Hostname: page-component-7dd5485656-frp75 Total loading time: 0 Render date: 2025-10-30T13:26:19.923Z Has data issue: false hasContentIssue false
  • English
  • Français

An Application of Spatial Poisson Models to Manufacturing Investment Location Analysis

Published online by Cambridge University Press:  28 April 2015

Dayton M. Lambert ,
Kevin T. McNamara  and
Megan I. Garrett
Dayton M. Lambert
Affiliation:
Economic Research Service at the U.S. Department of Agriculture
Kevin T. McNamara
Affiliation:
Department of Agricultural Economics, Purdue University, West Lafayette, IN
Megan I. Garrett
Affiliation:
Agricel, Effingham, IL
Get access Rights & Permissions [Opens in a new window]

Abstract

The influence product markets, agglomeration, labor, infrastructure, and government fiscal attributes had on manufacturing investment flows in Indiana between 2000 and 2004 were estimated using Poisson regression, geographically weighted regression, and a spatial general linear model. Counties with access to urbanization economies, product markets, available labor, a high-quality workforce, and transport infrastructure were more likely to attract manufacturing investment. These effects were magnified to some extent when inter-county spatial effects were modeled. The distributional assumptions of the spatial models are different, but both methods are useful for understanding the spatial context of the factors influencing manufacturing investment flows.

Keywords

geographically weighted regressionlocation determinantslocation theorymanufacturing site selectionPoisson spatial generalized linear modelR1R3

Information

Type
Articles
Information
Journal of Agricultural and Applied Economics , Volume 38 , Issue 1 , April 2006 , pp. 105 - 121
Copyright
Copyright © Southern Agricultural Economics Association 2006

