Choosing Among Alternative Long-Run Event-Study Techniques

Abstract

This paper reviews the long-run event-study debate by outlining the strengths and weakness of the most commonly used alternative techniques. The fist part of the discussion highlights that prior literature has failed to provide a single risk-adjusted model of long-run abnormal returns with no biases. Subsequently, the paper provides guidance on how one can choose among pertinent alternative techniques. As a conclusion, researchers ought to choose among alternative techniques after considering issues such as (i) the nature of dataset and market of interest, (ii) the event type (regulatory or corporate), (iii) returns' time-interval, (iv) association of the event with accounting data, (v) sample characteristics and prior evidence regarding similar events, as well as (vi) risk changes following the event. Robustness tests are essential, while the road for further research regarding the appropriate technique(s) is open.