This file is part of IDEAS, which uses RePEc data


[ Papers | Articles | Software | Books | Chapters | Authors | Institutions | JEL Classification | NEP reports | Search | New papers by email | Author registration | Rankings | Volunteers | FAQ | Blog | Help! ]

Regional employment forecasts with spatial interdependencies

Author info | Abstract | Publisher info | Download info | Related research | Statistics
Author Info
Hampel, Katharina (Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany])
Kunz, Marcus (Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany])
Schanne, Norbert () (Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany])
Wapler, Rüdiger () (Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany])
Weyh, Antje () (Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany])
Abstract

"The labour-market policy-mix in Germany is increasingly being decided on a regional level. This requires additional knowledge about the regional development which (disaggregated) national forecasts cannot provide. Therefore, we separately forecast employment for the 176 German labour- market districts on a monthly basis. We first compare the prediction accuracy of standard time-series methods: autoregressive integrated moving averages (ARIMA), exponentially weighted moving averages (EWMA) and the structural-components approach (SC) in these small spatial units. Second, we augment the SC model by including autoregressive elements (SCAR) in order to incorporate the influence of former periods of the dependent variable on its current value. Due to the importance of spatial interdependencies in small labour-market units, we further augment the basic SC model by lagged values of neighbouring districts in a spatial dynamic panel (SCSAR). The prediction accuracies of the models are compared using the mean absolute percentage forecast error (MAPFE) for the simulated out-of-sample forecast for 2005. Our results show that the SCSAR is superior to the SCAR and basic SC model. ARIMA and EWMA models perform slightly better than SCSAR in many of the German labour-market districts. This reflects that these two moving-average models can better capture the trend reversal beginning in some regions at the end of 2004. All our models have a high forecast quality with an average MAPFE lower than 2.2 percent." (author's abstract, IAB-Doku) ((en))

Download Info
To download:

If you experience problems downloading a file, check if you have the proper application to view it first. Information about this may be contained in the File-Format links below. In case of further problems read the IDEAS help file. Note that these files are not on the IDEAS site. Please be patient as the files may be large.

File URL: http://doku.iab.de/discussionpapers/2007/dp0207.pdf
File Format: application/pdf
File Function:
Download Restriction: no

Publisher Info
Paper provided by Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany] in its series IAB Discussion Paper with number 200702.

Download reference. The following formats are available: HTML, plain text, BibTeX, RIS (EndNote), ReDIF
Length: 46 pages
Date of creation: 16 Jan 2007
Date of revision:
Handle: RePEc:iab:iabdpa:200702

Contact details of provider:
Postal: Regensburger Str. 104, D-90327 N�rnberg
Phone: 0911/179-0
Fax: 0911/179-3258
Email:
Web page: http://www.iab.de/
More information through EDIRC

For technical questions regarding this item, or to correct its listing, contact: (IAB, Servicebereich Dokumentation und Bibliothek).

Related research
Keywords: regionaler Arbeitsmarkt Beschäftigungsentwicklung Prognoseverfahren Arbeitsmarktprognose - Methode

Find related papers by JEL classification:
C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Other Model Applications
J21 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Labor Force and Employment, Size, and Structure
O18 - Economic Development, Technological Change, and Growth - - Economic Development - - - Regional, Urban, and Rural Analyses

This paper has been announced in the following NEP Reports:

