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Towards Unrestricted Public Use Business Microdata: The Synthetic Longitudinal Business Database
February 2011
Working Paper Number:
CES-11-04
In most countries, national statistical agencies do not release establishment-level business microdata, because doing so represents too large a risk to establishments\' confidentiality. One approach with the potential for overcoming these risks is to release synthetic data; that is, the released establishment data are simulated from statistical models designed to mimic the distributions of the underlying real microdata. In this article, we describe an application of this strategy to create a public use file for the Longitudinal Business Database, an annual economic census of establishments in the United States comprising more than 20 million records dating back to 1976. The U.S. Bureau of the Census and the Internal Revenue Service recently approved the release of these synthetic microdata for public use, making the synthetic Longitudinal Business Database the first-ever business microdata set publicly released in the United States. We describe how we created the synthetic data, evaluated analytical validity, and assessed disclosure risk.
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Local Environmental Regulation and Plant-Level Productivity
September 2010
Working Paper Number:
CES-10-30R
This paper examines the impact of environmental regulation on the productivity of manufacturing plants in the United States. Establishment-level data from three Censuses of Manufactures are used to estimate 3-factor Cobb-Douglas production functions that include a measure of the stringency of environmental regulation faced by manufacturing plants. In contrast to previous studies, this paper examines effects on plants in all manufacturing industries, not just those in 'dirty' industries. Further, this paper employs spatial-temporal variation in environmental compliance costs to identify effects, using a time-varying county-level index that is based on multiple years of establishment-level data from the Pollution Abatement Costs and Expenditures survey and the Annual Survey of Manufactures. Results suggest that, for the average manufacturing plant, the effect on productivity of being in a county with higher environmental compliance costs is relatively small and often not statistically significant. For the average plant, the main effect of environmental regulation may not be in the spatial and temporal dimensions.
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On Spatial Heterogeneity in Environmental Compliance Costs
September 2009
Working Paper Number:
CES-09-25R
This paper examines the extent of variation in regulatory stringency below the state level, using establishment-level data from the U.S. Census Bureau's Pollution Abatement Costs and Expenditures (PACE) survey to estimate a county-level index of environmental compliance costs (ECC). County-level variation is found to explain 11-18 times more of the variation in ECC than state-level variation alone, and the range of ECC within a state is often large. At least 34% of U.S. counties have ECC that are statistically different from their states'. Results suggest that important spatial variation is lost in state-level studies of environmental regulation.
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The Green Industry: An Examination of Environmental Products Manufacturing
September 2008
Working Paper Number:
CES-08-34
The "green industry" is often noted in discussions of the costs and benefits of environmental policy, and it has been characterized as a unique industry with substantial potential for employment growth, well-paying jobs, and export opportunities. In this paper, we examine the characteristics and recent economic performance of the green industry, using establishment-level data on environmental products manufacturers (EPMs) from the 1995 Survey of Environmental Products and Services, together with data from the Annual Survey of Manufactures and various Census of Manufactures. Results suggest that there are some differences between EPMs and their non-EPM counterparts in the same industry, in terms of employment, employee compensation, exports, and productivity. However, we do not find any evidence that EPMs performed any better than otherwise similar plants, in terms of survival, employment growth, wage growth, and export growth. Our findings offer a more complex and nuanced portrayal of the green industry than is typical, and we suggest that this industry may not be as exceptional as is sometimes maintained.
