Here are some recent papers which I’m looking forward to reading!
Justin Esarey and Leslie Schwindt-Bayer. 2019. “Estimating Causal Relationships Between Women’s Representation in Government and Corruption.” Comparative Political Studies.
Does increasing the representation of women in government lead to less corruption, or does corruption prevent the election of women? Are these effects large enough to be substantively meaningful? Some research suggests that having women in legislatures reduces corruption levels, with a variety of theoretical rationales offered to explain the finding. Other research suggests that corruption is a deterrent to women’s representation because it reinforces clientelistic networks that privilege men. Using instrumental variables, we find strong evidence that women’s representation decreases corruption and that corruption decreases women’s participation in government; both effects are substantively significant.
Jesse Cunha, Giacomo De Giorgi, and Seema Jayachandran. 2019. “The Price Effects of Cash Versus In-Kind Transfers.” The Review of Economic Studies.
This article examines the effect of cash versus in-kind transfers on local prices. Both types of transfers increase the demand for normal goods; in-kind transfers also increase supply in recipient communities, which could lead to lower prices than under cash transfers. We test and confirm this prediction using a programme in Mexico that randomly assigned villages to receive boxes of food (trucked into the village), equivalently-valued cash transfers, or no transfers. We find that prices are significantly lower under in-kind transfers compared to cash transfers; relative to the control group, in-kind transfers cause a 4% fall in prices while cash transfers cause a positive but negligible increase in prices. In the more economically developed villages in the sample, households’ purchasing power is only modestly affected by these price effects. In the less developed villages, the price effects are much larger in magnitude, which we show is due to these villages being less tied to the outside economy and having less competition among local suppliers.
Brian Palmer-Rubin. 2019. “Evading the Patronage Trap: Organizational Capacity and Demand Making in Mexico.” Comparative Political Studies.
When do organizations broadly represent the interests of their economic sectors and when do they narrowly represent the interests of members? This article investigates how agricultural and small-business organizations in Mexico make demands for programmatic policies or patronage benefits. Contrary to explanations based on the class of members, I show that the source of organizational capacity shapes demand-making strategies. Organizations that generate selective benefits internally are able to engage in programmatic policies that shape sectoral competitiveness, whereas organizations that fail to solve membership challenges internally are vulnerable to the patronage trap, a self-reproducing cycle wherein they become specialized in demand making for discretionary private goods. I generate this argument through process tracing of two agricultural organizations in Mexico. Analysis of an original survey of economic interest organizations provides broader evidence that organizational capacity is a better predictor of policy demands than social class.
Christopher Blattman, Donald Green, Daniel Ortega, and Santiago Tobón. 2019. “Place-based interventions at scale: The direct and spillover effects of policing and city services on crime.” Innovations for Poverty Action working paper.
In 2016 the city of Bogotá doubled police patrols and intensified city services on high-crime streets. They did so based on a policy and criminological consensus that such place-based programs not only decrease crime, but also have positive spillovers to nearby streets. To test this, we worked with Bogotá to experiment on an unprecedented scale. They randomly assigned 1,919 streets to either 8 months of doubled police patrols, greater municipal services, both, or neither. Such scale brings econometric challenges. Spatial spillovers in dense networks introduce bias and complicate variance estimation through “fuzzy clustering.” But a design-based approach and randomization inference produce valid hypothesis tests in such settings. In contrast to the consensus, we find intensifying state presence in Bogotá had modest but imprecise direct effects and that such crime displaced nearby, especially property crimes. Confidence intervals suggest we can rule out total reductions in crime of more than 2–3% from the two policies. More promising, however, is suggestive evidence that more state presence led to an 5% fall in homicides and rape citywide. One interpretation is that state presence may more easily deter crimes of passion than calculation, and place-based interventions could be targeted against these incredibly costly and violent crimes.
Heather A. Knauer, Pamela Jakiela, Owen Ozier, Frances Aboud, and Lia C.H. Fernald. 2019. “Enhancing Young Children’s Language Acquisition through Parent-Child Book-Sharing: A Randomized Trial in Rural Kenya.” Center for Global Development working paper.
