Economics 4310

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Economics 4310

State and Local Public Finance

Written Assignment #1

Due: March 9, 2018

 

On the first page of your assignment, put your name and the first three lines in the heading above. Use a 12 point font size and standard margins for the paper. Indent the first word of every paragraph. You may use either single- or double-spacing. There is no word or page limit, but conciseness is highly valued.

 

1. Read “An Essay on Fiscal Federalism,” by Wallace Oats. (A link to the article can be found on Carmen.)

2. Prepare a detailed outline of the article. (A link to an example of a detailed outline can be found on Carmen.)

3. Write in your own words a brief one paragraph summary of the paper.

 

This assignment will be worth 25 points. You will be graded on the following criteria: 1) following instructions, 2) grammar, 3) citations, 4) clarity, 5) critical thinking. Each criterion represents 20% of your total score.

 

Criterion 100% 80% 60% 40% 20%
Instructions Followed all instructions Followed almost all instructions Followed most instructions Followed some instructions Did not follow instructions
Grammar 0-2 errors 3-4 errors 5-6 errors 7-8 errors 9 or more errors
Citations All information correctly cited in the MLA format All information correctly cited in the wrong format 1-3 missing citations or missing works cited page, in the MLA format 1-3 missing citations or missing works cited page, wrong format 4 or more missing citations
Clarity Clearly written and on topic Mostly clear and on topic Somewhat clear or tendencies to get off topic Not clear, but mostly on topic Not clear and off topic
Critical Thinking Demonstrates a clear understanding of the concepts Demonstrates a good understanding of the concepts Demonstrates a moderate understanding of the concepts Demonstrates a familiarity with the concepts Does not demonstrate an understanding of the concepts

Synthesis Of Statistical Findings Derived From ANOVA

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Submit a synthesis of statistical findings derived from ANOVA that follows the Week 4 Assignment Template. Your paper must include the following:

  • A description and justification for using the one-way ANOVA
  • A properly formatted research question
  • A properly formatted H0(null) and H1 (alternate) hypothesis
  • An APA-formatted “Results” section for the one-way ANOVA
    • Identification of the statistical test
    • Identification of independent and dependent variables, including the identification of the number of levels for the independent variable
    • Identification of data assumptions and assessment outcome
    • Inferential results in correct APA statistical notation format
    • A properly formatted box plot
  • A discussion on how you would extend the one-way ANOVA to a two-way ANOVA using the variables in the Week 4 Data File for One-way ANOVA.sav dataset.
  • Properly APA-formatted references
  • Appendix containing SPSS output (see Week 4 Assignment Exemplar)7

     

    DDBA 8307 Week 4 Assignment Exemplar – One-Way ANOVA[footnoteRef:1] [1: Footnotes within the narrative are depicted by bold yellow superscripts; the footnotes will not be in your final submission.]

     

     

     

     

    John Doe[footnoteRef:2] [2: Type your name here.]

     

    DDBA 8307-6[footnoteRef:3] [3: Type in DDBA section number (e.g. DDBA 8307 – 6). ]

     

    1

     

    Dr. Jane Doe[footnoteRef:4] [4: Enter faculty name here.]

     

     

    One-Way Analysis of Variance (ANOVA)

     

    You will describe and defend using the one-way ANOVA for your analysis. Use at least two outside resources—that is, resources not provided in the course resources, readings, etc. These citations will be presented in the References section. This exercise will give you practice for addressing Rubric Item 2.13b, which states, “Describes and defends, in detail, the statistical analyses that the student will conduct….” This section should be no more than two paragraphs.

    Research Question[footnoteRef:5] [5: Quantitative research questions can be presented in a variety of formats; however, you will be safe using this format. ]

     

    Is there a statistically significant difference in weekly widgets produced among day shift, night shift, and swing shift employees?

    Hypotheses[footnoteRef:6] [6: Two hypotheses, the null (H0) and alternative (H1), are to be stated for each research question. See p. 39 in the Research Handbook for more detailed examples. See more on hypotheses at http://www.socialresearchmethods.net/kb/hypothes.php ]

     

    Null Hypothesis (H0): There is not a statistically significant difference in weekly widgets produced among day shift, night shift, and swing shift employees.

    Alternative Hypothesis (H1): There is a statistically significant difference in weekly widgets produced among day shift, night shift, and swing shift employees.

     

     

     

     

     

     

     

    Results[footnoteRef:7] [7: DBA Rubric Item 3.2d: Reports inferential statistical analyses results, organized by research question, in proper APA statistical notation/format. Includes the alpha level chosen for the test, test value, p (significance level) values, effect size, degrees of freedom, confidence intervals (when appropriate), etc. ]

     

    In this subheading, I will present descriptive statistics, discuss testing of the assumptions, present inferential statistic results, and conclude with a concise summary.

    Descriptive Statistics

    A total of 435 employees participated in the study. The assumption of equality variances (Levene’s test, p = .475) was evaluated with no violation noted. Table 1 contains descriptive statistics for the study variables. Figure 1 depicts a box plot.

