The Review of International Organizations

, Volume 12, Issue 1, pp 1–38

Does it pay to be poor? Testing for systematically underreported GNI estimates

Article

DOI: 10.1007/s11558-015-9239-3

Cite this article as:
Kerner, A., Jerven, M. & Beatty, A. Rev Int Organ (2017) 12: 1. doi:10.1007/s11558-015-9239-3

Abstract

Coordinating aid distribution to the poorest countries requires identifying which countries are poor. In practice this has meant sorting countries into developmental cohorts on the basis of macroeconomic data, with countries in poorer cohorts gaining access to more and more concessional aid programs. To the extent that governments can influence their macroeconomic data, some, especially those in aid-dependent countries, may prefer to report data that sorts them into lower development cohorts. We term such behavior “aid-seeking data management.” The possibility of data management has substantial implications for aid distribution, and for the use of macroeconomic data in social scientific settings. We look for evidence of aid-seeking data management in the distribution of GNI per capita data around the eligibility threshold for the World Bank’s International Development Association (IDA). Because macroeconomic data are subject to frequent ex post revisions, we separately analyze the heavily revised data available for download from the World Bank’s World Development Indicators and the substantially less revised data that we gleaned from back issues of print edition of World Bank Atlas. We find that the less revised GNI per capita data display patterns that are consistent with aid-seeking data management among aid-dependent countries, and only among aid-dependent countries. This finding is robust to a variety of model specifications, but somewhat sensitive to the exclusion of individual countries from the sample. We find no such evidence in the currently downloadable data, suggesting that whatever biases aid-seeking data management may have generated in early data releases are largely and perhaps entirely wiped away in ex post revisions.

Keywords

World Bank Data Foreign Aid 

Supplementary material

11558_2015_9239_MOESM1_ESM.zip (220 kb)
ESM 1(ZIP 220 kb)

Copyright information

© Springer Science+Business Media New York 2015

Authors and Affiliations

  1. 1.University of MichiganAnn ArborUSA
  2. 2.Norwegian University of Life SciencesAkershusNorway