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Business Establishment Growth in the Appalachian Region, 2000-2007: An Application of Smooth Transition Spatial Process Models

Published online by Cambridge University Press:  26 January 2015

Wan Xu  and
Dayton M. Lambert
Wan Xu
Affiliation:
Department of Agricultural and Resource Economics, University of Tennessee, Knoxville, Tennessee
Dayton M. Lambert
Affiliation:
Department of Agricultural and Resource Economics, University of Tennessee, Knoxville, Tennessee
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Abstract

Business establishment growth in the Appalachian region (2000-2007) was regressed on industry sector composition controlling for demographic, physical, and economic determinants. We test the hypothesis that local response to growth determinants is geographically heterogeneous using Smooth Transition spatial process models. This class of models exhibiting endogenous regime switching behavior provides another tool for exploring the spatially heterogeneous effects of local determinants on economic growth.

Keywords

Appalachiabusiness establishment growthsmooth transition modelsspatial processesC21C51047R11
Type
Invited Paper Sessions
Information
Journal of Agricultural and Applied Economics , Volume 43 , Issue 3 , August 2011 , pp. 309 - 324
Copyright
Copyright © Southern Agricultural Economics Association 2011

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References

Aldstadt, J., and Getis, A. “Using AMOEBA to Create a Spatial Weights Matrix and Identify Spatial Clusters.” Geographical Analysis 38(2006):327-43.CrossRefGoogle Scholar
Anselin, L.Spatial Econometrics: Methods and Models. Dordrecht: Kluwer Academic Publishers, 1988.CrossRefGoogle Scholar
Anselin, L. “Under the Hood: Issues in the Specification and Interpretation of Spatial Regression Models.” Agricultural Economics 27(2002):247-67.CrossRefGoogle Scholar
Anselin, L. “Spatial Regression.” Working Paper, Spatial Analysis Laboratory, Department of Geography and National Center for Supercomputing Applications, Urbana-Champaign, 2006.Google Scholar
Anselin, L., and Florax, R.Small Sample Properties of Tests for Spatial Dependence in Regression Models. Berlin, Germany: New Directions in Spatial Econometrics, 1995.Google Scholar
Anselin, L., Florax, R.J.G.M., and Rey, S.J.Advances in Spatial Econometrics: Methodology, Tools and Applications. Berlin, Germany: Springer, 2004.CrossRefGoogle Scholar
Anselin, L., and Lozano-Gracia, N. “Error in Variables and Spatial Effects in Hedonic House Price Models of Ambient Air Quality.” Empirical Economics 34(2008):5—34.CrossRefGoogle Scholar
Anselin, L., Wendy, K., and Cho, T. “Spatial Effects and Ecological Inference.” Political Analysis 10(2002):276-97.CrossRefGoogle Scholar
Arbia, G., Basile, R., and Piras, G. “Using Spatial Panel Data in Modeling Regional Growth and Convergence.” Working paper, Institute for Studies and Economic Analyses, Rome, Italy, 2005.Google Scholar
Arraiz, I., Drukker, D.M., Kelejian, H.H., and Prucha, I.R. “A Spatial Cliff-Ord Type Model with Heteroskedastic Innovations: Small and Large Sample Results.” Journal of Regional Science 50(2010):592–614.CrossRefGoogle Scholar
Baldwin, R., Forslid, R.Martin, P., Ottaviano, G., and Robert-Nicoud, F.Economic Geography and Public Policy. Princeton, NJ: Princeton University Press, 2003.Google Scholar
Basile, R. “Regional Economic Growth in Europe: A Semi-parametric Spatial Dependence Approach.” Regional Science 87(2008):527-44.CrossRefGoogle Scholar
Basile, R., and Gress, B. “Semi-Parametric Spatial Auto-Covariance Models of Regional Growth in Europe.” Région et Dévéloppement 21(2005):93–118.Google Scholar
Boots, B., and Dufournaud, C. “A Programming Approach to Minimizing and Maximizing Spatial Autocorrelation Statistics.” Geographical Analysis 26(1994):54–66.CrossRefGoogle Scholar
Brakman, S., Garretsen, H., and Marrewijk, C.V.An Introduction to Geographical Economics: Trade, Location and Growth. Cambridge, UK: Cambridge University Press, 2001.CrossRefGoogle Scholar
Bureau of Economic Analysis. Internet site: http://www.bea.gov/ (Accessed 2007).Google Scholar
Casetti, E. “Generating Models by the Expansion Method: Applications to Geographical Research.” Geographical Analysis 4(1972):81–91.CrossRefGoogle Scholar
Cho, S., Lambert, D.M., and Chen, Z. “Geographically Weighted Regression Bandwidth Selection and Spatial Autocorrelation: An Empirical Example Using Chinese Agriculture Data.” Applied Economics Letters 17(2010):767-72.CrossRefGoogle Scholar
