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Can Index Insurance Improve Credit Access Among Smallholder Farmers in Ghana
1. Can Index Insurance Improve Credit Access Among
Smallholder Farmers in Ghana?
Does It Differ Over Male and Female Farmers?
Khushbu Mishra1 Richard Gallenstein1 Mario J. Miranda1
Abdoul G. Sam1 Patricia Toledo2
1The Ohio State University
2Ohio University
2016 AAEA Annual Meeting, July 31 - August 2, 2016
Mishra et al. (OSU) Index Insurance Ghana 2016 AAEA 1 / 20
2. Motivation and Theory
Poor farmers unable to obtain credit needed to invest in improved
production technologies
Catastrophic weather risk undermines efficiency of agricultural credit
markets, reducing supply of credit
Lenders suffer widespread loan defaults after a catastrophic weather
event
Index insurance: potential to expand credit access if properly
integrated into lenders’ agricultural credit portfolio
Mishra et al. (OSU) Index Insurance Ghana 2016 AAEA 2 / 20
3. Theoretical Predictions
Theoretical foundations based on structural models (Miranda &
Gonzalez-Vega, 2011; Farrin & Miranda, 2013).
Insuring agricultural loans, with payouts made to lenders, can reduce
impact of widespread default on lenders.
Reduced systemic risk allows lenders expand supply of credit, reduce
the interest rates, improve adoption of more productive technologies.
Mishra et al. (OSU) Index Insurance Ghana 2016 AAEA 3 / 20
4. Hypotheses
Insured loans can encourage the borrowers to seek credit.
Insured loans can encourage the lenders to give credit.
Male clients are known to have higher default rates; they will see a
larger positive effect in their likelihood of approval rates (Sharma &
Zeller 1997; Kevane & Wydick 2001).
Mishra et al. (OSU) Index Insurance Ghana 2016 AAEA 4 / 20
5. Research Design
258 farmer groups taken from existing or potential clients of RCBs.
Roughly account for 2500 individual farmers.
Randomly assigned treatments across farmer groups.
Control: Smallholders offered loans, but not index insurance.
Treatment 1 (Individual Policy): Insurance covering 100% of the loan
offered to borrowers, payout goes to the borrower.
Treatment 2 (Bank Policy): Insurance covering 100% of the loan
offered to borrowers, payout goes to the bank.
The insurance premium is covered in full by the project (as in Karlan
et al. 2011).
Mishra et al. (OSU) Index Insurance Ghana 2016 AAEA 5 / 20
6. Region of Study
Figure 1: Study Districts with Number of Farmer Groups
Mishra et al. (OSU) Index Insurance Ghana 2016 AAEA 6 / 20
7. Region of Study
Table 1: Farmer groups by treatment categories and region
Treatment status Control Treatment 1 Treatment 2 Total
Northern region 33 32 33 98
Upper East region 44 44 44 132
Upper West region 9 11 8 28
Total 87 88 87 258
Mishra et al. (OSU) Index Insurance Ghana 2016 AAEA 7 / 20
8. Preliminary Results
Table 2: Treatment Effects from LPM
Loan Application (1) (2)
Individual Policy (T1) 0.0421 0.0412
Bank Policy (T2) 0.0310 0.0346
Observations 1406 1394
Bank dummies Yes Yes
Additional Controls No Yes
Mishra et al. (OSU) Index Insurance Ghana 2016 AAEA 8 / 20
9. Preliminary Results
Table 3: Treatment Effects from LPM
Loan Approval (1) (2)
Individual Policy (T1) 0.0822 0.0987
Bank Policy (T2) 0.229*** 0.232***
Observations 1344 1331
Bank dummies Yes Yes
Additional Controls No Yes
Mishra et al. (OSU) Index Insurance Ghana 2016 AAEA 9 / 20
10. Preliminary Results
Table 4: Treatment Effects from Heckman Selection Model
