Linganisha mbinu

	Muundo wa Kukatizwa kwa Regressheni (RDD)	Urejeshaji wa Njia ya Viwango Vidogo vya Kawaida (OLS)
Nyanja	Uhitimisho wa Kisababishi	Ekonometriki
Familia	Regression model	Regression model
Mwaka wa asili	2008	2019
Mwanzilishi	Imbens & Lemieux (guide to practice); Cattaneo, Idrobo & Titiunik (practical introduction)	Wooldridge (textbook treatment); classical least squares
Aina	Quasi-experimental causal design	Linear regression
Chanzo asilia	Imbens, G. W., & Lemieux, T. (2008). Regression Discontinuity Designs: A Guide to Practice. Journal of Econometrics, 142(2), 615-635.	Wooldridge, J. M. (2019). Introductory Econometrics: A Modern Approach (7th ed.). Cengage Learning. ISBN: 978-1337558860
Majina mbadala	RDD, regression discontinuity design, sharp RDD, fuzzy RDD	ordinary least squares, classical linear regression, linear regression, en küçük kareler regresyonu
Zinazohusiana	5	5
Muhtasari	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.	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).