1. Outline 1. An institutional perspective 2.Experimental design 3.Main result: convergence 4."Clumsy" behavior 5.Simulations 6.Final remarks Raluca PARVULESCU EXPERIMENTAL AGENTS’ CLUMSINESS, THE MAIN REASON WHY MARKETS CONVERGE TOWARDS AN INEXISTENT EQUILIBRIUM

2. 1. An institutional perspective 1.1 Market taxonomy 1.2 Price convergence issue 1.3 What predictions ? Main feature: prices are decided by the market operators themselves Double auction markets Posted-offer markets: buyers = "price takers"  Production "to order" Production "in advance"  Production "in advance" One important question: Price convergence (or its absence) towards the competitive issue

3. 1. Theoretical predictions 1.1 Market taxonomy 1.2 Price convergence issue 1.3 What predictions ? D – A markets: prices converge towards the "competitive" level (= Nash equilibrium) P - O markets with production "to order" prices converge towards the "competitive" level, be it a Nash equilibrium or not P– O markets with production "in advance" in theory, there is no Nash equilibrium, so no convergence ? Alger [1979] Friedman [1988]

4. 1. Theoretical predictions 1.1 Market taxonomy 1.2 Price convergence issue 1.3 What predictions ? Does the Posted-Offer market with "advance production" converge towards the "competitive" issue, which is not a Nash equilibrium ? If this convergence is observed, what are the forces accounting for it ? agents’ "clumsy" behavior observed in the experiments simulations

5. 2. Experimental design 2.1 General remarks 2.2 Specific details Supply : Every subject was a strawberry producer Inventories or carryover of unfilled orders from buyers are not permitted At the beginning of each period: a price and output decision Decision support: - table with all types of costs (total, average and marginal) - subjects’ own previous results (sold output and realised profit) - all posted prices on the market during the previous periods Demand : computer simulated stable all along the experiment

6. 2. Experimental design 2.1 General remarks 2.2 Specific details 2 phases: - agents are alone on the market - agents play against each others on a competitive market 2 experiments - 9 participants in each session - feb- april 2006 - 2h30 on average - 15€ / person, on average Theoretical benchmarks: - the "competitive" issue: price = 1.3; output = 200 - the "monopoly/cartel" issue: price = 2; output = 85

7. 3. Main result: convergence Fig.1 Average price convergence

8. 3. Main result: convergence Fig 2. Prices variation coefficient

9. 4. "Clumsy" behavior 4.1 Criteria for "clumsiness " 4.1.1 Market adaptation 4.1.2 Overproduction 4.1.3 Profit increase 4.2 Market response Fig 3. Evolution of the rationing phenomenon

10. 4."Clumsy " behavior 4.1 Criteria for "clumsiness " 4.1.1 Market adaptation 4.1.2 Overproduction 4.1.3 Profit increase 4.2 Market response Table 1. Impact of an incurred rationing (or its absence) on a the posted price at the next round Rationing phenomenon intensity DecreaseMaintainingIncrease Very important (23 observations) 91% 4% 5% Significant 87%10% 3% Null or negligible 37%21% 42% (32 observations) (289 observations) 50% of the decisions are "reasonable" 32% of the decisions are "unreasonable" Subjects are very heterogeneous

11. 4. "Clumsy " behavior 4.1 Criteria for "clumsiness " 4.1.1 Market adaptation 4.1.2 Overproduction 4.1.3 Profit increase 4.2 Market response Overproduction : 28% of the decisions Fig 4. Evolution of the indicator of average overproduction ( %)

12. Overproduction: 2 kinds of effects Direct effect agents who disrespect this rule obtain smaller profits (44%) Indirect effect agents who respect this rule obtain smaller profits too (40%) Rationing phenomenon: 18% less in the first session 26% less in the second session Agents are very heterogenous 4. "Clumsy " behavior 4.1 Criteria for "clumsiness " 4.1.1 Market adaptation 4.1.2 Overproduction 4.1.3 Profit increase 4.2 Market response

13. 4. "Clumsy" behavior 4.1 Criteria for "clumsiness " 4.1.1 Market adaptation 4.1.2 Overproduction 4.1.3 Profit increase 4.2 Market response Compare the policy adopted with a reference policy: maintain the same policy when the subject got rationed post the same price and reduce output to the sales level Ex ante and ex post comparaisons of respective profits Table.3 All decisions considered when the subject sold the entire produced Reasonable ex ante and ex post Unreasonable ex ante and ex post 55%28% Reasonable ex ante and ex post Unreasonable ex ante and ex post 40%50% Table 2. Only not " irrational " decisions considered

14. 4. "Clumsy " behavior 4.1 Criteria for "clumsiness " 4.2 Market response Examine agents’ behavior impact on the market 2 individual indicators: the proportion of reasonable decisions from a market adaptation criterion the proportion of reasonable decisions from a profit increase criterion (takes implicitly into consideration the tendency to overproduce) Correlation coefficient: 41% Regression equation: Av.  = 33.4 + 31.53 * Capacity to - 97.53 * Capacity to adapt increase  to the market (t=4.33) (t=2.11) (t=-6.4)

15. 5.1 Decision rules 5. Simulations 5.2 Results 2 types of agents: "clumsy" agent: inspired by the human subjects "rational" type: "best-response " strategy

16. 5. Simulations 5.1 Decision rules 5.2 Results Fig 5. Average sales price evolution on a market with 9 "clumsy" players

17. 5. Simulations 5.1 Decision rules 5.2 Results Fig 6. Average sales price evolution on a market with 9 players adopting a "best response" strategy

18. 5. Simulations 5.1 Decision rules 5.2 Results Fig 7. Average sales price evolution on a market with 3 players adopting a "best response" strategy and 6 "clumsy" players

19. 6. Final remarks Average prices seem to be converging towards the competitve issue in the two sessions carried out Agents’ behavior seems to be far from the "rationality" canons When the number of automates adopting a "clumsy" behavior is predominant, markets stabilize.