Forecasting the sectoral GVA of a small Spanish region
DOI:
https://doi.org/10.17811/ebl.5.2.2016.38-44Abstract
Our main goal in this paper is to evaluate the point forecasting accuracy of several time series econometric models when applied to a small Spanish region. The variable of interest is the sectoral GVA of the Basque Country. The results support the use of univariate models, such as ARMA and SETAR, which outperform the causal model in forecasting accuracy. The use of a causal model, such as the Transfer Function model, does not offer a systematic advantage, even if it makes use of the regional statistical information available for the Basque Country.
References
B. Baltagi, B. Fingleton, and A. Pirotte. Estimating and forecasting with a dynamic spatial panel data model. Oxford Bulletin of Economics and Statistics, 76(1):112–138, 2014.
G. Box and G. Jenkins. Time Series Analysis: Forecasting and Control. Holden-Day, New York, 1976.
L. Ferrara, M. Marcellino, and M. Mogliani. Macroeconomic forecasting during the Great Recession: The return of non-linearity? Working papers 383, Banque de France, May 2012.
T. Fullerton and T. West. Assessing the Historical Accuracy of Regional Economic Forecasts. Journal Of Forecasting, 15(1):19–36, 1996.
T. Fullerton, M. Laaksonen, and T. West. Regional multi-family housing start forecast accuracy. International Journal of Forecasting, 17(2):171–180, 2001.
C. Granger and T. Terasvirta. Modelling Nonlinear Economic relationships. Oxford
University Press, Oxford, 1993.
D. Jones, M. Manning, and M. Stevenson. The Unemployment Rate and the Business Cycle in Britain: An Aggregate and Regional Analysis. Regional Studies, 28: 591–604., 1994.
A. Kopoin, K. Moran, and J.-P. Par´e. Forecasting Regional GDP with Factor Mod- els: How Useful are National and International Data? Economics Letters, 121(2):
– 270, 2013.
R. Lehmann and K. Wohlrabe. Forecasting GDP at the Regional Level with Many
Predictors. German Economic Review, 2013.
R. Lehmann and K. Wohlrabe. Regional economic forecasting: state-of-the-art methodology and future challenges. Economics and Business Letters, 3(4):218–
, 2014.
R. Luukkonen and T. Terasvirta. Testing linearity of economic time series against cyclical asymmetry. Annales de l’economic et de statistique, 20/21:125–142, 1991.
M. Mayor, A. Lopez, and R. P´erez. Forecasting regional employment with shiftshare and arima modelling. Regional Studies, 41:543–551, 2007.
R. Patuelli and M. Mayor. Introduction to the Special Issue: Advances in Regional
Forecasting. Economics and Business Letters, 3(4):191–193, 2014.
T. Terasvirta, D. van Dijk, and M. Medeiros. Linear models, smooth transition autoregressions, and neural networks for forecasting macroeconomic time series: A re-examination. International Journal of Forecasting, 21:755–774, 2005.
T. Terasvirta, D. Tjostheim, and C. W. J. Granger. Modelling Nonlinear Economic
Time Series. Oxford University Press, 2010.
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