Bruno, Giancarlo and Lupi, Claudio (2003): Forecasting Euro-Area Industrial Production Using (Mostly) Business Surveys Data.
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In this paper we propose a relatively simple procedure to predict Euro-zone industrial production using mostly data derived from the business surveys of the three major economies within the European Monetary Union (France, Germany, and Italy). The basic idea is that of estimating business cyclical indicators to be used as predictors for the industrial production in France and Germany; as far as Italy is concerned, forecasts are produced using a model that in the recent past proved to be able to produce accurate forecasts up to six months ahead. In order to derive quantitative predictors from the business surveys data and to aggregate the nation-wide forecast into the Euro-zone forecast, we propose using an approach based on dynamic factors and unobserved components models. The resulting forecasts are accurate up to six steps ahead.
|Item Type:||MPRA Paper|
|Original Title:||Forecasting Euro-Area Industrial Production Using (Mostly) Business Surveys Data|
|Keywords:||Forecasting; VAR models; Industrial production; Cyclical Analysis|
|Subjects:||C - Mathematical and Quantitative Methods > C3 - Multiple or Simultaneous Equation Models ; Multiple Variables > C32 - Time-Series Models ; Dynamic Quantile Regressions ; Dynamic Treatment Effect Models ; Diffusion Processes ; State Space Models
E - Macroeconomics and Monetary Economics > E3 - Prices, Business Fluctuations, and Cycles > E32 - Business Fluctuations ; Cycles
C - Mathematical and Quantitative Methods > C5 - Econometric Modeling > C53 - Forecasting and Prediction Methods ; Simulation Methods
|Depositing User:||Giancarlo Bruno|
|Date Deposited:||01. Nov 2012 05:38|
|Last Modified:||29. Mar 2015 11:17|
Baffigi, A., Golinelli, R. & Parigi, G. (2002). Real-time GDP forecasting in the Euro area, Bank of Italy, mimeo.
Ballabriga, F.C. & Castillo, S. (2000). BBVA-ARIES: a forecasting and sim- ulation model for the EMU economy, mimeo.
Batchelor, R.A. (1981). Aggregate expectations under the stable laws, Journal of Econometrics, 2, 199-210.
Batchelor, R.A. (1986). Qualitative vs quantitative measures of inflation ex- pectations, Oxford Bulletin of Economics and Statistics, 2, 99-120.
Bergstr ̈m, R. (1995). The relationship between manufacturing production o and different business survey series in Sweden 1968–1992, International Journal of Forecasting, 11, 379-393.
Bodo, G., Golinelli, R. & Parigi, G. (2000). Forecasting industrial production in the Euro area, Empirical Economics, 25, 541-561.
Buffeteau, S. & Mora, V. (2000). Predicting the national accounts of the euro zone using business surveys, Insee Conjoncture, December 2000, 10-18.
Brunello, G., Lupi, C. & Ordine, P. (2000). Regional disparities and the Italian NAIRU, Oxford Economic Papers, 52, 146-177.
Bruno, G., Cubadda, G., Giovannini, E. & Lupi, C. (2002). The flash estim- ate of the Italian real gross domestic product, in R.Barcellan and G.L.Mazzi (Eds.), Workshop on Quarterly National Accounts. Luxembourg, Eurostat.
Bruno, G. & Lupi, C. (2001). Forecasting industrial production and the early detection of turning points, ISAE Documenti di Lavoro n. 20/01: improved and updated version presented at the 22nd International Symposium on Fore- casting (ISF), Dublin, June 2002.
Cainelli, G. & Lupi, C. (1999). Aggregazione contemporanea e specificazione econometrica nella stima trimestrale dei conti economici nazionali, Statistica, 49, 239-267.
Carlson, J.A. and Parkin, J.M. (1975). Inflation expectations, Economica, 123-138.
Doornik, J.A. & Hansen, H. (1994). A practical test for univariate and mul- tivariate normality, Nuffield College Discussion Paper
Doornik, J.A. & Hendry, D.F. (2001). Modelling Dynamic Systems Using PcGive, Vol II. London: Timberlake Consultants Ltd.
Doz, C. & F. Lenglart (1999). Analyse factorielle dynamique: test du nombre de facteurs, estimation et application a l’enquˆte de conjoncture dans ` e l’industrie. Annales d’ ́conomie et de statistique, 54, 91-127.
Eurostat (1997). Handbook on Quarterly National Accounts. Luxembourg, Eurostat.
European Commission (1997). The joint harmonised EU programme of busi- ness and consumer surveys, European Economy, 6.
European Euro Commission Area, (2000). Business Climate Indicator for the (http://europa.eu.int/comm/economy finance/indicators /business climate/2001/presentation climate.pdf).
Foster, J. and Gregory, M. (1977). Inflation expectations: The use of qualitative survey data, Applied Economics, 9, 319-329.
Garc ́ıa-Ferrer, A. & Bujosa-Brun, M. (2000). Forecasting OECD industrial turning points using unobserved components models with business survey data, International Journal of Forecasting, 16, 207-227.
G ́mez, o SEATS: V., & Maravall, Instructions for the A. (1998). User, Programs Madrid: Banco TRAMO de and Espa ̃a. n (http://www.bde.es/servicio/software/econome.htm).
Harvey, A.C. (1989). Forecasting, Structural Time Series Models and the Kal- man Filter. Cambridge: Cambridge University Press.
Huh, C. (1998). Forecasting industrial production using models with business cycle asymmetry, Federal Reserve Bank of San Francisco Economic Review, n. 1, 29-41.
Istat (1996). ”Numeri indici della produzione industriale”, Metodi e Norme.
Kauppi, E., Lassila, J. & Ter ̈svirta, T. (1996). Short-term forecasting of a industrial production with business survey data: experience from Finland’s great depression 1990–1993, International Journal of Forecasting, 12, 373-381.
Marcellino, M., Stock, J.H. & Watson, M.W. (2001). Macroeconomic forecast- ing in the Euro Area: country specific versus area-wide information, IGIER Working Paper n. 201.
Marchetti, D.J. & Parigi, G. (2000). Energy consumption, survey data and the prediction of industrial production in Italy: A comparison and combination of different models, Journal of Forecasting, 19, 419-440.
Mitchell, J., Smith, R.J. & Weale, M.R. (2002). Quantification of qualitative firm-level survey data, Economic Journal, 112, C117-C135.
Pesaran, M.H. (1987). The Limits to Rational Expectations. Oxford, Basil Blackwell.
Osborn, D.R. (2001). Unit-Root versus deterministic representations of sea sonality for forecasting, Ch. 18 in Clements M.P. & Hendry, D.F. (Eds.) A Companion to Economic Forecasting. Oxford: Basil Blackwell.
Osborn, D.R., Heravi, S. & Birchenhall, C.R. (1999). Seasonal unit roots and forecasts of two-digit European industrial production, International Journal of Forecasting, 15, 27-47.
Simpson, P.W., Osborn D.R. & Sensier, M. (2000). Forecasting UK industrial production over the business cycle, Centre for Growth and Business Cycle Research, School of Economic Studies, University of Manchester, mimeo. (http://fmwww.bc.edu/RePEc/es2000/1059.pdf)
White, H. (1980). A heteroskedastic-consistent covariance matrix estimator and a direct test for heteroskedasticity, Econometrica, 48, 817-838.
Zizza, R. (2002): Forecasting the industrial production index for the Euro area through forecasts for the main countries, Bank of Italy Temi di Discussione No. 411.