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Efficiency of Bankrupt Firms and Industry Conditions: Theory and Evidence
October 1996
Working Paper Number:
CES-96-12
We show that the incentives to reorganize inefficient firms and redeploy their assets depend on the change in industry output and industry characteristics. We use plant-level data to investigate the productivity of Chapter 11 bankrupt firms and asset-sale and closure decisions. We find no evidence of bankruptcy costs in industries with declining output growth, where most bankruptcies occur. In declining industries, bankrupt firms' plants are not less productive than industry averages and do not decline in productivity while in Chapter 11. In these industries, Chapter 11 appears to be a mechanism for fostering exit of capacity. In high-growth industries, there is some limited evidence of productivity declines while in Chapter 11 for a subsample of firms that remain in Chapter 11 for four or more years. Examining asset sales and closures by bankrupt firms and their competitors, we find that Chapter 11 status is of limited importance in predicting these decisions once industry and plant characteristics are taken into account. More generally, the findings imply that Chapter 11 may involve few real economic costs, and that industry effects and sample selection issues are very important in evaluating the performance of bankrupt firms.
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Technology and Jobs: Secular Changes and Cyclical Dynamics
September 1996
Working Paper Number:
CES-96-07
In this paper, we exploit plant-level data for U.S. manufacturing for the 1970s and 1980s to explore the connections between changes in technology and the structure of employment and wages. We focus on the nonproduction labor share (measured alternatively by employment and wages) as the variable of interest. Our main findings are summarized as follows: (i) aggregate changes in the nonproduction labor share at annual and longer frequencies are dominated by within plant changes; (ii) the distribution of annual within plant changes exhibits a spike at zero, tremendous heterogeneity and fat left and right tails; (iii) within plant secular changes are concentrated in recessions; and (iv) while observable indicators of changes in technology account for a significant fraction of the secular increase in the average nonproduction labor share, unobservable factors account for most of the secular increase, most of the cyclical variation and most of the cross sectional heterogeneity.
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ARE FIXED EFFECTS FIXED? Persistence in Plant Level Productivity
May 1996
Working Paper Number:
CES-96-03
Estimates of production functions suffer from an omitted variable problem; plant quality is an omitted variable that is likely to be correlated with variable inputs. One approach is to capture differences in plant qualities through plant specific intercepts, i.e., to estimate a fixed effects model. For this technique to work, it is necessary that differences in plant quality are more or less fixed; if the "fixed effects" erode over time, such a procedure becomes problematic, especially when working with long panels. In this paper, a standard fixed effects model, extended to allow for serial correlation in the error term, is applied to a 16-year panel of textile plants. This parametric approach strongly accepts the hypothesis of fixed effects. They account for about one-third of the variation in productivity. A simple non-parametric approach, however, concludes that differences in plant qualities erode over time, that is plant qualities f-mix. Monte Carlo results demonstrate that this discrepancy comes from the parametric approach imposing an overly restrictive functional form on the data; if there were fixed effects of the magnitude measured, one would reject the hypothesis of f-mixing. For textiles, at least, the functional form of a fixed effects model appears to generate misleading conclusions. A more flexible functional form is estimated. The "fixed" effects actually have a half life of approximately 10 to 20 years, and they account for about one-half the variation in productivity.
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Evaluation And Use Of The Pollution Abatement Costs And Expenditures Survey Micro Data
January 1996
Working Paper Number:
CES-96-01
The Pollution Abatement Costs and Expenditures Survey (PACE) is an annual survey of manufacturing establishment=s operating costs and capital investment expenditures for pollution abatement purposes. This paper provides a description and evaluation of the PACE micro data available at the Center for Economic Studies (CES). The paper provides an overview of the survey, how the sample is drawn, how the survey questionnaire has changed over time, an assessment of the data quality, and suggestions for the use of the data, as well as its limitations. Also included are suggestions for modifying the survey design and data processing procedures. The PACE data series, linked to the economic data in CES= Longitudinal Research Database (LRD), covers the years 1979-1993, excluding 1983 and 1987.
