data("USConsump1993")

## data from Baltagi (2002)
data("USConsump1993", package = "AER")
plot(USConsump1993, plot.type = "single", col = 1:2)

## Chapter 5 (p. 122-125)
fm <- lm(expenditure ~ income, data = USConsump1993)
summary(fm)
## Durbin-Watson test (p. 122)
dwtest(fm)
## Breusch-Godfrey test (Table 5.4, p. 124)
bgtest(fm)
## Newey-West standard errors (Table 5.5, p. 125)
coeftest(fm, vcov = NeweyWest(fm, lag = 3, prewhite = FALSE, adjust = TRUE)) 

## Chapter 8
library("strucchange")
## Recursive residuals
rr <- recresid(fm)
rr
## Recursive CUSUM test
rcus <- efp(expenditure ~ income, data = USConsump1993)
plot(rcus)
sctest(rcus)
## Harvey-Collier test
harvtest(fm)
## NOTE" Mistake in Baltagi (2002) who computes
## the t-statistic incorrectly as 0.0733 via
mean(rr)/sd(rr)/sqrt(length(rr))
## whereas it should be (as in harvtest)
mean(rr)/sd(rr) * sqrt(length(rr))

## Rainbow test
raintest(fm, center = 23)

## J test for non-nested models
library("dynlm")
fm1 <- dynlm(expenditure ~ income + L(income), data = USConsump1993)
fm2 <- dynlm(expenditure ~ income + L(expenditure), data = USConsump1993)
jtest(fm1, fm2)

## Chapter 14
## ACF and PACF for expenditures and first differences
exps <- USConsump1993[, "expenditure"]
(acf(exps))
(pacf(exps))
(acf(diff(exps)))
(pacf(diff(exps)))

## dynamic regressions, eq. (14.8)
fm <- dynlm(d(exps) ~ I(time(exps) - 1949) + L(exps))
summary(fm)