    Table 1

    Work Shift M SD
    Day Shift 21.36 4.55
    Night Shift 22.10 4.15
    Swing Shift 22.96 4.49

     

    Figure 1. Box-plot comparing number of weekly widgets produced by work shift.

    Inferential Results[footnoteRef:8] [8: All values required for the APA write-up are derived from the SPSS output.]

    A one-way ANOVA, a = .05, was conducted to assess whether there was a statistically significant difference in weekly widgets produced among day shift, night shift[footnoteRef:9], and swing shift employees. The independent variable was work shift, with three levels: day shift, night shift, and swing shift. The dependent variable was the number of weekly widgets produced. The assumption of equality variances (Levene’s statistic = .746, p = .475)[footnoteRef:10] was evaluated with no violation noted. The results were significant,[footnoteRef:11] F(2, 432) = 4.641, p =.01[footnoteRef:12]. The measure of effect size measured by η2 was .02[footnoteRef:13], indicating that 2% of the variance in widgets produced is accounted for by work shift. Post hoc analysis[footnoteRef:14], using Tukey’s HSD test, indicated that the mean number of widgets for the day shift (M = 21.36, SD = 4.55) was significantly different from the swing shift (M = 22.96, SD = 4.49). The night shift (M = 22.10, SD = 4.15) did not differ significantly from the day shift or swing shift. Table 2 depicts the ANOVA summary. Figure 1 depicts a box-plot comparing weekly numbers of widgets produced by work shift. [9: Note the one-way ANOVA can assess group difference between more than two groups, unlike the independent-samples t-test, which is used when there are only two groups being compared.] [10: Values derived from SPSS output.] [11: Remember, your results might not be significant; this would be evidenced by p > .05. ] [12: This is the correct format for reporting ANOVA results. However, it is important to understand the parameters. F indicates an ANOVA test was conducted; (2, 432) = the degrees of freedom for between (df = 2) and within groups (df = 432). respectively; (df) are an indication of the number of groups being compared and the sample size. The df (2) is the number of groups minus one, in this case 3 – 1 = 2, whereas (df) = 432 can give an indication of the sample size—the total sample should be very close to this value; 9.1 = the calculated F statistic; p = .01 indicated there was a significant difference among the three groups, as p < .05. Remember, p values ≤ .05 are statistically significant.] [13: η2 is calculated as follows: SS between groups/Total sum of squares (derived from SPSS output—see Table 2).] [14: Post hoc (after the fact) analysis must be conducted when there is a statistically significant (p ≤. 05) omnibus finding. The post hoc test will identify where the specific pairwise differences are (see “multiple comparisons” table in SPSS output). ]

    Table 2

     

    ANOVA Summary Table for the Impact of Work Shift on Widgets Produced

    Source df SS MS F η2 p
    Between-group 2 179.07 89.54 4.461 0.00 .01
    Within-group 432 8,333.95 19.23      
    Total 434 8,513.02        

     

    Extend One-Way ANOVA to Two-Way ANOVA

    Type text here. As you are aware, quantitative DBA Doctoral Studies require the use of at least two independent variables. Discuss briefly how you could extend the one-way ANOVA to a two-way ANOVA. Identify and discuss a second hypothetical independent variable and the number of levels to the second independent variable.

     

     

     

    2

     

     

    References

     

    Type references here in proper APA format.

     

    Appendix – One-Way ANOVA SPSS Output[footnoteRef:15] [15: You will copy and paste the appropriate SPSS output into the Assignment. See the document titled “Copying and Pasting SPSS Output Into Word,” located in the Week 2 Resources. ]

     

     

     

    Descriptives
    Total Optimism
      N Mean Std. Deviation Std. Error 95% Confidence Interval for Mean Minimum Maximum
              Lower Bound Upper Bound    
    Day Shift 147 21.36 4.551 .375 20.62 22.10 7 30
    Night Shift 153 22.10 4.147 .335 21.44 22.77 10 30
    Swing Shift 135 22.96 4.485 .386 22.19 23.72 8 30
    Total 435 22.12 4.429 .212 21.70 22.53 7 30

     

     

     

    Test of Homogeneity of Variances
    Total Optimism
    Levene Statistic df1 df2 Sig.
    .746 2 432 .475

     

     

     

    ANOVA
    Total Optimism
      Sum of Squares df Mean Square F Sig.
    Between Groups 179.069 2 89.535 4.641 .010
    Within Groups 8,333.951 432 19.292    
    Total 8,513.021 434      

     

     

     

     

     

    Post Hoc Tests

     

    Multiple Comparisons
    Dependent Variable: Total Optimism
    Tukey HSD
    (I) age 3 groups (J) age 3 groups Mean Difference (I-J) Std. Error Sig. 95% Confidence Interval
              Lower Bound Upper Bound
    Day Shift Night Shift -.744 .507 .308 -1.94 .45
      Swing Shift -1.595* .524 .007 -2.83 -.36
    Night shift Day Shift .744 .507 .308 -.45 1.94
      Swing shift -.851 .519 .230 -2.07 .37
    Swing Shift Day Shift 1.595* .524 .007 .36 2.83
      Night Shift .851 .519 .230 -.37 2.07
    *. The mean difference is significant at the 0.05 level.

