GENERAL INSTRUCTIONS: You will execute multiple regression models using data in the worksheets, Time Series Data...

   
 

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GENERAL INSTRUCTIONS: You will execute multiple regression models using data in the worksheets, "Time Series Data" and "Cross Sectional Data." For all regressions, you will use the same dependent variable (Unit Sales (i.e. bottles) of Table Wine), and use all of the independent variables given in each worksheet (although ignore column A in the Cross Sectional worksheet). SPECIFIC INSTRUCTIONS: Part 1: Run a time series regression using the data in the "Time Series Data" worksheet, and then answer the questions in the worksheet, QUESTIONS_a. Each observation of the time series data provides unit sales of wine in Los Angeles County as the dependent variable, and a set of independent variables that includes: the price of a bottle of wine (measured in dollars and cents), a trend variable (with a starting value of 1 going up to 52), and a dummy variable, "Peak," indicating the holiday season at the end of the year (NOTE: Each observation represents a four-week period. Thus, every 13 observations represents a year of time). Part 2: Run TWO regressions using the data in the worksheet, "Cross Sectional Data." Each observation of the cross-sectional data provides unit sales of wine in a California county at a particular point in time as the dependent variable, and a set of independent variables that includes: price of a bottle of wine, county median income, county population density, and a dummy variable indicating whether or not the county represents a primarily urban setting. a. Regression 1: Use the data as given. b. Regression 2: Run a log-linear regression model, transforming each continuous (i.e. non-dummy) variable--including the dependent variable-- to its natural log form before running the regression. Use the Excel function, LN(variable), to transform each continuous variable to its natural log form. NOTE: Do not transform the dummy variable, Urban, but include it in your regression. c. After running both regressions, answer the questions in the worksheet, QUESTIONS_b. 1 2 3 Table Wine 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 Unit Sales of 55 56 2,337,203 2,459,584 2,580,770 2,624,247 2,262,262 2,330,873 2,282,355 2,379,487 2,321,668 2,316,209 2,482,686 3,169,843 2,923,818 2,441,194 2,561,594 2,534,459 2,431,278 2,363,073 2,380,267 2,480,495 2,326,408 2,276,162 2,226,475 2,379,567 3,104,285 3,150,728 2,377,966 2,566,015 2,465,395 2,545,242 2,294,803 2,256,763 2,227,268 2,106,009 2,217,999 2,302,779 2,492,324 3,137,366 3,247,539 2,298,451 2,360,494 2,535,444 2,596,670 2,504,948 2,447,083 2,581,565 2,555,526 2,657,483 2,608,792 2,686,719 3,554,860 3,318,317 Price of Table Wine 6.42 6.40 6.40 6.65 6.81 6.86 6.95 6.94 6.99 6.96 7.05 6.99 7.27 7.30 7.30 7.24 7.31 7.39 7.58 7.72 7.63 7.68 7.70 7.59 7.51 7.60 7.64 7.65 7.74 7.61 7.64 7.90 8.01 8.05 8.09 8.05 8.08 8.17 8.23 7.80 7.83 8.04 8.02 8.13 8.07 7.96 8.20 8.24 8.25 8.30 8.39 8.67 Time 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 Peak White Zinfandel, Los Angeles County (Keat, Young, and Erfle; 2013) 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 0 0 1 1 1 2 3 County: FIPS Code and Name 4 06001 Alameda County, CA 5 06003 Alpine County, CA 6 7 8 | 9 10 06005 Amador County, CA 06007 Butle County, CA 06009 Calaveras County, CA 06011Colusa County, CA 06013 Contra Costa County, CA 11 06015 Del Norte County, CA 12 06017 El Dorado County, CA 13 06019 Fresno County, CA 14 06021 Glenn County, CA 15 06023 Humboldt County, CA. 16 06025 Imperial County, CA 17 06027 Inyo County, CA 18 06029 Kern County, CA 19 06031 Kings County, CA 20 06033 Lake County, CA 21 06035 Lassen County, CA 22 06037 Los Angeles County, CA 23 06039 Madera County, CA 24 06041 Marin County, CA 25 06043 