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Cover crops, crop insurance losses, and resilience to extreme weather events

Research output: Contribution to journalArticlepeer-review

Abstract

This study investigates whether cover crop adoption reduces extreme-weather-related crop insurance losses. To achieve this objective, we utilize a county-level panel data set with information on cover crop adoption acres, crop insurance losses (i.e., specifically due to drought, excess heat, or excess moisture), and a number of weather variables. The data cover the main row crop production region in the Midwestern United States (US) for the period 2005 to 2018. We utilize linear fixed effects econometric models and a number of robustness checks in the empirical analysis (i.e., a fractional regression approach, two “external-instrument-free” estimation procedures, and a variety of alternative empirical specifications). The estimation methods used take advantage of the panel nature of the data to address various specification and endogeneity issues. We find evidence that counties with higher cover crop adoption tend to have lower crop insurance losses due to drought, excess heat, or excess moisture. Our analysis also indicates that cover crops likely have stronger loss mitigation effects against excess moisture events (like floods) and somewhat weaker loss mitigation impacts against droughts and excess heat. Nonetheless, our results overall suggest that cover crops can enhance resilience to extreme weather events and have the potential to be an effective climate change adaptation strategy in US agriculture.

Original languageEnglish (US)
Pages (from-to)1410-1434
Number of pages25
JournalAmerican Journal of Agricultural Economics
Volume106
Issue number4
DOIs
StatePublished - Aug 2024
Externally publishedYes

Keywords

  • climate change
  • cover crops
  • crop insurance losses
  • kinky least squares
  • moment-based instrumental variable (IV)
  • panel data
  • soil health
  • weather resilience

ASJC Scopus subject areas

  • Agricultural and Biological Sciences (miscellaneous)
  • Economics and Econometrics

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