Good evening all,

I am trying to determine the effect of financialisation on inequality. I have panel data for 6 countries covering a period of 25 years. My dependent variable is the Gini coefficient, my independent variables that work as a proxy for financialisation are the volume of stocks traded as a percentage of GDP and the level of corporate debt as a percentage of GDP. Following several articles I read about similar subjects I've also included a lag of the dependent variable as well as several control variables including the female labour participation rate, GDP growth, unemployment rate, union density, social expenditure as a percentage of gdp, and trade as a percentage of GDP.

I ran a regression using panel-corrected standard errors, however it's been brought to my attention that dynamic panel models with fixed effects produce biased results. My supervisor recommended using GMM or Hausman-Taylor estimators instead, however by researching online I've found that GMM does not work with a N<T panel, and I don't have time-invariant variables in order to use Hausman-Taylor, so this is not possible (as far as I understand).

By taking this into account, is it possible to use one of those two? If it is, how can I reliably test which of my variables can be treated as endogenous? If it's not possible, what other type of regression could I run instead?

Thank you for your time!