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Managerial Economics

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Jorge Sánchez

on 18 January 2014

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Transcript of Managerial Economics

Chapter 3: Marginal Analysis for Optimal Decisions
Chapter 1: Managers, Profits and Markets
Chapter 2: Demand, Supply and Market Equilibrium
Supply and demand analysis applies principally to markets characterized b many buyers and sellers in which a homogeneous or relatively non differentiated good or service is sold.
Chapter 4: Basic Estimation Techniques
Chapter 6: Elasticity and Demand
Measures responsiveness or sensitivity of consumers to changes in the price of a good:
Managerial Economics
Foundations of Business Analysis and Strategy
The study of individual behavior of consumers, business firms and markets.
Branch of microeconomics focusing on the behavior and structure of firms and industries.
There is no successful business decisions without a clear understanding of how market forces create both opportunities and constraints for business enterprises.

The goal: long-run profitability of the firms.
Develops foundation concepts and optimization techniques that explain everyday business decisions.
Sometimes referred to as business practices or tactics.

Goal: create the greatest possible profit for business enterprises.
Strategic decisions
Business actions taken to alter market conditions and behaviors of rivals in ways that increase and/or protect the strategic firm´s profit.
Long-run profitability
Strong entry barriers
Weak rivalry within market
Low market power of input suppliers
Low market power of consumers
Abundant complementary products
Few close substitutes
Limited harmful government intervention
The role:
It is essential that Managers never forget that the goal of the firm is to maximize economic profits.
Opportunity cost
What a firm´s owners give up to use resources to produce goods or services.
Market-supplied resources
Resources owned by others and hired, rented or leased in resource markets.
Owner-supplied resources
Resources owned by and used by a firm.
Total Economic Cost
So, taking into account that:

* Cost opportunity of Market-supplied resources = explicit costs, and
* Cost opportunity of Owner supplied resources = implicit costs,
Total Economic Cost = Explicit costs + Implicit costs
* Cash (Equity capital)
* Land
* Owner´s time spent managing the firm
Economic Profit
Economic Profit = Total Revenue - Total economic cost
Economic Profit = Total Revenue - (Explicit costs + Implicit costs)
Be careful:
Accounting profit <> Economic Profit
Accounting profit = Total Revenue - Explicit costs
presented in financial statements (balance sheets, cash flow statements and income statements)
So, Better economic profit, better value of the firm.
Price for which the firm can be sold, which equals the present value of future profits.
Since future profits are expected, a risk is associated as a consequence of the possible variation of the profits in the future.
If cost and revenue conditions in any period are independent of decisions made in other time periods, a manager will maximize the value of a firm (the present value of the firm) by making decisions that maximize profit in every single time period.
To take into account
In order to avoid Common mistakes in managing decisions, don´t forget...
1. Never increase output simply to reduce average costs.
2. Pursuit of market share usually reduces profit.
3. Focusing on profit margin won´t maximize total profit.
4. Maximizing total revenue reduces profit.
5. Cost-plus pricing formulas don´t produce profit-maximizing prices.
Separation of ownership and control
are both?
It could be better. Goals tend to be always the same.
It could be a problem.
* Manager´s objectives could differ from owners ones
* Moral hazard
* The principal-agent problem
* Corporate control mechanisms
- Require equity results
- More outsiders
- New investments with debt instead of equity
- Corporate takeovers
It is important to the firm, to know its role in the market:
Price-taking firm
So, what is a market?
Cost of making a transaction happen, other than the price of the good or service itself.
Transaction costs
A firm that can not set the price of the product it sells, since price is determined strictly by the market forces of demand and supply.
Price-setting firm
A firm that can rise its price without losing all of its sales.
Any arrangement through which buyers and sellers exchange anything of value.
Market structures
It depends on:
- The number and size of the firms operating in the market.
- The degree of product differentiation among competing producers.
The likelihood of new firms entering a market when incumbent firms are earning economic profits.

Their structures:
- Perfect competition.
- Monopoly.
- Monopolistic competition.
- Oligopoly.
Presented by: JORGE SANCHEZ
January 16th, 2013

Business decisions
Quantity demanded (Qd): amount of a good or service that consumers are willing and able to purchase during a given period of time (week, month, etc.)
General demand function
Relationship between quantity demanded and the six factors that affect quantity demanded:
) Price of the good or service
) Consumers´s income
) Prices of related goods or services
) Tastes or preference patterns of consumers
) Expected price of the product in future periods
) Number of consumers in the market

= f(
General demand function
In a more specific mathematical form:

= a + b
+ c
+ d
+ e
+ f
+ g

where "a" is the intercept parameter, and "b, c, d, e, f y g" are slope parameters.
General demand function
Intercept parameter
Show the value of
when variables
are all simultaneously equal to zero.
Slope parameters
Parameters in a linear function that measure the effect on the dependent variable (
) of changing one of the independent variables (
) while holding the rest of these variables constant.

