or Mexico and are the darkest. Streams that flow into these are lighter; streams that flow into these are still lighter, etc. Panel C shows monitoring sites appearing in years 1962-2001.
Paper not yet in RePEc: Add citation now - Figure 2. Water Pollution Trends, 1962-2001 Panel A. Dissolved Oxygen Deficit Panel B. Share Not Fishable Figure 3. Effects of Clean Water Act Grants on Water Pollution: Event Study Graphs Panel A. Dissolved Oxygen Deficit Panel B. Share Not Fishable Figure 4. Effects of Clean Water Act Grants on Log Mean Home Values: Event Study Graphs Panel A. Homes Within 0.25 Miles of River Panel B. Homes Within 25 Miles of River Notes: Graphs show year fixed effects plus a constant from regressions which also control for monitoring site fixed effects, a day-of-year cubic polynomial, and an hour-of-day cubic polynomial, corresponding to equation (2) from the text.
Paper not yet in RePEc: Add citation now - Finally, row 8 of Appendix Table 7 uses data on city growth and amenities. To identify declining urban areas, we follow Glaeser and Gyourko (2005) by taking 1970-2000 city population growth rate as reported in the 1972 and 2000 city data books (Haines and ICPSR 2010). We define declining urban areas as cities with population above 25,000 in the year 1970 which had a population decline by the year 2000. High amenity areas are defined as counties in an SMSA with above-median total amenity value, as reported in Albouy (2016), Appendix Table A1. B.9 Tract Versus House-Level Data for Hedonic Models Consider the following simplified regression model for home i in tract t Pit = X0 itβ + it Let Ωt denote the set of homes in tract t. Summing across homes within a tract and dividing by the number of housing units within a tract gives P i∈Ωt Pit Nt =
Paper not yet in RePEc: Add citation now - First, the effects of these grants could have been reflected in changes in housing supply or in the characteristics of local residents (Greenstone and Gallagher 2008). As discussed earlier, Table 6 and Appendix Table 8 show little evidence of changes in either.
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Paper not yet in RePEc: Add citation now - In order to test the accuracy of the microdata on 35,000 grants, we compare the grants against several published reports describing this program. A USEPA (2000b) report and associated book (Stoddard, Harcum, Simpson, Pagenkopf, and Bastian 2002) were based on detailed data describing these grants. Andy Stoddard and Jon Harcum generously shared the microdata underlying these reports. The grants data they analyze exactly mirror ours, with two exceptions. First, the aggregate nominal figure they report for grants ($61 billion) reflects both federal and municipal capital spending, though their publications and the associated EPA website describe it as federal money only. Second, they only obtained records of 10,000 grants. This appears to be because their data apply several exclusion criteria.
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Paper not yet in RePEc: Add citation now - Measuring such expenditures is difficult. The first attempt by the Bureau of Economic Analysis (BEA) to measure pollution abatement costs describes five challenges (Cremeans and Segel 1975) including determining counterfactual pollution abatement; the problem that many abatement technologies also have valuable byproducts; the proper classification of capital goods used for abatement; the difficulty in recognizing business decisions as environmental or not; and the separation of pollution abatement expenditures from expenditures for industrial safety and related purposes. These are only accounting challenges; an additional challenge is that even correct accounting measures do not equal full economic costs. Our goal is simply to describe available estimates, recognizing these caveats.
