• Lecture 24 Insurance.xlsx

Insurance Lecture 24

• Insurance is a risk management tool• Buy insurance to cover a specific risk of

a loss to the business– Low yield due to fire, hail, drought, flood,

etc.– Low prices– Low revenue due to low production of price– Health, auto, and home insurance most

popular– Liability insurance

• Insurance transfers a part of the risk to a third party

Principal of Insurance

• States risk to protect against– Conditions for a loss– Amount of loss that must occur for a

payment• States the premium to be paid • States indemnity payment conditions

– Amount of the deductible (losses not paid)– Formula for calculating a payment

Terms for an Insurance Policy

• Premiums are set to cover the expected loss plus a risk premium and a profit for the insurance company

• Premium = E(losses) + RP + Profit• Calculate the E(Losses) with simulation

– Simulate the type of loss and use the losses in the formula for calculating the premium

– Calculate the average loss over a given time period, usually a year

– Profit is a set fraction by the company– RP covers risk not fully captured in PDF for

risk

Insurance Premiums

• Crop Yield insurance– Low yields insured against hail, fire, insects,

drought, flood• Revenue insurance

– Protects crop farmers from low revenues relative to historical averages

Insurance for Agriculture

• Agricultural risks widespread due to weather affecting large regions when drought of occur

• If an insurance co. covered all the risk they would be wiped out

• Solution was for the federal government to back up these companies– USDA-Risk Management Agency (RMA)

write insurance policies and set premiums and terms

– Private cos. sell these policies• Sell most policies to RMA, keep the lower risk

policies as an investment

Agriculture Insurance Presents Unique Problems

US Drought: Current Conditions

Texas is actually looking pretty goodrelative to 2011 …

… but parts of Texas are still in an exceptional,

multi-year drought …

September 13, 2011 February 3, 2015

• 1930’s USDA offered yield insurance in the Great Plains for wheat– Experimental project

• Expanded to other crops gradually• 1971 Farm program offered Disaster

Program– Paid farmers for low yield and prevented

plantings– Replaced with FCIC insurance in 1983

• In ‘83 FCIC yield insurance expanded to all crops in all counties

Brief History of Federal Crop Insurance

• Production guarantee = APH * coverage level percentage elected– APH = 10 year yield history on the farm unit– Premium set by RMA based on announced

price guarantee and coverage level percentage

• Indemnity = Max[0, (Actual Yield – Production Guarantee) * Projected Price * Acreage Covered]

FCIC Yield Insurance

• 50 acres of corn, RMA projected price of $3.50/bu, APH yield 145 bu/acre, 85% coverage level

• Production guarantee = 0.85 * 145 = 123.3

• If actual yield = 115 so lost yield is 123.3-115

• Indemnity = (123.3-115) * 2.25 * 50

FCIC Yield Insurance

• Crop Revenue Coverage (CRC) – Producers buy a fraction of the historical

revenue – 65% to 85% in 5% fractions– Insure with a projected price or the harvest

price• Indemnity = Max[0, (Guaranteed

Revenue – Actual Revenue) * Acres ]– Actual Revenue = actual yield * (RMA

projected price OR harvest time price)

Revenue Insurance

• 50 acres of corn, RMA projected price of $3.50/bu, APH yield 145 bu/acre, 85% coverage level

• Revenue guarantee = 50 * 145 * 0.85 * 3.50

• Actual yield = 100• Indemnity = Max[0, (revenue guarantee

– 50 * 100 * 3.50 or actual harvest time price)]

• Electing the RMA projected price is referred to “Harvest Price Exclusion” and is cheaper

Revenue Insurance

• Simple simulation problem• Simulate yield and price• Compare yield or revenue to alternative

coverage levels, calculate indemnities and premiums

• Pick insurance policy which is best at reducing risk and increasing net income, NPV, or cash flows

Analyzing Insurance Options

• General Policies and Provisions

• Actual Revenue History (ARH) Pilot Endorsement (14-arh).• Area Risk Protection Insurance (14-ARPI)• Commodity Exchange Price Provisions (CEPP)• Catastrophic Risk Protection Footnote 5.• Ineligibility Amendment (15-Ineligibility) Footnote 1.• Farm Bill Amendment (15-ARPI-Farm-Bill) Footnote 6.• Catastrophic Risk Protection Endorsement (15-cat).

Footnote 3.• Common Crop Insurance Policy, Basic Provisions (11-br)• Commodity Exchange Price Provisions (CEPP)• Contract Price Addendum (CPA)• Ineligibility Amendment (15-Ineligibility) Footnote 1.• Farm Bill Amendment (15-CCIP-Farm-Bill) Footnote 2.• Other Information• Supplemental Coverage Option (SCO-15)• High-Risk Alternate Coverage Endorsement (HR-ACE)(13-

HR-ACE)• High-Risk Alternate Coverage Endorsement Standards

Handbook• High-Risk Alternate Coverage Endorsement Frequently

Asked Questions• Livestock• Quarantine Endorsement Pilot (11-qe).• Rainfall and Vegetation Indices Pilot• Whole-Farm Revenue Protection (WFRP) Pilot Policy

RMA Insurance Policies

Insurance policies must be purchased prior to planting to reduce:• Moral hazard --

buying insurance when farmers know the crop will fail

• xxx

• 2014 Farm Bill is relying more on insurance and less on direct or indirect subsidies

• Agricultural Risk Coverage (ARC)• Supplemental Crop Optionm(SCO)

Insurance and Farm Policy

Agriculture Risk Coverage (ARC-CO)

• Payments when actual revenue for the covered commodity < ARC revenue guarantee, where:– Actual County Revenue = Actual county yield per planted

acre * Max of {National Marketing Year Price or Marketing Loan Rate}

– ARC Revenue Benchmark = (5 Year U.S. Olympic average marketing year price) * (5 Year Olympic average county)

• If any of the 5 years of prices are lower than Reference Price then replace with the Reference Price.

