IDEAS home Printed from
MyIDEAS: Log in (now much improved!) to save this paper

Forecasting with panel data

  • Baltagi, Badi H.

This paper gives a brief survey of forecasting with panel data. Starting with a simple error component regression and surveying best linear unbiased prediction under various assumptions of the disturbance term. This includes various ARMA models as well as spatial autoregressive models. The paper also surveys how these forecasts have been used in panal data applications, running horse races between heterogeneous and homogeneous panel data models using out of sample forecasts.

If you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.

File URL:
Download Restriction: no

Paper provided by Deutsche Bundesbank, Research Centre in its series Discussion Paper Series 1: Economic Studies with number 2006,25.

in new window

Date of creation: 2006
Date of revision:
Handle: RePEc:zbw:bubdp1:4754
Contact details of provider: Postal:
Postfach 10 06 02, 60006 Frankfurt

Phone: 0 69 / 95 66 - 34 55
Fax: 0 69 / 95 66 30 77
Web page:

More information through EDIRC

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.:

as in new window
  1. Kajal Lahiri, 2005. "Analysis of Panel Data," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 87(4), pages 1093-1095.
  2. Karlsson, Sune & Skoglund, Jimmy, 2000. "Maximum-likelihood based inference in the two-way random effects model with serially correlated time effects," SSE/EFI Working Paper Series in Economics and Finance 383, Stockholm School of Economics.
  3. Fok, Dennis & van Dijk, Dick & Franses, Philip Hans, 2005. "Forecasting aggregates using panels of nonlinear time series," International Journal of Forecasting, Elsevier, vol. 21(4), pages 785-794.
  4. 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.
  5. Falko Fecht & Kevin X. D. Huang & Antoine Martin, 2008. "Financial Intermediaries, Markets, and Growth," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 40(4), pages 701-720, 06.
  6. Gary Koop & Simon M. Potter, 2003. "Forecasting in large macroeconomic panels using Bayesian Model Averaging," Staff Reports 163, Federal Reserve Bank of New York.
  7. Maddala, G S, et al, 1997. "Estimation of Short-Run and Long-Run Elasticities of Energy Demand from Panel Data Using Shrinkage Estimators," Journal of Business & Economic Statistics, American Statistical Association, vol. 15(1), pages 90-100, January.
  8. Zellner, A. & Hong, C., 1988. "Forecasting International Growth Rates Using Bayesian Shrinkage And Other Procedures," Papers m8802, Southern California - Department of Economics.
  9. Kajal Lahiri & Fushang Liu, 2006. "Modeling Multi-Period Inflation Uncertainty Using a Panel of Density Forcasts," Discussion Papers 06-05, University at Albany, SUNY, Department of Economics.
  10. Fuller, Wayne A. & Battese, George E., 1974. "Estimation of linear models with crossed-error structure," Journal of Econometrics, Elsevier, vol. 2(1), pages 67-78, May.
  11. MaCurdy, Thomas E., 1982. "The use of time series processes to model the error structure of earnings in a longitudinal data analysis," Journal of Econometrics, Elsevier, vol. 18(1), pages 83-114, January.
  12. Erik Hjalmarsson, 2006. "Predictive regressions with panel data," International Finance Discussion Papers 869, Board of Governors of the Federal Reserve System (U.S.).
  13. M. Hashem Pesaran & Til Schuermann & Scott M. Weiner, 2002. "Modeling Regional Interdependencies Using a Global Error-Correcting Macroeconometric Model," Center for Financial Institutions Working Papers 01-38, Wharton School Center for Financial Institutions, University of Pennsylvania.
  14. Binder, Michael & Hsiao, Cheng & Pesaran, M. Hashem, 2005. "Estimation And Inference In Short Panel Vector Autoregressions With Unit Roots And Cointegration," Econometric Theory, Cambridge University Press, vol. 21(04), pages 795-837, August.
  15. Francis X. Diebold & Jose A. Lopez, 1995. "Forecast evaluation and combination," Research Paper 9525, Federal Reserve Bank of New York.
