This paper investigates the cross-sectional and time-series implications of capital imperfections for inventory investment in retail trade. In particular, it focuses on the relevance of firms' balance sheet positions in obtaining access to external sources of finance. The paper utilizes an entirely new source of firm-level data at a quarterly frequency; the micro data underlying the published Quarterly Financial Reports (QFR). Under the maintained hypothesis, firms with 'weak' balance sheet positions face a higher-and quite possibly prohibitive-premium on external finance than do firms with 'strong' balance sheet positions. Consequently, inventory investment decisions of firms with 'weak' balance sheet positions are in large part determined by the availability of internally generated funds-that is, profits or cash flow. A panel data modification of an error-correction model that incorporates internal finance variables and forward-looking expectations of the stochastic process of sales is not rejected by the data. Both the cross-sectional and time-series results are consistent with the existence of capital market imperfections; namely, (1) internal finance is a highly significant-statistically and economically-predictor of inventory investment of firms with 'weak' balance sheet positions; and (2) the predictive power of internal finance for inventory investment of firms with 'weak' balance sheet positions is highly asymmetric over the course of a business cycle, increasing considerably in recession relative to expansionary times. The quantitative significance of financial factors suggest that a large portion of the observed volatility aggregate retail inventory investment over a business cycle is potentially due to fluctuations in internal finance.
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The Industry Life-Cycle of the Size Distribution of Firms
July 2005
Working Paper Number:
CES-05-10
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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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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Factoryless Goods Producers in the US
September 2013
Working Paper Number:
CES-13-46
This paper documents the extent and characteristics of plants and firms in the US that are outside the manufacturing sector according to official government statistics but nonetheless are heavily involved in activities related to the production of manufactured goods. Using new data on establishment activities in the Census of Wholesale Trade conducted by the US Bureau of the Census in 2002 and 2007, this paper provides evidence on so-called 'factoryless goods producers' (FGPs) in the US economy. FGPs are formally in the wholesale sector but, unlike traditional wholesale establishments, FGPs design the goods they sell and coordinate the production activities. This paper documents the extent of FGPs in the wholesale sector and how they differ from traditional wholesalers in terms of their employment, wages, productivity and output. Reclassifying FGP establishments to the manufacturing sector using our definition would have shifted at least 595,000 workers to as many as 1,311,000 workers from wholesale to manufacturing sectors in 2002 and at least 431,000 workers to as many as 1,934,000 workers in 2007.
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Asymmetric Learning Spillovers
April 1993
Working Paper Number:
CES-93-07
In this paper, I employ a linear-quadratic model of an industry characterized by learning by doing to examine the implications of asymmetric learning spillovers. Importantly, I show that distribution of spillover benefits can influence market structure in ways that can not be seen in models where spillovers are symmetric. If spillovers are asymmetric, a tradeoff between improved industry performance and increased market concentration can arise which does not occur when they are symmetric. This tradeoff leads to a policy dilemma; whether to promote static or dynamic efficiency in markets where learning is important.
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What Causes Industry Agglomeration? Evidence from Coagglomeration Patterns
April 2007
Working Paper Number:
CES-07-13
Many industries are geographically concentrated. Many mechanisms that could account for such agglomeration have been proposed. We note that these theories make different predictions about which pairs of industries should be coagglomerated. We discuss the measurement of coagglomeration and use data from the Census Bureau's Longitudinal Research Database from 1972 to 1997 to compute pairwise coagglomeration measurements for U.S. manufacturing industries. Industry attributes are used to construct measures of the relevance of each of Marshall's three theories of industry agglomeration to each industry pair: (1) agglomeration saves transport costs by proximity to input suppliers or final consumers, (2) agglomeration allows for labor market pooling, and (3) agglomeration facilitates intellectual spillovers. We assess the importance of the theories via regressions of coagglomeration indices on these measures. Data on characteristics of corresponding industries in the United Kingdom are used as instruments. We find evidence to support each mechanism. Our results suggest that input-output dependencies are the most important factor, followed by labor pooling.
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Learning By Doing And Competition In The Early Rayon Industry
February 1993
Working Paper Number:
CES-93-04
In this paper, I derive a structural econometric model of learning by doing from a dynamic oligopoly game. Unlike previous empirical models, this model is capable of testing hypotheses concerning both the technological nature and behavioral implications of learning. I estimate the model with firm level data from the early U.S. rayon industry. The empirical results show that there were considerable differences across firms in both proprietary and spillover learning. The results also indicate that two of the three firms took their rival's reactions into account when choosing their strategies.
