The Blitz Company Case Study

Blitz Company, based in Berlin, is a leading local producer and marketer of household laundry detergent and bleach products. About a year ago, Blitz Company rolled out its new Mach3 detergent in 30 regional markets following its success in test markets. This isn't just a 'me too' product in a commodity market. Blitz detergent contains branded A bleach, a successful laundry product in its own right. At the time of the introduction, management wondered whether the company could successfully crack this market dominated by Procter & Gamble and other big players. Table 1 below shows weekly demand (cross-sectional) data for Mach3 detergent in these 30 regional markets:

Table 1: Weekly Demand for Mach3 Detergent in 30 Reginal Markets

Reginal Market	Q	P in	CP in	A in	HI in
1	1290	137	94	8140	53123
2	1177	147	81	8960	51749
3	1155	149	89	8520	49881
4	1299	117	92	8540	43589
5	1166	135	86	8100	42799
6	1186	143	79	7680	55565
7	1293	113	91	9780	37959
8	1322	111	82	8210	47196
9	1338	109	81	8430	50163
10	1160	129	82	8490	39080
11	1293	124	91	7970	43263
12	1413	117	76	9880	51291
13	1299	106	90	9140	38343
14	1238	135	88	9130	39473
15	1467	117	99	8670	51501
16	1089	147	76	7850	37809
17	1203	124	83	8170	41471
18	1474	103	98	8460	46663
19	1235	140	78	7680	55839
20	1367	115	83	8560	47438
21	1310	119	76	7710	54348
22	1331	138	100	9470	45066
23	1293	122	90	8310	44166
24	1437	105	86	9050	55380
25	1165	145	96	9960	38656
26	1328	138	97	9290	46084
27	1515	116	97	10000	52249
28	1223	148	84	9510	50855
29	1293	134	88	8480	54546
30	1215	127	87	8910	38085

Where Q is weekly demand in cases, P is price per case in , CP is competitor price in , A is advertising in , and HI is household income in .

Questions:

1. Using the multiple linear regression facility of Excel, estimate the coefficients of the demand model for the data given in the table above. When you submit your solution, please remember to submit the Excel output sheet of the results.
2. Provide an economic interpretation for each of the coefficients in the regression equation you have estimated.
3. Is each of the explanatory variables statistically significant at 5% significance level? In your answer please use the t-statistics and the p-values, too.
4. What is the value of the adjusted value of coefficient of determination? How would you interpret this result?
5. Perform an F-test (at the 0.05 significance level) and give an interpretation of the result based on the critical value of F-statistic and its significance-F.
6. Calculate the price elasticity of demand for Mach3 detergent using the average value of P and the averages of other independent variables. What is your conclusion about it?
7. Does your conclusion in (9) above justify a proposal put forward by the Chief Financial Officer to the board of directors to raise the price per case of Mach3 detergent by 30%? Verify your answer by checking what will happen to the total revenue of the Blitz Company after the price increase in comparison to its total revenue before the price increase.
8. Calculate the income elasticity of demand for Mach3 detergent using the average data of the independent variables. What is your conclusion about the kind of the Mach3 detergent (i.e. is it a normal, cyclical, necessity, luxury or an inferior product)?
9. Calculate the cross-price elasticity of demand. What is the relation between Mach3 detergent and the product of the competitor?
10. What is the possible problem in such a regression analysis based on cross-sectional data? Does such a problem exist in this specific case of the Mach3 detergent? Verify your answer based on the plot between the error term and the price of the detergent.
11. Based on the regression results, what can you say about the presence of multicollinearity in the model (i.e. does it exist in this specific case)? Verify your answer by providing the matrix of correlation.
12. Use the regression equation to predict the weekly demand point estimate (i.e. Q in cases) for the Mach3 detergent in five new regional markets with the following characteristics as in table 2:

Table 2: Five New Regional Markets and Their Characteristics

New Reginal Market	Weekly Demand in Cases Q	Price per Case P in	Competitor Price CP in	Advertising A in	Household Income HI in
A		115	90	7900	41234
B		122	101	8120	39845
C		116	87	9050	47543
D		140	82	7780	53560
E		133	79	9960	39870

1. Give the 95% confidence level interval estimate of each of the new regional markets base on the regression results.
2. Run the multiple nonlinear regression of this case based on the data provided in table 1 above and please remember to submit the Excel output sheet of the regression. Based on the results of the this regression:
3. Write the estimated equation in its power format.
4. What do the coefficients of the independent variables represent?
5. Based on (b) above do you justify a proposal put forward by the Chief Financial Officer to the board of directors to raise the price per case of Mach3 detergent by 30%? Verify your answer by checking what will happen to the total revenue of the Blitz Company after the price increase in comparison to its total revenue before the price increase.
6. Compare your answer of (c) above with your answer in part (10) above. Which one do you think is more reliable? (Hint: For this part you have to use the idea of the Root Mean Square Error (RMSE) which I will explain in chapter 6).