Hypothesis tests in STATA
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1. The file cocaine.dta contains 56 observations on variables related to
sales of cocaine powder in northeastern California over the period 1984-
1991. The variables are
price = price per gram in dollars for a cocaine sale
quant = number of grams of cocaine in a given sale
qual = quality of the cocaine expressed as percentage purity
trend = a time variable with 1984 =1 up to 1991 =8.
Consider the regression model
price = B1 + B2quant + B3qual + B4trend + e (1)
(a) What proportion of variation in cocaine price is explained by variation
in quantity, quality, and time?
(b) It is claimed that the greater the number of sales, the higher the
risk of getting caught; and thus, sellers are willing to accept a
lower price if they can make sales in larger quantities. Set up H0
and H1 that would be appropriate to test this hypothesis. Carry
out the hypothesis test.
(c) Test the hypothesis that the quality of cocaine has no influence
on price against the alternative that a premium is paid for better
quality cocaine.
(d) What is the average annual change in the cocaine price? Can you
suggest why price might be changing in this direction?
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Solution Summary
Hypothesis tests in STATA are examined.
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1. The file cocaine.dta contains 56 observations on variables related to sales of cocaine powder in northeastern California over the period 1984- 1991. The variables are
price = price per gram in dollars for a cocaine sale
quant = number of grams of cocaine in a given sale
qual = quality of the cocaine expressed as percentage purity
trend = a time variable with 1984 =1 up to 1991 =8.
Consider the regression model
price = B1 + B2quant + B3qual + B4trend + e (1)
(a) What proportion of variation in cocaine price is explained by variation in quantity, quality, and time?
use STATA commend: regress price quant qual trend
we get the following ...
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