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Teach Examples of Monopoly Markets
using an Economic Simulation Game

There is an extensive and growing literature on the pedagogical effectiveness of simulation games in education (see Lean, Moizer, and Towler, 2006; Simkins, 1999; Motahar, 1994). The purpose of this note is to explain and illustrate how an economics simulation game can be used as an example and application of the monopoly market to help in the teaching and learning of this market. A comprehensive guide on how to incorporate simulation games in business education at the college level is given by Gentry, et. Al. (1990).

Use in Standard Classroom or for Experimental Economics

A monopoly market simulation can be used as an example in the standard economics classroom or for experimental economics. Economic experiments using monopoly market simulations can create real-world incentives that may be used in the teaching and learning of economics to help students better understand why markets and other exchange systems work the way they do. A detailed explanation of experimental economics is given by Roth (1995).

An online computerized economic simulation game called “Beat the Market” is used to simulate several different examples of the monopoly market (see a brief description of the simulation game at the AEA website. This simulation is designed to put students inside the theoretical world of perfect competition as described in the standard economics textbook.  Through the simulation, students participate directly in the market by managing a simulated firm and making decisions on price and production to maximize profits. 

Assumptions of Monopoly Market Simulation Game Example

All the example simulations follow the basic theoretical assumptions of the monopoly market structure and include:

  1. Only one firm is in the market, with a market share of 100%.
  2. A unique product with no close substitutes
  3. Entry of firms is not permitted (completely blocked).
Options in Simulating the Monopoly Market

In the example simulations, the instructor may select different environments within the context of a monopoly market, including:

  1. Short-run versus long-run
  2. Changing events (random exogenous shocks)
  3. Macroeconomic environment (stable, growth, cyclical)

Two simulation game examples will be illustrated, including one short-run and one long-run simulation. The example simulations illustrated here will not have any random events and will hold the macroeconomic environment constant. (But the software does allow these variables, options 2 and 3 above, to be included at the discretion of the instructor.)

Short-run Monopoly Market Game Example Simulation

The short-run simulations do not allow students to change the plant size of their firm.

Controllable Decisions in the Short-run Monopoly Market Simulation Game Example

  1. Firm price
  2. Firm production

Simulation Performance in Short-run Example

At the start, the market is not in equilibrium and has the following characteristics.

Quarter

Monopoly Price

Monopoly Demand

Monopoly Supply

Profit

0

$75.11

5,087

4,100

$119,522

Students make decisions for their firms based on their own firm characteristics. The simulation example is challenging because the monopoly firm does not start in equilibrium and has an excess demand of 987 units.  To eliminate the excess demand, the monopolist has three choices:

  1. Raise production to meet demand and keep price constant
  2. Raise price to reduce quantity demanded and keep production constant
  3. Do some of combination of both, i.e. raise price and increase production.

To help make decisions on price and production, students are given information on their firm costs and revenues, including marginal costs, marginal revenues, and price elasticity. 

To maximize profits, the knowledgeable student learns that it is necessary to change price and production until marginal revenue equals marginal costs at the point where quantity demanded equals quantity supplied. 

The challenge in the simulation is to use information on price elasticity to estimate demand and marginal revenue; and then study the costs data to estimate marginal costs.  In the game, students are “not” given equations of the demand and cost functions, rather they are only expected to interpolate or graph data to estimate the impact of price and production on demand, costs and revenues.

To provide additional help and insight, the simulation allows students to compare their results to monopoly firms that are managed by the computer.  The computer managed firms make decisions based on sound economic principles, i.e. MR and MC analysis. By comparing their work with the computer managed firms, students can gain insights and learn on their own by playing the game. 

The following results show a sample of the decisions made by a computer managed firm in the monopoly market simulation.

Monopoly Market Results in Short-run Simulation

Quarter

Monopoly Price

Monopoly Production

Monopoly Demand

Marginal Revenue

Marginal Cost

Monopoly Profit

1

$78.79

4,373

4,375

$56.28

$55.64

$137,941

2

$78.65

4,402

4,402

$56.00

$56.96

$137,969

3

$78.70

4,392

4,392

$56.11

$56.38

$137,987

4

$78.76

4,388

4,388

$56.23

$56.23

$138,000

Since demand is estimated, the production level does not exactly equal the quantity demanded in quarter 1, but it is close. This is a more realistic way of showing how firms operate in the “real world” where there are no exact equations.  

