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| Bayesiansk ADF-enhedsrodstest× | Bayesiansk VAR-model (BVAR)× | |
|---|---|---|
| Fagområde | Økonometri | Økonometri |
| Familie | Regression model | Regression model |
| Oprindelsesår≠ | 1991–1992 | 1984 |
| Ophavsperson≠ | Sims & Uhlig (1991); Koop, Osiewalski & Steel (1992) | Doan, Litterman & Sims |
| Type≠ | Bayesian hypothesis test | Multivariate time-series model |
| Oprindelig kilde≠ | Sims, C. A., & Uhlig, H. (1991). Understanding unit rooters: A helicopter tour. Econometrica, 59(6), 1591–1599. DOI ↗ | Doan, T., Litterman, R., & Sims, C. (1984). Forecasting and conditional projection using realistic prior distributions. Econometric Reviews, 3(1), 1–100. DOI ↗ |
| Aliasser | Bayesian ADF test, Bayesian unit root test, Bayesian Dickey-Fuller, BADF | BVAR, Bayesian VAR, Bayesian vector autoregressive model, BVAR model |
| Relaterede≠ | 6 | 5 |
| Resumé≠ | The Bayesian Augmented Dickey-Fuller (BADF) unit root test re-frames the classical ADF test within a Bayesian framework. Rather than computing a frequentist p-value, it quantifies evidence for or against a unit root by comparing posterior probabilities or Bayes factors under the null (unit root) and alternative (stationarity) hypotheses, incorporating prior beliefs about the autoregressive parameter. | The Bayesian Vector Autoregression (BVAR) model extends the classical VAR framework by incorporating prior beliefs about the model coefficients. Priors — most commonly the Minnesota prior — shrink VAR coefficients toward economically sensible values, dramatically reducing overfitting and improving out-of-sample forecast accuracy even when the number of variables is large. |
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