This paper analyzes the evolution of the distributions of output and employment across firms in U.S. manufacturing industries from 1963 until 1997. The evolutions of the employment and output distributions differ, but display strong inter-industry regularities, including that the nature of the evolution depends whether the industry is experiencing growth, shakeout, maturity, or decline. The observed patterns have implications for theories of industry dynamics and evolution.
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Information and Industry Dynamics
August 2010
Working Paper Number:
CES-10-16R
This paper develops a dynamic industry model in which firms compete to acquire customers over time by disseminating information about themselves under the presence of random shocks to their efficiency. The properties of the model's stationary equilibrium are related to empirical regularities on firm and industry dynamics. As an application of the model, the effects of a decline in the cost of information dissemination on firm and industry dynamics are explored.
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Wage Dynamics along the Life-Cycle of Manufacturing Plants
August 2011
Working Paper Number:
CES-11-24R
This paper explores the evolution of average wage paid to employees along the life-cycle of a manufacturing plant in U.S. Average wage starts out low for a new plant and increases along with labor productivity, as the plant survives and ages. As a plant experiences productivity decline and approaches exit, average wage falls, but more slowly than it rises in the case of surviving new plants. Moreover, average wage declines slower than productivity does in failing plants, while it rises relatively faster as productivity increases in surviving new plants. These empirical regularities are studied in a dynamic model of labor quality and quantity choice by plants, where labor quality is reflected in wages. The model's parameters are estimated to assess the costs a plant incurs as it alters its labor quality and quantity in response to changes in its productivity over its life-cycle.
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An Anatomy of U.S. Firms Seeking Trademark Registration
April 2018
Working Paper Number:
CES-18-22
This paper reports on the construction of a new dataset that combines data on trademark applications and registrations from the U.S. Patent and Trademark Office with data on firms from the U.S. Census Bureau. The resulting dataset allows tracking of various activity related to trademark use and protection over the life-cycle of firms, such as the first application for a trademark registration, the first use of a trademark, and the renewal, assignment, and cancellation of trademark registrations. Facts about firm-level trademark activity are documented, including the incidence and timing of trademark registration filings over the firm life-cycle and the connection between firm characteristics and trademark applications. We also explore the relation of trademark application filing to firm employment and revenue growth, and to firm innovative activity as measured by R&D and patents.
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Product Choice and Product Switching
October 2005
Working Paper Number:
CES-05-22
This paper develops a model of endogenous product selection within industries by firms. The model is motivated by new evidence we present on the prevalence and importance of product changing activity by U.S. manufacturers. Three-fifths of continuing firms alter their product mix within an industry every five years, and added and dropped products account for a substantial portion of firm output. In the model, firms make decisions about both industry entry and product choice. Product choice is shaped by the interaction of heterogeneous firm characteristics and diverse product attributes. Changes in market conditions within an industry result in simultaneous adjustment along a number of margins, including both entry/exit and product choice.
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The Industry Life Cycle and Acquisitions and Investment: Does Firm Organization Matter?
October 2005
Working Paper Number:
CES-05-29
We examine the effect of financial dependence on the acquisition and investment of single segment and conglomerate firms for different long-run changes in industry conditions. Conglomerates and single-segment firms differ in the investments they make. The main differences are in the investment in acquisitions rather than in the level of capital expenditure. Financial dependence, a deficit in a segment's internal financing, decreases the likelihood of acquisitions and opening new plants, especially for single-segment firms. These effects are mitigated for conglomerates in growth industries and also for firms that are publicly traded. In declining industries, plants of segments that are financially dependent are less likely to be closed by conglomerate firms. These findings persist after controlling for firm size and segment productivity. We also find that plants acquired by conglomerate firms in growth industries increase in productivity post-acquisition. The results are consistent with the comparative advantages of different firm organizations differing across long-run industry conditions.
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Heavy Tailed, but not Zipf: Firm and Establishment Size in the U.S.
July 2021
Working Paper Number:
CES-21-15
Heavy tails play an important role in modern macroeconomics and international economics.
