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Kikadiriaji cha OLS Iliyorekebishwa Kikamilifu (FMOLS)×Kipimo cha Vikomo vya ARDL (Kipimo cha Vikomo cha Pesaran)×Njia ya Athari za Kawaida Zinazohusiana za Kikundi cha Maana (CCEMG)×Urejeshaji wa Njia ya Viwango Vidogo vya Kawaida (OLS)×
NyanjaEkonometrikiEkonometrikiEkonometrikiEkonometriki
FamiliaRegression modelRegression modelRegression modelRegression model
Mwaka wa asili1990200120062019
MwanzilishiPhillips & Hansen (time series); Pedroni (heterogeneous panels)Pesaran, Shin & SmithM. Hashem PesaranWooldridge (textbook treatment); classical least squares
AinaCointegrating regression estimatorCointegration test / Autoregressive distributed lag modelHeterogeneous panel estimatorLinear regression
Chanzo asiliaPhillips, 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 ↗Pesaran, M. H. (2006). Estimation and Inference in Large Heterogeneous Panels with a Multifactor Error Structure. Econometrica, 74(4), 967-1012. DOI ↗Wooldridge, J. M. (2019). Introductory Econometrics: A Modern Approach (7th ed.). Cengage Learning. ISBN: 978-1337558860
Majina mbadalafully modified OLS, Phillips-Hansen FMOLS, Tam Düzeltilmiş OLS (FMOLS)Pesaran bounds test, bounds testing approach, ARDL cointegration test, ARDL Sınır Testi (Pesaran Bounds Test)common correlated effects, CCE, CCEMG, Pesaran CCE estimatorordinary least squares, classical linear regression, linear regression, en küçük kareler regresyonu
Zinazohusiana5445
MuhtasariFully 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.The Common Correlated Effects Mean Group estimator, introduced by Pesaran in 2006, is a heterogeneous panel-data estimator that controls for cross-sectional dependence by approximating unobserved common factors with the cross-section averages of the variables. It remains consistent when the slope coefficients differ across units.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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ScholarGateLinganisha mbinu: FMOLS Estimator · ARDL Bounds Test · CCEMG Estimator · OLS Regression. Imepatikana 2026-06-20 kutoka https://scholargate.app/sw/compare