Reference no: EM132394497

Assignment: ECON 2311Q Econometrics I, University of Connecticut

1. The data file Growth contains data on average growth rates from 1960 through 1995 for 65 countries, along with variables that are potentially related to growth. In this exercise, you will investigate the relationship between growth and trade.

(a) Construct a scatterplot of average annual growth rate ( Growth) on the average trade share (TradeShare). Does there appear to be a relationship between the variables?

(b) One country, Malta, has a trade share much larger than the other countries. Find Malta on the scat- terplot. Does Malta look like an outlier?

(c) Using all observations, run a regression of Growth on TradeShare. What is the estimated slope? What is the estimated intercept? Use the regression to predict the growth rate for a country with a trade share of 0.5 and with a trade share equal to 1.0.

(d) Estimate the same regression, excluding the data from Malta. Answer the same questions in (c).

(e) Plot the estimated regression functions from (c) and (d). Using the scatterplot in (a), explain why the regression function that includes Malta is steeper than the regression function that excludes Malta.

(f) Where is Malta? Why is the Malta trade share so large? Should Malta be included or excluded from the analysis?

2. The data file Earnings_and_Height contains data on earnings, height, and other characteristics of a random sample of U.S. workers. In this exercise, you will investigate the relationship between earnings and height.

(a) What is the median value of height in the sample?

(b) i.Estimate average earnings for workers whose height is at most 67 inches.

ii. Estimate average earnings for workers whose height is greater than 67 inches.

iii.On average, do taller workers earn more than shorter workers? How much more? What is a 95% confidence interval for the difference in average earnings?

(c) Construct a scatterplot of annual earnings (Earnings) on height (Height). Notice that the points on the plot fall along horizontal lines. (There are only 23 distinct values of Earnings). Why? (Hint: Carefully read the detailed data description.)

(d) Run a regression of Earnings on Height. i.What is the estimated slope?

ii.Use the estimated regression to predict earnings for a worker who is 67 inches tall, for a worker who is 70 inches tall, and for a worker who is 65 inches tall.

(e) Suppose height were measured in centimeters instead of inches. Answer the following questions about the Earnings on Height (in cm) regression.

i. What is the estimated slope of the regression?

ii. What is the estimated intercept?

iii. What is the R2?

iv. What is the standard error of the regression?

(f) Run a regression of Earnings on Height, using data for female workers only. i.What is the estimated slope?

ii. A randomly selected woman is 1 inch taller than the average woman in the sample. Would you predict her earnings to be higher or lower than the average earnings for women in the sample? By how much?

(g) Repeat (f) for male workers.

(h) Do you think that height is uncorrelated with other factors that cause earning? That is, do you think that the regression error term, say ui, has a conditional mean of zero, given Height (xi)?

3. The data file Birthweight_Smoking, which contains data for a random sample of babies born in Pennsyl- vania in 1989. The data include the baby's birth weight together with various characteristics of the mother, including whether she smoked during the pregnancy. In this exercise you will investigate the relationship between birth weight and smoking during pregnancy.

(a) In the sample:

i. What is the average value of Birthweight for all mothers?

ii. For mothers who smoke?

iii. For mothers who do not smoke?

(b) i. Use the data in the sample to estimate the difference in average birth weight for smoking and nonsmoking mothers.

ii. What is the standard error for the estimated difference in (i)?

iii. Construct a 95% confidence interval for the difference in the average birth weight for smoking and nonsmoking mothers.

(c) Run a regression of Birthweight on the binary variable Smoker.

i. Explain how the estimated slope and intercept are related to your answers in parts (a) and (b). ii.Explain how the s.e.(βˆ1) is related to your answer in b(ii).

iii.Construct a 95% confidence interval for the effect of smoking on birth weight.

(d) Do you think smoking is uncorrelated with other factors that cause low birth weight? That is, do you think that the regression error term, say ui, has a conditional mean of zero, given Smoking (xi)?

Instruction: (1) Please hand in a hardcopy of your .log file, which contains your STATA codes and your answers to the questions, before the class on 10/30/2019. Please make sure you number each question in your .do file.

(2) You can either include your answers to the questions in your .do file as comments (everything you include in .do file will be included in .log file as well) or answer them separately. If your answers are in your .log file, you only need to print out the .log file otherwise you need to submit both .log file and your answers to the questions.

(3) For creating .log file, you need to specify the command of creating .log file at the beginning of your .do file, for example "log using hw2_FirstLastName.log, replace" and use "log close" at the end of your .do file.

Information related to above question is enclosed below:

Attachment:- Assignment.rar