Patterns Of Rainfall Insurance Participation In Rural India

Abstract

Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. A basic research question for the study of micro-insurance markets is estimating the crosssectional determinants of household insurance takeup, and identifying the impediments to trade that prevent remaining households from participating. After describing the insurance product, we present empirical evidence on the determinants of insurance participation, based on a household survey implemented by ICRISAT and the World Bank in late 2004. We first evaluate takeup patterns against a simple neoclassical benchmark, which predicts that insurance participation is increasing in risk aversion and the variance of risk, and decreasing in basis risk between insurance payouts and the risk to be insured. We find some evidence consistent with the basis risk prediction; Terms of use: Documents in EconStor maynamely households who historically plant a high share of castor and groundnut, the two crops for which contracts are designed, are more likely to purchase insurance. Takeup rates are also higher amongst wealthy households, and lower amongst households identified as credit constrained. These findings are consistent with an extension of the 'benchmark' model to include borrowing constraints.Other evidence is more difficult to reconcile with the benchmark model. First, amongst the quantitatively most significant determinants of insurance takeup are variables measuring the household's degree of familiarity with the insurance vendor, such as whether the household is an existing BASIX customer. Participation is also higher amongst households that are members of the town Gran Panchayat (local council), and those that are connected to other village networks, especially when a larger number of other members or the household's primary network also buy insurance. Second, risk-averse households are somewhat less likely to take up rainfall insurance, 3 not more likely as the neoclassical framework would suggest. This result is concentrated amongst households who are unfamiliar with the vendor, BASIX, or do not use other types of insurance.We interpret these finding to suggest that many households are uncertain about the insurance product itself, leading risk-averse households, households with higher costs of evaluating new technologies, and households who are less familiar or place less trust in the insurance provider, to eschew purchasing insurance. This interpretation is also consistent with qualitative evidence: lack of understanding about the product was the most commonly cit...

Barriers to Household Risk Management: Evidence from India

“…They are also in line with the evidence in Giné, Townsend and Vickery (2008), which presents correlates of the determinants of insurance participation using an earlier 2004 household survey.…”

“…One interesting related finding documented in Section VI.A is that measured household risk aversion is negatively correlated with insurance demand in both Andhra Pradesh and Gujarat. Giné, Townsend and Vickery (2008) also find the same result, which they show is concentrated amongst households without knowledge of BASIX or of insurance. One potential interpretation is that uninformed risk-averse or ambiguity-averse households are unwilling to experiment with the insurance product, given their limited experience with it.…”

“…These households were originally selected in 2004 based on a stratified random sample from a census of approximately 7,000 landowner households (see Giné, Townsend and Vickery (2008) for details). This survey sample is exactly the same set of households used for our field experiments (details of the experimental design are presented in Section III).…”

“…As a result, we examine which non-price frictions further limit insurance demand (see also Giné, Townsend and Vickery, 2008, and Giné et al, 2012, for a discussion of these frictions). Our first finding is that households do not fully trust or understand the insurance product, and that their level of trust significantly affects demand.…”

Meso-level weather index insurance

“…Despite the potential of (agricultural) insurance for investment stimulation (Karlan et al, 2014), there is evidence that insurance uptake in developing countries is low (Cole et al, 2013a;Dercon et al, 2014;Giné et al, 2008;Giné and Yang, 2009;Janvry et al, 2014). There is research arguing that non-price aspects, such as trust or salience, are important (Cole et al, 2013a;Giné and Yang, 2009) and others that focus on price effects.…”