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A robust Bayesian dynamic linear model for Latin-American economic time series: “the Mexico and Puerto Rico cases”

Author

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  • Jairo Fúquene
  • Marta Álvarez
  • Luis Raúl Pericchi

Abstract

The traditional time series methodology requires at least a preliminary transformation of the data to get stationarity. On the other hand, robust Bayesian dynamic models (RBDMs) do not assume a regular pattern or stability of the underlying system but can include points of statement breaks. In this paper we use RBDMs in order to account possible outliers and structural breaks in Latin-American economic time series. We work with important economic time series from Puerto Rico and Mexico. We show by using a random walk model how RBDMs can be applied for detecting historic changes in the economic inflation of Mexico. Also, we model the Consumer Price Index, the Economic Activity Index and the total number of employments economic time series in Puerto Rico using local linear trend and seasonal RBDMs with observational and states variances. The results illustrate how the model accounts the structural breaks for the historic recession periods in Puerto Rico. Copyright The Author(s) 2015

Suggested Citation

  • Jairo Fúquene & Marta Álvarez & Luis Raúl Pericchi, 2015. "A robust Bayesian dynamic linear model for Latin-American economic time series: “the Mexico and Puerto Rico cases”," Latin American Economic Review, Springer;Centro de Investigaciòn y Docencia Económica (CIDE), vol. 24(1), pages 1-17, December.
    • Handle: RePEc:spr:laecrv:v:24:y:2015:i:1:p:1-17:10.1007/s40503-015-0020-z
    DOI: 10.1007/s40503-015-0020-z
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    References listed on IDEAS

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    1. Hansen, Bruce E., 2000. "Testing for structural change in conditional models," Journal of Econometrics, Elsevier, vol. 97(1), pages 93-115, July.
    2. David Ardia & Lennart F. Hoogerheide, 2010. "Bayesian Estimation of the GARCH(1,1) Model with Student-t Innovations," Tinbergen Institute Discussion Papers 10-045/4, Tinbergen Institute.
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    Cited by:

    1. Olawale Awe O. & Adedayo Adepoju A., 2018. "Modified Recursive Bayesian Algorithm For Estimating Time-Varying Parameters In Dynamic Linear Models," Statistics in Transition New Series, Polish Statistical Association, vol. 19(2), pages 258-293, June.
    2. O. Olawale Awe & A. Adedayo Adepoju, 2018. "Modified Recursive Bayesian Algorithm For Estimating Time-Varying Parameters In Dynamic Linear Models," Statistics in Transition New Series, Polish Statistical Association, vol. 19(2), pages 239-258, June.

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    More about this item

    Keywords

    Robust Bayesian dynamic model; Outliers and structural breaks; Latin-American time series; Consumer Price Index ; Economic Activity Index; Total number of employments; C11; C40; G17; N16;
    All these keywords.

    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • C40 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - General
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation
    • N16 - Economic History - - Macroeconomics and Monetary Economics; Industrial Structure; Growth; Fluctuations - - - Latin America; Caribbean

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