This lecture summary covers the following topics: 1) Game theory concepts like payoff matrices, dominant strategies, Nash equilibrium, and maximin strategies as well as the Prisoner's Dilemma and first mover advantages. 2) Minimizing risk and uncertainty through probability distributions, standard deviation, and the coefficient of variation. 3) Capital as a factor of production.

1. Lecture 2
Economics 2B
Optimisation (2)
Production factors (1)
(layout of lecture &
figures)

2. References in textbook
Micro Management Economics
Section A Pages 14-28
Section B Pages 32-44
Workbook section

3. Concepts to be covered in
lecture
 1) Game theory.
 Payoff matrix.
 Dominant strategy.
 Nash equilibrium.
 Maximin strategies.
 Prisoner’s dilemma.
 First mover advantages.
 2) Minimisation of risk & uncertainty.
 Probability distributions.
 Standard deviation.
 Coefficient of variation
 3) Capital as a factor of production

15. Coefficient variation = v = σ/X*
The coefficient of variation, thus, measures the
standard deviation per pound of expected value
or mean. As such, it is dimension-free, or, in other
words, it is a pure number that can be used
to compare the relative risk of two or more projects.
The project with the largest coefficient of
variation will be the most risky. For example, if the
expected value and standard deviation of
project A were, respectively, X*A = ￡ 600, and σA =
￡ 219.09 while X*B = ￡ 660 and σB = ￡ 287.05.
However, the coefficient of variation (v) as a measure
of relative dispersion or risk would still
be smaller for project A than for project B. That is,
VA = σA/XA = ￡ 219.09/ ￡ 600 = 0.37 while VB =
σB/XB= ￡ 287.05/ ￡ 660 = 0.44
Thus, project A would have less dispersion relative to
its expected profit (i.e., it would be less
risky) than project B.

16. Capital as factor of production