In the model Wage = B0 + B1 Education + U, if U is correlated with Educatiom and 8, > 0 the oLS estimators areSelect one: a.biased and consistentb,unbiased and inconsistentc,positively biased and consistentd,biased and inconsistent e.negatively biased and inconsistentf,unbiased and consistent

Imagine you regressed earnings of individuals on a constant (intercept), a dummy variable (‘male’) which takes on the value 1 for males and is 0 otherwise, and another dummy variable (‘female’) which takes on the value 1 for females and 0 otherwise. Because females typically earn less than males, you would expect ________. a. none of the OLS estimators to exist because there is perfect multicollinearity b. both coefficients to be the same distance from the constant, one above and the other below c. the coefficient for ‘male’ to have a positive sign, and for ‘female’ a negative sign d. the coefficient for ‘male’ to have a negative sign, and for ‘female’ a positive sign

Andy wants to examine the impact of years of education (EDUC) and labour productivity(PROD) on monthly salary (SALARY) of a sample of 150 teachers at StellenboschMunicipality. However, it is difficult to measure productivity. Hence, it is approximated asfollows: PROD = Pupil/Teacher ratio of the school where the teacher works. In other words,the regression model is:).,( PRODEDUCfSALARY = Andy argues that various reasonslead to the presence of error terms in the above regression. Explain any five of these reasons.Always refer to the above regression in your explanationQUESTION 2Busisiwe would like to investigate the relationship between weekly party hours (PARTY) andmodule test marks (MARKS) of a sample of 12 second-year Microeconomics students. Theinformation is presented in the following table:Student PARTY (X) MARKS (Y)[A] 02 90[B] 03 85[C] 04 82[D] 04 76[E] 04 75[F] 05 74[G] 05 70[H] 06 62[I] 07 55[J] 08 52[K] 10 43[L] 14 402.1 Complete the following table with the aid of the data in the above table: XYXY XY 2X5562.2 By using the OLS method to derive the parameters of the bivariate regression:.^2^1^PARTYMARKS +=Show all calculations.Hints:22^2XnXYXnYXiii−−=XY ^2^1−=

In this exercise we examine which factors might influence the wages of employees. To do so, the variable wage is regressed on the variables educ, tenure, tensq, female, married, and m_female.Table 1: Descriptive StatisticsVariable Explanationwage Average hourly wage (in €)educ Years of educationtenure Employment duration (current employer)tensq = tenure × tenurefemale dummy (= 1 if female)married dummy (= 1 if married)m_female      Interaction term (= married × female)The corresponding Stata output is:Source | SS df MS N. of obs. = 526 + F(6, 519) = 57.23 Model | 2851.181 6 475.197 Prob > F = 0.000 Residual | 4309.233 519 8.303 R-squared = 0.398 + Adj. R-sq. = 0.391 Total | 7160.414 525 13.639 Root MSE = 2.882 wage | Coef. S. Err. t-stat. P > |t| [95% Conf. Int.] + educ |0.522 0.046 ? ? ? ? tenure | 0.263 0.046 5.69 0.000 0.172 0.354 tensq | -0.005 0.002 -2.77 0.006 -0.008 -0.001 female | -0.321 0.408 -0.79 0.431 -1.123 0.480 married | 1.807 0.389 4.65 0.000 1.043 2.571 m_female | -2.326 0.526 ? ? ? ? _cons | -2.012 0.662 -3.04 0.002 -3.313 -0.711 Reference: Wooldridge, J. (2013). Introductory Econometrics, 5E. © 2013 South-Western, a part of Cengage, Inc. Reproduced by permission. www.cengage.com/permissions.Does educ have a significant relationship with the outcome wage? State the associated null hypothesis and alternative hypothesis for the coefficient βeduc. Also, determine its statistical significance at the 5 percent significance level in a two-sided test. Which one is the correct answer?Answer 1H0:   vs.   H1: c(0.05, 526-6-1) = 1.645⇒ t > c⇒ H0 can be rejected at the 5 percent significance level.Answer 2H0:   vs.   H1: c(0.05, 526-6-1) = 1.645⇒ t > c⇒ H0 can be rejected at the 5 percent significance level.Answer 3H0:   vs.   H1: c(0.05, 526-6-1) = 1.960⇒ t > c⇒ H0 can be rejected at the 5 percent significance level.Answer 4H0:   vs.   H1: c(0.05, 526-6-1) = 1.960⇒ t > c⇒ H0 can be rejected at the 5 percent significance level.

According to the Becker/Rosen human capital model of educational choice, workers invest in education until:          Group of answer choicesThe marginal utility from education is equal to zero.The marginal rate of return from education is equal to their discount rate.The percent increase in lifetime earnings from one more year of education is 0.The marginal rate of return from education becomes negativeThe marginal utility from education equals to the cost of education.

We want to estimate the treatment effect of D on y via a linear regression model y equals b subscript 0 plus b subscript 1 x plus r D plus u, where x is an exogenous control variable. If the value of the treatment variable D is randomly assigned, then: a. the OLS estimate of r is unbiased. b. the OLS estimate of r is biased due to sample selection. c. the OLS estimator is BLUE. d. the error u is homoskedastic.