Previous work often assumes a Pareto distribution for firm size, typically with a shape parameter approaching Zipf's law. This convenient approximation has dramatic consequences for the importance of large firms in the economy. But we show that a lognormal distribution, or better yet, a convolution of a lognormal and a non-Zipf Pareto distribution, provides a better description of the U.S. economy, using confidential Census Bureau data. These findings hold even far in the upper tail and suggest heterogeneous firm models should more systematically explore deviations from Zipf's law.
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Labor Market Segmentation and the Distribution of Income: New
Evidence from Internal Census Bureau Data
August 2023
Working Paper Number:
CES-23-41
In this paper, we present new findings that validate earlier literature on the apparent segmentation of the US earnings distribution. Previous contributions posited that the observed distribution of earnings combined two or three distinct signals and was thus appropriately modeled as a finite mixture of distributions. Furthermore, each component in the mixture appeared to have distinct distributional features hinting at qualitatively distinct generating mechanisms behind each component, providing strong evidence for some form of labor market segmentation. This paper presents new findings that support these earlier conclusions using internal CPS ASEC data spanning a much longer study period from 1974 to 2016. The restricted-access internal data is not subject to the same level of top-coding as the public-use data that earlier contributions to the literature were based on. The evolution of the mixture components provides new insights about changes in the earnings distribution including earnings inequality. In addition, we correlate component membership with worker type to provide a tacit link to various theoretical explanations for labor market segmentation, while solving the problem of assigning observations to labor market segments a priori.
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Micro Data and the Macro Elasticity of Substitution
March 2012
Working Paper Number:
CES-12-05
We estimate the aggregate elasticity of substitution between capital and labor in the US manufacturing sector. We show that the aggregate elasticity of substitution can be expressed as a simple function of plant level structural parameters and sufficient statistics of the distribution of plant input cost shares. We then use plant level data from the Census of Manufactures to construct a local elasticity of substitution at various levels of aggregation. Our approach does not assume the existence of a stable aggregate production function, as we build up our estimate from the cross section of plants at a point in time. Accounting for substitution within and across plants, we find that the aggregate elasticity is substantially below unity at approximately 0.7. Lastly we assess the sources of the bias of aggregate technical change from 1987 to 1997. We find that the labor augmenting character of aggregate technical change is due almost exclusively to labor augmenting productivity growth at the plant level rather than relative growth in capital intensive plants.
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The Effects of Industry Classification Changes on US Employment Composition
June 2018
Working Paper Number:
CES-18-28
This paper documents the extent to which compositional changes in US employment from 1976 to 2009 are due to changes in the industry classification scheme used to categorize economic
activity. In 1997, US statistical agencies began implementation of a change from the Standard Industrial Classification System (SIC) to the North American Industrial Classification System (NAICS). NAICS was designed to provide a consistent classification scheme that consolidated declining or obsolete industries and added categories for new industries. Under NAICS, many activities previously classified as Manufacturing, Wholesale Trade, or Retail Trade were re-classified into the Services sector. This re-classification resulted in a significant shift of measured activities across sectors without any change in underlying economic activity. Using a newly developed establishment-level database of employment activity that is consistently classified on a NAICS basis, this paper shows that the change from SIC to NAICS increased the share of Services employment by approximately 36 percent. 7.6 percent of US manufacturing employment, equal to approximately 1.4 million jobs, was reclassified to services. Retail trade and wholesale trade also experienced a significant reclassification of activities in the transition.
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Estimating market power Evidence from the US Brewing Industry
January 2017
Working Paper Number:
CES-17-06R
While inferring markups from demand data is common practice, estimation relies on difficult-to-test assumptions, including a specific model of how firms compete. Alternatively, markups can be inferred from production data, again relying on a set of difficult-to-test assumptions, but a wholly different set, including the assumption that firms minimize costs using a variable input. Relying on data from the US brewing industry, we directly compare markup estimates from the two approaches. After implementing each approach for a broad set of assumptions and specifications, we find that both approaches provide similar and plausible markup estimates in most cases. The results illustrate how using the two strategies together can allow researchers to evaluate structural models and identify problematic assumptions.
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