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 insurance spatial econometric models with missing data NDVI Kenya pastoralist livestock production cross-validation model 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