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رگرسیون کوانتایل×رگرسیون حداقل مربعات معمولی (OLS)×مدل اثرات ثابت داده‌های پانل×
حوزهاقتصادسنجیاقتصادسنجیاقتصادسنجی
خانوادهRegression modelRegression modelRegression model
سال پیدایش197820192014
پدیدآورKoenker & BassettWooldridge (textbook treatment); classical least squaresHsiao (textbook treatment); within transformation of panel data
نوعConditional quantile regressionLinear regressionPanel data regression
منبع بنیادینKoenker, R. & Bassett, G., Jr. (1978). Regression Quantiles. Econometrica, 46(1), 33-50. DOI ↗Wooldridge, 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 ↗
نام‌های دیگرconditional quantile regression, regression quantiles, Kantil Regresyonordinary least squares, classical linear regression, linear regression, en küçük kareler regresyonufixed effects model, within estimator, panel fixed-effects regression, Panel Veri — Sabit Etkiler Modeli
مرتبط555
خلاصهQuantile 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.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).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).
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ScholarGateمقایسهٔ روش‌ها: Quantile Regression · OLS Regression · Panel Fixed Effects. بازیابی‌شده در 2026-06-18 از https://scholargate.app/fa/compare