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1. Econ 415 Project



Select one time series of real data. The series can be selected from the published data (http://research.stlouisfed.org/fred2/). The data series must comprise at least 30 observations.



Make a time plot of the data and describe the main features of the series.
Transform your series if necessary. Explain which transformation was used and why? If no transformation was used, explain why not.
Decompose the transformed series.
Produce forecasts of the series using an exponential smoothing method/ARIMA model. (holt, holt winter, holt winter additive, multi….etc, use all the models and compare them, which is the best. By look into some critical values, such as ljung-box, MAD, MAPE, BIC….etc)
Diagnostics
Forecasts and prediction intervals


Explain carefully what you have done and why you have done it. You should also compare you results with those obtained using an ARIMA model/exponential smoothing method. Which method do you think gives the better forecasts?



You should write as if your report is to a client who is interested in forecasts of your data. You may assume that your client is familiar with the material covered in the text.



You will be graded on the sophistication of your techniques, as well as on the thoughtfulness and clarity of your discussion and the communication of your results.



The report should be from 10-15 pages including figures and tables.



You will also be required to give a presentation of your analysis in class.





2. ECON 414 (ECONOMETRICS)
COMPUTER PROJECT


PART I: Use the data in the file andy.dat consisting of data on hamburger franchises in 75 cities from Big Andy''s Burger Barn. The data are available at the website for the text: http://www.principlesofeconometrics.com/ Simply click Principles of Econometrics, 4th Edition and then click Ascii files (or Excel Spreadsheets) and Data Definition files. The files are in *.Zip format and you will need to unzip/extract them. After extracting the files, look for the files: (i) andy and (ii) andy.def. You will use these files for econometric analysis in the following problem.



Set up the model



ln(Si)=b1 + b2ln(Ai) + ei,



where



Si = Monthly sales revenue ($1000s) for the i-th firm

Ai = Expenditure on advertising ($1000s) for the i-th firm



(a) Interpret the estimates of slope and intercept.

(b) How well did the model fit to the data? Use any tests and measures presented in class.

(c) Perform any test for heteroscedasticity in your data.







andy.def File: The data definition file is reproduced below.



sales price advert



obs: 75 a sample of hamburger franchises in 75 cities from Big Andy''s Burger Barn.



sales = S Monthly sales revenue ($1000s)

price = P A price index for all products sold in a given month.

advert = A Expenditure on advertising ($1000s)





Data source: Courtesy of hamburger franchise, called Big Andy''s Burger Barn





Variable | Obs Mean Std. Dev. Min Max

-------------+--------------------------------------------------------

sales | 75 77.37467 6.488537 62.4 91.2

price | 75 5.6872 .518432 4.83 6.49

advert | 75 1.844 .8316769 .5 3.1

















PART II: Can a corporation''s annual profit be predicted from information about the company''s CEO? Forbes (May 1999) presented data (shown in TABLE 2) on company profit (y) in (millions of dollars), CEO''s annual income (x1) (in thousands of dollars) and percentage of the company''s stock owned by the CEO (x2). Use the data in the TABLE below and answer the following questions.



(a) Fit a multiple regression model of y on x1 and x2. Fit two simple linear regressions: (I) y on x1; (II) y on x2. Compare the results of multiple regression analysis with each of simple linear regressions.

Rank the models in terms of usefulness and briefly comment on their performance. Use all of the tests and measures of usefulness discussed in class.

(b) Do you detect any signs of multicollinearity?

(c) Use the printout to test the following hypotheses using a significance level of 5%: (I) increasing the CEO''s annual income (other things constant) will increase the company profit; (II) increasing the percentage of company stock owned by the CEO will increase the company profit.



TABLE: Company profit (y), CEO''s annual income (x1), and the company stock owned by the CEO (x2)



Company
Profit (y)
CEO''s income (x1)
% of the company stock owned by the CEO (x2)

Gap
824.5
3743
1.71

Intel
6068.0
52598
.13

Gateway 2000
346.4
855
43.93

HJ Heinz
746.9
2916
1.63

Conseco
630.7
124579
3.64

Citicorp
5807.0
6200
.22

Cisco Systems
1362.3
560
.06

General Electric
9296.0
40626
.03

America Online
254.0
26917
.54

Computer Associates
570.0
10614
3.79

Lockheed Martin
1001.0
2533
.01

Bear Stearns
538.6
23215
3.44





Source: "Compensation Fit for a King", Forbes, May 1999.





Please let me know your best price, and you must be 100% confident that you can finish the job very nice. They are very important projects for my study.

I wish you can finish them in a week, later deadline can be discuss, it all depends on price you offer as well. Thank you.

Microeconomics, Economics

  • Category:- Microeconomics
  • Reference No.:- M9503541

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