Scrutinizing the Monotonicity Assumption in IV and fuzzy RD designs*
| Autor: | Mario Fiorini, Katrien Stevens |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2021 |
| Předmět: |
Statistics and Probability
Economics and Econometrics Interpretation (logic) Computer science Economics 05 social sciences Instrumental variable Sorting Monotonic function Fuzzy logic Discontinuity (linguistics) Fuzzy regression 0502 economics and business 050207 economics Statistics Probability and Uncertainty Set (psychology) Mathematical economics Social Sciences (miscellaneous) 14 Economics 050205 econometrics |
| Popis: | Whenever treatment effects are heterogeneous, and there is sorting into treatment based on the gain, monotonicity is a condition that both instrumental variable (IV) and fuzzy regression discontinuity (RD) designs must satisfy for their estimate to be interpretable as a local average treatment effect. However, applied economic work often omits a discussion of this important assumption. A possible explanation for this missing step is the lack of a clear framework to think about monotonicity in practice. In this paper, we use an extended Roy model to provide insights into the interpretation of IV and fuzzy RD estimates under various degrees of treatment effect heterogeneity, sorting on gain and violation of monotonicity. We then extend our analysis to two applied settings to illustrate how monotonicity can be investigated using a mix of economic insights, data patterns and formal tests. For both settings, we use a Roy model to interpret the estimate even in the absence of monotonicity. We conclude with a set of recommendations for the applied researcher. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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