Bruno, Giancarlo and Malgarini, Marco (2002): An Indicator of Economic Sentiment for the Italian Economy.
Preview |
PDF
MPRA_paper_42331.pdf Download (366kB) | Preview |
Abstract
The long and sustained expansion of the nineties has generated, especially in the US, widespread rumours about the “death of the cycle”. Nevertheless, towards the end of the last decade, it became clear that fluctuations of economic activity were far from being extinct. This has contributed greatly to a renewed interest among economists for the elaboration of statistical indicators capable of tracking and, if possible, anticipating the cyclical features of the economy. The aim of this paper is to build such an aggregate composite indicator for the Italian Economy, based on the ISAE surveys on households and those on the manufacturing, retail and construction sector. The first step of the analysis consists in using a dynamic factor model to extract a “common factor” from the different series of each survey, which may be interpreted as a composite confidence indicator. We then evaluate, for each survey, its in-sample and out-of sample properties, comparing them with those of the usual ISAE-EC Confidence indicators. Finally, we use again the dynamic factor model to build, from the sectoral Composite Indicator (CI), a Composite Aggregate Indicator (CAI) for the Italian economy, and test its ability in tracking the cyclical features of Italian aggregate GDP.
Item Type: | MPRA Paper |
---|---|
Original Title: | An Indicator of Economic Sentiment for the Italian Economy |
Language: | English |
Keywords: | Confidence Indicators; Leading Indicators; Cyclical Analysis |
Subjects: | E - Macroeconomics and Monetary Economics > E3 - Prices, Business Fluctuations, and Cycles > E32 - Business Fluctuations ; Cycles E - Macroeconomics and Monetary Economics > E3 - Prices, Business Fluctuations, and Cycles > E37 - Forecasting and Simulation: Models and Applications |
Item ID: | 42331 |
Depositing User: | Giancarlo Bruno |
Date Deposited: | 01 Nov 2012 05:37 |
Last Modified: | 07 Oct 2019 16:34 |
References: | Altissimo, F., Marchetti, D.J. and G.P. Oneto, (2000). The Italian Business Cycle: Coincident and Leading Indicators and Some Stylized Facts, Temi di Discussione del Servizio Studi, n. 377, Banca d’Italia, Rome. Andrews, D.W.K. (1991). Heteroskedasticity and Autocorrelation Consistent Covariance Matrix Estimation. Econometrica, 59, pp. : 817-858. Baxter, M. and R.G. King (1999). Measuring Business Cycles: Approximate Band-Pass Filters for Economic Time Series Review of Economics and Statistics, n. 81. Bovi, M., Lupi C. and C. Pappalardo (2000). Predicting GDP Components Using ISAE Bridge Equations Econometric Forecasting Model (BEEF), Documento di Lavoro ISAE, n. 12, Rome. Bry, G. and C. Boschan (1971). Cyclical Analysis of Time Series: Selected Procedures and Computer Programs, NBER Technical Papers, n. 20, New York. Brunello, G., Lupi, C. and P. Ordine (2000). Regional disparities and the Italian NAIRU, Oxford Economic Papers, 52, pp. 146-177. Burns, A. and W.C. Mitchell (1946). Measuring Business Cycles, NBER, New York. Carnazza, P. and G.P. Oneto (1996). Searching for a Leading Indicator of Household Consumption in the Italian Economy, in Oppenlaender K.H. and G. Poser (eds), Business Cycles Surveys: Forecasting Issues and Methodological Aspects. Selected Papers, presented at the 22nd Ciret Conference, Singapore, Avebury, Aldershot. Carnazza, P. and G. Parigi (2001). Tentative Business Confidence Indicators for the Italian Economy, Documento di Lavoro ISAE, n. 17, Rome. Croux, C., Forni, M. and L. Reichlin (2001). A Measure of Comovement for economic Variables: Theory and Empirics. The Review of Economics and Statistics, 83, pp. 232-241. Doan, T.A. (2000). RATS for Windows - Version 5, Evanston: Estima. Doz, C. and F. Lenglart (1999). Analyse factorielle dynamique: test du nombre de facteurs, estimation et application à l'enquête de conjoncture dans l'industrie. Annales d'économie et de statistique, 54, pp. 91-127. European Commission (2000). Business Climate Indicator for the Euro Area, (http://europa.eu.int/comm/economy_finance/indicators/business_climate/2001/presentation\_climate.pdf). Forni, M. and L. Reichlin (1996). Let’s Get Real: A Dynamic Factor Analytical Approach to Disaggregated Business Cycle. Review of Economic Studies, 65, pp. 454-474. Geweke, J. (1977). The Dynamic factor Analysis of Economic Time Series. In D.J. Aigner and A.S. Goldberger (eds.), Latent Variables in Socio-Economic Models, North Holland, Amsterdam, Ch. 19. Goldrian, G., Lindbauer, J.D. and G. Nerb (2001). Evaluation and Development of Confidence Indicators Based on Harmonised Business and Consumer Surveys, EC Economic Paper, n. 151, Bruxelles. Gómez, V. and A. Maravall (1998). Programs TRAMO and SEATS: Instructions for the User, Madrid: Banco de España. (http://www.bde.es/servicio/software/econome.htm). Harvey, A. (2001). Testing in Unobserved Component Models. Journal of Forecasting, 20, pp. 1-19. Kwiatkowsky, D., Phillips, P.C.B., Schmidt, P. and Y. Shin (1992). Testing the null hypothesis of stationarity against the alternative of a unit root: How sure are we that economic time series have a unit root ?, Journal of Econometrics, 44, pp. 159-178. Martelli, B. (1998). Le Inchieste Congiunturali dell’ISCO: aspetti metodologici, Rassegna di Lavori dell’ISCO, Vol. XV, n. 3, Rome. Mintz, I. (1972). Dating American Growth Cycles, in V. Zarnowitz (ed.), Business Cycle Today, NBER, New York. Nyblom, J. and A. Harvey (2000). Tests of Common Stochastic Trends, Econometric Theory, 16, pp. 176-199. Pagan, A. and D. Harding (2001). Extracting, Analysing and Using Cyclical Information, Publication, paper presented at the Banca d’Italia-CEPR Conference on Monitoring the Euro Area Business Cycle, Rome, 7/8 September 2001. Sargent, T.J. and C.A. Sims (1977). Business Cycle Modeling without Pretendig to have Too Much a-priori Economic Theory. In C. Sims et al. (eds.), New Methods in Business Cycle Research, Minneapolis: Federal Reserve Bank of Minneapolis. Schlitzer, G. (1993). Nuovi Strumenti per la Valutazione e la Previsione del Ciclo Economico in Italia, Temi di Discussione del Servizio Studi, n. 200, Banca d’Italia, Roma. Stock, J.H and M.W. Watson (1991). A Probability Model of the Coincident Economic Indicators. In K. Lahiri and G.H. Moore (eds.), Leading Economic Indicators: New Approaches and Forecasting Records, Ch. 4. New York: Cambridge University Press, pp. 63-85. Stock, J.H and M.W. Watson (1998). Diffusion Indexes, NBER working paper n. 6702. |
URI: | https://mpra.ub.uni-muenchen.de/id/eprint/42331 |