In my research, I aim to evaluate the impact of Uber's market entry on various labor market variables in Brazil. My panel data is on a quarterly basis, encompassing labor market information for individuals across several Brazilian capitals, but my individuals only shows up 5 times at the most, since the data is a rotating sample. Moreover, I possess the specific dates when Uber commenced operations in these cities (totaling 27).
I intend to apply a dynamic difference-in-differences methodology, correlating my variable of interest with the interaction of each time period and a dummy variable representing Uber's entry.
My limitation on the number of individuals goes harder because they don't always shows up 5 times, they can show less than that and not in a uniform manner (e.g. one person can appear only two times, one in the first visit and one in the fourth visit). Leaving the sample problems aside (another source of headache..) it is possible to implement a dynamic difference-in-differences in this context? I intend to use the extended two way fixed effects by prof. Jeff Wooldridge , but i'm not sure it is doable.
My thanks in advance,
Pedro Gesteira
I intend to apply a dynamic difference-in-differences methodology, correlating my variable of interest with the interaction of each time period and a dummy variable representing Uber's entry.
My limitation on the number of individuals goes harder because they don't always shows up 5 times, they can show less than that and not in a uniform manner (e.g. one person can appear only two times, one in the first visit and one in the fourth visit). Leaving the sample problems aside (another source of headache..) it is possible to implement a dynamic difference-in-differences in this context? I intend to use the extended two way fixed effects by prof. Jeff Wooldridge , but i'm not sure it is doable.
My thanks in advance,
Pedro Gesteira
