Cointegration and Unit Root Tests: A Fully Bayesian Approach
To perform statistical inference for time series, one should be able to assess if they present deterministic or stochastic trends. For univariate analysis, one way to detect stochastic trends is to test if the series has unit roots, and for multivariate studies it is often relevant to search for sta...
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2020-08-01
|
| Series: | Entropy |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1099-4300/22/9/968 |
| _version_ | 1797555030250749952 |
|---|---|
| author | Marcio A. Diniz Carlos A. B. Pereira Julio M. Stern |
| author_facet | Marcio A. Diniz Carlos A. B. Pereira Julio M. Stern |
| author_sort | Marcio A. Diniz |
| collection | DOAJ |
| description | To perform statistical inference for time series, one should be able to assess if they present deterministic or stochastic trends. For univariate analysis, one way to detect stochastic trends is to test if the series has unit roots, and for multivariate studies it is often relevant to search for stationary linear relationships between the series, or if they cointegrate. The main goal of this article is to briefly review the shortcomings of unit root and cointegration tests proposed by the Bayesian approach of statistical inference and to show how they can be overcome by the Full Bayesian Significance Test (FBST), a procedure designed to test sharp or precise hypothesis. We will compare its performance with the most used frequentist alternatives, namely, the Augmented Dickey–Fuller for unit roots and the maximum eigenvalue test for cointegration. |
| first_indexed | 2024-03-10T16:40:25Z |
| format | Article |
| id | doaj.art-17e11c5744ab4e61a31d3b61efab787c |
| institution | Directory Open Access Journal |
| issn | 1099-4300 |
| language | English |
| last_indexed | 2024-03-10T16:40:25Z |
| publishDate | 2020-08-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Entropy |
| spelling | doaj.art-17e11c5744ab4e61a31d3b61efab787c2023-11-20T12:01:56ZengMDPI AGEntropy1099-43002020-08-0122996810.3390/e22090968Cointegration and Unit Root Tests: A Fully Bayesian ApproachMarcio A. Diniz0Carlos A. B. Pereira1Julio M. Stern2Statistics Department, Universidade Federal de S. Carlos, Rod. Washington Luis, km 235, S. Carlos 13565-905, BrazilStatistics Department, Universidade de S. Paulo, São Paulo 01000, BrazilApplied Mathematics Department, Universidade de S. Paulo, São Paulo 01000, BrazilTo perform statistical inference for time series, one should be able to assess if they present deterministic or stochastic trends. For univariate analysis, one way to detect stochastic trends is to test if the series has unit roots, and for multivariate studies it is often relevant to search for stationary linear relationships between the series, or if they cointegrate. The main goal of this article is to briefly review the shortcomings of unit root and cointegration tests proposed by the Bayesian approach of statistical inference and to show how they can be overcome by the Full Bayesian Significance Test (FBST), a procedure designed to test sharp or precise hypothesis. We will compare its performance with the most used frequentist alternatives, namely, the Augmented Dickey–Fuller for unit roots and the maximum eigenvalue test for cointegration.https://www.mdpi.com/1099-4300/22/9/968time seriesBayesian inferencehypothesis testingunit rootcointegration |
| spellingShingle | Marcio A. Diniz Carlos A. B. Pereira Julio M. Stern Cointegration and Unit Root Tests: A Fully Bayesian Approach Entropy time series Bayesian inference hypothesis testing unit root cointegration |
| title | Cointegration and Unit Root Tests: A Fully Bayesian Approach |
| title_full | Cointegration and Unit Root Tests: A Fully Bayesian Approach |
| title_fullStr | Cointegration and Unit Root Tests: A Fully Bayesian Approach |
| title_full_unstemmed | Cointegration and Unit Root Tests: A Fully Bayesian Approach |
| title_short | Cointegration and Unit Root Tests: A Fully Bayesian Approach |
| title_sort | cointegration and unit root tests a fully bayesian approach |
| topic | time series Bayesian inference hypothesis testing unit root cointegration |
| url | https://www.mdpi.com/1099-4300/22/9/968 |
| work_keys_str_mv | AT marcioadiniz cointegrationandunitroottestsafullybayesianapproach AT carlosabpereira cointegrationandunitroottestsafullybayesianapproach AT juliomstern cointegrationandunitroottestsafullybayesianapproach |