Research

PAPERS IN REVIEW

• Hongqiang Yan, Ashok K. Mishra, Xi Zhou. Voluntary ESG Reporting and Firm Performance: An Exploration in China’s Food and Beverage Industry. (Revise and resubmit, Agribusiness: an international journal)

• Khanal, Aditya, Ashok K. Mishra, Jaweriah Hazrana, Hongqiang Yan. Risk Attitude, Perception, Management Experience, and Productivity: Evidence from a Semiparametric Approach and a Less-Developed Economy. (Revise and resubmit, European Review of Agricultural Economics)

• Mitchell Roznik, Ashok K. Mishra, Hongqiang Yan. Estimating the Effect of Temporal Changes in Soil-Related Crop Productivity Index on Crop Yield Risk. (Revise and resubmit, American Journal of Agricultural Economics)

WORKING PAPER

• Hongqiang Yan, Serkan Aglasan, Le Chen, Roderick Rejesus. The Impact of Soil Erosion on Mean Yields and Yield Risk.
  Latest version

  Abstract: This study examines the impact of soil erosion on crop yields in the United States (US) using county-level panel data. We use linear panel fixed effects (FE) models and a number of robustness checks to assess how soil erosion affects the mean, variance, skewness, and kurtosis of US corn and soybean yield distributions. Our analysis suggests that soil erosion, specifically caused by both water and wind, has a statistically significant negative impact on mean corn and soybean yields. We also find evidence that counties with higher levels of soil erosion tend to have corn yields with statistically higher variance and kurtosis. This suggests that soil erosion can lead to higher corn yield risks (or more instability in corn yields over time). However, we do not find strong evidence of this risk-increasing effect for soybean yields. Moreover, our analysis indicates that water-caused erosion tends to have a larger mean-yield-reducing effect compared to wind-caused erosion for soybeans, whereas no strong evidence of this pattern is found in corn. Overall, we estimate that the total damage of soil erosion for corn and soybeans in terms of mean yield reduction and risk increases amounts to around $4.43 billion in 2024. Findings from our analysis provide a better understanding of the economic damage caused by soil erosion since we not only provide evidence of its potential mean-yield-reducing effect, but also provide evidence of its potential risk-increasing effect.

• Hongqiang Yan, Barry Goodwin, Mehmet Caner. Global Maize Market Integration: A High-Dimensional Local Projection Approach with Mixed-Frequency Data and Regime Switching.
  (Available upon request)
  Abstract: This paper investigates the degree of market integration, exchange rate pass-through, and the market factors that contribute to deviations from perfect integration. To analyze the price linkage dynamics, we apply the novel debiased LASSO for Local Projection Approach, including linearity testing within high-dimensional Regime Switching regression models. Our findings reveal significant global maize market integration, particularly when incorporating threshold effects and key market factors. Notably, consumer prices and unemployment emerge as important determinants of price linkages, underscoring their relevance in the global commodity market.

• Hongqiang Yan, Ashok K. Mishra, Jaweriah Hazrana. Spatial Analysis of Modern Rice Varieties Technology on Production: Evidence from Panel Data in Bangladesh.
  (Available upon request)
  Abstract: Although modern rice varieties have the potential to enhance yields, their adoption among smallholder farmers in Bangladesh remains limited. Many farmers continue to favor inbred high-yielding or traditional local rice varieties, despite their suboptimal productivity. However, there is a lack of research examining how the adoption of modern rice varieties influences productivity in developing nations. This study explores this relationship by incorporating village- and location-specific heterogeneity in production technology within an advanced econometric framework. Using data from the Bangladesh Integrated Household Survey, we analyze spatial heterogeneity by integrating geographical coordinate information with a household-level panel dataset on rice production and technology adoption. Furthermore, we develop and estimate a location-dependent production function incorporating Hicks-neutral productivity. The findings reveal that the productivity impact of improved seed varieties is highly variable, primarily influenced by spatial characteristics rather than the specific rice variety type. These results underscore the crucial role of spatial factors in the adoption of modern rice varieties in Bangladesh and highlight important policy implications for optimizing resource and financial allocations to promote the adoption of improved agricultural technologies and support sustainable agricultural development in emerging economies.

• Jiatong Li, Hongqiang Yan. Uniform Inference in High-Dimensional Threshold Regression Models. (Co-first authored).
  Latest version

  Abstract: We develop a uniform inference theory for high-dimensional slope parameters in threshold regression models, allowing for either cross-sectional or time-series data. We first establish oracle inequalities for prediction errors and ℓ1 estimation errors for the Lasso estimator of the slope parameters and the threshold parameter, accommodating heteroskedastic non-subgaussian error terms and non-subgaussian covariates. Next, we derive the asymptotic distribution of tests involving an increasing number of slope parameters by debiasing (or desparsifying) the Lasso estimator in cases with no threshold effect and with a fixed threshold effect. We show that the asymptotic distributions in both cases are the same, allowing us to perform uniform inference without specifying whether the model is a linear or threshold regression. Additionally, we extend the theory to accommodate time-series data under the near-epoch dependence assumption. Finally, we demonstrate the consistent performance of our estimator in both cases through Monte Carlo simulations, and we apply the proposed estimator to empirical analyses of cross-country economic growth rates and the effect of a military news shock on U.S. government spending.
  Supplementary Material

• Mitchell Roznik, Ashok K. Mishra, Hongqiang Yan. Extreme Climate, Financial Health, and Credit Default Risk: An American Landscape.

  Abstract: Climate change is expected to increase the frequency and severity of drought in the United States. This study investigates the effect of drought conditions on farm credit default risk and examines the vulnerability of farms to enhanced drought risk. We use individual-level data from Farm Service Agency loan data covering seven-year operating loans. The study applies Cox proportional hazard and Generalized Gamma parametric survival models with various established financial health variables and drought. Findings suggest that lagged drought conditions, occurring in the growing season before loan origination, significantly increase the probability of default. A drought-affected borrower is about 11% more likely to default than an equivalent borrower who has not experienced drought. Non-white and Hispanic farmers affected by drought have higher default risks than their counterparts. Similarly, small and medium-sized farms, compared to large farms affected by drought, exhibit higher loan risk. These findings have important implications for lenders and policymakers, emphasizing the need for comprehensive risk assessment strategies that account for financial, demographic, and environmental factors in the agricultural sector.

WORK IN PROGRESS

• Hongqiang Yan Data-Driven Estimates of Structural Change in the Demand for Multiple Peril Crop Insurance.

• Hongqiang Yan, Mark Manfredo, Ashok K. Mishra. Machine Learning Forecasts for Food Price Inflation: Expanding FRED-MD.

• Hongqiang Yan, Ashok K. Mishra, Xi Zhou. Examining the Role of Spatial Heterogeneity in Productivity-Enhancing Activities: Evidence from the Chinese Food and Beverage Sector.