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Insurance and Inventory Management Lecture 23. Lecture 23 Inventory Management.xlsx Lecture 23 Insurance.xlsx. Principal of Insurance. 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.
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Insurance and Inventory Management Lecture 23 • Lecture 23 Inventory Management.xlsx • Lecture 23 Insurance.xlsx
Principal of Insurance • 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 yield or price • Health, auto, and home insurance most popular • Liability insurance • Insurance transfers a part of the risk to a third party for a fee
Terms for an Insurance Policy • States the 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
Insurance Premiums • Premiums are set to cover the expected loss plus a risk premium (RP) and a profit for the insurance company • Premium = Expected($Lose) + RP + Profit • Calculate the Expected($Lose) w/ simulation • Simulate the type of losses and use the losses in the formula for calculating the premium • Calculate the average loss over a given time period, usually a year for the “group” • Profit is a set fraction (e.g., 20%) • RP covers risk not fully captured in PDF for risk
Brief History of Federal Crop Insurance • 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; no premium was charged • Replaced with FCIC insurance in 1983 • In ‘83 FCIC yield insurance expanded to all crops in all counties • Congress eliminated the Low Yield Disaster Prog.
Insurance for Agriculture • Crop Yield multi-peril insurance • Low yields insured against hail, fire, insects, drought, flood • Revenue insurance • Protects crop farmers from low revenues relative to their historical average revenue • The federal government through the USDA FCIC (federal crop insurance corporation -- Risk Management Agency) provides crop and revenue coverage policies for most crops and pasture
Agriculture Insurance Presents Unique Problems • Agricultural risks widespread due to weather affecting large regions when drought occurs • If a private insurance company 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) writes insurance policies and sets premiums and terms • Private companies sell these policies • Re-sellmost of the policies to RMA • Keeps the lower risk policies as an investment
Agriculture Insurance Industry • Very large (international) reinsurance companies, such as: • Zurich Insurance Group AG • Bermuda based Aspen Insurance Holdings Ltd. • Next layer of insurance companies actually have a sales force that sells insurance policies • Farmers Mutual Hail Insurance Co., Rain and Hail, AgriLogic, ARMtech Insurance • Cargill, John Deere, Wells Fargo recently exited the business • Local insurance agents who meet with farmers • All companies belong to NCIS
Agriculture Insurance Industry • USDA-Risk Management Agency (RMA) is the “reinsurance agent” • Insurance companies sell the policies that RMA develops as well as their own • RMA will buy back the policies that it develops so the insurance companies do not have to cover all of the losses • Insurance companies face a portfolio problem: • Policies sold to RMA only earn a % of the premium • Policies they retain earn 100% of the premium if there is no indemnity, there in lies the risk of which policies to sell to RMA
Compare Conditions for Two years September 13, 2011 February 3, 2015 … but parts of Texas are still in an exceptional, multi-year drought …
FCIC Yield Insurance (YP) • Production guarantee = APH * coverage level percentage elected • APH = 10 year yield history on the farm unit • Based on actual yields for the farm unit • Farm unit can be a field or all fields (enterprise option) • Premium set by RMA based on announced price guarantee, APH, county, and coverage level percentage • Indemnity = Max[0, (Production Guarantee - Actual Yield)] * (AnnouncedPrice * Acreage Covered)
FCIC Yield Insurance • 50 acres of corn, RMA projected/announced price of $3.50/bu, APH yield 145 bu/acre, 85% coverage level • Production guarantee = 0.85 * 145 = 123.3 • If actual yield is stochastic = 115 so lost yield =123.3-115 • Indemnity = (123.3-115) * 3.50* 50
Revenue Insurance • Crop Revenue Coverage (CRC) • Producers buy a fraction of historical revenue • Insured Revenue = APH * Announced Price * Fraction • Revenue fractions are: 50% to 85% in 5% deltas • Insure with a projected price or the harvest price based on the futures contract • 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 is stochastic= 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 because the harvest price is generally lower
