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Εκτιμητής Ελαχίστων Τετραγώνων Πλήρως Τροποποιημένος (FMOLS)×Η δοκιμή ορίων ARDL (Pesaran Bounds Test)×Εκτιμητής Δυναμικών Ελαχίστων Τετραγώνων (DOLS)×Παλινδρόμηση Ελαχίστων Τετραγώνων (OLS)×
ΠεδίοΟικονομετρίαΟικονομετρίαΟικονομετρίαΟικονομετρία
ΟικογένειαRegression modelRegression modelRegression modelRegression model
Έτος προέλευσης1990200119932019
ΔημιουργόςPhillips & Hansen (time series); Pedroni (heterogeneous panels)Pesaran, Shin & SmithStock & Watson (1993); panel extension Kao & Chiang (2001)Wooldridge (textbook treatment); classical least squares
ΤύποςCointegrating regression estimatorCointegration test / Autoregressive distributed lag modelCointegrating regression estimatorLinear regression
Θεμελιώδης πηγήPhillips, P. C. B. & Hansen, B. E. (1990). Statistical Inference in Instrumental Variables Regression with I(1) Processes. Review of Economic Studies, 57(1), 99–125. DOI ↗Pesaran, 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 ↗Stock, J. H. & Watson, M. W. (1993). A Simple Estimator of Cointegrating Vectors in Higher Order Integrated Systems. Econometrica, 61(4), 783–820. DOI ↗Wooldridge, J. M. (2019). Introductory Econometrics: A Modern Approach (7th ed.). Cengage Learning. ISBN: 978-1337558860
Εναλλακτικές ονομασίεςfully modified OLS, Phillips-Hansen FMOLS, Tam Düzeltilmiş OLS (FMOLS)Pesaran bounds test, bounds testing approach, ARDL cointegration test, ARDL Sınır Testi (Pesaran Bounds Test)DOLS, Stock-Watson dynamic OLS, dynamic least squares cointegration estimator, Dinamik OLS (DOLS)ordinary least squares, classical linear regression, linear regression, en küçük kareler regresyonu
Συναφείς5455
ΣύνοψηFully Modified OLS, introduced by Phillips and Hansen (1990), estimates the long-run coefficients of a cointegrating relationship among I(1) variables. It applies a semi-parametric correction to ordinary least squares to remove the bias that endogeneity and serial correlation otherwise induce in cointegrated time series or panel data.The 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.Dynamic OLS is a cointegrating-regression estimator introduced by Stock and Watson (1993) that recovers the long-run relationship between I(1) variables. It augments the static regression with leads and lags of the differenced regressors, correcting endogeneity bias parametrically so that the long-run coefficient can be estimated by ordinary least squares.Ordinary Least Squares is the classical linear regression method that explains a continuous outcome as a linear combination of predictors. It estimates the coefficients by minimising the sum of squared residuals, and under the Gauss-Markov assumptions these estimates are the best linear unbiased estimator (BLUE).
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ScholarGateΣύγκριση μεθόδων: FMOLS Estimator · ARDL Bounds Test · Dynamic OLS · OLS Regression. Ανακτήθηκε στις 2026-06-20 από https://scholargate.app/el/compare