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Whittling Away At Productivity Dispersion
March 1995
Working Paper Number:
CES-95-05
In any time period, in any industry, plant productivity levels differ widely and this dispersion is persistent. This paper explores the sources of this dispersion and their relative magnitudes in the textile industry. Plants that are measured as being more productive but pay higher wages are not necessarily more profitable; wage dispersion can account for approximately 15 percent of productivity dispersion. A plant that is highly productive today may not be as productive tomorrow. I develop a new method for measuring ex-ante dispersion and the percentage of dispersion "explained" by mean reversion. Mean reversion accounts for as much as one half the observed productivity dispersion. A portion of the dispersion, however, appears to reflect real quality differences between plants; plants that are measured as being more productive expand faster and are less likely to exit.
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Pollution Abatement Costs, Regulation And Plant-Level Productivity
December 1994
Working Paper Number:
CES-94-14
We analyze the connection between productivity, pollution abatement expenditures, and other measures of environmental regulation for plants in three industries (paper, oil, and steel). We examine data from 1979 to 1990, considering both total factor productivity levels and growth rates. Plants with higher abatement cost levels have significantly lower productivity levels. The magnitude of the impact is somewhat larger than expected: $1 greater abatement costs appears to be associated with the equivalent of $1.74 in lower productivity for paper mills, $1.35 for oil refineries, and $3.28 for steel mills. However, these results apply only to variation across plants in productivity levels. Estimates looking at productivity variation within plants over time, or estimates using productivity growth rates show a smaller (and insignificant) relationship between abatement costs and productivity. Other measures of environmental regulation faced by the plants (compliance status, enforcement activity, and emissions) are not significantly related to productivity.
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Evidence on the Employer Size-Wage Premium From Worker-Establishment Matched Data
August 1994
Working Paper Number:
CES-94-10
In spite of the large and growing importance of the employer size-wage premium, previous attempts to account for this phenomenon using observable worker or employer characteristics have met with limited success. The primary reason for this lack of success has been the lack of suitable data. While most theoretical explanations for the size-wage premium are based on the matching of employer and employee characteristics, previous empirical work has relied on either worker surveys with little information about a worker's employer, or establishment surveys with little information about workers. In contrast, this study uses the newly created Worker-Establishment Characteristic Database, which contains linked employer-employee data for a large sample of manufacturing workers and establishments, to examine the employer size-wage premium. The main results are: 1) Examining the cross-plant distribution of the skill of workers shows that managers with larger observable measures of skill work in large plants and firms with production workers with larger observable measures of skill. 2) Results from reduced form wage regressions show that including measures of the amount or type of capital in a worker's plant eliminates the establishment size-wage premium. 3) These results are robust to efforts at correcting for possible bias in the parameter estimates due to sample selection. While these findings are consistent with neoclassical explanations for the size-wage premium that hypothesize that large employers employ more skilled workers, their primary importance is that they show that the employer size-wage premium can be accounted for with employer-employee matched data. As such, these data lend support to models which emphasize the role of employer-employee matching in accounting for both cross-sectional and dynamic aspects of the wage distribution.
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On The Turnover of Business Firms and Business Managers
April 1994
Working Paper Number:
CES-92-06
The success of a business depends in part on whether or not the manager and the business make a good "fit" or "match." Success also depends upon characteristics of the business that are distinct from the manager, for example, the convenience of the business location to customers. Variations across firms in "match quality" and in "business quality" account, in part, for why some businesses survive and others are discontinued. This paper is a first attempt at assessing the relative importance of variation in match quality and variation in business quality in accounting for the turnover dynamics of the U.S. small business sector. An evolutionary model is developed in which a selection process tends to eliminate both "unfit" business as well as "unfit" pairings between businesses and managers. We estimated this model with the Characteristics of Business Owners Survey. Our estimates suggest that variations in match quality play a more significant role than variations in business, or general, quality in accounting for turnover behavior of U.S. of small businesses. We discuss the implications of this finding and demonstrate its importance in the context of an experiment conducted in the estimated model economy.
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The Choice of Input-Out Table Embedded in Regional Econometric Input-Out Models
January 1994
Working Paper Number:
CES-94-01
In this paper we investigate the role of input-output data source in the regional econometric input-output models. While there has been a great deal of experimentation focused on the accuracy of alternative methods for estimating regional input-output coefficients, little attention has been directed to the role of accuracy when the input-output system is nested within a broader accounting framework. The issues of accuracy were considered in two contexts, forecasting and impact analysis focusing on a model developed for the Chicago Region. We experimented with three input-output data sources: observed regional data, national input-output, and randomly generated input-output coefficients. The effects of different sources of input-output data on regional econometric input-output model revealed that there are significant differences in results obtained in impact analyses. However, the adjustment processes inherent in the econometric input-output system seem to mute the initial differences in input- output data when the model is used for forecasting. Since applications of these types of models involve both impact and forecasting exercises, there would still seem to be a strong motivation for basing the system on the most accurate set of input-output accounts.
