Description Usage Arguments Details Value References See Also Examples
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).
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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: |
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:
|
M |
size of the simulated sample. |
plot |
if |
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.
egini
returns a list with the following objects:
Gini_index
: evolution of the Gini index of education
from the initial to the last year.
countries
: countries used to compute the Gini index.
If plot = TRUE
, graphical representation of the numerical results.
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.
GenGamma.orig
, Gini
, data_country
.
Visit http://www.educationdata.unican.es for more information on
the constructoin of the dataset and the available
countries.
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