Clark, C.D., Lambert, D.M., Park, W.M., and Wilcox, M.D. “Willingness to Fund Public Education in a Rural Retirement Destination County.” Journal of Research in Rural Education 24(2009):1–16.Google Scholar
Deller, S.C., Tsai, T.-H., Marcouiller, D.W., and English, D.B.K. “The Role of Amenities and Quality of Life in Rural Economic Growth.” American Journal of Agricultural Economics 83(2001):352-65.CrossRefGoogle Scholar
Feser, E., Renski, H., and Goldstein, H. “Clusters and Economic Development Outcomes: An Analysis of the Link between Clustering and Industry Growth.” Economic Development Quarterly 22(2008):324-44.CrossRefGoogle Scholar
Fingleton, B. “A Generalized Method of Moments Estimator for a Spatial Model with Moving Average Errors, with Application to Real Estate Prices.” Empirical Economics 34(2008):35–57.CrossRefGoogle Scholar
Florax, R.J.G.M., Folmer, H., and Rey, S.J. “Specification Searches in Spatial Econometrics: The Relevance of Hendry's Methodology.” Regional Science and Urban Economics 33(2003):557-79.CrossRefGoogle Scholar
Foster, S.A., and Gorr, W.L. “An Adaptive Filter for Estimating Spatially-Varying Parameters: Application to Modeling Police Hours Spent in Response to Calls for Service.” Management Science 32(1986):878-89.CrossRefGoogle Scholar
Fritsch, M., and Mueller, P. “Regional Growth Regimes Revisited—The Case of West Germany.” Discussion paper, Germany. Max Planck Institute of Economics, Entrepreneurship, Growth and Public Policy Group, March 2004.Google Scholar
Fujita, M., Krugman, P., and Venables, A.J.The Spatial Economy. Cambridge, MA: MIT Press, 1999.CrossRefGoogle Scholar
Fujita, M., and Thisse, J.-F.Economics of Agglomeration: Cities, Industrial Location, and Regional Growth. Cambridge, UK: Cambridge University Press, 2002.CrossRefGoogle Scholar
Getis, A., and Aldstadt, J. “Constructing the Spatial Weights Matrix Using a Local Statistic.” Geographical Analysis 36(2004):90–104.CrossRefGoogle Scholar
Greene, W.H.Econometric Analysis. Upper Saddle River, NJ: Prentice Hall, 2000.Google Scholar
Gress, B. “Semiparametric Spatial Autocovar-iance Models.” PhD Dissertation, University of California, Riverside, 2004.Google Scholar
Hendry, D.F. “A Comment on Specification Searches in Spatial Econometrics: The Relevance of Hendry's Methodology.” Regional Science and Urban Economics 36(2006):309-12.CrossRefGoogle Scholar
Holt, T.M., and Craig, L.A. “Nonlinear Dynamic and Structural Change in the U.S. Hog-Corn Cycle: A Time-Varying STAR Approach.” American Journal of Agricultural Economics 88(2006):215-33.CrossRefGoogle Scholar
Irwin, E., Isserman, A.M., Kilkenny, M., and Partridge, M.D. “A Century of Research on Rural Development and Regional Issues.” American Journal of Agricultural Economics 92(2010):522-53.CrossRefGoogle Scholar
Jacobs, J.The Death and Life of Great American Cites. London, UK: Penguin Books, 1965.Google Scholar
Johnson, T.G. “The Rural Economy in a New Century.” International Review of Regional Science 24(2001):21–37.CrossRefGoogle Scholar
Kahn, R., Orazem, P.F., and Otto, D.M. “Deriving Empirical Definitions of Spatial Labor Markets: The Roles of Competing versus Complementary Growth.” Journal of Regional Science 41(2001):735-56.CrossRefGoogle Scholar
Keefe, S.E.Participatory Development in Appalachia: Cultural Identity, Community, and Sustainability. Knoxville, TN: University of Tennessee Press, 2009.Google Scholar
Kelejian, H.H., and Prucha, I.R. “A Generalized Moments Estimator for the Autoregressive Parameter in a Spatial Model.” International Economic Review 40(1999):509-33.CrossRefGoogle Scholar
Kelejian, H.H., and Prucha, I.R. “Specification and Estimation of Spatial Autoregressive Models with Autoregressive and Heteroskedastic Disturbances.” Journal of Econometrics 157(2010):53–67.CrossRefGoogle ScholarPubMed
Kooijman, S.A.L.M. “Some Remarks on the Statistical Analysis of Grids Especially with Respect to Ecology.” Annals of Systems Research 5(1976):113-32.CrossRefGoogle Scholar
Lambert, D.M., Clark, C.D., Wilcox, M.D., and Park, W.M. “Do Migrating Retirees Affect Business Establishment and Job Growth? An Empirical Look at Southeastern Non-Metropolitan Counties, 2000-2004.” The Review of Regional Studies 37(2007):251-78.CrossRefGoogle Scholar
Lambert, D.M., and McNamara, K.T. “Location Determinants of Food Manufacturers in the U.S., 2000-2004: Are Nonmetropolitan Counties Competitive?” Agricultural Economics 40(2009):617-30.CrossRefGoogle Scholar
