Bušs, Ginters (2010): Forecasts with single-equation Markov-switching model: an application to the gross domestic product of Latvia.
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Abstract
The paper compares one-period ahead forecasting performance of linear vector-autoregressive (VAR) models and single-equation Markov-switching (MS) models for two cases: when leading information is available and when it is not. The results show that single-equation MS models tend to perform slightly better than linear VAR models when no leading information is available. However, if reliable leading information is available, single-equation MS models tend to give somewhat less precise forecasts than linear VAR models.
Item Type: | MPRA Paper |
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Original Title: | Forecasts with single-equation Markov-switching model: an application to the gross domestic product of Latvia |
Language: | English |
Keywords: | Markov-switching, VAR, forecasting, leading information |
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 C - Mathematical and Quantitative Methods > C1 - Econometric and Statistical Methods and Methodology: General > C13 - Estimation: General C - Mathematical and Quantitative Methods > C5 - Econometric Modeling > C51 - Model Construction and Estimation C - Mathematical and Quantitative Methods > C5 - Econometric Modeling > C53 - Forecasting and Prediction Methods ; Simulation Methods C - Mathematical and Quantitative Methods > C5 - Econometric Modeling > C52 - Model Evaluation, Validation, and Selection C - Mathematical and Quantitative Methods > C2 - Single Equation Models ; Single Variables > C22 - Time-Series Models ; Dynamic Quantile Regressions ; Dynamic Treatment Effect Models ; Diffusion Processes |
Item ID: | 20688 |
Depositing User: | Ginters Buss |
Date Deposited: | 14 Feb 2010 19:45 |
Last Modified: | 29 Sep 2019 10:36 |
References: | [1] Bellone, B. (2005),"Classical Estimation of Multivariate Markov-Switching Models using MSVARlib", Econometrics 0508017, EconWPA [2] Buss, G. (2009), "Comparing Forecasts of Latvia’s GDP Using Simple Seasonal ARIMA Models and Direct Versus Indirect Approach", MPRA Paper 16832, University Library of Munich, Germany [3] Dubois, E. and Michaux, E. (2010), "Grocer 1.41: an econometric toolbox for Scilab", available at http://dubois.ensae.net/grocer.html [4] Hamilton, J. D. (1989), "A New Approach to the Economic Analysis of Nonstationary Time Series and the Business Cycle", Econometrica, Vol. 57, No. 2, 357-384 [5] Hamilton, J. D. (1994), Time Series Analysis, Princeton University Press, Ch. 22, 677-703 [6] Krolzig, H.M. (1998), "Econometric Modelling of Markov-Switching Vector Autoregressions using MSVAR for Ox", Working paper [7] Krolzig, H. M. (2000), "Predicting Markov-Switching Vector Autoregressive Processes", Working paper [8] Krolzig, H. M. (2003), "Constructing Turning Point Chronologies with Markov-Switching Vector Autoregressive Models: the Euro-Zone Business Cycle", Working paper |
URI: | https://mpra.ub.uni-muenchen.de/id/eprint/20688 |