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Regresi Kuasa Dua Terkecil Biasa (OLS)×Reka Bentuk Pecahan Regresi (RDD)×
BidangEkonometrikInferens Kausal
KeluargaRegression modelRegression model
Tahun asal20192008
PengasasWooldridge (textbook treatment); classical least squaresImbens & Lemieux (guide to practice); Cattaneo, Idrobo & Titiunik (practical introduction)
JenisLinear regressionQuasi-experimental causal design
Sumber perintisWooldridge, J. M. (2019). Introductory Econometrics: A Modern Approach (7th ed.). Cengage Learning. ISBN: 978-1337558860Imbens, G. W., & Lemieux, T. (2008). Regression Discontinuity Designs: A Guide to Practice. Journal of Econometrics, 142(2), 615-635. DOI ↗
Aliasordinary least squares, classical linear regression, linear regression, en küçük kareler regresyonuRDD, regression discontinuity design, sharp RDD, fuzzy RDD
Berkaitan55
RingkasanOrdinary 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).Regression Discontinuity Design is a quasi-experimental method that identifies a causal effect by locally comparing units just above and just below a cutoff on a continuous assignment (running) variable. Formalised for applied work by Imbens and Lemieux (2008) and developed as a practical framework by Cattaneo, Idrobo, and Titiunik (2020), it estimates a local average treatment effect (LATE) at the threshold.
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ScholarGateBandingkan kaedah: OLS Regression · Regression Discontinuity. Dicapai 2026-06-18 daripada https://scholargate.app/ms/compare