Mariposa County, CA 26 06045 Mendocino County, CA 27 06047 Merced County, CA 28 06049 Modoc County, CA. 29 06051 Mono County, CA. 30 06053 Monterey County, CA 31 06055 Napa County, CA 32 06057 Nevada County, CA 33 06059 Orange County, CA 34 06061 Placer County, CA 35 06063 Plumas County, CA. 36 06065 Riverside County, CA 37 06067 Sacramento County, CA 38 06069 San Benito County, CA 39 06071 San Bernardino County, CA 40 06073 San Diego County, CA 41 06075 San Francisco County, CA 42 06077 San Joaquin County, CA 43 06079 San Luis Obispo County, CA 44 06081 San Mateo County, CA 45 06083 Santa Barbara County, CA 46 06085 Santa Clara County, CA 47 06087 Santa Cruz County, CA 48 06089 Shasta County, CA 49 06091 Sierra County, CA 50 06093 Siskiyou County, CA 51 06095 Solano County, CA 52 06097 Sonoma County, CA 53 06099 Stanislaus County, CA 54 06101 Sutter County, CA 55 06103 Tehama County, CA 56 06105 Trinity County, CA 57 06107 Tulare County, CA 58 06109 Tuolumne County, CA 59 06111 Ventura County, CA 60 06113 Yolo County, CA 61 06115 Yuba County, CA B Unit Sales of Table Wine 4,838,094 3,581,113 3,661,067 2,456,382 3,077,276 1,796,686 3,866,314 1,096,958 2,605,832 2,012,772 1,681,082 1,804,220 1,116,288 2,291,419 1,495,419 1,277,211 549,320 2,230,991 3,826,227 1,761,556 4,835,561 1,530,888 1,340,277 643,564 1,740,765 2,607,008 1,352,961 3,415,226 1,569,045 6,163,518 2,658,347 1,225,250 3,655,448 2,404,648 2,515,884 2,767,735 4,114,544 8,657,517 1,613,654 2,803,992 5,312,762 1,710,184 5,242,670 3,262,030 471,762 1,959,957 795,463 2,593,508 2,450,440 2,033,577 2,209,940 594,493 1,300,288 2,120,535 1,378,331 4,470,669 1,377,746 1,569,834 Price- Median Table Wine Income 6.42 6.40 6.40 6.65 6.81 6.86 6.95 6.94 6.99 6.96 7.05 6.99 8.67 8.70 8.33 7.45 7.18 7.60 8.28 White Zinfandel, California (Keat, Young, and Erfle; 2013) Urban: 1 for an urban county, 0 otherwise 43550 47359 76728 57920 46617 Pop. Per Sq. Mile 70821 59018 56180 42971 55256 49558 79135 37588 68815 46903 156.2 43239 21.4 40376 37.7 7.27 39402 41.8 7.30 49571 1.8 7.30 48021 103.3 7.24 48838 110.1 7.31 39525 51.5 7.39 52484 7.7 7.58 56266 2419.6 7.72 47724 70.6 7.63 89605 485.1 7.68 49174 12.6 7.70 44527 25.1 7.59 43945 132.2 7.51 35402 2.5 7.60 60469 4.7 7.64 59737 126.5 182.4 68641 58077 103.1 7.65 7.74 7.61 7.64 75762 3807.7 74645 247.6 7.90 44151 7.8 8.01 58365 303.8 8.05 56553 1470.8 8.09 65570 39.8 8.05 55853 101.5 63857 735.8 72947 17179.1 492.6 81.7 1602.2 89064 8.08 8.17 8.23 53764 7.80 58630 7.83 87633 8.04 61896 8.02 8.13 8.07 7.96 8.20 37865 8.24 8.25 8.30 66030 44058 50308 69914 64343 50671 8.39 50010 38753 37672 2043.6 1.6 64.1 134.4 44.7 18.6 1465.2 28.4 106 155 1381 589.4 46.9 3.4 7.2 503 307.1 344.2 157.3 21.5 4.3 91.7 24.9 446.7 197.9 114.2 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 0 0 0 0 0 0 0 0 1 0 0 1 1 0 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 Answer questions a through e: 4 a. How are the two models different in terms of the number of statistically significant explanatory variables (excluding the constant term)? 5 6 10 12 14 b. In the boxes below, calculate the respective mean values of the following (non-transformed) variables: 15 Unit Sales- Table 16 Wine 17 18 19 P Table Wine Median Income 20 21 22 23 24 c. For Regression 1, what is the price elasticity of demand at the mean values of price (P TableWine) and quantity (Unit Sales - Table Wine)? 25 NOTE: Enter a formula using the mean values above and estimated coefficient from the regression. 26 27 28 29 30 31 32 d. For Regression 1, what is the income elasticity of demand at the mean values of income (Median Income) and quantity (Unit Sales - Table Wine)? 33 NOTE: Enter a formula using the mean values above and estimated coefficient from the regression. 34 35 36 37 38 39 40 e. For Regression 2, what are the price and income elasticities of demand? 