Linganisha mbinu

	Usanifu wa Tofauti-katika-Usitishaji	Urejeshaji wa Njia ya Viwango Vidogo vya Kawaida (OLS)
Nyanja	Uhitimisho wa Kisababishi	Ekonometriki
Familia	Regression model	Regression model
Mwaka wa asili	2016	2019
Mwanzilishi	Grembi, Nannicini & Troiano	Wooldridge (textbook treatment); classical least squares
Aina	Hybrid quasi-experimental causal design (RDD + DID)	Linear regression
Chanzo asilia	Grembi, V., Nannicini, T. & Troiano, U. (2016). Do Fiscal Rules Matter? A Difference-in-Discontinuities Design. American Economic Journal: Applied Economics, 8(3), 1-30.	Wooldridge, J. M. (2019). Introductory Econometrics: A Modern Approach (7th ed.). Cengage Learning. ISBN: 978-1337558860
Majina mbadala	diff-in-disc, DiD-RDD, Süreksizliklerde Fark (Difference-in-Discontinuities)	ordinary least squares, classical linear regression, linear regression, en küçük kareler regresyonu
Zinazohusiana	5	5
Muhtasari	Difference-in-Discontinuities is a hybrid quasi-experimental design that fuses regression discontinuity (RDD) with difference-in-differences (DID), introduced by Grembi, Nannicini and Troiano (2016). It compares the discontinuity at the same cutoff value across two periods to isolate a causal effect.	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).