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 Structure of Firm R&D and the Factor Intensity of Production
October 1997
Working Paper Number:
CES-97-15
This paper studies the influence of the structure of firm R&D, industry R&D spillovers, and plant level physical capital on the factor intensity of production. By the structure of firm R&D we mean its distribution across states and products. By factor intensity we mean the cost shares of variable factors, which in this paper are blue collar labor, white collar labor, and materials. We characterize the effect of the structure of firm R&D on factor intensity using a Translog cost function with quasi-fixed factors. This cost function gives rise to a system of variable cost shares that depends on factor prices, firm and industry R&D, and physical capital.
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Science, R&D, And Invention Potential Recharge: U.S. Evidence
January 1993
Working Paper Number:
CES-93-02
The influence of academic science on industrial R&D seems to have increased in recent years compared with the pre-World War II period. This paper outlines an approach to tracing this influence using a panel of 14 R&D performing industries from 1961-1986. The results indicate an elasticity between real R&D and indicators of stocks of academic science of about 0.6. This elasticity is significant controlling for industry effects. However, the elasticity declines from its level during the 1961-1973 subperiod, when it was 2.2, to 0.5 during the 1974-1986 subperiod. Reasons for the decline include exogenous and endogenous exhaustion of invention potential, and declining incentives to do R&D stemming from a weakening of intellectual property rights. The growth of R&D since the mid-1980s suggests a restoration of R&D incentives in still more recent times.
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Learning by Doing and Plant Characteristics
August 1996
Working Paper Number:
CES-96-05
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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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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Intra-Firm Spillovers? The Stock and Flow Effects of Collocation
January 2015
Working Paper Number:
CES-15-01
We examine the impact of collocation on local within-firm performance, or intra-firm spillovers, by decomposing spillovers into one-time stock and recurring flow effects. Stock effects include one-time learning effects. Flow effects include ongoing resource sharing as well as cannibalization. Using data on the population of U.S. hotels and restaurants from 1977-2007, we exploit changes in the number of collocated establishments owned by the same firm to estimate the relative importance of stock and flow benefits. We find that collocation improves the productivity of new and existing establishments by 1-2%, even when correcting for endogenous sorting into collocation. The results, in conjunction with our field work, suggest that collocation generally facilitates the transfer of knowledge within the firm, but that flow effects of collocation are more sensitive to the broader economic environment.
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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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Marshall's Scale Economies
December 2001
Working Paper Number:
CES-01-17
In this paper, using panel data, I estimate plant level production functions that include variables that allow for two types of scale externalities which plants experie nce in their local industrial environments. First are externalities from other plants in the same industry locally, usually called localization economies or, in a dynamic context, Marshall, Arrow, Romer [MAR] economies. Second are externalities from the scale or diversity of local economic activity outside the own industry involving some type of cross- fertilization, usually called urbanization economies or, in a dynamic context, Jacobs economies. Estimating production functions for plants in high tech industries and in capital goods, or machinery industries, I find that local own industry scale externalities, as measured specifically by the count of other own industry plants locally, have strong productivity effects in high tech but not machinery industries. I find evidence that single plant firms both benefit more from and generate greater external benefits than corporate plants. On timing, I find evidence that high tech single plant firms benefit from the scale of past own industry activity, as well as current activity. I find no evidence of urbanization economies from the diversity of local economic activity outside the own industry and limited evidence of urbanization economies from the overall scale of local economic activity.
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Pollution Abatement Costs, Regulation And Plant-Level Productivity
December 1994
Working Paper Number:
CES-94-14
We analyze the connection between productivity, pollution abatement expenditures, and other measures of environmental regulation for plants in three industries (paper, oil, and steel). We examine data from 1979 to 1990, considering both total factor productivity levels and growth rates. Plants with higher abatement cost levels have significantly lower productivity levels. The magnitude of the impact is somewhat larger than expected: $1 greater abatement costs appears to be associated with the equivalent of $1.74 in lower productivity for paper mills, $1.35 for oil refineries, and $3.28 for steel mills. However, these results apply only to variation across plants in productivity levels. Estimates looking at productivity variation within plants over time, or estimates using productivity growth rates show a smaller (and insignificant) relationship between abatement costs and productivity. Other measures of environmental regulation faced by the plants (compliance status, enforcement activity, and emissions) are not significantly related to productivity.
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A Guide To R&D Data At The Center For Economic Studies U.S. Bureau Of THe Census
August 1994
Working Paper Number:
CES-94-09
The National Science Foundation R&D Survey is an annual survey of firms' research and development expenditures. The survey covers 3000 firms reporting positive R&D. This paper provides a description of the R&D data available at the Center for Economic Studies (CES). The most basic data series available contains the original survey R&D data. It covers the years 1972-92. The remaining two series, although derived from the original files, specialize in particular items. The Mandatory Series contains required survey items for the years 1973-88. Items reported at firms' discretion are in the Voluntary Series, which covers the years 1974-89. Both of the derived series incorporate flags that track quality of the data. Both also include corrections to the data based on original hard copy survey evidence stored at CES. In addition to describing each dataset, we offer suggestions to researchers wishing to use the R&D data in exploring various economic issues. We report selected response rates, discuss the survey design, and provide hints on how to use the data.
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When Do Firms Shift Production Across States to Avoid Environmental Regulation?
December 2001
Working Paper Number:
CES-01-18
This paper examines whether a firm's allocation of production across its plants responds to the environmental regulation faced by those plants, as measured by differences in stringency across states. We also test whether sensitivity to regulation differs based on differences across firms in compliance behavior and/or differences across states in industry importance and concentration. We use Census data for the paper and oil industries to measure the share of each state in each firm's production during the 1967-1992 period. We use several measures of state environmental stringency and test for interactions between regulatory stringency and three factors: the firm's overall compliance rate, a Herfindahl index of industry concentration in the state, and the industry's share in the state economy. We find significant results for the paper industry: firms allocate smaller production shares to states with stricter regulations. This impact is concentrated among firms with low compliance rates, suggesting that low compliance rates are due to high compliance costs, not low compliance benefits. The interactions between stringency and industry characteristics are less often significant, but suggest that the paper industry is more affected by regulation where it is larger or more concentrated. Our results are weaker for the oil industry, reflecting either less opportunity to shift production across states or a greater impact of environmental regulation on paper mills.
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