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Granska de valda metoderna sida vid sida; rader som skiljer sig är markerade.
| Bayesiansk Grangerkausalitet× | Vektorautoregression (VAR)× | |
|---|---|---|
| Ämnesområde | Ekonometri | Ekonometri |
| Familj | Regression model | Regression model |
| Ursprungsår≠ | 1969 (frequentist); 1984 (Bayesian treatment) | 1980 |
| Upphovsperson≠ | Clive W. J. Granger (frequentist basis, 1969); Bayesian extension by Geweke (1984) and subsequent literature | Christopher A. Sims |
| Typ≠ | Bayesian causal inference test | Multivariate time-series model |
| Ursprungskälla≠ | Geweke, J. (1984). Inference and causality in economic time series models. Handbook of Econometrics, 2, 1101-1144. Elsevier. link ↗ | Sims, C. A. (1980). Macroeconomics and Reality. Econometrica, 48(1), 1–48. DOI ↗ |
| Alias | Bayesian Granger test, Bayesian predictive causality, BGC, Bayesian causality in mean | VAR, VAR model, vector autoregressive model, multivariate autoregression |
| Närliggande≠ | 6 | 5 |
| Sammanfattning≠ | Bayesian Granger causality tests whether past values of one time series carry predictive information about another, framing the hypothesis through Bayesian inference rather than frequentist p-values. It combines a vector autoregressive (VAR) structure with prior distributions over coefficients and evaluates causal claims via posterior probabilities or Bayes factors, providing a probabilistic and nuanced alternative to the classical Granger test. | Vector Autoregression is a multivariate time-series model in which each variable is regressed on its own lags and the lags of all other variables in the system. Originally proposed by Sims (1980) as a data-driven alternative to large structural macroeconomic models, VAR has become the standard workhorse for dynamic analysis in empirical economics and finance. |
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