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A farmer's tomato crop is wilting, and he must decide whether to water it. If he waters the tomatoes, or if it rains, the crop will yield \(\$ 1,000\) in profits; but if the tomatoes get no water, they will yield only \(\$ 500 .\) Operation of the farmer's irrigation system costs \(\$ 100 .\) The farmer seeks to maximize expected profits from tomato sales. a. If the farmer believes there is a 50 percent chance of rain, should he water? b. What is the maximum amount the farmer would pay to get information from an itiner ant weather forecaster who can predict rain with 100 percent accuracy? c. How would your answer to part (b) change if the forecaster were only 75 percent accurate?

Short Answer

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Answer: The farmer should water his tomato crop with a 50% chance of rain, as the expected profit from watering ($900) is higher than the expected profit without watering ($750). The maximum amount the farmer should pay for perfectly accurate weather information is $50, while he should pay up to $37.50 for 75% accurate information.

Step by step solution

01

Calculate expected profits with and without watering

To decide whether the farmer should water his crop or not, we need to compare the expected profits in each case. 1. Calculate the expected profit with watering: - Irrigation operating cost: $100 - Profit if it rains, or irrigation is used: $1,000 - Expected profit from watering: \(1,000 - \)100 = $900 2. Calculate the expected profits without watering: - Probability of rain: 50% or 0.5 - Profit if it rains: $1,000 - Profit if there's no rain: $500 - Expected profit without watering: (0.5 * \(1,000) + (0.5 * \)500) = $750
02

Compare expected profits to make a decision

Now, we'll compare the expected profits in both scenarios: - Expected profit with watering: $900 - Expected profit without watering: $750 Since the expected profit with watering is higher, the farmer should water his crop when there's a 50% chance of rain. b. Calculate the maximum amount the farmer would pay for accurate weather forecasting
03

Determine the value of perfect information

If the farmer can obtain perfectly accurate weather forecasting information, he can make the best decision every time, either irrigating when rain won't come or not irrigating when it will. With a 50% chance of rain, the optimal decision would yield an expected profit of (0.5 * \(1,000) + (0.5 * \)900) = $950 The value of perfect information is the difference between the expected profit with perfect information and the expected profit with current information: Value of perfect information = \(950 - \)900 = $50 The farmer should be willing to pay up to $50 for perfectly accurate information from the weather forecaster. c. Determine the maximum amount the farmer would pay for 75% accurate weather forecasting
04

Calculate expected profits with and without a 75% accurate forecast

With a 75% accurate weather forecaster, the farmer can choose the optimal action in 75% of the cases. This means he will make the correct decision 75% of the time. 1. Probability of correct decision: 75% or 0.75 2. Probability of incorrect decision: 25% or 0.25 Expected profit with a 75% accurate forecast: - (0.75 * \(950) + (0.25 * \)900) = $937.50 The value of the 75% accurate information is the difference between the expected profit with the 75% accurate forecast and the expected profit with current information: Value of 75% accurate information = \(937.50 - \)900 = $37.50 The farmer should be willing to pay up to $37.50 for 75% accurate information from the weather forecaster.

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Key Concepts

These are the key concepts you need to understand to accurately answer the question.

Probability in Decision Making
When making decisions, especially under uncertain conditions, probability can be extremely helpful. Let's look at the case of the farmer's watering decision. The probability of rain is a key factor. In this scenario, a 50% chance of rain was given. Probability helps us determine how likely it is that a particular outcome will occur.
By understanding these chances, the farmer can better assess the potential profits or losses associated with each decision. Here, the probability helps the farmer weigh the profit from watering versus not watering. If the probability of rain were higher or lower, the decision might change.
Understanding probability allows individuals to make informed decisions by evaluating the risk and potential rewards. Hence, using probability let's the farmer improve his decision-making by considering all possible outcomes and their likelihood. Some essential elements to consider include:
  • Probability of a favorable outcome (rain leading to more profit)
  • Probability of unfavorable outcomes (no rain leading to lesser profit)
  • Using probability to determine expected value, which aids in decision making.
Cost-Benefit Analysis
Cost-Benefit Analysis (CBA) is a method used to weigh the benefits and costs of a particular decision. For the farmer, watering the crop versus not watering it requires a CBA. The benefits of watering are higher profits if conditions are right, while the cost is the operational expense of the irrigation system, which is $100.
In this situation, performing a cost-benefit analysis involves calculating the expected profits in dollars for each scenario. With watering, the potential for earning $1,000 minus the watering cost results in an expected profit of $900. Without watering, the expected profit, considering probability, is $750.
This comparison allows the farmer to see that watering provides a larger net benefit (or profit) of $150 more than not watering. CBA is a valuable tool for decision-making as it quantifies the potential benefits and costs, assisting in making choices that maximize profit or value.
The core steps of a Cost-Benefit Analysis are:
  • Identify all potential costs and benefits.
  • Quantify them in economic terms.
  • Compare the total benefits and costs to determine the most profitable option.
Value of Information
Knowing the "Value of Information" is crucial in making smart choices. But what does it mean? Information has value if it can change the decision you make to achieve better outcomes. For the farmer, knowing the weather forecast with certainty has value. This value is the improvement in expected profits by using the additional information.
For perfect information about rain, the farmer finds out that the maximum value he can get is $950. This means if he had perfect weather prediction, he could potentially increase his profit by $50 compared to no extra information ($900). Thus, he should be willing to pay up to $50 for exact forecasts.
With a 75% accurate forecast, the expected additional profit is $937.50, which equates to a $37.50 increase. This tells the farmer the maximum amount he should be willing to pay for the forecasts considering the information's accuracy.
The calculation for the information value involves:
  • Assess the benefits of having the information.
  • Evaluate decisions that will change due to new information.
  • Compute the difference in outcomes with and without information.
  • Keep in mind that more accurate information often holds more value because it reduces uncertainty.

