I'm new to econometrics and need some help with my research. I'm working with research that has cross-sectional data. I have collected information about publicly-listed banks in many countries. For example, for each bank I collected the following information:



I have 619 banks in 58 different countries. In my research I want to test how variation in bank characteristics (Tier 1,Tangible Equity, etc) affected bank stock returns during crisis time. I write my equation as follows:

BPb,c = 𝑎 + ð›―1RETURNS_2019b + ð›―2TIER_1b + ð›―3DEPb,+ ð›―4NPLb + ð›―5NONIIb + ð›―6LIQASSb + ð›―8SIZEb + ð›―9DENb + ð›―10ROAEb + ð›―11 LOANSb + ð›―3*TANEQb + ð›ūc + ub,c

Where BPb,c is the performance of a bank b in country c. The coefficients 𝑎, ð›―, represent vectors of coefficient estimates and ub.c is the error term. ð›ūc - country fixed effects.

All the literature I read fixed effects is applied to panel data models. However, I follow the paper Beltrati and Stulz (2012), which to my understanding has cross-sectional data as well and in their research, they apply fixed effects and use standard errors clustered by country. Can someone help me if this approach using country fixed effects and clustering error by coutnry having cross-sectional data is logical? Also, perhaps someone could advise how to implement this model with stata.

Many thanks