Reported expenditures for environmental protection in the U.S. are estimated to exceed $150 billion annually or about 2% of GDP. This estimate is often used as an assessment of the burden of current regulatory efforts and a standard against which the associated benefits are measured. This makes it a key statistic in the debate surrounding both current and future environmental regulation. Little is known, however, about how well reported expenditures relate to true economic cost. True economic cost depends on whether reported environmental expenditures generate incidental savings, involve uncounted burdens, or accurately reflect the total cost of environmental protection. This paper explores the relationship between reported expenditures and economic cost in a number of major manufacturing industries. Previous research has suggested that an incremental $1 of reported environmental expenditures increases total production costs by anywhere from $1 to $12, i.e., increases in reported costs probably understate the actual increase in economic cost. Surprisingly, our results suggest the reverse, that increases in reported costs may overstate the actual increase in economic cost. Our results are based a large plant-level data set for eleven four-digit SIC industries. We employ a cost-function modeling approach that involves three basic steps. First, we treat real environmental expenditures as a second output of the plant, reflecting perceived environmental abatement efforts. Second, we model the joint production of conventional output and environmental effort as a cost-minimization problem. Third, we calculate the effect of an incremental dollar of reported environmental expenditures at the plant, industry, and manufacturing sector levels. Our approach differs from previous work with similar data by considering a large number of industries, using a cost-function modeling approach, and paying particular attention to plant-specific effects. Our preferred, fixed-effects model obtains an aggregate estimate of thirteen cents in increased costs for every dollar of reported incremental pollution control expenditures, with a standard error of sixty-one cents. This single estimate, however, conceals the wide range of values observed at the industry and plant level. We also find that estimates using an alternative, random-effects model are uniformly higher. Although the higher, random-effects estimates are more consistent with previous work, we believe they are biased by omitted variables characterizing differences among plants. While further research is needed, our results suggest that previous estimates of the economic cost associated with environmental expenditures have been biased upward and that the possibility of overstatement is quite real. Key words: environmental costs, fixed-effects, translog cost model
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Costs of Air Quality Regulation
July 1999
Working Paper Number:
CES-99-09
This paper explores some costs associated with environmental regulation. We focus on regulation pertaining to ground-level- ozone (O) and its effects on two manufacturing industries - industrial organic chemicals (SIC 2865-9) and miscellaneous plastic products (SIC 308). Both are major emitters of volatile organic compounds (VOC) and nitrogen oxides (NO), the chemical precursors to ozone. Using plant-level data from the Census Bureau's Longitudinal Research Database (LRD), we examine the effects of regulation on the timing and magnitudes of investments by firms and on the impact it has had on their operating costs. As an alternative way to assess costs, we also employ plant-level data from the Pollution Abatement Costs and Expenditures (PACE) survey. Analyses employing average total costs functions reveal that plants' production costs are indeed higher in (heavily-regulated) non-attainment areas relative to (less-regulated) attainment areas. This is particularly true for younger plants, consistent with the notion that regulation is most burdensome for new (rather existing) plants. Cost estimates using PACE data generally reveal lower costs. We also find that new heavily-regulated plants start out much larger than less-regulated plants, but then do not invest as much. Among other things, this highlights the substantial fixed costs involved in obtaining expansion permits. We also discuss reasons why plants may restrict their size.
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ENVIRONMENTAL REGULATION AND INDUSTRY EMPLOYMENT: A REASSESSMENT
July 2013
Working Paper Number:
CES-13-36
This paper examines the impact of environmental regulation on industry employment, using a structural model based on data from the Census Bureau's Pollution Abatement Costs and Expenditures Survey. This model was developed in an earlier paper (Morgenstern, Pizer, and Shih (2002) - MPS). We extend MPS by examining additional industries and additional years. We find widely varying estimates across industries, including many implausibly large positive employment effects. We explore several possible explanations for these results, without reaching a satisfactory conclusion. Our results call into question the frequent use of the average impacts estimated by MPS as a basis for calculating the quantitative impacts of new environmental regulations on employment.
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Estimating market power Evidence from the US Brewing Industry
January 2017
Working Paper Number:
CES-17-06R
While inferring markups from demand data is common practice, estimation relies on difficult-to-test assumptions, including a specific model of how firms compete. Alternatively, markups can be inferred from production data, again relying on a set of difficult-to-test assumptions, but a wholly different set, including the assumption that firms minimize costs using a variable input. Relying on data from the US brewing industry, we directly compare markup estimates from the two approaches. After implementing each approach for a broad set of assumptions and specifications, we find that both approaches provide similar and plausible markup estimates in most cases. The results illustrate how using the two strategies together can allow researchers to evaluate structural models and identify problematic assumptions.
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Environmental Regulation, Abatement, and Productivity: A Frontier Analysis
September 2013
Working Paper Number:
CES-13-51
This research studies the link between environmental regulation and plant level productivity in two U.S. manufacturing industries: pulp and paper mills and oil refineries using Data Envelopment Analysis (DEA) models. Data on abatement spending, emissions and abated emissions are used in different DEA models to study plant productivity outcomes when accounting for abatement spending or emissions regulations. Results indicate that pulp and paper mills and oil refineries in the U.S. suffered decreases in productivity due to pollution abatement activities from 1974 to 2000. These losses in productivity are substantial but have been slowly trending downwards even when the regulations have tended to become more stringent and emission of pollutants has declined suggesting that the best practice has shifted over time. Results also show that the reported abatement expenditures are not able to explain all the losses arising out of regulation suggesting that these abatement expenditures are consistently under-reported.
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Industrial Investments in Energy Efficiency: A Good Idea?
