Learning by doing, especially spillover learning, has received much attention lately in models of industry evolution and economic growth. The predictions of these models depend on the distribution of learning abilities and knowledge flows across firms and countries. However, the empirical literature provides little guidance on these issues. In this paper, I use plant level data on a sample of entrants in SIC 38, Instruments, to examine the characteristics associated with both proprietary and spillover learning by doing. The plant level data permit tests for the relative importance of within and between firm spillovers. I include both formal knowledge, obtained through R&D expenditures, and informal knowledge, obtained through learning by doing, in a production function framework. I allow the speed of learning to vary across plants according to characteristics such as R&D intensity, wages, and the skill mix. The results suggest that (a) Ainformal@ knowledge, accumulated through production experience at the plant, is a much more important source of productivity growth for these plants than is Aformal@ knowledge gained via research and development expenditures, (b) interfirm spillovers are stronger than intrafirm spillovers, (c) the slope of the own learning curve is positively related to worker quality, (d) the slope of the spillover learning curve is positively related to the skill mix at plants, (e) neither own nor spillover learning curve slopes are related to R&D intensities. These results imply that learning by doing may be, to some extent, an endogenous phenomenon at these plants. Thus, models of industry evolution that incorporate learning by doing may need to be revised. The results are also broadly consistent with the recent growth models.
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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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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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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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The Span of the Effect of R&D in the Firm and Industry
May 1994
Working Paper Number:
CES-94-07
Previous studies have found that the firm's own research and spillovers of research by related firms increase firm productivity. In contrast, in this paper we explore the impact of firm R&D on the productivity of its individual plants. We carry out this investigation of within firm R&D effects using a unique set of Census data. The data, which are from the chemicals industry, are a match of plant level productivity and other characteristics with firm level data on R&D of the parent company, cross-classified by location and applied product field. We explore three aspects of the span of effect of the firm's R&D: (i), the degree to which its R&D is "public" across plants; (ii), the extent of its localization in geographic space, and (iii), the breadth of its relevance outside the applied product area in which it is classified. We find that (i), firm R&D acts more like a private input which is strongly amortized by the number of plants in the firm; (ii), firm R&D is geographically localized, and exerts greater influence on productivity when it is conducted nearer to the plant; and (iii), firm R&D in a given applied product area is of limited relevance to plants producing outside that product area. Moreover, we find that while geographic localization remains significant, it diminishes over time. This trend is consistent with the effect of improved telecommunications on increased information flows within organizations. Finally, we consider spillovers of R&D from the rest of industry, finding that the marginal product of industry R&D on plant productivity, though positive and significant, is far smaller than the marginal product of parent firm's R&D.
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The Demand for Human Capital: A Microeconomic Approach
December 2001
Working Paper Number:
CES-01-16
We propose a model for explaining the demand for human capital based on a CES production function with human capital as an explicit argument in the function. The resulting factor demand model is tested with data on roughly 6,000 plants from the Census Bureau's Longitudinal Research Database. The results show strong complementarity between physical and human capital. Moreover, the complementarity is greater in high than in low technology industries. The results also show that physical capital of more recent vintage is associated with a higher demand for human capital. While the age of a plant as a reflection of learning-by-doing is positively related to the accumulation of human capital, this relation is more pronounced in low technology industries.
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Industrial Spillovers In Developing Countries: Plant-Level Evidence From Chile, Mexico And Morocco
January 1998
Working Paper Number:
CES-98-02
Recent trade and growth models have underscored the potential importance of external economies of scale. However, many of the most frequently modeled externalities have either not been measured or have been estimated with data too aggregate to be informative. In this paper, plant-level longitudinal data from Chile, Mexico and Morocco allow me to provide some of the first micro evidence on several types of external economies from plant-level production functions. The results indicate that in many industries own-industry output contributes positively to plant-level productivity. However, the effects of geographic concentration are mixed. Cross-country concentration, as measured by a geographic GINI index, often decreases productivity but within-province, same industry activity enhances it.
