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The Basics of Designing and Running an Economics Experiment







Economics 328

Spring 2005

The Purposes of Running an Experiment



 Test a Theory

 Gather Empirical Regularities to Inform a Theory

 Test Institutions

What Makes a Good Experiment?



 Should an experiment replicate reality?

 No! We have field studies for that.

 Should an experiment replicate a formal model?

 No! We have theory for that.

 A good experiment tries to capture the most relevant

features of reality in a simple, carefully controlled

environment. Good experiments are usually

designed to test specific hypotheses, sometimes

derived from the implications of some economic

theory and other times based on previous

observations in either experiments or field data.

What is a Controlled Experiment?



 As much as possible, the experiment controls all

elements of the environment in which the experiment

takes place.

 The experimenter determines the rules – what choices are

available to subjects, when decisions are made, and what

the consequences of these decisions will be.

 The experimenter controls subjects’ payoffs as a function of

the actions they take.

 The experimenter controls the information that is available

to subjects.

What is a Controlled Experiment?



 Between treatments, the experimenter only changes variables which

are directly relevant to the hypothesis being tested, otherwise holding

the environment fixed.

 Control vs. Treatment Sessions

 Avoid Confounds (e.g. Don’t change more than one thing at a time.)

 Variables that cannot be directly controlled are typically controlled via

randomization.



Example: Many experiments are designed to test subjects’ attitudes

towards fairness are affected by some treatment variable. To the extent

that subjects enter the lab with differing attitudes about fairness, a true

controlled experiment can’t be run. However, by randomly assigning

subjects to treatments, we can eliminate subjects differing attitudes as a

cause of differences between treatments. This relies on the law of large

numbers, implying that a large sample may be necessary.

Designing an Experiment

 Identify an interesting question or questions. These should be issues that are

better addressed through a controlled experiment than through gathering field

data.



 Determine hypotheses you would like to test.



Example: Increased payoffs lead to fewer mistakes in solving logic problems.



Example: Face-to-face interaction will lead to greater concern with fairness.



 Design a simple environment that allows you to test the hypotheses you are

interested in. Remember, the more complicated the environment is, the more

likely you are to lose control. An experiment is not meant to replicate reality.

The reason we use controlled experiments is because reality is too complicated.

Brandts and Cooper:

The Weak Link Game

 The employee payoff Worker i's Payoff Table, B = 6



function is given by the Minimum Effort by Other Workers

following equation: 0 10 20 30 40









  E 

0 200 200 200 200 200

Effort 10 150 210 210 210 210

π  200  5E i  B  min

i

e j

by 20 100 160 220 220 220

j1,2,3,4 Worker i 30 50 110 170 230 230

40 0 60 120 180 240

 Having all five players

choose the same effort level

is a Nash equilibrium.

 The critical variable here is Worker i's Payoff Table, B = 14



B, the bonus rate. Higher Minimum Effort by Other Workers

values of B give greater 0 10 20 30 40



benefits to successful Effort

0

10

200

150

200

290

200

290

200

290

200

290

coordination. by 20 100 240 380 380 380



Trying to move to a higher

Worker i 30 50 190 330 470 470

 40 0 140 280 420 560

effort level is a risky

strategy.

Brandts and Cooper:

Research Questions



 Can an increase in the bonus rate enable a firm to overcome

coordination failure?

 Does the magnitude of the bonus rate increase matter or is the

simple fact of an increase effective as such?

 If an increase in the bonus rate brings about improved coordination,

can the bonus rate increase be revoked without affecting the

improved outcome?

 Does the length of time a firm has been underperforming affect the

impact of the increase?

Designing an Experiment



 Test your hypotheses by varying a small number of variables

within the experiment. If at all possible, you should not vary

more than one variable at a time.

 Within vs. Between Subject Designs

 Some important factors to remember . . .

 Subjects get bored.

 Subjects get confused.

 Subjects learn as they gain experience within the experiment.

You should anticipate changes in their behavior (order effects).

