Regression Discontinuity Design
Lesson 1 of 2
  1. 1
    Research suggests that individuals put more into retirement accounts or pension plans if their employer matches a portion of their contributions. Imagine that a country’s legislature passes a law…
  2. 2
    We need a little more vocabulary before we can dive into more details about Regression Discontinuity Design. Sometimes treatment group assignment is dictated by one continuous variable known as a …
  3. 3
    The forcing variable cutpoint can either be exact or not exact: - If the cutpoint is exact, the probability of treatment changes from zero to one at the cutpoint. In other words, all observations…
  4. 4
    We saw that our employee contribution example requires a sharp regression discontinuity design: all companies with at least 300 employees have a contribution matching program, and all companies wit…
  5. 5
    A scatter plot of our data allows us to check certain RDD conditions visually. We can see whether we have a sharp or fuzzy cutoff. We can also use the plot to check for a discontinuity — a …
  6. 6
    In RDD, we know we need to look at points near the cutoff to find treatment and control groups that are similar. But how do we know how close to look? The bandwidth describes the distance on eit…
  7. 7
    The use of a bandwidth impacts the type of causal estimand we can calculate in a regression discontinuity design analysis. Because the RDD approach uses a subset of the full dataset, we can only es…
  8. 8
    As we’ve seen, the advantages of regression discontinuity design are that RDD: - Is a simple method to understand and implement. - Avoids using a complicated regression model for the entire data…
  9. 9
    In this lesson, we showed that the implementation of an employee-sponsored retirement matching program led to an increase in average monthly employee contributions. We learned a lot about regressi…

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