  16. Ziemer, Rod F. & Wetzstein, Michael E., 1983. "A Stein-rule method for pooling data," Economics Letters, Elsevier, vol. 11(1-2), pages 137-143.
  17. Nandram, Balgobin & Petruccelli, Joseph D, 1997. "A Bayesian Analysis of Autoregressive Time Series Panel Data," Journal of Business & Economic Statistics, American Statistical Association, vol. 15(3), pages 328-34, July.
  18. Hendry, David F & Hubrich, Kirstin, 2006. "Forecasting Economic Aggregates by Disaggregates," CEPR Discussion Papers 5485, C.E.P.R. Discussion Papers.
  19. Marcellino, Massimiliano & Stock, James H. & Watson, Mark W., 2003. "Macroeconomic forecasting in the Euro area: Country specific versus area-wide information," European Economic Review, Elsevier, vol. 47(1), pages 1-18, February.
  20. Giacomini, Raffaella & Granger, Clive W.J., 2001. "Aggregationn of Space-Time Processes," University of California at San Diego, Economics Working Paper Series qt77f76455, Department of Economics, UC San Diego.
  21. Campbell, John Y. & Hilscher, Jens & Szilagyi, Jan, 2005. "In search of distress risk," Discussion Paper Series 1: Economic Studies 2005,27, Deutsche Bundesbank, Research Centre.
  22. Koetter, M. & Bos, J.W.B. & Heid, F. & Kolari, J.W. & Kool, C.J.M. & Porath, D., 2007. "Accounting for distress in bank mergers," Journal of Banking & Finance, Elsevier, vol. 31(10), pages 3200-3217, October.
  23. Donald Robertson & James Symons, 1991. "Some Strange Properties of Panel Data Estimators," CEP Discussion Papers dp0044, Centre for Economic Performance, LSE.
  24. Swamy, P A V B, 1970. "Efficient Inference in a Random Coefficient Regression Model," Econometrica, Econometric Society, vol. 38(2), pages 311-23, March.
  25. Boozer, Michael A., 1997. "Econometric Analysis of Panel Data Badi H. Baltagi Wiley, 1995," Econometric Theory, Cambridge University Press, vol. 13(05), pages 747-754, October.
  26. Francis X. Diebold & Robert S. Mariano, 1994. "Comparing Predictive Accuracy," NBER Technical Working Papers 0169, National Bureau of Economic Research, Inc.
  27. Baltagi, Badi H. & Liu, Long, 2012. "The Hausman–Taylor panel data model with serial correlation," Statistics & Probability Letters, Elsevier, vol. 82(7), pages 1401-1406.
  28. William T. Gavin & Athena T. Theodorou, 2005. "A common model approach to macroeconomics: using panel data to reduce sampling error," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 24(3), pages 203-219.
  29. 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.
  30. Ciaran Driver & Katsushi Imai & Paul Temple & Giovanni Urga, 2004. "The effect of uncertainty on UK investment authorisation: Homogenous vs. heterogeneous estimators," Empirical Economics, Springer, vol. 29(1), pages 115-128, January.
  31. Frees, Edward W. & Young, Virginia R. & Luo, Yu, 1999. "A longitudinal data analysis interpretation of credibility models," Insurance: Mathematics and Economics, Elsevier, vol. 24(3), pages 229-247, May.
  32. Frees, Edward W. & Miller, Thomas W., 2004. "Sales forecasting using longitudinal data models," International Journal of Forecasting, Elsevier, vol. 20(1), pages 99-114.
  33. repec:cup:etheor:v:10:y:1994:i:2:p:396-408 is not listed on IDEAS
  34. Nelson Mark & Donggyu Sul, 1998. "Norminal Exchange Rates and Monetary Fundamentals: Evidence from a Small Post-Bretton Woods Panel," Working Papers 98-19, Ohio State University, Department of Economics.
  35. Galbraith, John W. & Zinde-Walsh, Victoria, 1995. "Transforming the error-components model for estimation with general ARMA disturbances," Journal of Econometrics, Elsevier, vol. 66(1-2), pages 349-355.
  36. MOUCHART, Michel & ROMBOUTS, Jeroen, 2003. "Clustered panel data models: an efficient approach for nowcasting from poor data," CORE Discussion Papers 2003090, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
  37. 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.
  38. Baltagi, Badi H. & Wu, Ping X., 1999. "Unequally Spaced Panel Data Regressions With Ar(1) Disturbances," Econometric Theory, Cambridge University Press, vol. 15(06), pages 814-823, December.
