Extracting Valuable Data from Classroom Trading Pits

1. Extracting Valuable Data from Classroom Trading Pits Ted Bergstrom & Eugene Kwok University of California, Santa Barbara

2. The Origin of Experimental Economics • The first scientific experiments in economics were classroom market experiments by Edward Chamberlin at Harvard in 1940’s.

3. Chamberlin’s experiments • Assigned Buyer Values and Seller Costs. • Let students mill around and trade. • Recorded prices. • Remarked on difference from competitive equilibrium outcome. • Observed excess trading.

4. Revival at Purdue • Chamberlin’s experiments went almost unnoticed until Vernon Smith revisited them in his classroom at Purdue.

5. Smith’s experiments • Gave competition a better chance. • Two main differences from Chamberlin. • Double oral auction, not pit trading • Ran 3-5 rounds, repeating same setup • Found outcomes very close to competitive equilibrium

6. Edward Chamberlin Vernon Smith Founders of Experimental Economics

7. Our Data • Classroom experiments from Experiments with Economic Principles, a principles text by Bergstrom and Miller • Experiments conducted in 31 classrooms, 10 universities.

8. The Apple Market • Students assigned roles as apple suppliers or apple demanders. • Suppliers supply at most 1 bushel. • Demanders demand at most 1 bushel.

9. Buyer Values and Seller Costs • Two types of demanders • High Value—Buyer Value is $40 • Low Value—Buyer Value is $20 • Two types of suppliers • High Cost—Seller Cost is $30 • Low Cost—Seller Cost is $10

10. Session 1 • 2/3 of Sellers have low cost, 1/3 high. • 2/3 of Demanders have low value, 1/3 high.

11. Demand and Supply in Session 1

12. Session 2 • 2/3 of Sellers have high cost, 1/3 low. • 2/3 of Demanders have high value, 1/3 low.

13. Demand and Supply in Session 2

14. Session 1: Distribution of Average Prices

15. Session 2: Distribution of Average Prices

16. Session 1: Distribution of Quantity Deviations

17. Session 2: Distribution of Quantity Deviations

18. Enough to convince crudulous students, maybe… But does the evidence show that competitive theory is empirically useful?

19. An alternative hypothesis: Profit Splitting • Demanders meet suppliers chosen at random. • If mutually profitable trade is available they trade, splitting the profits. • Demander with value $40 and supplier with cost $30 trade at $35, etc. • There is trading at $15, $25, and $40. • If high cost seller meets low value demander, no trade. .

20. Average Prices are predicted better by Profit-Splitting

21. Detailed predictions • Competitive theory and profit splitting theory both make detailed predictions beyond average price and total quantity. • Distribution of prices • Competition implies uniform price. • Splitting implies trading at $15, $25, and $40. • Both theories predict who trades with whom as well as total number of trades.

22. Demand and Supply in Session 1

23. Session 1: Detailed Price Predictions Competitive vs Profit-splitting

24. Session 1: Distribution of All Prices

25. Demand and Supply in Session 2

26. Session 2: Detailed Price Predictions Competitive vs Profit-splitting

27. Session 2: Distribution of All Prices

28. Session 1: Detailed Quantity Predictions Competitive vs Profit-Splitting

29. Session 2: Detailed Quantity Predictions Competitive vs Profit-Splitting

30. Remarks • Sometimes trading environment is like Smith’s, much repetition with same environments and public trading. • Sometimes more like Chamberlin’s or like ours. • Seems worth understanding what happens in environments with intermediate levels of information.

31. Mining Classroom Trading Pits • Data is cheap and abundant. • Design is less flexible. • But worth saving and studying. • Remember where experimental economics started.

32. That’s all for now… • Mine tailings