Index Based Livestock Insurance (IBLI) 04
My previous essay reviews the household data we collected to study insurance uptake and impacts. In this essay, I will review how to measure the impact using the data and insurance premium discount coupons.
The major challenge in measuring the impact is endogeneity of insurance uptake. Our central question is how much insurance improves households’ welfare. The cause is insurance and the result is welfare. Studying this causality is difficult due to unobserved household characteristics and endogeneity of insurance uptake. To simplify this reasoning, let us say unobserved household characteristics is household ability and more able households buy insurance more likely (and endogenously). Let us call the latter endogeneity of insurance uptake. If so, we cannot tell whether insurance improves household welfare or more able households improve their welfare and buy insurance at the same time. In this case, if we do not control this endogeneity of insurance uptake, our estimate of the impacts of insurance on household welfare will end up larger than the true value.
To control this endogeneity, we designed a randomized controlled trial (RCT). Since it is difficult to ask insurance companies to sell insurance to particular households or in particular villages and not to sell to the others, we provided insurance premium discount coupons to particular households among our 924 sample households in Marsabit, Kenya and 515 sample households in Borena, Ethiopia. We call households who received the coupons treatment group and the other households who did not receive the coupons control group. We randomly split the households into treatment group and control group. The simplest RCT compares average welfare in the treatment group with average welfare in the control group and the impacts is the difference in welfare. In our case, if we did so, the difference in average welfare would be the impacts of discount coupon rather than the impacts of insurance.
In order to obtain the impacts of insurance, we use an Econometircs method called instrument variable (IV) method. Our dependent variable Y is household welfare such as income and explanatory variable X is insurance uptake. Our equation of interest is Y = a + bX + e where a is average welfare (called constant term) and e is other factors influencing welfare (called error term). Coefficient b is the estimate we would like to have and the impacts of insurance (X) on household welfare (Y). IV method allows us the following. Even if insurance uptake (X) is influenced by ability captured in error term (e), we can estimate coefficient b using an instrument variable (Z) which is strongly related to insurance uptake (X) but unrelated to error term (e). Let us consider whether discount coupon can be an instrument variable (Z). First, discount coupon encourages insurance uptake and thus our instrument variable (Z) can strongly related to insurance uptake (X). Second, we randomly split households into treatment group who receives discount coupons and control group who does not and thus our instrument variable (Z) should be unrelated to other factors affecting household welfare (error term, e).
In this essay, I review that insurance premium discount coupon allows us to measure the impact of insurance on household welfare. In the next essay, I will review studies on insurance uptake and impacts using the household data and the discount coupons.
(Author: Munenobu Ikegami)