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Paper not yet in RePEc: Add citation now - mg/L -25 to -20 -20 to -15 -15 to -10 -10 to -5 -5 to 0 0 to 5 5 to 10 10 to 15 15 to 20 20 to 25 Miles Downstream from Treatment Plant -500 0 500 1000 1500 MPN/100mL -25 to -20 -20 to -15 -15 to -10 -10 to -5 -5 to 0 0 to 5 5 to 10 10 to 15 15 to 20 20 to 25 Miles Downstream from Treatment Plant -.04 -.02 0 .02 .04 .06 Share -25 to -20 -20 to -15 -15 to -10 -10 to -5 -5 to 0 0 to 5 5 to 10 10 to 15 15 to 20 20 to 25 Miles Downstream from Treatment Plant -1 0 1 2 3
Paper not yet in RePEc: Add citation now - mg/L 1 2 3 4 5 6 7 8 9 10 11 12 Month Panel A. Biochemical Oxygen Demand Panel B. Fecal Coliforms Panel C. Not Swimmable Panel D. Total Suspended Solids Appendix Figure 4. Water Pollution Trends, Other Pollution Measures, 1962-2001 Notes: These graphs show year fixed effects plus the constant from regressions which control for station fixed effects, year fixed effects, day-of-year cubic polynomial, and hour-of-day cubic polynomial, corresponding to equation (2) in the text. Connected dots show yearly values, dashed lines show 95% confidence interval, and 1962 is reference category. Standard errors are clustered by watershed. 20 40 60 80 100 mg/L 1962 1972 1982 1992 2001 Year 2 3 4 5 6
Paper not yet in RePEc: Add citation now - mg/L 1962 1972 1982 1992 2001 Year 0 1000 2000 3000 4000 5000 MPN/100mL 1962 1972 1982 1992 2001 Year .3 .4 .5 .6 .7 Share Not Swimmable 1962 1972 1982 1992 2001 Year Panel A. Dissolved Oxygen Deficit Panel B. Not Fishable Panel C. Biochemical Oxygen Demand Panel D. Fecal Coliforms Panel E. Not Swimmable Panel F. Total Suspended Solids Appendix Figure 5. Water Pollution, by Distance Downstream from Treatment Plant, Other Pollution Measures Notes: Graphs show coefficients on distance-from-plant indicators from regressions which also control for plant-by-year fixed effects, corresponding to equation (3) from the main text. Connected dots show yearly values, dashed lines show 95% confidence interval. Data cover years 1962-2001. Standard errors are clustered by watershed. -10 -5 0 5 10 mg/L -25 to -20 -20 to -15 -15 to -10 -10 to -5 -5 to 0 0 to 5 5 to 10 10 to 15 15 to 20 20 to 25 Miles Downstream from Treatment Plant -.5 0 .5 1
Paper not yet in RePEc: Add citation now - National data are consistent with the idea that the ratio of lifetime O&M costs to upfront capital costs increased almost linearly from 130 percent in 1972 to 259 percent in 1996. We linearly extrapolate these values to years before and after 1972-1996. These values reflect several sources. Two independent sources provide identical reports that concrete structures of treatment plants have a useful life of 50 years but mechanical and electrical components have a useful life of 15-25 years (American Society of Civil Engineers 2011 and USEPA 2002). We assume grants require O&M expenditures for 25.
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Paper not yet in RePEc: Add citation now - not total water pollution emissions, the SWUM survey questions and resulting report both focus on water pollution,58 and plants with extensive water use also emit large amounts of water pollution. For example, the industries that consume the most water in the 1978 version of these data (Becker 2015) – blast furnaces and steel mills, industrial organic chemicals, petroleum refining, and paper mills – are also the industries that emit the most water pollution.
Paper not yet in RePEc: Add citation now - Notes: Graphs show coefficients on downstream times year-since-grant indicators from regressions which correspond to the specification of Table 3. These regressions are described in equation (5) from the main text. Data cover years 1962-2001. Connected dots show yearly values, dashed lines show 95% confidence interval. Standard errors are clustered by watershed.
Paper not yet in RePEc: Add citation now - Notes: Graphs show coefficients on year-since-grant indicators from regressions corresponding to the specification of Table 6, column (3). Connected dots show yearly values, dashed lines show 95% confidence interval. Standard errors are clustered by watershed. Panels A and B show different ranges of values on their y-axes. Data cover decennial census years 1970-2000. 15 20 25 30 35 Saturation Deficit (%) 1962 1972 1982 1992 2001 Year .1 .2 .3 .4 Share Not Fishable 1962 1972 1982 1992 2001 Year -4 -2 0 2 4
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Paper not yet in RePEc: Add citation now - One sensitivity analysis in our paper looks only at grants given for construction rather than engineering plans. Following Stoddard, Harcum, Simpson, Pagenkopf, and Bastian (2002), we define a grant as for construction if the grants microdata list the grant “Step†as equal to three or four, and if the grant also lists the facility number of the plant receiving the grant. Operating and Maintenance Costs. Clean Water Act grants involve three types of costs: federal grants for capital, local matching expenditures for capital, and expenditures for operating and maintenance (O&M). Our grants microdata report only the first two costs, so we estimate the third from other sources.
