# Econ

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1. 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 2. Sensitivity Analysis
We change the parameters of the model and determine how the firm optimal decision changes
3. Determinants of Demand
• Concumer Preference
• Consumer Expectations (Conditions about future)
• Income
• Price of Related Goods
• Size of the Market
4. Intercepting Coefficients
Tells us how much the dependent variable changes in response to one unit chagne in the independent variable
5. 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
6. Price Elasticity 7. Ep < -1
• Elastic
• Consumer is Price sensitive
• The curve is flatter
• Between the top and the Unit Elastic point on the chart
8. -1<Ep<0
• Inelastic
• Consumer is not price sencitive
• Curve is steeper
• Between Unit Elastic and the bottom of the chart
9. 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)
10. Cross Price Elasticity
Shows how quantity demanded responds to change in the price of another
11. The mark up equation is
• • OR
• 12. Price Discrimination
• Conditions for:
• 1) Distinguishing between consumers types, demographiscs, etc
• 2) Can prevent arbitrage (Selling amongs consumers)
13. Second degree Price Discriminatoin
Different Price depednig on Quantity
14. Third degree Price Discrimination
Charging different Price to different segment of the market for the same product
15. First Degree Price Discrimination
Offering different price to different consumer according to their willingness to pay
16. Using Mark Up rule:
MC=5 Ep1= -1.6; 17. 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
18. Confidence Intervals
95% will be within 2 Standard Deviation of the sample mean
19. Ordinary least Squares (OLS)
method to run regression. Finds the line that best fits the data
20. Goodness of Fit Measure (OLS regression)
R^2 statistic (

• (basically it's • TSS= • 21. If SSE=0
• No Unexplained Varations
• 22. SSE=1
Doesn't fit the data at all
23. Adjusted ALWASYS USE THAT SHIT! 24. F-Statisics
• Ratio between explained vaiation to unexplained variation
• • High values implies that the module is explaining something
• Low values ... the other way around
25. Critical Value (F-distrivution)
Table based on (k-1), (n-k) degrees of freedom for specific confidence level
26. Significance F
• The probability of getting the f-stat value if the Null Hypothsis is true
• Low Sig Fs - better chance of it being true (regression)
27. How to Reject Null Hypothysis
• YOU CAN"T REJECT IF:
• if F-Stat < Critical Value
• if Significant F > 1 - confidence level
28. 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
29. 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)
30. Cross secion Data
Spans one time period, they tend to have a lot of variables
31. Time Sieries Dat
Spans mulitiple time presiods, few variables
32. If demand becomes more elastic profit mazimizing price will
Decrease
33. If variable cost increases, the marginal cost curve will
Increase
34. If demand decreases, profit maximizing price will
decrease
35. the T-stat tsts the null hypothesis that
of the coefficient could be 0, tbad to see if the coeffiecnt is statisitcally significant
36. Olygopoly
• Few Large firms
• Homogeneous or Heterogenous
• Imeded Entry
• Economies of Scale / High Start up cost
37. Olygopoly Priceing Strategy
Not streight forward