Reference no: EM132368458
Econometrics Problems -
Problem One (to be done before the lab session) Do Problem on page 203 of the textbook "Principles of Econometrics". You can exclude (d).
When estimating wage equations, we expect that young, inexperienced workers will have relatively low wages and that with additional experience their wages will rise, but then begin to decline after middle age, as the worker nears retirement. This life-cycle pattern of wages can be captured by introducing experience and experience squared to explain the level of wages. If we also include years of education, we have the equation
WAGE = β1 + β2EDUC + β3EXPER + β4EXPER2 + e
(a) What is the marginal effect of experience on wages?
(b) What signs do you expect for each of the coefficients β2, β3, and β4? Why?
(c) After how many years of experience do wages start to decline? (Express your answer in terms of β's.)
(d) The results from estimating the equation using 1000 observations in the file cps4c_small.dat are given in Table 5.9 on page 204. Find 95% interval estimates for
(i) The marginal effect of education on wages.
(ii) The marginal effect of experience on wages when EXPER = 4.
(iii) The marginal effect of experience on wages when EXPER = 25.
(iv) The number of years of experience after which wages decline.
Problem Two (to be done during the lab session) Review sections 5.1 to 5.3 and 5.5 of Chapter 5 of "Using Eviews for Principles of Econometrics, Fourth Edition". It would be a good idea to work through this at home. Download the files cocaine.wfl and cocaine.def and complete exercise on pages 204 and 205 of the textbook. Exclude (d) and (e).
The file cocaine.dat contains 56 observations on variables related to sales of cocaine powder in northeastern California over the period 1984-1991. The data are a subset of those used in the study Caulkins. J. P. and R. Padman (1993). "Quantity Discounts and Quality Premia for Illicit Drugs," Journal of the American Statistical Association, 88, 748-757. The variables are
PRICE = price per grain 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 = β1 + β2QUANT + β3QUAL + β4TREND + e
(a) What signs would you expect on the coefficients β2, β3, and β4?
(b) Use your computer software to estimate the equation. Report the results and interpret the coefficient estimates. Have the signs turned out as you expected?
(c) What proportion of variation in cocaine price is explained jointly by variation in quantity, quality, and time?
(d) It is claimed that the greater the number of sales, the higher the risk of getting caught. 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.
(e) 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.
(f) What is the average annual change in the cocaine price? Can you suggest why price might be changing in this direction?
Attachment:- Assignment - Econometrics Problems.rar