This study shows how heterogeneous slopes or trends can bias conventional FE estimators, and demonstrates how Fixed Effects Individual Slopes estimators in combination with two specification tests can overcome this bias.
We investigate the link between public childcare and FLP, using different indicators of childcare and accounting for heterogeneous time trends and regional heterogeneity.
Building on an original dataset including georeferenced data of 6,570 highly polluting industrial facilities over the period from 2008 to 2017 along with income and demographic data of 4,455 municipalities, we investigate socio-demographic changes before and after the occurrence of new facilities.
This package implements Fixed Effects Individual Slopes Estimators and related test statistics in R.