This game implements a competitive market for labor. Each firm can submit one wage offer at a time, and each worker decides whether to accept the highest current offer.
When a perfectly competitive market determines wages, the equilibrium wage, per unit of labor, is equal to the value of the marginal product of labor of the last worker hired.
A minimum wage decreases the quantity of labor demanded, which will lead to a decrease in employment. By increasing the opportunity cost of supplying labor, unemployment insurance decreases employment. These policies may therefore affect structural unemployment, and thus, an economy's natural rate of unemployment.
By default, we set Group Size equal to 16 (12 players will be workers, 4 will be firms) and Jobs Per Firm equal to 3. This induces a market with 12 workers vying for 12 jobs (4 firms × 3 jobs per firm = 12 jobs available in the market). With the Value of Marginal Labor Product ranging from $8.00 to $13.00 and the opportunity cost of labor from $2.50 to $8.50, our default parameters induce an equilibrium wage of $8.20 with 11 units of labor employed.
It generally takes two iterations for the market wage to approximately converge to equilibrium. Your options:
Once labor markets have qualitatively converged to the equilibrium prediction, consider implementing labor-market policies which reduce employment levels:
The market summary table (Figure 1) summarizes each group's outcome. The first row gives the equilibrium benchmark for the market without labor market intervention. The second row reports statistics averaged across groups. Each subsequent row reports the outcome for a specific group: average wage, quantity of workers employed, and realized surplus (firm, worker, and total.)
In addition, we report two graphs for each group (Figure 2). On the left is the supply and demand graph, modified to incorporate the unemployment insurance payment or minimum wage if applicable. The graph on the right—with wage on the vertical axis and time on the horizontal— records each transaction. The graph at the bottom of the results page (Figure 3) records transactions across all groups.
Our robot (i.e., an automated player) strategies for each role are the following:
Robots begin by offering 60% of their marginal revenue. Bids increase at regular time intervals (one quarter of round duration) such that profit declines by 50% with each updated bid.
If the best offer is less than opportunity cost, the robots reject the offer. Above opportunity cost, the probability of acceptance is an increasing function of wage. When wage is double opportunity cost the worker accepts with certainty.