Understanding Conditions for Statistical Capacity in Developing Countries

• In Event: Poster Session: Comparative Politics of Developing Countries I

Abstract

The United Nations Sustainable Development Goals envision a world in which data can be harnessed to fuel evidence-based decision making and enhance accountability. However, many countries are still experiencing a lack of access to reliable data, as well as poor cultures of data use in government. That is, statistical capacity is still low in many areas of the world, especially in less developed countries that struggle to produce, disseminate, and utilize statistics. International support toward statistical capacity building through foreign aid has steadily increased in recent years, with even more funding being called for to help fill the existing data gaps. However, we still do not fully understand the effect of foreign aid on statistical capacity. Despite the rising interest in statistical capacity development and government accountability, we also do not know much about other enabling conditions that may help generate higher statistical capacity.
In this paper, I investigate the conditions that affect statistical capacity, modeling data for 135 developing countries over 2004-2016 using a panel regression model with country and year fixed-effects. The analyses and discussion are centered around money versus policy: whether it is foreign aid that matters most for statistical capacity building, which is an activity heavily driven by external financial support, or whether government participation through policy programs matters more. I also explore other possible enabling factors for higher levels of statistical capacity, such as the political, economic environment and the technological development in each country. I find that countries with better established National Strategies for the Development of Statistics, as well as higher percentages of foreign aid that is allocated toward developing such national strategies and policies, have higher statistical capacity. In addition, I find that political regime type has a significant effect, with authoritarian states having higher statistical capacity. My findings point to the importance of considering country ownership and political buy-in for statistical capacity building.

Author

• Eun Young Kim, The University of Texas at Austin