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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Longitudinal Economic Data At The Census Bureau: A New Database Yields Fresh Insight On Some Old Issues
January 1990
Working Paper Number:
CES-90-01
This paper has two goals. First, it illustrates the importance of panel data with examples taken from research in progress using the U.S. Census Bureau's Longitudinal Research Database ( LRD ). Although the LRD is not the result of a "true" longitudinal survey, it provides both balanced and unbalanced panel data sets for establishments, firms, and lines of business. The second goal is to integrate the results of recent research with the LRD and to draw conclusions about the importance of longitudinal microdata for econometric research and time series analysis. The advantages of panel data arise from both the micro and time series aspects of the observations. This also leads us to consider why panel data are necessary to understand and interpret the time series behavior of aggregate statistics produced in cross-section establishment surveys and censuses. We find that typical homogeneity assumptions are likely to be inappropriate in a wide variety of applications. In particular, the industry in which an establishment is located, the ownership of the establishment, and the existence of the establishment (births and deaths) are endogenous variables that cannot simply be taken as time invariant fixed effects in econometric modeling.
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Industry Learning Environments and the Heterogeneity of Firm Performance
December 2006
Working Paper Number:
CES-06-29
This paper characterizes inter-industry heterogeneity in rates of learning-by-doing and examines how industry learning rates are connected with firm performance. Using data from the Census Bureau and Compustat, we measure the industry learning rate as the coefficient on cumulative output in a production function. We find that learning rates vary considerably among industries and are higher in industries with greater R&D, advertising, and capital intensity. More importantly, we find that higher rates of learning are associated with wider dispersion of Tobin's q and profitability among firms in the industry. Together, these findings suggest that learning intensity represents an important characteristic of the industry environment.
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The Impact of Vintage and Survival on Productivity: Evidence from Cohorts of U.S. Manufacturing Plants
May 2000
Working Paper Number:
CES-00-06
This paper examines the evolution of productivity in U.S. manufacturing plants from 1963 to 1992. We define a 'vintage effect' as the change in productivity of recent cohorts of new plants relative to earlier cohorts of new plants, and a 'survival effect' as the change in productivity of a particular cohort of surviving plants as it ages. The data show that both factors contribute to industry productivity growth, but play offsetting roles in determining a cohort's relative position in the productivity distribution. Recent cohorts enter with significantly higher productivity than earlier entrants did, while surviving cohorts show significant increases in productivity as they age. These two effects roughly offset each other, however, so there is a rough convergence in productivity across cohorts in 1992 and 1987. (JEL Code: D24, L6)
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An Option-Value Approach to Technology in U.S. Maufacturing: Evidence from Plant-Level Data
July 2000
Working Paper Number:
CES-00-12
Numerous empirical studies have examined the role of firm and industry heterogeneity in the decision to adopt new technologies using a Net Present Value framework. However, as suggested by the recently developed option-value theory, these studies may have overlooked the role of investment reversibility and uncertainty as important determinants of technology adoption. Using the option-value investment model as my underlying theoretical framework, I examine how these two factors affect the decision to adopt three advanced manufacturing technologies. My results support the option-value model's prediction that plants operating in industries facing higher investment reversibility and lower degrees of demand and technological uncertainty are more likely to adopt advanced manufacturing technologies.
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USING LINKED CENSUS R&D-LRD DATA TO ANALYZE THE EFFECT OF R&D INVESTMENT ON TOTAL FACTOR PRODUCTIVITY GROWTH
January 1989
Working Paper Number:
CES-89-02
Previous studies have demonstrated that productivity growth is positively correlated with the intensity of R&D investment. However, existing studies of this relationship at the micro (firm or line of business) level have been subject to some important limitations. The most serious of these has been an inability to adequately control for the diversified activities of corporations. This study makes use of linked Census R&D - LRD data, which provides comprehensive information on each firms' operations at the 4-digit SIC level. A marked improvement in explaining the association between R&D and TFP occurs when we make appropriate use of the data by firm by industry. Significant relationships between the intensities of investment in total, basic, and company-funded R&D, and TFP growth are confirmed.
