This question is concerned with the value of Major League Baseball (MLB) franchises. The data was obtained for all U.S. franchises across the 1992 to 1997 period.  

Here you do not need to run the regression; we will focus on hypothesis testing and interpretation.  The regression results are provided below, using 176 observations. The variable Franchise Value is the dependent variable.

            Adjusted R-squared = 0.57

The variables are defined as follows:

Franchise Value =  the present discounted value of the team's net revenue stream at the point in time (in millions of 1997 US Dollars)

Income = City's Real Per Capita Income (1997 US Dollars);

Pop = City's population (millions);

Place = Team's final divisional standings in the previous season (min=1, max=7);

New Team = equals 1 for the first 3 years the team enters the league, 0.8 in the 4^th year, 0.6 in the 5^th year, 0.4 in the 6^th year, 0.2 in the 7^th year, and 0 beyond [we interpret this coefficient in the same manner as any other variable - increasing this variable by one whole unit (i.e. changing from zero to 1) will have some differential effect on franchise value]; 

New Facility = dummy equal to one if the team is playing in a new stadium, and zero otherwise;

Regid = dummy equal to one if the team has what the authors characterize as a "regional identity" (i.e. the 'Colorado' Rockies and the 'Florida' Marlins have a "regional identity" where the 'St. Louis' Cardinals and the 'Cincinnati' Reds do not);

Regpop = Regid * Pop = this is an "interaction term".  The authors include this variable to test the specific hypothesis of whether the effect of "regional identity" varies with market size.

a. Explain briefly how each of the variables affects the value of an MLB franchise (i.e., use the variable definitions above to interpret, in words, the coefficient estimates with regard to each variable).

b. Find 90% confidence intervals for the coefficients on Pop, Place, and Income.