USGasG: US Gasoline Market Data (1960-1995, Greene)
In AER: Applied Econometrics with R

USGasG

R Documentation

US Gasoline Market Data (1960–1995, Greene)

Description

Time series data on the US gasoline market.

Usage

data("USGasG")

Format

An annual multiple time series from 1960 to 1995 with 10 variables.

gas: Total US gasoline consumption (computed as total expenditure divided by price index).
price: Price index for gasoline.
income: Per capita disposable income.
newcar: Price index for new cars.
usedcar: Price index for used cars.
transport: Price index for public transportation.
durable: Aggregate price index for consumer durables.
nondurable: Aggregate price index for consumer nondurables.
service: Aggregate price index for consumer services.
population: US total population in millions.

Source

Online complements to Greene (2003). Table F2.2.

https://pages.stern.nyu.edu/~wgreene/Text/tables/tablelist5.htm

References

Greene, W.H. (2003). Econometric Analysis, 5th edition. Upper Saddle River, NJ: Prentice Hall.

Examples


data("USGasG", package = "AER")
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
linearHypothesis(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)
library("strucchange")
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")

AER documentation built on Sept. 28, 2024, 9:07 a.m.