In quarter 2, the monopoly firm lowered price and increased quantity produced because in quarter 1 marginal revenue of $56.28 exceeded marginal costs of $55.64.  Profits improved but were still not maximized since marginal revenue was now below marginal costs.

In quarter 3, the monopoly firm raised price slightly to increase marginal revenues, and lowered production which decreased marginal costs. Marginal revenues were now very close to marginal costs. But profits were still not maximized. 

Finally, the computer managed monopoly firm found the exact profit maximizing point in quarter 4, where production equaled demand and marginal revenue equaled marginal costs.

Long-run Monopoly Market Simulation Example

The long-run simulation example allows students to change the plant size of their firm and take advantage of economies of scale.  Both economies and diseconomies of scale exist in the simulation. Students are given information on how the average variable costs change in the simulation with increases in plant size.   

Controllable Student Decisions in Long-run Simulation Example

In this example, plant size is added as a third controllable student decision, and now includes:

  1. Firm price
  2. Firm production
  3. Firm plant size
Simulation Performance in Long-run Example

At the start, the market is not in equilibrium and has the following characteristics.

Quarter

Average Plant Size

Monopoly Price

Monopoly Demand

Monopoly Supply

Profit

0

6.0

$75.11

5,087

4,100

$119,522

Note that the starting characteristics of the market are set to be the same as in the short-run example.  In this way comparisons can be made more directly between the two simulation examples.  The major difference in the long-run example is that plant size may now be changed.  As in the previous simulation example, all firms start with an excess demand. Given this starting scenario, students again begin by raising their prices and increasing the quantity supplied.  But this time, plant size also increases as students take advantage of economies of scale that is built into this simulation example.

Long-run Simulation Results

Quarter

Average Plant Size

Monopoly Price

Monopoly Production

Monopoly Profit

1

6

$78.79

4,373

$137,941

2

8

$76.01

5,013

$155,423

3

10

$72.87

5,673

$167,545

4

12

$70.30

6,229

$171,522

5

12

$70.43

6,272

$172,067

6

12

$70.71

6,298

$172,757

These results had a number of similarities to the short-run example, but also some major differences. As in the short-run example, monopoly firms set marginal revenue equal or close to marginal costs given any plant. But in the long-run simulation example there were several important differences.

  1. Plant size increased significantly since it was a controllable decision of the firm and there were economies of scale.
  2. Economies of scale meant firms were able to take advantage of lower average costs and earn higher profits.
  3. Firms continued to increase plant size if the marginal revenues exceeded the marginal costs of doing so, and economic profits increased.
  4. Market price was bid down much lower than in the short-run example because firms were able to lower their average costs of production, and the monopoly firms in the simulation found it most profitable to pass along some of the cost savings by reducing the selling price.

Concluding Remarks

From an educational point of view, the benefit of a simulation game example is that students will have an “opportunity” to learn by their own observations and experience.  In these simulation examples, student participants would observe and experience that the monopolist does not charge the highest price possible. They would “experience” that in the simulation the maximum profit occurs by setting price and production where marginal revenue equals marginal cost, which turns out to be a lower price than in the initial period.  In the long-run simulation example, they would see the impact of changing plant size.  They would observe that the successful firms would take advantage of economies of scale. Students would see the benefits of economies of scale in reducing costs and increasing profits; and that the profit maximizing monopolist would lower price along with the cost the savings derived from economies of scale. This result is typically not intuitive to the new economics student.

While participating in the simulation, students would experience the same challenges that monopolists face in the real world.  This experience provides students another opportunity to learn (as a supplement to the lecture and readings) the economic messages of the monopoly market.

References on Active Learning and Experimental Economics

Gentry, J., ed., (1990), Guide to Business Gaming and Experiential Learning, ABSEL, Nichols/GP Publishing, East Brunswick.

Lean, J., Moizer, M., Towler, C. A. (2006). Active Learning in Higher Education, Journal of Simulation and games, 7(3), 227-242.

Simkins, S.P. (1999), Promoting active-student learning using the World Wide Web in economics courses, Journal of Economic Education, 30(Summer), 278-291.

Motahar, Eshragh (1994), Teaching modeling and simulations in economics: A Pleasant Surprise, Journal of Economics Education, 25 (4), 335-342.

Roth, A.E. (1995), Introduction to experimental economics, in Kagel, J.H. and Roth, A.E. (eds.), The Handbook of Experimental Economics. Princeton: Princeton University Press, pp. 3-109.