Question

Title: Measuring Employment, Unemployment, and Labor Force Participation Consider a small economy composed of six people: Alex, Becky, Clancy, Eileen, Kate, and Hubert. Each person's employment status is described in the following table. Complete the right half of the following equation to reflect the labor force participation rate reported by the BLS. Labor Force Participation Rate = According to this formula, what is the labor force participation rate of this economy of six people? a) 40% b) 50% c) 80% d) 100% Complete the right half of the following equation to reflect the unemployment rate reported by the BLS. Unemployment Rate = __ According to this formula, what is the unemployment rate of this economy of six people? a) 40% b) 50% c) 80% d) 100%

Name: 4 measuring employment unemployment and labor force participation consider a small economy composed of six people alex becky clancy eileen kate and hubert each persons employment status is d 20905
Uploaded: 2023-07-27T05:25:33-08:00
Duration: 27 s
Channel: Numerade
Description: 4 measuring employment unemployment and labor force participation consider a small economy composed of six people alex becky clancy eileen kate and hubert each persons employment status is d 20905

          Title: Measuring Employment, Unemployment, and Labor Force Participation

Consider a small economy composed of six people: Alex, Becky, Clancy, Eileen, Kate, and Hubert. Each person's employment status is described in the following table.

Complete the right half of the following equation to reflect the labor force participation rate reported by the BLS.

Labor Force Participation Rate
= ______________

According to this formula, what is the labor force participation rate of this economy of six people?
a) 40%
b) 50%
c) 80%
d) 100%

Complete the right half of the following equation to reflect the unemployment rate reported by the BLS.

Unemployment Rate
= ________________

According to this formula, what is the unemployment rate of this economy of six people?
a) 40%
b) 50%
c) 80%
d) 100%

4 measuring employment unemployment and labor force participation consider a small economy composed of six people alex becky clancy eileen kate and hubert each persons employment status is d 20905

Added by Kevin C.

Close

Principles of Economics

Gregory Mankiw 8th Edition

Instant Answer

Solved by Expert Kamlesh Goyal

Step 1

The labor force includes all individuals who are either employed or actively seeking employment. In this case, we have six people in total, and we need to identify how many of them are in the labor force. From the table, we can see that Alex, Becky, Clancy, and Show more…

Show all steps

Please give Ace some feedback

Your feedback will help us improve your experience

Thanks for your feedback!

Title: Measuring Employment, Unemployment, and Labor Force Participation Consider a small economy composed of six people: Alex, Becky, Clancy, Eileen, Kate, and Hubert. Each person's employment status is described in the following table. Complete the right half of the following equation to reflect the labor force participation rate reported by the BLS. Labor Force Participation Rate = ______________ According to this formula, what is the labor force participation rate of this economy of six people? a) 40% b) 50% c) 80% d) 100% Complete the right half of the following equation to reflect the unemployment rate reported by the BLS. Unemployment Rate = ________________ According to this formula, what is the unemployment rate of this economy of six people? a) 40% b) 50% c) 80% d) 100%

Play audio

Feedback

Powered by NumerAI

Kamlesh Goyal and 86 other subject Microeconomics educators are ready to help you.

Ask a new question

Labs

Want to see this concept in action?

NEW

Explore this concept interactively to see how it behaves as you change inputs.

View Labs

Key Concepts

Key Concept

Premium Feature

Explore the core concept behind this problem.

Key Concept

Premium Feature

Explore the core concept behind this problem.

