\name{OECDGrowth}
\alias{OECDGrowth}

\title{OECD Macroeconomic Data}

\description{
Cross-section data on OECD countries, used for growth regressions. 
}

\usage{data("OECDGrowth")}

\format{
A data frame with 22 observations on the following 6 variables.
\describe{
  \item{gdp85}{real GDP in 1985 (per person of working age, i.e., age 15 to 65),
    in 1985 international prices.}
  \item{gdp60}{real GDP in 1960 (per person of working age, i.e., age 15 to 65),
    in 1985 international prices.}
  \item{invest}{average of annual ratios of real domestic investment to real GDP (1960--1985).}
  \item{school}{percentage of the working-age population that is in secondary school.}
  \item{randd}{average of annual ratios of gross domestic expenditure on research 
	and development to nominal GDP (of available observations during 1960--1985).}    
  \item{popgrowth}{annual population growth 1960--1985, computed as \code{log(pop85/pop60)/25}.}
}
}

\source{
Appendix 1 Nonneman and Vanhoudt (1996), except for one bad misprint:
The value of \code{school} for Norway is given as 0.01, the correct value is 0.1
(see Mankiw, Romer and Weil, 1992). \code{OECDGrowth} contains the corrected data.
}

\references{
Mankiw, N.G., Romer, D., and Weil, D.N. (1992). A Contribution to the Empirics of Economic Growth. 
\emph{Quarterly Journal of Economics}, \bold{107}, 407--437.

Nonneman, W., and Vanhoudt, P. (1996). A Further Augmentation of the Solow Model
and the Empirics of Economic Growth. \emph{Quarterly Journal of Economics}, \bold{111}, 943--953.

Zaman, A., Rousseeuw, P.J., and  Orhan, M. (2001). Econometric Applications of
High-Breakdown Robust Regression Techniques. \emph{Economics Letters}, \bold{71}, 1--8.
}

\seealso{\code{\link{GrowthDJ}}, \code{\link{GrowthSW}}}

\examples{
\dontshow{ if(!requireNamespace("MASS")) {
  if(interactive() || is.na(Sys.getenv("_R_CHECK_PACKAGE_NAME_", NA))) {
    stop("not all packages required for the example are installed")
  } else q() }}
data("OECDGrowth")

## Nonneman and Vanhoudt (1996), Table II
cor(OECDGrowth[, 3:6])
cor(log(OECDGrowth[, 3:6]))

## textbook Solow model
## Nonneman and Vanhoudt (1996), Table IV, and
## Zaman, Rousseeuw and Orhan (2001), Table 2
so_ols <- lm(log(gdp85/gdp60) ~ log(gdp60) + log(invest) + log(popgrowth+.05),
  data = OECDGrowth)
summary(so_ols)

## augmented and extended Solow growth model
## Nonneman and Vanhoudt (1996), Table IV
aso_ols <- lm(log(gdp85/gdp60) ~ log(gdp60) + log(invest) +
  log(school) + log(popgrowth+.05), data = OECDGrowth)
eso_ols <- lm(log(gdp85/gdp60) ~ log(gdp60) + log(invest) +
  log(school) + log(randd) + log(popgrowth+.05), data = OECDGrowth)

## determine unusual observations using LTS
library("MASS")
so_lts <- lqs(log(gdp85/gdp60) ~ log(gdp60) +  log(invest) + log(popgrowth+.05),
  data = OECDGrowth, psamp = 13, nsamp = "exact")

## large residuals
nok1 <- abs(residuals(so_lts))/so_lts$scale[2] > 2.5
residuals(so_lts)[nok1]/so_lts$scale[2]

## high leverage
X <- model.matrix(so_ols)[,-1]
cv <- cov.rob(X, nsamp = "exact")
mh <- sqrt(mahalanobis(X, cv$center, cv$cov))
nok2 <- mh > 2.5
mh[nok2]

## bad leverage
nok <- which(nok1 & nok2)
nok

## robust results without bad leverage points
so_rob <- update(so_ols, subset = -nok)
summary(so_rob)
## This is similar to Zaman, Rousseeuw and Orhan (2001), Table 2
## but uses exact computations (and not sub-optimal results
## for the robust functions lqs and cov.rob)
}

\keyword{datasets}
