Bayesian Analysis of Coefficient Instability in Dynamic Regressions
This paper deals with instability in regression coefficients. We propose a Bayesian regression model with time-varying coefficients (TVC) that allows to jointly estimate the degree of instability and the time-path of the coefficients. Thanks to the computational tractability of the model and to the...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2019-06-01
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| Series: | Econometrics |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2225-1146/7/3/29 |
| _version_ | 1811302037198995456 |
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| author | Emanuela Ciapanna Marco Taboga |
| author_facet | Emanuela Ciapanna Marco Taboga |
| author_sort | Emanuela Ciapanna |
| collection | DOAJ |
| description | This paper deals with instability in regression coefficients. We propose a Bayesian regression model with time-varying coefficients (TVC) that allows to jointly estimate the degree of instability and the time-path of the coefficients. Thanks to the computational tractability of the model and to the fact that it is fully automatic, we are able to run Monte Carlo experiments and analyze its finite-sample properties. We find that the estimation precision and the forecasting accuracy of the TVC model compare favorably to those of other methods commonly employed to deal with parameter instability. A distinguishing feature of the TVC model is its robustness to mis-specification: Its performance is also satisfactory when regression coefficients are stable or when they experience discrete structural breaks. As a demonstrative application, we used our TVC model to estimate the exposures of S&P 500 stocks to market-wide risk factors: We found that a vast majority of stocks had time-varying exposures and the TVC model helped to better forecast these exposures. |
| first_indexed | 2024-04-13T07:20:43Z |
| format | Article |
| id | doaj.art-ebb8319f5fba47b9b0e3252e2cb0b94b |
| institution | Directory Open Access Journal |
| issn | 2225-1146 |
| language | English |
| last_indexed | 2024-04-13T07:20:43Z |
| publishDate | 2019-06-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Econometrics |
| spelling | doaj.art-ebb8319f5fba47b9b0e3252e2cb0b94b2022-12-22T02:56:38ZengMDPI AGEconometrics2225-11462019-06-01732910.3390/econometrics7030029econometrics7030029Bayesian Analysis of Coefficient Instability in Dynamic RegressionsEmanuela Ciapanna0Marco Taboga1Directorate General for Economics, Statistics and Research, Banca d’Italia, Via Nazionale 91, 00184 Roma, ItalyDirectorate General for Economics, Statistics and Research, Banca d’Italia, Via Nazionale 91, 00184 Roma, ItalyThis paper deals with instability in regression coefficients. We propose a Bayesian regression model with time-varying coefficients (TVC) that allows to jointly estimate the degree of instability and the time-path of the coefficients. Thanks to the computational tractability of the model and to the fact that it is fully automatic, we are able to run Monte Carlo experiments and analyze its finite-sample properties. We find that the estimation precision and the forecasting accuracy of the TVC model compare favorably to those of other methods commonly employed to deal with parameter instability. A distinguishing feature of the TVC model is its robustness to mis-specification: Its performance is also satisfactory when regression coefficients are stable or when they experience discrete structural breaks. As a demonstrative application, we used our TVC model to estimate the exposures of S&P 500 stocks to market-wide risk factors: We found that a vast majority of stocks had time-varying exposures and the TVC model helped to better forecast these exposures.https://www.mdpi.com/2225-1146/7/3/29coefficients’ instabilityTVC modelBayesian regressionMonte Carlo experiments |
| spellingShingle | Emanuela Ciapanna Marco Taboga Bayesian Analysis of Coefficient Instability in Dynamic Regressions Econometrics coefficients’ instability TVC model Bayesian regression Monte Carlo experiments |
| title | Bayesian Analysis of Coefficient Instability in Dynamic Regressions |
| title_full | Bayesian Analysis of Coefficient Instability in Dynamic Regressions |
| title_fullStr | Bayesian Analysis of Coefficient Instability in Dynamic Regressions |
| title_full_unstemmed | Bayesian Analysis of Coefficient Instability in Dynamic Regressions |
| title_short | Bayesian Analysis of Coefficient Instability in Dynamic Regressions |
| title_sort | bayesian analysis of coefficient instability in dynamic regressions |
| topic | coefficients’ instability TVC model Bayesian regression Monte Carlo experiments |
| url | https://www.mdpi.com/2225-1146/7/3/29 |
| work_keys_str_mv | AT emanuelaciapanna bayesiananalysisofcoefficientinstabilityindynamicregressions AT marcotaboga bayesiananalysisofcoefficientinstabilityindynamicregressions |