Event Study

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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.

In the case above, comparing the average of the poor and after period can, given sufficient power, reject the hypothesis that the average of the outcome variable (in this case NDVI) before the start of the treatment is lower than the average after the treatment begins. Without additional structure, however, the difference in means is not a causally valid estimate of the treatment effect, since factors influencing the outcome variable other than the treatment confound the effect of the treatment.

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]