  39. 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.
  40. Groen, Jan J J, 2005. "Exchange Rate Predictability and Monetary Fundamentals in a Small Multi-country Panel," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 37(3), pages 495-516, June.
  41. Badi H. Baltagi & Georges Bresson & James M. Griffin & Alain Pirotte, 2003. "Homogeneous, heterogeneous or shrinkage estimators? Some empirical evidence from French regional gasoline consumption," Empirical Economics, Springer, vol. 28(4), pages 795-811, November.
  42. Mark W. Watson & James H. Stock, 2004. "Combination forecasts of output growth in a seven-country data set," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 23(6), pages 405-430.
  43. 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 274-83, July.
  44. 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.
  45. Hsiao, C. & Pesaran, M. H. & Tahmiscioglu, A. K., 1998. "Bayes Estimation of Short-run Coefficients in Dynamic Panel Data Models," Cambridge Working Papers in Economics 9804, Faculty of Economics, University of Cambridge.
  46. 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.
  47. von Kalckreuth, Ulf, 2005. "A "wreckers theory" of financial distress," Discussion Paper Series 1: Economic Studies 2005,40, Deutsche Bundesbank, Research Centre.
  48. Baltagi, Badi H. & Li, Qi, 1994. "Estimating Error Component Models With General MA(q) Disturbances," Econometric Theory, Cambridge University Press, vol. 10(02), pages 396-408, June.
  49. Keane, Michael P & Runkle, David E, 1990. "Testing the Rationality of Price Forecasts: New Evidence from Panel Data," American Economic Review, American Economic Association, vol. 80(4), pages 714-35, September.
  50. Taub, Allan J., 1979. "Prediction in the context of the variance-components model," Journal of Econometrics, Elsevier, vol. 10(1), pages 103-107, April.
  51. Battese, George E. & Coelli, Tim J., 1988. "Prediction of firm-level technical efficiencies with a generalized frontier production function and panel data," Journal of Econometrics, Elsevier, vol. 38(3), pages 387-399, July.
  52. 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.
  53. Garcia-Ferrer, Antonio, et al, 1987. "Macroeconomic Forecasting Using Pooled International Data," Journal of Business & Economic Statistics, American Statistical Association, vol. 5(1), pages 53-67, January.
  54. 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).
  55. Pesaran, H. & Smith, R. & Im, K.S., 1995. "Dynamic Linear Models for Heterogeneous Panels," Cambridge Working Papers in Economics 9503, Faculty of Economics, University of Cambridge.
  56. Zellner, Arnold & Hong, Chansik & Min, Chung-ki, 1991. "Forecasting turning points in international output growth rates using Bayesian exponentially weighted autoregression, time-varying parameter, and pooling techniques," Journal of Econometrics, Elsevier, vol. 49(1-2), pages 275-304.
Full references (including those not matched with items on IDEAS)

This item is not listed on Wikipedia, on a reading list or among the top items on IDEAS.

When requesting a correction, please mention this item's handle: RePEc:zbw:bubdp1:4754. See general information about how to correct material in RePEc.

For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (ZBW - German National Library of Economics)

If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

If references are entirely missing, you can add them using this form.

If the full references list an item that is present in RePEc, but the system did not link to it, you can help with this form.

If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your profile, as there may be some citations waiting for confirmation.

Please note that corrections may take a couple of weeks to filter through the various RePEc services.

This information is provided to you by IDEAS at the Research Division of the Federal Reserve Bank of St. Louis using RePEc data.