Research

Journal Publications 

Joshua Deutschmann, Molly Lipscomb, Laura Schechter, and Jessica Zhu. Spillovers without social interactions in urban sanitation, American Economic Journal: Applied Economics, forthcoming.

• Abstract: We run a randomized controlled trial coupled with lab-in-the-field social network experiments in urban Dakar. Decision spillovers and health externalities play a large role in determining uptake of the sanitation technology, with decision spillovers being largest among households that don’t receive significant subsidies. There is no evidence that the spillovers are explained by social forces in general, nor that they are explained by specific social mechanisms such as learning from others, social pressure, or reciprocity. We do find evidence of a fourth, non-social, mechanism impacting decisions: increasing health benefits. As more neighbors adopt the sanitary technology, it becomes more worthwhile for other households to adopt as well.

Jennifer Alix-Garcia, Laura Schechter, Felipe Valencia Caicedoc, and Jessica Zhu. Country of women? Repercussions of the Triple Alliance War in Paraguay, Journal of Economic Behavior & Organization, 202:131-167, October 2022.

• Abstract: The War of the Triple Alliance (1864–1870) in South America killed up to 70% of the Paraguayan male population. According to Paraguayan national lore, the skewed sex ratios resulting from the conflict are the cause of present-day low marriage rates and high rates of out-of-wedlock births. We collate historical and modern data to test this conventional wisdom in the short, medium, and long run. We examine both cross-border and within-country variation in child-rearing, education, labor force participation, and gender norms in Paraguay over a 150 year period. We find that more skewed post-war sex ratios are associated with more out-of-wedlock births, more female-headed households, better female educational outcomes, higher female labor force participation, and more gender-equal gender norms. The impacts of the war persist into the present, are seemingly unaffected by variation in economic openness or ties to indigenous culture, and appear to be driven by social attitudes towards gender.

Florence Kondylis, Valerie Mueller, and Jessica Zhu. Seeing is believing? Evidence from an extension network experiment, Journal of Development Economics, 125:1-20, March 2017.

• Abstract: Extension is designed to enable lab-to-farm technology diffusion. Decentralized models assume that information flows from researchers to extension workers, and from extension agents to contact farmers (CFs). CFs should then train other farmers in their communities. Such a modality may fail to address informational inefficiencies and accountability issues. We run a field experiment to measure the impact of augmenting the CF model with a direct CF training on the diffusion of a new technology. All villages have CFs and access the same extension network. In treatment villages, CFs additionally receive a three-day, central training on the new technology. We track information transmission through two nodes of the extension network: from extension agents to CFs, and from CFs to other farmers. Directly training CFs leads to a large, statistically significant increase in adoption among CFs. However, higher levels of CF adoption have limited impact on the behavior of other farmers.

Florence Kondylis, Valerie Mueller, Glenn Sheriff, and Jessica Zhu. Do female instructors reduce gender bias in diffusion of sustainable land management techniques? Experimental evidence from Mozambique, World Development, 78:436-449, February 2016.

• Abstract: Agricultural innovation is essential to meet the food requirements of Africa’s growing population. One pathway to increasing yields may be to enhance female farmer productivity. In many settings, married women cultivate plots separated from those of other family members. They face different challenges to productivity, such as deficiencies in inputs, weak property rights, and time constraints. It has long been argued that traditionally male-dominated extension services may also contribute to a gender bias in adoption of new agricultural techniques. If this is true, placing women in extension positions may help other women overcome barriers to adoption posed by inequitable access to agricultural extension services or exposure to inapt information. To better understand the role of gender in the dissemination of sustainable land management (SLM) techniques, this study uses a randomized policy experiment conducted in 200 communities in Mozambique. We examine the impact of training female messengers of SLM techniques on the awareness, knowledge, and adoption of SLM practices by other female farmers. Communities were randomly selected in 2010 to have a female messenger trained in SLM who was encouraged to teach other women the techniques. Using data from panel surveys collected in the experimental areas, we find women’s awareness of pit planting farming techniques increased by 9 percentage points in 2012 and adoption of the technology by 5 percentage points in 2013 in communities with female messengers.

Florence Kondylis, Valerie Mueller, and Jessica Zhu. Measuring agricultural knowledge and adoption, Agricultural Economics, 46:449-462, May 2015.