Recommended Videos

While an abundance of research has addressed the issue of employee turnover, this work has been largely conducted in the full-time employment context. There is a great need to increase research attention toward the study of part-time workers, given that entire industries rely on part-time labor as a major source of employment, as well as the continuing increase in employment opportunities in the part-time labor sector (see Feldman, 1990; Nardone, 1993). Consistent with Tansky et al.'s (1997) observation, little research has focused on differences among part-time workers, and this research has been largely inconsistent and non-theoretical (e.g. Lee and Johnson, 1991; McGinnis and Morrow, 1990). Specifically, there is a need to develop a fuller understanding of the nature of the part-time workforce itself and those factors that influence behavior among this portion of the workforce. One such area is that of turnover behavior. Regardless of the model employed, much of the research has drawn attention to the following categories of influence on turnover: Push or work-related factors The aspects which may "push" an individual into voluntarily leaving his/her organization are associated with the nature of organizational life itself and include such important factors as job satisfaction. The negative relationship between job satisfaction and turnover has been empirically validated by many studies of turnover (e.g. Arnold and Feldman, 1982). The rationale for this view is that a dissatisfied worker will escape from an unfavorable work situation. The higher the satisfaction with pay/financial rewards received the lower the expected level of turnover behavior (Dalton and Todor, 1979, 1982; Porter and Steers, 1973). However, these findings need to be assessed in the part-time work context. In addition, performance-reward contingencies have a significant and negative association with turnover, according to the research conducted among full-time employees. External or pull factors Influences which could "pull" an individual out of his/her present employment (i.e. cause turnover) are: personal and household income levels, wage earner status in the household, family commitments, as well as acceptable job alternatives (Mobley et al., 1979a). With regard to income levels, the research in the full-time employment context has suggested that main household wage earners will be less likely to exhibit turnover behavior than those individuals who are not the main wage earners for their households. The rationale for this view is that main household wage earners possess relatively greater responsibility for the financial viability of their households than do secondary wage earners. For this reason, it is expected that main wage earners will have less freedom and flexibility to explore job alternatives (i.e. lower turnover), without incurring substantial penalties (loss of primary income) for their household units. It is of interest to consider whether this relationship holds in the part-time employment context. Individual characteristics. A large number of research studies have identified the importance of individual or demographic factors as predictors of job turnover (e.g. Arnold and Feldman, 1982; Cotton and Tuttle, 1986; Lee and Mowday, 1987). First, the research has largely supported the argument that education is positively related to employee turnover (e.g. Arnold and Feldman, 1982; Brief and Aldag, 1980). Tansky et al. (1997) suggested that while this might also hold true for part-time workers, the reverse relationship might also apply. Second, the research evidence that has been generated suggests that older workers are typically more satisfied than younger workers, in the part-time context (e.g. Greenberger and Steinberg, 1996). The research has also suggested that younger part-timers are more likely to have higher rates of absenteeism and turnover (e.g. Kahne, 1985). Third, there are numerous research studies which suggest that a negative relationship exists between tenure and turnover (e.g. Steers, 1977). The research has indicated that relatively high turnover occurs among new employees (e.g. Mobley, 1982a, 1982b). Finally, a number of research studies have suggested that married employees are less likely to quit an organization than are unmarried employees (e.g. Cotton and Tuttle, 1986; Youngblood et al., 1983). Again, this relationship needs to be more fully assessed in the part-time employment context.

Sri K.

need-urgent-will-definitely-upvote-and-rate-subject-research-methodology-while-an-abundance-of-research-has-addressed-the-issue-of-employee-turnover-this-work-has-been-largely-conducted-in-t-84898

Subject: Research Methodology While an abundance of research has addressed the issue of employee turnover, this work has been largely conducted in the full-time employment context. There is a great need to increase research attention toward the study of part-time workers, given that entire industries rely on part-time labor as a major source of employment, as well as the continuing increase in employment opportunities in the part-time labor sector (see Feldman, 1990; Nardone, 1993). Consistent with Tansky et al.'s (1997) observation, little research has focused on differences among part-time workers, and this research has been largely inconsistent and non-theoretical (e.g. Lee and Johnson, 1991; McGinnis and Morrow, 1990). Specifically, there is a need to develop a fuller understanding of the nature of the part-time workforce itself and those factors that influence behavior among this portion of the workforce. One such area is that of turnover behavior. Regardless of the model employed, much of the research has drawn attention to the following categories of influence on turnover: Push or work-related factors The aspects which may "push" an individual into voluntarily leaving his/her organization are associated with the nature of organizational life itself and include such important factors as job satisfaction. The negative relationship between job satisfaction and turnover has been empirically validated by many studies of turnover (e.g. Arnold and Feldman, 1982). The rationale for this view is that a dissatisfied worker will escape from an unfavorable work situation. The higher the satisfaction with pay/financial rewards received, the lower the expected level of turnover behavior (Dalton and Todor, 1979, 1982; Porter and Steers, 1973). However, these findings need to be assessed in the part-time work context. In addition, performance-reward contingencies have a significant and negative association with turnover, according to the research conducted among full-time employees. External or pull factors Influences which could "pull" an individual out of his/her present employment (i.e. cause turnover) are: personal and household income levels, wage earner status in the household, family commitments, as well as acceptable job alternatives (Mobley et al., 1979a). With regard to income levels, the research in the full-time employment context has suggested that main household wage earners will be less likely to exhibit turnover behavior than those individuals who are not the main wage earners for their households. The rationale for this view is that main household wage earners possess relatively greater responsibility for the financial viability of their households than do secondary wage earners. For this reason, it is expected that main wage earners will have less freedom and flexibility to explore job alternatives (i.e. lower turnover), without incurring substantial penalties (loss of primary income) for their household units. It is of interest to consider whether this relationship holds in the part-time employment context. Individual characteristics A large number of research studies have identified the importance of individual or demographic factors as predictors of job turnover (e.g. Arnold and Feldman, 1982; Cotton and Tuttle, 1986; Lee and Mowday, 1987). First, the research has largely supported the argument that education is positively related to employee turnover (e.g. Arnold and Feldman, 1982; Brief and Aldag, 1980). Tansky et al. (1997) suggested that while this might also hold true for part-time workers, the reverse relationship might also apply. Second, the research evidence that has been generated suggests that older workers are typically more satisfied than younger workers, in the part-time context (e.g. Greenberger and Steinberg, 1996). The research has also suggested that younger part-timers are more likely to have higher rates of absenteeism and turnover (e.g. Kahne, 1985). Third, there are numerous research studies which suggest that a negative relationship exists between tenure and turnover (e.g. Steers, 1977). The research has indicated that relatively high turnover occurs among new employees (e.g. Mobley, 1982a, 1982b). Finally, a number of research studies have suggested that married employees are less likely to quit an organization than are unmarried employees (e.g. Cotton and Tuttle, 1986; Youngblood et al., 1983). Again, this relationship needs to be more fully assessed in the part-time employment context. Source: McBey and Karakowsky (2000) "Examining sources of influence on employee turnover in the part-time work context", Leadership Organization Dev. J. 21 (3):136-144.

