Mai Mahmoud - Research

Pricing and Allocation of New Agricultural Technologies (Job Market Paper)

World Bank Development Impact Blog post: available here

This study uses a two-stage experiment to examine whether lower prices allocate new agricultural technologies to farmers with lower returns. In stage one, I randomize a price subsidy, ranging from full to zero subsidies, for a new wheat seed variety. In stage two, I randomize free distribution across the self-selected sample of non-buyers from stage one. This design allows me to compare treatment effects across the entire population with treatment effects among the sample choosing not to buy the seed. If higher prices screen out farmers with low willingness to adopt, then the effect of stage-two free distribution on adoption by non-buyers should be trivial. Instead, I find that the stage-two free distribution increases adoption and wheat cultivation by an amount almost equal to the effect from stage one. In addition, farmers choosing not to buy in stage one do not realize lower returns to adoption --despite there being substantial heterogeneity in returns across the sample. Taken together, these findings imply that policy makers who aim to increase dissemination of agricultural technologies cannot rely on market prices as a mechanism for targeting high return farmers.

Targeting of Food Aid Programs (with Sikandra Kurdi)

Paper: available here

In-kind food aid programs remain prominent world-wide. Targeting in these programs is complex due to the potential for distortion of consumption choices and the need to balance competing objectives. This paper uses data from a randomized controlled trial (RCT) to examine whether observable characteristics can be leveraged to improve the targeting of food transfers. Using machine learning (ML) techniques, we demonstrate heterogeneity in impacts across a range of outcomes. Importantly, observable characteristics, such as demographics, dwelling conditions, and asset ownership, significantly predict this heterogeneity. However, the relevant predictors vary by outcome and by treatment type. These findings suggest that ML methods can identify targeting criteria tailored to specific policy objectives, though policymakers must decide on the weights to give to competing objectives.

Are Those Who Know and Those Who Don’t Know Alike? Implication of Seed Misclassification on Adoption of Complementary Inputs and Agricultural Yield (with Kibrom Abay)

Imperfect information on agricultural inputs can impede technology adoption and farm management decisions. In this paper, we use a dataset that contrasts farmers’ perceptions of the type of seed variety with a lab-based measure using DNA-fingerprints. We show that farmers use of complementary inputs is driven by farmers’ (mis)perceptions of the seed type rather than actual features of the seed. We also provide suggestive evidence that accurate knowledge of seed variety is associated with higher yield. Ideally, the yield gap between farmers who act based on correct versus wrong perceptions should be directly observable to all farmers. However, farmers observe yield outcomes (measured by dividing total harvest by farm area) with a margin of error due to mismeasurements in both harvest quantity and size of farm plot. The combination of measurement errors in both input and output may explain the persistence of wrong perceptions of seed types over time.

Publications

Plot Size and Sustainable Input Intensification in Smallholder Irrigated Agriculture: Evidence from Egypt (with Kibrom A. Abay, Lina Abdelfattah, Hoda El-Enbaby, Clemens Breisinger), Agricultural Economics, 2022.

Increasing population pressure and population density in many African countries are inducing land scarcity and land constraints. Tightening land constraints are expected to trigger various responses, including agricultural intensification, as postulated by the Boserup hypothesis. The relevance of the Boserup hypothesis in irrigated agriculture, and in contexts where application of improved inputs is high, remains largely unexplored. Furthermore, while much of the debate on the topic in Africa has focused on how to boost agricultural intensification, there is scant evidence on whether evolving agricultural intensification practices in some parts of Africa are sustainable. In this article, we investigate the implication of land size (at the plot and farm level) on agricultural intensification. Our analysis sheds light on the relevance of the Boserup hypothesis in the context of Egypt, where irrigation dominates agriculture and input application rates are high relative to global standards. We also examine whether evolving agricultural intensification practices induced by land scarcity are agronomically appropriate. Our findings show that smaller plot and farm sizes are associated with higher application of agricultural inputs, mainly nitrogen fertilizers. Importantly, small plot size is associated with overapplication of nitrogen fertilizer relative to crop-specific agronomic recommendations. In addition, smaller plots are associated with higher rates of labor application and lower rates of mechanization.

Do Estimates of Women’s Control over Income and Decisionmaking Vary Across Nationally Representative Survey Programs? (with Kalyani Raghunathan, Jessica Heckert, Gayathri Ramani, Greg Seymour) Social Indicators Research, 2025

Empowering women is an explicit aim of Sustainable Development Goal (SDG) 5 and underpins 12 of the 17 SDGs. It is also a key objective of other pan-national agreements, such as the Comprehensive African Agriculture Development Programme. Tracking global progress toward these goals requires being able to measure empowerment in ways that are consistent and comparable—both within and across countries. However, empowerment is a complex concept, hard to quantify, and even harder to standardize across contexts. Two large survey programs—Feed the Future and the Demographic Health Surveys—ask women about two aspects of empowerment, their control over income and input into decisionmaking. Each program uses a different set of questions administered to different sub-populations of women. We use data from 12 countries to show that large within-country inter-survey differences persist even after efforts to harmonize questions and samples. Where available, we compare the FTF and DHS with the Living Standards and Measurement Surveys-Integrated Surveys on Agriculture. We present several hypotheses related to survey structure and survey administration to explain these inter-survey differences. We then either test for or rule out the role of these competing theories in driving differences in levels and in associations with commonly used characteristics. Standardizing survey measures of decisionmaking and control over income and how they are administered is important to track progress toward the SDGs; meanwhile, caution should be exercised in comparing seemingly similar survey items across survey programs.

Work-in-progress

Do Carbon Offsets in Agriculture Deliver Benefits to the Environment?: Evidence from a Randomized Evaluation (with Siddhi Doshi and Kyle Emerick)

Unpacking Social Perceptions of Technical Education and Vocational Occupations (with Adam Osman and Abu Shonchoy)