USGasG {AER} | R Documentation |
Time series data on the US gasoline market.
data("USGasG")
An annual multiple time series from 1960 to 1995 with 10 variables.
Online complements to Greene (2003). Table F2.2.
http://pages.stern.nyu.edu/~wgreene/Text/tables/tablelist5.htm
Greene, W.H. (2003). Econometric Analysis, 5th edition. Upper Saddle River, NJ: Prentice Hall.
data("USGasG") plot(USGasG) ## Greene (2003) ## Example 2.3 fm <- lm(log(gas/population) ~ log(price) + log(income) + log(newcar) + log(usedcar), data = as.data.frame(USGasG)) summary(fm) ## Example 4.4 ## estimates and standard errors (note different offset for intercept) coef(fm) sqrt(diag(vcov(fm))) ## confidence interval confint(fm, parm = "log(income)") ## test linear hypothesis linear.hypothesis(fm, "log(income) = 1") ## Example 7.6 ## re-used in Example 8.3 trend <- 1:nrow(USGasG) shock <- factor(time(USGasG) > 1973, levels = c(FALSE, TRUE), labels = c("before", "after")) ## 1960-1995 fm1 <- lm(log(gas/population) ~ log(income) + log(price) + log(newcar) + log(usedcar) + trend, data = as.data.frame(USGasG)) summary(fm1) ## pooled fm2 <- lm(log(gas/population) ~ shock + log(income) + log(price) + log(newcar) + log(usedcar) + trend, data = as.data.frame(USGasG)) summary(fm2) ## segmented fm3 <- lm(log(gas/population) ~ shock/(log(income) + log(price) + log(newcar) + log(usedcar) + trend), data = as.data.frame(USGasG)) summary(fm3) ## Chow test anova(fm3, fm1) sctest(log(gas/population) ~ log(income) + log(price) + log(newcar) + log(usedcar) + trend, data = USGasG, point = c(1973, 1), type = "Chow") ## Recursive CUSUM test rcus <- efp(log(gas/population) ~ log(income) + log(price) + log(newcar) + log(usedcar) + trend, data = USGasG, type = "Rec-CUSUM") plot(rcus) sctest(rcus) ## Note: Greene's remark that the break is in 1984 (where the process crosses its boundary) ## is wrong. The break appears to be no later than 1976. ## More examples can be found in: ## help("Greene2003")