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Autoregressió Vectorial (VAR)×Model ARIMA (Autoregressive Integrated Moving Average)×
CampEconometriaEconometria
FamíliaRegression modelRegression model
Any d'origen19801970
Autor originalChristopher A. SimsGeorge Box and Gwilym Jenkins
TipusMultivariate time-series modelTime series forecasting model
Font seminalSims, C. A. (1980). Macroeconomics and Reality. Econometrica, 48(1), 1–48. DOI ↗Box, G. E. P., & Jenkins, G. M. (1970). Time Series Analysis: Forecasting and Control. Holden-Day. link ↗
ÀliesVAR, VAR model, vector autoregressive model, multivariate autoregressionARIMA, Box-Jenkins model, integrated ARMA, ARIMA(p,d,q)
Relacionats56
ResumVector 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.The ARIMA(p,d,q) model is the standard workhorse for univariate time series forecasting. It combines autoregressive terms (past values), differencing to induce stationarity, and moving average terms (past shocks) into a unified linear framework. Developed by Box and Jenkins (1970), it remains one of the most widely applied models in econometrics and applied statistics.
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ScholarGateCompara mètodes: Vector Autoregression · ARIMA model. Recuperat el 2026-06-17 de https://scholargate.app/ca/compare