Design for Brandts and Cooper



List of Treatments



Cell 1 Cell 2 Cell 3 Cell 4 Cell 5 Cell 6

Bonus Rate

6 6 6 6 6 6

Rounds 1 – 10

Bonus Rate

14 10 8 14 14 6

Rounds 11 – 20

Bonus Rate

14 10 8 10 6 14

Rounds 21-30

Results for Brandts and Cooper



Comparison of Treatments, Second Block





40









30

Average Minimum Effort









20









10









0

10 11 12 13 14 15 16 17 18 19 20

Period



Treatment 6/6/14 Treatment 6/8/8 Treatment 6/10/10 Treatment 6/14/X

Results of Classroom Experiment



Effect of Bonus Rate Increase





40









30

Average Minimum Effort









20









10









0

5 6 7 8 9 10

Round



B = 8 or B = 10 B = 14

Results of Classroom Experiment



Effect of Bonus Rate Increase





40









30

Average Effort









20









10









0

5 6 7 8 9 10

Round



B = 8 or B = 10 B = 14

Designing an Experiment



 Avoid the use of deceit. This is a very tempting trap, but one that is

highly frowned upon by the profession. In particular, what is going to

happen the next time you try to run an experiment?

 Anonymity: Most experiments guarantee subjects anonymity. In other

words, subjects are guaranteed that no other subjects (or indeed,

nobody other than the researchers) will be able to ever identify their

actions or payoffs. For some experiments, abandoning anonymity is an

important part of the design. If so, subjects should know what

information about them is be revealed publicly. Subjects should have

the option of withdrawing if they do not want information about them

revealed publicly.

Subjects

 What population should you use as subjects?

 Undergraduates are the easiest to get, but subjects with relevant experience are often

more interesting to study.

 How do you get subjects?

 Advertisements can be placed on posters, electronic bulletin boards, or in newspapers.

Spamming, while effective, is generally not a good way to make friends.

 What should be in the advertisement?

 It should include a very brief description, a summary of payoffs (average payoff is

sufficient), the time necessary to complete the experiment, and contact information.

(E-mail addresses work well. A website where people can sign up for the experiment

works even better.)

 The advertisement should stress the monetary payoffs. Remember, you want

controlled experiments. This means that you want subjects who care about the

monetary payoffs being offered.

Play Games!!!

Earn Cash!!!

Participate in an Experiment in

Economic Decision Making!!!

Average Earnings = $20 - 25!!!

Takes 1½ Hours or Less!!!



Wednesday, September 4th, 4:30

Thursday, September 5th, 4:30

Monday, September 9th, 4:30

Tuesday, September 10th, 9:30

More Times Available



Sign up at :

www.weatherhead.cwru.edu/exper





Play Games!!!

Earn $$$

Subjects

 Avoid unintentional selection of the subject population. For example, if you post

all of you ads in the weight room in Veale, your subject population will be

skewed towards men. You should also avoid unintentional clustering (e.g. don’t

sign up ten people from the same fraternity for a single session).

 Have times and locations for sessions selected before posting any ads. Be

certain to schedule potential subjects as soon as they respond to your ad. Be

certain to get contact information from your subjects. Confirm that all subjects

will attend the day before the session. Even with confirmation, you should

anticipate that only about 80% of subjects will show up (CWRU students tend to

be pretty good about showing up).

 Keep careful track of all contacts with potential subjects. You should never use

a subject twice for the same set of experiments. Most experimental groups

keep a black list – subjects who don’t show up or disrupt sessions are

undesirable.

Instructions

 Most experiments include some form of consent form. For those of you who

plan on publishing your research, this brings up the issue of the dread IRB . . .

 The overarching goal of instructions is to make certain that the subjects

understand the rules of the experiment. If subjects do not understand the

rules, you have immediately lost control.

 Instructions should be as clear and complete as possible. Any critical points

should be repeated at least once. If in doubt, make the instructions too

detailed. Nobody likes sitting through lengthy instructions, but remember your

goal – the subjects need to understand the rules of the experiment.

 Context: Many experiments like to frame their instructions in a generic context

that does not have any real world connotations. In my opinion, this often

generates confusion for experimental subjects, but that is a controversial point.

All experimenters agree that you should avoid any loaded terms.

 Example: In a Prisoner’s Dilemma Game, you wouldn’t want to label the two

strategies as “Cooperate” and “Cheat” even though this is how game theorists often

refer to them.



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