# FIN 484 2 Exercises 1

Smart Study
(Not rated)
(Not rated)
Chat
DateBWL SalesDPI
Jan-200321348251.3  1. Find the appropriate univariate model for the sale of Beer, Wine, and Liquor data (BWL Sales) and justify your answer using data from Jan-2003 to Dec-2006
Feb-200320598268.1   Calculate the MAPE and RMSE for the data used to run the model and for the hold-up period (7 months)
Mar-200322898317.6  2. Run a bivariate model using BWL Sales and DPI using data from Jan-2003 to Dec-2006
Apr-200323488356.8   Compare the results to the univariate model in terms of RMSE and/or MAPE for the data used to run the model and for the hold-up period
May-200325938412.0  3. Account for the trend and seasonality of BWL sales by adding a time index variable and dummies for months 2-12. Run this new model using data from Jan-2003 to Dec-2006
Jun-200324508449.6   Compare the results to the univariate model in terms of RMSE and/or MAPE for the data used to run the model and for the hold-up period
Jul-200326298567.8
Aug-200326788648.0
Sep-200324788572.4
Oct-200326598606.2
Nov-200326788678.3
Dec-200336818712.4
Jan-200423088753.6
Feb-200422328792.7
Mar-200424118839.9
Apr-200425678884.2
May-200427028960.1
Jun-200426608989.2
Jul-200428869015.5
Aug-200426419049.3
Sep-200426399066.9
Oct-200427539110.0
Nov-200427929119.1
Dec-200438439458.4
Jan-200522549148.5
Feb-200523559179.0
Mar-200525769235.1
Apr-200526919279.7
May-200527679326.7
Jun-200528469359.1
Jul-200529959422.6
Aug-200528659476.0
Sep-200528619518.7
Oct-200528849578.4
Nov-200530259622.2
Dec-200542679675.3
Jan-200625629848.2
Feb-200626679894.7
Mar-200629189929.2
Apr-200629639957.7
May-200632079971.2
Jun-2006325210017.0
Jul-2006332210049.7
Aug-2006322810079.7
Sep-2006321210116.6
Oct-2006312010147.8
Nov-2006335910186.3
Dec-2006458810254.7
Jan-2007271010295.7
Feb-2007274810356.6
Mar-2007317610424.2
Apr-2007303710442.3
May-2007345910466.5
Jun-2007357810476.0
Jul-20073541

10515.3

 QTR ACC FUEL 1.QTR: Quarter (Quarters 1-29 = Control, Quarters 30-50 = Experimental) 1 192 32.592 2.ACC: Injuries and fatalities from Wednesday to Saturday nighttime accidents 2 238 37.25 3.FUEL: Fuel consumption (million gallons) in Albuquerque 3 232 40.032 4 246 35.852 The Police Department in Alburquerque, New Mexico introduced a van that housed a Blood Alcohol Testing (BAT) device to try to reduce DWI related accidents 5 185 38.226 This BATmobile was introduced in Quarter 30 of your data, so you have 29 observations before the program (Control) and 21 during the program (Experimental) 6 274 38.711 Part of your job is to decide whether or not the program was effective in reducing DWI related accidents 7 266 43.139 8 196 40.434 1. Using the number of accidents (ACC) and the fuel consumption (FUEL), calculate the average number of injuries before and after the program. 9 170 35.898 Does it look like the program was effective? Explain 10 234 37.111 2. Run a multiple-regression model using ACC, FUEL, Quarter dummies (Q2, Q3, Q4), and a dummy variable for whether or not the program was in effect (BAT) 11 272 38.944 Describe the results for the FUEL and quarter dummies and comment on the evidence related to the efficacy of the BATmobile program. 12 234 37.717 3. Programs like the BATmobile usually take time to catch on (ramping up). To account for this, modify the BAT dummy variable so that the zero values remain unchanged but 13 210 37.861 the 1's are modified so that the new values are 1, 2, 3, 4, etc. Having this new variable, run the multiple-regression model and comment on whether or not there is 14 280 42.524 evidence of a ramping up effect of the BATmobile program in reducing DWI related accidents. 15 246 43.965 16 248 41.976 17 269 42.918 18 326 49.789 19 342 48.454 20 257 45.056 21 280 49.385 22 290 42.524 23 356 51.224 24 295 48.562 25 279 48.167 26 330 51.362 27 354 54.646 28 331 53.398 29 291 50.584 30 377 51.32 31 327 50.81 32 301 46.272 33 269 48.664 34 314 48.122 35 318 47.483 36 288 44.732 37 242 46.143 38 268 44.129 39 327 46.258 40 253 48.23 41 215 46.459 42 263 50.686 43 319 49.681 44 263 51.029 45 206 47.236 46 286 51.717 47 323 51.824 48 306 49.38 49 230 47.961 50 304 46.039

• 5 years ago
FIN 484 2 Exercises 1
NOT RATED

Purchase the answer to view it

• fin_484_2_exercises_1.xlsx