FIN 484 2 Exercises 1DateBWL SalesDPIJan-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-2006Feb-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-2006Jun-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-2007354110515.3QTRACCFUEL 1.QTR: Quarter (Quarters 1-29 = Control, Quarters 30-50 = Experimental) 119232.592 2.ACC: Injuries and fatalities from Wednesday to Saturday nighttime accidents 223837.25 3.FUEL: Fuel consumption (million gallons) in Albuquerque 323240.032 424635.852 The Police Department in Alburquerque, New Mexico introduced a van that housed a Blood Alcohol Testing (BAT) device to try to reduce DWI related accidents518538.226 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)627438.711 Part of your job is to decide whether or not the program was effective in reducing DWI related accidents 726643.139 819640.434 1. Using the number of accidents (ACC) and the fuel consumption (FUEL), calculate the average number of injuries before and after the program. 917035.898 Does it look like the program was effective? Explain 1023437.111 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)1127238.944 Describe the results for the FUEL and quarter dummies and comment on the evidence related to the efficacy of the BATmobile program. 1223437.717 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 but1321037.861 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 1428042.524 evidence of a ramping up effect of the BATmobile program in reducing DWI related accidents. 1524643.965 1624841.976 1726942.918 1832649.789 1934248.454 2025745.056 2128049.385 2229042.524 2335651.224 2429548.562 2527948.167 2633051.362 2735454.646 2833153.398 2929150.584 3037751.32 3132750.81 3230146.272 3326948.664 3431448.122 3531847.483 3628844.732 3724246.143 3826844.129 3932746.258 4025348.23 4121546.459 4226350.686 4331949.681 4426351.029 4520647.236 4628651.717 4732351.824 4830649.38 4923047.961 5030446.039 Here is a perfect answer: