Bandingkan kaedah

	Penentu Kumpulan Purata Diperluas (AMG)	Regresi Kuasa Dua Terkecil Biasa (OLS)	Ujian Kointegrasi Panel (Pedroni, Kao, Westerlund)	Model Kesan Tetap Data Panel
Bidang	Ekonometrik	Ekonometrik	Ekonometrik	Ekonometrik
Keluarga	Regression model	Regression model	Regression model	Regression model
Tahun asal	2010	2019	2004	2014
Pengasas	Eberhardt & Teal; Bond & Eberhardt	Wooldridge (textbook treatment); classical least squares	Pedroni; Kao; Westerlund	Hsiao (textbook treatment); within transformation of panel data
Jenis	Heterogeneous panel data estimator	Linear regression	Panel cointegration test	Panel data regression
Sumber perintis	Eberhardt, M. & Teal, F. (2010). Productivity Analysis in Global Manufacturing Production. Economics Series Working Papers, No. 515, University of Oxford.	Wooldridge, J. M. (2019). Introductory Econometrics: A Modern Approach (7th ed.). Cengage Learning. ISBN: 978-1337558860	Pedroni, P. (2004). Panel Cointegration: Asymptotic and Finite Sample Properties of Pooled Time Series Tests with an Application to the PPP Hypothesis. Econometric Theory, 20(3), 597–625.	Hsiao, C. (2014). Analysis of Panel Data (3rd ed.). Cambridge University Press.
Alias	AMG estimator, augmented mean group, Artırılmış Ortalama Grup Tahmincisi (AMG)	ordinary least squares, classical linear regression, linear regression, en küçük kareler regresyonu	Pedroni cointegration test, Kao cointegration test, Westerlund cointegration test, panel long-run equilibrium tests	fixed effects model, within estimator, panel fixed-effects regression, Panel Veri — Sabit Etkiler Modeli
Berkaitan	4	5	3	5
Ringkasan	The Augmented Mean Group estimator, developed by Eberhardt and Teal (2010), is a panel data method for estimating heterogeneous slope coefficients in the presence of cross-sectional dependence. It approximates the unobserved common dynamic process driving all units and folds it into unit-by-unit regressions, then averages the results.	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).	Panel cointegration tests check whether a set of integrated variables share a stable long-run equilibrium relationship across a panel of cross-sectional units. Pedroni (1999, 2004) provides heterogeneous-panel tests with seven statistics, Kao (1999) gives an ADF-based homogeneous-panel test, and Westerlund (2007) adds error-correction-based tests robust to structural breaks and cross-sectional dependence.	The Panel Data Fixed Effects model estimates relationships from panel data (the same units observed over several time periods) while controlling for unit- and/or time-specific effects, supporting causal inference. It is developed as the within estimator in standard treatments such as Hsiao's Analysis of Panel Data (2014).