Costs Of Production, Overall Market, And Recommendation

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IV. Examine the costs of production for Netflix.

  1. a)  Analyze the various costs a firm faces, their trends over time, and how they have impacted your firm’s profitability.
  2. b)  Apply the concepts of variable and fixed costs to your firm for informing its output decisions. For instance, analyze how different kinds of costs
    (labor, research and development, raw materials) affect the firm’s level of output.
  1. Explore the overall market of Netflix.
    1. a)  Discuss the market share of the firm and its top competitors by providing details on current percentages for each firm and describing the trend
      over time. You might consider presenting the data graphically.
    2. b)  Analyze the barriers to entry in this market to illustrate the potential for new competition and its impact on your firm’s future in the market.
    3. c)  Describe the market structure for this firm and analyze how this affects the firm’s ability to influence the market.
  1. Recommendation
  2. a)  Develop a recommendation for how the firm can manage its future production by synthesizing the data presented.
  3. b)  Suggest how the firm’s position within the market and among its competitors will allow it to take your recommended action.
  4. c)  Describe how the firm can sustain its success going forward by evaluating the findings from demand trends and price elasticity.

Data Analysis Of Nordstrom Company (Clothing)

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Part 1: Time Series analysis: discuss the revenue data similar to what I have showed in the Sear example is expected: scatter plot of revenue; linear trend; moving average; structural break. Your company revenue may not exhibit strong seasonality. For practice purpose, you are required to fit a moving average to your revenue data nevertheless.

 

First explain what the graph tells you as a manager about the trend, seasonality, and structural break in this company data. Then conduct research to find out how management actually made the decisions in the data.

Note: you do not need to provide the graphs that cannot be obtained using Excel (eg. the four figures shown in the second to last slide in the Time Series Analysis ppt file)

 

Part 2: Linear regression using Macro data:

a. Select one variable from the macro data file that you believe can be highly correlated with the revenue data.

b. Run a simple linear regression using the macro variable as the independent variable and the revenue data as the dependent variable. Report the regression results: show the excel output.

c. Note that the dates for the revenue data and macro variables do not necessarily match each other. You will need to determine the date range that has available data for all variables and drop the extra data. For example, if the date for GDP ranges from 2000 to 2015 and the revenue data ranges from 1995 to 2016. Then you would only keep data from 2000 to 2015.

d. Comment on the significance of the slope coefficient. Briefly discuss the relationship (positive or negative) between the dependent variable and the independent variable. Is the relationship expected?

e. Report R-squared and briefly comment on the fitness of the model based on your opinion.

Introduction

Note about the Data UPDATED 12/8/2017
These company data were originally obtained from Bloomberg and were captured from
company quarterly 10-K reports filed with the SEC. They have been updated using Ycharts
See https://ycharts.com/companies/(company symbol)/revenues
Ycharts can provide company information based on the stock symbol that you have beside the company name.
Each of the data observations are expressed in millions of U.S. dollars.
Some of the company Revenue information do no have corresponding Sales General and Administrative Expenses (SG&A).
If they do not appear they were not reported.
Companies Listed (75)
Primarily Internet Retailers
Amazon
eBay
Clothing and Retail
1 JC Penny
2 GAP
Sears
3 Best Buy
4 Costco
5 WalMart
6 Nordstrom
7 Target
Entertainment
8 Dish
9 NetFlix
TIVO
Insurance
10 Geico
11 Aflac
12 United Health Group
Metlife
Computers and High Tech
13 AMD
14 Intel
15 IBM
16 Oracle
Auto Parts & Care
17 Oreillys Auto Parts
18 WD-40
19 Auto Zone
Genuine Parts Company
Telecommunications
20 AT&T
21 Verizon
22 Sprint
23 Comcast
Auto Companies
24 Ford Motor Company
25 GM
26 Chrysler
27 Toyota
28 Tesla
Sporting Goods
Hibbett Sports
29 Dicks Sporting Goods
Home Improvement
30 Home Depot
31 Lowes
Airlines
32 JetBlue Airlines
33 American Airlines
34 Southwest Arilines
35 United Continental
36 Hawaii Air
37 Alaska Air
SkyWest US
Shipping
38 FedEx
39 UPS
JB Hunt
Food & Home
40 Kelloggs
41 Proctor & Gamble
General Mills
ConAgra
42 Coca Cola
Hormel Foods
Campbell Soup
43 Starbucks
44 McDonalds
Home Builders
Pulte Homes
45 KB Home
46 Lennar
Banking
47 JP Morgan Chase
48 Citi Group
CoAmerica
49 Wells Fargo
50 Bank of America
Oil & Gas
51 Exxon Mobile
52 Conoco Phillips
53 Chevron
AeroSpace
54 Boeing
Northrup Grumman
Lockheed Martin
Heavy Equipment
John Deere
Catepillar
Industry and Chemicals
55 General Electric
56 Dow Chemical
Healthcare & Pharma
57 Johnson & Johnson
58 Pfizer
Merck

