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Class 1: Intro and Demand Class 2: Costs Class 3: Competition Class 4: Market Failure Class 5: Information and Decisions Class 6: Capstone Class Class 7: Presentations

Outline

1 Class 1: Intro and Demand

2 Class 2: Costs

3 Class 3: Competition

4 Class 4: Market Failure

5 Class 5: Information and Decisions Definitions Decisions on Expected Value Features of Decision-making: Risk Preferences Recap

6 Class 6: Capstone Class

7 Class 7: Presentations

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Class 1: Intro and Demand Class 2: Costs Class 3: Competition Class 4: Market Failure Class 5: Information and Decisions Class 6: Capstone Class Class 7: Presentations

Quiz 3

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Class 1: Intro and Demand Class 2: Costs Class 3: Competition Class 4: Market Failure Class 5: Information and Decisions Class 6: Capstone Class Class 7: Presentations

Why are we in class today?

You don’t know?... How do you know that I know?

Most times, firms have far too little info

So, firms must understand how to take decisions with probabilities - not full information

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Class 1: Intro and Demand Class 2: Costs Class 3: Competition Class 4: Market Failure Class 5: Information and Decisions Class 6: Capstone Class Class 7: Presentations

Key Learning Objectives

Expected value - what it means

Risk Aversion - what it means and how it relates to expected value

Expected Utility - how it could be used to describe rational decisions

Decision Trees - how to construct and use one

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Class 1: Intro and Demand Class 2: Costs Class 3: Competition Class 4: Market Failure Class 5: Information and Decisions Class 6: Capstone Class Class 7: Presentations

Definitions

Uncertainty

Uncertainty is not Risk:

Risk is usually quantifiable By definition, uncertainty is not

Uncertainty represents the absence of information

"The essential fact is that ’risk’ means in some cases a quantity susceptible of measurement.... It will appear that a measurable uncertainty, or ’risk’ proper, as we shall use the term, is so far different from an unmeasurable one that it is not in effect an uncertainty at all." – Frank Knight (1885-1972), Risk, Uncertainty, and Profit

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Class 1: Intro and Demand Class 2: Costs Class 3: Competition Class 4: Market Failure Class 5: Information and Decisions Class 6: Capstone Class Class 7: Presentations

Definitions

Risk

Known Unknowns of Iraq War

Pure risk examples: the lottery, rolling dice

Other examples: commodity prices, interest rates

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Class 1: Intro and Demand Class 2: Costs Class 3: Competition Class 4: Market Failure Class 5: Information and Decisions Class 6: Capstone Class Class 7: Presentations

Decisions on Expected Value

Discussion: Is it Rational to Play Powerball?

Derive the expected value of a:

coin toss bet

Roll of the die

Expected value of playing the lottery

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Class 1: Intro and Demand Class 2: Costs Class 3: Competition Class 4: Market Failure Class 5: Information and Decisions Class 6: Capstone Class Class 7: Presentations

Decisions on Expected Value

Expected Value

E(v) = p1v1 + p2v2 + .... + pnvn (1)

= i=n∑ i=1

pivi (2)

=

∫ v ∗ p(v)dvfor continuous probability distribution (3)

Decisions based expected value are rational

They do not consider ’risk preferences’, (economic agents’ risk aversion)

How people gamble Class exercises

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Class 1: Intro and Demand Class 2: Costs Class 3: Competition Class 4: Market Failure Class 5: Information and Decisions Class 6: Capstone Class Class 7: Presentations

Decisions on Expected Value

Decisions and Outcomes

Can a ’good’ rational decision lead to a bad outcome?

Can a ’bad’ rational choice lead to a good outcome?

What then makes for a good decision? Or choosing to do nothing?

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Class 1: Intro and Demand Class 2: Costs Class 3: Competition Class 4: Market Failure Class 5: Information and Decisions Class 6: Capstone Class Class 7: Presentations

Decisions on Expected Value

Decision Trees

A decision tree is a good way to represent the interaction of: decisions states of the world (SOWs) OR chance events

Useful for visualizing how we derive expected value

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Class 1: Intro and Demand Class 2: Costs Class 3: Competition Class 4: Market Failure Class 5: Information and Decisions Class 6: Capstone Class Class 7: Presentations

Decisions on Expected Value

Class Exercise

Faced with two opportunities to take a risk: 1% chance of winning $10,000 and 99% chance of winning $0

1% chance of winning $1 million, 1% chance of losing $990,000 and 98% chance of winning $0

What is the expected value of these games?

Would you pay $100 to play game 1? game 2?

