AGEC 407 Risk Goals: 1.Convey an understanding of what is meant by risk 2.Describe the different types and sources of risk in agricultural production 3.Demonstrate why it is important to consider risk when making management decisions

AGEC 407 Risk Modeling Reality –Using math to describe a situation Deterministic Models –Outcome is known with certainty –No variation Stochastic Models –From Greek word “stochos” meaning guess –Precise outcome is uncertain –Contains a random element –Characterized by a probability distribution

AGEC 407 Pennsylvania All Milk Price

AGEC 407 SE Pennsylvania Corn Price

AGEC 407 Probability Distributions Usually described by “mean” and “variance” Mean –Arithmatic average Variance –Measures the spread of observations around the mean

AGEC 407 Risk vs. Reward Risk and reward are directly correlated The safest investment will generally provide the lowest expected return Two alternative investments (A and B) with the same price: –If A is a safer investment (smaller variance) and has a higher expected payoff (higher mean) than B, everyone would want A and its price would go up relative to B

AGEC 407 Risk Averse, Risk Neutral or Risk Loving? Ability to take risks –Equity to cover losses –Cash flow commitments Willingness to take risks –Are you willing to gamble to get ahead?

AGEC 407 Types of Agricultural Risk Production or Yield Risk –Weather, new technologies, old technologies Price or Market Risk –Farmers are generally price takers –Prices are stochastic Financial Risk –Interest rates –Debt structure and cash flow

AGEC 407 Types of Agricultural Risk Institutional or Legal Risk –Changes in policies and regulations –Trade embargoes, production limits, environmental regulations Human, Personal or Asset Risk –Injury, illness, death, divorce –Fire, theft, loss or damage to assets –Adequate labor force?

AGEC 407 Why Consider Risk in Decision-making? In reality, outcomes are rarely certain With more information (probability distribution), more accurate decisions can be made Can minimize the probability of incurring unbearable losses

AGEC 407 Decision Making Under Risk 1.Identify sources of risk 2.Estimate the possible outcomes and associated probabilities 3.Identify alternative strategies 4.Measure the results of each outcome for each strategy 5.Evaluate risks and expected returns

AGEC 407 Different Decision Rules 1.Most Likely Outcome 2.Maximum Expected Value 3.Risk vs. Expected Returns 4.Maxi-min 5.Breakeven Probability

AGEC 407 Probabilities Historical probabilities –based on actual data Subjective probabilities –the degree of belief that an individual has about the occurrence of an outcome Rules of probability

AGEC 407 Cumulative Distribution Function (CDF) Shows the probability that an outcome will be equal to or less than a specified value Makes discrete probabilities continuous

AGEC 407 Constructing a CDF List a set of outcomes for an event or strategy List outcomes from smallest to largest Outcomes are midpoints of each range Assign cumulative probability to first range equal to one-half of that range Assign cumulative probabilities to subsequent ranges by adding their probability previous ranges Graph cumulative probs over outcomes

AGEC 407 More Decision Rules Principle of Insufficient Reason Maxi-max Safety first Mean-Variance (EV)

AGEC 407 Principle of Insufficient Reason You don’t have information on the probabilities Treat all outcomes as equally likely Use simple average of outcomes Choose strategy with the most desirable average outcome

AGEC 407 Safety-First Best strategy that meets a minimum net income level with a specified probability Specify the minimum net income level needed Specify the probability by which the minimum net income level must be met or exceeded

AGEC 407 Safety-First Disregard actions that do not provide the minimum net income with the specified probability Select the action with the highest expected return of those that meet the safety-first criteria

AGEC 407 Stochastic Dominance Higher outcomes with less risk is preferable to all decision makers Comparing the CDFs associated with alternative actions Two types of Stochastic Dominance –First Degree –Second Degree

AGEC 407 First Degree Stochastic Dominance Action A dominates Action B if: –For all outcomes, the cumulative probability of A is less than that of B –CDF for A is completely to the Right of CDF for B CDFs do not cross Action A is prefered by all decision makers

AGEC 407 Second Degree Stochastic Dominance Assumes decision maker is risk averse Is an application of Mean-Variance (E-V) decision rule Action A is preferred to Action B if: –Area under CDF for A is less than area under CDF First degree S.D. implies Second degree S.D. (but not visa-versa)