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Using the regression data below: Ignoring uncertainty regarding the coefficient estimates. In other words, assume your demand exactly equals the demand specified by your coefficient
Using the regression data below:
Ignoring uncertainty regarding the coefficient estimates. In other words, assume your demand exactly equals the demand specified by your coefficient estimates. Your memo should contain the following information:
- Give a recommendation on which of Market 1 or 2 to enter.
- Assuming only a single price can be set, state what price should be charged in each of the markets and how price should vary with the advertising budget. State what level of profit you expect from each of the two markets. Please note under this demand specification, using the single-pricing markup rule can be difficult since the demand elasticity changes as we move along the demand curve. As such, you will likely bebetter off performing a "brute-force" analysis. In other words, calculating the profits at a variety of relevant advertising/price/etc. levels.
- Discuss the value (if there is any) of doing additional market research to learn what prices other firms are charging in Market 2. Give advice on whether this research should be conducted.
- Offer conclusions, for future reference and guidance, about what "kind" of market your firm should look to for subsequent market expansions based on your quantitative analysis.
Regression Statistics | ||||||||
Multiple R | 0.981 | |||||||
R Square | 0.962 | |||||||
Adjusted R Square | 0.957 | |||||||
Standard Error | 29493.745 | |||||||
Observations | 48 | |||||||
ANOVA | ||||||||
df | SS | MS | F | Significance F | ||||
Regression | 6 | 910215513269.525 | 151702585544.921 | 174.395 | 0.000 | |||
Residual | 41 | 35665120548.788 | 869880988.995 | |||||
Total | 47 | 945880633818.312 | ||||||
Coefficients | Standard Error | t Stat | P-value | Lower 95% | Upper 95% | Lower 95.0% | Upper 95.0% | |
Intercept | 282031.242 | 59886.492 | 4.709 | 0.000 | 161088.018 | 402974.467 | 161088.018 | 402974.467 |
Price | -81266.483 | 9541.152 | -8.517 | 0.000 | -100535.231 | -61997.735 | -100535.231 | -61997.735 |
Advertising | 3.664 | 0.597 | 6.139 | 0.000 | 2.458 | 4.869 | 2.458 | 4.869 |
Competitor's Price | 19969.543 | 8075.832 | 2.473 | 0.018 | 3660.069 | 36279.017 | 3660.069 | 36279.017 |
Income | 0.052 | 1.293 | 0.041 | 0.968 | -2.559 | 2.664 | -2.559 | 2.664 |
Population | 0.031 | 0.002 | 20.445 | 0.000 | 0.028 | 0.034 | 0.028 | 0.034 |
Time | 1918.019 | 1951.702 | 0.983 | 0.331 | -2023.523 | 5859.561 | -2023.523 | 5859.561 |
Demand Specification | ||||||||
Qband=a+bPband+cA+dPcomp+eI+fPop+gT+u | ||||||||
Inputs | ||||||||
Market 1 | Market 2 | |||||||
Price | $5.49 | $4.20 | ||||||
Compet Price | $4.99 | $3.70 | ||||||
Advertising | $15,000.00 | $15,000.00 | ||||||
Advertising 2 | $7,500.00 | $7,500.00 | ||||||
Income | $20,000.00 | $16,000.00 | ||||||
Population | 2,010,000.00 | 5,500,000.00 | ||||||
Time | 9 | 9 | ||||||
Cost | $3.00 | $3.00 | ||||||
Market 1 | Market 2 | |||||||
Qband | $71,494.17 | $259,230.61 | ||||||
Gross Profit | $392,503.01 | $1,088,768.56 | ||||||
Operating Profit | $163,020.49 | $296,076.73 | ||||||
Comp Elasticity | 1.39 | 0.29 | ||||||
Own Elasticity | -6.24 | -1.32 | ||||||
Income Elasticity | 0.01 | 0.00 | ||||||
Advertisting Elasticity | 0.77 | 0.21 | ||||||
Pop Elasticity | 0.88 | 0.66 | ||||||
Time Elasticity | 0.24 | 0.07 | ||||||
Marginal Cost | $3 | $3 | ||||||
Optimal Mark-Up | 1.190824744 | 4.157936015 | ||||||
Optimal Pricing | $3.57 | $12.47 | ||||||
Profit Price w/ advertsiting at $7500 | $4.52 | $5.03 | ||||||
Profit Price w/ advertsiting at $15000 | $4.70 | $5.28 | ||||||
Profit w/ advertsiting at $7500 | $179,225.21 | $326,033.66 | ||||||
Profit w/ advertsiting at $15000 | $218,095.06 | $375,935.20 | ||||||
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