2022 article

Risk effects of GM corn: Evidence from crop insurance outcomes and high-dimensional methods

Aglasan, S., Goodwin, B. K., & Rejesus, R. M. (2022, December 30). AGRICULTURAL ECONOMICS.

By: S. Aglasan*, B. Goodwin n & R. Rejesus n

author keywords: cluster-lasso; genetically modified corn; high-dimensional weather variables; post-double-selection; yield risk
UN Sustainable Development Goal Categories
1. No Poverty (Web of Science)
2. Zero Hunger (Web of Science)
13. Climate Action (Web of Science)
Source: Web Of Science
Added: January 17, 2023

AbstractThis study evaluates whether genetically modified (GM) corn hybrids with rootworm resistant traits (GM‐RW) have lower yield risk. A crop insurance actuarial performance measure, the loss cost ratio (LCR), is used to represent yield risk. High‐dimensional methods are utilized in this study to maintain parsimony in the empirical specification, and facilitate estimation. Specifically, we employ the Cluster‐Lasso (cluster‐least absolute shrinkage and selection operator) procedure. This method produces uniformly valid inference on the main variable of interest (i.e., the GM‐RW variable) in a high‐dimensional panel data setting even in the presence of heteroskedastic, non‐Gaussian, and clustered error structures. After controlling for a large set of potential weather confounders using Cluster‐Lasso, we find consistent evidence that GM corn hybrids with rootworm resistant traits have lower yield risk.