41 42 43 GENERAL INSTRUCTIONS: You will execute multiple regression models using data in the worksheets, "Time Series Data" and "Cross Sectional Data." For all regressions, you will use the same dependent variable (Unit Sales (i.e. bottles) of Table Wine), and use all of the independent variables given in each worksheet (although ignore column A in the Cross Sectional worksheet). SPECIFIC INSTRUCTIONS: Part 1: Run a time series regression using the data in the "Time Series Data" worksheet, and then answer the questions in the worksheet, QUESTIONS_a. Each observation of the time series data provides unit sales of wine in Los Angeles County as the dependent variable, and a set of independent variables that includes: the price of a bottle of wine (measured in dollars and cents), a trend variable (with a starting value of 1 going up to 52), and a dummy variable, "Peak," indicating the holiday season at the end of the year (NOTE: Each observation represents a four-week period. Thus, every 13 observations represents a year of time). Part 2: Run TWO regressions using the data in the worksheet, "Cross Sectional Data." Each observation of the cross-sectional data provides unit sales of wine in a California county at a particular point in time as the dependent variable, and a set of independent variables that includes: price of a bottle of wine, county median income, county population density, and a dummy variable indicating whether or not the county represents a primarily urban setting. a. Regression 1: Use the data as given. b. Regression 2: Run a log-linear regression model, transforming each continuous (i.e. non-dummy) variable--including the dependent variable-- to its natural log form before running the regression. Use the Excel function, LN(variable), to transform each continuous variable to its natural log form. NOTE: Do not transform the dummy variable, Urban, but include it in your regression. c. After running both regressions, answer the questions in the worksheet, QUESTIONS_b. 1 2 3 Table Wine 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 Unit Sales of 55 56 2,337,203 2,459,584 2,580,770 2,624,247 2,262,262 2,330,873 2,282,355 2,379,487 2,321,668 2,316,209 2,482,686 3,169,843 2,923,818 2,441,194 2,561,594 2,534,459 2,431,278 2,363,073 2,380,267 2,480,495 2,326,408 2,276,162 2,226,475 2,379,567 3,104,285 3,150,728 2,377,966 2,566,015 2,465,395 2,545,242 2,294,803 2,256,763 2,227,268 2,106,009 2,217,999 2,302,779 2,492,324 3,137,366 3,247,539 2,298,451 2,360,494 2,535,444 2,596,670 2,504,948 2,447,083 2,581,565 2,555,526 2,657,483 2,608,792 2,686,719 3,554,860 3,318,317 Price of Table Wine 6.42 6.40 6.40 6.65 6.81 6.86 6.95 6.94 6.99 6.96 7.05 6.99 7.27 7.30 7.30 7.24 7.31 7.39 7.58 7.72 7.63 7.68 7.70 7.59 7.51 7.60 7.64 7.65 7.74 7.61 7.64 7.90 8.01 8.05 8.09 8.05 8.08 8.17 8.23 7.80 7.83 8.04 8.02 8.13 8.07 7.96 8.20 8.24 8.25 8.30 8.39 8.67 Time 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 Peak White Zinfandel, Los Angeles County (Keat, Young, and Erfle; 2013) 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 0 0 1 1 1 2 3 County: FIPS Code and Name 4 06001 Alameda County, CA 5 06003 Alpine County, CA 6 7 8 | 9 10 06005 Amador County, CA 06007 Butle County, CA 06009 Calaveras County, CA 06011Colusa County, CA 06013 Contra Costa County, CA 11 06015 Del Norte County, CA 12 06017 El Dorado County, CA 13 06019 Fresno County, CA 14 06021 Glenn County, CA 15 06023 Humboldt County, CA. 16 06025 Imperial County, CA 17 06027 Inyo County, CA 18 06029 Kern County, CA 19 06031 Kings County, CA 20 06033 Lake County, CA 21 06035 Lassen County, CA 22 06037 Los Angeles County, CA 23 06039 Madera County, CA 24 06041 Marin County, CA 25 06043 Mariposa County, CA 26 06045 Mendocino County, CA 27 06047 Merced County, CA 28 06049 Modoc County, CA. 29 06051 Mono County, CA. 30 06053 Monterey County, CA 31 06055 Napa