Human-wildlife conflict is one of the most pressing sustainable development challenges globally. This is particularly the case where ecologically and economically important wildlife impact the livelihoods of humans. Large carnivores are one such group and their co-occurrence with low-income rural communities often results in real or perceived livestock losses that place increased costs on already impoverished households. Here we show the disparities associated with the vulnerability to conflict arising from large carnivores on cattle (Bos taurus) globally. Across the distribution of 18 large carnivores, we find that the economic vulnerability to predation losses (as measured by impacts to annual per capita income) is between two and eight times higher for households in transitioning and developing economies when compared to developed ones. This potential burden is exacerbated further in developing economies because cattle keepers in these areas produce on average 31% less cattle meat per animal than in developed economies. In the lowest-income areas, our estimates suggest that the loss of a single cow or bull equates to nearly a year and a half of lost calories consumed by a child. Finally, our results show that 82% of carnivore range falls outside protected areas, and five threatened carnivores have over one third of their range located in the most economically sensitive conflict areas. This unequal burden of human-carnivore conflict sheds light on the importance of grappling with multiple and conflicting sustainable development goals: protecting life on land and eliminating poverty and hunger.

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China is commonly depicted as a "rogue" donor, using aid to further its own interests abroad and secure access to natural resources. Especially China’s involvement in African countries has been criticized for being guided by self-interest rather than recipient need or merit. For the period 2000-2012, we compare China’s aid allocation behaviour to that of the five largest donor countries globally: France, Germany, Japan, the UK, and the USA. We use regression analysis and a rigorous variance decomposition method to measure the importance of various factors in predicting aid commitments. We find that donors differ markedly in how they allocate aid. While Germany, Japan, the USA, and the UK assign high importance to recipient need, France’s and China’s allocation models are, for a large part, driven by variables that relate to self-interest: trade in the case of France, and the adherence to the "One-China policy" in the case of China. However, China is not a purely selfish donor. As most Western donors, China commits more aid to poorer countries. Furthermore, we find no evidence that commercial interests, such as trade or access to natural resources, determine Chinese aid allocation. This latter result contrasts with Western donors, which allocate more aid to their trade partners. France and the UK also commit significantly more aid to their former colonies. In conclusion, the claim that China’s aid allocation is different must be qualified.

The study made use of a dataset published by Axel Dreher and Andreas Fuchs - also members of the Research Group on Development Economics - together with Brad Parks, Austin M. Strange and Michael J. Tierney in the article "Apples and Dragon Fruits: The Determinants of Aid and Other Forms of State Financing from China to Africa".

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To identify areas at highest risk of infectious disease transmission in Africa, we develop a physical distancing index (PDI) based on the share of households without access to private toilets, water, space, transportation, and communication technology and weight it with population density. Our results highlight that in addition to improving health systems, countries across Africa, especially in the western part of Africa, need to address the lack of essential domestic infrastructure. Missing infrastructure prevents societies from limiting the spread of communicable diseases by undermining the effectiveness of governmental regulations on physical distancing. We also provide high-resolution risk maps that show which regions are most limited in protecting themselves. We find considerable spatial heterogeneity of the PDI within countries and show that it is highly correlated with detected COVID-19 cases. Governments could pay specific attention to these areas to target limited resources more precisely to prevent disease transmission.

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Since 2015, the Social Health Protection Initiative (SHPI) aims at increasing access of the poor to health services in Khyber Pakhtunkhwa (KP) and Gilgit Baltistan (GB) in Pakistan. The KfW-financed project removes financial barriers by providing a subsidized health insurance. Phase 1 extended insurance for the poorest 21% of the population covering inpatient services in selected public and private hospitals. Phase 2 is now extending coverage to include outpatient services (OPD). KfW selected the research consortium consisting of Friedrich-Alexander University Erlangen-Nürnberg, Heidelberg Institute of Global Health, and Khyber Medical University, to provide evidence in support of the implementation. The research component covers 1) preparatory studies in support of the design of the scheme, 2) implementation research throughout the project cycle, 3) outcome and impact evaluation, and 4) additional research on out-of-pocket (OOP) expenditures for inpatient care services (IPD) under Phase 1.

Source of funding: KfW
Project period: August 2021 – August 2023 (initially)
Beteiligte Forscherinnen und Forscher (Principal Investigators): Andreas Landmann (Friedrich-Alexander-Universität Erlangen-Nürnberg), Zohaib Khan (Khyber Medical University), Manuela De Allegri (Heidelberg Institute of Global Health, Medizinische Fakultät der Universität Heidelberg)

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Almost half of the world's states provide bilateral development assistance. While previous research takes the set of donor countries as exogenous, this article introduces a new dataset on aid giving that covers all countries in the world, both rich and poor, and explores the determinants of aid donorship. It argues and shows empirically that democratic institutions support the setup of an aid program in richer countries but undermine its establishment in poorer countries. The findings hold in instrumental-variable regressions and the pattern is similar for the amount of aid.

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We find that foraging humans forage, reproduce, share parenting, and even organise their social groups in similar ways as surrounding mammal and bird species, depending on where they live in the world. Our results imply that local environments exert a key influence on how foraging human populations and non-human species behave, despite their very different backgrounds. Local environmental conditions select for similar foraging, social, and reproductive behaviors across human foragers and non-human animals, driving behavioral diversity worldwide.

