Investment {sandwich} | R Documentation |
US data for fitting an investment equation.
data(Investment)
An annual time series from 1963 to 1982 with 7 variables.
Table 15.1 in Greene (1993)
Greene W.H. (1993), Econometric Analysis, 2nd edition. Macmillan Publishing Company, New York.
Executive Office of the President (1984), Economic Report of the President. US Government Printing Office, Washington, DC.
## Willam H. Greene, Econometric Analysis, 2nd Ed. ## Chapter 15 ## load data set, p. 411, Table 15.1 data(Investment) ## fit linear model, p. 412, Table 15.2 fm <- lm(RealInv ~ RealGNP + RealInt, data = Investment) summary(fm) ## visualize residuals, p. 412, Figure 15.1 plot(ts(residuals(fm), start = 1964), type = "b", pch = 19, ylim = c(-35, 35), ylab = "Residuals") sigma <- sqrt(sum(residuals(fm)^2)/fm$df.residual) ## maybe used df = 26 instead of 16 ?? abline(h = c(-2, 0, 2) * sigma, lty = 2) if(require(lmtest)) { ## Newey-West covariances, Example 15.3 coeftest(fm, vcov = NeweyWest(fm, lag = 4)) ## Note, that the following is equivalent: coeftest(fm, vcov = kernHAC(fm, kernel = "Bartlett", bw = 5, prewhite = FALSE, adjust = FALSE)) ## Durbin-Watson test, p. 424, Example 15.4 dwtest(fm) ## Breusch-Godfrey test, p. 427, Example 15.6 bgtest(fm, order = 4) } ## visualize fitted series plot(Investment[, "RealInv"], type = "b", pch = 19, ylab = "Real investment") lines(ts(fitted(fm), start = 1964), col = 4) ## 3-d visualization of fitted model if(require(scatterplot3d)) { s3d <- scatterplot3d(Investment[,c(5,7,6)], type = "b", angle = 65, scale.y = 1, pch = 16) s3d$plane3d(fm, lty.box = "solid", col = 4) }