পদ্ধতির তুলনা করুন

	ডাইনামিক অর্ডিনারি লিস্ট স্কোয়ারস (DOLS) এস্টিমেটর	বর্ধিত গড় গোষ্ঠী (AMG) অনুমানকারী	সাধারণ ন্যূনতম বর্গক্ষেত্র (OLS) রিগ্রেশন	প্যানেল কোইন্টিগ্রেশন পরীক্ষা (পেডরনি, কাও, ওয়েস্টারলাউন্ড)
ক্ষেত্র	অর্থমিতি	অর্থমিতি	অর্থমিতি	অর্থমিতি
পরিবার	Regression model	Regression model	Regression model	Regression model
উদ্ভবের বছর	1993	2010	2019	2004
প্রবর্তক	Stock & Watson (1993); panel extension Kao & Chiang (2001)	Eberhardt & Teal; Bond & Eberhardt	Wooldridge (textbook treatment); classical least squares	Pedroni; Kao; Westerlund
ধরন	Cointegrating regression estimator	Heterogeneous panel data estimator	Linear regression	Panel cointegration test
মৌলিক উৎস	Stock, J. H. & Watson, M. W. (1993). A Simple Estimator of Cointegrating Vectors in Higher Order Integrated Systems. Econometrica, 61(4), 783–820.	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.
অপর নাম	DOLS, Stock-Watson dynamic OLS, dynamic least squares cointegration estimator, Dinamik OLS (DOLS)	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
সম্পর্কিত	5	4	5	3
সারসংক্ষেপ	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.	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.