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Product Quality and Firm Heterogeneity in International Trade
March 2013
Working Paper Number:
CES-13-08
I develop and implement a methodology for obtaining plant-level estimates of product quality from revenue and physical output data. Intuitively, firms that sell large quantities of output conditional on price are classified as high quality producers. I use this method to decompose cross-plant variation in price and export status into a quality and an efficiency margin. The empirical results show that prices are increasing in quality and decreasing in efficiency. However, selection into exporting is driven mainly by quality. The finding that changes in quality and efficiency have different impact on the firm's export decision is shown to be inconsistent with the traditional iceberg trade cost formulation and points to the importance of per unit transport costs.
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ARE FIXED EFFECTS FIXED? Persistence in Plant Level Productivity
May 1996
Working Paper Number:
CES-96-03
Estimates of production functions suffer from an omitted variable problem; plant quality is an omitted variable that is likely to be correlated with variable inputs. One approach is to capture differences in plant qualities through plant specific intercepts, i.e., to estimate a fixed effects model. For this technique to work, it is necessary that differences in plant quality are more or less fixed; if the "fixed effects" erode over time, such a procedure becomes problematic, especially when working with long panels. In this paper, a standard fixed effects model, extended to allow for serial correlation in the error term, is applied to a 16-year panel of textile plants. This parametric approach strongly accepts the hypothesis of fixed effects. They account for about one-third of the variation in productivity. A simple non-parametric approach, however, concludes that differences in plant qualities erode over time, that is plant qualities f-mix. Monte Carlo results demonstrate that this discrepancy comes from the parametric approach imposing an overly restrictive functional form on the data; if there were fixed effects of the magnitude measured, one would reject the hypothesis of f-mixing. For textiles, at least, the functional form of a fixed effects model appears to generate misleading conclusions. A more flexible functional form is estimated. The "fixed" effects actually have a half life of approximately 10 to 20 years, and they account for about one-half the variation in productivity.
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Measuring the Impact of the Manufacturing Extension Partnership
September 1996
Working Paper Number:
CES-96-08
In this paper, I measure the impact of the Manufacturing Extension Partnership (MEP) on productivity and sales growth at manufacturing plants. To do this, I match MEP client data to the Census Bureau's Longitudinal Research Database (LRD). The LRD contains data for all manufacturing establishments in the U.S. and provides a number of measures of plant performance and characteristics that are measured consistently across plants and time. This facilitates valid comparisons between both client and non-client plants and among clients served by different MEP centers. The National Institute of Standards and Technology (NIST) administers the MEP as part of their effort to improve the competitiveness of U.S. manufacturing. The program provides business and technical assistance to small and medium sized manufacturers much as agricultural extension does for farmers. The goal of the paper is to see if measures of plant performance (e.g., productivity and sales growth) are systematically related to participation in the MEP, while controlling for other factors that are known or thought to influence performance. Selection bias is often a problem in evaluation studies so I specify an econometric model that controls for selection. I estimate the model with data from 8 manufacturing extension centers in 2 states. The control group includes all plants from each state in the LRD. Preliminary results indicate that MEP participation is systematically related to productivity growth but not to sales growth.
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Industrial Spillovers in Developing Countries: Plant-level Evidence From Chile, Mexico, and Morocco
January 1998
Working Paper Number:
CES-98-01
This paper documents the procedure used to match firm-level data from the Quarterly Financial Reports (QFR) to plant-level (establishment) data from the Longitudinal Research Database (LRD). The resulting matched firms and their plants provide a link between a firm's financial structure and its manufacturing plants. The linked database provides a resource that researchers can use to examine the interaction of financial structure with firm decisions - including decisions such as employment, investment, mergers, and asset redeployment. Financial structure characteristics in the QFR include the composition and amount of debt claims.
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