Regression modelEconometrics / time series
Vector Autoregression (VAR)
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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Sources
- Sims, C. A. (1980). Macroeconomics and Reality. Econometrica, 48(1), 1–48. DOI: 10.2307/1912017 ↗
- Lütkepohl, H. (2005). New Introduction to Multiple Time Series Analysis. Springer. ISBN: 978-3540401728
Related methods
Referenced by
ARCH modelARIMA modelARMA modelAutoregressive modelBayesian AR modelBayesian ARIMA modelBayesian ARMA modelBayesian DCC-GARCHBayesian Granger CausalityBayesian SVAR modelBayesian Toda-Yamamoto CausalityBayesian VAR modelDCC-GARCH modelEGARCH modelFourier DCC-GARCHFourier Granger CausalityFourier VAR modelGranger Causality TestMarkov-Switching ModelMarkov-Switching MultifractalMoving Average ModelNonlinear GARCH modelNonlinear Granger CausalityNonlinear SVAR ModelNonlinear VAR ModelPanel ARIMA modelPanel ARMA modelPanel DCC-GARCHPanel GARCH modelPanel SVAR modelQuantile-on-Quantile RegressionRobust DCC-GARCHRobust SVAR modelSARIMA modelStructural break DCC-GARCHStructural Break Granger CausalityStructural Break OLSStructural Break Toda-Yamamoto CausalityStructural Break VAR ModelStructural VARTGARCH modelTime-varying parameter Granger causalityTime-varying parameter VAR modelToda-Yamamoto causality testVector Error Correction ModelZivot-Andrews Structural Break Test