Worldwide, 250 million children under five (43 percent) are not meeting their developmental potential because they lack adequate nutrition and cognitive stimulation in early childhood. Several parent support programs have shown significant benefits for children’s development, but the programs are often expensive and resource intensive. The objective of this study was to test several variants of a potentially scalable, cost-effective intervention to increase cognitive stimulation by parents and improve emergent literacy skills in children. The intervention was a modified dialogic reading training program that used culturally and linguistically appropriate books adapted for a low-literacy population. We used a cluster randomized controlled trial with four intervention arms and one control arm in a sample of caregivers (n = 357) and their 24- to 83-month-old children (n = 510) in rural Kenya. The first treatment group received storybooks, while the other treatment arms received storybooks paired with varying quantities of modified dialogic reading training for parents. Main effects of each arm of the trial were examined, and tests of heterogeneity were conducted to examine differential effects among children of illiterate vs. literate caregivers. Parent training paired with the provision of culturally appropriate children’s books increased reading frequency and improved the quality of caregiver-child reading interactions among preschool-aged children. Treatments involving training improved storybook-specific expressive vocabulary. The children of illiterate caregivers benefited at least as much as the children of literate caregivers. For some outcomes, effects were comparable; for other outcomes, there were differentially larger effects for children of illiterate caregivers.
Chris Mahony, Eduardo Albrecht, and Murat Sensoy. 2019. “The relationship between influential actors’ language and violence: A Kenyan case study using artificial intelligence.” International Growth Centre working paper.
Scholarly work addressing the drivers of violent conflict predominantly focus on macro-level factors, often surrounding social group-specific grievances relating to access to power, justice, security, services, land, and resources. Recent work identifies these factors of risk and their heightened risk during shocks, such as a natural disaster or significant economic adjustment. What we know little about is the role played by influential actors in mobilising people towards or away from violence during such episodes. We hypothesise that influential actors’ language indicates their intent towards or away from violence. Much work has been done to identify what constitutes hostile vernacular in political systems prone to violence, however, it has not considered the language of specific influential actors. Our methodology targeting this knowledge gap employs a suite of third party software tools to collect and analyse 6,100 Kenyan social media (Twitter) utterances from January 2012 to December 2017. This software reads and understands words’ meaning in multiple languages to allocate sentiment scores using a technology called Natural Language Processing (NLP). The proprietary NLP software, which incorporates the latest artificial intelligence advances, including deep learning, transforms unstructured textual data (i.e. a tweet or blog post) into structured data (i.e. a number) to gauge the authors’ changing emotional tone over time. Our model predicts both increases and decreases in average fatalities 50 to 150 days in advance, with overall accuracy approaching 85%. This finding suggests a role for influential actors in determining increases or decreases in violence and the method’s potential for advancing understandings of violence and language. Further, the findings demonstrate the utility of local political and sociological theoretical knowledge for calibrating algorithmic analysis. This approach may enable identification of specific speech configurations associated with an increased or decreased risk of violence. We propose further exploration of this methodology.
Vincent Hardy and Jostein Hauge. 2019. “Labour challenges in Ethiopia’s textile and leather industries: no voice, no loyalty, no exit?” African Affairs.
A state-led industrialization push inspired by the East Asian ‘developmental state’ model is at the centre of Ethiopia’s recent economic success. This model has historically proved potent for achieving rapid industrialization, but the business-state alliance at the heart of the model generally aimed to curb the power of labour. Focusing on textile and leather manufacturing in Ethiopia, this article addresses two questions: are workers capable of extracting gains from the process of industrialization, and have the actions of workers affected global value chain integration in the two industries? Our data show that opportunities for collective voice among workers are limited. However, workers have expressed their discontent by leaving employers when working conditions fail to meet their expectations. The resulting turnover has generated significant obstacles for local and foreign firms attempting to participate in global value chains. In response, the Ethiopian state and employers implemented a number of measures, including restrictions on emigration and more generous non-wage benefits. Recent research on global value chains and labour highlights how workers are able to influence work practices through individual action. The present article builds on these ideas, but shows that firms and governments have the ability to respond and limit this power.