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Paper not yet in RePEc: Add citation now - Row 2 of Appendix Table 7 distinguishes grant projects which have a total cost (including federal and local contributions) above $1.2 million, measured in $2014. This is the median cost.
Paper not yet in RePEc: Add citation now - Row 7 of Appendix Table 7 uses data on environmental views from the “Total Green Index†of Hall and Kerr (1991). States with Pro-Environmental Views are defined as those with above-median values of the total green index.
Paper not yet in RePEc: Add citation now - Rows 14-16 of Appendix Table 3 report results separately for three small and well-documented networks of high-quality monitoring sites, all managed by USGS. Row 14 shows estimates for the National 63 Most pollutants, including BOD, fecal coliforms, and dissolved oxygen deficits, increase fairly abruptly in the 5 miles just before and after a treatment plant. TSS, which is the only exception, increases somewhat steadily in the 25 miles downstream of a treatment plant. These TSS patterns are consistent with the idea that urban runoff accounts for a large share of TSS emissions (Gianessi and Peskin 1981), and that urban runoff occurs in cities around treatment plants. 64 A river here is defined as a “levelpathi†from NHD.
Paper not yet in RePEc: Add citation now - Shapiro, J. S., and R. Walker (2014): “Why is Pollution from U.S. Manufacturing Declining? The Roles of Trade, Regulation, Productivity, and Preferences,†Mimeo, Yale University.
Paper not yet in RePEc: Add citation now - Smith, R. A., R. B. Alexander, and M. G. Wolman (1983): “Analysis and Interpretation of water-Quality Trends in Major U.S. Rivers, 1974-81,†USGS Water-Supply Paper 2307.
Paper not yet in RePEc: Add citation now - Smith, V. K., and W. H. Desvousges (1986): Measuring Water Quality Benefits. Kluwer.
Paper not yet in RePEc: Add citation now - Snow, J. (1855): On the Mode of Communication of Cholera. John Churchill, New Burlington Street.
Paper not yet in RePEc: Add citation now - Some sensitivity analyses control for county-by-year-by-pollutant nonattainment designations. For years after 1977, these data come from the EPA Green Book. Data for years 1972-1977 are constructed from raw monitors based on the reported nonattainment rule. We define ozone nonattainment to include all ozone or nitrogen oxides designations, and we define particulate matter nonattainment to include Total Suspended Particulates (TSPs), particulates smaller than 10 micrometers (PM10), and particulates smaller than 2.5 micrometers (PM2.5). Our binary measures of nonattainment include all partial, wholecounty, and other types of nonattainment. B.8 Data for Analyzing Heterogeneous Effects Appendix Table 7 analyzes how the effects of grants on water pollution and housing values differs for certain subsets of grants. This subsection describes how we define these subsets.
Paper not yet in RePEc: Add citation now - Steinwender, A., C. Gundacker, and K. J. Wittmann (2008): “Objective versus subjective assessments of environmental quality of standing and running waters in a large city,†Landscape and Urban Planning, 84, 116–126.
Paper not yet in RePEc: Add citation now - Stigler, G. J. (1952): The Theory of Price. Macmillan.
Paper not yet in RePEc: Add citation now - Stigler, G. J. (1966): The Theory of Price. Macmillan.
Paper not yet in RePEc: Add citation now - Stoddard, A., J. B. Harcum, J. T. Simpson, J. R. Pagenkopf, and R. K. Bastian (2002): Municipal Wastewater Treatment: Evaluating Improvements in National Water Quality. Wiley.