Analyzing & Picking Best Insurance Option • This is a simple simulation problem • Simulate yield and price based on history • Compare yield or revenue to alternative (insured) coverage levels, calculate indemnities and premiums • Pay premiums every year • Collect indemnities only when there is a loss • Pick insurance policy which is best at reducing risk and increasing net income, NPV, or cash flows
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 • 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
Insurance and Farm Policy • 2014 Farm Bill is relying more on insurance and less on direct or indirect subsidies • Supplemental Crop Option (SCO) • STAX insurance for cotton lint • The 2018 farm bill could change the insurance options and premium subsidies • So far the announcements are no change in insurance from the House – The Senate is yet to speak up
Insurance Job Opportunities • Sales representative for the large companies • Insurance actuary and analysts • Insurance 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
Simulating a Learning Curve to Represent the Demand Cycle • 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 production 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
Life Cycle Costing • A new concept in project feasibility analysis • Explicitly consider externalities • Such as cleanup costs at the end of the 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 RisksJohn Wiley & Sons Inc. 2003
Life Cycle Analysis • 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 Analyzed the carbon footprint for crop and dairy farms in principal production regions in the US • GREET Model developed by Dept. of Energy engineers at Argonne National Labs • Download it and use it for free • Contains NO risk variables
Inventory Management • Inventory management is about • When to re-order • How much to order • Factors to consider • Cost of storage • Cost of placing an order • Cost of lost sales due to shortage • Stochastic demand • Delivery time from time order is placed • Can you backlog demand
Inventory Management • Simulate the inventory management problem as a stochastic problem • Simulate N periods to test impacts of alternative inventory management schemes • Period -- length of time for the problem – week, month • Based on the time period for the demand data • Also based on order/delivery time
Inventory Management • Example of a weekly Inv. Management Problem • Cost to place an order $200 • Cost of a unit purchased $4 • Cost of storage for 1 week $3 • Cost of each lost sale $10 • Price of product sold $25 • Weekly demand PDF ~ N(40,6) • 2 week delivery time; could be stochastic • Beginning inventory 100 • Inventory management rule to test: • Place order if inventory on hand <= 50 units • Amount to order = 150 minus the inventory on hand • KOV = average weekly profit, cost, inventory, revenue
Rules for Simulating Inventory • Demandt is stochastic • Beginning inventoryt= ending inventoryt-1 • Supplyt = beginning inventoryt + quantity receivedt • Salest = Minimum (demandt or supplyt) • Ending Inventoryt= supplyt – salest • Quantity receivedt = quantity orderedt-n • if it takes “n” periods for the delivery • Could have a stochastic under shipment factor Lost salest= 0.0 If(supplyt> demandt) else Lost salest = demandt– supplyt
Calculating Inventory Costs • Purchase costst = cost per unit paid for product • Order costst = fixed cost to place an order (shipping costs, office expense, delivery processing costs, Fed Ex rush delivery fee, etc.) • Storage costst = cost per unit * beginning inventoryt • Penalty costst = cost to the business for lost sales or lost salest * cost for perceived lost goodwill
Inventory Management Model • The model should have 40 to 50 weeks so the startup conditions do not dictate the results for the inventory management rule being analyzed
Inventory Management Scenarios • Test alternative reorder points • Should firm reorder when inventory < 50? • Scenarios: 40, 50, 60, 70, 80, 90 for the reorder point • Order up to some amount • Should firm reorder a larger amount • Scenarios: 140, 150, 160, 170, 190, or more • Would it be more profitable to pay more (or less) to get the order delivered faster (slower)? • Pay $300/order to get delivery in 1 week • Pay $100/order to get delivery in 3 weeks • The profit PDF changes for each question; use simulation to estimate the profit PDF for each scenario
Inventory Management.XLS • Scenario reorder points of: 50, 60, 70, 80, 90