Nicki Kindersley. 2019. “Rule of whose law? The geography of authority in Juba, South Sudan.” The Journal of Modern African Studies.
This study asks: in the general absence of a functioning and effective civil administration in Juba’s huge suburbs, how have people negotiated personal disputes and neighbourhood management since conflict began in 2013? Who arbitrates in Juba, and on what terms? This study challenges top-down analyses that see political-military elites managing their ethnic enclaves of followers and fighters through nepotism and gifts. Such patronage requires the complex negotiation of responsibilities and rights, including over community safety and order. In Juba, the local authorities who mediate this have been built by men and women with extensive expertise and connections in South Sudan’s long history of ‘civil-military’ governance systems. These local authorities have established lasting institutions by negotiating rights to residence in, arbitrating over, and knowing the human geography of their neighbourhoods. Their authority is rooted in this deep politics, drawing on their detailed knowledge of topographies of power in these multi-ethnic, highly military neighbourhood spaces.
Peer Schouten. 2019. “Roadblock politics in Central Africa.” Environment and Planning D: Society and Space.
A frequent sight along many roads, roadblocks form a banal yet persistent element across the margins of contemporary global logistical landscapes. How, this article asks, can we come to terms with roadblocks as a logistical form of power? Based on an ongoing mapping of roadblocks in the Democratic Republic of Congo and the Central African Republic, it sketches a political geography of “roadblock politics”: a spatial pattern of control concentrated around trade routes, where the capacity to disrupt logistical aspirations is translated into other forms of power, financial and political. While today’s roadblocks are tied up with the ongoing conflict in both countries, the article shows, roadblock politics has a much deeper history. Before colonization, African rulers manufactured powerful polities out of control over points of passage along long-distance trade routes crisscrossing the continent. The article traces how since precolonial times control over long-distance trade routes was turned into a source of political power, how these routes were forcefully appropriated through colonial occupation, how after the crumbling of the colonial order new connections were engineered between political power and the circulation of goods in Central Africa, and how control over these flows ultimately became a key stake in ongoing civil wars in the region.
Louisa Lombard and Enrica Picco. 2019. “Distributive Justice at War: Displacement and Its Afterlives in the Central African Republic.” Journal of Refugee Studies.
One of the defining features of the crisis in the Central African Republic (CAR) since 2013 has been massive displacement. Currently, about a quarter of the country’s population is displaced. People who have been forcibly displaced, whether internally or abroad, and people who stayed behind this time (but frequently have their own memories of displacement) provide particular kinds of information about war and its not particularly peaceful aftermath. In this article, based on interviews with a broad range of people affected by displacement, we show that Central African views about the prospects for peace are deeply affected by how displacement has shaped tensions over the political senses of distribution (who has a right to what, and on what basis). Who should pay for war, in senses both material and otherwise, and who should be compensated? However, distribution and belonging are not the issues prioritized in the aftermath of war, when elite deals, punitive justice and technocratic recovery plans crowd out treatment of the material justice and belonging questions that dominate neighbourhoods. The political dimensions of material justice in the aftermath of war require more thorough treatment, as listening to people who have experienced displacement makes abundantly clear.
Wenjie Hu, Jay Harshadbhai Patel, Zoe-Alanah Robert, Paul Novosad, Samuel Asher, Zhongyi Tang, Marshall Burke, David Lobell, and Stefano Ermon. 2019. “Mapping Missing Population in Rural India: A Deep Learning Approach with Satellite Imagery.” AAAI / ACM Conference on Artificial Intelligence, Ethics and Society working paper.
Millions of people worldwide are absent from their country’s census. Accurate, current, and granular population metrics are critical to improving government allocation of resources, to measuring disease control, to responding to natural disasters, and to studying any aspect of human life in these communities. Satellite imagery can provide sufficient information to build a population map without the cost and time of a government census. We present two Convolutional Neural Network (CNN) architectures which efficiently and effectively combine satellite imagery inputs from multiple sources to accurately predict the population density of a region. In this paper, we use satellite imagery from rural villages in India and population labels from the 2011 SECC census. Our best model achieves better performance than previous papers as well as LandScan, a community standard for global population distribution.