Demand can be estimated with experimental data, time-series data, or cross-section
data. In this case, cross-section data appear in the Excel file. Soft drink consumption in
cans per capita per year is related to six-pack price, income per capita, and mean
temperature across the 48 contiguous states in the United States.
1. Given the data, please construct the demand estimation for soft drink consumption in
the United States by
(1) a multiple-linear regression equation (10%), and
(2) a log-linear (exponential) regression equation (10%).
2. Given the MS Excel output in Question 1, please compare the two regression
equations’ coefficient of determination (R-square), F-test and t-test. Which equation
is a good (better) fit? Which equation shows the stronger overall significance to
predict the future demand? Which equation will you choose as a better estimation for
quantity demanded? Which equation will you choose as a better estimation for
elasticities? Explain your answer in the language of statistics. (20%)