Larch, M., and Walde, J. “Lag or Error? Detecting the Nature of Spatial Correlation.” Data Analysis, Machine Learning and Applications. Preisach, C., Burkhardt, H., Schmidit-Thieme, L., and Decker, R., eds. Berlin, Germany: Springer, 2008.Google Scholar
Lebreton, J.-D. “Dynamical and Statistical Models for Exploited Populations.” Australian and New Zealand Journal of Statistics 47 (2005):49–63.CrossRefGoogle Scholar
Lee, L.-F. “Best Spatial Two-Stage Least Squares Estimators for a Spatial Autoregressive Model with Autoregressive Disturbances.” Econometric Reviews 22(2003):307-35.CrossRefGoogle Scholar
LeGallo, J., and Ertur, C. “Exploratory Spatial Data Analysis of the Distribution of Regional per Capita GDP in Europe, 1980-1995.” Regional Science 82(2003):175–201.CrossRefGoogle Scholar
LeSage, J.P., and Pace, K.Introduction to Spatial Econometrics. Boca Raton, FL: Taylor & Francis Group LLC, 2009.CrossRefGoogle Scholar
Maddala, G.S.Limited-Dependent and Qualitative Variables in Econometrics. Cambridge, UK: Cambridge University Press, 1983.CrossRefGoogle Scholar
McGranahan, D.A.Natural Amenities Drive Rural Population Change. Agricultural Economic Report No. 781. Washington, DC: U.S. Department of Agriculture, 1999.Google Scholar
McGranahan, D.A. “Landscape Influence on Recent Rural Migration in the U.S.” Landscape and Urban Planning 85(2008):228-10.CrossRefGoogle Scholar
Moreno, R., Lopez-Bazo, E., Vaya, E., and Artis, M. “External Effects and Cost of Production.” Advances in Spatial Econometrics: Methodology, Tools and Applications. Berlin, Germany: Springer, 2004.Google Scholar
Partridge, M.D., Rickman, D.S., Ali, K., and Olfert, M.R. “The Geographic Diversity of U.S. Nonmetropolitan Growth Dynamics: A Geographically Weighted Regression Approach.” Land Economics 84(2008):241-66.CrossRefGoogle Scholar
Pede, V.O. “Spatial Dimensions of Economic Growth: Technological Leadership and Club Convergence.” Ph.D. Dissertation, Purdue University, 2010.Google Scholar
Pede, O.V., Florax, R.J.G.M., and Holt, M.T. “A Spatial Econometric STAR Model with an Application to U.S. County Economic Growth, 1969-2003.” Working paper, Department of Agricultural Economics, Purdue University, 2009.Google Scholar
Pede, O.V., Florax, R.J.G.M., Lambert, D.M., and Holt, M.T. “Spatial Econometric STAR Models: Lagrange Multiplier Tests and Monte Carlo Simulations.” Paper presented at the 53rd Annual Meeting of North American Regional Science Association, November 2010.Google Scholar
Quandt, R. “The Estimation of the Parameters of a Linear Regression System Obeying Two Separate Regimes.” Journal of the American Statistical Association 53(1958):873-80.CrossRefGoogle Scholar
Rogoff, E.G.The Issues and Opportunities of Entrepreneurship after Age 50. Washington, DC: AARP, Office of Academic Affairs. Occasional Paper No. 5, 2008.Google Scholar
Schabenberger, O., and Pierce, F.J.Contemporary Statistical Models for the Plant and Soil Sciences. New York: CRC Press, 2002.Google Scholar
Spencer, G.M., Vinodrai, T.M., Gertler, S., and Wolfe, D.A. “Do Clusters Make a Difference? Defining and Assessing Their Economic Performance.” Regional Studies 44(2010):697–715.CrossRefGoogle Scholar
Terasvirta, T., and Anderson, H.M. “Characterizing Nonlinearities in Business Cycles Using Smooth Transition Autoregressive Models.” Journal of Applied Econometrics 7(1992):119-36.CrossRefGoogle Scholar
Van Dijk, D., and Franses, P.H. “Nonlinear Error-Correction Models for Interest Rates in The Netherlands.” Nonlinear Econometric Modelling. Barnett, W.A., Hendry, D.F., Hylleberg, S., Teräsvirta, T., Tjøstheim, D. and Wiirtz, A., eds. Cambridge, UK: Cambridge University Press, 2000.Google Scholar
Voss, P.R., White, K.J.C., and Hammer, R.B. “The (Re-) Emergence of Spatial Demography.” Working paper. Madison, WI: Center for Demography and Ecology, University of Wisconsin, 2004.Google Scholar
Whittle, P. “On Stationary Processes in the Plane.” Biometrika 41(1954):434-49.CrossRefGoogle Scholar
Wojan, T.R., and McGranahan, D.A. “Ambient Returns: Creative Capital's Contribution to Local Manufacturing Competitiveness.” Agricultural and Resource Economics Review 36(2007):133-8.CrossRefGoogle Scholar
Wojan, T.R., McGranahan, D.A., and Lambert, D.M. “The Rural Growth Trifecta: Outdoor Amenities, Creative Class and Entrepreneurial Context.” Journal of Economic Geography. (2010):1–29.Google Scholar