Reference no: EM13760926

Questions:

The following graph shows the cost curves for aPerfectly competitive firm. Identify the shutdownpoint, the breakeven point, and the firm's short runsupply curve.

 GRAPHS is attached as a photo file

Technical Questions:

Draw graphs showing a perfectly competitive firm and industry in long-run equilibrium.

a. How do you know that the industry is in long run equilibrium?

b. Suppose that there is an increase in demand for this product. Show and explain the short-runadjustment process for both the firm and the industry.

c. Show and explain the long-run adjustment process for both the firm and the industry. Whatwill happen to the number of firms in the new long-run equilibrium?

Application Questions

The following facts characterize the furniture industry in the United States:

a. The industry has been very fragmented, so that few companies have the financial backing to make heavy investments in new technology and equipment.

b. In 1998, only three U.S. furniture manufacturers had annual sales exceeding $1 billion. These firms accounted for only 20 percent of the market share, with the remainder split among 1,000 other manufacturers.

c. Capital spending at one manufacturer, Furniture Brands, was only 2.2 percent ofsales compared with 6.6 percent at FordMotor Company. Outdated, labor-intensiveproduction techniques were still being usedby many firms.

d. Furniture manufacturing involves a huge number of options to satisfy consumer preferences,but this extensive set of choices slows productionand raises costs.

e. Small competitors can enter the industry because large manufacturers have not built upany overwhelming advantage in efficiency.

f. The American Furniture Manufacturers Association has prepared a public relations campaign to "encourage consumers to part with more of their disposable income on furniture."

g. In fall 2003, a group of 28 U.S. furniture manufacturers asked the U.S. government to impose antidumping trade duties on Chinese-made bedroom furniture, alleging unfair pricing.

h. The globalization of the furniture industry since the 1980s has resulted from technological innovations, governmental implementation of economic development strategies and regulatory regimes that favor global investment and trade, and the emergence of furniture manufacturers and retailers with a capacity to develop global production and distribution networks. The development of global production networks using Chinese subcontractors has accelerated globalization in recent years.

Discuss how these facts are consistent with the model of perfect competition.

Application Questions

5. In a perfectly competitive industry, the market price is $25. A firm is currently producing 10,000units of output, its average total cost is $28, its marginal cost is $20, and its average variable costis $20. Given these facts, explain whether the following statements are true or false:

a. The firm is currently producing at the minimum average variable cost.

b. The firm should produce more output to maximize its profit.

c. Average total cost will be less than $28 at the level of output that maximizes the firm's profit.

Technical Questions 3

3. Suppose the demand curve for a monopolist is QD = 500 - P, and the marginal revenue functionis MR = 500 - 2Q. The monopolist has a constant marginal and average total cost of $50 per unit.

a. Find the monopolist's profit-maximizing output and price.

b. Calculate the monopolist's profit.

c. What is the Lerner Index for this industry?

Technical Questions 7

7. The following graph shows a firm in a monopolistically competitive industry.

a. Show the firm's short-run profit-maximizing quantity and price. Is the firm making a profit?

b. Carefully explain what will happen in the industry over time, and draw a graph of a monopolistically competitive firm in long-run equilibrium.

Follow these instructions for completing and submitting your assignment:

1. Place all  answers, both numerical and written, in a single excel spreadsheet.
2. Place each  problem into a separate tab or sheet in an Excel file.
3. Place labels on  spreadsheet inputs and outputs, and use the yellow highlighter on the top  menu bar to highlight your final answer.
4. If the question  incorporates graphs, you must replicate the graph on your spreadsheet  file.
5. Do not submit  Word files or multiple files for a single assignment.

Farnham, P. G. (2014). Economics for Managers (3rd ed.). Upper Saddle River, NJ: Pearson.

Running Regression on Excel

Doing regression analysis on Excel is a two-step process. Complete the following:

1. Install the Analysis Tool-Pak on your PC.

2. Run the regression analysis.

The Analysis Tool-Pak is an Excel add-in. The Analysis Tool-Pak is part of Excel, but is not installed in the typical initial installation.

The directions on this handout are based on Excel 2007. If you have a different version of Excel, the steps below will be the same, but their location on the menu may be somewhat different. Consult the "Help" function for specifics about your version of Excel.

1. To install the Analysis Tool-Pak on your PC:
   1. Click  on the "Office" button (the yellow circle on the upper left corner of the  screen), then click the "Excel Options" button at the bottom.
   2. Click  "Add-Ins" on the left panel.
   3. Select  "Excel Add-Ins" from the dropdown list at the bottom.Then click "Go."
   4. Select  the "Analysis Tool-Pak" check box in the "Add-Ins" dialog box, and then  click "OK."
   5. If an  alert appears that asks if you want to install the Add-In, click yes.
2. Enter  your data and run the regression analysis.
3. Enter  the data to be used for your problem.Data must be entered by columns, with  the independent variables (x-variables) in adjacent columns.
4. The dependent variable can be entered in ether the left or right column of your spreadsheet.For purposes of running the example in this hando ut, enter the data below as shown

    

   Sample Problem for Regression Handout
   y	xl	x2
   2	3	7
   4	4	11
   6	6	13
   8	8	19
   10	9	23

5. Click  on "Data" (top menu bar), then "Data Analysis," then "Regression," and  then "OK."
6. Place  the cursor in the "Input Y Range" box.  Highlight the range of cellson the spreadsheet that contain the  y-variable.
7. Place  the cursor in the "Input X Range" box.  Highlight the range of cells on the spreadsheet that contain the  x-variables. (Recall that they  should be entered in adjacent rows or columns.)
8. Click  on the "Output Range" button. Place  the cursor in a blank cell on the spreadsheet where no spreadsheet content  currently appears (either below or to the right of the cell). (Cell A10 should work for this example.) Click on that cell, and the cell address  will appear in the box next to Output Range. This cell represents the upper-left  corner of the location where your regression output will appear.
9. Cl ick "OK" on the regression dialog box. The regression output will app ear. You may need to widen the column widths on your spreadsheet to get the entire variable label to appear.

   Sample Problem for Regression Handout

    

   x/                 x2

   2                 3                  7

   4                 4                 11

   6                 6                 13

   8                 8                 19

   10                 9                 23

   SUMMARY OUTPUT

   Regression Statistics

   Multiple R            0.995642681

   R Square                   0.991304348

   Adjusted R Square      0.982608696

   Standard Error         0.417028828

   Observations                  S

   ANOVA

   	di	SSMS 2     39.65217391 19.82608696 2     0.347826087 0.173913043 4                 40	F Significance F
   Regression Residual Total			114 0.008695652

   Coefficients     Standard Error   t Stat          P-value    Lower 95%

   -1.347826087    0.525799418 -2.563384515 0.124413 -3.61015839  0.914506; 0.695652174     0.43910891 1.584236069 0.253996 -1.193680978  2.584985: 0.217391304     0.175266473 1.240347346 0.34062 -0.536719463  0.971502(

10. To help you locate important results, the following are highlighted in yellow.(These are discussed in the textbook.)They are not highlighted in the default output of Excel.
    
    1. Intercept  and variable coefficients
    2. Standard  error of the intercept and of each coefficient
    3. T-statistic  of the intercept and of each coefficient
    4. The  probability of obtaining a t-statistic of this value, given that the null  hypothesis (the intercept or variable coefficient) is zero.(The null  hypothesis holds.)
    5. The  95% confidence interval for the variable coefficient and the intercept.
    6. The  adjusted R-square value
    7. The  F-statistic and its significance