Managerial Economics
Fundamental Economic Concepts
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Marginal analysis:
Analyse the additional (marginal) benefit of any decision
and compare it with additional (marginal) costs
incurred
 The marginal cost versus marginal revenue.
 The additional costs versus additional (or
incremental) profits (or benefits). Example page54
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Total, Average, and Marginal profit
Functions
Where is the Efficiency Point?
Total Profit π
Total Profit
Average Profit
Margianl Profit
Uints of Output Q
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Present Value and Net Present Value
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A marginal cost is present value (PV) while
marginal profit is a future or expected value (FV).
Thus comparison is not correct.
How to discount future value to get present value?
Now compare PV for Present discount Value
Net Present Value NPV is present value minus
initial outlay (expenditure) of investment.
In perfect competitive market NPV should be
zero………………………………….….Why?
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Meaning and Measuring Risks
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Risk is the uncertainty.
Statistical measure of Risks is: the Standard
Deviation.
Discrete versus continuous functions
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Discrete values.
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Continuous functions: the normal probability
distribution.
z=
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The Four Steps Procedure to
Estimate Risks (standard deviation)
Estimate most Optimistic outcome.
 Estimate most Pessimistic outcome.
The Expected Value is midway
between both.
Calculate the standard deviation.
(using z table in any Statistics Book)
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The Normal Probability Distribution
Curve
The normal distribution is an continuous
probability distributions, it may be
defined by two parameters the mean
("average", μ) and variance (standard
deviation squared) σ2, respectively. The
standard normal distribution is the
normal distribution with a mean of zero
and a variance of one
.
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Standard Normal Distribution
Once calculated Z is obtained the probability of occurrence
can be checked from the table
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Standard Normal Distribution
The opposite way of manipulation when you have the
probability of occurrence and you check the table for
the standard deviations
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Coefficient of Variations
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To compare different investment decisions; it is
better to have low Coefficient of Variations, even if
r is very high.
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