Primarily Internet Retailers

Amazon (AMZN) eBay (EBAY)
Date Revenue SG&A Date Revenue SG&A
3/31/96 0.9 3/31/98 6.0
6/30/96 2.2 6/30/98 19.5 10.8
9/30/96 4.2 9/30/98 21.7 13.6
12/31/96 8.4 12/31/98 30.9 19.5
3/31/97 16.0 5.1 3/31/99 42.8 24.6
6/30/97 27.9 9.5 6/30/99 49.5 33.0
9/30/97 37.9 12.8 9/30/99 58.5 39.0
12/31/97 66.1 19.0 12/31/99 73.9 43.6
3/31/98 87.4 22.0 3/31/00 85.9 56.5
6/30/98 116.0 29.7 6/30/00 98.2 57.7
9/30/98 153.6 42.5 9/30/00 113.4 58.5
12/31/98 252.8 55.4 12/31/00 134.0 67.9
3/31/99 293.6 71.9 3/31/01 154.1 76.9
6/30/99 314.4 105.1 6/30/01 180.9 85.7
9/30/99 355.8 116.9 9/30/01 194.4 93.9
12/31/99 676.0 219.8 12/31/01 219.4 102.8
3/31/00 573.9 179.8 3/31/02 245.1 105.6
6/30/00 577.9 166.5 6/30/02 266.3 116.4
9/30/00 637.9 168.7 9/30/02 288.8 127.4
12/31/00 972.4 213.3 12/31/02 413.9 172.1
3/31/01 700.4 163.8 3/31/03 476.5 186.8
6/30/01 667.6 145.4 6/30/03 509.3 204.1
9/30/01 639.3 132.9 9/30/03 530.9 210.7
12/31/01 1115.0 165.0 12/31/03 648.4 268.8
3/31/02 847.4 153.9 3/31/04 756.2 283.3
6/30/02 805.6 157.2 6/30/04 773.4 292.1
9/30/02 851.3 134.9 9/30/04 805.9 313.0
12/31/02 1429.0 219.8 12/31/04 935.8 402.6
3/31/03 1084.0 180.4 3/31/05 1032.0 407.7
6/30/03 1100.0 179.1 6/30/05 1086.0 418.0
9/30/03 1134.0 180.1 9/30/05 1106.0 440.3
12/31/03 1946.0 234.5 12/31/05 1329.0 563.6
3/31/04 1530.0 195.3 3/31/06 1390.0 618.2
6/30/04 1387.0 191.0 6/30/06 1411.0 620.9
9/30/04 1463.0 270.0 9/30/06 1449.0 622.0
12/31/04 2541.0 104.0 12/31/06 1720.0 737.1
3/31/05 1902.0 257.0 3/31/07 1768.0 721.6
6/30/05 1753.0 240.0 6/30/07 1834.0 761.3
9/30/05 1858.0 368.0 9/30/07 1889.0 772.7
12/31/05 2977.0 47.0 12/31/07 2181.0 825.9
3/31/06 2279.0 292.0 3/31/08 2192.0 796.3
6/30/06 2139.0 295.0 6/30/08 2196.0 846.5
9/30/06 2307.0 337.0 9/30/08 2118.0 700.7
12/31/06 3986.0 466.0 12/31/08 2036.0 623.4
3/31/07 3015.0 388.0 3/31/09 2021.0 671.6
6/30/07 2886.0 384.0 6/30/09 2098.0 722.0
9/30/07 3262.0 430.0 9/30/09 2238.0 763.6
12/31/07 5672.0 668.0 12/31/09 2371.0 1147.0
3/31/08 4135.0 524.0 3/31/10 2196.0 722.9
6/30/08 4063.0 537.0 6/30/10 2215.0 740.3
9/30/08 4264.0 838.0 9/30/10 2249.0 745.3
12/31/08 6703.0 34.0 12/31/10 2495.0 839.4
3/31/09 4889.0 893.0 3/31/11 2546.0 826.0
6/30/09 4651.0 615.0 6/30/11 2760.0 1000.0
9/30/09 5449.0 698.0 9/30/11 2966.0 959.0
12/31/09 9520.0 1129.0 12/31/11 3380.0 1018.0
3/31/10 7131.0 844.0 3/31/12 3277.0 1049.0
6/30/10 6566.0 906.0 6/30/12 3398.0 1107.0
9/30/10 7560.0 1038.0 9/30/12 3404.0 1095.0
12/31/10 12950.0 1609.0 12/31/12 3993.0 1229.0
3/31/11 9857.0 1315.0 3/31/13 3748.0 1105.0
6/30/11 9913.0 1448.0 6/30/13 3877.0 1190.0
9/30/11 10880.0 1666.0 9/30/13 3892.0 1170.0
12/31/11 17430.0 2436.0 12/31/13 3260.0 441.0
3/31/12 13180.0 1975.0 3/31/14 4262.0 1270.0
6/30/12 12830.0 2125.0 6/30/14 4103.0 1333.0
9/30/12 13810.0 3242.0 9/30/14 2150.0 827.0
12/31/12 21270.0 786.0 12/31/14 2323.0 838.0
3/31/13 16070.0 2674.0 3/31/15 2061.0 821.0
6/30/13 15700.0 2798.0 6/30/15 2110.0 941.0
9/30/13 17090.0 3006.0 9/30/15 2099.0 772.0
12/31/13 25590.0 4369.0 12/31/15 2322.0 855.0
3/31/14 19740.0 3514.0 3/31/16 2137.0 747.0
6/30/14 19340.0 3702.0 6/30/16 2230.0 840.0
9/30/14 20580.0 4042.0 9/30/16 2217.0 824.0
12/31/14 29330.0 5392.0 12/31/16 2395.0 857.0
3/31/15 22720.0 4269.0 3/31/17 2217.0 807.0
6/30/15 23180.0 4493.0 6/30/17 2328.0 904.0
9/30/15 25360.0 4957.0 9/30/07 2409.0 881.0
12/31/15 35750.0 6693.0
3/31/16 29130.0 5620.0
6/30/16 30400.0 6004.0
9/30/16 32710.0 6712.0
12/31/16 43740.0 8949.0
3/31/17 35710.0 7412.0
6/30/17 37960.0 8261.0
9/30/07 43740.0 9859.0