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.:
  1. Uwe Blien, Alexandros Tassinopoulos, 2001. "Forecasting Regional Employment with the ENTROP Method," Regional Studies, Taylor and Francis Journals, vol. 35(2), pages 113-124, April. [Downloadable!] (restricted)
  2. [Reference to Proietti], Tommaso, 2000. "Comparing seasonal components for structural time series models," International Journal of Forecasting, Elsevier, vol. 16(2), pages 247-260. [Downloadable!] (restricted)
  3. Weller, Barry R., 1989. "National indicator series as quantitative predictors of small region monthly employment levels," International Journal of Forecasting, Elsevier, vol. 5(2), pages 241-247. [Downloadable!] (restricted)
  4. Partridge, Mark D & Rickman, Dan S, 1998. "Generalizing the Bayesian Vector Autoregression Approach for Regional Interindustry Employment Forecasting," Journal of Business & Economic Statistics, American Statistical Association, vol. 16(1), pages 62-72, January.
  5. Jan G. De Gooijer & Rob J. Hyndman, 2005. "25 Years of IIF Time Series Forecasting: A Selective Review," Monash Econometrics and Business Statistics Working Papers 12/05, Monash University, Department of Econometrics and Business Statistics. [Downloadable!]
    Other versions:
  6. Graham R. Schindler, Philip R. Israilevich, Geoffrey J. D. Hewings, 1997. "Regional Economic Performance: An Integrated Approach," Regional Studies, Taylor and Francis Journals, vol. 31(2), pages 131-137, April. [Downloadable!] (restricted)
  7. Giuseppe Arbia & Marco Bee & Giuseppe Espa, 2007. "Aggregation of regional economic time series with different spatial correlation structures," Department of Economics Working Papers 0720, Department of Economics, University of Trento, Italia. [Downloadable!]
  8. Roberto Patuelli & Aura Reggiani & Peter Nijkamp & Uwe Blien, 2006. "New Neural Network Methods for Forecasting Regional Employment: An Analysis of German Labour Markets," Tinbergen Institute Discussion Papers 06-020/3, Tinbergen Institute. [Downloadable!]
    Other versions:
  9. Edlund, Per-Olov & Karlsson, Sune, 1993. "Forecasting the Swedish unemployment rate VAR vs. transfer function modelling," International Journal of Forecasting, Elsevier, vol. 9(1), pages 61-76, April. [Downloadable!] (restricted)
  10. Michael Beenstock & Daniel Felsenstein, 2007. "Spatial Vector Autoregressions," Spatial Economic Analysis, Taylor and Francis Journals, vol. 2(2), pages 167-196. [Downloadable!] (restricted)
  11. Klaus, Joachim & Maußner, Alfred, 1988. "Regionale Arbeitsmarktanalysen mittels vergleichender Arbeitsmarktbilanzen," Mitteilungen aus der Arbeitsmarkt- und Berufsforschung, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany], vol. 21(1), pages 74-83. [Downloadable!]
  12. Inoue, Atsushi & Kilian, Lutz, 2006. "On the selection of forecasting models," Journal of Econometrics, Elsevier, vol. 127(2), pages 273-306, February. [Downloadable!] (restricted)
    Other versions:
  13. Swanson, Norman R. & White, Halbert, 1997. "Forecasting economic time series using flexible versus fixed specification and linear versus nonlinear econometric models," International Journal of Forecasting, Elsevier, vol. 13(4), pages 439-461, December. [Downloadable!] (restricted)
  14. Giacomini, Raffaella & Granger, Clive W. J., 2004. "Aggregation of space-time processes," Journal of Econometrics, Elsevier, vol. 118(1-2), pages 7-26. [Downloadable!] (restricted)
    Other versions:
  15. James H. Stock & Mark W. Watson, 1998. "A Comparison of Linear and Nonlinear Univariate Models for Forecasting Macroeconomic Time Series," NBER Working Papers 6607, National Bureau of Economic Research, Inc. [Downloadable!] (restricted)
Full references

Cited by:
(explanations, 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.)

  1. Eckey, Hans-Friedrich & Schwengler, Barbara & Türck, Matthias, 2007. "Vergleich von deutschen Arbeitsmarktregionen," IAB Discussion Paper 200703, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany]. [Downloadable!]
  2. Hohendanner, Christian, 2007. "Verdrängen Ein-Euro-Jobs sozialversicherungspflichtige Beschäftigung in den Betrieben?," IAB Discussion Paper 200708, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany]. [Downloadable!]
Statistics
Access and download statistics

Did you know? You too can volunteer for RePEc, for example by editing a NEP report.

This page was last updated on 2008-7-5.

This information is provided to you by IDEAS at the Department of Economics, College of Liberal Arts and Sciences, University of Connecticut using RePEc data on a server sponsored by the Society for Economic Dynamics.