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Struktureller Bruch ARIMA-Modell×ARIMA-Modell (Autoregressives integriertes gleitendes Durchschnittsmodell)×Chow-Test auf Strukturbruch×
FachgebietÖkonometrieÖkonometrieÖkonometrie
FamilieRegression modelRegression modelRegression model
Entstehungsjahr1989-199819701960
UrheberPerron (1989); extended by Bai & Perron (1998)George Box and Gwilym JenkinsGregory C. Chow
TypTime series model with regime detectionTime series forecasting modelTest for structural break in regression coefficients
Wegweisende QuelleBai, J., & Perron, P. (1998). Estimating and testing linear models with multiple structural changes. Econometrica, 66(1), 47-78. DOI ↗Box, G. E. P., & Jenkins, G. M. (1970). Time Series Analysis: Forecasting and Control. Holden-Day. link ↗Chow, G. C. (1960). Tests of equality between sets of coefficients in two linear regressions. Econometrica, 28(3), 591–605. DOI ↗
AliasnamenARIMA with structural breaks, break-adjusted ARIMA, piecewise ARIMA, ARIMA with regime shiftsARIMA, Box-Jenkins model, integrated ARMA, ARIMA(p,d,q)Chow breakpoint test, structural break test, Chow yapısal kırılma testi
Verwandt362
ZusammenfassungA structural break ARIMA model extends the standard ARIMA framework by explicitly identifying and accommodating one or more abrupt shifts in the level, trend, or dynamics of a time series. Rather than forcing a single set of ARIMA parameters across the entire sample, it fits separate ARIMA specifications for each regime defined by the detected break dates.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.The Chow test, introduced by Gregory Chow in 1960, checks whether the coefficients of a linear regression are the same across two subsamples — that is, whether a structural break occurs at a known point such as a policy change, crisis, or regime shift. It compares the fit of a single pooled regression with the combined fit of two separate regressions; a large improvement from splitting indicates the relationship differs between the two periods or groups.
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ScholarGateMethoden vergleichen: Structural Break ARIMA Model · ARIMA model · Chow Test. Abgerufen am 2026-06-18 von https://scholargate.app/de/compare