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

Article purchase

Temporarily unavailable

References

Anselin, L.Spatial Econometrics: Methods and Models. London: Kluwer Academic Publishers, 1988.CrossRefGoogle Scholar
Anselin, L., Florax, R.J.G.M., and Rey, S.J.. Advances in Spatial Econometrics: Methodology, Tools and Applications. Berlin: Springer, 2004.CrossRefGoogle Scholar
Bartik, T.J. “Business Location Decisions in the United States: Estimates of the Effects of Unionization, Taxes, and Other Characteristics of States.” Journal of Business and Economic Statistics 3, 1(1985):14–22.Google Scholar
Bartik, T.J. “Small Business Start-Ups in the United States: Estimates of the Effects of Characteristics of States.” Southern Economic Journal 55, 4(1989):1004-18.CrossRefGoogle Scholar
Bivand, R.S., and Brunstad, R.J.. “Further explorations of interactions between agricultural policy and regional growth in Western Europe: Approaches to nonstationarity in spatial econometrics.” Paper presented at the Kiel Spatial Econometrics Workshop, Kiel, Germany, April 8-9, 2005 (Accessed July 12, 2005, http://www.uni-kiel.de/ifw/konfer/spatial/bivand.brunstadt.pdf).Google Scholar
Brundson, C., Fotheringham, A.S., and Charlton, M.. “Geographically Weighted Regression: A Method for Exploring Spatial Nonstationarity.” Geographical Analysis 28(1996):218-98.Google Scholar
Bureau of Labor Statistics REIS Data Base. Internet site: http://data.bls.gov/PDQ/outside.jsp?survey=sm (Accessed January 12, 2004).Google Scholar
Cohen, J.P., and Paul, C.M.. “Agglomeration Economies and Industry Location Decisions: The Impacts of Spatial and Industrial Spillovers.” Regional Science and Urban Economics, 35 (2005):215-37.CrossRefGoogle Scholar
Coughlin, C.C., Terza, J.V., and Arromdee, V.. “State Characteristics and the Location of Foreign Direct Investment within the United States.” The Review of Economics and Statistics 73, 4(1991):675-83.CrossRefGoogle Scholar
Cressie, N.Statistics for Spatial Data. New York: Wiley, 1993.CrossRefGoogle Scholar
Dubin, R. “Estimating Logit Models with Spatial Dependencies.” New Directions in Spatial Econometrics. Anselin, L. and Florax, R., eds. Heidelberg: Springer-Verlag, 1995.Google Scholar
Eberts, R.W., and McMillen, D.P.. “Agglomeration Economies and Urban Public Infrastructure.” Handbook of Regional and Urban Economics. Mills, E.S. and Cheshire, P., eds. Amsterdam: Elsevier, 1999.Google Scholar
Fotheringham, A.S., Brunson, C., and Charlton, M.. Geographically Weighted Regression. Hoboken, NJ: Wiley, 2002.Google Scholar
Gabe, T.M. “Industry Agglomeration and Investment in Rural Business.” Review of Agricultural Economics 27, 1(2005):89–103.CrossRefGoogle Scholar
Glickman, N.J., and Woodward, D.P.. “The Location of Foreign Direct Investment in the United States: Patterns and Determinants.” International Regional Science Review 11, 2(1988):137-54.CrossRefGoogle Scholar
Goetz, S. “State- and County-Level Determinants of Food Manufacturing Establishment Growth: 1987—1993.” American Journal of Agricultural Economics 79, 3(1997): 838-50.CrossRefGoogle Scholar
Greene, W.H.Econometric Analysis, 4th ed. NJ: Prentice Hall, 2000.Google Scholar
Guimarães, P., Figueiredo, O., and Woodward, D.. “Industrial Location Modeling: Extending the Random Utility Framework.” Journal of Regional Science 44, 1(2004): 1–20.CrossRefGoogle Scholar
Henderson, V. “Externalities and Industrial Development.” City scape: A Journal of Policy Development and Research 1, 1(1994):75–93.Google Scholar
Henderson, J.R., and McNamara, K.T.. “Community Attributes Influencing Local Food Processing Growth in the U.S. Corn Belt.” Canadian Journal of Agricultural Economics 45(1997): 235-50.CrossRefGoogle Scholar
Henderson, J.R., and McNamara, K.T.. “The Location of Food Manufacturing Plant Investments in Corn Belt Counties.” Journal of Agricultural and Resource Econmics 25(2) (2000):680-97.Google Scholar
Henry, M., and Drabenscott, M.. A New Micro View of the U.S. Rural Economy. Economic Review. Federal Reserve Bank of Kansas City, Second Quarter, 1996.Google Scholar
Huang, Y, and Leung, Y.. “Analyzing Regional Industrialization in Jiangsu Province Using Geographically Weighted Regression.” Journal of Geographical Systems 4(2002):233-49.CrossRefGoogle Scholar
