pglm fixed effect Poisson model with offset

Question

I would like to run a fixed effect Poisson model with panel data in R, with a count variable as the outcome, and the log of the population as an offset variable (i.e. modeling a rate). However, using the example dataset below, I get the same results when I run the two models m1 and m2. I'd be grateful if anyone could point out what I'm doing wrong in terms of specifying m1, or offer a solution using a different package? Many thanks

library(AER)
data(Fatalities)

library(pglm)

m1 <- pglm(fatal ~ beertax + as.factor(year) + offset(log(pop)), index = c("state"), model = "within", effect="individual", data = Fatalities, family = poisson)
summary(m1)

m2 <- pglm(fatal ~ beertax + as.factor(year), index = c("state"), model = "within", effect="individual", data = Fatalities, family = poisson)
summary(m2)

Hi Matthew, no I haven't found a solution yet unfortunately. Using Stata to run these models instead — Christina
– Christina, Commented Feb 18, 2020 at 9:29

bayescraze · Accepted Answer · 2021-05-02 14:58:56Z

1

One direct solution is by using glm instead, with dummy variables for year and state:

fit_model <- glm(fatal ~ beertax + as.factor(year) + as.factor(state) + offset(log(pop)) , data = Fatalities, family = poisson)

which gives the same result in STATA (at least using this command: xtpoisson fatal beertax year1-year7, fe offset(log_pop)).

This approach is not feasible when the number of states is reasonably large. In CRAN, there is the novel fixest package (https://cran.r-project.org/web/packages/fixest/index.html) that provides a fast solution with robust standard errors.

edited May 2, 2021 at 14:58

answered Apr 10, 2021 at 21:51

bayescraze

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