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Papers Containing Keywords(s): 'industry growth'

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Viewing papers 11 through 15 of 15


  • Working Paper

    Firm Performance And Evolution Empirical Regularities In The U.S. Microdata

    October 1996

    Working Paper Number:

    CES-96-10

    This paper presents a view of firm performance, industry evolution, and economic growth that contrasts with the traditional representative firm model. The paper reviews recent empirical work, primarily studies using the Longitudinal Research Database (LRD), that explicitly focuses on individual business units. The major empirical regularity in the studies is that heterogeneity is pervasive -- it is found across and within all sectors and across all plant characteristics. Further, firms are not only different in the cross-section. They enter at different times, make different choices, and react differently to economic shocks. Thus, to understand economic performance and competition, one must move beyond representative firm models. Competition must be understood as a process in which some firms choose correctly and grow while other firms choose poorly and die; the growth of the successful firms at the expense of less successful rivals drives economic growth.
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  • Working Paper

    Academic Science, Industrial R&D, and the Growth of Inputs

    January 1993

    Working Paper Number:

    CES-93-01

    This paper is a theoretical and empirical investigation of the connection between science, R&D, and the growth of capital. Studies of high technology industries and recent labor studies agree in assigning a large role to science and technology in the growth of human and physical capital, although direct tests of these relationships have not been carried out. This paper builds on the search approach to R&D of Evenson and Kislev (1976) to unravel the complex interactions between science, R&D, and factor markets suggested by these studies. In our theory lagged science increases the returns to R&D, so that scientific advance later feeds into growth of R&D. In turn, product quality improvements and price declines lead to the growth of industry by shifting out new product demand, perhaps at the expense of traditional industries. All this tends to be in favor of the human and physical capital used intensively by high technology industries. This is the source of the factor bias which is implicit in the growth of capital per head. Our empirical work overwhelmingly supports the contention that growth of labor skills and physical capital are linked to science and R&D. It also supports the strong sequencing of events that is a crucial feature of our model, first from science to R&D, and later to output and factor markets.
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  • Working Paper

    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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  • Working Paper

    The Time-Series Pattern Of Firm Growth In Two Industries

    September 1992

    Authors: Kenneth R Troske

    Working Paper Number:

    CES-92-10

    Using a unique firm-level longitudinal data set that covers both the manufacturing and finance, insurance and real estate (FIRE) industries, this paper examines the time-series pattern of firm growth both immediately after entry and immediately prior to exit, and compares these patterns across the two industries. While previous research has examined the post-entry time-series behavior of firms, this research has focused exclusively on manufacturing firms. Examining the behavior of nonmanufacturing firms is important for two reasons. First, since the relative importance of the manufacturing industry has been declining recently, the behavior of manufacturing firms may be much different than the behavior of firms in an expanding industry, such as FIRE. Thus, comparing the growth of firms in a nonmanufacturing industry, with the growth of manufacturing firms provides more general knowledge about firm behavior. Second, since any good theory of firm dynamics should explain cross-industry differences in firm behavior, cross-industry differences in behavior must be documented before models of this type can be developed. The main finding of this paper are: (1) relative to FIRE firms, manufacturing firms experience more periods of above average growth immediately after entry; (2) relative to FIRE firms, manufacturing firms experience more periods of below average growth immediately prior to exit; and (3) relative to the growth of manufacturing firms, the growth of the typical FIRE firm is much more responsive to transitory shocks.
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  • Working Paper

    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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