The following data from a random sample of individuals that are 25 years old. Note, wage is the hourly earnings in US dollars and educ is years of education. i 1 2 3 4 wage 12.18 12.18 20.09 7.39 educ 13 11 16 12 Consider the following model: In(wage)-Bo+B₂educ+u. Calculate the estimate of B₁. Round your answer to two decimal places.
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- A male oriented jeans manufacturer is interested in designing and marketing jeans exclusively designed for women. In this case, the primary segmentation variable the jeans manufacturing is using is: A Gender В Age C Race D Usage rateexplain how they find the quantities using MRS = MRTWe have learned what problems arise from drawing a figure incorrectly. It is a histogram of hourly wage. The number of observations in a data set is 1 million. Discuss the problems of the following figure. How do we draw a figure to show the information of the hourly wage accurately? Draw ideal picture. Can we roughly make a relative frequency table from this picture.
- Compute the R² using the following information. What does this number mean? Wage = 4.43 +0.61Edu + e n = 1089, SST = 37211.6, SSE 37211.6, SSE 19848.2 R² = = = 0.4666. 46.66% of the variation in wage can be explained by education. R² = 0.5334. 53.34% of the variation in wage can be explained by education. R² = 0.61.61% of the variation in wage can be - explained by education. R² = 0.3043. 30.43% of the variation in wage can be explained by education.A researcher estimates a model of CEO salary. She regresses this variable on CEO tenure and CEO tenure squared. The coefficient on those two variables are 20.29 and -1.14, respectively. Calculate the value of CEO tenure at which the impact of this variable on CEO salary is optimised..What is Heteroscedastic? And is there a way to fix data in case of heteroscedasticity presence ?
- Consider the following regression estimates (ID6) Source Model Residual Total wage educ exper exper2 _cons inverse u-shaped SS C. linear d. exponential 1927.87673 5232.53756 7160.41429 df -.0046123 -3.96489 642.625576 3 522 10.0240183 525 Coef. Std. Err. .5953429 .0530251 .268287 .0368969 .000822 .7521526 MS 13.6388844 Number of obs F(3, 522) Prob > F R-squared Adj R-squared Root MSE t P>|t| 0.000 11.23 7.27 0.000 -5.61 0.000 -5.27 0.000 = .4911741 .1958023 -.006227 -5.442508 = = = 526 64.11 0.0000 0.2692 0.2650 3.1661 [95% Conf. Interval] .6995118 .3407717 where wage is hourly wage in US$, educ is years of education, exper is years of work experience and exper2 is experience squared (exper* exper). According to these estimates, what is the functional form of the relationship between experience and predicted wage when we hold education constant? a. u-shaped b.i -.0029975 -2.487272P Take a Test - Panela Kancefwere Personal - Microsoft Edge A https/www.mathxl.com/Student/PlayerTest.aspx?testid-2339589008centerwin 2021FL ECON-2301-20005 (T Th 08:00 AM-09:20 AM) Pamela Kamdefwere & 09/25/2112:36 = Test: Exam 1 Question 3 This Test: 64 pts possible Submit Tes st If the current market price is $25, the market will achieve equilibrium by 50- O A. a price increase, increasing the quantity supplied and decreasing the quantity demanded, 45- O B. a price decrease, decreasing the supply and increasing the demand. 40- O C. a price decrease, decreasing the quantity supplied and increasing the quantity demanded. 35- 30- O D. a price increase, increasing the supply and decreasing the demand. 25 20- 15- 10- 5- 0- 100 200 300 400 500 600 700 800 900 1000 1100 Quantity O Time Remaining: 01:24:39 Next 11:59pm Pearcon ($) aoudAssume 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: Bo
- O Macmillan Learning A study is designed to examine the relationship between employees' job satisfaction and the amount of sleep they get. Think about creating a data set for this study. Assume that job satisfaction is measured by a scale of 1 (very dissatisfied) to 5 (very satisfied). Cases: Label Variable(s): Quantitative Variable(s): Categorical Variable(s): Explanatory Variable(s): Response Variable(s): Employee's name Answer Bank Job satisfaction Employees Amount of sleep6. A study analyzing college faculty salaries obtained the results shown below. The dependent variable is academic year salary in dollars. Independent variables Intercept Number of textbooks published Number of articles published Number of dissertations supervised Rating of public service Number of university committees served on Years of experience Index of teacher ratings Coefficient 21,155 23,568 586 489 389 156 2,189 530 -9,293 -6,410 21,919 Dummy var. for being an English professor Dummy var. for being female Dummy var. for having a Ph.D. R-squared = 0.68, n = 596 a) Precisely, interpret what the articles published coefficient tells us. c) The R² is 0.68. Precisely, what does this mean? T-statistic 2.35 7.21 5.37 66.85 5.65 10.02 126.92 0.01 18.75 0.80 10.01 b) Do these results support the hypothesis that there is gender discrimination in the academic community? Briefly, why or why not?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?