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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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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An Applied General Equilibrium Model Of Moroccan Trade Liberalization Featuring External Economies
November 1997
Working Paper Number:
CES-97-16
Since the 1920's economists have wrestled with the effects of external economies on trade liberalization. In this paper I show that under extreme conditions, externalities can reverse the gains from trade found in perfectly competitive trade models. However, the externalities needed to generate this result, even under the worst possible conditions (all expanding industries are subject to negative externalities, all contracting industries have positive externalities) are orders of magnitude larger than those estimated in Krizan (1997). This suggests that the presence of external economies of scale does not provide a credible argument for protectionism. On the other hand, the CGE model showed that external effects can increase the welfare gains from trade liberalization, but the combined effect is still small compared to other policy options. This finding contrasts sharply with many models featuring internal returns to scale that are able to generate large welfare benefits from trade liberalization.
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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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A Flexible Test for Agglomeration Economies in Two U.S. Manufacturing Industries
August 2004
Working Paper Number:
CES-04-14
This paper uses the inverse input demand function framework of Kim (1992) to test for economies of industry and urban size in two U.S. manufacturing sectors of differing technology intensity: farm and garden machinery (SIC 352) and measuring and controlling devices (SIC 382). The inverse input demand framework permits the estimation of the production function jointly with a set of cost shares without the imposition of prior economic restrictions. Tests using plant-level data suggest the presence of population scale (urbanization) economies in the moderate- to low-technology farm and garden machinery sector and industry scale (localization) economies in the higher technology measuring and controlling devices sector. The efficiency and generality of the inverse input demand approach are particularly appropriate for micro-level studies of agglomeration economies where prior assumptions regarding homogeneity and homotheticity are less appropriate.
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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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Tracing the Sources of Local External Economies
August 2004
Working Paper Number:
CES-04-13
In a cross-sectional establishment-level analysis using confidential secondary data, I evaluate the influence of commonly postulated sources of localized external economies'supplier access, labor pools, and knowledge spillovers'on the productivity of two U.S. manufacturing sectors (farm and garden machinery and measuring and controlling devices). Measures incorporating different distance decay specifications provide evidence of the spatial extent of the various externality sources. Chinitz's (1961) hypothesis of the link between local industrial organization and agglomeration economies is also investigated. The results show evidence of labor pooling economies and university-linked knowledge spillovers in the case of the higher technology measuring and controlling devices sector, while access to input supplies and location near centers of applied innovation positively influence efficiency in the farm and garden machinery industry. Both sectors benefit from proximity to producer services, though primarily at a regional rather than highly localized scale.
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Agglomeration, Enterprise Size, and Productivity
August 2004
Working Paper Number:
CES-04-15
Much research on agglomeration economies, and particularly recent work that builds on Marshall's concept of the industrial district, postulates that benefits derived from proximity between businesses are strongest for small enterprises (Humphrey 1995, Sweeney and Feser 1998). With internal economies a function of the shape of the average cost curve and level of production, and external economies in shifts of that curve, a small firm enjoying external economies characteristic of industrial districts (or complexes or simply urbanized areas) may face the same average costs as the larger firm producing a higher volume of output (Oughton and Whittam 1997; Carlsson 1996; Humphrey 1995). Thus we observe the seeming paradox of large firms that enjoy internal economies of scale co-existing with smaller enterprises that should, by all accounts, be operating below minimum efficient scale. With the Birch-inspired debate on the relative job- and innovation-generating capacity of small and large firms abating (Ettlinger 1997), research on the small firm sector has shifted to an examination of the business strategies and sources of competitiveness of small enterprises (e.g., Pratten 1991, Nooteboom 1993). Technological external scale economies are a key feature of this research (Oughton and Whittam 1997).
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The Effects of Outsourcing on the Elasticity of Labor Demand
March 2006
Working Paper Number:
CES-06-07
In this paper, I focus on the effects of outsourcing on conditional labor demand elasticities. I begin by developing a model of outsourcing that formalizes this relationship. I show that the increased possibility of outsourcing (modeled as a decline in foreign intermediate input prices and an increase in the elasticity of substitution between foreign and domestic intermediate inputs) should increase labor demand elasticities. I also show that, a decline in the share of unskilled labor, due either to skill biased technological change or to movement of unskilled labor intensive stages abroad, can work in the opposite direction and reverse the increasing trend in elasticities. I then test the predictions of the model using the U.S. Census Bureau's Longitudinal Research Database (LRD). The instrumental variable approach used in the estimation of labor demand equations is the main methodological contribution of this paper. I directly address the endogeneity of wages in the labor demand equation by using average nonmanufacturing wages for each location and year as an instrumental variable for the plant-level wages in the manufacturing sector. The results support the main predictions of my model. U.S. manufacturing plants operating in industries that heavily outsource experienced an increase in their conditional labor demand elasticities during the 1980-1992 period. After 1992 elasticities began to decrease in outsourcing industries. This finding is consistent with the model which suggests that a decline in the share of unskilled labor in total cost could result in such a decrease in labor demand elasticities, precisely when the level of outsourcing is high. Estimates at the two-digit industry level provide further evidence in support of the hypothesis that heavily outsourcing industries experience greater increases in their elasticities.
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Evidence on IO Technology Assumptions From the Longitudinal Research Database
May 1993
Working Paper Number:
CES-93-08
This paper investigates whether a popular IO technology assumption, the commodity technology model, is appropriate for specific United States manufacturing industries, using data on product composition and use of intermediates by individual plants from the Census Longitudinal Research Database. Extant empirical research has suggested the rejection of this model, owing to the implication of aggregate data that negative inputs are required to make particular goods. The plant-level data explored here suggest that much of the rejection of the commodity technology model from aggregative data was spurious; problematic entries in industry-level IO tables generally have a very low Census content. However, among the other industries for which Census data on specified materials use is available, there is a sound statistical basis for rejecting the commodity technology model in about one-third of the cases: a novel econometric test demonstrates a fundamental heterogeneity of materials use among plants that only produce the primary products of the industry.
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Computer Networks and U.S. Manufacturing Plant Productivity: New Evidence from the CNUS Data
January 2002
Working Paper Number:
CES-02-01
How do computers affect productivity? Many recent studies argue that using information technology, particularly computers, is a significant source of U.S. productivity growth. The specific mechanism remains elusive. Detailed data on the use of computers and computer networks have been scarce. Plant-level data on the use of computer networks and electronic business processes in the manufacturing sector of the United States were collected for the first time in 1999. Using these data, we find strong links between labor productivity and the presence of computer networks. We find that average labor productivity is higher in plants with networks. Computer networks have a positive and significant effect on plant labor productivity after controlling for multiple factors of production and plant characteristics. Networks increase estimated labor productivity by roughly 5 percent, depending on model specification. Model specifications that account for endogenous computer networks also show a positive and significant relationship. Our work differs from others in several important aspects. First, ours is the first study that directly links the use of computer networks to labor productivity using plant-level data for the entire U.S. manufacturing sector. Second, we extend the existing model relating computers to productivity by including materials as an explicit factor input. Third, we test for possible endogeneity problems associated with the computer network variable.
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