ECON
Durban watson test
- will detect serial correlation -want to be as close to 2 as possible -if close to 0 or 4, you're effed
Assuming the inverse demand function for good Z can be written as P=90 - 3Q when P=20, the point price elasticity of demand is equal to (approx)
-0.29
What to look for in a regression
-R-squared/ Adj. R squared = close to 1 as possible -Significance of F to be as close to 0 as possible -If both are 0, look for highest F score -How many t-stats are significant -p-value as close to 0 as possible -t-stat within 1.96 barrier
tests to find problems w regression
-correlation matrix -durban watson
R^2 aka r-squared
-known as the coefficient of determination -between 0 and 1 (the closer to 1 the better) -adding another variable increases r^2
Firms want to maximize profit
-maximize TR, minimize TC -when E = 1, TR is maximized
To maximize profit
-maximize total revenue -minimize total costs -MR = 0 -E = 1
product development
-prices could go up , lowering demand -long adjustment periods getting used to new products
Cross price elasticity
ecp= (%change Qd1)/(%change P2)
E=
(% change in QD)/(%change in P)
Income elasticity of demand
ey = (%change Qd)/(% change y) ey < 0 = inferior good 0 < ey < 1 = income inelastic ey > 0 = income elastic
serial correlation
found by looking at residuals over time
Heteroskedasticity
getting bigger and bigger -an argument to revisit demand ex: silly bands -something has structurally changed in the market and you need to adjust your demand curve
positive serial correlation
getting greater overtime but following a cyclical pattern
If the price of a video download is above the equilibrium price, the quantity supplied is ___________ than the quantity demanded.
greater
shortages and surpluses are
signals that markets are adjusting
Some sales managers are talking shop. Which of the following quotations refers to a movement along the demand curve
"We decided to cut our prices, and the increase in our sales has been remarkable"
The figure illustrates demand for hamburgers. When the price is $1.00 a hamburger, the elasticity of demand is ______ and a 1 percent increase in the price will ____ the quantity of hamburgers demanded by ______ percent
0.40; decrease; 0.40
Suppose the price of movies seen at a theater rises from $12 per couple to $20 per couple. The theatre manager observes that the rise in price causes attendance at a given movie to fall from 300 persons to 200 persons. What is the price elasticity of demand for movies
0.8
What are determinants of elasticity
1. Products w many close substitutes have highly elastic demand. ex: toothpaste 2. Individual brands have more elastic demand than industries. ex: healthcare 3. The greater proportion of income spent on a good, the more elastic your demand is. 4. in the long run, demand becomes more elastic 5. As price increases, quantity becomes more elastic
Determinants of demand
1. consumer tastes 2. prices of related goods 3. income 4. population 5. expected future prices
determinants of supply
1. price of resources 2. level of technology 3. prices of alternatively producible goods 4. expected future prices 5. # of firms
If the local pizzeria raises the price of a medium pizza from $6 to $10 and quantity demanded falls from 700 pizzas a night to 100 pizzas a night, the arc price elasticity of demand for pizzas is
3.0
T-stat range
> |1.96|, your p-value will be significant
Which of the following would NOT cause the supply curve for gasoline to shift
A change in the incomes of drivers
To maximize its revenue:
A firm facing inelastic demand should always rise its price
R2
A number that tells you how how well your model is explaining the variance in the dependent variable
Serial Correlation
A problem that a model may have that means the results of the model are untrustworthy and seldom worth the paper they are printed on
ANOVA
Analysis of variance
Selling Price and amount spent advertising were entered into a multiple regression to determine what affects flat panel LCD TV sales. The regression coefficient for Advertising was found to be +3.0926, which of the following is the correct interpretation for this value?
At a given price, a one percent increase in the amount spent on advertising the Sony Bravia over the previous quarter is associated with an increase in sales of 3.0926.
Imperfect multi-collinearity
Big problem. Regression will run but results are not trustworthy. R^2 & F will be very high but nothing in the model is significant
Suppose we observe that both the equilibrium price of film cameras and the equilibrium quantity of film cameras have fallen. Which of the following could be responsible for this?
Consumers' preferences changed in favor of digital cameras
Price elasticity of supply
Es = (%change Qs)/(%change P) * you can break down supply chain and see where weaknesses are and how big they are
negative serial correlation
In theory, should go away but also could mean that you're not explaining something in your model
Which of the following is NOT one of the factors that influences supply of a product
Income
This summer the lobster catch in Maine has been especially large, but instead of celebrating the fisherman are suffering from a lower total of revenue. We learn from the article that despite the larger quantity of lobster caught, the total revenue of the fisherman has decreased. This fact means that the demand for lobster is:
Inelastic
Along a straight-line demand curve, as the price falls....
