Gender Progressiveness Index (GPI)

Measuring GPI

The Gender Progressiveness Index (GPI) evaluates the progress margin of Gender Equity Index (GEI) derived from UN Human Development Indicators (HDI) for Gender Inequality over the Global Gender Gap (GGG) Index provided by the World Economic Forum. GPI is estimated by the following equation.

GPI = {[1-GEI(x)] / [GGG(x)], simplified

GPI = [ Gender Equity ] / [Gender Gap ]

Drawing on all available country data, the GPI survey for 2017 is estimated for a maximum count of 134 countries.

Statistical Results

Results of the statistical analysis (cf. GPI Data Set) indicate a high level of annual sample independence and low variance in mean and median values through the time series.

In the aggregate, a total of 76.12% (102 out of 187) of representative countries obtained affirmative gender progress indicators during the 2017 survey. GPI Leading 25 countries obtained substantive transitions in the range -3.25% to +54.16%  and -2.52% to +54.52% through 12mth and 5yr interval. Global benchmarks in gender progressiveness for the Bottom 25 countries were similarly in the range -2.95% to +2.55% and -3.1% to +6.99% through the 12mth and 5yr interval. Notwitstanding, the steady consolidation of gender progressiveness worldwide is emblematised by medium-long run transition in the global poles of India (+3.94%) and China (+5.72%), each representing 17.96% and 18.89% of the world population weight, respectively.

Current GPI trending exhibits an improved sample distribution through the time series and modest increments of the survey mean, together contributing approximately +2.36% correction to central tendency and nominal skewness (-21.33% (12mths), -16.87% (36mths), and -10.92%(5yrs)). Overall, the GPI Spread (xmax - xmin) obtained was +0.06% (intra-year) and +10.00% (inter-year), narrowing substantively by -4.49% over the 5 year period.

The GPI may be construed as an insightful indicator of the net outcome of historical social engineering policies around the world, notionally capturing the long run efficacy of domesticated gender equalisation programs.

Data Analysis