Paper not yet in RePEc: Add citation now - Stream Quality Accounting Network (NASQAN). Row 15 shows estimates for the National Water-Quality Assessment (NAWQA) (Smith, Alexander, and Wolman 1987; Alexander, Slack, Ludtke, Fitzgerald, and Schertz 1998; Rosen and Lapham 2008).65 Row 16 shows estimates for the Hydrologic Benchmark Network (HBN), which includes 37 watersheds expected to have “minimal†effects from human activity (Alexander, Slack, Ludtke, Fitzgerald, and Schertz 1998). HBN shows smaller trends than the main sample for BOD, fecal coliforms, and TSS, which is consistent with anthropogenic causes of these pollutants in the national data.
Paper not yet in RePEc: Add citation now - Such self-reported home values may also suffer from inertia. Owner-occupants who have not purchased a home recently may be slow to update their beliefs about a home’s value (Kuzmenko and Timmins 2011; Henriques 2013). This inertia appears to be consistent with a simple Bayesian updating model, specifically, a Kalman filter (Davis and Quintin 2016). But this means that homeowners may be slow to reflect changes in local amenities due to investments in surface water quality. Longstanding rental tenants often receive tenure discounts, though we are not aware of direct evidence on the speed with which such discounts adjust to changes in amenities. As one way to address these concerns, in analyzing home values and rents, we report specifications which allow homeowners and renters up to 10 years to reflect changes in water quality.
Paper not yet in RePEc: Add citation now - Table 5. Effect of Clean Water Act Grants on Housing Demand Notes: Analysis includes homes within a given distance of downstream river segments. Data include decennial census years 1970-2000. Cumulative grants include grants in all previous years, not only census years. See main text for description of dwelling and baseline covariates. Standard errors are clustered by watershed. Asterisks denote p-value < 0.10 (*), < 0.05 (**), or < 0.01 (***). A Expenditure on Water Pollution Abatement This Appendix reviews available data on expenditures for abating water pollution and air pollution.
Paper not yet in RePEc: Add citation now - The BEA data report total air pollution abatement expenditures at $1.0 to $1.4 trillion ($2014) using quantity or price indices, respectively, including expenditures by private households (e.g., for vehicles). This indicates that water pollution abatement expenditures exceed air pollution abatement expenditures by 6 to 27 percent.
Paper not yet in RePEc: Add citation now - The census data are also top-coded. Many studies find high correlation between self-reported home values and sales price indices, either in the cross-section, time-series, or panel (James R. Follain and Malpezzi 1981; Ihlanfeldt and Martinez-Vazquez 1986; John L. Goodman and Ittner 1992; DiPasquale and Somerville 1995; Kiel and Zabel 1999; Banzhaf and Farooque 2013; BenıÌÂtez-Silva, Eren, Heiland, and JimeÃŒÂnez-MartıÌÂn 2015), suggesting that self-reports are informative about market valuations. Banzhaf and Farooque (2013) actually find that community-mean rental values from the U.S. census are more strongly correlated with local amenities and with income than home sales value are. Because home values are the dependent variable in hedonic regressions, using self-reported home values in the presence of classical measurement error may decrease the precision of estimates but not create attenuation bias (Griliches and Hausman 1986; Bound and Krueger 1991).
Paper not yet in RePEc: Add citation now - The EPA does not have plant-level records from the 1970s. The current PCS data do list the first year a plant received a water pollution emissions permit. These data suffer from incomplete reporting, since not all states and plants uploaded data to the EPA’s centralized database. They also suffer from sample selection, since plants which closed may not appear in the data.
Paper not yet in RePEc: Add citation now - The first set of estimates comes from the Bureau of Economic Analysis (BEA) for the years 1972-1994 (Vogan 1996).45 The BEA estimates aggregate expenditure on water pollution abatement in the period 1972-1994 of $1.3 or $1.4 trillion ($2014) when deflated using quantity or price indices, respectively. Private business accounts for two-thirds of these expenditures, and government for the remaining one-third.
