Tracking Underreported Financial Flows: China’s Development Finance and the Aid–Conflict Nexus Revisited

Abstract

China's development finance is sizable but reliable information is scarce. To address critical African countries. We use this database to extend previous research on the aid-conflict nexus. Our results show that sudden withdrawals of "traditional" aid are only more likely to induce conflict in the absence of sufficient alternative funding from China. More broadly, these findings highlight the importance of gathering better data on the development activities of China and other non-traditional donors to better understand the link between foreign aid and conflict.

Do authoritarian regimes receive more Chinese development finance than democratic ones? Empirical evidence for Africa

“…Source: Authors' own calculations based on data from Strange, Dreher et al (2015) and OECD/DAC Statistics database.…”

Chinese aid and local corruption

“…6 The data on Chinese aid projects is obtained from georeferenced project-level data of version 1.1 of AidData's Chinese Official Finance to Africa dataset, introduced by Strange et al (2015) and geocoded by Dreher et al (2016). Given that the Chinese government does not release official, project-level financial information about its foreign aid activities, this data is based on AidData's Tracking Underreported Financial Flows (TUFF) methodology.…”

“…Strange et al, 2015;Dreher et al, 2011;. Largest among the 'new' donors is China, and with the explosion of Chinese funds, concerns over its donor practices has followed.…”

International organizations and development finance: Introduction to the special issue

“…See Tierney et al (2011), Strange et al (2017) and OECD statistics at: http://www.oecd.org/dac/stats/statisticsonresourceflowstodevelopingcountries.htm.…”

“…Second, a growing number of bilateral donors and lenders refuse to disclose detailed information about their overseas activities (e.g., China Development Bank, China Ex-IM Bank, the Brazilian Development Bank, the Development Bank of Southern Africa, the Industrial Development Bank of India, Vnesheconombank, Russian Regional Development Bank, and the Export Development Bank of Iran), so inasmuch as researchers wish to study the distinctiveness of IO development finance by comparing it to bilateral development finance, this type of comparative analysis will become more rather than less difficult in the coming years. The Brazys et al (2017) contribution to this volume, which compares the local corruption effects of World Bank projects and Chinese projects (using the new open source AidData-TUFF method to identify the latter as explained in Strange et al 2017), represents one example of how researchers can work around this increasingly binding constraint. However, many more efforts of this type will be needed going forward to ensure that knowledge accumulation about IO development finance (and its distinctiveness) does not slow or degrade over time because of growing informational scarcity.…”