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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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Estimating Capital Efficiency Schedules Within Production Functions
May 1992
Working Paper Number:
CES-92-04
The appropriate method for aggregating capital goods across vintages to produce a single capital stock measure has long been a contentious issue, and the literature covering this topic is quite extensive. This paper presents a methodology that estimates efficiency schedules within a production function, allowing the data to reveal how the efficiency of capital goods evolve as they age. Specifically we insert a parameterized investment stream into the position of a capital variable in a production function, and then estimate the parameters of the production function simultaneously with the parameters of the investment stream. Plant level panel data for a select group of steel plants employing a common technology are used to estimate the model. Our primary finding is that when using a simple Cobb Douglas production function, the estimated efficiency schedules appear to follow a geometric pattern, which is consistent with the estimates of economic depreciation of Hulten and Wykoff (1981). Results from more flexible functional forms produced much less precise and unreliable estimates.
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The Dynamics Of Productivity In The Telecommunications Equipment Industry
February 1992
Working Paper Number:
CES-92-02
Technological change and deregulation have caused a major restructuring of the telecommunications equipment industry over the last two decades. We estimate the parameters of a production function for the equipment industry and then use those estimates to analyze the evolution of plant-level productivity over this period. The restructuring involved significant entry and exit and large changes in the sizes of incumbents. Since firms choices on whether to liquidate and the on the quantities of inputs demanded should they continue depend on their productivity, we develop an estimation algorithm that takes into account the relationship between productivity on the one hand, and both input demand and survival on the other. The algorithm is guided by a dynamic equilibrium model that generates the exit and input demand equations needed to correct for the simultaneity and selection problems. A fully parametric estimation algorithm based on these decision rules would be both computationally burdensome and require a host of auxiliary assumptions. So we develop a semiparametric technique which is both consistent with a quite general version of the theoretical framework and easy to use. The algorithm produces markedly different estimates of both production function parameters and of productivity movements than traditional estimation procedures. We find an increase in the rate of industry productivity growth after deregulation. This in spite of the fact that there was no increase in the average of the plants' rates of productivity growth, and there was actually a fall in our index of the efficiency of the allocation of variable factors conditional on the existing distribution of fixed factors. Deregulation was, however, followed by a reallocation of capital towards more productive establishments (by a down sizing, often shutdown, of unproductive plants and by a disproportionate growth of productive establishments) which more than offset the other factors' negative impacts on aggregate productivity.
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Technical Inefficiency And Productive Decline In The U.S. Interstate Natural Gas Pipeline Industry Under The Natural Gas Policy Act
October 1991
Working Paper Number:
CES-91-06
The U.S. natural gas industry has undergone substantial change since the enactment of the Natural Gas Policy Act of 1978. Although the major focus of the NGPA was to initiate partial and gradual price deregulation of natural gas at the well-head, the interstate transmission industry was profoundly affected by changes in the relative prices of competing fuels and contractual relationships among producers, transporters, distributors, and end-users. This paper assesses the impact of the NGPA on the technical efficiency and productivity of fourteen interstate natural gas transmission firms for the period 1978-1985. We focus on the distortionary effects that resulted in the industry during a period in which changes in regulatory policy could neither anticipate changing market conditions nor rapidly adjust to those changes. Two alternative estimating methodologies, stochastic frontier production analysis and data envelopment analysis, are used to measure the firm-specific and temporal distortionary effects. Concordant findings from these alternative methodologies suggest a pervasive pattern of declining technical efficiency in the industry during the period in which this major regulatory intervention was introduced and implemented. The representative firms experience an average annual decline in efficiency of .55 percent over the sample period. In addition, it appears that the industry suffered a decline in productivity during the sample period, averaging -1.18 percent annually.
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Decomposing Technical Change
May 1991
Working Paper Number:
CES-91-04
A production function is specified with human capital as a separate argument and with embodied technical change proxied by a variable that measures the average vintage of the stock of capital. The coefficients of this production function are estimated with cross section data for roughly 2,150 new manufacturing plants in 41 industries, and for subsets of this sample. The question of interactions between new investment and initial endowments of capital is then examined with data for roughly 1,400 old plants in 15 industries.
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Measuring Total Factor Productivity, Technical Change And The Rate Of Returns To Research And Development
May 1991
Working Paper Number:
CES-91-03
Recent research indicates that estimates of the effect of research and development (R&D) on total factor productivity growth are sensitive to different measures of total factor productivity. In this paper, we use establishment level data for the flat glass industry extracted from the Census Bureau's Longitudinal Research Database (LRD) to construct three competing measures of total factor productivity. We then use these measures to estimate the conventional R&D intensity model. Our empirical results support previous finding that the estimated coefficients of the model are sensitive to the measurement of total factor productivity. Also, when using microdata and more detailed modeling, R&D is found to be a significant factor influencing productivity growth. Finally, for the flat glass industry, a specific technical change index capturing the learning-by-doing process appears to be superior to the conventional time trend index.
