Measures used in entrepreneurship research are often subject to spatial dependence. Spatial dependence renders ordinary least squares (OLS) estimation inappropriate because the estimates will be biased, inconsistent, and/or inefficient. The aims of this article are (a) to demonstrate how spatial dependence is especially problematic for entrepreneurship research and (b) to arm researchers with spatial modeling techniques that are more appropriate for such analysis. As such, not only will this article illustrate how to incorporate spatial dependence explicitly into the linear regression model, it also discusses how these techniques make it possible to explore and locate areas with particularly high levels of spatial dependence (i.e., hot spots). These techniques, although new to the management literature, are well known in both the regional science and geography literatures and are rapidly diffusing to economics, sociology, and related social sciences.
Acs, Z.J., Audretsch, D.B., Braunerhjelm, P., & Carlsson, B. ( 2005). The knowledge spillover theory of entrepreneurship. Unpublished Working Paper.
2.
Acs, Z.J., & Plummer, L.A. ( 2005). Penetrating the ‘knowledge filter’ in regional economies. Annals of Regional Science, 39, 439-456.
3.
Acs, Z.J., Plummer, L.A., & Sutter, R. (in press). Penetrating the knowledge filter in ‘rust belt’ economies. Annals of Regional Science.
4.
Almeida, P., & Kogut, B. ( 1997). The exploration of technological diversity and the geographic localization of innovation. Small Business Economics, 9, 21-31.
5.
Andersson, D.E. ( 2005). The spatial nature of entrepreneurship. Quarterly Journal of Austrian Economics, 8, 21-34.
6.
Anselin, L. ( 1988). Spatial econometrics: Methods and models. Dordrecht, The Netherlands: Kluwer Academic.
7.
Anselin, L. ( 1995). Local indicators of spatial association - LISA. Geographical Analysis, 27, 93-115.
8.
Anselin, L. ( 2001a). Rao’s score test in spatial econometrics. Journal of Statistical Planning and Inference, 97, 113-139.
9.
Anselin, L. ( 2001b). Spatial econometrics. In B. Baltagi (Ed.), A companion to theoretical econometrics (pp. 310-330). Oxford, UK: Basil Blackwell.
10.
Anselin, L. ( 2002). Under the hood: Issues in the specification and interpretation of spatial regression models. Agricultural Economics, 27, 247-267.
11.
Anselin, L., & Bera, A.K. ( 1998). Spatial dependence in linear regression models with an introduction to spatial econometrics. In A. Ullah & D. Giles (Eds.), Handbook of applied economic statistics (pp. 237-246). New York: Marcel Dekker.
12.
Anselin, L., Le Gallo, J., & Jayet, H. ( 2008). Spatial panel econometrics. In L. Matyas & P. Sevestre (Eds.), The econometrics of panel data, fundamentals and recent developments in theory and practice (3rd ed., pp. 625-660). Dordrecht, The Netherlands: Kluwer.
13.
Anselin, L., Syabri, I., & Kho, Y. ( 2006). GeoDa: An introduction to spatial data analysis. Geographical Analysis, 38, 5-22.
14.
Anselin, L., Syabri, I., & Smirnov, O. ( 2002). Visualizing multivariate spatial correlation with dynamically linked windows. Unpublished Working Paper.
15.
Anselin, L., Varga, A., & Acs, Z.J. ( 1997). Local geographic spillovers between university research and high technology innovations. Journal of Urban Economics , 42, 422-448.
16.
Armington, C., & Acs, Z.J. ( 2002). The determinants of regional variation in new firm formation . Regional Studies, 36, 33-45.
17.
Atkinson, P.M. ( 1995). A method for describing quantitatively the information, redundancy and error in digital spatial data. In P. Fisher (Ed.), Innovation in GIS 2 (pp. 85-96). Bristol, PA: Taylor and Francis, Inc.
18.
Ballinger, G.A. ( 2004). Using generalized estimating equations for longitudinal data analysis. Organizational Research Methods, 7, 127-150.
19.
Barber, B.M., & Lyon, J.D. ( 1996). Detecting abnormal operating performance: The empirical power and specification of test statistics. Journal of Financial Economics, 41, 359-399.
20.
Barnett, V., & Lewis, T. ( 1994). Outliers in statistical data. Chichester , UK: John Wiley.
21.
Beck, N., Gleditsch, K.S., & Beardsley, K. ( 2006). Space is more than geography: Using spatial econometrics in the study of political economy. International Studies Quarterly , 50, 27-44.
22.
Belsley, D.A., Kuh, E., & Welsch, R. ( 1980). Regression diagnostics. New York: John Wiley.
23.
Bhagat, S., & Jefferis, R. ( 2002). The econometrics of corporate governance. Cambridge, MA: MIT Press.
24.
Bliese, P.D., & Hanges, P.J. ( 2004). Being both too liberal and too conservative: The perils of treating grouped data as though they were independent. Organizational Research Methods, 7, 400-417.
25.
Cooper, A.C., & Folta, T.B. ( 2000). Entrepreneurship in high-technology clusters. In D. L. Sexton & H. Landstrom (Eds.), Handbook of entrepreneurship (pp. 348-367). Malden, MA: Blackwell Publishers.
26.
Darmofal, D. ( 2006). Spatial econometrics and political science. Paper presented at the Southern Political Science Association . Retrieved September 5, 2008, from http://polmeth.wustl.edu/retrieve.php?id=575
27.
Davidsson, P. ( 2004). Researching entrepreneurship. New York: Springer.
28.
