Regional economic forecasting: state-of-the-art methodology and future challenges
DOI:
https://doi.org/10.17811/ebl.3.4.2014.218-231Abstract
Over the last decade, the topic of regional economic forecasting has become increasingly prevalent in academic literature. The most striking problem in this context is data availability at a regional level. However, considerable methodological improvements have been made to address this problem. This paper summarises a multitude of articles from academic journals and describes state-of-the-art techniques in regional economic forecasting. After identifying current practices, the article closes with a roadmap for possible future research activities.
References
Baltagi, B.H., Fingleton, B. and Pirotte, A. (2014) Estimating and Forecasting with a Dynamic Spatial Panel Data Model, Oxford Bulletin of Economics and Statistics, 76(1), 112-138.
Bandholz, H. and Funke, M. (2003) Die Konstruktion und Schätzung eines Konjunkturfrühindikators für Hamburg, Wirtschaftsdienst, 83(8), 540-548.
Blien, U. and Tassinopoulos, A. (2001) Forecasting Regional Employment with the ENTROP Method, Regional Studies, 32(2), 113-124.
Chow, G.C. and Lin, A. (1971) Best linear unbiased interpolation, distribution and exploration of time series by related series, The Review of Economics and Statistics, 53(4), 372-375.
Coomes, P.A. (1992) A Kalman filter formulation for noisy regional job data, International Journal of Forecasting, 7(4), 473-481.
Dreger, C. and Kholodilin, K.A. (2007) Prognosen der regionalen Wirtschaftsentwicklung, Vierteljahreshefte zur Wirtschaftsforschung, 76(4), 47-55.
Dua, P. and Miller, S.M. (1996) Forecasting and Analyzing Economic Activity with Coincident and Leading Indexes: The Case of Connecticut, Journal of Forecasting, 15(7), 509-526.
Girardin, E. and Kholodilin, K.A. (2011) How Helpful are Spatial Effects in Forecasting the Growth of Chinese Provinces? Journal of Forecasting, 30(7), 622-643.
Glennon, D., Lane, J. and Johnson, S. (1987) Regional econometric models that reflect labor market relations, International Journal of Forecasting, 3(2), 299-312.
Holmes, R.A. and Shamsuddin, A.F.M. (1993) Evaluation of alternative leading indicators of British Columbia industrial employment, International Journal of Forecasting, 9(1), 77-83.
Kholodilin, K.A., Kooths, S. and Siliverstovs, B. (2008) A Dynamic Panel Data Approach to the Forecasting of the GDP of German Länder, Spatial Economic Analysis, 3(2), 195-207.
Kopoin, A., Moran, K. and Paré, J.P. (2013) Forecasting regional GDP with factor models: How useful are national and international data? Economics Letters, 121(2), 267-270.
Lehmann, R. and Wohlrabe, K. (2014a) Forecasting gross value-added at the regional level: Are sectoral disaggregated predictions superior to direct ones? Review of Regional Research: Jahrbuch für Regionalwissenschaft, 34(1), 61-90.
Lehmann, R. and Wohlrabe, K. (2014b) Forecasting GDP at the regional level with many predictors, German Economic Review, forthcoming.
LeSage, J.P. (1990) Forecasting metropolitan employment using an export-base error-correction model, Journal of Regional Science, 30(3), 307-323.
Longhi, S. and Nijkamp, P. (2007) Forecasting Regional Labor Market Developments under Spatial Autocorrelation, International Regional Science Review, 30(2), 100-119.
Longhi, S., Nijkamp, P., Reggiani, A. and Maierhofer, E. (2005) Neural Network Modeling as a Tool for Forecasting Regional Employment Patterns, International Regional Science Review, 28(3), 330-346.
Mayor, M. and Patuelli, R. (2012) Short-Run Regional Forecasts: Spatial Models through Varying Cross-Sectional and Temporal Dimensions. In Vázquez, E.F. and Morollón, F.R. (Eds): Defining the Spatial Scale in Modern Regional Analysis: New Challenges from Data at the Local Level. Springer-Verlag Berlin Heidelberg, Chapter 9, 173-192.
Mayor, M., López, A.J. and Pérez, R. (2007) Forecasting Regional Employment with Shift-Share and ARIMA Modelling, Regional Studies, 41(4), 543-551.
Megna, R. and Xu, Q. (2003) Forecasting the New York State Economy: The coincident and leading indicators approach, International Journal of Forecasting, 19(4), 701-713.
Miller, J.R. (1998) Spatial aggregation and regional economic forecasting, The Annals of Regional Science, 32(2), 253-266.
Patuelli, R., Longhi, S., Nijkamp, P., Reggiani, A. and Blien, U. (2007) A Rank-Order Test on the Statistical Performance of Neural Network Models for Regional Labor Market Forecasts, The Review of Regional Studies, 37(1), 64-81.
Patuelli, R., Longhi, S., Nijkamp, P. and Reggiani, A. (2008) Neural networks and genetic algorithms as forecasting tools: a case study on German regions, Environment and Planning B: Planning and Design, 35(4), 701-722.
Polasek, W., Sellner, R. and Schwarzbauer, W. (2007) Long term regional forecasting with spatial equation systems, RCEA Working Paper series WP 10-07. Rimini, RN.
Puri, A. and Soydemir, G. (2000) Forecasting industrial employment figures in Southern California: A Bayesian vector autoregressive model, The Annals of Regional Science, 34(4), 503-514.
Rapach, D.E. and Strauss, J.K. (2005) Forecasting Employment Growth in Missouri with Many Potentially Relevant Predictors: An Analysis of Forecast Combining Methods, Federal Reserve Bank of St. Louis: Regional Economic Development, 1(1), 97-112.
Rapach, D.E. and Strauss, J.K. (2012) Forecasting US state-level employment growth: An amalgamation approach, International Journal of Forecasting, 28(2), 315-327.
Schanne, N., Wappler, R. and Weyh, A. (2010) Regional unemployment forecasts with spatial interdependencies, International Journal of Forecasting, 26(4), 908-926.
Shoesmith, G.L. (2000) The Time-Series Relatedness of State and National Indexes of Leading Indicators and Implications for Regional Forecasting, International Regional Science Review, 23(3), 281-299.
Thirlwall, A.P. (1975) Forecasting regional unemployment in Great Britain, Regional Science and Urban Economics, 5(3), 357-374.
Trívez, F.J. and Mur, J. (1999) A short-term forecasting model for sectoral regional employment, The Annals of Regional Science, 33(1), 69-91.
Weller, B.R. (1989) National indicator series as quantitative predictors of small region monthly employment levels, International Journal of Forecasting, 5(2), 241-247.
Weller, B.R. and Kurre, J.A. (1987) Applicability of the transfer function approach to forecasting employment levels in small regions, The Annals of Regional Science, 21(1), 34-43.
Weller, B.R. and Kurre, J.A. (1989) Forecasting the local economy, using time-series and shift-share techniques, Environment and Planning A, 21(6), 753-770.
Wenzel, L. (2013) Forecasting Regional Growth in Germany: A panel approach using Business Survey Data, HWWI Research Paper 133. Hamburg, DE.
Wenzel, L. and Wolf, A. (2013) Short-term Forecasting with Business Surveys: Evidence for German IHK Data at Federal State Level, HWWI Research Paper 140. Hamburg, DE.
West, C.T. and Fullerton, T.M. (1996) Assessing the Historical Accuracy of Regional Economic Forecasts, Journal of Forecasting, 15(1), 19-36.
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