GrowthDJ | R Documentation |

Growth regression data as provided by Durlauf & Johnson (1995).

data("GrowthDJ")

A data frame containing 121 observations on 10 variables.

- oil
factor. Is the country an oil-producing country?

- inter
factor. Does the country have better quality data?

- oecd
factor. Is the country a member of the OECD?

- gdp60
Per capita GDP in 1960.

- gdp85
Per capita GDP in 1985.

- gdpgrowth
Average growth rate of per capita GDP from 1960 to 1985 (in percent).

- popgrowth
Average growth rate of working-age population 1960 to 1985 (in percent).

- invest
Average ratio of investment (including Government Investment) to GDP from 1960 to 1985 (in percent).

- school
Average fraction of working-age population enrolled in secondary school from 1960 to 1985 (in percent).

- literacy60
Fraction of the population over 15 years old that is able to read and write in 1960 (in percent).

The data are derived from the Penn World Table 4.0 and are given in Mankiw, Romer and Weil (1992),
except `literacy60`

that is from the World Bank's World Development Report.

Journal of Applied Econometrics Data Archive.

http://qed.econ.queensu.ca/jae/1995-v10.4/durlauf-johnson/

Durlauf, S.N., and Johnson, P.A. (1995). Multiple Regimes and Cross-Country
Growth Behavior. *Journal of Applied Econometrics*, **10**, 365–384.

Koenker, R., and Zeileis, A. (2009). On Reproducible Econometric Research.
*Journal of Applied Econometrics*, **24**(5), 833–847.

Mankiw, N.G, Romer, D., and Weil, D.N. (1992). A Contribution to the Empirics of Economic Growth.
*Quarterly Journal of Economics*, **107**, 407–437.

Masanjala, W.H., and Papageorgiou, C. (2004). The Solow Model with CES
Technology: Nonlinearities and Parameter Heterogeneity. *Journal of
Applied Econometrics*, **19**, 171–201.

`OECDGrowth`

, `GrowthSW`

## data for non-oil-producing countries data("GrowthDJ") dj <- subset(GrowthDJ, oil == "no") ## Different scalings have been used by different authors, ## different types of standard errors, etc., ## see Koenker & Zeileis (2009) for an overview ## Durlauf & Johnson (1995), Table II mrw_model <- I(log(gdp85) - log(gdp60)) ~ log(gdp60) + log(invest/100) + log(popgrowth/100 + 0.05) + log(school/100) dj_mrw <- lm(mrw_model, data = dj) coeftest(dj_mrw) dj_model <- I(log(gdp85) - log(gdp60)) ~ log(gdp60) + log(invest) + log(popgrowth/100 + 0.05) + log(school) dj_sub1 <- lm(dj_model, data = dj, subset = gdp60 < 1800 & literacy60 < 50) coeftest(dj_sub1, vcov = sandwich) dj_sub2 <- lm(dj_model, data = dj, subset = gdp60 >= 1800 & literacy60 >= 50) coeftest(dj_sub2, vcov = sandwich)