Normal good
: good or service for which an increase (decrease) in income causes consumers to demand more (less) of the good, holding all other variables in the general demand function constant.
Inferior good
: good or service for which an increase (decrease) in income causes consumers to demand less (more) of the good, all other factors held constant.
: two goods are substitutes if an increase (decrease) in the price of one of the goods causes consumers to demand more (less) of the other good, holding all other factors constant.
: two goods are complements if an increase (decrease) in the price of one of the goods causes consumers to demand less (more) of the other good, all other factors held constant.
Summary of the General (Linear) demand function
Direct demand function
Relation between price and quantity demanded per period of time, when all factors that affect consumer demand are held constant:

= f (
Demand schedule
A table showing a list o possible product prices and the corresponding quantities demanded.
Demand curve
A graph showing the relation between quantity demanded and price when all other variables influencing quantity demanded are held constant.
Inverse demand function
Mathematical inverse of the direct demand function:

= f (
decreases -> Demand curve reflects a rightward shift.
increases -> Demand curve reflects a leftward shift.
Quantity supplied (Qs): amount of a good or service offered for sale during a given period of time (week, month, etc.)
General supply function
Relation between quantity supplied and the six factors that jointly affect quantity supplied:
) Price of the good itself
) Price of the inputs used to produce the good
) Prices of related goods in production
) Level of available technology
) Expectations of the producers concerning the future price of the good
) Number of firms or the amount of productive capacity in the industry

= f(
General supply function
In a more specific mathematical form:

= h + k
+ l
+ m
+ n
+ r
+ s

where "h" is the intercept parameter, and "k, l, m, n, r y s" are slope parameters.
General supply function
Direct supply function
A table, a graph or an equation that shows how quantity supplied is related to product price, holding constant the five other variables that influence supply:

= f (
Supply schedule
A table showing a list o possible product prices and the corresponding quantities supplied.
Supply curve
A graph showing the relation between quantity supplied and price, when all other variables influencing quantity supplied are held constant.
Inverse supply function
Mathematical inverse of the direct demand function:

= f (
increases -> Demand curve reflects a rightward shift.
decreases -> Demand curve reflects a leftward shift.

Substitutes in production
: goods for which an increase in the price of one good relative to the price of another good causes producers to increase production of the now higher priced good and decrease production of the other good.
Complements in production
: goods for which an increase in the price of one good, relative to the price of another good, causes producers to increase production of both goods.
Summary of the General (Linear) supply function
Market equilibrium
: Excess demand (Shortage)
Qd = Qs
: Market equilibrium (Price in witch
Qd < Qs
: Excess supply (Surplus)
Problem that involves the specification of three things:
* Objective function (maximization or minimization).
* Activities or choice variables (to determine the value of the objective function).
* Any constraints that may restrict the values of the choice variables.
Types of Optimization
Maximization problem: involves maximizing the objective function.
Minimization problem: involves minimizing the objective function.
Other categories of Optimization
* Unconstrained optimization:
the decision maker can choose the level of activity from an unrestricted set of values.

* Constrained optimization:
the decision maker chooses values for the choice variables from a restricted set of values.
Choice variables
Determine the value of the objective function:

* Continuous variables
(any value between two end points).
* Discrete variables
(integer values).
Net benefit
NB = TB - TC
It is the objective function of an unconstrained maximization to be maximized, where:
NB: Net benefit
TB: Total benefit
TC: Total cost

The optimal level of activity (A*) is the level that maximizes Net benefit.
Marginal Benefit and Marginal Cost
Marginal Benefit:
Change in total benefit
Change in activity
Change in total cost
Change in activity
Marginal Cost:
Using Marginal Analysis to find A*
Maximization with Discrete Choice Variables
Decision makers must increase activity until the last level of activity is reached for which marginal benefit exceeds marginal cost.
Sunk costs
Costs that have previously been paid and can not be recovered.
Fixed costs
Costs that are constant and must be paid no matter what evel of the activity is chosen.
Are irrelevant
Constrained optimization
Can be solved sing the logic of marginal analysis.
A crucial concept -> marginal benefit per dollar spent on an activity (Bang per buck).
The ratio MB/P represents the additional benefit per additional dollar spent on the activity.
Ratios of marginal benefits to prices of various activities are used to allocate a fixed number of dollars among activities.
To maximize total benefits subject to a constraint on the levels of activities, choose the level of each activity so that the marginal benefit per dollar spent is equal for all activities.
Average costs
Cost per unit of activity computed by dividing total cost by the number of units of activity.
Q = quantity demanded
P = price of the good
Price Elasticity of demand
If known:
* The percentage change in quantity demanded can be predicted for a given percentage change in price:
* The percentage change in price required for a given change in quantity demanded can be predicted:
Price Elasticity and Total Revenue
Taking into account that:

TR = P x Q,

we have:
It s the change in total revenue per unit change in output.