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Class 1: Intro and Demand Class 2: Costs Class 3: Competition Class 4: Market Failure Class 5: Information and Decisions Class 6: Capstone Class Class 7: Presentations

Decisions on Expected Value

Expected Values in Sequence

Refer to the R&D question of page 511 of text

Some choices only happen at a later stage

There may be ’wait-and-see’ decisions

First, draw the decision tree

then estimate conditional expected values Estimate expected values in sequence in reverse (backwards from the last to the first decision or SOW)

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Class 1: Intro and Demand Class 2: Costs Class 3: Competition Class 4: Market Failure Class 5: Information and Decisions Class 6: Capstone Class Class 7: Presentations

Decisions on Expected Value

Class Exercises

Sequential decision problem: page 516 (Check Station 3)

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Class 1: Intro and Demand Class 2: Costs Class 3: Competition Class 4: Market Failure Class 5: Information and Decisions Class 6: Capstone Class Class 7: Presentations

Decisions on Expected Value

Class Discussion and Group Work

Take 10 mins- working in assigned groups, draft notes on risk issues for your class project Discuss how the risk factors affect your business prospects

Business or Income Cycles Natural Gas and Coal Prices Electric Utility Rates Solar Panel Prices Lithium Prices

Focus on numbers - (outcomes) What is possible? (probability) How likely is it to happen?

From the Solar Energy Industry Association: Outlook

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Class 1: Intro and Demand Class 2: Costs Class 3: Competition Class 4: Market Failure Class 5: Information and Decisions Class 6: Capstone Class Class 7: Presentations

Features of Decision-making: Risk Preferences

Risk Aversion

Risk neutral person is indifferent between a sure income and an uncertain income with the same expected value

Risk averse person prefers a sure income (the certainty equivalent), over an uncertain income with the same expected value

To avoid risk, a risk averse person will be willing to pay extra (i.e. a risk premium) Alternatively, such a person will require extra compensation if (s)he is made to bear risk

Risk loving person prefers an uncertain income over a sure income with the same expected value

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Class 1: Intro and Demand Class 2: Costs Class 3: Competition Class 4: Market Failure Class 5: Information and Decisions Class 6: Capstone Class Class 7: Presentations

Features of Decision-making: Risk Preferences

Ways to Deal with Risk

Risk financing (e.g. insurance) With insurance, transfer risk to another entity, usually for a fee Costly, so it is meant for non-diversifiable risk Who, among the risk neutral, risk loving, and risk averse, will always buy actuarially fair insurance?

Risk mitigation (e.g. diversification, divestment) The "Don’t put all your eggs in the same basket" strategy With two investments that are not perfectly positively correlated, the variance of a combination will be lower than variance of either investment (for the same total investment) Generally, lower risk for same return...but beware transaction costs

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Class 1: Intro and Demand Class 2: Costs Class 3: Competition Class 4: Market Failure Class 5: Information and Decisions Class 6: Capstone Class Class 7: Presentations

Recap

Decision-making Pitfalls: Excluding relevant alternatives

Choices Remember the die toss exercise!

More Choices

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Class 1: Intro and Demand Class 2: Costs Class 3: Competition Class 4: Market Failure Class 5: Information and Decisions Class 6: Capstone Class Class 7: Presentations

Recap

Decision-making Pitfalls: Vague Probability Specifications

There is a good chance it is sunny tomorrow

Is that a 50% or a 90% probability?

There is a fair chance of winning the lottery

Is that a 50% or a 0.00000000342 probability?

When it comes to money, which is always measured in numbers, every number is your friend!

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Class 1: Intro and Demand Class 2: Costs Class 3: Competition Class 4: Market Failure Class 5: Information and Decisions Class 6: Capstone Class Class 7: Presentations

Recap

Decision-making Pitfalls: Overoptimism and Overconfidence

The odds must be in my favor

The tendency to skew outcome probabilities

Exercise: Repeat coin toss exercise, but with subjective probabilities on outcomes

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Class 1: Intro and Demand Class 2: Costs Class 3: Competition Class 4: Market Failure Class 5: Information and Decisions Class 6: Capstone Class Class 7: Presentations

Recap

Failing to gather data

PwC: Big Decisions

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Class 1: Intro and Demand Class 2: Costs Class 3: Competition Class 4: Market Failure Class 5: Information and Decisions Class 6: Capstone Class Class 7: Presentations

Recap

Recap

Risk is not uncertainty (the absence of information) Decisions are often not rational because they require information:

Obtaining information is costly

Processing information is costly

Separating biases and preferences from information is not easy

Nevertheless, good rational decision-makers should consider all possible outcomes (use decision trees) identify (or guess) probabilities for each outcome determine the expected value of each choice

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Class 1: Intro and Demand Class 2: Costs Class 3: Competition Class 4: Market Failure Class 5: Information and Decisions Class 6: Capstone Class Class 7: Presentations

Recap

What Comes Next?

Submit projects before deadline

Put all our class concepts to work in simulation

Laptops are required

Come with all class notes, those notes will be needed to create winning strategy

Read simulation case carefully, simulation could be a pop quiz Register at MIT website

Register as part of class (class code - 592S16; pwd - 592S16 )

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