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Experimental Economics: Short Course Universidad del Desarrollo Santiago, Chile December 16, 2009

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Experimental Economics: Short CourseUniversidad del DesarrolloSantiago, ChileDecember 16, 2009

Dr. Jonathan E. Alevy

Department of Economics

University of Alaska Anchorage

- Hypothetical responses
- usually more noise in data
- Poor publication prospects

- Recent discussion on Economic Science Association Listserv

- Dear colleagues,Is there a classical paper (or at least well-known) paper that specifically compares people's behavior in experiments where they are not paid for theirchoices and when they are.I googled keywords "hypothetical choice" and similar but somehow all papersthat it shows seem to be, well, too applied.Thank you in advance,Dmitry

After doing (experimental economics) for several decades, just don't waste time on this issue. I remain astonished to see how many fine researchers still decide to waste time on this, when the evidence is so clear and has been for decades.

We really have much more important issues to debate. If you or someone else insists on doing some hypthetical choices, then at least run some checks when you pay for real (and please do not do comical things like pay 1-in-3000, which one recent study did as an alleged check on hypothetical bias).

- Glenn Harrison

Holt & Laury, “Risk Aversion and Incentive Effects,” AER 2002

Holt & Laury Elicitation Results

Hypothetical payments

Real payments

Visually: a treatment effect!

Statistically: How can we be more certain?

- Experimental design drives the statistical analysis
- What type of data? Binary, ordinal, cardinal?
- HL Binary data (choose A or B)

- Within or between subjects?
- At what level are observations independent?
- HL: Dependent across Hypothetical and Real treatments
- HL: independent across subjects. (individual choice)

- What type of data? Binary, ordinal, cardinal?
- Two approaches:
- Historically: Simple nonparametric tests provide insight on treatment effects.
- Different tests used for within or between subjects designs

- Current practice: Supplement nonparametric tests with conditional (regression) estimates of parameters.
- Use demographic or other data to explain results.
- Panel data techniques account for dependencies.

- Historically: Simple nonparametric tests provide insight on treatment effects.

- Approach 1: nonparametric statistics
- If A choice = 1, B choice = 0. Define variable as sum of choices for individual iin treatmentt
- Higher value implies more risk averse.
- Wilcoxon test for matched data (within subjects)
- Mann-Whitney test for between subjects design
- See appendix slides for details or Siegel & Castellan 1988

- Note: HL protocol is used to understand behavior in other experiments (e.g. auction studies) .
- Use the risk variable on right side of estimation equation is one way to do this.

- Approach 2: Maximum likelihood techniques
- Maintain data in original binary form
- Estimate probability of A choice given treatment dummy and other control variables.
- Probit (or logit) specification

- Multiple choices by individuals accounted for in error term (random effects model).
- Can impose structure on utility
- estimate Coefficient of Relative Risk Aversion and other parameters
- See Harrison 2008 Maximum Likelihood in STATA on course webpage
- For extensions (includes STATA code).

- Assume U(y) = y1-r/(1-r) for r ≠ 1
- In this case r=0 is RN, r>0 is RA, and r<0 is RL

- Holt and Laury
- Important contribution to measuring risk attitudes
- Menu of choices (with real payments) provides incentive for truthful response.
- Relatively easy to understand.

- Criticisms
- Original study confounds incentive effect by not varying order
- Controlling for order, basic result holds
- Salient payments important, contra Kahneman & Tversky conjecture.

- Large number of applications follow this protocol.
- Include extensions to non-expected utility, time preferences, valuation of goods.

- Important contribution to measuring risk attitudes

- Becker Degroot Marschak
- Handout

- A “single person auction”
- Comparison to HL
- Advantages
- Single decision

- Disadvantage
- Cognitively demanding?

- Advantages

- Yesterday we looked at induced value double auction (commodity market)
- Smith 1962
- Quickly and reliably goes to competitive equilibrium

- Asset market experiment
- Smith, Suchanek, and Williams (1988)
- Prices diverge from fundamental values
- Price bubbles and crashes frequently observed

- Why the difference?

- Core methodological contribution: Able to induce value of the asset
- Identification problem in field studies.
- What is the fundamental value?

- Solution: Create asset with specific payoff attributes and duration

- Identification problem in field studies.
- Able to control information
- Asset structure is common knowledge
- Endowments are private information

- Replication
- Test robustness of existing findings
- Systematically study new treatments

- Smith, Suchanek and Williams, 1988

- 15 trading periods - ‘days’
- Each trader is endowed with assets and cash
- Endowments are private information
- Endowments are of equal expected value for all traders

- The asset traded has
- State contingent dividend = {0, 8, 28, 60}
- Equal probability for each state.
- Expected value of 24 cents
- Dividends that pay at end of each trading day

- Traders can bid, offer, buy or sell or do nothing

- Rational Expectations Equilibrium
- Price falls by value of expected dividend each period (-24).
Tirole (1982)

- Price falls by value of expected dividend each period (-24).

