I. The Fortune 500, 1999 : Fifty Firms Ranked by RevenuesOct. 27, 2004 LAB #5 ECON 240A-1 L. PhillipsExploratory Data Analysis, Scatterplots, and Regression I. The Fortune 500, 1999 : Fifty Firms Ranked by RevenuesSource: http://www. fortune.com/fortune/Data for these fifty firms includes, in addition to revenues in millions of dollars, firm name, firm industry, profits, assets, stockholders’ equity, market value (all of the preceding quantitative variables in millions of dollars), earnings per share, total return to investors in 1999 in percent, number of employees.A. Assets Versus Revenue1.Select these two variables, assets as the dependent variable and revenue as the explanatory variable, and insert an xy chart. Note that the data is fan shaped when the data is linear in scale. 2. Take the natural logarithms of these two variables and insert an xy chart. Explore the data points at the top of the chart. For example, the data point with the highest value of assets is Citigroup in the diversified financials industry. The point to its left, with the second highest value of assets is Bank of America. If you select the data points, and then double click on the point of interest and go to the format menu, there is a format data series box. Select the“data labels” tab, and select the “show value” button. From the value you can identify the company and then select the value and type in the company name.The points along the top edge tend to be in the financial sector from industriessuch as (1) commercial banks, (2) diversified financials, (3) insurance, and securities. To check this, select the company name and industry columns and copy them to two new columns. Then select the industry column, go to the “data” menu and choose sort. Sort by column x and expand the selection to next sort by column w. Under options choose normal and case sensitive. Note there are 3 commercial banks, 3 diversified financials, 5 insurance companies,and 2 securities firms. I selected and labeled the appropriate data points, and the results are displayed in Figure 1. State Farm and Allstate look like they may belong to a different set, leaving 11 firms. I chose these 11 firms to run the regression.Oct. 27, 2004 LAB #5 ECON 240A-2 L. PhillipsExploratory Data Analysis, Scatterplots, and Regression Figure 1: Log of Assets Versus Log of Revenue, 50 Fortune 500 FirmsLooking along the lower edge, I identified the firms as shown in Figure 2. Most of these were wholesalers, specialty retailers, food and drug store, or general merchandisers. The exceptions were in the upper right hand lower edge, General Motors and Exxon Mobil. From this graphical analysis I formed the following hypothesis. With the variables in log-log form, the relationship had a constant slope, but the intercept varied by industry:Ln Assets(j) = a(k) + b ln Revenue(j),where j indexes firm and k indexes industry. Thus the regression shifts up and down depending on the industry. There are 24 different industries among the 50 firms, counting the different insurance companies together, which may not be appropriate. The industries and number of firms in each are shown in Table 1. Some grouping may be necessary to implement the regression analysis, but we will start with all 24 industries.Fortune 500, 1999: Assets Vs. Revenue, In LogsGeneral ElectricCitigroupBank of AmericaFannie MayChase ManhattenMorgan StanleyMerrill LynchPrudential Bank OneAmerican InternationalTIAA-CREFState FarmAllstate100010000100000100000010000 100000 1000000Log RevenueLog AssetsOct. 27, 2004 LAB #5 ECON 240A-3 L. PhillipsExploratory Data Analysis, Scatterplots, and Regression Figure 2: Log of Assets Vs. Log of RevenuTable 1: Industry and Number of FirmsIndustry # of FirmsAerospace 1Chemicals 1Commercial Banks 3Computers, Office Equipment 3Diversified Financials 3Electronics, Electrical Equipment 1Entertainment 1Food and Drug Stores 3General Merchandisers 5Health Care 1Insurance 5Mail, Package, Freight Delivery 1Motor Vehicles and Parts 2Network Communications 1Petroleum Refining 3Pharmaceuticals 2Pipelines 1Securities 2Semiconductors 1Soaps, Cosmetics 1Specialty Retailers 2Telecommunications 4Tobacco 1Fortune 500, 1999: Assets Vs. Revenue, In LogsGeneral MotorsExxon MobilWal-MartKrogerIngram MicroCostco WholesaleMcKesson HBOCGeneral ElectricCitigroupBank of AmericaFannie MayChase ManhattenMorgan StanleyMerrill LynchPrudential Bank OneAmerican InternationalTIAA-CREFState FarmAllstate100010000100000100000010000 100000 1000000Log RevenueLog AssetsOct. 27, 2004 LAB #5 ECON 240A-4 L. PhillipsExploratory Data Analysis, Scatterplots, and Regression Wholesalers 2II. Regression with EviewsOpen EViews file Fortune 50.wf1. Go to the quick menu, choose estimate equation, and specify:lnassets aero banks chem computers divfinanc electronics entertain fooddrug genmerch health insurance mail netcom petrol pharma pipelines securities semicon soaps specretail telecom tobac vehicles wholesale lnsalesand hit OK. The goodness of fit R2 =0.96 and the elasticity of assets to sales is 0.78 and significant. Under View, look at actual, fitted, residual:graph. The fit looks pretty good over the 50 observations. Of course for the industries with only one firm there are no degrees of freedom. Note that the group we discovered using graphical exploratory analysis all have a large intercept in the range from 3.71 to 4.77. These intercepts are all significantly different from zero at the 5% level. This group includes commercial banks, diversified financials, health care (Aetna, which may be similar to the 5 other insurance companies), insurance, and securities.We can test whether the coefficients for food and drug companies, general merchandisers, and specialty retailers, are equal. Under View, look at representations, and notice that the coefficients for these four industries are c(8), c(9), and c(20),. Under View, go to coefficient tests/Wald-coefficient restrictions. In the box type in c(8)=c(9)=c(20). This restriction is not significant at the 5% level so we could group these observations into one industry, trade. To do this, go to the workfile window and select the Genr command in the menu bar. Enter the equation:trade= fooddrug+genmerch+specretailReestimate the equation substituting trade for its three components. III. Orientation to EviewsHelp Menu: About Eviews: creditsHelp Menu: Read MeHelp Menu: Eviews Help Topics/contents tab1. Eviews Basics2. Statistical Views and Procedures3.
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