Hi
I'm estimating a Gravity Model for Italian regions export using PPMLHDFE in a panel dataset
For now my model is exports_trade(euro) = b_1[ln_GDP_exporter_region(logs of GDPs in Euro)] + b_2[ln_GDPs_importer_country(logs of GDPs in Dollars)] + b_3[ln_dist_reg_country(logs of distance in kilometers)] + a(i.region#c.year i.country_id#c.year) - the latter term is for absorbing region-time country-time fixed effects
I obtained these estimates:
exports_trade(euro) = 2.11[ln_GDP_exporter_region(logs of GDPs in Euro)] + 0.65[ln_GDPs_importer_country(logs of GDPs in Dollars)] -0.63[ln_dist_reg_country(logs of distance in kilometers)]
These coefficient have to be interpreted as elasticities 1%+ -> 2.11% for the first coefficient for example
Is there a way to convert these elasticieties to volume trade effects in monetary terms and so evaluate marginal effects of covariates in terms of Euro variation in exports?
Thanks
ppmlhdfe
I'm estimating a Gravity Model for Italian regions export using PPMLHDFE in a panel dataset
For now my model is exports_trade(euro) = b_1[ln_GDP_exporter_region(logs of GDPs in Euro)] + b_2[ln_GDPs_importer_country(logs of GDPs in Dollars)] + b_3[ln_dist_reg_country(logs of distance in kilometers)] + a(i.region#c.year i.country_id#c.year) - the latter term is for absorbing region-time country-time fixed effects
I obtained these estimates:
exports_trade(euro) = 2.11[ln_GDP_exporter_region(logs of GDPs in Euro)] + 0.65[ln_GDPs_importer_country(logs of GDPs in Dollars)] -0.63[ln_dist_reg_country(logs of distance in kilometers)]
These coefficient have to be interpreted as elasticities 1%+ -> 2.11% for the first coefficient for example
Is there a way to convert these elasticieties to volume trade effects in monetary terms and so evaluate marginal effects of covariates in terms of Euro variation in exports?
Thanks
ppmlhdfe
