A Dynamic Binary Probit Model with Time-Varying Parameters and Shrinkage Prior
Bibliographic Data
| ID | 19418957 |
|---|---|
| Authors | Zhongfang He (Royal Bank of Canada, corresponding author) |
| Year | 2024 |
| Volume | 42 |
| Issue | 1 |
| Pages | 335-346 |
| Publication date | 2024-01-02 |
| Peer Reviewed | Yes |
| Open Access | No |
| Type | ARTICLE |
| Venue | Journal of Business and Economic Statistics (JOURNAL) |
| Journal identifiers | ISSN: 0735-0015 • E-ISSN: 1537-2707 |
| Publisher | Informa UK Limited (PUBLISHER • GB) |
| DOI | 10.1080/07350015.2023.2200458 |
| OpenAlex | W4362697698 |
| Language | EN |
| References cited | 39 |
This article studies a time series binary probit model in which the underlying latent variable depends on its lag and exogenous regressors. The regression coefficients for the latent variable are allowed to vary over time to capture possible model instability. Bayesian shrinkage priors are applied to automatically differentiate fixed and truly time-varying coefficients and thus avoid unnecessary model complexity. I develop an MCMC algorithm for model estimation that exploits parameter blocking to boost sampling efficiency. An efficient Monte Carlo approximation based on the Kalman filter is developed to improve the numerical stability for computing the predictive likelihood of the binary outcome. Benefits of the proposed model are illustrated in a simulation study and an application to forecast economic recessions
Bayes estimator · Bayesian probability · Econometrics · Kalman filter · Latent variable · Markov chain Monte Carlo · Monte Carlo method · Prior probability · Probit · Probit model · Statistics · Computer Science · Financial Risk and Volatility Modeling · Mathematics · Monetary Policy and Economic Impact · Statistical Methods and Inference
Time Series Analysis
Strictly Proper Scoring Rules, Prediction, and Estimation
Bayesian Analysis of Binary and Polychotomous Response Data
Binary Conditional Forecasts
Conditional Heteroscedasticity in Qualitative Response Models of Time Series
How Useful are Historical Data for Forecasting the Long-Run Equity Return Distribution
Dynamic Forecasts of Qualitative Variables
How Stable is the Predictive Power of the Yield Curve? Evidence from Germany and the United States
Predicting U.S. Recessions with Dynamic Binary Response Models
Bank Rate Policy Under the Interwar Gold Standard
| Citation velocity | historical |
|---|---|
| Highly cited | No |