Poster Paper: The Effectiveness of International Development Assistance Toward Statistical Capacity Building

Saturday, November 4, 2017
Regency Ballroom (Hyatt Regency Chicago)

*Names in bold indicate Presenter

Eun Young Kim, University of Texas, Austin

The availability and use of data in policy analysis and decision-making is often taken for granted in developed democracies. Yet in most developing countries, data-driven decision making is hindered by the lack of access, or non-existence, of reliable data and poor cultures of data use in government. Nevertheless, the timely generation and availability of data to all stages of policy-making is even more important in such developing countries; for governments and international aid organizations alike, data is crucial in understanding problematic development situations and utilizing what limited resources there are to create more effective outcomes. Various international organizations have recognized the power of data through the creation of several initiatives to support statistical capacity building, and donors have also contributed aid toward the development of statistics in developing countries.

This paper evaluates the possible effect of such foreign aid on statistical capacity. Has international development assistance specified for enhancing the creation and use of statistics in developing countries improved their capacity to generate data and statistics according to international standards? By restricting international development assistance to the amounts that were given specifically for statistical capacity building purposes, this question digs deeper into a fundamental capacity—the ability to generate data and statistics—that would influence both economic development policies and social development programs.

The empirical analysis conducted in this paper is based on a regression model with panel data on 135 countries, using the Statistical Capacity Indicator scores from the World Bank as its dependent variable, and aid disbursement amounts from the “Partner Report on Support to Statistics (PRESS)” published by the Partnership in Statistics for Development in the 21stCentury (PARIS21) as its main independent variable. In order to investigate the possible effects of country ownership on statistical capacity building, the status of each countries’ National Strategies for the Development of Statistics (NSDS) is also included in the analysis as a mediating variable. The type of development assistance given is also a factor that is considered through inclusion as a moderating variable. Country specific characteristics that may have influenced the relationship between development assistance and statistical capacity, such as political type, corruption levels, GDP per capita, income group categorization, and net aid levels, are controlled for.

Previous research on statistical capacities of developing countries were limited in scope and generalizability because they were mostly case studies specific to individual countries. The analysis in this paper aims to extend the existing research with quantitative analysis that explores the possible effects of international development assistance as a driving force for the variance and change in statistical capacities across countries. The findings are expected to contribute toward a better understanding of statistical capacity building. As the initial requirement for data use in policy-making, a better understanding of statistical capacity building would then be linked to better policy analysis and evaluation practices in developing countries. It will also help in shaping future development assistance structures toward statistical capacity building.