An estimation of the industrial production dynamic in the MERCOSUR countries using the Markov switching model

Autores/as

  • Saba Infante Universidad Yachay Tech Ecuador
  • Edward Gómez Universidad de Carabobo Venezuela, República Bolivariana de
  • Luis Sánchez Universidad T´ecnica de Manab´ı Ecuador
  • Aracelis Hernández Universidad Yachay Tech Ecuador

DOI:

https://doi.org/10.24310/recta.20.1.2019.19895

Palabras clave:

Markov Switching Models, Algorithms Monte Carlo Markov Chains,, Industrial Production in MERCOSUR

Resumen

In this work the methodology applied is based on Bayesian statistical methods inspired by Markov chain Monte Carlo sampling schemes, which simplifies the estimation and prediction process of the Markov switching model. The general objective of this study is to determine simultaneously: non-linearity, structural changes, asymmetries and outliers that are characteristics present in many financial series. The methodology is empirically illustrated using series that measure the annual growth rate of industrial production in the MERCOSUR countries. The sampling algorithm [1] is implemented to estimate the parameters of the model. The parameters were estimated in terms of expected values a posteriori and standard deviations a posteriori. Three criteria is used to assess the prediction model: square root of the mean quadratic error (RSME), the Diebold-Mariano (DM) test and the TRC statistical test. These measures of goodness-of-fit show, that the estimates have small errors. The execution time of the algorithm is calculated, observing high performance. As a result of the analysis of the data, it is concluded that there is no reduction of economic volatility and no reduction in the depth of economic cycles. At the breakpoints, atypical values and non-linearity in the data are observed. It also shows that there are no common economic cycles for the countries analyzed.

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Publicado

2019-06-30

Cómo citar

Infante, S., Gómez, E., Sánchez, L., & Hernández, A. (2019). An estimation of the industrial production dynamic in the MERCOSUR countries using the Markov switching model. Revista Electrónica De Comunicaciones Y Trabajos De ASEPUMA, 20(1), 21–42. https://doi.org/10.24310/recta.20.1.2019.19895