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رگرسیون حداقل مربعات معمولی (OLS)×مدل اثرات ثابت داده‌های پانل×رگرسیون کوانتایل×
حوزهاقتصادسنجیاقتصادسنجیاقتصادسنجی
خانوادهRegression modelRegression modelRegression model
سال پیدایش201920141978
پدیدآورWooldridge (textbook treatment); classical least squaresHsiao (textbook treatment); within transformation of panel dataKoenker & Bassett
نوعLinear regressionPanel data regressionConditional quantile regression
منبع بنیادینWooldridge, J. M. (2019). Introductory Econometrics: A Modern Approach (7th ed.). Cengage Learning. ISBN: 978-1337558860Hsiao, C. (2014). Analysis of Panel Data (3rd ed.). Cambridge University Press. DOI ↗Koenker, R. & Bassett, G., Jr. (1978). Regression Quantiles. Econometrica, 46(1), 33-50. DOI ↗
نام‌های دیگرordinary least squares, classical linear regression, linear regression, en küçük kareler regresyonufixed effects model, within estimator, panel fixed-effects regression, Panel Veri — Sabit Etkiler Modeliconditional quantile regression, regression quantiles, Kantil Regresyon
مرتبط555
خلاصهOrdinary 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).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).Quantile regression models conditional quantiles of an outcome - the median, the 25th or 75th percentile, and so on - rather than the conditional mean that OLS targets. Introduced by Koenker and Bassett in 1978, it reveals how predictors act across the whole distribution, including its tails.
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ScholarGateمقایسهٔ روش‌ها: OLS Regression · Panel Fixed Effects · Quantile Regression. بازیابی‌شده در 2026-06-17 از https://scholargate.app/fa/compare