Financial Literacy, Social Networks, & Index Insurance

Transcription

1 Financial Literacy, Social Networks, and Index-Based Weather Insurance Xavier Giné, Dean Karlan and Mũthoni Ngatia Building Financial Capability January 2013

2 Introduction Introduction Agriculture in developing countries is characterised by high risk: high dependence on weather limited irrigation. Weather shocks are a major source of income fluctuation for rural households involved in agricultural activities.

3 Introduction Do Households Need Insurance? There is evidence that risk-sharing mechanisms are inadequate particularly against covariate weather risk: Local rainfall variation around the time of birth significantly affects schooling, health and socio-economic status measured in adulthood (Maccini and Yang, 2009). Duflo and Udry (2004) reject the null of perfect risk-sharing even with respect to rainfall shocks within households. Evidence that rainfall shocks generate plausibly exogenous variation in income that can lead to poverty traps (Dercon and Oates, 2009). Households engage in costly income smoothing in response to rainfall risk.

4 Introduction Insurance Traditional crop insurance has had limited success. Index-based weather insurance Farmer insures crop, based on a proxy (rainfall) that causes yield loss. Insurance pays the farmer if expected rainfall does not occur, irrespective of yield loss, as long as the the index is triggered. Benefits: Eliminates Moral Hazard Low transaction Costs Fast settlement of claims, payments are not subjective. However, voluntary uptake of Index Insurance has been limited (Giné et al. 2007, 2008, Cole et al. 2009).

5 Introduction Insurance Role of financial literacy in influencing attitudes and understanding of insurance. Role of social networks.

6 Introduction Results Social networks reinforce messages from financial literacy materials. Receiving financial literacy materials when 60% or more of a farmers neighbours also receive financial literacy materials increases the likelihood that a farmer will purchase insurance by 4.3% (s.e. 2.5%) Receiving a financial literacy materials when 40% or fewer of a farmers neighbours also receive financial literacy materials decreases the likelihood that a farmer will purchase insurance by 2.6% (s.e. 2.5%). Strong individual effects for discount vouchers on farmers decision to purchase insurance but no social network effects.

7 Introduction Outline Study Design Results Conclusion

8 Study Design I Study was carried out with coffee farmers in Eastern Kenya. At the baseline we first enumerated all the coffee growing households within the study area. Following the census, households were grouped together into clusters based on geographic proximity. Clusters were randomized to either high or low intensity of comic and voucher provision.

9 Study Design II 904 Households 189 Clusters No Comic 276 Households 61 Clusters Low Comic 307 Households 65 Clusters High Comic 321 Households 63 Clusters High Voucher 138 Households 31 Clusters Low Voucher 138 Households 30 Clusters High Voucher 163 Households 33 Clusters Low Voucher 144 Households 32 Clusters High Voucher 164 Households 31 Clusters Low Voucher 157 Households 32 Clusters Figure : Study Design

10 This is how it will work in the field: Rainfall will be measured throughout the season. Each of the growing phases of the crop has its specific water requirement. Planting and Germination Flowering Harvest If the rainfall is too Figure low at : any Panel part 1 of the crop season, the farmer will receive an insurance payout that will be offset against the outstanding loan amount. For instance, if rainfall is too low at germination, Giné, the Karlan maize & Ngatia won t Financial grow at Literacy, all. Farmers Social Networks, will & receive Index Insurance

11 Stunted crop Average crop The insurance payout amount is calculated using a formula that is specified in the insurance contract and triggered automatically if rainfall amounts are above or below given levels. The more extreme the rainfall compared to historical averages, the larger the payout and more of the loan is paid down. 0mm Low rainall Average rainfall No germination Payout Stunted crop Some payout No payout 10 Figure : Panel 2

12 But what will happen if the rains are normal and we receive a good harvest? Will we get our premium back? No, premiums are non refundable. Once the premium is paid, it cannot be returned. Figure 13 : Panel 3

13 50 % 50 % INSURANCE DISCOUNT COUPON This voucher entitles to get a 50% discount on the purchase of Name: ID Number: Please present this voucher with your ID card to receive the discount amount mentioned above. Expires: 5th March, 2011 Weather Index Insurance offered by APA Insurance Company. Authorized by: Figure : 50% Voucher

14 Summary Table : Summary Statistics by Intervention Mean Comic in High Comic Cluster Comic in Low Comic Cluster No Comic in High Comic Cluster No Comic in Low Comic Cluster Voucher in High Voucher Cluster Voucher in Low Voucher Cluster p value Male (0.039) (0.057) (0.059) (0.039) (0.075) (0.086) Age (1.714) (2.647) (3.035) (1.792) (3.530) (3.953) Household size (0.213) (0.292) (0.303) (0.214) (0.405) (0.493) Years of education (0.396) (0.574) (0.620) (0.394) (0.748) (0.951) Able to read a newspaper (0.041) (0.059) (0.062) (0.041) (0.080) (0.092) Asked for credit year before (0.039) (0.051) (0.056) (0.039) (0.071) (0.087) Agrees Drought is the most impt risk my household faces. (0.041) (0.057) (0.062) (0.042) (0.080) (0.093) Patient (0.043) (0.061) (0.064) (0.044) (0.083) (0.100) Understand insurance (0.045) (0.065) (0.065) (0.047) (0.087) (0.103) Notes: * significant with 90% confidence, ** 95%, *** 99%. Patient is a dummy equal to 1 if the respondent prefers to receive KSh 1250 in a month to KSh 1000 today. Exchange rate was about 80 KSh to 1Giné, USD during Karlan the & Ngatia study period.