Since MR measures the rate of change in total revenue as quantity changes, MR is the slope of the total revenue (TR) curve:
Affected by:
* Availability of substitutes
* Percentage of Consumer´s budget
* Time period of adjustment
* Over an interval
Can be measured:
* At a point (linear demand):
= a + b
+ c
+ d
M: income
Pr: price of a related good
Expressing demand as:
= a' + b

where a' = a + c
+ d
and the slope parameter is:
Using either of the two formulas below which give the same value for E:
Marginal Revenue
* When inverse demand is linear,
P = A + BQ (A > 0, B < 0)
* Marginal revenue is also linear, intersects the vertical (price) axis at the same point as demand, & is twice as steep as demand:
MR = A + 2BQ
Demand and Marginal Revenue
MR more simple:
For all demand y marginal revenue curves using price elasticity of demand:
* Income elasticity (Em):

* Cross-price elasticity (Exr):
Other demand elasticities
Basic estimation
: coefficients in an equation that determine the exact mathematical relation among the variables.
Parameter estimation
: process of finding estimates of the numerical values of the parameters of an equation
Regression analysis
Statistical technique for estimating the parameters of an equation and testing for statistical significance.
Linear regression analysis
Simple linear regression model
Relation between dependent variable Y to only one independent (or explanatory) variable X in a linear way:
a: intercept parameter
b: slope parameter
Parameter estimates are obtained by choosing values of a y b that minimize the sum of squared residuals. The residual is the difference between the actual and fitted values (Y: Yi – Y'i).
The sample regression line is an estimate of the true regression line.
Statistical significance
Purpose of regression analysis
1) Estimate the parameters (a and b) of the true regression line.
2) Test whether the estimated values of the parameters are statistically significant.
* Time series
* Cross-sectional data set
* Scatter diagram
* Method of least-squares
Statistically significant
There is sufficient evidence from the sample to indicate that the true value of the coefficient is not 0.
* The relative frequency distribution for b'.
* The t-Ratio
* p values.
Exact level of significance for a test statistic, which is the probability of finding significance when none exists.
Evaluation of the regression equation
* Coefficient of determination (R2)
* The F-Statistic
Fraction of total variation in the dependent variable explained by the regression equation.
Used to test whether the overall regression equation is statistly significant.
Multiple regression
Regression models that use more than one explanatory variable to explain the variation in the dependent variable.
Nonlinear regression analysis
Quadratic regression model
A nonlinear regression model of the form:
Log-linear regression model
A nonlinear regression model of the form:
and substituting Z for X2 to transform into a linear model:

Y = a + bX + cZ
Taking into account that b and c are elasticities and taking natural logarithms we have:
Finally, replacing Y' by ln Y, X' by n X, Z' by ln Z and a' by ln a, we have:
Chapter 7: Demand Estimation and Forecasting
Empirical demand functions
- Fundamental building block of statistical demand analysis.
- They are demand equations derived from actual market data.
- Extremely useful in making pricing and production decisions.
Direct methods of demand estimation
Consumer interviews
Problems to consider:
1. The selection of a representative sample.
2. Response bias.
3. Inability of the respondent to answer accurately.
Market studies and experiments
A somewhat more expensive technique for estimating demad and demand elasticity.
Specification of the empirical demand function
General empirical demand specification
Linear empirical demand specification
Its elasticities:
Nonlinear empirical demand specification
Converted to natural logarithms:
Demand for a Price-Setting firm
Follow the next steps:
Step 1: Specify price-setting firm’s demand function
Step 2: Collect data for the variables in the firm’s demand function
Step 3: Estimate firm’s demand using ordinary least-squares regression (OLS)

Time series forecasts of sales and price
* A time-series model shows how a time-ordered sequence of observations on a variable is generated.
* Simplest form is linear trend forecasting:
- Sales in each time period (Qt ) are assumed to be linearly related to time (t).
Linear trend forecasting
Use regression analysis to estimate values of a and b:
Seasonal (or cyclical) variation
Regular variation that time-series data frequently exhibit.
* To account for such variation, dummy variables are added (values of 0 and 1) to the trend equation.
Final Warnings
* The further into the future a forecast is made, the wider is the confidence interval or region of uncertainty
* Model misspecification, either by excluding an important variable or by using an inappropriate functional form, reduces reliability of the forecast.
* Forecasts are incapable of predicting sharp changes that occur because of structural changes in the market.
Christopher Thomas, S. Charles Maurice
11th. edition
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