India’s main crop insurance scheme is the Pradhan Mantri Fasal Bima Yojana (PMFBY), a multiple-peril yield-based crop insurance program. A majority of PMFBY premiums are subsidized by central and state government payments to insurers to maintain modest premium rates charged to farmers, which are 1.5–2.0% of sum insured for most crops.
The central government–run PMFBY has seen two major operational changes since its inception in 2016 and some states are now exploring further changes to minimize the net cost of their premium subsidies. A key example is the “cup and cap” crop insurance approach developed by the state of Maharashtra. That approach was first implemented in Beed district, which is prone to crop-damaging droughts, and it is therefore commonly referred to as the “Beed model” of crop insurance.
Under the “cap” part of cup and cap, the state will pay claims in excess of a 110% loss ratio within a cluster—which is a group of districts within a state aggregated for PMFBY administrative purposes. Under the “cup” part, when a cluster loss ratio is below 80% the insurance company retains 20% of the premium, pays all the claims, and refunds the remainder to the state.
Cup and cap approaches are gaining more widespread interest. Madhya Pradesh, a key crop-growing state, implemented a similar scheme for the 2020-2021 cropping season and other states are exploring similar options. Our analysis indicates that implementation of a cup and cap approach—relative to the current PMFBY approach—could reduce private insurance company profits in good years by tens of percent and could increase net state-government contributions to premium subsidies plus their claims payments by tens of percent in poor years.
PMFBY vs. Cup and Cap Model: a Comparative Analysis
In the cup and cap model, states reduce their net subsidy paid on crop insurance premiums during seasons with lower claims by receiving what is essentially a refund on premium subsidies paid at the start of the season. Conversely, in years with large crop insurance losses, states would supplement their crop insurance premium subsidies with additional payments to cover losses above the cap level.
To illustrate some potential outcomes—to both insurance companies and states—of a move toward a cup and cap approach, we analyzed five scenarios of potential crop yields and associated insurance claims outcomes. In the scenarios, we used strings of three-year periods to simulate the current PMFBY structure of awarding insurance company approvals to offer insurance in a cluster of districts for three-year periods. While we would expect actual results to vary, in some cases considerably, across different states and years, our analysis provides an objective view of the sorts of effects that might be seen with a cup and cap approach.
Table 1 gives information on the example crop yield years considered in our analysis. The values are derived from AIR’s multiple-peril crop insurance (MPCI) model for India for a PMFBY cluster in Madhya Pradesh. In this case, the loss in the “moderate” yield year reflects the model’s average annual loss (AAL) for that cluster.
|Crop Yield Year||Exceedance Probability (Return Period)||Loss Ratio|
|Good||67% (1.5 years)||59%|
|Moderate||40% (2.5 years)||80%|
|Poor||14% (7 years)||117%|
|Extremely Poor||5% (20 years)||158%|
Different combinations of three crop yield years from Table 1 were used to define five scenarios as the basis for our analysis of potential outcomes under a cup and cap scheme with 80% and 110% loss ratio thresholds (Table 2).
|Year 1||Year 2||Year 3||Three-year Total|
|1||3 Good Years||59%||59%||59%||59%|
|2||2 Good & 1 poor Year||59%||59%||117%||78%|
|3||3 Moderate Years||80%||80%||80%||80%|
|4||2 Moderate & 1 poor year||80%||80%||117%||92%|
|5||1 Moderate, 1 poor & 1 Extremely poor Year||80%||117%||158%||118%|
Scenario Analysis—Government Perspective
The gross premium for the example cluster for a year is USD 65.35 million as per 2020-2021 crop insurance premium rates. The government subsidy is USD 64.17 million; the remainder is borne by farmers. The total government premium expenditure if the PMFBY model is followed in all three years for the cluster is USD 192.5 million, assuming constant sum insured and premium rates in this scenario analysis (Table 3).
|Scenario||Modeled loss (USD millions)||Premium subsidy by government (A)||Premium refund (B)||Claims paid by govt. over 110% LR (C)||Net Expenditure by government in cup and cap (D = A-B+C)||Difference of expenditure in cup and cap model- PMFBY (D-A)||% change in government expenditure with cup and cap|
For this cluster, the government expenditure fell by 21% in the best-case scenario (Scenario 1) with three back to back good years. And in Scenario 2 net government expenditure fell 12% because the “refunded” premium amount in years 1 and 2 outweighed the extra costs to the government caused by the 117% loss ratio in Year 3. Conversely, state expenditure increased 18.7% in Scenario 5 with one moderate, one poor, and one extremely poor crop yield year during the three-year analysis period.
In Scenario 3, when all three years experienced moderate crop yield losses, the burden to the government is unchanged. Similarly, Scenario 4 saw only a 2.3% increase in government expenditure under cup and cap with the overall loss ratio for the three-year period at 92%. The small increase resulted from modest state expenditures to cover losses above the 110% loss ratio threshold in the third year.
Scenario Analysis—Insurance Company Perspective
For the five scenarios analyzed, insurance claims paid and net premium for the cup and cap approach vs. PMFBY are provided in Table 4.
|Scenario||Modeled loss (USD millions)||Total Premium (A)||Claims Paid (B)||Net Earnings by Insurer under PMFBY (C)= A-B||Net Premium collected in cup and cap Model (D)||Claims Paid by insurer in cup and cap Model (E)||Net Earnings by Insurer with cup and cap Model (F) = D-E||Difference in earnings with cup and cap (F-C)||% change in insurers' earning with cup and cap|
In scenarios 1 and 2, the percentage change in earnings for the insurance company is reduced in the cup and cap model by 20.8% and 11.5%, respectively (Table 4) due to refunding of premiums as the loss ratio in a good year was 59%. Under scenarios 4 and 5, having poor and extremely poor crop yield years, the insurance company benefits from cup and cap because the government pays the claims exceeding the loss capping at 110%, with percentage increases in earning by 2.3% and 18.3%, respectively.
Assessing the Risk for PMFBY and Cup and Cap
From the insurer and reinsurer points of view, loss correlation within a portfolio of clusters needs to be considered in assessments of net effects of a cup and cap approach. These spatial and temporal correlations between clusters within a portfolio are critical from a risk management perspective because they are the basis of risk protection available from a well-diversified crop insurance portfolio. It is also critical to understand potential tail risk as it is important to loss ratio above the “cap” threshold. States should assess which circumstances would increase their costs owing to high crop insurance loss ratios, and the probability of those circumstances for their insured crops.
Both states and (re)insurers need to examine probable losses and expected net premiums under all likely scenarios to assess which insurance program (PMFBY or cup and cap) will be beneficial—or detrimental—in the long run.