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Plant Exit and U.S. Imports from Low-Wage Countries
January 2016
Working Paper Number:
CES-16-02
Over the past twenty years, imports to the U.S. from low-wage countries have increased dramatically. In this paper we examine how low-wage country import competition in the U.S. influences the probability of manufacturing establishment closure. Confidential data from the U.S. Bureau of the Census are used to track all manufacturing establishments between 1992 and 2007. These data are linked to measures of import competition built from individual trade transactions. Controlling for a variety of plant and firm covariates, we show that low-wage import competition has played a significant role in manufacturing plant exit. Analysis employs fixed effects panel models running across three periods: the first plant-level panels examining trade and exit for the U.S. economy. Our results appear robust to concerns regarding endogeneity.
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Multiple Classification Systems For Economic Data: Can A Thousand Flowers Bloom? And Should They?
December 1991
Working Paper Number:
CES-91-08
The principle that the statistical system should provide flexibility-- possibilities for generating multiple groupings of data to satisfy multiple objectives--if it is to satisfy users is universally accepted. Yet in practice, this goal has not been achieved. This paper discusses the feasibility of providing flexibility in the statistical system to accommodate multiple uses of the industrial data now primarily examined within the Standard Industrial Classification (SIC) system. In one sense, the question of feasibility is almost trivial. With today's computer technology, vast amounts of data can be manipulated and stored at very low cost. Reconfigurations of the basic data are very inexpensive compared to the cost of collecting the data. Flexibility in the statistical system implies more than the technical ability to regroup data. It requires that the basic data are sufficiently detailed to support user needs and are processed and maintained in a fashion that makes the use of a variety of aggregation rules possible. For this to happen, statistical agencies must recognize the need for high quality microdata and build this into their planning processes. Agencies need to view their missions from a multiple use perspective and move away from use of a primary reporting and collection vehicle. Although the categories used to report data must be flexible, practical considerations dictate that data collection proceed within a fixed classification system. It is simply too expensive for both respondents and statistical agencies to process survey responses in the absence of standardized forms, data entry programs, etc. I argue for a basic classification centered on commodities--products, services, raw materials and labor inputs--as the focus of data collection. The idea is to make the principle variables of interest--the commodities--the vehicle for the collection and processing of the data. For completeness, the basic classification should include labor usage through some form of occupational classification. In most economic surveys at the Census Bureau, the reporting unit and the classified unit have been the establishment. But there is no need for this to be so. The basic principle to be followed in data collection is that the data should be collected in the most efficient way--efficiency being defined jointly in terms of statistical agency collection costs and respondent burdens.
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The Importance of Establishment Data in Economic Research
August 1993
Working Paper Number:
CES-93-10
The importance and usefulness of establishment microdata for economic research and policy analysis is outlined and contrasted with traditional products of statistical agencies -- aggregate cross-section tabulations. It is argued that statistical agencies must begin to seriously rethink the way they view establishment data products.
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The Missing Link: Technology, Productivity, and Investment
October 1995
Working Paper Number:
CES-95-12
This paper examines the relationship between productivity, investment, and age for over 14,000 plants in the U.S. manufacturing sector in the 1972-1988 period. Productivity patterns vary significantly due to plant heterogeneity. Productivity first increases and then decreases with respect to plant age, and size and industry are systematically correlated with productivity and productivity growth. However, there is virtually no observable relationship between investment and productivity or productivity growth. Overall, the results indicate that plant heterogeneity and fixed effects are more important determinants of observable productivity patterns than sunk costs or capital reallocation. Key Words: productivity, investment, technical change
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The Impact of Ownership Changes: A View from Labor Markets
March 2000
Working Paper Number:
CES-00-02
Previous studies of mergers and acquisition often focus on firms' performance such as profits, productivity and market shares. However, from a broad competition policy perspective, the impacts on labor and wages are crucial. In this study, we use plant-level data for the entire U.S. manufacturing for the period 1977-87 to examine the effects of ownership changes on employment, wages and plant closing. Our principal findings are that ownership changes are not a primary vehicle for cuts in employment and wages, or closing plants. Instead, the typical ownership change appear to increase jobs and their quality as measured by wages. However, some ownership changes, particularly those in bigger plants, are associated with job loss, and the typical worker fares much worse than the typical plant. Finally, we find that plants that changed owners have a higher probability of survival than those that did not. Overall, the impact of ownership changes on labor markets are positive.
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