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Business Volatility, Job Destruction, and Unemployment
August 2008
Working Paper Number:
CES-08-26
Unemployment inflows fell from 4 percent of employment per month in the early 1980s to 2 percent or less by the mid 1990s and thereafter. U.S. data also show a secular decline in the job destruction rate and the volatility of firm-level employment growth rates. We interpret this decline as a decrease in the intensity of idiosyncratic labor demand shocks, a key parameter in search and matching models of unemployment. According to these models, a lower intensity of idiosyncratic shocks produces less job destruction, fewer workers flowing through the unemployment pool and less frictional unemployment. To evaluate the importance of this theoretical mechanism, we relate industry-level unemployment flows from 1977 to 2005 to industry-level indicators for the intensity of idiosyncratic shocks. Unlike previous research, we focus on the lower frequency relationship of job destruction and business volatility to unemployment flows. We find strong evidence that declines in the intensity of idiosyncratic labor demand shocks drove big declines in the incidence and rate of unemployment. This evidence implies that the unemployment rate has become much less sensitive to cyclical movements in the job-finding rate.
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Mergers and Acquisitions, Employment, Wages and Plant Closures in the U.S. Meat Product Industries: Evidence from Micro Data
March 2007
Working Paper Number:
CES-07-08
The purpose of this paper is to evaluate the impact of mergers and acquisitions (M&As) on wages and employment and plant closures in the meat packing, prepared meat products, and poultry slaughter and processing industries over 1977-87 and 1982-92. The analysis relies on a balanced panel dataset of all plants owned by meat and poultry firms that existed over 1977-87 or 1982-92. We find that (1) M&As are positively associated with wages in the meat packing and prepared meat products industries over 1977-87, but not over 1982-92; (2) changes in employment are positively related to M&As in all three meat and poultry industries over 1977-87, but only in the poultry industry over 1982-92; and (3) M&As are negatively associated with plant closures.
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Micro and Macro Data Integration: The Case of Capital
May 2005
Working Paper Number:
CES-05-02
Micro and macro data integration should be an objective of economic measurement as it is clearly advantageous to have internally consistent measurement at all levels of aggregation ' firm, industry and aggregate. In spite of the apparently compelling arguments, there are few measures of business activity that achieve anything close to micro/macro data internal consistency. The measures of business activity that are arguably the worst on this dimension are capital stocks and flows. In this paper, we document, quantify and analyze the widely different approaches to the measurement of capital from the aggregate (top down) and micro (bottom up) perspectives. We find that recent developments in data collection permit improved integration of the top down and bottom up approaches. We develop a prototype hybrid method that exploits these data to improve micro/macro data internal consistency in a manner that could potentially lead to substantially improved measures of capital stocks and flows at the industry level. We also explore the properties of the micro distribution of investment. In spite of substantial data and associated measurement limitations, we show that the micro distributions of investment exhibit properties that are of interest to both micro and macro analysts of investment behavior. These findings help highlight some of the potential benefits of micro/macro data integration.
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Estimating A Multivariate Arma Model with Mixed-Frequency Data: An Application to Forecasting U.S. GNP at Monthly Intervals
July 1990
Working Paper Number:
CES-90-05
This paper develops and applies a method for directly estimating a multivariate, autoregressive moving-average (ARMA) model with mixed-frequency, time-series data. Unlike standard, single-frequency methods, the method does not require the data to be transformed to a single frequency (by temporally aggregating higher-frequency data to lower frequencies for interpolating lower-frequency data to higher frequencies) or the model to be restricted by frequency. Subject to computational constraints, the method can handle any number of variable and frequencies. In addition, variable can be treated as temporally aggregated and observed with errors and delays. The key to the method is to view lower-frequency data as periodically missing and to use the missing-data variant of the Kalman filter.
In the application, a bivariate, ARMA model is estimated with monthly observations on total employment and quarterly observations on real GNP, in the U.S., for January 1958 to December 1978. The estimated model is, then, used to compute monthly forecasts of the variables for 1 to 12 months ahead, for January 1979 to December 1988. Compared with GNP forecasts, in particular, for similar periods produced by established econometric and time series models, present GNP forecasts are generally more accurate for 1 to 4 months ahead and about equally or slightly less accurate for 5 to 12 months ahead. The application, thus, shows that the present method is tractable and able to effectively exploit cross-frequency sample information, in ARMA estimate and forecasting, which standard methods cannot exploit at all.
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