- Rational expectations: Backward induction no bubbles
- No trade if all are risk neutral
- Price path follows the red dashes
- Tirole (1982)

- Rational bubbles – relax rational expectations assumption
- Price rises due to:
- Lack of common knowledge of bubble
- Limits to arbitrage

- Risk of crash exists
- A coordinating device is needed to induce sales
- Abreu & Brunnemeier (2003)

- Price rises due to:

- Bubbles are observed in markets with new traders
- Robust to many alternative treatments
- Short-selling, futures markets, dividend certainty, price limits, initial endowments, informed confederates.

- Robust to many alternative treatments
- What works? Experience
- “…trades fluctuate around fundamental values when the same group returns for a third session.”
Porter and Smith (2003 JBF) (emphasis added)

- “…trades fluctuate around fundamental values when the same group returns for a third session.”
- Two new results
- Alevy & Price 2008
- Convergence with inexperienced traders who have received advice

- Hussam Porter & Smith, 2008
- Convergence is not robust
- New fundamentals bubbles resume.

- Alevy & Price 2008

- Control
- Single session of stage game - no advice.
- Do we get a bubble with our protocol?
- software, subject pool, instructions etc.

- Own-experience
- Same cohort repeats stage game three times

- Intergenerational advice
- Three generations - new traders in each

- Three “generations” of markets
- Second and third generation receives advice from immediate predecessor.
- Incentive to leave quality advice
- Predecessors receive payment tied to successors performance

- Full advice
- All traders receive unique advice from predecessors

- Three or six traders receive advice

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- Bubble size declining by generation p<.05
- No significant difference between advice and experience

- Dynamic model: price depends on history
: average price in session i onday t

: number of offers in session i onday t

: number of bids in session i onday t

- Prediction under rational expectations

Table A.1. Random Effects –Advice Only

** Denotes statistical significance at the p < 0.05 level

* Denotes statistical significance at the p < 0.10 level

- (Models A and B) Fail to reject Ho: alpha = -24
- (Model B) Fail to reject Ho: betaBO+ beta3Gen*BO= 0 rational expectations

- Fundamentalist
- If price > fundamentals, active as a seller
- Definition: # offers > # bids when prices are above fundamental value

- If price > fundamentals, active as a seller
- Momentum Trader
- If price > fundamentals, active as a buyer
- Definition: # bids > # offers when prices are above fundamental value

- If price > fundamentals, active as a buyer

- 75% of advised and 48% of unadvised are fundamentalists.
- Qualitative analysis of advice shows
- Little stress on fundamentals
- Heuristics adopted due to advice move prices towards fundamentals
- Advice is ‘sticky’
- In 2nd generation those receiving advice leave advice like their predecessor
- Those without advice differ…slightly greater emphasis on fundamentals.

- Prices converge rapidly to rational expectations equilibrium
- A novel finding in the literature

- Advice is unsophisticated but effective in changing behavior
- Benefits of advice accrue at market level
- Reduces variance in earnings
- Advised do not earn more

- Achieve convergence in usual manner
- Experienced group of traders

- After convergence
- Change fundamentals, wider distribution of dividends
- Bubbles rekindle.

- Would advised be more robust?
- Think more deeply about the problem when giving or receiving advice.
- Perhaps less brittle type of learning

- The Dictator “game”
- An individual decision task on splitting a surplus with another

- Stylized fact across many replications
- Give none or give some (often half) two “types”
- Selfish & Altruistic

- Give none or give some (often half) two “types”

- Dictator game run to better understand ultimatum game results
- Ultimatum game (two person)
- Player 1: Offers a division of surplus
- Player 2: Accept or reject offer
- If reject both players receive zero.

- Dictator game
- Decompose ultimatum game offers
- Is a component of ultimatum offer altruistic?

- Decompose ultimatum game offers

Forsythe et al. 1994

- Innovation: The “Bully” game
- Extend the action space to allow giving & taking
- List 2007, Bardsley 2008

Give

Take 1

Take 5 Earn

Take 5

- Behavior inconsistent with “preference based” explanation
- Emphasizes importance of institutions in shaping behavior.
- Including experimenter demand effects in the laboratory.
- Property rights (earned endowment treatment)

- From Andreas Lange University of Maryland