Clothing & Retail

J.C.Penny (JCP) GAP (GPS) Sears (SHLD) Best Buy (BBY) Costco (C0ST) Walmart (WMT)) Target (TGT) Nordstrom (JWN)
Date Revenue SG&A Date Revenue Date Revenue SG&A Date Revenue SG&A Date Revenue SG&A Date Revenue SG&A Date Revenue SG&A Date Revenue SG&A
3/30/90 3530.0 1149.0 3/30/90 402.4 3/31/95 7443.0 3/30/90 198.3 33.4 6/29/90 1177.0 90.6 3/30/90 6768.0 1103.0 3/30/90 3007.0 544.0 6/30/92 951.6 242.2
6/29/90 3580.0 1175.0 6/29/90 405.0 6/30/95 8440.0 6/29/90 126.1 28.3 9/28/90 1200.0 93.5 6/29/90 7544.0 1227.0 6/29/90 3242.0 563.0 9/30/92 737.3 213.4
9/28/90 3995.0 1276.0 9/28/90 501.7 9/29/95 7975.0 9/28/90 152.2 31.6 12/31/90 2162.0 160.4 9/28/90 7931.0 1310.0 9/28/90 3625.0 647.0 12/31/92 1069.0 257.7
12/31/90 5260.0 1708.0 12/31/90 624.7 12/29/95 7855.0 12/31/90 170.8 33.1 3/29/91 1362.0 113.9 12/31/90 10360.0 1512.0 12/31/90 4865.0 724.0 3/31/93 695.6 208.2
3/29/91 3433.0 1161.0 3/29/91 490.3 3/29/96 6975.0 3/29/91 215.7 37.7 6/28/91 1504.0 122.0 3/29/91 9281.0 1485.0 3/29/91 3349.0 607.0 6/30/93 1018.0 248.3
6/28/91 3456.0 1160.0 6/28/91 523.1 6/28/96 7566.0 6/28/91 165.6 34.2 9/30/91 1570.0 132.6 6/28/91 10340.0 1616.0 6/28/91 3562.0 639.0 9/30/93 769.4 216.3
9/30/91 3937.0 1225.0 9/30/91 702.1 9/30/96 7212.0 9/30/91 193.6 36.7 12/31/91 2454.0 193.7 9/30/91 10630.0 1697.0 9/30/91 3955.0 711.0 12/31/93 1107.0 267.7
12/31/91 5375.0 1737.0 12/31/91 803.5 12/31/96 9684.0 12/31/91 230.6 39.6 3/31/92 1519.0 139.0 12/31/91 13640.0 1887.0 12/31/91 5249.0 844.0 3/31/94 762.1 214.9
3/31/92 3793.0 1195.0 3/31/92 588.9 3/31/97 7263.0 3/31/92 339.9 51.7 6/30/92 1658.0 144.8 3/31/92 11650.0 1808.0 3/31/92 3719.0 656.0 6/30/94 1080.0 267.6
6/30/92 3789.0 1208.0 6/30/92 614.1 6/30/97 7846.0 6/30/92 246.5 46.8 9/30/92 1689.0 152.0 6/30/92 13030.0 1996.0 6/30/92 3967.0 704.0 9/30/94 862.0 246.3
9/30/92 4342.0 1261.0 9/30/92 827.2 9/30/97 7315.0 9/30/92 285.4 49.5 12/31/92 2590.0 223.8 9/30/92 13680.0 2143.0 9/30/92 4340.0 756.0 12/30/94 1191.0 294.5
12/31/92 6085.0 1496.0 12/31/92 930.2 12/31/97 9759.0 12/31/92 474.4 68.0 3/31/93 1634.0 159.7 12/31/92 17120.0 2374.0 12/31/92 5901.0 862.0 3/31/95 815.6 239.8
3/31/93 3964.0 1187.0 3/31/93 643.6 3/31/98 7515.0 3/31/93 613.6 83.8 6/30/93 1729.0 162.6 3/31/93 13920.0 2246.0 3/31/93 4040.0 698.0 6/30/95 1149.0 299.8
6/30/93 3963.0 1192.0 6/30/93 693.2 6/30/98 8116.0 6/30/93 441.9 70.8 9/30/93 9202.0 821.2 6/30/93 16240.0 2520.0 6/30/93 4287.0 748.0 9/29/95 906.8 267.6
