Connective Financing: Chinese Infrastructure Projects and the Diffusion of Economic Activity in Developing Countries

Abstract

This paper studies the causal effect of transport infrastructure on the spatial concentration of economic activity. Leveraging a new global dataset of geo-located Chinese government-financed projects over the period from 2000 to 2014 together with measures of spatial inequality based on remotely-sensed data, we analyze the effects of transport projects on the spatial distribution of economic activity within and between regions in a large number of developing countries. We find that Chinese-financed transportation projects reduce spatial concentration within but not between regions. In line with land use theory, we document a range of results which are consistent with a relocation of activity from city centers to their immediate periphery. Transport projects decentralize economic activity particularly strongly in regions that are more urbanized, located closer to the coast, and less developed.

Aid and Conflict at the Subnational Level – Evidence from World Bank and Chinese Development Projects in Africa

“…The high conflict reducing effect of aid in the "transportation" sector also corresponds to other related studies, which indicate the salience of transport costs for economic growth across African countries(Berman and Couttenier, 2015;Storeygard, 2016;Bluhm et al, 2018) 26Table A47presents the regressions for the WB with OLS and China with IV. The OLS results differ in some cases, but again there is no significant positive coefficient for any sector.5 RESULTS…”

“…If aid receipts stop in 1999, the probability would decline to 0.5 in 2000 as the country would have received aid in three out of six years. The constant probability used in Nunn and Qian (2014) or Bluhm et al (2018) relies on all observed treatment values per unit, i.e., the term for region i in year t also depends on the values in t + 1, t + 2, .... These future values can themselves be a function of conflict.…”

“…The production level was shown to affect the overall amount of Chinese aid as China would commit to more aid projects to clear markets and protect domestic companies from potential losses (Dreher et al, 2016). These projects are often large-scale infrastructure projects (Bräutigam, 2011), but Bluhm et al (2018) show that steel production also induces variation in other sectors (social, education or health) beyond roads and railways. China is also generally known as engaging in "mega-deals" (Strange et al, 2017), which are generally larger than WB projects.…”

“…In order to establish causality, our identification strategy combines pre-determined cross-sectional variation interacted with a conditionally exogenous time series (as in Lang, 2016). Similar to Nunn and Qian (2014) and Bluhm et al (2018), we create this crosssectional variation by computing the probability that a region receives aid from a donor. Based on Dreher et al (2017), we use official information on the WB's funding position and Chinese steel (over-)production (World Steel Association, 2014) as temporal variation that is arguably exogenous to conflict in individual region-years when conditioning on regional and country-year fixed effects.…”

Chinese Aid and Local Ethnic Identification

“…Until recently, studying the motivations behind and effects of Chinese development finance has been very difficult since the Chinese government, unlike the OECD-DAC donors, does not routinely publish information on its foreign assistance. However, with a new comprehensive dataset on Chinese Official Finance to Africa issued by the AidData research laboratory (Bluhm et al, 2018), systematic quantitative analysis of Chinese aid flows is now possible. Using this data, Dreher et al (2016) find that Chinese development finance is disproportionately allocated to the birth regions of African leaders and, less clearly so, to areas populated by individuals who share their ethnicity.…”