egini {educineq}

Gini index of education

Description

egini is a function to compute the Gini index of education for any group of countries using the set of estimates developed in Jorda and Alonso (2017).

Usage

egini(countries, init.y, final.y, database, M = 5000, plot = TRUE)

Arguments

countries

character vector with the country codes of the countries to be used. Some macro-regions are already defined and can be used instead of the country codes: South Asia, Europe and Central Asia, Middle East and North Africa, Latin America and the Caribbean, Advanced Economies, Sub-Saharan Africa, East Asia and the Pacific and all for the 142 counrties included in the dataset (see data_country).

init.y

the first year in which the function is calculated. Available years are 1970, 1975, 1980, 1985, 1990, 1995, 2000, 2005, 2010.

final.y

the last year in which the function is calculated Available years are 1970, 1975, 1980, 1985, 1990, 1995, 2000, 2005, 2010.

database

population subgrup for which the function is calculated. The following options are available:

1. "total15": Total population aged over-15.

2. "total25": Total population aged over-25.

3. "male15": Male population aged over-15.

4. "male25": Male population aged over-25.

5. "female15": Female population aged over-15.

6. "female25": Female population aged over-25.

M

size of the simulated sample.

plot

if TRUE (the default), displays a graph of the results.

Details

We use the set of estimates developed in Jorda and Alonso (2017), where the generalized gamma distribution (Stacy, 1962) is used to model the time that individuals attend school until they complete the educational cycle or decide to drop out. The Gini index is computed from a synthetic sample of size M of the distribution of education of the specified group of countries. The sample is obtained by Monte Carlo simulation using the mixture of the national distributions, weighted by their population shares.

Value

egini returns a list with the following objects:

1. Gini_index: evolution of the Gini index of education from the initial to the last year.

2. countries: countries used to compute the Gini index.

3. If plot = TRUE, graphical representation of the numerical results.

References

Cowell, F. (2011). Measuring inequality. Oxford University Press.

Jorda, V. and Alonso, J.M. (2017). New estimates on educational attainment using a continuous approach (1970-2010), World Development, 90, 281 - 293. http://www.sciencedirect.com/science/article/pii/S0305750X16305010

Stacy, E. W. (1962). A generalization of the gamma distribution. Annals of Mathematical Statistics, 33, 1187 - 1192.

See Also

GenGamma.orig, Gini, data_country. Visit http://www.educationdata.unican.es for more information on the constructoin of the dataset and the available countries.

Examples

egini(countries = c("DNK", "FIN"), init.y = 1995, final.y = 1995,
  database = "male25", M = 100, plot = FALSE)