9/30/93 4735.0 1315.0 9/30/93 898.7 9/30/98 7642.0 9/30/93 563.0 81.1 12/31/93 3688.0 321.7 9/30/93 16830.0 2719.0 9/30/93 4625.0 809.0 12/29/95 1242.0 314
12/31/93 6321.0 814.0 12/31/93 1060.0 12/31/98 10401.0 12/31/93 808.5 100.3 3/31/94 4101.0 352.6 12/31/93 20360.0 2848.0 12/31/93 6281.0 920.0 3/31/96 906.0 268.8
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12/31/13 3782.0 861.0 12/31/13 4575.0 12/31/13 12670.0 2048.0 3/31/14 26310.0 2539.0 12/31/13 129710.0 24390.0 12/31/13 20200.0 3325.0 3/31/16 3249.0 1043
3/31/14 2801.0 1010.0 3/31/14 3774.0 3/31/14 8639.0 1755.0 6/30/14 25790.0 2503.0 3/31/14 114960.0 22050.0 3/31/14 16660.0 3376.0 6/30/16 3651.0 1071
6/30/14 2799.0 966.0 6/30/14 3981.0 6/30/14 8459.0 1748.0 9/30/14 35520.0 3395.0 6/30/14 120120.0 23380.0 6/30/14 16960.0 3599.0 9/30/16 3542.0 1029
9/30/14 2764.0 989.0 9/30/14 3972.0 9/30/14 9032.0 1866.0 12/31/14 26870.0 2711.0 9/30/14 119000.0 23490.0 9/30/14 17250.0 3644.0 12/31/16 4316.0 1172
12/31/14 3893.0 980.0 12/31/14 4708.0 12/31/14 14210.0 2223.0 3/31/15 27450.0 2680.0 12/31/14 131560.0 24500.0 12/31/14 21750.0 4057.0 3/31/17 3354.0 1048
3/31/15 2857.0 965.0 3/31/15 3657.0 3/31/15 8558.0 1766.0 6/30/15 26100.0 2593.0 3/31/15 114830.0 22660.0 3/31/15 17120.0 3514.0 6/30/17 3793.0 1125
6/30/15 2875.0 885.0 6/30/15 3898.0 6/30/15 8528.0 1811.0 9/30/15 35780.0 3526.0 6/30/15 120230.0 24100.0 6/30/15 17430.0 3495.0 9/30/17 3629.0 1106
9/30/15 2897.0 959.0 9/30/15 3857.0 9/30/15 8819.0 1874.0 12/31/15 27220.0 2832.0 9/30/15 117410.0 24250.0 9/30/15 17610.0 3736.0
12/31/15 3996.0 1089.0 12/31/15 4385.0 12/31/15 13620.0 2167.0 3/31/16 28170.0 2845.0 12/31/15 129670.0 26030.0 12/31/15 21630.0 3920.0
3/31/16 2811.0 872.0 3/31/16 3438.0 3/31/16 8443.0 1744.0 6/30/16 26770.0 2749.0 3/31/16 115900.0 24080.0 3/31/16 16200.0 3153.0
6/30/16 2918.0 855.0 6/30/16 3851.0 6/30/16 8533.0 1773.0 9/30/16 29770.0 2995.0 6/30/16 120850.0 25200.0 6/30/16 16170.0 3249.0
9/30/16 2857.0 889.0 9/30/16 3798.0 9/30/16 8945.0 1891.0 12/31/16 28099.0 2963.0 9/30/16 118180.0 25580.0 9/30/16 16440.0 3339.0
12/31/16 3961.0 939.0 12/31/16 4429.0 12/31/16 13480.0 2149.0 3/31/17 29766.0 3720.0 12/31/16 130940.0 26990.0 12/31/16 20690.0 3615.0
3/31/17 2706.0 845.0 3/31/17 3440.0 3/31/17 8528.0 1722.0 6/30/17 28860.0 2922.0 3/31/17 117540.0 24620.0 3/31/17 16020.0 3132.0
6/30/17 2962.0 838.0 6/30/17 3799.0 6/30/17 8940.0 1830.0 9/30/17 42300.0 4153.0 6/30/17 123360.0 25860.0 6/30/17 16430.0 3382.0
9/30/17 2808.0 849.0 9/30/17 3838.0 9/30/17 9320.0 1932.0 9/30/17 123180.0 26870.0 9/30/17 16670.0 3512.0

