educineq (version 0.1.0)

emld: Mean log deviation (MLD) of education

Description

emld function computes the MLD of education, with for any group of countries included in the dataset developed in Jorda and Alonso (2017). The function also provides a decomposition of this index in between-county and within-country inequality.

Usage

emld(countries, init.y, final.y, database, 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.

plot

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

Value

emld returns a list with the following objects:

1. MLD: evolution of the MLD of education from the initial to the last year, decomposed in between-country and within-country inequality.
2. countries: countries used to compute the MLD.
3. If plot = TRUE, graphical representation of the numerical results.

Details

The estimates of the MLD for the specified group of countries can be easily derived by taking advantage of the decomposition of this family. It is computed as the sum of the following terms, which correspond to within- country and between, country inequality respectively (see, e.g., Cowell, 2011): \(MLD_W=\sum_{i=1}^{N} p_i MLD_i;\) \(MLD_B=\sum_{i=1}^{N} p_i log(\mu / \mu_i),\) where N is the number of countries, \(MLD_i\) and \(p_i\) denote, respectively, the MDL and the population weight of the country i.

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

See Also

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

emld(countries = "East Asia and the Pacific", init.y = 1980,
     final.y = 2000, database = "female25")
emld(countries = c("DNK", "FIN", "ISL", "NOR", "SWE"), init.y = 1980,
     final.y = 2000, database = "total25")