Working Paper: NBER ID: w16949
Authors: Erik Snowberg; Justin Wolfers; Eric Zitzewitz
Abstract: This review paper articulates the relationship between prediction market data and event studies, with a special focus on applications in political economy. Event studies have been used to address a variety of political economy questions from the economic effects of party control of government to the importance of complex rules in congressional committees. However, the results of event studies are notoriously sensitive to both choices made by researchers and external events. Specifically, event studies will generally produce different results depending on three interrelated things: which event window is chosen, the prior probability assigned to an event at the beginning of the event window, and the presence or absence of other events during the event window. In this paper we show how each of these may bias the results of event studies, and how prediction markets can mitigate these biases.
Keywords: prediction markets; event studies; political economy; biases; economic impact
JEL Codes: A2; C5; D72; G14; H50
Edges that are evidenced by causal inference methods are in orange, and the rest are in light blue.
| Cause | Effect |
|---|---|
| Choice of event windows (G14) | Biased results (C83) |
| Different event windows (G14) | Conclusion drawn from the study (C20) |
| Prior probability assigned to a political event (D79) | Different interpretations of the same data (Y10) |
| Integrating prediction markets into event studies (G14) | More accurate estimates of the economic effects of political events (E65) |
| Prediction markets provide a more reliable measure of prior probabilities (D81) | More accurate estimates of economic effects (C13) |
| Prediction markets help delineate the impacts of unrelated events (D89) | More accurate estimates of economic effects (C13) |