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Оцінювач Fully Modified OLS (FMOLS)×Тест меж ARDL (Тест меж Pesaran)×Оцінювач динамічних звичайних найменших квадратів (DOLS)×
ГалузьЕконометрикаЕконометрикаЕконометрика
РодинаRegression modelRegression modelRegression model
Рік появи199020011993
Автор методуPhillips & Hansen (time series); Pedroni (heterogeneous panels)Pesaran, Shin & SmithStock & Watson (1993); panel extension Kao & Chiang (2001)
ТипCointegrating regression estimatorCointegration test / Autoregressive distributed lag modelCointegrating regression estimator
Основоположне джерелоPhillips, 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 ↗
Інші назвиfully 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)
Пов'язані545
ПідсумокFully 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.
ScholarGateНабір даних
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ScholarGateПорівняння методів: FMOLS Estimator · ARDL Bounds Test · Dynamic OLS. Отримано 2026-06-20 з https://scholargate.app/uk/compare