Group08 Proposal

Understanding gender equality from a visual perspective

Overview

Proposal

Poster

Application

Report

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Background

With the improvement of quality of life across the world, the argument for various freedoms and rights surface and turn to hotly debated topics especially in highly developed countries. One such agenda is the push for the empowerment of women, amongst the fight against other forms of discrimination.

Moral and ethical concerns aside, there appears to be a strong economic case for the empowerment of women. Intuitively, this makes sense since it increases human capital and potential contribution of half the population towards a nation's economy. This is further argued by the International Institute for Environment and Development on "Why women's empowerment is essential for sustainable development" - which highlights factors on the direct contribution of women, the value of diverse opinions, as well as accounting for the huge untapped potential economic resource.

Given the growing importance on this area, our project seeks to encapsulate existing data and present it visually in a simple, understandable manner, to help further efforts in driving the agenda. Using graphical techniques complemented with some level of statistical modelling in R, our dashboard will provide a view on changing patterns in key indicators relating to gender equality and women empowerment with time, as well as attempt to highlight important variables which aid the growth of such indicators.

Data Sources

The World Bank is a global partnership between 189 countries across the world that seeks to "reduce poverty and build shared prosperity in developing countries". While it regularly collects information and publishes reports toward its work, it also hosts its data on data.worldbank.org in a bid to provide free and open access to development data across the globe.

As a significant area of our topic covers economic indicators as proxies of women empowerment, the World Bank database serves as a primary source of data for us to work with.

Approach

We will be exploring the following few approaches to the analysis and visualisation of the data:

Exploration

• Illustrate every independent variable’s changing pattern by countries
• Illustrate changing patterns in indicators of women empowerment for various countries or groups of countries
• Detect any exceptional variations or trends for further analysis

Multi-variate linear regression

With some reorganisation, the data can be structured into 3 dimensions of country (region), time (year), and indicators for the purpose of multi-variate linear regression.

Y_i = β₀ + β₁X_i + β₂X_2i + ... + β_nX_ni

• Y represents the dependent variable which is an indicator of women empowerment, while X denotes dependent variables influence Y values. We have identified female labor force participation rate (or calculated Non-agricultural female employment rate) as one such potential indicator
• The model will be used to evaluate various X variables and generate a list of featured variables of high importance. Statistical significance and adjusted R-squared values will be key deciding factors to help us exclude irrelevant variables
• Set assumptions: Classical Hypothesis, significance level, OLSE (ordinary least squares estimation); set applicable testing methods for model updating: goodness of fit, F-test, T-test, multicollinearity, etc.
• With the model, we will perform cross-comparison between countries and regions, and identify potential segregation factors such as rate of development, geographical, environmental etc.

Time series forecasting

• Capture important features (those which significantly impact Y) of each year for every country in each group
• Illustrate how impact factors change as time goes by for countries
• Set customized tolerance level (low, medium, high)
• Forecast Y value(s) towards the near future for each selected country based on input variables using ARIMA (Auto-Regressive Integrated Moving Average) algorithm or Xgboost
• Model performance evaluation

Design Approach

The approach to the design principles are outlined under each area:

Data visualisation

• Animation to show the impact factors changing year by year automatically
• Good viz way to show the target changing patterns by time and comparison among countries
• Good viz way to show variables text info, country info, outliers and so on

Application Interface

• Allow users to select their tolerance for forecasting women empowerment measures in the near future
• Allow users to select time and country for indicators they want to explore under the filters and embed controls to avoid 'overcrowding' of parameters in any visualization
• Allow users to customize variables to be input in the model so that they may directly see the difference of target results between their input and important features input
• Creative visuals to complement key insights or commentaries generated in the dashboard

References

Essay on Women Empowerment: Its Meaning and Importance - published by Important India	https://www.importantindia.com/19050/essay-on-women-empowerment/
Ready to Measure: Twenty Indicators for Monitoring SDG Gender Targets - published by Data2X	http://data2x.org/wp-content/uploads/2017/11/Ready-to-Measure.pdf
Ready to Measure: Phase II - published by Data2X	http://data2x.org/wp-content/uploads/2017/09/Ready-to-Measure-Phase-II_Report.pdf
Indicators for Gender Equality and Women's Empowerment - published by OECD	http://www.oecd.org/dac/gender-development/43041409.pdf
Indicators of Gender Equality - published by UNECE	https://www.unece.org/fileadmin/DAM/stats/publications/2015/ECE_CES_37_WEB.pdf