Yuyuan Che

Assistant Professor
Department of Agricultural and Applied Economics
Texas Tech University

Peer-Reviewed Publications

  1. Che, Y., H. Feng, and D. A. Hennessy. 2023. Will Adoption Occur if a Practice is Win-Win for Profit and the Environment? An Application to a Rancher’s Grazing Practice Choices. Ecological Economics 209: 107826. Link

  2. Lu, X., Y. Che, R. M. Rejesus, B. K. Goodwin, S. K. Ghosh, and J. Paudel. 2023. Unintended Environmental Benefits of Crop Insurance: Nitrogen and Phosphorus in Water Bodies. Ecological Economics 204: 107657. Link

  3. Che, Y., R.M. Rejesus, M. Cavigelli, K. White, S. Aglasan, L.G. Knight, C. Dell, D. Hollinger, and E.D. Lane. 2023. Long-Term Economic Impacts of No-Till Adoption. Soil Security 13: 100103. Link

  4. Che, Y., H. Feng, and D. A. Hennessy. 2022. Assessing Peer Effects and Subsidy Impacts in Conservation Technology Adoption: Application to Grazing Management Choices. Journal of the Agricultural and Applied Economics Association 1(3): 285–303. Link

  5. Park, B., R. M. Rejesus, S. Aglasan, Y. Che, S. C. Hagen, and W. Salas. 2022. Payments from Agricultural Conservation Programs and Cover Crop Adoption. Applied Economic Perspectives and Policy 1-24. Link

  6. Hennessy, D. A., A. J. Lindsey, Y. Che, L. E. Lindsey, M. P. Singh, H. Feng, E. M. Hawkins, S. Subburayalu, R. Black, E. A. Richer, and D. S. Ochs. 2022. Characterizing the Decision Process in Setting Corn and Soybean Seeding Rates. The Journal of Extension 60(1): 3. Link

  7. Che, Y., H. Feng, and D. A. Hennessy. 2020. Recency Effects and Participation at the Extensive and Intensive Margins in the U.S. Federal Crop Insurance Program. The Geneva Papers on Risk and Insurance-Issues and Practice 45(1): 52-85. Link

  8. Wang, T., H. Jin, U. Kreuter, H. Feng, D. A. Hennessy, R. Teague, and Y. Che. 2020. Challenges for Rotational Grazing Practice: Views from Non-adopters across the Great Plains, USA. Journal of Environmental Management 256: 109941. Link

  9. Yu, Y., H. Li, Y. Che, and Q. Zheng. 2017. The Price Evolution of Wind Turbines in China: A Study Based on the Modified Multi-factor Learning Curve. Renewable Energy 103: 522-536. Link

Working Papers

  1. Seeding Rate Responses to Markets, Resources and Technologies. Yuyuan Che, David A. Hennessy, and Hongli Feng.

    Abstract: Corn and soybean seeding rates in the United States have moved in opposite directions over recent decades, with the former trending upward and the latter trending downward. Such different trends provide interesting opportunities to better understand how farmers’ seeding rate choices respond to market, resource, and technological factors. We develop a theoretical model of seeding rate choices by incorporating a resource budget trade-off between seeds and resources allocated to each seed. With a large and detailed U.S. farm-level market dataset over twenty years, we find the soybean seeding rate choice to be more price elastic than that for corn. Specifically, the seeding rate for soybean would decrease by 15% more than that for corn in response to a 10% increase in seed price or 10% decrease in crop price. Furthermore, more land-embodied inputs (e.g., soil nutrients) increase both corn and soybean seeding rates; while more seed-embodied inputs (e.g., genetically engineered treatment) increase corn rates but decrease soybean rates. The difference in price elasticities across crops due to different plant architectures has consequential implications, including for division of economic surplus arising from innovations and for the outcomes of policy incentives intended to mitigate the negative ecological impacts from seed use.

  2. Estimating Stochastic Production Functions with Linear Inequality Constraints. Yuyuan Che, Sujit K. Ghosh, and Roderick M. Rejesus.

    Abstract: This study develops moment-based parametric methods that accommodate linear inequality constraints when estimating stochastic production functions for production risk analysis. The estimation procedures developed are based on a frequentist and a Bayesian framework, which are respectively called Inequality Constrained Least Squares (ICLS) and Bayesian Inequality Constrained Least Squares (BICLS). Monte Carlo simulation results suggest that our proposed methods perform much better than traditional unconstrained moment-based procedures in terms of lower mean squared errors, variances, and standard errors for the parameter estimates. In addition, the superiority of the ICLS and BICLS procedures are empirically illustrated using long-term corn production data from university field trials that examine the performance of genetically modified (GM) corn varieties on experimental fields. Specifically, the proposed approaches with linear inequality constraints are used to examine the production risk effects of selected GM variety variables and a planting density variable.

  3. Cover Crops and Climate Risks: An Application of Causal Random Forests. David Quigley, Yuyuan Che, Mahmut Yasar, and Roderick M. Rejesus.

    Abstract: This study applies the causal random forest approach to investigate the extent to which persistent warming temperatures might induce farmers to utilize cover crops. Causal random forests is a novel statistical approach that allows for consistent and flexible estimation of heterogeneous treatment effects. The causal random forest technique is then applied to a unique satellite-based panel data set on cover crop adoption at pixel-level resolution. On average, we find evidence that being exposed to higher-than-average maximum temperatures at the end of the harvest season for multiple consecutive years influences farmers’ decisions to utilize cover crops. Moreover, our causal random forest analysis suggests that there is heterogeneity in the effect of persistent end-of-season heat events, and the heterogeneity is likely driven by precipitation and drought conditions at different points of the growing season. The evidence points to farmers increasingly utilizing cover crops voluntarily as weather patterns associated with global warming become increasingly common.

Work in Progress

  1. Evidence on the Private-Excess Fertilization Hypothesis. (with Hongli Feng, David A. Hennessy, and Chaoqun Lu)

  2. Irrationality of Recency Effects on U.S. Crop Insurance Program Participation. (with Hongli Feng and David A. Hennessy)

  3. Landscape Complexity, Crop Insurance Losses, and Resilience to Extreme Weather Events.

  4. Assessing Medium-Term Economic Impacts of Cover Crop Adoption.

  5. Payments from Agricultural Conservation Programs and No-Till Adoption.

  6. Do No-Till Practices Help Mitigate the Adverse Impacts of Excess Moisture Events?