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State Taxation and the Reallocation of Business Activity: Evidence from Establishment-Level Data
January 2017
Working Paper Number:
CES-17-02
Using Census microdata on multi-state firms, we estimate the impact of state taxes on business activity. For C corporations, employment and the number of establishments have corporate tax elasticities of -0.4, and do not vary with changes in personal tax rates. Pass-through entity activities show tax elasticities of -0.2 to -0.3 with respect to personal tax rates, and are invariant with respect to corporate tax rates. Reallocation of productive resources to other states drives around half the effect. Capital shows similar patterns but is 36% less elastic than labor. The responses are strongest for firms in tradable and footloose industries.
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Measuring Plant Level Energy Efficiency and Technical Change in the U.S. Metal-Based Durable Manufacturing Sector Using Stochastic Frontier Analysis
January 2016
Working Paper Number:
CES-16-52
This study analyzes the electric and thermal energy efficiency for five different metal-based durable manufacturing industries in the United States from 1987-2012 at the 3 digit North American Industry Classification System (NAICS) level. Using confidential plant-level data on energy use and production from the quinquennial U.S. Economic Census, a stochastic frontier regression analysis (SFA) is applied in six repeated cross sections for each five year census. The SFA controls for energy prices and climate-driven energy demand (heating degree days - HDD - and cooling degree days - CDD) due to differences in plant level locations, as well as 6-digit NAICS industry effects. A Malmquist index is used to decompose aggregate plant technical change in energy use into indices of efficiency and frontier (best practice) change. Own energy price elasticities range from -.7 to -1.0, with electricity tending to have slightly higher elasticity than fuel. Mean efficiency estimates (100 percent equals best practice level) range from a low of 32 percent (thermal 334 - Computer and Electronic Products) to a high of 86 percent (electricity 332 - Fabricated Metal Products). Electric efficiency is consistently better than thermal efficiency for all NAICS. There is no clear pattern to the decomposition of aggregate technical Thermal change. In some years efficiency improvement dominates; in other years aggregate technical change is driven by improvement in best practice.
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Water Use and Conservation in Manufacturing:
Evidence from U.S. Microdata
June 2015
Working Paper Number:
CES-15-16R
Water can be a scarce resource, particularly in certain places at certain times. Understanding both water use and conservation efforts can help ensure that limited supplies can meet the demands of a growing population and economy. This paper examines water use and recirculation in the U.S. manufacturing sector, using newly recovered microdata from the Survey of Water Use in Manufacturing, merged with establishment-level data from the Annual Survey of Manufactures and the Census of Manufactures. Results suggest that water use per unit of output is largest for larger establishments, in part because larger establishments use water for more purposes. Larger establishments are also found to recirculate water more ' satisfying demand (water use) without necessarily increasing water intake. Various costs also appear to play a role in water recirculation. In particular, the water circulation rate is found to be higher when water is purchased from a utility. Relatively low (internal) prices for self-supplied water could suppress the incentive to invest in recirculation. Meanwhile, establishments with higher per-gallon intake treatment costs also recirculate more, as might be expected. The cost associated with water discharge ' due to regulation or otherwise ' also increases circulation rates. The aridity of a locale is found to have little effect on circulation rates.
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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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Are We Undercounting Reallocation's Contribution to Growth?
January 2013
Working Paper Number:
CES-13-55R
There has been a strong surge in aggregate productivity growth in India since 1990, following
significant economic reforms. Three recent studies have used two distinct methodologies to decompose the sources of growth, and all conclude that it has been driven by within-plant increases in technical efficiency and not between-plant reallocation of inputs. Given the nature of the reforms, where many barriers to input reallocation were removed, this finding has surprised researchers and been dubbed 'India's Mysterious Manufacturing Miracle.' In this paper, we show that the methodologies used may artificially understate the extent of reallocation. One approach, using growth in value added, counts all reallocation growth arising from the movement of intermediate inputs as technical efficiency growth. The second approach, using the Olley-Pakes decomposition, uses estimates of plant-level total factor productivity (TFP) as a proxy for the marginal product of inputs. However, in equilibrium, TFP and the marginal product of inputs are unrelated. Using microdata on manufacturing from five countries ' India, the U.S., Chile, Colombia, and Slovenia ' we show that both approaches significantly understate the true
role of reallocation in economic growth. In particular, reallocation of materials is responsible for over half of aggregate Indian manufacturing productivity growth since 2000, substantially larger than either the contribution of primary inputs or the change in the covariance of productivity and size.
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Productivity Dispersion and Plant Selection in the Ready-Mix Concrete Industry
September 2011
Working Paper Number:
CES-11-25
This paper presents a quantitative model of productivity dispersion to explain why inefficient producers are slowly selected out of the ready-mix concrete industry. Measured productivity dispersion between the 10th and 90th percentile falls from a 4 to 1 difference using OLS, to a 2 to 1 difference using a control function. Due to volatile productivity and high sunk entry costs, a dynamic oligopoly model shows that to rationalize small gaps in exit rates between high and low productivity plants, a plant in the top quintile must produce 1.5 times more than a plant in the bottom quintile.
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The Cyclicality of Productivity Dispersion
May 2011
Working Paper Number:
CES-11-15
Using plant-level data, I show that the dispersion of total factor productivity in U.S. durable manufacturing is greater in recessions than in booms. This cyclical property of productivity dispersion is much less pronounced in non-durable manufacturing. In durables, this phenomenon primarily reflects a relatively higher share of unproductive firms in a recession. In order to interpret these findings, I construct a business cycle model where production in durables requires a fixed input. In a boom, when the market price of this fixed input is high, only more productive firms enter and only more productive incumbents survive, which results in a more compressed productivity distribution. The resulting higher average productivity in durables endogenously translates into a lower average relative price of durables. Additionally, my model is consistent with the following business cycle facts: procyclical entry, procyclical aggregate total factor productivity, more procyclicality in durable than non-durable output, procyclical employment and countercyclicality in the relative price of durables and the cross section of stock returns.
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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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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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The Impact of Plant-Level Resource Reallocations and Technical Progress on U.S. Macroeconomic Growth
December 2009
Working Paper Number:
CES-09-43
We build up from the plant level an "aggregate(d) Solow residual" by estimating every U.S. manufacturing plant's contribution to the change in aggregate final demand between 1976 and 1996. We decompose these contributions into plant-level resource reallocations and plant-level technical efficiency changes. We allow for 459 different production technologies, one for each 4- digit SIC code. Our framework uses the Petrin and Levinsohn (2008) definition of aggregate productivity growth, which aggregates plant-level changes to changes in aggregate final demand in the presence of imperfect competition and other distortions and frictions. On average, we find that aggregate reallocation made a larger contribution than aggregate technical efficiency growth. Our estimates of the contribution of reallocation range from 1:7% to2:1% per year, while our estimates of the average contribution of aggregate technical efficiency growth range from 0:2% to 0:6% per year. In terms of cyclicality, the aggregate technical efficiency component has a standard deviation that is roughly 50% to 100% larger than that of aggregate total reallocation, pointing to an important role for technical efficiency in macroeconomic fluctuations. Aggregate reallocation is negative in only 3 of the 20 years of our sample, suggesting that the movement of inputs to more highly valued activities on average plays a stabilizing role in manufacturing growth.
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