On model specification and parameter space definitions in higher order spatial econometric models
Higher-order spatial econometric models that include more than one weights matrix have seen increasing use in the spatial econometrics literature. There are two distinct issues related to the specification of these extended models. The first issue is what form the higher-order spatial econometric model takes, i.e. higher-order polynomials in the spatial weights matrices vs. higher-order spatial autoregressive processes. The second issue relates to the parameter space in such models and how this can affect the choice of model specification, estimation, and inference. We outline a procedure that is simple both mathematically and computationally for finding the stationary region for spatial econometric models with up to K weights matrices for higher-order spatial autoregressive processes. We also compare and contrast this approach with the parameter space for models that incorporate higher-order polynomials in the spatial weights matrices. Regardless of the model utilized in empirical practice, ignoring the relevant parameter region can lead to incorrect inferences regarding both the nature of the spatial autocorrelation process and the effects of changes in covariates on the dependent variable.
References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Kelejian, Harry H. & Prucha, Ingmar R., 2002. "2SLS and OLS in a spatial autoregressive model with equal spatial weights," Regional Science and Urban Economics, Elsevier, vol. 32(6), pages 691-707, November.
- Kelejian, Harry H. & Prucha, Ingmar R., 2010. "Specification and estimation of spatial autoregressive models with autoregressive and heteroskedastic disturbances," Journal of Econometrics, Elsevier, vol. 157(1), pages 53-67, July.
- Kathleen P. Bell & Nancy E. Bockstael, 2000. "Applying the Generalized-Moments Estimation Approach to Spatial Problems Involving Microlevel Data," The Review of Economics and Statistics, MIT Press, vol. 82(1), pages 72-82, February.
- Harald Badinger & Peter Egger, 2011. "Estimation of higher‐order spatial autoregressive cross‐section models with heteroscedastic disturbances," Papers in Regional Science, Wiley Blackwell, vol. 90(1), pages 213-235, 03.
- Lung-Fei Lee, 2004. "Asymptotic Distributions of Quasi-Maximum Likelihood Estimators for Spatial Autoregressive Models," Econometrica, Econometric Society, vol. 72(6), pages 1899-1925, November.
- Lung-fei Lee, 2003. "Best Spatial Two-Stage Least Squares Estimators for a Spatial Autoregressive Model with Autoregressive Disturbances," Econometric Reviews, Taylor & Francis Journals, vol. 22(4), pages 307-335.
- Kelejian, Harry H & Prucha, Ingmar R, 1999. "A Generalized Moments Estimator for the Autoregressive Parameter in a Spatial Model," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 40(2), pages 509-33, May.
- A S Brandsma & R H Ketellapper, 1979. "A biparametric approach to spatial autocorrelation," Environment and Planning A, Pion Ltd, London, vol. 11(1), pages 51-58, January.
- Maarten Allers & J. Elhorst, 2005. "Tax Mimicking and Yardstick Competition Among Local Governments in the Netherlands," International Tax and Public Finance, Springer, vol. 12(4), pages 493-513, August.
- Nicolas DEBARSY (CERPE De Namur) & Cem ERTUR & James P. LeSAGE, 2010.
"Interpreting Dynamic Space-Time Panel Data Models,"
800, Orleans Economic Laboratorys, University of Orleans.
- Bordignon, Massimo & Cerniglia, Floriana & Revelli, Federico, 2003. "In search of yardstick competition: a spatial analysis of Italian municipality property tax setting," Journal of Urban Economics, Elsevier, vol. 54(2), pages 199-217, September.
- Krugman, Paul, 1993. "On the number and location of cities," European Economic Review, Elsevier, vol. 37(2-3), pages 293-298, April.
- Harry Kelejian & George Tavlas & George Hondroyiannis, 2006. "A Spatial Modelling Approach to Contagion Among Emerging Economies," Open Economies Review, Springer, vol. 17(4), pages 423-441, December.
- J. Paul Elhorst & Sandy Fréret, 2009. "Evidence Of Political Yardstick Competition In France Using A Two-Regime Spatial Durbin Model With Fixed Effects," Journal of Regional Science, Wiley Blackwell, vol. 49(5), pages 931-951.
- Case, Anne C, 1991. "Spatial Patterns in Household Demand," Econometrica, Econometric Society, vol. 59(4), pages 953-65, July.
- Lee, Lung-fei & Liu, Xiaodong, 2010. "Efficient Gmm Estimation Of High Order Spatial Autoregressive Models With Autoregressive Disturbances," Econometric Theory, Cambridge University Press, vol. 26(01), pages 187-230, February.
- Blommestein, Hans J. & Koper, Nick A. M., 1998. "The influence of sample size on the degree of redundancy in spatial lag operators," Journal of Econometrics, Elsevier, vol. 82(2), pages 317-333, February.
- Olivier Parent & James P. Lesage, 2010.
"A Spatial Dynamic Panel Model with Random Effects Applied to Commuting Times,"
University of Cincinnati, Economics Working Papers Series
2010-01, University of Cincinnati, Department of Economics.
- Parent, Olivier & LeSage, James P., 2010. "A spatial dynamic panel model with random effects applied to commuting times," Transportation Research Part B: Methodological, Elsevier, vol. 44(5), pages 633-645, June.
- Kelejian, Harry H & Prucha, Ingmar R, 1998. "A Generalized Spatial Two-Stage Least Squares Procedure for Estimating a Spatial Autoregressive Model with Autoregressive Disturbances," The Journal of Real Estate Finance and Economics, Springer, vol. 17(1), pages 99-121, July.
- Sandy Dall’erba & Marco Percoco & Gianfranco Piras, 2009. "Service industry and cumulative growth in the regions of Europe," Entrepreneurship & Regional Development, Taylor & Francis Journals, vol. 21(4), pages 333-349, July.
- J. Barkley Rosser, 2009. "Introduction," Chapters, in: Handbook of Research on Complexity, chapter 1 Edward Elgar.
- Beach, Charles M. & MacKinnon, James G., 1978.
"Full maximum likelihood estimation of second- order autoregressive error models,"
Journal of Econometrics,
Elsevier, vol. 7(2), pages 187-198, June.
- Charles M. Beach & James G. MacKinnon, 1977. "Full Maximum Likelihood Estimation of Second-Order Autoregressive Error Models," Working Papers 259, Queen's University, Department of Economics.
- DANIEL P. McMILLEN & LARRY D. SINGELL & GLEN R. WADDELL, 2007. "Spatial Competition And The Price Of College," Economic Inquiry, Western Economic Association International, vol. 45(4), pages 817-833, October.
- Lee, Lung-Fei, 2002. "Consistency And Efficiency Of Least Squares Estimation For Mixed Regressive, Spatial Autoregressive Models," Econometric Theory, Cambridge University Press, vol. 18(02), pages 252-277, April.
- L W Hepple, 1995. "Bayesian techniques in spatial and network econometrics: 2. Computational methods and algorithms," Environment and Planning A, Pion Ltd, London, vol. 27(4), pages 615-644, April.
- J. Elhorst, 2010. "Applied Spatial Econometrics: Raising the Bar," Spatial Economic Analysis, Taylor & Francis Journals, vol. 5(1), pages 9-28.
When requesting a correction, please mention this item's handle: RePEc:eee:regeco:v:42:y:2012:i:1:p:211-220. See general information about how to correct material in RePEc.
If references are entirely missing, you can add them using this form.