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Most popular questions from this chapter

A farmer believes there is a \(50-50\) chance that the next growing season will be abnormally rainy. His expected utility function has the form \\[ \begin{array}{c} \mathbf{1} \\ \text { expected utility }=-\boldsymbol{I} \boldsymbol{n} \boldsymbol{Y}_{N R}+-\boldsymbol{I} \boldsymbol{n} \boldsymbol{Y}_{R} \end{array} \\] where \(Y_{N R}\) and \(Y_{R}\) represent the farmer's income in the states of "normal rain" and "rainy," respectively. a. Suppose the farmer must choose between two crops that promise the following income prospects: $$\begin{array}{lcr} \text { Crop } & Y_{H} & Y_{R} \\ \hline \text { Wheat } & \$ 28,000 & \$ 10,000 \\ \text { Corn } & 19,000 & 15,000 \end{array}$$ Which of the crops will he plant? b. Suppose the farmer can plant half his field with each crop. Would he choose to do so? Explain your result. c. What mix of wheat and corn would provide maximum expected utility to this farmer? d. Would wheat crop insurance, available to farmers who grow only wheat, which costs \(\$ 4000\) and pays off \(\$ 8000\) in the event of a rainy growing season, cause this farmer to change what he plants?

Show that if an individual's utility-of-wealth function is convex (rather than concave, as shown in Figure 8.1 ), he or she will prefer fair gambles to income certainty and may even be willing to accept somewhat unfair gambles. Do you believe this sort of risk-taking behavior is common? What factors might tend to limit its occurrence?

In some cases individuals may care about the date at which the uncertainty they face is resolved. Suppose, for example, that an individual knows that his or her consumption will be 10 units today \((Q)\) but that tomorrow's consumption \(\left(\mathrm{C}_{2}\right)\) will be either 10 or \(2.5,\) depending on whether a coin comes up heads or tails. Suppose also that the individual's utility function has the simple Cobb-Douglas form \\[U\left(Q, C_{2}\right)=V^{\wedge} Q.\\] a. If an individual cares only about the expected value of utility, will it matter whether the coin is flipped just before day 1 or just before day \(2 ?\) Explain. More generally, suppose that the individual's expected utility depends on the timing of the coin flip. Specifically, assume that \\[\text { expected utility }=\mathbf{f}^{\wedge}\left[\left(\mathrm{fi}\left\\{17\left(\mathrm{C}, \mathrm{C}_{2}\right)\right\\}\right) \text { ) } \text { ? } |\right.\\] where \(E_{x}\) represents expectations taken at the start of day \(1, E_{2}\) represents expectations at the start of day \(2,\) and \(a\) represents a parameter that indicates timing preferences. Show that if \(a=1,\) the individual is indifferent about when the coin is flipped. Show that if \(a=2,\) the individual will prefer early resolution of the uncertainty - that is, flipping the coin at the start of day 1 Show that if \(a=.5,\) the individual will prefer later resolution of the uncertainty (flipping at the start of day 2 ). Explain your results intuitively and indicate their relevance for information theory. (Note: This problem is an illustration of "resolution seeking" and "resolution-averse" behavior. See D. M. Kreps and E. L. Porteus, "Temporal Resolution of Uncertainty and Dynamic Choice Theory," Econometrica [January \(1978]: 185-200\).

Ms. Fogg is planning an around-the-world trip on which she plans to spend \(\$ 10,000\). The utility from the trip is a function of how much she actually spends on it \((Y),\) given by \\[ U(Y)=\ln Y \\] a. If there is a 25 percent probability that Ms. Fogg will lose \(\$ 1000\) of her cash on the trip, what is the trip's expected utility? b. Suppose that Ms. Fogg can buy insurance against losing the \(\$ 1000\) (say, by purchasing traveler's checks) at an "actuarially fair" premium of \(\$ 250 .\) Show that her expected utility is higher if she purchases this insurance than if she faces the chance of losing the \(\$ 1000\) without insurance. c. What is the maximum amount that Ms. Fogg would be willing to pay to insure her \(\$ 1000 ?\)

Suppose there is a \(50-50\) chance that a risk-averse individual with a current wealth of \(\$ 20,000\) will contact a debilitating disease and suffer a loss of \(\$ 10,000\) a. Calculate the cost of actuarially fair insurance in this situation and use a utility-of-wealth graph (such as shown in Figure 8.1 ) to show that the individual will prefer fair insurance against this loss to accepting the gamble uninsured. b. Suppose two types of insurance policies were available: (1) A fair policy covering the complete loss. (2) A fair policy covering only half of any loss incurred. Calculate the cost of the second type of policy and show that the individual will generally regard it as inferior to the first.

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