Entertainment

DISH (DISH) Disney (DIS) Netflix (NFLX) TIVO (TIVO)
Date Revenue SG&A Date Revenue SG&A Date Revenue SG&A Date Revenue SG&A
12/31/04 1938.0 3/30/90 1304.0 34.6 3/31/02 30.5 16.2 3/31/99 0.1
3/31/05 2024.0 6/29/90 1540.0 33.4 6/30/02 36.4 17.3 6/30/99 0.1 3.8
6/30/05 2095.0 113.2 9/28/90 1712.0 37.5 9/30/02 40.7 17.5 9/30/99 0.0 13.0
9/30/05 2128.0 116.3 12/31/90 1492.0 35.9 12/31/02 45.2 19.6 12/31/99 0.2 27.8
12/31/05 2199.0 113.9 3/29/91 1439.0 36.5 3/31/03 55.7 26.4 3/31/00 0.4 17.4
3/31/06 2299.0 455.4 6/28/91 1512.0 44.9 6/30/03 63.2 21.0 6/30/00 0.9 30.2
6/30/06 2466.0 471.0 9/30/91 1739.0 43.6 9/30/03 72.2 26.0 9/30/00 1.0 53.4
9/30/06 2475.0 135.4 12/31/91 1937.0 42.2 12/31/03 81.2 30.4 12/31/00 1.4 81.0
12/31/06 2578.0 142.9 3/31/92 1655.0 36.9 3/31/04 100.4 45.1 3/31/01 3.2 41.3
3/31/07 2645.0 530.4 6/30/92 1854.0 36.5 6/30/04 120.3 42.3 6/30/01 4.1 26.5
6/30/07 2760.0 483.8 9/30/92 2059.0 32.6 9/30/04 141.6 43.7 9/30/01 5.3 23.9
9/30/07 2794.0 151.4 12/31/92 2391.0 43.0 12/31/04 138.3 -4.8 12/31/01 6.8 32.1
12/31/07 2891.0 172.6 3/31/93 2026.0 39.8 3/31/05 152.5 42.5 3/31/02 9.9 35.0
3/31/08 2844.0 504.5 6/30/93 1937.0 41.5 6/30/05 164.0 33.2 6/30/02 35.0 12.6
6/30/08 2915.0 135.0 9/30/93 2175.0 39.3 9/30/05 172.7 43.0 9/30/02 25.0 8.1
9/30/08 2937.0 147.6 12/31/93 2727.0 43.6 12/31/05 193.0 60.6 12/31/02 23.0 7.3
12/31/08 2921.0 131.9 3/31/94 2276.0 37.4 3/31/06 224.1 61.3 3/31/03 28.5 7.8
3/31/09 2905.0 136.9 6/30/94 2354.0 39.6 6/30/06 239.4 53.8 6/30/03 26.7 8.6
6/30/09 2904.0 155.9 9/30/94 2698.0 41.6 9/30/06 256.0 69.3 9/30/03 43.3 9.7
9/30/09 2892.0 157.7 12/30/94 3302.0 42.3 12/31/06 277.2 77.3 12/31/03 42.6 9.3
12/31/09 2963.0 152.2 3/31/95 2923.0 45.8 3/31/07 305.3 84.3 3/31/04 34.5 9.8
3/31/10 3057.0 150.8 6/30/95 2764.0 38.7 6/30/07 303.7 59.1 6/30/04 39.8 9.8
6/30/10 3169.0 155.0 9/29/95 3162.0 112.2 9/30/07 294.0 62.1 9/30/04 38.3 18.6
9/30/10 3208.0 155.4 12/29/95 3818.0 54.0 12/31/07 302.4 65.3 12/31/04 59.6 15.7
12/31/10 3207.0 164.6 3/31/96 4543.0 97.0 3/31/08 326.2 68.6 3/31/05 51.6 13.0
3/31/11 3224.0 161.8 6/30/96 5087.0 66.0 6/30/08 337.6 53.4 6/30/05 44.4 16.0
6/30/11 3590.0 325,26 9/30/96 5272.0 61.0 9/30/08 341.3 61.0 9/30/05 49.6 21.7
9/30/11 3603.0 382.6 12/31/96 6278.0 90.0 12/31/08 359.6 66.4 12/31/05 49.5 24.6
12/31/11 2657.0 232.3 3/31/97 5481.0 108.0 3/31/09 394.1 75.3 3/31/06 57.0 22.7
3/31/12 3582.0 376.2 6/30/97 5194.0 69.0 6/30/09 408.5 59.5 6/30/06 58.4 19.6
6/30/12 3572.0 327.7 9/30/97 5520.0 100.0 9/30/09 423.1 70.1 9/30/06 58.2 20.3
9/30/12 3523.0 330.4 12/31/97 6339.0 78.0 12/31/09 444.5 84.2 12/31/06 52.2 25.6
12/31/12 2504.0 312.2 3/31/98 5242.0 48.0 3/31/10 493.7 90.8 3/31/07 36.6 22.3
3/31/13 3376.0 173.3 6/30/98 5248.0 49.0 6/30/10 519.8 89.7 6/30/07 57.1 24.8
6/30/13 3486.0 202.2 9/30/98 6147.0 11.0 9/30/10 553.2 97.1 9/30/07 45.1 26.1
9/30/13 3505.0 191.4 12/31/98 6597.0 38.0 12/31/10 595.9 80.7 12/31/07 52.6 24.8
