We are working with stock return data and have a conditional double-sort first on firm size (characteristic 1) into terciles and then on whether an event has occurred to this firm within the past year (characteristic 2). Event occurrence is not evenly distributed across size terciles.
How can we test whether the average return difference between states of event occurrence is itself different in small vs large firm terciles? In another word, how can we test whether the return difference along characteristic 2 is different across terciles of characteristic 1?
For example, in the tercile with the biggest firms, 500 firms experienced the event, and 300 firms did not; in the tercile with the smallest firms, 600 firms experienced the event, and 700 firms did not. Say an unpaired t-test among the biggest firms produces an average return difference of 3% with a standard error of 0.4%, and an unpaired t-test among the smallest firms produces an average return difference of 2% with a standard error of 0.5%. How can we test whether the 3% is statistically significantly different from the 2%?
Thank you very much for your time and help in advance!
How can we test whether the average return difference between states of event occurrence is itself different in small vs large firm terciles? In another word, how can we test whether the return difference along characteristic 2 is different across terciles of characteristic 1?
For example, in the tercile with the biggest firms, 500 firms experienced the event, and 300 firms did not; in the tercile with the smallest firms, 600 firms experienced the event, and 700 firms did not. Say an unpaired t-test among the biggest firms produces an average return difference of 3% with a standard error of 0.4%, and an unpaired t-test among the smallest firms produces an average return difference of 2% with a standard error of 0.5%. How can we test whether the 3% is statistically significantly different from the 2%?
Thank you very much for your time and help in advance!
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