Underinsured by Precision: Weather Forecasts, Contract Timing, and Risk Sharing under Liquidity Constraints

Climate forecasts and index insurance are often viewed as complementary tools for managing climate risk, especially in developing countries. I show how this complementarity can fail when climate information changes the terms on which insurance is available. When that information enters insurance pricing, adverse news raises actuarially fair premiums, exposing insured households to premium risk and liquidity-constrained households to underinsurance. A model quantified with data from Ethiopia’s Index-Based Livestock Insurance program shows that, under an illustrative high-precision forecast, 54.1 percent of households cannot finance a standardized coverage package, while only 1.5 percent cannot finance one tropical livestock unit. With adaptation and exposure adjustment disabled, the repricing loss equals about half the value of full pooled insurance. Forecasts also improve adaptation, creating a trade-off between decision gains and lost risk sharing. Earlier contracting can preserve pooling while retaining the decision value of information, making adaptation capacity and contract timing jointly central to the value of better forecasts.