Suppose you are estimating a wage regression, where salary is the dependent variable and age, years of education and a dummy variable for male are your independent variables. You are interested in measuring how salary differs between those who have at least a college education with those who have less than a college education. If a person is considered as having a college education when she has more than 12 years of education, how can you measure the difference in salary between college and non-college educated individuals? Select one: a. Multiply coefficient for years of education in original regression by 12 O b. Re-estimate model replacing years of education with a dummy variable for college c. Re-estimate model replacing years of education with a dummy variable for college and one for no college d. Re-estimate model interacting years of education with a dummy variable for oollogo

Suppose you are estimating a wage regression, where salary is the dependent variable and age, years of education and a dummy variable for male are your independent variables. You are interested in measuring how salary differs between those who have at least a college education with those who have less than a college education. If a person is considered as having a college education when she has more than 12 years of education, how can you measure the difference in salary between college and non-college educated individuals? Select one: a. Multiply coefficient for years of education in original regression by 12 O b. Re-estimate model replacing years of education with a dummy variable for college c. Re-estimate model replacing years of education with a dummy variable for college and one for no college d. Re-estimate model interacting years of education with a dummy variable for oollogo

Managerial Economics: Applications, Strategies and Tactics (MindTap Course List)

14th Edition

ISBN:9781305506381

Author:James R. McGuigan, R. Charles Moyer, Frederick H.deB. Harris

Publisher:James R. McGuigan, R. Charles Moyer, Frederick H.deB. Harris

Chapter7: Production Economics

Section: Chapter Questions

Problem 1.3CE

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We know that discrimination exists. It influences wages, but also many other dimensions over the life cycle which affect wages indirectly. I run OLS regression with variables wage, age, female and degree. The dependent variable is log(wage) and we replace the variables female and degree with the interaction term. However, discrimination is not included among the observed regressors. Given that omitting confounding variables from regression model can bias the coefficient estimates, omitting discrimination would lead to biased results. Could you please help me provide an example of how unobserved gender discrimination can affect my OLS estimates. [Hint: think about ways in which discrimination can invalidate OLS assumptions.].
MP 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
Given the following data X (consumers of teff) or popn 3 6 8 1 13 13 14 Y ( teff consumption) 8 6 10 12 12 14 20 year 2013 2014 2015 2016 2017 2018 2019 Estimate the regression equation, Y= a+bX, Where Y denotes demand for teff while X is consumers of teff (population) By assuming demand for teff is only affected by its consumers, find the amount demand for teff in the year 2022 if the populations (consumers of teff) are about 18 people? (Hint: use the least square method, parameter a and b can be estimated by solving the two linear equations) SY= na+ bSX SXY=aSX +b Where n is number of years. For example, Estimate the sales for 2012, 2015 and fit a linear regression equation and draw a trend line.ar X Sales (Y) XY X2 year X Sales (Y) XY X2 2002 1 22734 22734 1 2003 2 24731 49462 4 2004 3 31489 94467 9 2005 4 44685 178740 16 2006 5 55319…
Suppose a researcher is using a panel data set on n = 10,000 workers over T = 20 years (from 2000 through 2019) that contains the workers’ earnings, sex, education, and age. The researcher is interested in the effect of education on earnings. Give some examples of unobserved person-specific variables that are correlated with both education and earnings. Can you think of examples of time-specific variables that might be correlated with education and earnings? How would you control for these person-specific and time-specific effects in a panel data regression?
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 * EDUC
What is Heteroscedastic? And is there a way to fix data in case of heteroscedasticity presence ?
Some MPs 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. (300 words)
look at the influence of mileage on the sale price of each brand ofautomobile. Postulate the following statistical models,?_ℎ????? = ?0 + ?1?????? + ?? and ?_?ℎ??? = ?0 + ?1?????? + ?? with ??~?(0, ?2).For each model (‘model_honda’ and ‘model_chev’) perform the following,Comment on the miles variable after examining it with hist() and summary() commands.What does the assumption of non-random independent variable imply about how thedata must be collected if the same miles variable is used for both brand of automobile?
does the simple regression of log (price) on log (nox) produce an upward or a downward biased estimator of β1?
Candy is a Year 4 full-time undergraduate student majoring in marketing at a private university in Hong Kong and she is going to be graduated after the summer break. She has collected some data from the Student Careers and Affairs Office (SCAO) related to her job planning. According to the graduate employment surveys conducted for the last two years by the private university, the average salary earned by the graduates of her programme is constant at around $14,000. Actually, Candy is quite disappointed. In view of this, Candy is considering to participate in an one-year internship program launched by the SCAO after her graduation. In other words, she would enter the job market “formally” one year later if she joins the internship program. Finally, with the help of the SCAO, she could get an internship offer from a famous marketing company in Hong Kong. The monthly salary provided by the company is $12,000 while a good reference letter would be prepared for the interns completing the…
Candy is a Year 4 full-time undergraduate student majoring in marketing at a private university in Hong Kong and she is going to be graduated after the summer break. She has collected some data from the Student Careers and Affairs Office (SCAO) related to her job planning. According to the graduate employment surveys conducted for the last two years by the private university, the average salary earned by the graduates of her programme is constant at around $14,000. Actually, Candy is quite disappointed. In view of this, Candy is considering to participate in an one-year internship program launched by the SCAO after her graduation. In other words, she would enter the job market “formally” one year later if she joins the internship program. Finally, with the help of the SCAO, she could get an internship offer from a famous marketing company in Hong Kong. The monthly salary provided by the company is $12,000 while a good reference letter would be prepared for the interns completing the…
Give typing answer with explanation and conclusion if education is heavily affected by IQ and IQ is closely correlated with both wage and education level, how would a regression of wage on education be biased? What regression violation is this? (For econometrics)