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P=20.5Q; TC=5+10Q
What can be done here?
 You can find the Q*
 You can Find P*
 and even Profit Level!
 1) P*Q and then get the dirivitive to find Q*
 2) Plug in Q* into P and get P*
 3) Now that we know both TR and TC get

Sensitivity Analysis
We change the parameters of the model and determine how the firm optimal decision changes

Determinants of Demand
 Concumer Preference
 Consumer Expectations (Conditions about future)
 Income
 Price of Related Goods
 Size of the Market

Intercepting Coefficients
Tells us how much the dependent variable changes in response to one unit chagne in the independent variable

Elasticity
A measure of the sensitivity of one variable in response to a change in another. Specifically it is the % change that will occur in one variable in response to a 1% change in another


Ep < 1
 Elastic
 Consumer is Price sensitive
 The curve is flatter
 Between the top and the Unit Elastic point on the chart

1<Ep<0
 Inelastic
 Consumer is not price sencitive
 Curve is steeper
 Between Unit Elastic and the bottom of the chart

Determinants of Demand Elasticity
 Availability of close substiutes (more subs, more elastic)
 % of income devoted to the purchase
 How necessary the good is (more essential the more inelastic it is > gas, medicne, etc
 Time frame considered (overtime other options develop)

Cross Price Elasticity
Shows how quantity demanded responds to change in the price of another

The mark up equation is

 OR

Price Discrimination
 Conditions for:
 1) Distinguishing between consumers types, demographiscs, etc
 2) Can prevent arbitrage (Selling amongs consumers)

Second degree Price Discriminatoin
Different Price depednig on Quantity

Third degree Price Discrimination
Charging different Price to different segment of the market for the same product

First Degree Price Discrimination
Offering different price to different consumer according to their willingness to pay

Using Mark Up rule:
MC=5 Ep1= 1.6;

Regression Analysis
 1) Develop a theory that explains economic behavior
 2) Collect Data
 3) Estimate the effectivness of the regression equation
 4) Analize and interprate
 5) Compare results and hypthesys

Confidence Intervals
95% will be within 2 Standard Deviation of the sample mean

Ordinary least Squares (OLS)
method to run regression. Finds the line that best fits the data

Goodness of Fit Measure (OLS regression)

If SSE=0
 No Unexplained Varations

SSE=1
Doesn't fit the data at all

Adjusted
ALWASYS USE THAT SHIT!

FStatisics
 Ratio between explained vaiation to unexplained variation
 High values implies that the module is explaining something
 Low values ... the other way around

Critical Value (Fdistrivution)
Table based on (k1), (nk) degrees of freedom for specific confidence level

Significance F
 The probability of getting the fstat value if the Null Hypothsis is true
 Low Sig Fs  better chance of it being true (regression)

How to Reject Null Hypothysis
 YOU CAN"T REJECT IF:
 if FStat < Critical Value
 if Significant F > 1  confidence level

Possible issues w/ Regression Results
 1) Size of sample  less thena 32 not good represenattive
 2) Equation Specification  if lenier is used but the relationship isn't liner
 3)Omited variable
 4)Multicolinarity  occurs when two or more independent varianles are close related or highly corrilated
 5)Simiultinaty and Identification  Observed prices and quantity are result of Supply and Demand
 Bias in the Data

Data Souce
 1) Consumer survey (Sampple Bias, Responce Bias, Responce Accuracy  not knowing 100% how one would actually behave)
 2) Consumer Experiments  reduces respoce accuracy bias
 3) Contrilled Market Studies  Real world data, short term demand picture
 4) Uncontrolled Market Data  gathering available market transaction data (available, cheap; problem w/ similarity)

Cross secion Data
Spans one time period, they tend to have a lot of variables

Time Sieries Dat
Spans mulitiple time presiods, few variables

If demand becomes more elastic profit mazimizing price will
Decrease

If variable cost increases, the marginal cost curve will
Increase

If demand decreases, profit maximizing price will
decrease

the Tstat tsts the null hypothesis that
of the coefficient could be 0, tbad to see if the coeffiecnt is statisitcally significant

Olygopoly
 Few Large firms
 Homogeneous or Heterogenous
 Imeded Entry
 Economies of Scale / High Start up cost

Olygopoly Priceing Strategy
Not streight forward

Advertising Strategy (Olygopoly)
Lot's of advertising, depends on industry

Duopoly
Olygopoly with two firms

Walfare is maesured in
Consumer Surplus

ASsumptions under perfect competition
 Large number of buyers and sellers
 Easy entry and exit
 Firms produce Homogenious products
 Perfect information

Through a numerical example, they show how an airline would appropriately price their tickets. Why is it that in the case of airlines, ticket prices are determined by maximizing revenues and not profits?
Because all costs of production are fixed, which makes profit maximization and revenue maximization equivalent.