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Published Versus Sample Statistics From The ASM: Implications For The LRD
January 1991
Working Paper Number:
CES-91-01
In principle, the Longitudinal Research Database ( LRD ) which links the establishments in the Annual Survey of Manufactures (ASM) is ideal for examining the dynamics of firm and aggregate behavior. However, the published ASM aggregates are not simply the appropriately weighted sums of establishment data in the LRD . Instead, the published data equal the sum of LRD-based sample estimates and nonsample estimates. The latter reflect adjustments related to sampling error and the imputation of small-establishment data. Differences between the LRD and the ASM raise questions for users of both data sets. For ASM users, time-series variation in the difference indicates potential problems in consistently and reliably estimating the nonsample portion of the ASM. For LRD users, potential sample selection problems arise due to the systematic exclusion of data from small establishments. Microeconomic studies based on the LRD can yield misleading inferences to the extent that small establishments behave differently. Similarly, new economic aggregates constructed from the LRD can yield incorrect estimates of levels and growth rates. This paper documents cross-sectional and time-series differences between ASM and LRD estimates of levels and growth rates of total employment, and compares them with employment estimates provided by Bureau of Labor Statistics and County Business Patterns data. In addition, this paper explores potential adjustments to economic aggregates constructed from the LRD. In particular, the paper reports the results of adjusting LRD-based estimates of gross job creation and destruction to be consistent with net job changes implied by the published ASM figures.
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Returns to Scale in Small and Large U.S. Manufacturing Establishments
September 1990
Working Paper Number:
CES-90-11
The objective of this study is to assess the possibility of differences in the production technologies between large and small establishments in five selected 4-digit SIC manufacturing industries. We particularly focus on estimating returns to scale and then make interferences regarding the efficiency of small businesses relative to large businesses. Using cross-section data for two census years, 1977 and 1982, we estimate a transcendental logarithmic (translog) production model that provides direct estimates of economies of scale parameters for both small and large establishments. Our primary findings are: (i) there are significant differences in the production technologies between small and large establishments; and (ii) based on the scale parameter estimates, small establishments appear to be as efficient as large establishments under normal economic conditions, suggesting that large size is not a necessary condition for efficient production. However, small establishments seem to be unable to maintain constant returns to scale production during economic recession such as that in 1982.
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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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Gross Job Creation, Gross Job Destruction and Employment Reallocation
June 1990
Working Paper Number:
CES-90-04
This paper measures the heterogeneity of establishment-level employment changes in the U.S. manufacturing sector over the 1972 to 1986 period. Our empirical work exploits a rich data set with approximately 860,000 annual observations on 160,000 manufacturing establishments to calculate rates of gross job creation, gross job destruction, and their sum, gross job reallocation. The central empirical findings are as follows: (1) Based on March-to-March establishment-level employment changes, gross job reallocation averages more than 20% of employment per year. (2) For the manufacturing sector as a whole, March-to-March gross job reallocation varies over time from 17% to 23% of employment per year. (3) Time variation in gross job reallocation is countercyclic-gross job reallocation rates covary negatively with own-sector and manufacturing net employment growth rates. (4) Virtually all of the time variation in gross job reallocation is accounted for by idiosyncratic effects on the establishment growth rate density. Changes in the shape and location of the growth rate density due to aggregate-year effects and sector-year effects cannot explain the observed variation in gross job reallocation. (5) The part of gross job reallocation attributable to idiosyncratic effects fluctuates countercyclically. Combining (3) ' (5), we conclude that the intensity of shifts in the pattern of employment opportunities across establishments exhibits significant countercyclic variation. In preparing the data for this study, we have greatly benefited from the assistance of Robert Bechtold, Timothy Dunne, Cyr Linonis, James Monahan, Al Nucci and other Census Bureau employees at the Center for Economic Studies. We have also benefited from helpful comments by Katherine Abraham, Martin Baily, Fischer Black, Timothy Dunne, David Lilien, Robert McGuckin, Kevin M. Murphy, Larrty Katz, John Wallis, workshop participants at the University of Maryland, the Resource Mobility Session of the Econometric society (Winter 1988 meetings), an NBER conference on Alternative Explanations of Employment Fluctuations, and the NBER's Economic Fluctuations Program Meeting (Summer 1989). Scott Schuh provided excellent research assistance. We gratefully acknowledge the financial assistance of the National Science Foundation (SES-8721031 and SES-8720931), the Hoover Institution, and the Office of Graduate Studies and Research at the University of Maryland. Davis also thanks the National Science Foundation for it's support through a grant to the National Fellows Program at the Hoover Institution. Most of the research for this paper was conducted while Davis was a National Fellow at the Hoover Institution.
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