Deeds, D.L., Decarolis, D., & Coombs, J.E. ( 1997). The impact of firm-specific capabilities on the amount of capital raised in an initial public offering: Evidence from the biotechnology industry. Journal of Business Venturing, 12, 31-46.
29.
Doh, J.P., & Hahn, E.D. ( 2008). Using spatial methods in strategy research. Organizational Research Methods, 11, 659-681.
30.
Dumais, G., Ellison, G., & Glaeser, E.L. ( 2002). Geographic concentration as a dynamic process. Review of Economics and Statistics, 84, 193-204.
31.
Eckhardt, J.T., & Shane, S. ( 2003). Opportunities and entrepreneurship. Journal of Management, 29, 333-349.
32.
Fama, E.F., & French, K. ( 1995). Size and book-to-market factors in earnings and returns . Journal of Finance, 50, 131-155.
33.
Gilbert, B.A., McDougall, P.P., & Audretsch, D.B. (2008). Clusters, knowledge spillovers and new venture performance: An empirical examination. Journal of Business Venturing, 23, 405-422.
34.
Goddard, J.A., & Wilson, J.O.S. (1999). The persistence of profit: A new empirical interpretation. International Journal of Industrial Organization, 17, 663-687.
Haining, R. ( 1990). Spatial data analysis in the social and environmental sciences. Cambridge, UK: Cambridge University Press.
37.
Heywood, I. ( 1998). Introduction to geographical information systems. New York: Addison Wesley Longman.
38.
Hitt, M.A., Gimeno, J., & Hoskisson, R.E. (1998). Current and future research methods in strategic management. Organizational Research Methods , 1, 6-44.
39.
Kennedy, P. ( 2003). A guide to econometrics. Cambride, MA: MIT Press.
40.
Lacombe, D.J. ( 2004). Does econometric methodology matter? An analysis of public policy using spatial econometric techniques. Geographical Analysis, 36, 105-118.
41.
LeSage, J.P. ( 1999). Spatial econometrics. Retrieved July 31, 2005, from http://www.rri.wvu.edu/regscweb.htm
42.
LeSage, J.P., & Charles, J. ( 2008). Using home buyers’ revealed preferences to define the urban-rural fringe. Journal of Geographical Systems, 10, 1-21.
43.
Martin, R., & Sunley, P. ( 2003). Deconstructing clusters: Chaotic concept or policy panacea ? Journal of Economic Geography, 3, 5-35.
44.
McCann, B.T., & Folta, T.B. ( 2008). Location matters: Where we have been and where we might go in agglomeration research. Journal of Management, 34, 532-565.
45.
McDougall, P.P., Deane, R.H., & D’Souza, D.E. (1992). Manufacturing strategy and business origin of new venture firms in the computer and communications equipment industries. Production and Operations Management , 1, 53-69.
46.
Messner, S.F., Anselin, L., Baller, R.D., Hawkins, D.F., Deane, G., & Tolnay, S.E. ( 1999). The spatial patterning of county homicide rates: An application of exploratory spatial data analysis. Journal of Quantitative Criminology, 15, 423-450.
47.
Parker, S.C. ( 2004). The economics of self-employment and entrepreneurship . Cambridge, UK: Cambridge University Press.
48.
Parker, S.C. ( 2008). Statistical issues in applied entrepreneurship: Data, methods and challenges. In E. Congregado (Ed.), Measuring entrepreneurship (pp. 9-20). New York: Springer.
49.
Pe’er, A., & Vertinsky, I. ( 2008). Firm exits as a determinant of new entry: Is there evidence of local creative destruction?Journal of Business Venturing , 23, 280-306.
50.
Pisati, M. ( 2001). Tools for spatial data analysis. Stata Technical Bulletin, STB-60, 21-37.
51.
Rosenthal, S.S., & Strange, W.C. ( 2004). Evidence on the nature and sources of agglomeration economies . In J. V. Henderson & J.-F. Thisse (Eds.), Handbook of urban and regional economics (Vol. 4, pp. 2119-2172). New York: North Holland.
52.
Russell, C.J., & Dean, M.A. ( 2000). To log or not to log: Bootstrap as an alternative to the parametric estimation of moderation effects in the presence of skewed dependent variables. Organizational Research Methods, 3, 166-185.
53.
Sarafoglou, N., & Paelinck, J. ( 2008). On diffusion of ideas in the academic world: The case of spatial econometrics. Annals of Regional Science, 42, 487-500.
54.
Shane, S., & Venkataraman, S. (2000). The promise of entrepreneurship as a field of research. Academy of Management Review, 25, 217-226.
55.
Sorenson, O., & Stuart, T.E. ( 2001). Syndication networks and the spatial distribution of venture capital investments. American Journal of Sociology , 106, 1546-1588.
56.
Strang, D., & Soule, S.A. ( 1998). Diffusion in organizations and social movements: From hybrid corn to poison pills. Annual Review of Sociology, 24, 265-290.
57.
Stuart, T., & Sorenson, O. ( 2003). The geography of opportunity: Spatial heterogeneity in founding rates and the performance of biotechnology firms. Research Policy, 32, 229-253.
58.
Tobler, W.R. ( 1970). A computer movie simulating urban growth in the Detroit region. Economic Geography, 46, 234-240.
59.
Varga, A. ( 1998). University research and regional innovation: A spatial econometric analysis of academic technology transfer. Boston: Kluwer.
60.
Waring, G.F. ( 1996). Industry differences in the persistence of firm-specific returns. American Economic Review, 86, 1253-1265.
61.
White, M.C., Tansey, R., Smith, M., & Long, R.G. ( 1998). Generalized linear models: Loglinear modeling in managerial research. Organizational Research Methods, 1, 223-247.