15 Results I Dependent Variable: Bought Index Insurance (1) (2) (3) (4) Comic (0.019) Voucher (0.039) Low Comic (0.020) High Comic (0.023) High Voucher (0.017) Comic in High Comic (0.025) (0.025) Comic in Low Comic (0.025) (0.026) No Comic in High Comic (0.037) (0.037) No Comic in Low Comic (0.023) (0.023) Voucher in High Voucher (0.046) (0.047) Voucher in Low Voucher (0.049) (0.050) Observations Mean among Controls Controls NO NO NO YES Notes: Robust standard errors, in parentheses.

16 Results II Dependent Variable: Bought Index Insurance (1) (2) (3) (4) (5) (6) 0-150m away 0-200m away 0-300m away Comic (0.025) (0.025) (0.028) (0.028) (0.032) (0.032) # Comics 0-Xm away (0.010) (0.011) (0.009) (0.009) (0.006) (0.006) Comic * # Comics Xm away (0.017) (0.017) (0.012) (0.012) (0.007) (0.007) Voucher (0.052) (0.054) (0.058) (0.059) (0.071) (0.072) # 50% vouchers 0-Xm away (0.012) (0.012) (0.009) (0.009) (0.007) (0.007) Voucher * # 50% vouchers Xm away (0.020) (0.021) (0.016) (0.017) (0.010) (0.011) # Contacts Xm away (0.008) (0.008) (0.006) (0.006) (0.004) (0.004) Observations Mean among Controls 0.02 Village Fixed Effects YES YES YES YES YES YES Controls NO YES NO YES NO YES Notes: * significant with 90% confidence, ** 95%, *** 99%. Robust standard errors clustered at the village level, in parentheses. Regressions (2), (4) and (6) includes controls for farmer s raven score, years of education, gender, ability to read a newspaper, ability to write a letter, score for coffee best practices followed, whether or not the farmer agrees that drought is the most important risk that he/she faces, a score for whether the farmer is patient, number of coffee trees, whether the farmer understands index insurance, whether the farmer can identify Giné, 60mm Karlan in& angatia drawing.

17 Follow up A phone follow-up survey was carried about 7 months after the start of the contract. There had been a drought, and insurance paid out.

18 Follow-up Dependent Variable: Interviewed in Follow-up Survey (1) (2) (3) Comic (0.035) Voucher (0.078) High Comic Cluster (0.042) Low Comic Cluster (0.042) High Voucher Cluster (0.034) Comic in High Comic (0.045) Comic in Low Comic (0.062) No Comic in High Comic (0.066) No Comic in Low Comic (0.046) Voucher in High Voucher (0.085) Voucher in Low Voucher (0.102) Observations Mean among Controls F test P-value of F model Giné, Karlan 0.186& Ngatia Financial Literacy, Social Networks, & Index Insurance

19 Knowledge Knowledge Score on Index Insurance at Follow-up (1) (2) Comic in High Comic (0.044) (0.045) Comic in Low Comic (0.068) (0.069) No Comic in High Comic (0.063) (0.063) No Comic in Low Comic (0.046) (0.046) Voucher in High Voucher (0.086) (0.086) Voucher in Low Voucher (0.101) (0.100) Baseline knowledge score of index insurance (0.032) (0.051) (0.058) Observations R-squared Mean of Dependent Variable Among Controls Village Fixed Effects YES YES Controls NO YES * significant with 90% confidence, ** 95%, *** 99%. Robust standard errors in parentheses. All regressions include Village Fixed Effects. Regressions (2) includes controls for farmer s raven score, years of education, gender, ability to read a newspaper, ability to write a letter, score for coffee best practices followed, whether or not the farmer agrees that droughtginé, is thekarlan most & important Ngatia risk Financial that he/she Literacy, faces, Sociala score Networks, for whether & Indexthe Insurance farmer is

20 Insurance Attitudes Insurance protects you in times of emergency (1) (2) (3) Insurance companies try to cheat people even when they have a good claim I don t need insurance because my family, friends or relatives provide cover when necessary Comic in High Comic (0.029) (0.063) (0.061) Comic in Low Comic (0.052) (0.088) (0.088) No Comic in High Comic (0.034) (0.086) (0.089) No Comic in Low Comic (0.033) (0.063) (0.062) Voucher in High Voucher (0.059) (0.113) (0.115) Voucher in Low Voucher (0.055) (0.142) (0.140) Baseline Attitude (0.023) (0.056) (0.080) Observations R-squared Mean Among Controls Village Fixed Effects YES YES YES Notes: Robust standard errors, in parentheses. significant with 90% confidence, 95%, 99%.

21 Conclusion I Using a randomized experiment we compare the effect of financial literacy materials and discount vouchers in influencing farmers decision to purchase index insurance. Our results provide suggestive evidence that financial literacy materials are efficacious in encouraging take-up when farmers social contacts are similarly receive access to financial literacy materials.

22 Conclusion II Thank you!