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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Cogeneration Technology Adoption in the U.S.
January 2016
Working Paper Number:
CES-16-30
Well over half of all electricity generated in recent years in Denmark is through cogeneration. In U.S., however, this number is only roughly eight percent. While both the federal and state governments provided regulatory incentives for more cogeneration adoption, the capacity added in the past five years have been the lowest since late 1970s. My goal is to first understand what are and their relative importance of the factors that drive cogeneration technology adoption, with an emphasis on estimating the elasticity of adoption with respect to relative energy input prices and regulatory factors. Very preliminary results show that with a 1 cent increase in purchased electricity price from 6 cents (roughly current average) to 7 cents per kwh, the likelihood of cogeneration technology adoption goes up by about 0.7-1 percent. Then I will try to address the general equilibrium effect of cogeneration adoption in the electricity generation sector as a whole and potentially estimate some key parameters that the social planner would need to determine the optimal cogeneration investment amount. Partial equilibrium setting does not consider the decrease in investment in the utilities sector when facing competition from the distributed electricity generators, and therefore ignore the effects from the change in equilibrium price of electricity. The competitive market equilibrium setting does not consider the externality in the reduction of CO2 emissions, and leads to socially sub-optimal investment in cogeneration. If we were to achieve the national goal to increase cogeneration capacity half of the current capacity by 2020, the US Department of Energy (DOE) estimated an annual reduction of 150 million metric tons of CO2 annually ' equivalent to the emissions from over 25 million cars. This is about five times the annual carbon reduction from deregulation and consolidation in the US nuclear power industry (Davis, Wolfram 2012). Although the DOE estimates could be an overly optimistic estimate, it nonetheless suggests the large potential in the adoption of cogeneration technology.
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The Effect of Power Plants on Local Housing Values and Rents: Evidence from Restricted Census Microdata
July 2008
Working Paper Number:
CES-08-19
Current trends in electricity consumption imply that hundreds of new fossil-fuel power plants will be built in the United States over the next several decades. Power plant siting has become increasingly contentious, in part because power plants are a source of numerous negative local externalities including elevated levels of air pollution, haze, noise and traffic. Policymakers attempt to take these local disamenities into account when siting facilities, but little reliable evidence is available about their quantitative importance. This paper examines neighborhoods in the United States where power plants were opened during the 1990s using household-level data from a restricted version of the U.S. decennial census. Compared to neighborhoods farther away, housing values and rents decreased by 3-5% between 1990 and 2000 in neighborhoods near sites. Estimates of household marginal willingness-to-pay to avoid power plants are reported separately for natural gas and other types of plants, large plants and small plants, base load plants and peaker plants, and upwind and downwind households.
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Technology Lock-In and Costs of Delayed Climate Policy
July 2023
Working Paper Number:
CES-23-33
This paper studies the implications of current energy prices for future energy efficiency and climate policy. Using U.S. Census microdata and quasi-experimental variation in energy prices, we first show that manufacturing plants that open when electricity prices are low consume more energy throughout their lifetime, regardless of current electricity prices. We then estimate that a persistent bias of technological change toward energy can explain the long-term effects of entry-year electricity prices on energy intensity. Overall, this 'technology lock-in' implies that increasing entry-year electricity prices by 10% would decrease a plant's energy intensity of production by 3% throughout its lifetime.
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Older and Slower: The Startup Deficit's Lasting Effects on Aggregate Productivity Growth
June 2018
Working Paper Number:
CES-18-29
We investigate the link between declining firm entry, aging incumbent firms and sluggish U.S. productivity growth. We provide a dynamic decomposition framework to characterize the contributions to industry productivity growth across the firm age distribution and apply this framework to the newly developed Revenue-enhanced Longitudinal Business Database (ReLBD). Overall, several key findings emerge: (i) the relationship between firm age and productivity growth is downward sloping and convex; (ii) the magnitudes are substantial and significant but fade quickly, with nearly 2/3 of the effect disappearing after five years and nearly the entire effect disappearing after ten; (iii) the higher productivity growth of young firms is driven nearly exclusively by the forces of selection and reallocation. Our results suggest a cumulative drag on aggregate productivity of 3.1% since 1980. Using an instrumental variables strategy we find a consistent pattern across states/MSAs in the U.S. The patterns are broadly consistent with a standard model of firm dynamics with monopolistic competition.
