Forecasting Regional Labour Markets with GVAR Models and Indicators (refereed paper)
AbstractThe development of employment and unemployment in regional labour markets is known to spatially interdependent. Global Vector-Autoregressive (GVAR) models generate a link between the local and the surrounding labour markets and thus might be useful when analysing and forecasting employment and unemployment even if they are non-stationary or co-trending. Furthermore, GVARs have the advantage to allow for both strong cross-sectional dependence on ``leader regions' and weak cross-sectional, spatial dependence. For the recent and further development of labour markets the economic situation (described e.g. by business-cycle indicators), politics and environmental impacts (e.g. climate) may be relevant. Information on these impacts can be integrated in addition to the joint development of employment and unemployment and the spatial link in a way that allows on the one hand to carry out economic plausibility checks easily and on the other hand to directly receive measures regarding the statistical properties and the precision of the forecasts. Then, the forecasting accuracy is demonstrated for German regional labour-market data in simulated forecasts at different horizons and for several periods. Business-cycle indicators seem to have no information regarding labour-market prediction, climate indicators little. In contrast, including information about labour-market policies and vacancies, and accounting for the lagged and contemporaneous spatial dependence can improve the forecasts relative to a simple bivariate model.
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Bibliographic InfoPaper provided by European Regional Science Association in its series ERSA conference papers with number ersa10p1044.
Date of creation: Sep 2011
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This paper has been announced in the following NEP Reports:
- NEP-ALL-2012-07-29 (All new papers)
- NEP-FOR-2012-07-29 (Forecasting)
- NEP-GEO-2012-07-29 (Economic Geography)
- NEP-LAB-2012-07-29 (Labour Economics)
- NEP-URE-2012-07-29 (Urban & Real Estate Economics)
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- Pesaran, M.H. & Weiner, S.M., 2001.
"Modelling Regional Interdependencies Using a Global Error-Correcting Macroeconometric Model,"
Cambridge Working Papers in Economics
0119, Faculty of Economics, University of Cambridge.
- Pesaran M.H. & Schuermann T. & Weiner S.M., 2004. "Modeling Regional Interdependencies Using a Global Error-Correcting Macroeconometric Model," Journal of Business & Economic Statistics, American Statistical Association, vol. 22, pages 129-162, April.
- 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.
- M. Hashem Pesaran & Til Schuermann & Scott M. Weiner, 2001. "Modelling regional interdependencies using a global error-correcting macroeconometric model," 10th International Conference on Panel Data, Berlin, July 5-6, 2002 B4-1, International Conferences on Panel Data.
- Hampel, Katharina & Kunz, Marcus & Schanne, Norbert & Wapler, Rüdiger & Weyh, Antje, 2007.
"Regional employment forecasts with spatial interdependencies,"
IAB Discussion Paper
200702, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany].
- Schanne, N. & Wapler, R. & Weyh, A., 2010. "Regional unemployment forecasts with spatial interdependencies," International Journal of Forecasting, Elsevier, vol. 26(4), pages 908-926, October.
- Schanne, Norbert & Wapler, Rüdiger & Weyh, Antje, 2008. "Regional unemployment forecasts with spatial interdependencies," IAB Discussion Paper 200828, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany].
- Joseph Beaulieu, J. & Miron, Jeffrey A., 1993.
"Seasonal unit roots in aggregate U.S. data,"
Journal of Econometrics,
Elsevier, vol. 55(1-2), pages 305-328.
- Eleonora Patacchini & Yves Zenou, 2007. "Spatial dependence in local unemployment rates," Journal of Economic Geography, Oxford University Press, vol. 7(2), pages 169-191, March.
- Pierre Cahuc & AndrÃ© Zylberberg, 2004. "Labor Economics," MIT Press Books, The MIT Press, edition 1, volume 1, number 026203316x, December.
- Schanne, Norbert, 2012. "The formation of experts' expectations on labour markets : do they run with the pack?," IAB Discussion Paper 201225, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany].
- Alexander Chudik & M. Hashem Pesaran, 2014.
"Theory and Practice of GVAR Modeling,"
CESifo Working Paper Series
4807, CESifo Group Munich.
- Chudik, Alexander & Pesaran, M. Hashem, 2014. "Theory and practice of GVAR modeling," Globalization and Monetary Policy Institute Working Paper 180, Federal Reserve Bank of Dallas.
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