se that we want to check whether it is true that on the average men (MM) earn in of 500 pesos more per week than women (uw) in a certain job classification. Which choices below is a suitable alternative hypothesis against the null hypothesis of w = 500?
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- The following equation has been used to estimate wages: ln (Y) = ln (Yo) + b2EDU + b3 EXPER + b4 EXPER2 + e where Y is income, Y0 is income of someone with no education or experience, EDU is years of education and EXPER is experience in the field. If you suspect males earn higher wages than females and that the wage difference increases with education how would you adjust the econometric model to estimate wages? OPTIONS - a. include a binary variable for gender, MALE b. include an interaction term equal to MALE* EDUC c. include an indicator variable for MALE and one for FEMALE d. include a binary variable for MALE and an interaction term equal to MALE * EDUCSuppose the researcher considers the following model : Wage = Bo+B,Female + u, and runs OLS, using wage data on 250 randomly selected male workers and 280 female workers. The researcher has obtained the estimated equation as Wage = 15 (1.00) 3 Female, R = 0.05. (0.5) In the equation, Wage is measured in dollars per hour, Female is a binary variable that is equal to 1 if the person is a female and O if the person is a male. The numbers in the parentheses are the standard errors of the coefficients. Which Statement is NOT correct? The coefficient of Female, -3.00, is statistically significant at 5%. O The p-value for the test that Ho: B = 0, H : B 0 is less than 0.05. This regression may suffer omitted variable bias. R Since insignificant. is too low, the wage difference between men and women is The researcher can increase R- by including more regressors in the model.Suppose we estimate the following model of hourly wage as a function of years of education, given data on a sample of individuals: wage = Bo + Biedu + u Suppose that for one individual in the sample wâge = 32 and û = -3 . What is this person's actual hourly wage? 29 O 32 O 35 3.
- Assume that the dummy variables Marriedal if married (0 if not married), Sex=1if male (0 if female), and that you estimate the equation: loglwage) le + B,'Married + B'Sex + B,(Married Sex). The estimated log wage for an unmarried woman can be estimated by: BoMP believe that there is a causal relationship between earnings and years of schooling. They show you an estimate of the impact of years of schooling on annual earnings: There are two groups of individuals – group 1 and group 2. Group 1 on average earns £60,000 per year with the average level of post-compulsory education of 6 years, while group 2 earns on average £40,000 with the average post-compulsory education of 4 years. The MPs conclude that the annual return to an additional year of education is 25% using the following equation [(£60,000-£40,000)/40,000]/(6-4)=25%. Ignoring time preferences and discounting, and if both groups face the same cost of schooling, you need to explain to the MPs why this is not a good estimate of the annual return to an additional year of education. Propose methods to the MPs to deal with the problem“It is hypothesized that there is a difference in job satis¬faction between those who receive regular feedback on their job performance and those who receive irregular feedback.” is an example of which type of hypothesis? a. Not a hypothesis b. Null hypothesis c. Directional hypothesis d. Non-directional hypothesis
- Suppose we are interested in evaluating the impact on wages of being a college graduate and of residing in California. To this end we define the following dummy variables if college graduate if not college graduate coll = ncoll = if not college graduate if college graduate 1 cali = if residing in California S 1 if not residing in California ncali = if not residing in California if residing in California and for wages denoting yearly wages, we estimate the following model of returns to education wages = B1 coll+ B2ncoll + B3 cali + B4(coll x cali) + e where E[e|coll, cali] = 0. Which parameter or combination of parameters measures the increase in expected wages from obtaining a college degree (comparing to not having a college degree) when residing California? O a. None of the other options is correct O b. Bi – B2 O c. B1 – B2 + ß4 O d. B4 O e. Bi + B3 – ßi – B4 O f. Bi + B4 – ß2 – B4 Clear my choiceConsider the following regression estimates (FN2) Linear regression belavg abvavg female married _cons b. 1 wage O C. 5 O d. 4 Robust Coef. Std. Err. 3047845 3150202 2820787 -1.063254 .0693348 -2.751963 .9686236 .2612646 6.699098 .2889831 Number of obs F(4, 1255) Prob > F R-squared Root MSE t P>|t| -3.49 0.001 0.22 0.826 -9.76 0.000 3.71 0.000 23.18 0.000 |||||||||| = = .45606 6.132155 = -1.661197 -.5486894 -3.305361 = = [95% Conf. Interval] 1,260 56.35 0.0000 0.1121 4.3987 assume that MLR 1-6 hold. In the regression above, how many coefficients (including the constant) are statistically significant at the 1% level? a. 3 -.4653108 .687359 -2.198565 1.481187 7.266042Latest statistics obtained from Board of Engineers Malaysia (BEM) official website states thatthere is currently a total of 14,794 registered Professional Engineers in Malaysia, as shown inFigure 1. This is slightly below 10% of the total Graduate Engineers registered with BEM.Most developed nations have an engineer to population ratio of 1:100, that is 1 engineer forevery 100 persons in the population. This means that there is still a shortage of registeredengineers in Malaysia since our population is approximately 32.7 million. Discuss the impact of a shortage in registered Graduate Engineers and ProfessionalEngineers to the nation. a) You are required to provide at least three (3) different impactsand include any credible references to support your discussion.b) Recommend at least four methods to increase the number of registered ProfessionalEngineers in Malaysia.(Answer must be at least 1500 words)
- 1. Suppose that a pay equity plan has just been put in place in your organization. The pay equity consulting firm did a job evaluation and assigned points to each of the male-dominated and female-dominated jobs. It then estimated the following male and female pay lines by ordinary least squares regression, where Y denotes annual earnings, P denotes job evaluation points, and the subscripts m and f denote male and female respectively: Ym = 5,000 + 100Pm Yf = 4,000 + 80Pf Assume that you were an employee in a female-dominated job and that your job evaluation score was 200. a. What would your pay be before pay equity? 2. In the above example, assume that the average job evaluation score was 300 points in male-dominated jobs and 200 points in female-dominated jobs. Page 387 a. What is the average pay in male-dominated jobs and in female-dominated jobs? b. Use a Oaxaca decomposition to determine the average pay differential between male- and female-dominated jobs into two components: a…Suppose now that that Y denotes the annual salaries (in thousands of dollars) for US citizenswho are in their 40s and 50; and X is an indicator (dummy) variable: X = 1 if that workergraduated from college and X=0 otherwise. Suppose the average annual salary for this age groupis $45,000 and the estimate for β is β~ = 15 with s.e. = 5.b. What is the upper and lower bound of a 95-percent confidence interval for β~ ?c. In a credible research design attending college would be randomly assigned to a largesample of potential students. Propose such a research design. What are the potential ethicalissues? d. The central problem with drawing credible casual inferences is that the counterfactual cannot be observed. What is the counterfactual in this case? What is a good strategy forobtaining the counter-factual? What are the ethical issues of doing this? b-d please!!!A commonly used functional form for wage equations is InW = a + bR + cR2, where W is the annual wage, R is the fatal accident rate, and the other job and employee characteristics are omitted for simplicity. 20 20 1. Derive an expression for the value of a statistical life. 2. Why is it important to include R2 in the wage equation?