Loan Approval (1) (2)
Individual Policy (T1) 0.154 0.146
Bank Policy (T2) 0.231** 0.230**
Observations 1039 1039
Bank dummies Yes Yes
Additional Controls No Yes
Note: Exclusion restriction - Risk Aversion & Risk Aversion Likert Scale 1-5
Mishra et al. (OSU) Index Insurance Ghana 2016 AAEA 10 / 20
11. Preliminary Results
Table 5: Treatment Impacts from LPM
Loan Application Female Male
Individual Policy (T1) 0.127 -0.0248
Bank Policy (T2) 0.0925 -0.0094
Observations 661 733
Bank dummies Yes Yes
Additional Covariates Yes Yes
Mishra et al. (OSU) Index Insurance Ghana 2016 AAEA 11 / 20
12. Preliminary Results
Table 6: Treatment Effects from LPM
Loan Approval Female Male
Individual Policy (T1) 0.117 0.0806
Bank Policy (T2) 0.215* 0.249**
Observations 637 694
Bank dummies Yes Yes
Additional Covariates Yes Yes
Mishra et al. (OSU) Index Insurance Ghana 2016 AAEA 12 / 20
13. Preliminary Results
Table 7: Treatment Effects from Heckman Selection Model
Loan Approval Female Male
Individual Policy (T1) 0.210 0.0879
Bank Policy (T2) 0.241* 0.245**
Observations 502 520
Mills Ratio 0.126 0.625**
Bank Dummies Yes Yes
Additional Covariates Yes Yes
Note: Exclusion restriction – Risk Aversion & Risk Aversion Likert Scale 1-5
Mishra et al. (OSU) Index Insurance Ghana 2016 AAEA 13 / 20
14. Results Summary
Results
Index insurance does not increase loan application rates.
Treatment 1 does not increase the bank’s likelihood of farmer’s loan
approval.
Treatment 2 increases the bank’s likelihood of farmer’s loan approval.
Treatment 1 does not impact male or female loan approval rates.
Treatment 2: marginally and moderately significant for female and
male farmers.
Mishra et al. (OSU) Index Insurance Ghana 2016 AAEA 14 / 20
15. Policy Implications
Index insurance can be a tool to reduce supply side barriers by
increasing the lenders’ portfolio.
Reduce interest rate.
Increase technology adoption and agricultural efficiencies.
Mishra et al. (OSU) Index Insurance Ghana 2016 AAEA 15 / 20
17. Preliminary Results
Table 8: Pairwise Mean Comparisons for All Applicants
Binary Outcomes Control Treatment 1 Treatment 2
Loan Application R0 0.9037 0.9403 0.9
Loan Application R1 0.7665 0.8506** 0.7915
Loan Approval R0 0.7423 0.7790 0.6718*
Loan Approval R1 0.6650 0.8219*** 0.8413***
Mishra et al. (OSU) Index Insurance Ghana 2016 AAEA 17 / 20
18. Results for Female vs. Male Farmers
Table 9: Pairwise Mean Comparisons for Males and Females
Endowment Males Female
Cattle 5.7 3.1**
Poultry 26 20.4***
Small Livestock 13.6 10.8*
Total Income 2403.6 1973.8***
Agricultural Income 1531 1278***
Amount of Savings 368.3 352
Total Acres Planted 7.8 5.7***
Mishra et al. (OSU) Index Insurance Ghana 2016 AAEA 18 / 20
19. Preliminary Results
Table 10: Pairwise Mean Comparisons for Male and Female Applicants
Binary Outcomes Control Treatment 1 Treatment 2
Female Applicants R0 0.9381 0.9722 0.973
Female Applicants R1 0.7321 0.8636*** 0.8195
Male Applicants R0 0.8760 0.9032 0.8181
Male Applicants R1 0.7931 0.8372 0.7619
Mishra et al. (OSU) Index Insurance Ghana 2016 AAEA 19 / 20
20. Preliminary Results
Table 11: Pairwise Mean Comparisons for Male and Female Applicants
Binary Outcomes Control Treatment 1 Treatment 2
Female Approval R0 0.7232 0.7954 0.7218
Female Approval R1 0.6136 0.8649*** 0.8349***
Male Approval R0 0.7568 0.7619 0.6190**
Male Approval R1 0.7043 0.7778 0.8485**
Mishra et al. (OSU) Index Insurance Ghana 2016 AAEA 20 / 20