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