# NOT RUN {
#### Example 2-6
## ------------------------------------------------------------------------
data("TexasElectr", package = "pder")
library("plm")
TexasElectr$cost <- with(TexasElectr, explab + expfuel + expcap)
TE <- pdata.frame(TexasElectr)
summary(log(TE$output))
ercomp(log(cost) ~ log(output), TE)
models <- c("within", "random", "pooling", "between")
sapply(models, function(x)
coef(plm(log(cost) ~ log(output), TE, model = x))["log(output)"])
#### Example 3-2
## ------------------------------------------------------------------------
data("TexasElectr", package = "pder")
library("dplyr")
TexasElectr <- mutate(TexasElectr,
pf = log(pfuel / mean(pfuel)),
pl = log(plab / mean(plab)) - pf,
pk = log(pcap / mean(pcap)) - pf)
## ------------------------------------------------------------------------
TexasElectr <- mutate(TexasElectr, q = log(output / mean(output)))
## ------------------------------------------------------------------------
TexasElectr <- mutate(TexasElectr,
C = expfuel + explab + expcap,
sl = explab / C,
sk = expcap / C,
C = log(C / mean(C)) - pf)
## ------------------------------------------------------------------------
TexasElectr <- mutate(TexasElectr,
pll = 1/2 * pl ^ 2,
plk = pl * pk,
pkk = 1/2 * pk ^ 2,
qq = 1/2 * q ^ 2)
## ------------------------------------------------------------------------
cost <- C ~ pl + pk + q + pll + plk + pkk + qq
shlab <- sl ~ pl + pk
shcap <- sk ~ pl + pk
## ------------------------------------------------------------------------
R <- matrix(0, nrow = 6, ncol = 14)
R[1, 2] <- R[2, 3] <- R[3, 5] <- R[4, 6] <- R[5, 6] <- R[6, 7] <- 1
R[1, 9] <- R[2, 12] <- R[3, 10] <- R[4, 11] <- R[5, 13] <- R[6, 14] <- -1
## ------------------------------------------------------------------------
z <- plm(list(cost = C ~ pl + pk + q + pll + plk + pkk + qq,
shlab = sl ~ pl + pk,
shcap = sk ~ pl + pk),
TexasElectr, model = "random",
restrict.matrix = R)
summary(z)
# }
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