####### Example 1: Estimate PCSEs for a balanced dataset. ######### # Package library("pcse") options(digits=3) # Load the data. data("agl") # OLS Estimation for a model of growth in OECD countries agl.lm <- lm(growth ~ lagg1 + opengdp + openex + openimp + central + leftc + inter + as.factor(year), data=agl) summary(agl.lm) # Estimate Panel-Corrected Standard-Errors and summarize the results. agl.pcse <- pcse(agl.lm, groupN=agl$country, groupT=agl$year) summary(agl.pcse) ####### Example 2: Estimate PCSEs for an unbalanced dataset. ######### # Load the data. data("aglUn") # Note: this is the orignal agl dataset with 10 observations randomly deleted. # OLS Estimation for a model of growth in OECD countries. aglUn.lm <- lm(growth ~ lagg1 + opengdp + openex + openimp + central + leftc + inter + as.factor(year), data=aglUn) summary(aglUn.lm) # Estimate Panel-Corrected Standard-Errors with Pairwise Selection # and summarize the results. aglUn.pcse1 <- pcse(aglUn.lm, groupN=aglUn$country, groupT=aglUn$year, pairwise=TRUE) summary(aglUn.pcse1) # Estimate Panel-Corrected Standard-Errors with Casewise Selection # and summarize the results. aglUn.pcse2 <- pcse(aglUn.lm, groupN=aglUn$country, groupT=aglUn$year, pairwise=FALSE) summary(aglUn.pcse2)