Difference between revisions of "Event Study"

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== Additional Resources ==
== Additional Resources ==
For a review of event study, including multiple events, in finance,


Tutorial of event study in stata [http://dss.princeton.edu/online_help/stats_packages/stata/eventstudy.html]
Tutorial of event study in stata [http://dss.princeton.edu/online_help/stats_packages/stata/eventstudy.html]
[[Category: Impact Evaluation Design ]]
[[Category: Impact Evaluation Design ]]

Revision as of 19:33, 21 November 2017


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An event study is a statistical method to assess the impact of an event on an outcome of interest. It can be used as a descriptive tool to describe the dynamic of the outcome of interest before and after the event or in combination regression discontinuity techniques around the time of the event to evaluate its impact. This method has been used mainly in finance to study the impact of specific events on firms value, as it relies on having high frequency data.

Guidelines

As a descriptive tool

Graphically, an event study will represent one or more time serie before and after the event. For example, if we study the impact of an intervention giving improved seeds and cattle to farmers, we can plot land yield before and fater the intervention as below. NDVI eventstudy.png

Combined with RD

To estimate the impact of the introduction of improved seeds on land yield, we can use Regression Discontinuity techniques by compare the average yield in a given time window before and after the event.

Attention to the time window and the frequency of the data is crucial: if the window is too large, the measured effect might aggregate the effect of the treatment and the effects of other factors, such as a change in pluviometry, introduction of new technologies,... If the window is too small, the sample size might be low such that the estimate will lack precision.

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This article is part of the topic Impact Evaluation Design


Additional Resources

Tutorial of event study in stata [1]