Journal Articles

- Trade-off between Yield and Nitrogen Pollution under Excessive Rainfall: Evidence from On-farm Field Experiments in Iowa (with Choi, E., G., P. Kyveryga, and S Fey). Accepted for Publication in Land Economics. (Link).

Climate change is expected to intensify rainfall, increasing the risk of nitrogen leaching in agriculture. This study incorporates the impact of excessive rainfall on crop yield and water pollution into an economic model for nitrogen management, tested using data from Iowa farm experiments. Findings show that optimal nitrogen application rates and environmental damage rise with excessive rainfall. Increased rainfall makes nitrogen more productive, raising the cost of controlling pollution. The study highlights resilient management practices like split nitrogen application with sidedressing. 

-Comparing Market Instruments for Forest Conservation in Brazil using Farm-level Census Data (with L. Veloso). Published online 2025:1-31 in Environment and Development Economics. doi:10.1017/S1355770X24000299 (Link).

This study evaluates the potential of agricultural land taxes and tradable forest certificates to conserve Brazil’s native vegetation on private properties using 2006 and 2017 micro census data. It examines optimal tax rates and forest certificate prices, revealing a supply-demand imbalance in the Amazon and high sensitivity to farmland opportunity costs. Despite changes in opportunity costs by 2017, market outcomes were unchanged. Expanding the market to include Amazon’s agricultural frontier could achieve 45% of conservation targets. The analysis highlights the interaction between conservation mechanisms and regional agricultural economics, emphasizing tailored approaches for effective conservation. 

-Smart Connected Farms and Networked Farmers to Improve Crop Production, Sustainability, and Profitability (with Asheesh K. Singh, Behzad J. Balabaygloo1, Barituka Bekee, Samuel W. Blair1, Suzanne Fey, Fateme Fotouhi, Ashish Gupta, Amit Jha, Jorge C. Martinez-Palomares, Kevin Menke, Aaron Prestholt, Vishesh K. Tanwar, Xu Tao, Anusha Vangala, Matthew E. Carroll, Sajal Das, Peter Kyveryga, Soumik Sarkar, Michelle Segovia, Simone Sylvestri, Corinne Valdivia). Frontiers in Agronomy, 2024, 6, p.1410829. (Link) 

Addressing agricultural challenges, including climate change impacts, requires integrating social science, technology, and agriculture experts. Advances in ICT, precision agriculture, and data analytics enable the development of smart connected farms (SCF) and networked farmers. These networks enhance farm production and profitability while mitigating climate effects. This article reviews SCF advancements in engineering, computer science, data science, social science, and economics, focusing on data privacy, sharing, and technology adoption. 

-Bundled Contracts and Technological Diffusion: Evidence from the Brazilian Soybean Boom. Journal of Development Economics, 2023, 165, p.103163. (Open access version)

Technological advances in the 1970s and 1980s allowed soybean cultivation in Brazil's Savanna, but many ranchers couldn't adopt it due to regional constraints. After Brazil's market reforms, international traders introduced a contract bundling technology, finance, inputs, and market access. Analysis of farm-level data shows this contract spurred rapid technological diffusion, agricultural expansion, and a 10-fold productivity increase by converting marginal land into commercial soybean plantations. 

-The distributional effect of climate change on agriculture: Evidence from a Ricar￾dian quantile analysis of Brazilian census data. Journal of Environmental Economics and Management, 2020, 104,p. 102378. (Link)

The economic impact of global warming varies across farms due to differences in climate, technology, and adaptive capacity, making average effect estimates insufficient for modeling climate change vulnerability. This study proposes a quantile model for climate change's distributional effect. Using data from 464,277 Brazilian farms, it finds that climate change impacts vary by climate, land quality, and irrigation choice. A 1°C increase harms warm climates, high-quality land, and irrigated farms the most. A 100-mm annual precipitation decrease severely affects dry climates, low-quality land, and irrigated farms. Vulnerability is highest in the warmest and driest climates, where farms have limited adaptive capacity. 

-Development and the Impact of Climate Change on Energy Demand: Evidence from Brazil. (With R. Mendelsohn). Climate Change Economics, 2010, vol. 1, No. 3 187-208. (Link)

This paper examines how climate affects residential electricity use across different income classes in Brazil. Using cross-sectional data, it finds that the temperature elasticity of electricity consumption varies significantly by income. Low-income households show no significant change, while middle and high-income households have long-run temperature elasticities of 0.8 and 1.6, respectively. As low latitude countries develop and incomes rise, the welfare damages of warming in the energy sector will become substantial.