Applicability of the Normalized Difference Vegetation Index (NDVI) in Index-Based Crop Insurance Design

Abstract

Abstract Index insurance is becoming increasingly popular because of its ability to provide low-cost, relatively easy to implement agricultural insurance for vegetation types whose productivity has been notoriously difficult to measure and to farmers in less-developed nations where traditional crop insurance schemes are not reasonable to implement. This study examines if the remotely sensed normalized difference vegetation index (NDVI) can be an effective basis for index-based crop insurance over a diverse set of locations. To do this the authors compare Advanced Very High Resolution Radiometer (AVHRR) values to cumulative precipitation, extreme heat, and crop yields for 60 locations across the United States for the years 1982–2003. Quadratic regression equations are used to explore these relationships. The findings suggest that the relationship between NDVI, precipitation, extreme heat, and crop yields is highly variable and dependent on location-specific characteristics. Without site-specific calibration, NDVI should not be widely applied to index-based insurance product design. However, NDVI may still be a useful tool in insurance design under certain circumstances. This may be disappointing to proponents of NDVI as a risk transfer mechanism but the authors believe it important to report negative results as a caveat, and to give researchers and practitioners pause before investing time and money into the proposition.