A breakfast this morning in which a group of economists presented the economic outlook for the Midwest region for the coming year. According to their forecasts, the likelihood of a recession is as high as 40 percent. It is imperative that we be prepared in case a recession hits the country.

Our research intern pulled some data on household income from the last economic slowdown and we matched it up with the number of subscriptions for our video services. At first glance, it looks like we didn't have too many cancellations. However, in looking a little closer, it appears that a significant number of subscribers downgraded their service to a lower tier.

As you know, our two most popular tiers of television programming are Favored TV for $80 per month and Basic TV for $40 per month. The programming fees that we pay for the Favored TV are $48.50 per subscriber, while programming fees for Basic TV are $18.50. Both sets of customers have maintenance, billing, and service costs of $9.20 per subscriber. Currently, in this region, we have 27,800 Favored TV subscribers and 17,800 Basic TV subscribers.

One member of our quant group ran a regression based on incomes and subscriptions from that two-year period, but I can't quite figure out what it means. Can you use the attached data to calculate the impact on our subscriptions, revenue, and profit in the Midwest region if we were to sustain a recession that led to a 2 percent decline in average household income?

SUMMARY OUTPUT - FAVORED TV
Regression Statistics		Dep. Variable - Natural Log of Favored TV Subscribers
Multiple R	0.836
R Square	0.699
Adjusted R Square	0.686
Standard Error	0.027
Observations	24
ANOVA
	df	SS	MS	F	Significance F
Regression	1	0.036	0.036	51.176	0.000
Residual	22	0.016	0.001
Total	23	0.052
	Coefficients	Standard Error	t Stat	P-value	Lower 95%	Upper 95%
Intercept	-8.882	2.652	-3.349	0.003	-14.383	-3.382
Natural Log of Income	1.793	0.251	7.154	0.000	1.274	2.313
SUMMARY OUTPUT - BASIC TV
			Dep. Variable - Natural Log of Basic TV Subscribers
Regression Statistics
Multiple R	0.727
R Square	0.529
Adjusted R Square	0.508
Standard Error	0.004
Observations	24
ANOVA
	df	SS	MS	F	Significance F
Regression	1	0.000	0.000	24.709	0.000
Residual	22	0.000	0.000
Total	23	0.001
	Coefficients	Standard Error	t Stat	P-value	Lower 95%	Upper 95%
Intercept	11.988	0.440	27.223	0.000	11.074	12.901
Natural Log of Income	-0.207	0.042	-4.971	0.000	-0.293	-0.121

Answer rating: 100% (QA)

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