Hurvich, C.M., Simonoff, J.S., and Tsai, C.-L.. “Smoothing Parameter Selection in Nonpara-metric Regression Using an Improved Akaike Information Criterion.” Journal of the Royal Statistical Society 60(1998):271-93.CrossRefGoogle Scholar
Kriesel, W, and McNamara, K.T.. “A County-Level Model of Manufacturing Plant Recruitment with Improved Industrial Site Quality Measurement.” Southern Journal of Agricultural Economics (July 1991): 121-7.Google Scholar
LeSage, J.P. “The Theory and Practice of Spatial Econometrics.” Unpublished Manuscript, Department of Economics, University of Toledo, 1999. Available at www.spatial-econometrics.com/html/sbook.pdf (Accessed November 23, 2004).Google Scholar
LeSage, J.P. Econometrics Toolbox for MATLAB. Internet site: http://www.spatial-econometrics.com/. (Accessed April 28, 2005).Google Scholar
LeSage, J.P. “A Family of Geographically Weighted Regression Models.” Advances in Spatial Econometrics: Methodology, Tools and Applications. Anselin, L., Florax, R.J.G.M., and Rey, S.J.. eds. Berlin: Springer, 2004.Google Scholar
Leung, Y, Mei, C.-L., and Zhang, W.-X.. “Statistical Tests for Spatial Nonstationarity Based on the Geographically Weighted Regression.” Environment and Planning 32(2000):871-90.CrossRefGoogle Scholar
Maddala, G.S.Limited-Dependent and Qualitative Variables in Econometrics. Cambridge, UK: Cambridge University Press, 1983.CrossRefGoogle Scholar
McNamara, K.T., Kriesel, W., and Rainey, D.V.. “Manufacturing Recruiting as a Rural Development Strategy.” Rural Development Strategies. Sears, D.W. and Reid, J.N.. eds. Chicago: Nelson-Hall, 1995.Google Scholar
McNamara, K.T., Kriesel, W.P., and Deaton, B.J.. “Manufacturing Location: The Impact of Human Capital Stocks and Flows.” Review of Regional Studies 18, 1(1988):42-8.CrossRefGoogle Scholar
McNamara, K.T., Lambert, D.M., and Garrett, M.I.. “The Influence of Local Attributes on Food Plant Location Choices.” Paper presented at the Kiel Spatial Econometrics Workshop, Kiel, Germany, April 8-9, 2005 (Accessed July 12, 2005, http://www.uni-kiel.de/ifw/konfer/spatial/mcnamaraJambert_garret.pdf).Google Scholar
Rasmussen, S. “Modeling of Discrete Spatial variation in Epidemiology with SAS using GLIM-MIX.” Computer Methods and Programs in Biomedicine 76(2004):83-9.CrossRefGoogle Scholar
Rainey, D.V., and McNamara, K.T.. “Taxes and Location Decision of Manufacturing Establishments.” Review of Agricultural Economics 21, 1(1999):86–98.Google Scholar
Richardson, H.W.Regional Growth Theory. New York: Wiley, 1973.CrossRefGoogle Scholar
Rosenthal, S.S., and Strange, W.C.. “The Determinants of Agglomeration.” Journal of Urban Economics 50(2001):191–229.CrossRefGoogle Scholar
SAS. Version 8.0. Cary, North Carolina: The SAS Institute, Inc., 2000.Google Scholar
Schabenberger, O., and Pierce, E.J.. Contemporary Statistical Models for the Plant and Soil Sciences. New York: CRC Press, 2002.Google Scholar
Smith, E.D., Deaton, B.J., and Kelch, D.R.. “Location Determinants of Manufacturing Industry in Rural Areas.” Southern Journal of Agricultural Economics(July 1978):23–32.Google Scholar
Smith, D.F., and Florida, R.. “Agglomeration and Industrial Location: An Econometric Analysis of Japanese-Affiliated Manufacturing Establishments in Automotive-Related Industries.” Journal of Urban Economics 36(1994):23–41.CrossRefGoogle Scholar
Strange, W.C. “Agglomeration.” The New Palgrave Dictionary of Economics and the Law, 2nd ed. Newman, P., ed. Macmillan Publishing: New Zealand, 2005.Google Scholar
Viladecans-Marsal, E. “Agglomeration Economies and Industrial Location: City-Level Evidence.” Journal of Economic Geography 4(2004):565-82.CrossRefGoogle Scholar
Wang, Q., Ni, J., and Tenhunen, J.. “Application of a Geographically Weighted Regression Analysis to Estimate Net Primary Production of Chinese Forest Ecosystems.” Global Ecology and Biogeography 14(2005):379-93.CrossRefGoogle Scholar
Wojan, T.R. “The Composition of Rural Employment Growth in the ‘New Economy’.” American Journal of Agricultural Economics 82 (2000):594–605.CrossRefGoogle Scholar
Woodward, D.P. “Locational Determinants of Japanese Manufacturing Start-ups in the United States.” Southern Economics Journal 58 (1992):690–708.CrossRefGoogle Scholar
Wooldridge, J.Introductory Econometrics. Mason, Ohio: Southwestern College Publishing, 2000.Google Scholar