• If the actual county yield is < 70% of T-yield replace with the T-yield.

– ARC Revenue Guarantee = 0.86 * ARC Revenue Benchmark

• ARC Payment = Minimum of [(ARC Revenue Guarantee – Actual County Revenue) OR 10% of the ARC Revenue Benchmark] * Base Acres * 0.85

• No yield risk in year one’s calculation but that does not last– Olympic average starts with 2009-2013, but then moves to 2010-2014,

2011-2015, 2012-2016, 2013-2017 with more and more risky yields in the Olympic Average each year of the farm program

Market Receipts

MLG

Revenue per cwt or bu

LoanRate

Market Price

Revenue Benchmark

Crop insurance coverage

86%

76%

Illustration of Government Support for Grains Under ARC-County

[paid on base acres x .65 (individual) or .85 (county)]

86% of Revenue Guarantee

Supplemental Coverage Option (SCO)

• Gap insurance: payments for losses from 86% of APH or CRC coverage level down to the underlying insurance coverage level

Revenue per cwt

Illustration of Government Support for Rice Under SCO

Crop insurance coverage

Supplemental Coverage Option

86% of Revenue Guarantee

• Sales repre’s for the large companies• Insurance actuarialists • Adjusters

– Seasonal employment that pays well– Work during growing season only– Visit damaged fields and prepare estimates

of the damages– Experience with crop production and

economics– Insurance companies complain there never

enough adjusters

Insurance Job Opportunities

Insurance Use in Texas for Cotton

0.5 0.55 0.6 0.65 0.7 0.75 0.8 0.85410,813 138,146 2,384,361 2,035,135 4,472,480 9,831,329 508,302 15,533

240650

232494146

11314

465105

4170387

44

-

2,000,000

4,000,000

6,000,000

8,000,000

10,000,000

12,000,000

Acres of Cotton Participating in Crop Insurance in TX by Coverage Level

0.5 0.55 0.6 0.65 0.7 0.75 0.8 0.85

Insurance Use in Texas for Corn

0.5 0.55 0.6 0.65 0.7 0.75 0.8 0.85147,477 17,136 210,009 304,214 716,190 1,035,911 200,897 52,649

S UM -

200,000

400,000

600,000

800,000

1,000,000

1,200,000

Acres of Corn Participating in Crop Insurance in TX by Coverage Level

0.5 0.55 0.6 0.65 0.7 0.75 0.8 0.85

• A new business may need a few months or years to grow sales to their potential

• May take months or years to learn how to reach potential for a prod function

• In either case, assume a stochastic growth function and simulate it, if nothing else is available, use a Uniform distribution

• Example of a growth function for 8 years

Learning Curve or Demand Cycle

Fan Graph for Realized Sales over 10 Years

-

50,000

100,000

150,000

200,000

250,000

Sales1 Sales3 Sales5 Sales7 Sales9Average 5th Percentile 25th Percentile

75th Percentile 95th Percentile

Learning Curve or Demand Cycle

• A new concept in project feasibility analysis

• Explicitly consider externalities– Such as cleanup costs at end of

business• Strip mining reclamation• Removal of underground fuel tanks• Removal of above ground assets • Restoration of site

– Prevention of future environmental hazards• Removal of waste materials• 100 year liners for ponds

Life Cycle Costing

• Steps to Life Cycle Costing Analysis– Identify the potential externalities – Determine costs of these externalities– Assign probabilities to the chance of

experiencing each potential cost• Assume distributions with GRKS or

Bernoulli– Simulate costs given the probabilities– Incorporate costs of cleanup and

prevention into the project feasibility– These terminal costs may have big

Black Swans so prepare the investor

Life Cycle Costing

• Bottom line is that LCC will increase the costs of a project and reduce its feasibility

• Affects the downside risk on returns • Does nothing to increase the positive

returns• Need to consider the FULL costs of a

proposed project to make the correct decision

• J. Emblemsvag – Life Cycle-Costing: Using Activity-Based Costing and Monte Carlo Simulation to

manage Future Costs and Risks John Wiley & Sons Inc. 2003

Life Cycle Costing

• LCA is a tool for determining the impact of a new process or project on the environment and climate change

• LCAs are concerned with quantifying– Energy Use and CO2 Balance– Green House Gases (GHGs)– Water use and indirect Land use– Nutrient (N,P,K) use and other factors

• Thus far these are deterministic analyses – This will soon change

Life Cycle Analysis

• For those interested in a good example of LCA see

MS thesis in our Department by Chris Rutland

Life Cycle Analysis