County, CA 32 06057 Nevada County, CA 33 06059 Orange County, CA 34 06061 Placer County, CA 35 06063 Plumas County, CA. 36 06065 Riverside County, CA 37 06067 Sacramento County, CA 38 06069 San Benito County, CA 39 06071 San Bernardino County, CA 40 06073 San Diego County, CA 41 06075 San Francisco County, CA 42 06077 San Joaquin County, CA 43 06079 San Luis Obispo County, CA 44 06081 San Mateo County, CA 45 06083 Santa Barbara County, CA 46 06085 Santa Clara County, CA 47 06087 Santa Cruz County, CA 48 06089 Shasta County, CA 49 06091 Sierra County, CA 50 06093 Siskiyou County, CA 51 06095 Solano County, CA 52 06097 Sonoma County, CA 53 06099 Stanislaus County, CA 54 06101 Sutter County, CA 55 06103 Tehama County, CA 56 06105 Trinity County, CA 57 06107 Tulare County, CA 58 06109 Tuolumne County, CA 59 06111 Ventura County, CA 60 06113 Yolo County, CA 61 06115 Yuba County, CA B Unit Sales of Table Wine 4,838,094 3,581,113 3,661,067 2,456,382 3,077,276 1,796,686 3,866,314 1,096,958 2,605,832 2,012,772 1,681,082 1,804,220 1,116,288 2,291,419 1,495,419 1,277,211 549,320 2,230,991 3,826,227 1,761,556 4,835,561 1,530,888 1,340,277 643,564 1,740,765 2,607,008 1,352,961 3,415,226 1,569,045 6,163,518 2,658,347 1,225,250 3,655,448 2,404,648 2,515,884 2,767,735 4,114,544 8,657,517 1,613,654 2,803,992 5,312,762 1,710,184 5,242,670 3,262,030 471,762 1,959,957 795,463 2,593,508 2,450,440 2,033,577 2,209,940 594,493 1,300,288 2,120,535 1,378,331 4,470,669 1,377,746 1,569,834 Price- Median Table Wine Income 6.42 6.40 6.40 6.65 6.81 6.86 6.95 6.94 6.99 6.96 7.05 6.99 8.67 8.70 8.33 7.45 7.18 7.60 8.28 White Zinfandel, California (Keat, Young, and Erfle; 2013) Urban: 1 for an urban county, 0 otherwise 43550 47359 76728 57920 46617 Pop. Per Sq. Mile 70821 59018 56180 42971 55256 49558 79135 37588 68815 46903 156.2 43239 21.4 40376 37.7 7.27 39402 41.8 7.30 49571 1.8 7.30 48021 103.3 7.24 48838 110.1 7.31 39525 51.5 7.39 52484 7.7 7.58 56266 2419.6 7.72 47724 70.6 7.63 89605 485.1 7.68 49174 12.6 7.70 44527 25.1 7.59 43945 132.2 7.51 35402 2.5 7.60 60469 4.7 7.64 59737 126.5 182.4 68641 58077 103.1 7.65 7.74 7.61 7.64 75762 3807.7 74645 247.6 7.90 44151 7.8 8.01 58365 303.8 8.05 56553 1470.8 8.09 65570 39.8 8.05 55853 101.5 63857 735.8 72947 17179.1 492.6 81.7 1602.2 89064 8.08 8.17 8.23 53764 7.80 58630 7.83 87633 8.04 61896 8.02 8.13 8.07 7.96 8.20 37865 8.24 8.25 8.30 66030 44058 50308 69914 64343 50671 8.39 50010 38753 37672 2043.6 1.6 64.1 134.4 44.7 18.6 1465.2 28.4 106 155 1381 589.4 46.9 3.4 7.2 503 307.1 344.2 157.3 21.5 4.3 91.7 24.9 446.7 197.9 114.2 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 0 0 0 0 0 0 0 0 1 0 0 1 1 0 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 Answer questions a through e: 4 a. How are the two models different in terms of the number of statistically significant explanatory variables (excluding the constant term)? 5 6 10 12 14 b. In the boxes below, calculate the respective mean values of the following (non-transformed) variables: 15 Unit Sales- Table 16 Wine 17 18 19 P Table Wine Median Income 20 21 22 23 24 c. For Regression 1, what is the price elasticity of demand at the mean values of price (P TableWine) and quantity (Unit Sales - Table Wine)? 25 NOTE: Enter a formula using the mean values above and estimated coefficient from the regression. 26 27 28 29 30 31 32 d. For Regression 1, what is the income elasticity of demand at the mean values of income (Median Income) and quantity (Unit Sales - Table Wine)? 33 NOTE: Enter a formula using the mean values above and estimated coefficient from the regression. 34 35 36 37 38 39 40 e. For Regression 2, what are the price and income elasticities of demand? 41 42 43

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Answer to Question a According to the different aspects displayed from the two models it is clear th... View the full answer