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Are We Overstating the Economic Costs of Environmental Protection?
May 1997
Working Paper Number:
CES-97-12
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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Evidence for the Effects of Mergers on Market Power and Efficiency
January 2016
Working Paper Number:
CES-16-43
Study of the impact of mergers and acquisitions (M&As) on productivity and market power has been complicated by the difficulty of separating these two effects. We use newly-developed techniques to separately estimate productivity and markups across a wide range of industries using confidential data from the U.S. Census Bureau. Employing a difference-in-differences framework, we find that M&As are associated with increases in average markups, but find little evidence for effects on plant-level productivity. We also examine whether M&As increase efficiency through reallocation of production to more efficient plants or through reductions in administrative operations, but again find little evidence for these channels, on average. The results are robust to a range of approaches to
address the endogeneity of firms' merger decisions.
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Unionization, Employer Opposition, and Establishment Closure
July 2023
Working Paper Number:
CES-23-35
We study the effect of private-sector unionization on establishment employment and survival. Specifically, we analyze National Labor Relations Board union elections from 1981'2005 using administrative Census data. Our empirical strategy extends standard difference-in-differences techniques with regression discontinuity extrapolation methods. This allows us to avoid biases from only comparing close elections and to estimate treatment effects that include larger marginof- victory elections. Using this strategy, we show that unionization decreases an establishment's employment and likelihood of survival, particularly in manufacturing and other blue-collar and industrial sectors. We hypothesize that two reasons for these effects are firms' ability to avoid working with new unions and employers' opposition to unions. We find that the negative effects are significantly larger for elections at multi-establishment firms. Additionally, after a successful union election at one establishment, employment increases at the firms' other establishments. Both pieces of evidence are consistent with firms avoiding new unions by shifting production from unionized establishments to other establishments. Finally, we find larger declines in employment and survival following elections where managers or owners were likely more opposed to the union. This evidence supports new reasons for the negative effects of unionization we document.
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Euler-Equation Estimation for Discrete Choice Models: A Capital Accumulation Application
January 2010
Working Paper Number:
CES-10-02
This paper studies capital adjustment at the establishment level. Our goal is to characterize capital adjustment costs, which are important for understanding both the dynamics of aggregate investment and the impact of various policies on capital accumulation. Our estimation strategy searches for parameters that minimize ex post errors in an Euler equation. This strategy is quite common in models for which adjustment occurs in each period. Here, we extend that logic to the estimation of parameters of dynamic optimization problems in which non-convexities lead to extended periods of investment inactivity. In doing so, we create a method to take into account censored observations stemming from intermittent investment. This methodology allows us to take the structural model directly to the data, avoiding time-consuming simulation based methods. To study the effectiveness of this methodology, we first undertake several Monte Carlo exercises using data generated by the structural model. We then estimate capital adjustment costs for U.S. manufacturing establishments in two sectors.
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Entry Costs Rise with Growth
October 2024
Working Paper Number:
CES-24-63
Over time and across states in the U.S., the number of firms is more closely tied to overall employment than to output per worker. In many models of firm dynamics, trade, and growth with a free entry condition, these facts imply that the costs of creating a new firm increase sharply with productivity growth. This increase in entry costs can stem from the rising cost of labor used in entry and weak or negative knowledge spillovers from prior entry. Our findings suggest that productivity-enhancing policies will not induce firm entry, thereby limiting the total impact of such policies on welfare.
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Empirical Distribution of the Plant-Level Components of Energy and Carbon Intensity at the Six-digit NAICS Level Using a Modified KAYA Identity
September 2024
Working Paper Number:
CES-24-46
Three basic pillars of industry-level decarbonization are energy efficiency, decarbonization of energy sources, and electrification. This paper provides estimates of a decomposition of these three components of carbon emissions by industry: energy intensity, carbon intensity of energy, and energy (fuel) mix. These estimates are constructed at the six-digit NAICS level from non-public, plant-level data collected by the Census Bureau. Four quintiles of the distribution of each of the three components are constructed, using multiple imputation (MI) to deal with non-reported energy variables in the Census data. MI allows the estimates to avoid non-reporting bias. MI also allows more six-digit NAICS to be estimated under Census non-disclosure rules, since dropping non-reported observations may have reduced the sample sizes unnecessarily. The estimates show wide variation in each of these three components of emissions (intensity) and provide a first empirical look into the plant-level variation that underlies carbon emissions.
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