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Productivity Races II: The Issue of Capital Measurement
January 1997
Working Paper Number:
CES-97-03
This paper explores the role of capital measurement in determining the productivity of individual textile plants. In addition to gross book value of capital, we experiment with a perpetual inventory measure of capital and implicit (estimated) deflator associated with the age of the plant. Following the methodology of the earlier paper (Productivity Races I), we find that measures of productivity constructed from different measures of capital are highly correlated. Further, their association with alternative measures of economic performance is approximately the same. Nevertheless, the perpetual inventory measure of capital -- the most desirable measure from a theoretical perspective -- does consistently outperform the other two measures.
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Productivity Races I: Are Some Productivuty Measures Better Than Others?
January 1997
Working Paper Number:
CES-97-02
In this study we construct twelve different measures of productivity at the plant level and test which measures of productivity are most closely associated with direct measures of economic performance. We first examine how closely correlated these measures are with various measures of profits. We then evaluate the extent to which each productivity measure is associated with lower rates of plant closure and faster plant growth (growth in employment, output, and capital). All measures of productivity considered are credible in the sense that highly productive plants, regardless of measure, are clearly more profitable, less likely to close, and grow faster. Nevertheless, labor productivity and measures of total factor productivity that are based on regression estimates of production functions are better predictors of plant growth and survival than factor share-based measures of total factor productivity (TFP). Measures of productivity that are based on several years of data appear to outperform measures of productivity that are based solely on data from the most recent year.
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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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Learning by Doing and Plant Characteristics
August 1996
Working Paper Number:
CES-96-05
Learning by doing, especially spillover learning, has received much attention lately in models of industry evolution and economic growth. The predictions of these models depend on the distribution of learning abilities and knowledge flows across firms and countries. However, the empirical literature provides little guidance on these issues. In this paper, I use plant level data on a sample of entrants in SIC 38, Instruments, to examine the characteristics associated with both proprietary and spillover learning by doing. The plant level data permit tests for the relative importance of within and between firm spillovers. I include both formal knowledge, obtained through R&D expenditures, and informal knowledge, obtained through learning by doing, in a production function framework. I allow the speed of learning to vary across plants according to characteristics such as R&D intensity, wages, and the skill mix. The results suggest that (a) Ainformal@ knowledge, accumulated through production experience at the plant, is a much more important source of productivity growth for these plants than is Aformal@ knowledge gained via research and development expenditures, (b) interfirm spillovers are stronger than intrafirm spillovers, (c) the slope of the own learning curve is positively related to worker quality, (d) the slope of the spillover learning curve is positively related to the skill mix at plants, (e) neither own nor spillover learning curve slopes are related to R&D intensities. These results imply that learning by doing may be, to some extent, an endogenous phenomenon at these plants. Thus, models of industry evolution that incorporate learning by doing may need to be revised. The results are also broadly consistent with the recent growth models.
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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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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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