• Abstract: Understanding the tradeoffs in improving the precision of agricultural measures through survey design is crucial. Yet, standard indicators used to determine program effectiveness may be flawed, and at a differential rate for men and women. We use a household survey from Mozambique to estimate the measurement error from male and female self‐reports of their adoption and knowledge of three practices: intercropping, mulching, and strip tillage. Despite clear differences in human and physical capital, there are no obvious differences in the knowledge, adoption, and error in self‐reporting between men and women. Having received training unanimously lowers knowledge misreports and increases adoption misreports. Other determinants of reporting error differ by gender. Misreporting is positively associated with a greater number of plots for men. Recall decay on measures of knowledge appears prominent among men but not women. Findings from regression and cost‐effectiveness analyses always favor the collection of objective measures of knowledge. Given the lowest rate of accuracy for adoption was around 80%, costlier objective adoption measures are recommended for a subsample in regions with heterogeneous farm sizes.

Working Papers

Targeting, personalization, and engagement in an agricultural advisory service, with Susan Athey, Shawn Cole, and Shanjukta Nath.

• Abstract: ICT is increasingly used to deliver customized information in developing countries. We examine whether individually targeting the timing of automated voice calls meaningfully increases engagement in an agricultural advisory service. We define, estimate, and evaluate a novel recommendation system that customizes contact times to individual characteristics. This system generates significant gains, up to an 8%  increase over the baseline pickup rate of 0.31. Our approach, delivered at scale, is well-suited for developing country settings. We show how to optimize around resource constraints, measure equity-efficiency trade-offs when targeting vulnerable groups, and evaluate the robustness of recommendations to technology or preference shocks.

How high to raise the bar? Causal effect of self-set goals, with Martin Abel, Tomoko Harigaya, and Michael Kremer.

• Abstract: We investigate the effect of self-set goals among decentralized agents. We elicited productivity goals from a sample of 10,187 volunteer agricultural extension workers in Rwanda and exogenously varied the salience of goals through reminders. Comparing people with the same initial goal hence allows us to disentangle the effect of goal magnitude from agent type. We find that goal reminders increase a performance index by 0.08 standard deviations. The relationship between goal magnitude and effectiveness follows an inverted U-shape. Our findings align with existing observational evidence and underscore the effectiveness of setting goals that are both ambitious and attainable.

Heterogeneous farmers' technology adoption decisions: Good on average is not good enough 

• Abstract: In spite of the importance of the agriculture sector and persistently low agricultural productivity, smallholders in Sub-Saharan Africa are unenthusiastic about a seemingly profitable modern technology — fertilizer, and at the same time are keen on a seemingly unbeneficial traditional technology — intercropping. This paper aims to understand the rationale behind farmers’ decisions about agricultural technology adoption and explain that adoption puzzle. I construct a farmer’s decision-making model that takes into account both the expected value and the variance of a farmer’s profit. This model features the farmer's production function with multiple technology choices, heterogeneous returns, selection bias, and heterogeneous variances for each technology. Using a Tanzanian panel dataset, I find that the expected returns of adopting the same technology vary significantly across farmers. Furthermore, adopting fertilizer significantly increases expected yields for farmers who adopt it every year, yet the higher expected returns are accompanied by larger variances. On the other hand, adopting intercropping does not increase the expected returns but significantly decreases the variance of yields. Farmers' technology adoption decisions are influenced positively by the expected value of profits and negatively by the variance of profits. These empirical results explain the low adoption rates of an intensively promoted higher-average-return technology such as fertilizer, and justify the high adoption rates of a seemingly unprofitable technology such as intercropping.   

• Blog post at Economics that really matters.

Works in Progress

The impact of digital agricultural extension service: Experimental evidence from rice farmers in India, with Shawn Cole, Jessica Goldberg, and Tomoko Harigaya.

Can mobile advisory improve nutritious crop adoption? Evidence from a field experiment in Kenya, with Tomoko Harigaya, Michael Kremer, and Jack Marshall.

Book Chapters and Policy Writings

Bryony Taylor, Henri Edouard Zefack Tonnang, Tim Beale, William Holland, Mary-Lucy Oronje, Elfatih Mohamed Abdel-Rahman, David Onyango, Cambria Finegold, Jessica Zhu, Stefania Pozzi, and Sean T. Murphy. Leveraging data, models & farming innovation to prevent, prepare for & manage pest incursions: Delivering a pest risk service for low-income countries. In Science and Innovations for Food Systems Transformation. Springer. 2022

Tomoko Harigaya, Jessica Zhu, Moses Mwanje, Emmanuel Bakirdjian, and Jackson Abuli. Digital platforms for boosting farmer knowledge: Two case studies in Kenya and Uganda. Proceedings of 1st African Conference of Precision Agriculture. 2020.

Tomoko Harigaya, Kaitlyn Turner, Hannah Timmis, Torsten Walter, and Jessica Zhu. Agro-dealer and farmer COVID-19 survey: April-June 2020. International Growth Center Policy Brief. 2020.