A Spatial Econometric Approach to Designing and Rating Scalable Index Insurance in the Presence of Missing Data

  • Joshua D Woodard
  • Apurba Shee
  • Andrew Mude
Original Article

DOI: 10.1057/gpp.2015.31

Cite this article as:
Woodard, J., Shee, A. & Mude, A. Geneva Pap Risk Insur Issues Pract (2016) 41: 259. doi:10.1057/gpp.2015.31

Abstract

Index-Based Livestock Insurance has emerged as a promising market-based solution for insuring livestock against drought-related mortality. The objective of this work is to develop an explicit spatial econometric framework to estimate insurable indexes that can be integrated within a general insurance pricing framework. We explore the problem of estimating spatial panel models when there are missing dependent variable observations and cross-sectional dependence, and implement an estimable procedure which employs an iterative method. We also develop an out-of-sample efficient cross-validation mixing method to optimise the degree of index aggregation in the context of spatial index models.

Keywords

index insurancespatial econometric models with missing dataNDVIKenya pastoralist livestock productioncross-validationmodel mixing

Copyright information

© The International Association for the Study of Insurance Economics 2016

Authors and Affiliations

  • Joshua D Woodard
    • 1
  • Apurba Shee
    • 2
  • Andrew Mude
    • 3
  1. 1.Charles H. Dyson School of Applied Economics and Management, Cornell UniversityNYU.S.A.
  2. 2.Environment and Production Technology DivisionInternational Food Policy Research InstituteArushaTanzania
  3. 3.International Livestock Research InstituteNairobiKenya