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Testul ARDL Bounds (Testul Pesaran Bounds)×Modelul ARIMA (Autoregresiv Integrat cu Medii Mobile)×Modelul Vectorial de Autoregresie (VAR)×
DomeniuEconometrieEconometrieEconometrie
FamilieRegression modelRegression modelRegression model
Anul apariției200120152005
Autorul originalPesaran, Shin & SmithBox & Jenkins (Box-Jenkins methodology)Lütkepohl (textbook treatment); Sims (1980) macroeconometric tradition
TipCointegration test / Autoregressive distributed lag modelUnivariate time-series modelMultivariate time-series model
Sursa seminalăPesaran, M. H., Shin, Y., & Smith, R. J. (2001). Bounds Testing Approaches to the Analysis of Level Relationships. Journal of Applied Econometrics, 16(3), 289–326. DOI ↗Box, G. E. P., Jenkins, G. M., Reinsel, G. C. & Ljung, G. M. (2015). Time Series Analysis: Forecasting and Control (5th ed.). Wiley. ISBN: 978-1118675021Lütkepohl, H. (2005). New Introduction to Multiple Time Series Analysis. Springer. DOI ↗
Denumiri alternativePesaran bounds test, bounds testing approach, ARDL cointegration test, ARDL Sınır Testi (Pesaran Bounds Test)Box-Jenkins model, ARIMA(p,d,q), ARIMA Modelivector autoregression, VAR, VAR Modeli (Vektör Otoregresyon), vektör otoregresyon
Înrudite454
RezumatThe ARDL bounds test is an autoregressive distributed lag method that tests for a cointegrating (long-run level) relationship between time series, introduced by Pesaran, Shin and Smith in 2001. Unlike the Johansen procedure, it remains valid whether the variables are I(0), I(1) or a mix of the two, and it is more reliable than Johansen in small samples of roughly 30 to 80 observations.ARIMA is a univariate time-series forecasting model that combines autoregressive, integrated (differencing), and moving-average components to predict a single continuous series from its own past. It is the centrepiece of the Box-Jenkins methodology set out in Box, Jenkins, Reinsel & Ljung's Time Series Analysis (5th ed., 2015).Vector Autoregression is a multivariate time-series model that treats several interdependent series symmetrically, letting each variable depend on its own past values and the past values of all the others. It is the standard tool for capturing mutual causality and joint dynamics, developed in the modern multiple-time-series tradition treated by Lütkepohl (2005).
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ScholarGateCompară metode: ARDL Bounds Test · ARIMA · VAR Model. Preluat la 2026-06-18 de pe https://scholargate.app/ro/compare