Suppose Two Retail Establishments, Talbots a High End Women S Store - and Talbot Kids

Economics 401 Hartmann

Spring 2011 Worksheet 2

Announcements:

·  If you need to see me outside of office hours either speak to me after class, stop by my office or email me to set up an appointment.

·  Same homework groups and rules as for the first assignment.

·  For this assignment, you will run some regressions in Excel. Direction on how to estimate regression equations in Excel have been attached to the assignment. Also, an Excel file (hwk2_dat.xls) containing the data has been posted on class webpage under “Materials”. Data has been saved on different worksheets of the file.

1. Suppose two retail establishments, Talbots – a high end women’s clothing store - and Talbot Kids – a high end kids’ store-, want to enter the Twin cities market and open one store each in the Twin Cities. (Assume they do not currently have stores in the Twin Cities.) Both establishments are owned by the same parent company, but operate independently of each other (i.e., will chose their store locations independently of each other). Assume each store has narrowed the choices down to three locations: Edina, Mall of America, and downtown Minneapolis. The Edina location is attractive because of the residents’ high medium income. The Mall of America attracts shoppers with families because of the amusement park, the movie theater, and other kid attractions. Finally, the downtown location is near where many professional women work.

a)  Solve for the Nash Equilibrium(s) and report them in this format:

e.g., Talbots locates in X with a payoff XX, while Talbots Kids locates in Y

with a payoff of YY.

b)  Now assume the stores make their location decisions sequentially with Talbots choosing first and Talbots Kids second. Solve for the Nash Equilibrium(s); report them in same manner as in (a).

2. Asymmetric Information: Adverse selection/moral hazard

In the early 1990s, Sears was charged with massive fraud in its auto repair centers. The accusation was that mechanics were convincing customers that they need expensive repairs when, in fact, they were unnecessary. Sears entered into a multimillion-dollar agreement to settle the case out of court. In addition, in a bid to win back business it had lost during the highly publicized case, Sears announced that its sales staff would no longer be paid on commission.

a.  Were the abuses by the mechanics a result of adverse selection, moral hazard, or both? Why did you come to this conclusion?

b.  What should Sears do to correct or at least reduce the asymmetric information problems? Provide one example and explain why and how this addresses an information problem identified in part (a).

Aside: At the end of the semester, we will discuss the disadvantages of ending the commission system.

3. An internet company that sells clothing exclusively over the internet has decided to do some test marketing. When customers inquire about a particular article of clothing, for which it has been charging $50, for a period of 6 weeks, it randomly quotes prices of $48, $49, $40, $51, and $52. (It quotes each of these five prices an equal number of times. You can assume that the firm has ways to make sure that once it quotes one of these prices to a customer, it continues to quote that price to the customer if he or she returns to the firm’s website. Actually, this is a bit of a problem in real life today, although with cookies, we are approaching the day we will be able to do this.) Over the six week period starting in mid-January, the firm records the sales data in Table 1.

a)  Using Ordinary Least Squares, estimate the demand function facing this firm. You must estimate this using Excel. (Directions are attached.)

Table 1: Sales per week per price quoted

Turn in the Excel regression output. Make sure you define all variables used.

b)  Name at least two other factors that would influence customers’ demand that you would have liked to have data on when constructing the demand curve. Your answer should not be vague (e.g. taste and preferences). Instead, provide a variable that is correlated with consumers’ taste and preferences and provide an explanation on why this variable is expected to influence demand.

4. Suppose an appliance manufacturer is doing a regression analysis, using quarterly time series data, of the factors affecting its sales of appliances. A regression equation was estimated between appliance sales (in dollars) as the dependent variable and disposable personal income and retail sales of durable goods as the independent variables. Although R2 statistic is high, the manufacturer also suspects that serious multicollinearity exists between the two independent variables.

a.  In what ways does the presence of this mutlicollinearity affect the results of the regression analysis?

b.  Under what conditions might the presence of multicollinearity cause problems in the use of this regression equation in designing a marketing plan for appliance sales?

