Part 1: INTRODUCTION.

1. Economic Models.

Appendix: Mathematics Used In Microeconomics.

Part 2: DEMAND.

2. Utility and Choice.
3. Individual Demand Curves.
4. Market Demand and Elasticity.

Part 3: UNCERTAINTY AND STRATEGY.

5. Uncertainty.
6. Game Theory and Strategy.

Part 4: PRODUCTION, COSTS, AND SUPPLY.

7. Production.
8. Costs.
9. Profit Maximization and Supply.

Part 5: PERFECT COMPETITION.

10. Perfect Competition in a Single Market.
11. Applying the Competitive Model.
12. General Equilibrium and Welfare.

Part 6: MARKET POWER.

13. Monopoly. 14. Imperfect Competition.

Part 7: ADDITIONAL TOPICS.

15. Input Markets.

Appendix: Individual Labor Supply.

16. Capital and Time.

Appendix: Compound Interest.

17. Asymmetric Information.
18. Externalities and Public Goods.

1 SIMULATION AND CONDITIONAL PROBABILITY.

1.0 Getting Started with Simtools in Excel
1.1 How to Toss Coins in a Spreadsheet
1.2 A Simulation Models of 20 Sales Calls
1.3 Analysis Using Excel's Data-Table Command
1.4 Conditional Independence
1.5 A Continuous Random Skill Variable from a Triangular Distribution
1.6 Probability Trees and Bayers' Rule
1.7 Advanced Spreadsheet Techniques: Constructing a Table with Multiple Inputs
1.8 Using Models
1.9 Summary
Exercises

2 DISCRETE RANDOM VARIABLES.

2.1 Unknown Quantities in Decisions Under Uncertainty
2.2 Charting a Probability Distribution
2.3 Simulating Discrete Random Variables
2.4 Expected Value and Standard Deviation
2.5 Estimates from Sample Data
2.6 Accuracy of Sample Estimates
2.7 Decision Criteria
2.8 Multiple Random Variables
2.9 Summary
Exercises

3 UTILITY THEORY WITH CONSTANT RISK TOLERANCE.

3.1 Taking Account of Risk Aversion: Utility Analysis with Probabilities
3.2 Utility Analysis from Simulation Data
3.3 The More General Assumption of Linear Risk Tolerance
3.4 Advanced Technical Note on Utility Theory
3.5 Advanced Technical Note on Constant Risk Tolerance
3.6 Summary
Exercises

4 CONTINUOUS RANDOM VARIABLES.

4.1 Normal Cistributions
4.2 EXP and LN
4.3 Lognormal Distributions
4.4 Generalized Lognormal Distributions
4.5 Subjective Probability Assessment
4.6 A Decision Problem with Discrete and Continuous Unknowns

5 CORRELATION AND MULTIVARIATE NORMAL RANDOM VARIABLES.

5.1 Joint Distributions of Discrete Random Variables
5.2 Covariance and Correlation
5.3 Linear Functions of Several Random Variables
5.4 Estimating Correlations from Data
5.5 Making Multivariate Normal Random Variables with CORAND and NORMINV
5.6 Portfolio Analysis with Multivariate Normal Asset Returns
5.7 Excel Solver and Efficient Portfolio Design
5.8 Subjective Assessment of Correlations
5.9 Using CORAND with Non-Normal Random Variables
5.10 More About Linear Functions of Random Variables
5.11 Fummary
Exercises

6 CONDITIONAL EXPECTATION.

6.1 Dependence Among Random Variables
6.2 Estimating Conditional Expectations and Standard Deviations
6.3 The Expected-Posterior Law in a Discrete Example
6.4 Backwards Analysis of Conditional Expectations in Tree Diagrams
6.5 Conditional Expectation Relationships and Correlation
6.6 Uncertainty About a Probability
6.7 Linear Regression Models
6.8 Regression Analysis and Least-Squared Errors
6.9 Summary
Exercises

PART 1: INTRODUCTION.

1. Economic Models.
2. Mathematics used in Microeconomics.

PART 2: CHOICE AND DEMAND.

3. Preferences and Utility.
4. Utility Maximization and Choice.
5. Income and Substitution Effects.
6. Demand Relationships Among Goods.
7. Uncertainty and Information.
8. Strategy and Game Theory.

PART 3: PRODUCTION AND SUPPLY.

9. Production Functions.
10. Cost Functions.
11. Profit Maximization.

PART 4: COMPETITIVE MARKETS.

12. The Partial Equilibrium Competitive Market.
13. General Equilibrium and Welfare.

PART 5: MARKET POWER.

14. Monopoly.
15. Imperfect Competition.

PART 6: INPUT MARKETS.

16. Labor Markets.
17. Capital and Time.

PART 7: OTHER TOPICS.

18. Asymmetric Information.
19. Externalities and Public Goods.