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China has become a major source of global development finance, but the nature and consequences of its official financing activities are poorly understood. The absence of systematic evidence and rigorous analysis on the economic growth effects of Chinese development finance represents a major blind spot in the literature. This article introduces a new dataset of official financing from China to 138 developing countries between 2000 and 2014. This allows us then to investigate whether Chinese development finance affects economic growth in recipient countries. The results demonstrate that Chinese development finance boosts short-term economic growth. An additional project increases growth by between 0.41 and 1.49 percentage points two years after commitment, on average. These effects persist across different aid sectors and appear to be driven by increases in investment and - to a lesser extent - consumption. While this study does not find that significant financial support from China impairs the overall effectiveness of aid from Western donors, aid from the United States tends to be more effective in countries that receive no substantial support from China. Overall, this evidence should allay some of the fears that policymakers have expressed about China acting as “rogue donor” that undermines the effectiveness of Western assistance.

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This paper studies the interactions between political and economic incentives to foster forest conversion in Indonesian districts. Using a district-level panel data set from 2001 to 2016, we analyze variation in remotely sensed forest losses as well as measures of land-use licensing. We link these outcomes to political incentives arising before idiosyncratically-timed local mayoral elections as well as to price exposure measures based on oil palm soil suitability combined with global price variations for palm oil. Empirical results document increases of about 4% in deforestation in the year prior to local mayoral elections on average. Additionally, palm oil plays a crucial role in driving deforestation dynamics. Deforestation rates increase by 7% in places that experience a one standard deviation increase in local price exposure, but no upcoming elections. These effects are amplified to almost 19% larger forest losses in places that experience pre-election years and a standard deviation higher palm oil price exposure at the same time. We thus find clear evidence for economic and political incentives reinforcing each other as drivers of forest loss and land conversion for oil palm cultivation.

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Following the 2007–2008 global food crisis, agricultural producers have invested in large tracts of land in developing countries. We investigate how the arrival of large-scale farms changes inter-personal trust and reciprocity, important components of social capital, in traditional Zambian villages. Using experimental methods, we elicit trust and reciprocal behaviour in villages that lie near large-scale farms and compare them with control villages at a distance. Our data reveal greater trust in villages close to large-scale farms, which is in line with communal coping as a response to the arrival of the large farms. Reciprocity is more frequent after farm employment, which points to reputation building.  

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Can workers in developing countries take advantage of trade? Alexander M. Danzer (KU Eichstätt-Ingolstadt) and Robert Grundke (OECD) answer this question by using fluctuations in the world market price for cotton and identifying the effects of higher export prices on the wages of poor agricultural workers in the cotton harvest, using the example of Tajikistan. The increased demand for workers during the high price episode doubles wages for cotton pickers on small private farms, but has no impact on wages on large parastatal farms. The different treatment of workers is due to market power and the continued use of coerced labor in large companies during the cotton harvest, not least of school children and university students. The research concludes that trade produces winners and losers based on the political power relations between local decision makers and managers of parastatal farms.

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The authors study the effect of participatory development projects on social and economic networks in rural villages in The Gambia. Participatory development projects actively involve villagers in financing and decision-making processes, intending to create more effective projects and to strengthen local institutions. These projects, in particular Community-Driven Development (CDD) projects, are a major form of international donor activity. As of March 2021, the World Bank alone supports 327 CDD projects in 90 countries, lending over 33 billion US$. Thus, it is important to understand the effects of such projects on local communities. Existing research on the intended effects of CDD projects is limited in breadth and typically finds moderate positive effects at best. At the same time, CDD projects risk having unintended negative effects, e.g. through their interactions with local power structures and decision-making mechanisms, or through unequally distributed benefits.

The authors first argue theoretically that the effects of CDD projects on decision-making processes and unequal economic outcomes can translate into effects on social and economic networks. To study the effect of CDD projects on networks empirically, the authors utilize the random allocation of a CDD project to villages in The Gambia. They collected detailed data on social and economic interactions in 56 villages, half of which had received CDD projects in the past. The central empirical finding is that the density of social and economic networks in program villages is lower than in non-program villages. Given the importance of these informal networks for risk-sharing (e.g., in case of an illness), the reduced density of networks implies a negative effect on expected household welfare. Further empirical analyses suggest that elite capture (i.e., the appropriation of project gains by village elites) contributed to the problem of unequally distributed benefits from the project, which in turn led to conflicts, thus weakening the networks. Overall, the results demonstrate possible unintended negative consequences of participatory development projects.

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The authors merged detailed household panel data from the TVSEP with grid‐level precipitation data to study the indirect effects of rainfall shocks on non‐farm enterprises in rural Thailand. They focus on both forward and backward linkages along the value chain as well as direct demand effects through farmer’s consumption. Overall, their analysis shows that the costs of agricultural shocks are higher than what much of the literature has suggested so far. Despite limited market integration in poor rural economies, the spill-overs are sizable and are transmitted through various channels. One implication is that safety nets targeted at farms may need to consider non‐farm enterprises too.

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