Cruz-Rodríguez, Alexis (2004): Un análisis del ciclo económico de la República Dominicana bajo cambios de régimen.
Preview |
PDF
MPRA_paper_54352.pdf Download (288kB) | Preview |
Abstract
This paper presents a univariate model that analyzes systematic changes in the behavior of the business cycle in the Dominican Republic, capturing changes in average growth and identifying differences between contractions and expansions with respect to their persistence and duration. To do so, it uses the classic algorithm described by Hamilton (1990, 1991) that consists of two parts. In the first part, population parameters, including joint probability density of unobserved states, are estimated. In the second part, using a nonlinear filter and smoothed probabilities, probabilistic inferences are made about unobserved states. Our results suggest that the characteristics of the distribution functions estimated for each scheme differ, both in mean and standard deviation. Thus, for a recessive event or contraction, average quarterly growth was around -0.33% with a standard deviation of 0.45%, whereas for an expanding statistical event, estimates were 0.23% and 0.27%, respectively.
Item Type: | MPRA Paper |
---|---|
Original Title: | Un análisis del ciclo económico de la República Dominicana bajo cambios de régimen |
English Title: | Analysis of business cycle of the Dominican Republic using Markov Switching model |
Language: | Spanish |
Keywords: | Business cycle, regime switching models |
Subjects: | E - Macroeconomics and Monetary Economics > E3 - Prices, Business Fluctuations, and Cycles > E30 - General E - Macroeconomics and Monetary Economics > E3 - Prices, Business Fluctuations, and Cycles > E32 - Business Fluctuations ; Cycles |
Item ID: | 54352 |
Depositing User: | A Cruz-Rodriguez |
Date Deposited: | 14 Mar 2014 14:08 |
Last Modified: | 06 Oct 2019 16:30 |
References: | Burns, A. F. y Mitchell, W.C. (1946). Measuring business cycles, New York: NBER. CEPAL y PUCMM (2001). Desarrollo Económico y Social en la República Dominicana, los últimos 20 años y perspectivas para el Siglo XXI. Medibyte. República Dominicana. Chauvet, Marcelle (1998): An Econometric Characterization of Business Cycle Dynamics with Factor Structure and Regime Switches. International Economic Review, Vol. 39, No. 4, pp. 969-996. Clements, M. P. y Krolzig, H-M. (2003). Business Cycle Asymmetries: Characterization and Testing Based on Markov-Switching Autoregressions. Journal of Business and Economic Statistics, Vol. 21, No.1 (January). Dempster, A.P., Laird, N.M. y Rubin, D.B. (1977). Maximum likelihood from incomplete data via the EM algorithm. Journal of the Royal Statistical Society, B39, 1-38. Diebold, F. X.; Lee, J. H. y Weinbach, G. C. (1994). Regimen Switching with Time-Varying Transition Probabilities. C. Hargreaves (editor): Nonstationary Time Series Analysis and Cointegration, Oxford: Oxford University Press, pp. 283-302. Diebold, F. X. y Rudebusch, G. D. (1996). Measuring Business Cycle: A Modern Perspective. The Review of Economics and Statistics, Vol. 78, No. 1, pp. 67-77. February. Dickey, D. y Fuller, W. (1981). Likelihood Ratio Statistics for Autoregressive Time Series with a Unit Root. Econometrica, Vol. 49, No. 4, pp. 1057-1072. July. Filardo, A. J. (1994). Business Cycle Phases and their Transitional Dynamics. Journal of Business and Economic Statistics, Vol. 12, pp.299-308. Filardo, A. J. y Gordon, S. F. (1998). Business cycle durations. Journal of Econometrics, Vol.85, pp. 99-123. Findley, D.; Monsell, B.; Bell, W.; Otto, M. y Chen, B-C. (1998). New Capabilities and Methods of the X-12-ARIMA Seasonal-Adjustment Program. Journal of Business & Economic Statistics. Vol.16, No.2, pp. 127-152. Hamilton, J. D. (1989). A New Approch to the Economic Analysis of Nonstationary Time Series and the Business Cycle. Econometrica, Volume 57, Issue 2, pp. 357-384. March. Hamilton, J. D. (1990). Analysis of time series subject to changes in regimes. Journal of Econometrics, Vol. 45, pp. 39-70. Hamilton, J. D. (1991). A Quasi-Bayesian Approch to Estimating Parameters for Mixtures of Normal Distributions. Journal of Business and Economic Statistics, Vol. 9, pp. 27-39. Hamilton, J. D. (1994). Time Series Analysis. Princeton: Princeton University Press. Hansen, B. E. (1992). The Likelihood Ratio Test Under Nonstandard Conditions: Testing the Markov Switching Model of GNP. Journal of Applied Econometrics. Vol. 7, pp.S61-S82. Johnson, C. A. (2000). Un Modelo de Switching para el Crecimiento en Chile. Documentos de Trabajo. No. 84, Banco Central de Chile. Kim, C. J. y Nelson, C. R. (1998). Business Cycles Turning Points: A new Coincident Index and Tests of Duration Dependence Based on a Dynamic Factor Model with Regime Switching. Review of Economics and Statistics, Vol. 80, pp. 188-201. Krolzig, H-M (1997). Markov Switching Vector Autoregressions. Modelling, Statistical Inference and Application to Business Cycle Analysis. Berlin: Springer. Krolzig, H-M. (1998). Econometric Modelling of Markov-Switching Vector Autoregressions using MSVAR for Ox. Mimeo. Department of Economics, Oxford University. December. Krolzig, H-M. (2002). Regime-Switching Models. Mimeo. Department of Economics, Nuffield College, Oxford University. Krolzig, H-M. (2003). Constructing Turning Point Chronologies with Markov-Switching Vector Autoregressive Models: the Euro-Zone Business Cycle. Discussion Paper. Oxford University. July. McQueen, G. y Thorley, S. (1993). Asymmetric business cycle turning points. Journal of Monetary Economics, Vol.31, pp. 341-362. Phillips, P.C.B. y Perron, P. (1988). Testing for a Unit Root in Time Series Regression. Biometrika. Vol. 75, pp. 335-346. Potter, S. M. (1999). Nonlinear Time Series Modelling: An Introduction. Discussion Paper, Federal Reserve Bank of New York. August. Sargent, T. y Sims, C. (1977). Business Cycles Modeling without pretending to have too much a priori Theory. Sims, C. (editor): New Methods of Business Cycle Research. Minneapolis: Federal Reserve Bank of Minneapolis. Sichel, D. E. (1993). Business cycle asymmetry. Economic Inquiry, Vol. 31, pp. 254-277. Stock, J. H. y Watson, M. W. (1993). A Procedure for Predicting Recessions with Leading Indicators: Econometric Issues and Recent Experience. Stock, J y Watson, M. W. (editores): Business Cycle, Indicators and Forecasting. Chicago: University of Chicago Press para el NBER, pp. 255-285. |
URI: | https://mpra.ub.uni-muenchen.de/id/eprint/54352 |