Ayushi S.

question-in-introduction-to-econometrics-3rd-edition-e62-a-run-a-regression-of-years-of-completed-education-ed-on-distance-to-the-nearest-college-dist-what-is-the-estimated-slope-b-run-a-reg-99468

E6.2 (a) Run a regression of years of completed education (ED) on distance to the nearest college (Dist). What is the estimated slope? (b) Run a regression of ED on Dist, but include some additional regressors to control for characteristics of the student, the student’s family, and the local labor market. In particular, include as additional regressors Bytest, Female, Black, Hispanic, Incomehi, Ownhome, DadColl, Cue80, and Stwmfg80. What is the estimated effect of Dist on ED? (c) Is the estimated effect of Dist on ED in the regression in (b) substantively different from the regression in (a)? Based on this, does the regression in (a) seem to suffer from important omitted variable bias? (d) Compare the fit of the regression in (a) and (b) using the regression standard errors. Why are the standard errors so similar in regression (b)? (e) The value of the coefficient on DadColl is positive. What does this coefficient measure? (f) Explain why Cue80 and Stwmfg80 appear in the regression. Are the signs of their estimated coefficients (+ or -) what you would have believed? Interpret the magnitudes of these coefficients. (g) Bob is a black male. His high school was 20 miles from the nearest college. His base-year composite test score (Bytest) was 58. His family income in 1980 was $26,000, and his family owned a home. His mother attended college, but his father did not. The unemployment rate in his county was 7.5%, and the state average manufacturing hourly wage was $9.75. Predict Bob’s years of completed schooling using the regression in (b). (h) Jim has the same characteristics as Bob except that his high school was 40 miles from the nearest college. Predict Jim’s years of completed schooling using the regression in (b). Data: Documentation for CollegeDistance Data These data are taken from the High School and Beyond survey conducted by the Department of Education in 1980, with a follow-up in 1986. The survey included students from approximately 1100 high schools. The data used here were supplied by Professor Cecilia Rouse of Princeton University and were used in her paper "Democratization or Diversion? The Effect of Community Colleges on Educational Attainment," Journal of Business and Economic Statistics, April 1995, Vol. 12, No. 2, pp 217-224. The data in CollegeDistance exclude students in the western states. The data in CollegeDistanceWest includes only those students in the western states. Series in Data Set Name Description ed Years of Education Completed (See below) female 1 = Female/0 = Male black 1 = Black/0 = Not-Black Hispanic 1 = Hispanic/0 = Not-Hispanic bytest Base Year Composite Test Score. (These are achievement tests given to high school seniors in the sample) dadcoll 1 = Father is a College Graduate/ 0 = Father is not a College Graduate momcoll 1 = Mother is a College Graduate/ 0 = Mother is not a College Graduate incomehi 1 = Family Income > $25,000 per year/ 0 = Income ≤ $25,000 per year. ownhome 1 = Family Owns Home / 0 = Family Does not Own Home urban 1 = School in Urban Area / 0 = School not in Urban Area cue80 County Unemployment rate in 1980 stwmfg80 State Hourly Wage in Manufacturing in 1980 dist Distance from 4yr College in 10's of miles tuition Avg. State 4yr College Tuition in $1000's Years of Education: Rouse computed years of education by assigning 12 years to all members of the senior class. Each additional year of secondary education counted as one year. Students with vocational degrees were assigned 13 years, AA degrees were assigned 14 years, BA degrees were assigned 16 years, those with some graduate education were assigned 17 years, and those with a graduate degree were assigned 18 years.

Sri K.

Recommended Textbooks

Principles of Economics

Gregory Mankiw 8th Edition