The demand becomes less elastic
Sara's strawberry Market maximizes its total revenue by selling strawberries for $1.25 a basket. At a price of $1.25 you predict that:
The demand for strawberries is unit elastic
Multicollinearity
The most common problem with data but the 'errors' have problems too
A sample of 33 companies was randomly selected and data collected on the average annual bonus, turnover rate (%), and trust index (measured on a scale of 0 — 100). Using the output below, and a significance level of α = .01, we can conclude that Dependent Variable is Turnover Rate Predictor Coef SE Coef T P Constant 12.1005 0.7826 15.46 0.000 Trust Index -0.07149 0.01966 -3.64 0.001 Average Bonus -0.0007216 0.0001481 -4.87 0.000 S = 1.49746 R-Sq = 79.6% R-Sq(adj) = 78.3% Analysis of Variance Source DF SS MS Regression 2 262.73 131.36 Residual Error 30 67.27 2.24 Total 32 330.00
The multiple regression model is significant overall
Coefficient
The number that tells you how much one variable effects the dependent variable
Demand is inelastic if:
The price elasticity of demand is less than 1
profit
Total Revenue - Total Cost
During the past 20 years the prices of prescription drugs, relative to the prices of other goods, have risen, yet Americans buy more prescription drugs than ever. This might be because
With higher incomes and more older Americans, the demand curve for prescription drugs has shifted rightward
Assume the supply function for good X can be written as Qs=-100+27Px-5Py-1.8W, where Px=the price of X, Py=the price of Y, and W= Wage index for workers in industry X. According to this equation
X and Y are substitutes
Why would you use Cross price elasticity
You would use this to prove what goods are substitutes, and what goods are compliments. Coefficient for P2 in your regression results. -Ecp > 0 = substitutes -Ecp < 0 = complements -Ecp = 0 = not related
Perfect multi-collinearity
Your variable will get dropped in excel or your model will not run at all * fix: drop duplicate variable
demand
a linear relationship between price and quantity demanded
when %change in QD > %change in P, E > 1
demand = elastic
when %change in QD < %change in P, E < 1
demand = inelastic
A change in the price of a good
does not shift the goods demand curve but does cause a movement along it
When supply decreases and demand does not change, the equilibrium quantity _________ and the equilibrium price ___________.
decreases, rises
If the price of a video download is below equilibrium price, the quantity supplied is _________ than the quantity demanded.
less
correlation matrix finds
multicollinearity
elasticity
price elasticity of demand (will always be negative, so we report in terms of absolute value)
one indicator of speed of adjustment is
elasticity
Which of the following leads to a movement along the demand curve for spinach but does not shift the demand curve for spinach?
A rise in the price of spinach
Multi-coliniarity
A situation where two or more variables in a model move together so much that they distort the results for your model
Regression
A tool to find relationships between 1 primary variable and other variables. primary variable for demand = quantity demanded, "y" variable in excel. price will always be one of the X variables. * in doing this, it tries to put one line that minimizes the distances between each observation and the line representing the relationship
The demand for a good is elastic if
An increase in its price results in a decrease in total revenue
The table shows the demand and supply schedules for jeans
At $40 a pair, there is a shortage of jeans and the price will rise.
Incremental decision making
Making small changes to lower the cost of a particular decision. (also called marginal decision making)
Assume the demand and supply functions for good X can be written as Qd = 1000 -40Px Qs = -200 +20Px
Price = $20 Equilibrium quantity = 200
People buy more of good 1 when the price of good 2 rises. These goods are
Substitutes
when E = 1
TR is maximized
Correlation Matrix
The primary test for determining serial correlation in a model
Durbin Watson (DW) Stat
The primary test for determining serial correlation in a model
Data Analysis
The tool-pack in excel you use to run regressions and other tools
When a market is in equilibrium:
There is no shortage and no surplus at the equilibrium price
Assume the demand function for good X can be written as Qd = 80-3Px-2Py+10I where Px= the price of X, and Py = the price of good Y, and I = consumer income
This equation implies that X and Y are complements
Goal of regression
To minimize error between regression and observation
A sample of 33 companies was randomly selected and data collected on the average annual bonus, turnover rate (%), and trust index (measured on a scale of 0 — 100). According to the output is shown below, what is the estimated multiple regression model? Dependent Variable is Turnover Rate Predictor Coef SE Coef T P Constant 12.1005 0.7826 15.46 0.000 Trust Index -0.07149 0.01966 -3.64 0.001 Average Bonus -0.0007216 0.0001481 -4.87 0.000
Turnover Rate = 12.1005 - 0.07149 Trust Index - 0.0007216 Average Bonus
To find relationships in a big set of data
We use regression
If shoes rise in price, the demand curve for shoes ___________ and the quantity of shoes demanded _____________.
does not shift; decreases
quantity demanded is going ________ when we are ______________
down; spending
markets are
self fufilling
durband watson finds
serial-correlation
"supply" is best defined as the relationship between
the price of a good or service and the quantity supplied by producers at each price during a period of time.
when %change in QD = %change in P, E = 1
unit elastic
F-score
what we use to determine which model has the best fit. judges overall quality of the model. if F=0, something is very important in your model -use F score to compare one model with another - Higher f = better fit - when p-value = 0, thats a good thing