educineq (version 0.1.0)

elc: Lorenz curve of education

Description

elc is a function to graph the Lorenz curve of education for any group of countries using the set of estimates developed in Jorda and Alonso (2017).

Usage

elc(countries, init.y, final.y, database, M = 5000)

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. (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 (default M = 5000).

Value

elc returns a graph of the evolution of the Lorenz curve of education over the specified period.

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. To accommodate time and country varying parameters, the distribution of education of each country and year is estimated by non-linear least squares (see, Jorda and Alonso (2017) for further description on the estimation strategy).The Lorenz curve 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.

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

Examples

elc(countries = c("CAN","USA"), init.y = 1985, final.y = 1985,
  database = "female25", M = 300)