12/31/13 3539.0 209.8 3/31/99 5516.0 70.0 3/31/11 718.6 127.3 3/31/08 32.2 17.4
3/31/14 3594.0 203.1 6/30/99 5531.0 17.0 6/30/11 788.6 125.7 6/30/08 73.1 17.7
6/30/14 3688.0 189.7 9/30/99 5791.0 15.0 9/30/11 821.8 118.9 9/30/08 108.5 19.2
9/30/14 3679.0 196.4 12/31/99 6940.0 12/31/11 875.6 157.8 12/31/08 118.2 19.6
12/31/14 3682.0 226.6 3/31/00 6307.0 3/31/12 869.8 165.0 3/31/09 111.2 18.9
3/31/15 3724.0 199.4 6/30/00 6053.0 6/30/12 889.2 148.0 6/30/09 119.5 17.5
6/30/15 3832.0 176.1 9/30/00 6118.0 9/30/12 905.1 143.8 9/30/09 114.5 18.1
9/30/15 3734.0 186.7 12/31/00 7433.0 12/31/12 945.2 121.4 12/31/09 137.1 18.6
12/31/15 3779.0 730.9 3/31/01 6049.0 3/31/13 1024.0 163.2 3/31/10 129.4 22.7
3/31/16 3827.0 201.0 6/30/01 5960.0 6/30/13 1069.0 158.5 6/30/10 133.9 22.1
6/30/16 3837.0 182.1 9/30/01 5786.0 9/30/13 1106.0 154.4 9/30/10 138.0 23.7
9/30/16 3746.0 190.7 12/31/01 7016.0 12/31/13 1175.0 174.1 12/31/10 140.2 26.8
12/31/16 3724.0 209.4 3/31/02 5856.0 3/31/14 1270.0 193.0 3/31/11 152.7 30.0
3/31/17 3680.0 131.0 6/30/02 5795.0 6/30/14 1340.0 180.8 6/30/11 179.0 27.2
6/30/17 3644.0 179.8 9/30/02 6662.0 9/30/14 1409.0 223.7 9/30/11 181.9 27.2
9/30/17 3583.0 187.0 12/31/02 7170.0 12/31/14 1485.0 279.5 12/31/11 170.5 45.9
3/31/03 6500.0 3/31/15 1573.0 286.2 3/31/12 171.7 23.7
6/30/03 6377.0 6/30/15 1645.0 293.1 6/30/12 154.6 35.0
9/30/03 7014.0 9/30/15 1738.0 319.0 9/30/12 163.7 31.3
12/31/03 8549.0 12/31/15 1823.0 333.2 12/31/12 138.3 36.1
3/31/04 7189.0 3/31/16 1958.0 335.2 3/31/13 132.8 32.2
6/30/04 7471.0 6/30/16 2105.0 354.4 6/30/13 129.2 34.3
9/30/04 7543.0 9/30/16 2290.0 436.2 9/30/13 123.5 28.7
12/31/04 8666.0 12/31/16 2478.0 444.0 12/31/13 152.0 33.7
3/31/05 7829.0 3/31/17 2637.0 465.6 3/31/14 142.5 27.2
6/30/05 7715.0 6/30/17 2785.0 488.3 6/30/14 137.1 27.3
9/30/05 7164.0 9/30/17 2985.0 528.0 9/30/14 128.4 27.6
12/31/05 8854.0 12/31/14 134.2 28.4
3/31/06 8027.0 3/31/15 134.0 27.5
6/30/06 8474.0 6/30/15 127.8 28.9
9/30/06 8652.0 9/30/15 114.9 29.2
12/31/06 9581.0 12/31/15 149.5 32.5
3/31/07 7954.0 3/31/16 118.4 36.7
6/30/07 9045.0 6/30/16 125.2 42.6
9/30/07 8930.0 9/30/16 153.1 54.1
12/31/07 10450.0 12/31/16 252.3 60.0
3/31/08 8710.0 3/31/17 205.8 54.0
6/30/08 9236.0 6/30/17 208.6 45.7
9/30/08 9445.0 9/30/17 197.9 47.4
12/31/08 9599.0
3/31/09 8087.0
6/30/09 8596.0
9/30/09 9867.0
12/31/09 9739.0
3/31/10 8580.0
6/30/10 10000.0
9/30/10 9742.0
12/31/10 10720.0
3/31/11 9077.0
6/30/11 10680.0
9/30/11 10420.0
12/31/11 10780.0
3/31/12 9629.0
6/30/12 11090.0
9/30/12 10780.0
12/31/12 11340.0
3/31/13 10550.0
6/30/13 11580.0
9/30/13 11570.0
12/31/13 12310.0 2018.0
3/31/14 11650.0 2116.0
6/30/14 12470.0 2047.0
9/30/14 12390.0 2384.0
12/31/14 13390.0 1935.0
3/31/15 12460.0 2081.0
6/30/15 13100.0 2101.0
9/30/15 13510.0 2406.0
12/31/15 15240.0 2025.0
3/31/16 12970.0 2137.0
6/30/16 14280.0 2305.0
9/30/16 13140.0 2787.0
12/31/16 14780.0 1985.0
3/31/17 13340.0 1941.0
6/30/17 14240.0 2022.0
9/30/17 12780.0 2228.0

Insurance