Ask Statistics and Probability Expert

1. Using the dataset WAGE1.dta…

a) Regress wages on education and experience but do so in a way that produces standardized betas. That is, you will have to take each variable and standardize it by subtracting from it the mean and dividing by the standard deviation, i.e.x_standard= (x-x_bar)/x_std.

b) Interpretation the coefficients on education and experience?

c) Now regress log wage (already defined as “lwage” in the dataset) on education, experience, non white, female, married. Now run the same regression but including a variable that is the interaction between female and education. Interpret the coefficient on the interaction term. describe what happens to the standard error of the main education effect and why. Would you recommend keeping this interaction term in the equation? Why or why not?

d) Now drop the female X education interaction, but add another interaction, between female and married. What is the effect of being married for men? Now report the coefficient and standard error of the marriage effect for women. Is it statistically different from zero? (hint: for the standard error of a linear combination of estimates, use “lincom”):

e) Manually find out the adjusted R-squared for the regression in (d). Note: take advantage of the Stata output. Type “help regress” and scroll to the bottom. There you will see that the model sum of squares (i.e. the Sum of Squares describeed SSE) can be referenced as e(mss).

However, you can only access these results right after the regression has been run and before performing any other calculations. So, run the regression in (e) again, though you can do so without printing the results to the screen using the syntax “quietly: regress y x”. Confirm that your R-squared is the same as the one produced by Stata.

f) Building on the regression in (d), add the occupation variables: profocc, clerocc, servocc. What happens to the estimated rate of return to education? Why does this happen? If our goal is to correctly identify the causal effect of education, would you recommend including or excluding these occupation variables? describe why.

g) Manually find out the adjusted R-squared for the model you just ran? Compare with the result in (e). From an adjusted R-squared perspective, did the extra variables (profocc, clerocc, servocc) add much explanatory power to the model?

2. The dataset KIELMC.dta has information about houses sold in 1978 and 1981 in a Massachusetts town. In 1981 an incinerator was built.

a) Regress the log of the house’s sale price against the log of distance from the incinerator for houses sold in 1978 only. Run the same regression for houses sold in 1981 only. (Hint: use the clause “if year==1978” to select just that year for the regression). Does the result for 1978 make sense, given that the incinerator wasn’t built yet? What could describe this result?

b) Add the following variables to the regression: log of square footage of lot (lland), log of square footage of house (larea), log of distance to interstate (linst), age of house, squared age of house, number of rooms, number of bathrooms. Run the regression again for 1978, and again for 1981. What are the estimated effects of distance from the incinerator in 1978 and 1981 now? Are they significant and do they make sense?

describe why these results are so different from the ones in a.

c) For the regression from part b), perform a Chow Test to determine whether the 1978 and the 1981 data have the same parameters. Given the results from b) what do you expect the outcome of this test to be? (Hint: quietly run a pooled regression, a 1978 regression, and a 1981 regression, saving the SSR each time. Remember that the sum of squared residuals (aka residual sum of squares) can be accessed after the regression by typing “scalar ssr = e(rss)”).

d) Again using the regression from b), for the data, at what age does a house reach its maximum or minimum value? Which is it, a max or a min, and how do you know? Does that make sense? Are there any houses older than this in the data?

e) Rerun the 1981 equation but including the squared log of the distance to the interstate. What happens to the coefficient on distance to the incinerator? What does this tell you about the importance of functional form?

3) This exercise uses the dataset GPA1.dta.

a) Run a regression of colGPA against all of the following: hsGPA, ACT, PC, skipped, alcohol, greek, bgfriend

b) Now run the “restricted” regression that you need to construct an F-test of the joint hypothesis that the three “social” variables (alcohol, greek, and bgfriend) do not matter. Construct that F-statistic. Are these social variables jointly significant at alpha=1%?

describe how you know.

c) Confirm that you can get a similar result using Stata’s test command, which performs a Wald test, which is very similar to the F-test you just ran. The syntax is test varlist.

d) Now run a Linear Probability Model where bgfriend is the dependent variable and alcohol, greek, and colGPA are the independent variables. What is the interpretation of the coefficient on on alcohol?

e) A critique of the LPM is that the predicated values might value outside the 0-1 range. (probabilities can only range from 0 to 1). find out the predict values from (d). What percent of the predicted values are outside the 0-1 range? (Hint: an easy way to do this is to generate an 0/1 variable where 1 indicates that yhat was out of the 0-1 range. Then simply take the mean of the 0/1 variable).

f) We know that the Linear Probability Model suffers from heteroskedasticity. Test for heteroskedasticity using the special case of the White Test. Do you reject the null hypothesis of homoscedasticity at the 5% level, at the 10% level? (Hint: use the version of the F-stata for testing the overall significance of a regression).

g) Re-run the LPM but this time telling Stata to find out robust standard errors, i.e. specifying the vce(robust) option when running the regression. How do these standard errors compare to those in (d)? How about the coefficient estimates?

