Effect of Mathematics Remediation on Academic Achievement – A Regression Discontinuity Approach

Evaluating the impact of partial driving restrictions on local air quality in Chongqing using regression discontinuity design

“…Theoretically, since RDD is characterized by a cutoff point where the probability of an individual being processed jumps from 0 to 1 (Zhang et al., 2020), it is well fitted with scenario of the driving restriction policy as the driving is prohibited after the policy is activated, representing by changing from 0 to 1 at the cutoff point, in the meanwhile, other variables correspondingly and continuously change along with timeline. Furthermore, due to the fact that RDD arbitrarily limits the samples into a narrow time window around the cutoff point, the impacts from those unobserved long-term factors, such as oil prices and other related policies, remain the same and are unchanged in the short interval, and would not result in biased estimation and endogenety problem (Baranyi and Molontay, 2019; Davis, 2008). And also, RDD simplifies the construction of the model by bypassing the problems concerning model specification such as which variables should be included and their functional forms (Hahn et al., 2001).…”

“…Consequently, this method is widely used in the evaluation of policy effect in the field of social sciences. At present, some studies have already successfully implemented RDD to test the impacts of various types of driving restrictions on air quality in megacities over the world (Baranyi and Molontay, 2019;Cao et al, 2014;Davis, 2008;Huang et al, 2017;Lu, 2016;Sun et al, 2014;2010;Viard and Fu, 2015;Zhang et al, 2020). For example, Davis (2008) measures the effectiveness of Mexico city's driving restrictions "Hoy No Circula" on air quality using regression discontinuity.…”