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Using Matched Client And Census Data To Evaluate The Performance Of The Manufacturing Extension Partnership
April 1995
Working Paper Number:
CES-95-07
This paper proposes a framework for evaluating the Manufacturing Extension Partnership (MEP). The MEP is administered by the National Institute of Standards and Technology (NIST) as part of its effort to improve the global competitiveness of U.S. manufacturing industries. As the name implies, the MEP is modelled after agricultural extension. Rather than farmers the MEP's target population is small and medium sized manufacturers, generally those with less than 500 employees. The MEP currently supports 44 manufacturing extension centers around the country. These centers provide technical and business assistance for manufacturers much as county extension agents do for farmers. The goal of evaluation is to see if MEP engagements lead to positive outcomes from the view of important MEP stakeholders (e.g., MEP clients, MEP centers, NIST, state and local governments and Congress). These outcomes are discussed in McGuckin and Redman (1995) and include: Process Outcomes (e.g., adoption of a new technology by a client); Intermediate Outcomes (e.g., reduction in the clients defect rate); Business Outcomes (e.g., survival and profits) and Policy Outcomes (increases in employment,wages and/or exports). The evaluation framework described in this paper has two components. The first component is an evaluation dataset which contains measures of many of the program outcomes listed above for both MEP clients and a representative control group of non- clients. This dataset will be constructed by linking MEP client records with plant level Census data housed at the Center for Economic Studies of the Census Bureau. The Census data provides measures of several outcome and control variables which are comparable across both plants and time. The Census data include observations for all manufacturing plants in the U.S. from which representative control groups can be constructed. The MEP client records provide data on the type and intensity of extension engagements. Linking these rich sources of information yields a comprehensive and powerful dataset for MEP evaluation. The second component is an evaluation methodology which exploits this rich dataset to make statistical inferences about the impact of MEP services, while carefully controlling for other influences. By using this methodology, we can address many of the shortcomings which plagued previous attempts to evaluate extension services. In addition to evaluation, the dataset described in this paper may be used to profile the characteristics of MEP clients and compare them to non-clients. The Census data contain the complete universe of manufacturing establishments in the U.S.
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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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Capital Structure and Product Market Behavior: An Examination of Plant Exit and Investment Decisions
March 1995
Working Paper Number:
CES-95-04
This paper examines whether capital structure decisions interact with product market characteristics to influence plant closing and investment decisions. The empirical evidence in this paper shows that a firm's capital structure, plant level efficiency, and industry capacity utilization are significant determinants of plant (dis)investment decisions. We find that the effects of high leverage on investment and plant closing are significant when the industry is highly concentrated. Following their recapitalizations, firms in industries with high concentration are more likely to close plants and less likely to invest. In addition, we find that rival firms are less likely to close plants and more likely to invest when the market share of leveraged firms is higher.
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Capital Structure And Product Market Rivalry: How Do We Reconcile Theory And Evidence?
February 1995
Working Paper Number:
CES-95-03
This paper presents empirical evidence on the interaction of capital structure decisions and product market behavior. We examine when firms recapitalize and increase the proportion of debt in their capital structure. The evidence in this paper shows that firms with low productivity plants in highly concentrated industries are more likely to recapitalize and increase debt financing. This finding suggests that debt plays a role in highly concentrated industries where agency costs are not significantly reduced by product market competition. Following the empirical evidence we introduce the "strategic investment" effects of debt and argue that this effect, in conjunction with agency costs, appears to fit the data.
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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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The Span of the Effect of R&D in the Firm and Industry
May 1994
Working Paper Number:
CES-94-07
Previous studies have found that the firm's own research and spillovers of research by related firms increase firm productivity. In contrast, in this paper we explore the impact of firm R&D on the productivity of its individual plants. We carry out this investigation of within firm R&D effects using a unique set of Census data. The data, which are from the chemicals industry, are a match of plant level productivity and other characteristics with firm level data on R&D of the parent company, cross-classified by location and applied product field. We explore three aspects of the span of effect of the firm's R&D: (i), the degree to which its R&D is "public" across plants; (ii), the extent of its localization in geographic space, and (iii), the breadth of its relevance outside the applied product area in which it is classified. We find that (i), firm R&D acts more like a private input which is strongly amortized by the number of plants in the firm; (ii), firm R&D is geographically localized, and exerts greater influence on productivity when it is conducted nearer to the plant; and (iii), firm R&D in a given applied product area is of limited relevance to plants producing outside that product area. Moreover, we find that while geographic localization remains significant, it diminishes over time. This trend is consistent with the effect of improved telecommunications on increased information flows within organizations. Finally, we consider spillovers of R&D from the rest of industry, finding that the marginal product of industry R&D on plant productivity, though positive and significant, is far smaller than the marginal product of parent firm's R&D.
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