Paper not yet in RePEc: Add citation now - The machine which originally housed these data was decommissioned around the year 2000, so we sought to corroborate the accuracy of the data.
Paper not yet in RePEc: Add citation now - The second set of estimates comes from the Census Bureau for private industry and EPA for government sources. The Census conducted the Pollution Abatement Costs and Expenditures survey annually between 1972 and 1994. We sum capital and operating costs from this survey, and linearly interpolate for the year 1987 (which had no survey). These data indicate total 1973-1994 abatement expenditures of $315 billion for water pollution abatement and $338 billion for air pollution abatement ($2014). These numbers include only the manufacturing sector. Our EPA data on the construction grants program indicate that local governments spent about $190 billion in federal grant funds, supplemented by local expenditures, and a federal Revolving Loan fund. 46 The third set of estimates is from EPA reports on the costs of the Clean Air and Clean Water Acts (USEPA 1997, 2000c). In 1990, the compliance cost of the Clean Air Act was about $25 billion ($1990).
Paper not yet in RePEc: Add citation now - These values reflect historic census records on O&M expenditures and perpetual inventory estimates of capital stocks (U.S. Army Corps of Engineers 1994), both for sewerage infrastructure.
Paper not yet in RePEc: Add citation now - Time (1969): “The Cities: The Price of Optimism,†Time Magazine, August 1.
Paper not yet in RePEc: Add citation now - U.S. Army Corps of Engineers (1994): “Consolidated Performance Report on the Nation’s Public Works: An Update,†Discussion paper, US Army Corps of Engineers.
Paper not yet in RePEc: Add citation now - USEPA (1974a): “Awards Register Volume II. Grants Assistance Programs. Showing Projects Awarded in Fiscal Year 1974.,†Discussion paper, USEPA.
Paper not yet in RePEc: Add citation now - USGAO (1994): “Water Pollution: Information on the Use of Alternative Wastewater Treatment Systems, †Discussion paper, USGAO.
Paper not yet in RePEc: Add citation now - USPHS (1961): “National Water Quality Network Annual Compilation of Data, October 1, 1960September 30, 1961,†Discussion paper, U.S. Department of Health, Education, and Welfare: Public Health Service.
Paper not yet in RePEc: Add citation now - Vogan, C. R. (1996): “Pollution Abatement and Control Expenditures,†Survey of Current Business, September, 48–67.
Paper not yet in RePEc: Add citation now - We also compared individual grants in the microdata we received against published reports we found that list individual grants given in early years (USEPA 1974a,b). The grants in our microdata also appear in these printed volumes, with the same plant and government authority listed. Grant dates are similar in the microdata and 1970s reports, though some differ by several months. The dollar amounts of individual grants have the same order of magnitude but the exact amounts differ. This may be because funds requested, approved, and disbursed can differ, and can take over a decade to finalize.
Paper not yet in RePEc: Add citation now - We combine this 25 year statistic with the estimated ratio of O&M costs to capital stock in a typical year. This ratio grew almost linearly from 3.7 percent in 1972 to 7.4 percent in 1996 (USEPA 2002).
Paper not yet in RePEc: Add citation now - We consider three sets of estimates: BEA annual accounts for the period 1972-1994; Census abatement cost surveys for manufacturing combined with EPA expenditure records for government; and EPA reports on the costs of the Clean Water Act and Clean Air Act. All three methods suggest that total expenditure on water pollution abatement since the Clean Water Act has exceeded $1 trillion ($2014), which is over $100 per person-year, or equivalently, annual expenditure just over half a percent of GDP. All three methods also imply that expenditure on water pollution abatement has exceeded expenditure on air pollution abatement.
Paper not yet in RePEc: Add citation now - We measure baseline pollution as the mean pollution level for each watershed as measured in the years 1962-1971. Baseline pollution levels are calculated separately for dissolved oxygen and for the fishable standard.
Paper not yet in RePEc: Add citation now
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