Forecasting with spatial panel data
Various forecasts using panel data with spatial error correlation are compared using Monte Carlo experiments. The true data generating process is assumed to be a simple error component regression model with spatial remainder disturbances of the autoregressive or moving average type. The best linear unbiased predictor is compared with other forecasts ignoring spatial correlation, or ignoring heterogeneity due to the individual effects. In addition, the root mean squared error performance of these forecasts is examined under misspecification of the spatial error process, various spatial weight matrices, and heterogeneous rather than homogeneous panel data models.
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Volume (Year): 56 (2012)
Issue (Month): 11 ()
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- Rapach, David E. & Wohar, Mark E., 2004. "Testing the monetary model of exchange rate determination: a closer look at panels," Journal of International Money and Finance, Elsevier, vol. 23(6), pages 867-895, October.
- Herbert Brücker & Boriss Siliverstovs, 2006.
"On the estimation and forecasting of international migration: how relevant is heterogeneity across countries?,"
Springer, vol. 31(3), pages 735-754, September.
- Brücker, Herbert & Siliverstovs, Boriss, 2005. "On the Estimation and Forecasting of International Migration: How Relevant Is Heterogeneity Across Countries?," IZA Discussion Papers 1710, Institute for the Study of Labor (IZA).
- Harry H. Kelejian & Ingmar R. Prucha, 1995.
"A Generalized Moments Estimator for the Autoregressive Parameter in a Spatial Model,"
Electronic Working Papers
95-001, University of Maryland, Department of Economics, revised Mar 1997.
- 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 509-533, May.
- Baltagi B-H & Bresson G. & Pirotte A., 2005.
"Panel Unit Root Tests and Spatial Dependence,"
Working Papers ERMES
0503, ERMES, University Paris 2.
- Badi H. Baltagi & Georges Bresson & Alain Pirotte, 2004. "Tobin q: Forecast performance for hierarchical Bayes, shrinkage, heterogeneous and homogeneous panel data estimators," Empirical Economics, Springer, vol. 29(1), pages 107-113, January.
- Badi H. Baltagi & Dong Li, 2006.
"Prediction in the Panel Data Model with Spatial Correlation: The Case of Liquor,"
Center for Policy Research Working Papers
84, Center for Policy Research, Maxwell School, Syracuse University.
- Badi Baltagi & Dong Li, 2006. "Prediction in the Panel Data Model with Spatial Correlation: the Case of Liquor," Spatial Economic Analysis, Taylor & Francis Journals, vol. 1(2), pages 175-185.
- Baltagi, Badi H. & Griffin, James M., 1997. "Pooled estimators vs. their heterogeneous counterparts in the context of dynamic demand for gasoline," Journal of Econometrics, Elsevier, vol. 77(2), pages 303-327, April.
- Bernard Fingleton, 2008. "A generalized method of moments estimator for a spatial model with moving average errors, with application to real estate prices," Empirical Economics, Springer, vol. 34(1), pages 35-57, February.
- Frees, Edward W. & Miller, Thomas W., 2004. "Sales forecasting using longitudinal data models," International Journal of Forecasting, Elsevier, vol. 20(1), pages 99-114.
- Baillie, R.T. & Baltagi, B.H., 1994. "Prediction from the Regression Model with one-way Error Components," Papers 9405, Michigan State - Econometrics and Economic Theory.
- Bernard Fingleton, 2008. "A Generalized Method of Moments Estimator for a Spatial Panel Model with an Endogenous Spatial Lag and Spatial Moving Average Errors," Spatial Economic Analysis, Taylor & Francis Journals, vol. 3(1), pages 27-44.
- Badi H. Baltagi, 2008.
"Forecasting with panel data,"
Journal of Forecasting,
John Wiley & Sons, Ltd., vol. 27(2), pages 153-173.
- Badi H. Baltagi, 2007. "Forecasting with Panel Data," Center for Policy Research Working Papers 91, Center for Policy Research, Maxwell School, Syracuse University.
- Baltagi, Badi H., 2006. "Forecasting with panel data," Discussion Paper Series 1: Economic Studies 2006,25, Deutsche Bundesbank, Research Centre.
- Taub, Allan J., 1979. "Prediction in the context of the variance-components model," Journal of Econometrics, Elsevier, vol. 10(1), pages 103-107, April.
- Badi H. Baltagi & James M. Griffin & Weiwen Xiong, 2000. "To Pool Or Not To Pool: Homogeneous Versus Hetergeneous Estimations Applied to Cigarette Demand," The Review of Economics and Statistics, MIT Press, vol. 82(1), pages 117-126, February.
- Kajal Lahiri, 2005. "Analysis of Panel Data," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 87(4), pages 1093-1095.
- Richard Schmalensee & Thomas M. Stoker & Ruth A. Judson, 1998. "World Carbon Dioxide Emissions: 1950-2050," The Review of Economics and Statistics, MIT Press, vol. 80(1), pages 15-27, February.
- Anselin, Luc & Moreno, Rosina, 2003.
"Properties of tests for spatial error components,"
Regional Science and Urban Economics,
Elsevier, vol. 33(5), pages 595-618, September.
- Baltagi, Badi H. & Bresson, Georges & Pirotte, Alain, 2002. "Comparison of forecast performance for homogeneous, heterogeneous and shrinkage estimators: Some empirical evidence from US electricity and natural-gas consumption," Economics Letters, Elsevier, vol. 76(3), pages 375-382, August.
- Kapoor, Mudit & Kelejian, Harry H. & Prucha, Ingmar R., 2007. "Panel data models with spatially correlated error components," Journal of Econometrics, Elsevier, vol. 140(1), pages 97-130, September.
- Pesaran, M. Hashem & Smith, Ron, 1995.
"Estimating long-run relationships from dynamic heterogeneous panels,"
Journal of Econometrics,
Elsevier, vol. 68(1), pages 79-113, July.
- Pesaran, M.H. & Smith, R., 1992. "Estimating Long-Run Relationships From Dynamic Heterogeneous Panels," Cambridge Working Papers in Economics 9215, Faculty of Economics, University of Cambridge.
- Hoogstrate, Andre J & Palm, Franz C & Pfann, Gerard A, 2000. "Pooling in Dynamic Panel-Data Models: An Application to Forecasting GDP Growth Rates," Journal of Business & Economic Statistics, American Statistical Association, vol. 18(3), pages 274-283, July.
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