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Clusters, Convergence, and Economic Performance
October 2010
Working Paper Number:
CES-10-34
This paper evaluates the role of regional cluster composition in the economic performance of industries, clusters and regions. On the one hand, diminishing returns to specialization in a location can result in a convergence effect: the growth rate of an industry within a region may be declining in the level of activity of that industry. At the same time, positive spillovers across complementary economic activities provide an impetus for agglomeration: the growth rate of an industry within a region may be increasing in the size and strength (i.e., relative presence) of related economic sectors. Building on Porter (1998, 2003), we develop a systematic empirical framework to identify the role of regional clusters ' groups of closely related and complementary industries operating within a particular region in regional economic performance. We exploit newly available data from the US Cluster Mapping Project to disentangle the impact of convergence at the region-industry level from agglomeration within clusters. We find that, after controlling for the impact of convergence at the narrowest unit of analysis, there is significant evidence for cluster-driven agglomeration. Industries participating in a strong cluster register higher employment growth as well as higher growth of wages, number of establishments, and patenting. Industry and cluster level growth also increases with the strength of related clusters in the region and with the strength of similar clusters in adjacent regions. Importantly, we find evidence that new industries emerge where there is a strong cluster environment. Our analysis also suggests that the presence of strong clusters in a region enhances growth opportunities in other industries and clusters. Overall, these findings highlight the important role of cluster-based agglomeration in regional economic performance.
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An Equilibrium Model of Sorting in an Urban Housing Market: A Study of the Causes and Consequences of Residential Segregation
January 2003
Working Paper Number:
CES-03-01
This paper presents a new equilibrium framework for analyzing economic and policy questions related to the sorting of households within a large metropolitan area. At its heart is a model describing the residential location choices of households that makes explicit the way that individual decisions aggregate to form a housing market equilibrium. The model incorporates choice-specific unobservables, and in the presence of these, a general strategy is provided for identifying household preferences over choice characteristics, including those that depend on household sorting such as neighborhood racial composition. We estimate the model using restricted access Census data that characterize the precise residential and employment locations of a quarter of a million households in the San Francisco Bay Area, yielding accurate measures of references for a wide variety of housing and neighborhood attributes across different types of household. The main economic analysis of the paper uses these estimates in combination with the equilibrium model to explore the causes and consequences of racial segregation in the housing market. Our results indicate that, given the preference structure of households in the Bay Area, the elimination of racial differences in income and wealth would significantly increase the residential segregation of each major racial group. Given the relatively small fractions of Asian, Black, and Hispanic households in the Bay Area (each ~10%), the elimination of racial differences in income/wealth (or, education or employment geography) spreads households in these racial groups much more evenly across the income distribution, allowing more racial sorting to occur at all points in the distribution ' e.g., leading to the formation of wealthy, segregated Black and Hispanic neighborhoods. The partial equilibrium predictions of the model, which do not account for the fact that neighborhood sociodemographic compositions and prices adjust as part of moving to a new equilibrium, lead to the opposite conclusion, emphasizing the value of the general equilibrium approach developed in the paper. Our analysis also provides evidence sorting on the basis of race itself (whether driven by preferences directly or discrimination) leads to large reductions in the consumption of public safety and school quality by all Black and Hispanic households, and large reductions in the housing consumption of upper-income Black and Hispanic households.
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Propagation and Amplification of Local Productivity Spillovers
August 2022
Working Paper Number:
CES-22-32
This paper shows that local productivity spillovers can propagate throughout the economy through the plant-level networks of multi-region firms. Using confidential Census plant-level data, we find that large manufacturing plant openings not only raise the productivity of local plants but also of distant plants hundreds of miles away, which belong to multi-region firms that are exposed to the local productivity spillover through one of their plants. To quantify the significance of plant-level networks for the propagation and amplification of local productivity shocks, we develop and estimate a quantitative spatial model in which plants of multi-region firms are linked through shared knowledge. Counterfactual exercises show that while knowledge sharing through plant-level networks amplifies the aggregate effects of local productivity shocks, it can widen economic disparities between workers and regions in the economy.
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