5. Many states offer drivers an opportunity to express their individuality with their automobile license plates. For the privilege of having your license plate imprinted with your own custom message -- such as Pisces, AG of 81, Plibit, My Benz, Van Go -- drivers normally pay a small premium to the state.

In 1965 when Texas introduced vanity license plates, they could be acquired for a mere $10. By 1985 the price had jumped to $25. At this price, 154,000 Texans invested in "their own automotive identity." As Texas entered the oil price recession of the mid-eighties, legislative leaders frantically scrambled for new sources of revenue. In 1986, the Texas legislature tripled the price to $75. Sales tumbled to only 51,000 custom plates. Faced with this sudden decline in demand, the legislature cut the price to $40 for 1987. The Texas legislators learned a quick lesson in the concept of price elasticity.

a.  Compute the price elasticity of demand for license plates between $25 and $75.

b.  Legislators raised price hoping to generate a significant increase in revenue for the government. Why were their expectations not realized; what error in judgment did they make? Think about a more in-depth encompassing answer.

6. In October 2010, the manager of Rockford Enterprises wanted to determine if the company was operating in the economies or diseconomies region of the average total cost curve. The capital stock at Rockford has remained unchanged since the second quarter of 2008. The manager collected quarterly observations on cost and output over this period and the resulting data were as follows:

a.  Estimate the (nominal) average total cost curve using Excel. You can get the functional form from homework #1 or the textbook. But, for an intellectual exercise, ask yourself what functional form would lead to a U-shaped cost curve and then check if you were correct. (See attached directions to estimate regressions using Excel.)

b.  Are each of the coefficient(s) significantly different from zero? Specify rule you use to make this assessment.

c.  If current output is 300, is the company producing in the economies or diseconomies region? Provide evidence. (You must use your regression output to obtain answer.)

d.  Re-estimate (a-c) using the implicit price deflator to adjust for inflation (i.e., estimate real ATC in terms of the second quarter of 2010 dollars). (See “Real v Nominal” link on the class website for an ECON 251 discussion on how to use the CPI or GDP implicit price deflator to adjust for inflation.)

e.  Suppose you re-estimate (a-c), but now you estimate real ATC in terms of base dollars). Would you expect the results to change from (d)? Why or why not? Explain.

Turn in the Excel output for regressions in (a-d). Make sure you define all variables

used.

Aside: Why did I choose to deflate the numbers using the implicit price deflator and not CPI for this problem? Answer not to be turned into me.

7.  The maker of a leading brand of low-calorie microwaveable food estimated the following demand equation for its product using data from 26 supermarkets around the country for the month of April:

Q = -5,200 – 42P + 20PX + 5.2I + .2A + .25M

(2.002) (2.4) (3.23) (2.08) (2.22) (.21)

T statistics are shown in parentheses.

Assume the following values for the independent variables:

Q = quantity sold per month

P = Price of product (in cents) = 500

PX = Price of leading competitor’s product (in cents) = 600

I = per capita income of the primary metropolitan statistical area (PMSA) in which the

supermarket is located (in dollars) = 5,500

A = monthly advertising expenditure (in dollars) = 10,000

M = number of microwave ovens sold in April in the PMSA in which the supermarket

is located = 5,000

Using this above information, answer the following questions:

a.  Compute elasticities for each variable. Show work.

b.  Should the company be concerned about the impact of a recession on its sales? Explain.

c.  Should the firm cut its price to increase its market share? Explain.

d.  Provide a reason on why you think the number of microwaves (as defined above) is not a statistically significant predictor of low-calorie microwaveable food sales.

8.  You just opened up a new grocery store. Every item you carry is generic (generic beer, generic bread, generic chicken, etc). You recently read in the Wall Street Journal that the price of recreation is expected to increase by 20%. How will this affect your store’s sales of generic food products? Assume the cross price elasticity of demand for generic food with respect to the price of recreation is 0.15. Show work.

(Source: M. Baye, D.W. Jansen, and W. Lee. (1992) “Advertising Effects in Complete Demand Systems.” Applied Economics, pg. 1087-96.)