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The Long-Run Demand for Labor: Estimates From Census Establishment Data
September 1993
Working Paper Number:
CES-93-13
This paper estimates long-run demand functions for production workers, production worker hours, and nonproduction workers using micro data from U.S. establishment surveys. The paper focuses on estimation of the wage and output elasticities of labor demand using data on over 41,000 U.S. manufacturing plants in 1975 and more than 30,000 plants in 1981. Particular attention is focused on the problems of unobserved producer heterogeneity and measurement errors in output that can affect labor demand estimates based on establishment survey data. The empirical results reveal that OLS estimates of both the own-price elasticity and the output elasticity of labor demand are biased downward as a result of unobserved heterogeneity. Differencing the data as a solution to this problem greatly exaggerates measurement error in the output coefficients. The use of capital stocks as instrumental variables to correct for measurement error in output significantly alters output elasticities in the expected direction but has no systematic effect on own-price elasticities. All of these patterns are found in estimates that pool establishment data across industries and in industry-specific regressions for the vast majority of industries. Estimates of the output elasticity of labor demand indicate that there are slight increasing returns for production workers and production hours, with a pooled data estimate of .92. The estimate for nonproduction workers in .98. The variation in the output elasticities across industries is fairly small. Estimates of the own-price elasticity vary more substantially with the year, type of differencing used, and industry. They average -.50 for production hours, -.41 for production workers, and -.44 for nonproduction workers. The price elasticities vary widely across manufacturing industries: the interquartile range for the industry estimates is approximately .40.
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Evidence on IO Technology Assumptions From the Longitudinal Research Database
May 1993
Working Paper Number:
CES-93-08
This paper investigates whether a popular IO technology assumption, the commodity technology model, is appropriate for specific United States manufacturing industries, using data on product composition and use of intermediates by individual plants from the Census Longitudinal Research Database. Extant empirical research has suggested the rejection of this model, owing to the implication of aggregate data that negative inputs are required to make particular goods. The plant-level data explored here suggest that much of the rejection of the commodity technology model from aggregative data was spurious; problematic entries in industry-level IO tables generally have a very low Census content. However, among the other industries for which Census data on specified materials use is available, there is a sound statistical basis for rejecting the commodity technology model in about one-third of the cases: a novel econometric test demonstrates a fundamental heterogeneity of materials use among plants that only produce the primary products of the industry.
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Environmental Regulation And Manufacturing Productivity At The Plant Level
March 1993
Working Paper Number:
CES-93-06
This paper presents results for an analysis of plant-level data from three manufacturing industries (paper, oil, and steel). We combine productivity data from the Longitudinal Research Database ( LRD ) with pollution abatement expenditures from the Census Bureau's Pollution Abatement Cost and Expenditures (PACE) survey, as well as regulatory measures taken from datasets maintained by the Environmental Protection Agency. We use data from 1979 to 1985, considering both labor and total factor productivity, both levels and growth rates, and both annual measures and averages over the period. We find a strong connection between regulation and productivity when regulation is measured by compliance costs. More regulated plants have significantly lower productivity levels and slower productivity growth rates than less regulated plants. The magnitude of the impacts are larger than expected: a $1 increase in compliance costs appears to reduce TFP by the equivalent of $3 to $4. Thus, commonly used methods of calculating the impact of regulation on productivity are substantially underestimated. These results are generally consistent across industries and for different estimation methods. Our other measures of regulation (compliance status, enforcement activity, and emissions) show much less consistent results. Higher enforcement, lower compliance, and higher emissions are generally associated with lower productivity levels and slower productivity growth, but the coefficients are rarely significant.
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Learning By Doing And Competition In The Early Rayon Industry
February 1993
Working Paper Number:
CES-93-04
In this paper, I derive a structural econometric model of learning by doing from a dynamic oligopoly game. Unlike previous empirical models, this model is capable of testing hypotheses concerning both the technological nature and behavioral implications of learning. I estimate the model with firm level data from the early U.S. rayon industry. The empirical results show that there were considerable differences across firms in both proprietary and spillover learning. The results also indicate that two of the three firms took their rival's reactions into account when choosing their strategies.
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Manufacturing Establishments Reclassified Into New Industries: The Effect Of Survey Design Rules
November 1992
Working Paper Number:
CES-92-14
Establishment reclassification occurs when an establishment classified in one industry in one year is reclassified into another industry in another year. Because of survey design rules at the Census Bureau these reclassifications occur systematically over time, and affect the industry-level time series of output and employment. The evidence shows that reclassified establishments occur most often in two distinct years over the life of a sample panel. Switches are not only numerous in these years, they also contribute significantly to measured industry change in industry output and employment. The problem is that reclassifications are not necessarily processed in the year that they occur. The survey rules restrict most change to certain years. The effect of these rules is evidenced by looking at the variance across industry growth rates which increases greatly in these two years. Whatever the reason for reclassifying an establishment, the way the switches are processed raises the possibility of measurement errors in the industry level statistics. Researchers and policymakers relying upon observations in annual changes in industry statistics should be aware of these systematic discontinuities, discrepancies and potential data distortions.
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