if(!requireNamespace("plm")) {
if(interactive() || is.na(Sys.getenv("_R_CHECK_PACKAGE_NAME_", NA))) {
stop("not all packages required for the example are installed")
} else q() }
## data from Stock and Watson (2007)
data("Fatalities", package = "AER")
## add fatality rate (number of traffic deaths
## per 10,000 people living in that state in that year)
Fatalities$frate <- with(Fatalities, fatal/pop * 10000)
## add discretized version of minimum legal drinking age
Fatalities$drinkagec <- cut(Fatalities$drinkage,
breaks = 18:22, include.lowest = TRUE, right = FALSE)
Fatalities$drinkagec <- relevel(Fatalities$drinkagec, ref = 4)
## any punishment?
Fatalities$punish <- with(Fatalities,
factor(jail == "yes" | service == "yes", labels = c("no", "yes")))
## plm package
library("plm")
## for comparability with Stata we use HC1 below
## p. 351, Eq. (10.2)
f1982 <- subset(Fatalities, year == "1982")
fm_1982 <- lm(frate ~ beertax, data = f1982)
coeftest(fm_1982, vcov = vcovHC(fm_1982, type = "HC1"))
## p. 353, Eq. (10.3)
f1988 <- subset(Fatalities, year == "1988")
fm_1988 <- lm(frate ~ beertax, data = f1988)
coeftest(fm_1988, vcov = vcovHC(fm_1988, type = "HC1"))
## pp. 355, Eq. (10.8)
fm_diff <- lm(I(f1988$frate - f1982$frate) ~ I(f1988$beertax - f1982$beertax))
coeftest(fm_diff, vcov = vcovHC(fm_diff, type = "HC1"))
## pp. 360, Eq. (10.15)
## (1) via formula
fm_sfe <- lm(frate ~ beertax + state - 1, data = Fatalities)
## (2) by hand
fat <- with(Fatalities,
data.frame(frates = frate - ave(frate, state),
beertaxs = beertax - ave(beertax, state)))
fm_sfe2 <- lm(frates ~ beertaxs - 1, data = fat)
## (3) via plm()
fm_sfe3 <- plm(frate ~ beertax, data = Fatalities,
index = c("state", "year"), model = "within")
coeftest(fm_sfe, vcov = vcovHC(fm_sfe, type = "HC1"))[1,]
## uses different df in sd and p-value
coeftest(fm_sfe2, vcov = vcovHC(fm_sfe2, type = "HC1"))[1,]
## uses different df in p-value
coeftest(fm_sfe3, vcov = vcovHC(fm_sfe3, type = "HC1", method = "white1"))[1,]
## pp. 363, Eq. (10.21)
## via lm()
fm_stfe <- lm(frate ~ beertax + state + year - 1, data = Fatalities)
coeftest(fm_stfe, vcov = vcovHC(fm_stfe, type = "HC1"))[1,]
## via plm()
fm_stfe2 <- plm(frate ~ beertax, data = Fatalities,
index = c("state", "year"), model = "within", effect = "twoways")
coeftest(fm_stfe2, vcov = vcovHC) ## different
## p. 368, Table 10.1, numbers refer to cols.
fm1 <- plm(frate ~ beertax, data = Fatalities, index = c("state", "year"), model = "pooling")
fm2 <- plm(frate ~ beertax, data = Fatalities, index = c("state", "year"), model = "within")
fm3 <- plm(frate ~ beertax, data = Fatalities, index = c("state", "year"), model = "within",
effect = "twoways")
fm4 <- plm(frate ~ beertax + drinkagec + jail + service + miles + unemp + log(income),
data = Fatalities, index = c("state", "year"), model = "within", effect = "twoways")
fm5 <- plm(frate ~ beertax + drinkagec + jail + service + miles,
data = Fatalities, index = c("state", "year"), model = "within", effect = "twoways")
fm6 <- plm(frate ~ beertax + drinkage + punish + miles + unemp + log(income),
data = Fatalities, index = c("state", "year"), model = "within", effect = "twoways")
fm7 <- plm(frate ~ beertax + drinkagec + jail + service + miles + unemp + log(income),
data = Fatalities, index = c("state", "year"), model = "within", effect = "twoways")
## summaries not too close, s.e.s generally too small
coeftest(fm1, vcov = vcovHC)
coeftest(fm2, vcov = vcovHC)
coeftest(fm3, vcov = vcovHC)
coeftest(fm4, vcov = vcovHC)
coeftest(fm5, vcov = vcovHC)
coeftest(fm6, vcov = vcovHC)
coeftest(fm7, vcov = vcovHC)
## TODO: Testing exclusion restrictions
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