Regression Discontinuity Design (RDD)

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Q1 (16 points) “Regression Discontinuity Design (RDD) is a quasi-experimental impact evaluation method used to evaluate programs that have a cutoff point determining who is eligible to participate.”

A. (4 points) Please use one of the examples below to make an argument that why it is (probably) a good RD design? (First start with running variable, cutoff, treatment, outcome and then clarify what is the underlying assumption. ) Examples: Whether you pass a test; Whether you are eligible for a program; Who wins an election; Which school district you reside in; Whether some punishment strategy is enacted

B. (4 points) In the Watering Down Environmental Regulation in China, He, Wang and Zhang (2020) estimate the effect of environmental regulation on firm productivity using a spatial regression discontinuity design implicit in China’s water quality monitoring system. Their research design is demonstrated by the graph below, please explain what is the running variable
and what is the cutoff? (He, Wang and Zhang, 2020)

C. (4 points) “In the 1990s, The water quality monitoring stations were considered to serve mostly scientific rather than regulatory purposes, and the locations of the monitoring stations were mainly determined by hydrological factors……. In 2003, the central government imposed high political stakes on the readings of water monitoring stations, the local officials would have strong incentives to regulate polluters base on the readings from monitoring network.”
Do you think the argument above validates the research assumption or not? Why?

D. (4 points) What is the secondary effect of China’s water quality regulation?