January 2017
Working Paper Number:
CES-17-05
Yes, from an energy-saving perspective. No, once we factor in the negative output and productivity adoption effects. These are the main conclusions we reach by conducting the first large-scale study on cogeneration technology adoption ' a prominent form of energy-saving investments ' in the U.S. manufacturing sector, using a sample that runs from 1982 to 2010 and drawing on multiple data sources from the U.S. Census Bureau and the U.S. Energy Information Administration. We first show through a series of event studies that no differential trends exist in energy consumption nor production activities between adopters and never-adopters prior to the adoption event. We then compute a distribution of realized returns to energy savings, using accounting methods and regression methods, based on our difference-in-difference estimator. We find that (1) significant heterogeneity exists in returns; (2) unlike previous studies in the residential sector, the realized and projected returns to energy savings are roughly consistent in the industrial sector, for both private and social returns; (3) however, cogeneration adoption decreases manufacturing output and productivity persistently for at least the next 7-10 years, relative to the control group. Our IV strategies also show sizable decline in TFP post adoption.
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Why is Pollution from U.S. Manufacturing Declining?
The Roles of Environmental Regulation, Productivity, and Trade
January 2015
Working Paper Number:
CES-15-03R
Between 1990 and 2008, air pollution emissions from U.S. manufacturing fell by 60 percent despite a substantial increase in manufacturing output. We show that these emissions reductions are primarily driven by within-product changes in emissions intensity rather than changes in output or in the composition of products produced. We then develop and estimate a quantitative model linking trade with the environment to better understand the economic forces driving these changes. Our estimates suggest that the implicit pollution tax that manufacturers face doubled between 1990 and 2008. These changes in environmental regulation, rather than changes in productivity and trade, account for most of the emissions reductions.
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Misallocation or Mismeasurement?
February 2020
Working Paper Number:
CES-20-07
The ratio of revenue to inputs differs greatly across plants within countries such as the U.S. and India. Such gaps may reflect misallocation which hinders aggregate productivity. But differences in measured average products need not reflect differences in true marginal products. We propose a way to estimate the gaps in true marginal products in the presence of measurement error. Our method exploits how revenue growth is less sensitive to input growth when a plant's average products are overstated by measurement error. For Indian manufacturing from 1985'2013, our correction lowers potential gains from reallocation by 20%. For the U.S. the effect is even more dramatic, reducing potential gains by 60% and eliminating 2/3 of a severe downward trend in allocative efficiency over 1978'2013.
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Plant Vintage, Technology, and Environmental Regulation
September 2001
Working Paper Number:
CES-01-08
Does the impact of environmental regulation differ by plant vintage and technology? We answer this question using annual Census Bureau information on 116 pulp and paper mills' vintage, technology, productivity, and pollution abatement operating costs for 1979-1990. We find a significant negative relationship between pollution abatement costs and productivity levels. This is due almost entirely to integrated mills (those incorporating a pulping process), where a one standard deviation increase in abatement costs is predicted to reduce productivity by 5.4 percent. Older plants appear to have lower productivity but are less sensitive to abatement costs, perhaps due to 'grandfathering' of regulations. Mills which undergo renovations are also less sensitive to abatement costs, although these vintage and renovation results are not generally significant. We find similar results using a log-linear version of a three input Cobb-Douglas production function in which we include our technology, vintage, and renovation variables. Sample calculations of the impact of pollution abatement on productivity show the importance of allowing for differences based on plant technology. In a model incorporating technology interactions we estimate that total pollution abatement costs reduce productivity levels by an average of 4.7 percent across all the plants. The comparable estimate without technology interactions is 3.3 percent, approximately 30% lower.
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The Effects of Environmental Regulation on the Competiveness of U.S. Manufacturing
January 2011
Working Paper Number:
CES-11-03
Whether and to what extent environmental regulations influence the competitiveness of firms remains a hotly debated issue. Using detailed production data from tens of thousands of U.S. manufacturing plants drawn from Annual Survey of Manufactures, we estimate the effects of environmental regulations'captured by the Clean Air Act Amendments' division of counties into pollutant-specific nonattainment and attainment categories'on manufacturing plants' total factor productivity (TFP) levels. We find that among surviving polluting plants, a nonattainment designation is associated with a roughly 2.6 percent decline in TFP. The regulations governing ozone have particularly discernable effects on productivity, though effects are also seen among particulates and sulfur dioxide emitters. Carbon monoxide nonattainment, on the other hand, appears to increase measured TFP, though this appears to be concentrated among refineries. When we apply corrections for two likely sources of positive bias in these estimates (price mismeasurement and sample selection on survival), we estimate that the total TFP loss for polluting plants in nonattaining counties is 4.8 percent. This corresponds to an annual lost output in the manufacturing sector of roughly $14.7 billion in 1987 dollars ($24.4 billion in 2009 dollars). These costs have important implications for both the intensity and location of firm expansions.
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Micro Data and the Macro Elasticity of Substitution
March 2012
Working Paper Number:
CES-12-05
We estimate the aggregate elasticity of substitution between capital and labor in the US manufacturing sector. We show that the aggregate elasticity of substitution can be expressed as a simple function of plant level structural parameters and sufficient statistics of the distribution of plant input cost shares. We then use plant level data from the Census of Manufactures to construct a local elasticity of substitution at various levels of aggregation. Our approach does not assume the existence of a stable aggregate production function, as we build up our estimate from the cross section of plants at a point in time. Accounting for substitution within and across plants, we find that the aggregate elasticity is substantially below unity at approximately 0.7. Lastly we assess the sources of the bias of aggregate technical change from 1987 to 1997. We find that the labor augmenting character of aggregate technical change is due almost exclusively to labor augmenting productivity growth at the plant level rather than relative growth in capital intensive plants.
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