Data-driven approach to gender inequality
In recent years, increasing economic, social, political and environmental crises have intersected with gender inequalities, causing different types and levels of losses for each individual. In particular, the Covid-19 pandemic, the war in Ukraine, the rising cost of living and the disproportionate negative impact of the climate crisis on women make the issue of gender equality even more important. Implementing the Sustainable Development Goals and ensuring gender equality within this framework is vital to reduce inequalities caused by these crises.
There are many challenges in obtaining and making gender-based data fully accessible. A paper published by the United Nations Entity for Gender Equality and the Empowerment of Women (UN Women) provides guidance for societies on the problems and possible solutions.
Inequality in access to data sources
In May 2020, nearly 90% of low- and lower-middle-income countries fell short of meeting international reporting requirements. By July 2022, only 42% of the data needed to examine the gender-related dimensions of the Global Development Goals was accessible. This is a significant achievement, given the enormous challenges in data collection during Covid-19. However, researchers and policymakers have a long and challenging road ahead to access the data needed to comprehensively assess the extent and impact of gender inequality.
Long way to go in accessing data
None of the 193 countries committed to meeting the 2030 targets have access to full gender data. If the trend of 3% annual growth in data access continues, it will take 22 years to provide access to gender data in these countries. This means that the 2030 targets will not be met in time.
Currently, Mexico, Armenia, Belarus, Guatemala, Ecuador, Peru, Costa Rica, Albania, Panama and Zimbabwe have made the most gendered data available. At the other end of the data availability spectrum, the countries with the least data are Monaco, Saint Kitts and Nevis, San Marino, Liechtenstein, Andorra, Bahamas, Micronesia, Dominica, Grenada and Eritrea. For these countries, it could take between 39 and 220 years to obtain and make available all gender data.
What can be done?
UN Women has set several goals to accelerate the process of collecting and making data available. One is to achieve 100 percent data availability by 2030, a 6 percent improvement each year. The other is to collect data on targets and indicators related to gender equality. The 14 indicators covered by the 2030 targets have not been achieved by any country. Some of these include women survivors of sexual violence (targets 5.2.2 and 11.7.2), women living below the national poverty line and 50% of median income (targets 10.2.1 and 1.2.1), and hourly earnings of female workers (target 8.5.1).
UN Women reports that about 95% of the data on some key indicators has been achieved. Some of these key indicators include the proportion of seats held by women in national parliaments (target 5.5.1), adolescent birth rate (target 3.7.2), unemployment rate (target 8.5.2), maternal mortality rate (target 3.1.1) and births attended by skilled health personnel (target 3.1.2).
There is a huge funding gap that stands in the way of achieving the targets set by UN Women. According to a report published by the Partner Report on Support to Statistics (PRESS) 2021, after 2015, when projects using gender data and statistics were most financially supported, this support has declined significantly. According to another study, State of Gender Data Financing 2021, $500 million needs to be invested each year to close this gap. Today, however, only half of this amount is available.
As a result, it is important to adopt a data-driven approach to the development and implementation of gender equality policies. This approach will enable the use of accurate and reliable data to identify problems and develop solutions, thereby achieving gender equality more effectively. Therefore, strengthening the institutions working in this field and creating resources are vital for the adoption of a data-driven approach.