Statistics and Probability, Statistics

  • Category:- Statistics and Probability
  • Reference No.:- M93542

Have any Question?


Related Questions in Statistics and Probability

Introduction to epidemiology assignment -assignment should

Introduction to Epidemiology Assignment - Assignment should be typed, with adequate space left between questions. Read the following paper, and answer the questions below: Sundquist K., Qvist J. Johansson SE., Sundquist ...

Question 1 many high school students take the ap tests in

Question 1. Many high school students take the AP tests in different subject areas. In 2007, of the 144,796 students who took the biology exam 84,199 of them were female. In that same year,of the 211,693 students who too ...

Basic statisticsactivity 1define the following terms1

BASIC STATISTICS Activity 1 Define the following terms: 1. Statistics 2. Descriptive Statistics 3. Inferential Statistics 4. Population 5. Sample 6. Quantitative Data 7. Discrete Variable 8. Continuous Variable 9. Qualit ...

Question 1below you are given the examination scores of 20

Question 1 Below you are given the examination scores of 20 students (data set also provided in accompanying MS Excel file). 52 99 92 86 84 63 72 76 95 88 92 58 65 79 80 90 75 74 56 99 a. Construct a frequency distributi ...

Question 1 assume you have noted the following prices for

Question: 1. Assume you have noted the following prices for paperback books and the number of pages that each book contains. Develop a least-squares estimated regression line. i. Compute the coefficient of determination ...

Question 1 a sample of 81 account balances of a credit

Question 1: A sample of 81 account balances of a credit company showed an average balance of $1,200 with a standard deviation of $126. 1. Formulate the hypotheses that can be used to determine whether the mean of all acc ...

5 of females smoke cigarettes what is the probability that

5% of females smoke cigarettes. What is the probability that the proportion of smokers in a sample of 865 females would be greater than 3%

Armstrong faber produces a standard number-two pencil

Armstrong Faber produces a standard number-two pencil called Ultra-Lite. The demand for Ultra-Lite has been fairly stable over the past ten years. On average, Armstrong Faber has sold 457,000 pencils each year. Furthermo ...

Sppose a and b are collectively exhaustive in addition pa

Suppose A and B are collectively exhaustive. In addition, P(A) = 0.2 and P(B) = 0.8. Suppose C and D are both mutually exclusive and collectively exhaustive. Further, P(C|A) = 0.7 and P(D|B) = 0.5. What are P(C) and P(D) ...

The time to complete 1 construction project for company a

The time to complete 1 construction project for company A is exponentially distributed with a mean of 1 year. Therefore: (a) What is the probability that a project will be finished in one and half years? (b) What is the ...

  • 4,153,160 Questions Asked
  • 13,132 Experts
  • 2,558,936 Questions Answered

Ask Experts for help!!

Looking for Assignment Help?

Start excelling in your Courses, Get help with Assignment

Write us your full requirement for evaluation and you will receive response within 20 minutes turnaround time.

Ask Now Help with Problems, Get a Best Answer

Why might a bank avoid the use of interest rate swaps even

Why might a bank avoid the use of interest rate swaps, even when the institution is exposed to significant interest rate

Describe the difference between zero coupon bonds and

Describe the difference between zero coupon bonds and coupon bonds. Under what conditions will a coupon bond sell at a p

Compute the present value of an annuity of 880 per year

Compute the present value of an annuity of $ 880 per year for 16 years, given a discount rate of 6 percent per annum. As

Compute the present value of an 1150 payment made in ten

Compute the present value of an $1,150 payment made in ten years when the discount rate is 12 percent. (Do not round int

Compute the present value of an annuity of 699 per year

Compute the present value of an annuity of $ 699 per year for 19 years, given a discount rate of 6 percent per annum. As