Papers Containing Keywords(s): 'cluster'
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Viewing papers 1 through 9 of 9
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Working PaperGrouped Variation in Factor Shares: An Application to Misallocation
August 2022
Working Paper Number:
CES-22-33
A striking feature of micro-level plant data is the presence of significant variation in factor cost shares across plants within an industry. We develop a methodology to decompose cost shares into idiosyncratic and group-specific components. In particular, we carry out a cluster analysis to recover the number and membership of groups using breaks in the dispersion of factor cost shares across plants. We apply our methodology to Chilean plant-level data and find that group-specific variation accounts for approximately one-third of the variation in factor shares across firms. We also study the implications ofthese groups in cost shares on the gains from eliminating misallocation. We place bounds on their importance and find that ignoring them can overstate the gains from eliminating misallocation by up to one-third.View Full Paper PDF
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Working PaperRecalculating... : How Uncertainty in Local Labor Market Definitions Affects Empirical Findings
January 2017
Working Paper Number:
CES-17-49R
This paper evaluates the use of commuting zones as a local labor market definition. We revisit Tolbert and Sizer (1996) and demonstrate the sensitivity of definitions to two features of the methodology: a cluster dissimilarity cutoff, or the count of clusters, and uncertainty in the input data. We show how these features impact empirical estimates using a standard application of commuting zones and an example from related literature. We conclude with advice to researchers on how to demonstrate the robustness of empirical findings to uncertainty in the definition of commuting zonesView Full Paper PDF
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Working PaperEstimation and Inference in Regression Discontinuity Designs with Clustered Sampling
August 2015
Working Paper Number:
carra-2015-06
Regression Discontinuity (RD) designs have become popular in empirical studies due to their attractive properties for estimating causal effects under transparent assumptions. Nonetheless, most popular procedures assume i.i.d. data, which is not reasonable in many common applications. To relax this assumption, we derive the properties of traditional non-parametric estimators in a setting that incorporates potential clustering at the level of the running variable, and propose an accompanying optimal-MSE bandwidth selection rule. Simulation results demonstrate that falsely assuming data are i.i.d. when selecting the bandwidth may lead to the choice of bandwidths that are too small relative to the optimal-MSE bandwidth. Last, we apply our procedure using person-level microdata that exhibits clustering at the census tract level to analyze the impact of the Low-Income Housing Tax Credit program on neighborhood characteristics and low-income housing supply.View Full Paper PDF
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Working PaperAgglomerative Forces and Cluster Shapes
June 2012
Working Paper Number:
CES-12-09
We model spatial clusters of similar firms. Our model highlights how agglomerative forces lead to localized, individual connections among firms, while interaction costs generate a defined distance over which attraction forces operate. Overlapping firm interactions yield agglomeration clusters that are much larger than the underlying agglomerative forces themselves. Empirically, we demonstrate that our model's assumptions are present in the structure of technology and labor flows within Silicon Valley and its surrounding areas. Our model further identifies how the lengths over which agglomerative forces operate influence the shapes and sizes of industrial clusters; we confirm these predictions using variations across both technology clusters and industry agglomeration.View Full Paper PDF
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Working PaperClusters, 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.View Full Paper PDF
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Working PaperClusters and Entrepreneurship
September 2010
Working Paper Number:
CES-10-31
This paper examines the role of regional clusters in regional entrepreneurship. We focus on the distinct influences of convergence and agglomeration on growth in the number of start-up firms as well as in employment in these new firms in a given region-industry. While reversion to the mean and diminishing returns to entrepreneurship at the region-industry level can result in a convergence effect, the presence of complementary economic activity creates externalities that enhance incentives and reduce barriers for new business creation. Clusters are a particularly important way through which location-based complementarities are realized. The empirical analysis uses a novel panel dataset from the Longitudinal Business Database of the Census Bureau and the U.S. Cluster Mapping Project (Porter, 2003). Using this dataset, there is significant evidence of the positive impact of clusters on entrepreneurship. After controlling for convergence in start-up activity at the region-industry level, industries located in regions with strong clusters (i.e. a large presence of other related industries) experience higher growth in new business formation and start-up employment. Strong clusters are also associated with the formation of new establishments of existing firms, thus influencing the location decision of multiestablishment firms. Finally, strong clusters contribute to start-up firm survival.View Full Paper PDF
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Working PaperAccess to Workers or Employers? An Intra-Urban Analysis of Plant Location Decisions
September 2010
Working Paper Number:
CES-10-21R
This analysis attributes economies of agglomeration to either labor market pooling or employer-based productivity spillovers by distinguishing the effect of access to workers, measured by place-of-residence, from the effect of access to employers. New establishment location choices serve as a measure of productivity advantages, while census tract level data on access to same-industry employment, other-industry employment, and specialized workers, as well as metropolitan area fixed effects, measure sources of agglomeration and other locational characteristics. The four industries included are selected so that each relies on a workforce with a specialized occupation that is identifiable by place-of-residence, and that productivity and cost advantages are the primary drivers of location choice. The results show that both access to specialized workers and access to same-industry employers contribute to economies of agglomeration at an intra-urban spatial scale, and that the magnitude of the worker effect is large relative to employer-based productivity spillovers.View Full Paper PDF
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Working PaperClusters of Entrepreneurship
October 2009
Working Paper Number:
CES-09-36
Employment growth is strongly predicted by smaller average establishment size, both across cities and across industries within cities, but there is little consensus on why this relationship exists. Traditional economic explanations emphasize factors that reduce entry costs or raise entrepreneurial returns, thereby increasing net returns and attracting entrepreneurs. A second class of theories hypothesizes that some places are endowed with a greater supply of entrepreneurship. Evidence on sales per worker does not support the higher returns for entrepreneurship rationale. Our evidence suggests that entrepreneurship is higher when fixed costs are lower and when there are more entrepreneurial people.View Full Paper PDF
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Working PaperThe Classification of Manufacturing Industries: an Input-Based Clustering of Activity
August 1990
Working Paper Number:
CES-90-07
The classification and aggregation of manufacturing data is vital for the analysis and reporting of economic activity. Most organizations and researchers use the Standard Industrial Classification (SIC) system for this purpose. This is, however, not the only option. Our paper examines an alternative classification based on clustering activity using production technologies. While this approach yields results which are similar to the SIC, there are important differences between the two classifications in terms of the specific industrial categories and the amount of information lost through aggregation.View Full Paper PDF
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