Question

In: Economics

Let's analyze the results of a fictional set of data for variation 1 of the Unemployment...

Let's analyze the results of a fictional set of data for variation 1 of the Unemployment Compensation experiment. The table below shows the worker costs and buyer values assigned to the students in variation 1 of the experiment. A worker's cost of working is what that worker has to give up in order to work for one hour. The cost of working includes work-related expenses plus the unemployment compensation the worker passes up by working. An employer's buyer value is the amount of revenue that employer would earn from hiring a worker for one hour. Recall that these particular workers are low skilled.

In variation 1 of this experiment, the government offered $1 of unemployment compensation to any worker who did not work. So, each worker's cost of working includes the $1 of unemployment compensation offered by the government. This table shows the workers' costs of working and the employers' buyer values in variation 1.

Worker Number Worker's Cost of
Working in Variation 1 ($)
Employer Number Employer's Buyer Value
in Variation 1 ($)
1 5.50 1 17.50
2 6.00 2 16.50
3 6.50 3 15.50
4 7.00 4 14.50
5 7.50 5 13.50
6 8.00 6 12.50
7 8.50 7 11.50
8 9.00 8 10.50
9 9.50 9 9.50
10 10.00 10 8.50

a)What is the highest wage employer 4 would be willing to pay to hire a worker for one hour?

b)What is the lowest wage worker 4 would be willing to accept to work for one hour? ​c)What equilibrium wage does supply and demand analysis predict for this market? d)What equilibrium quantity of labor does supply and demand analysis predict for this market? e)What gain from hiring a single worker does supply and demand analysis predict for employer 4 in equilibrium? f)What gain from working does supply and demand analysis predict for worker 4 in equilibrium?

Solutions

Expert Solution


Related Solutions

Let's talk that scenario and work with some fictional data from it: Let's imagine there was...
Let's talk that scenario and work with some fictional data from it: Let's imagine there was a question on the survey that asks "On average, how many times a day do you worry about COVID-19, either for yourself, family, or community? Below is some data for 10 respondents.  In the space below,describe all of the steps you would use to calculate the appropriate type of t-test (independent or paired samples), given we want to compare Trump voters to Clinton voters. For...
Describe a fictional example and generate a small data set in which data are heteroscedastic and...
Describe a fictional example and generate a small data set in which data are heteroscedastic and you need to apply a GLS.
Calculate the standard deviation and coefficient of variation for each data set below, be sure to...
Calculate the standard deviation and coefficient of variation for each data set below, be sure to attach an Excel file to show the work. Explain which of the two mentioned measures can more accurately specify which of these two data sets has more variability or dispersion in their data values, and why. Data set 1= 11,12,13,14,15,16,17,18,19,20 Data set 2= 8,9,28,29,5,4,1,3,2,10
Here is a data set on bird populations with color variation. The Y gene is autosomal...
Here is a data set on bird populations with color variation. The Y gene is autosomal with a Y allele (yellow plumage) and y allele (brown plumage), where Y is dominant to y (Y > y). The survey shows phenotypic frequencies for a large mainland population on the coast of Ecuador and a small island population. The island population was founded in 1960 by a small flock of birds. Thereafter, there has been some gene flow between the mainland and...
The standard project is to use multiple regression analysis to analyze a data set. The data...
The standard project is to use multiple regression analysis to analyze a data set. The data set is a study of student persistent enrolling in the next semester based on Gender, Age, GPA, a 22 questionnaire on self-efficacy, and student enrollment status. The educational researcher wants to study the relationship between student enrollment status as it relates to gender, age, GPA, and the total response to a 22 questionnaire survey. a. The estimated multiple regression analysis equation. b. Does the...
Analyze unemployment and inflation data for the (1950's-1960's) as to their relation to output and growth....
Analyze unemployment and inflation data for the (1950's-1960's) as to their relation to output and growth. explain how inflation and unemployment are calculated for the data presented. Discuss how changes in both are related to changes in GDP growth.
Let's consider a limited set of climate data, examining temperature differences in 1948 vs 2018
7.19 Global warming, Part I. Let's consider a limited set of climate data, examining temperature differences in 1948 vs 2018. We sampled 197 locations from the National Oceanic and Atmospheric Administration's (NOAA) historical data, where the data was available for both years of interest. We want to know: were there more days with temperatures exceeding 90°F in 2018 or in 1948?12 The difference in number of days exceeding 90'F (number of days in 2018- number of days in 1948) was calculated...
Trend in Ga vs. US unemployment rate -- why the variation ?
Trend in Ga vs. US unemployment rate -- why the variation ?
Purpose: To learn how to analyze data from a two-way Anova and apply the results to...
Purpose: To learn how to analyze data from a two-way Anova and apply the results to a research scenario. Instructions: Enter the data below into the SPSS Data Editor (download the .sav file from D2L to check your work). Run a two-way analysis of variance and create a line graph depicting the group means. Use your results to answer the questions below, and then submit in D2L. Research Scenario: You have been raising Bombina orientalis, or Oriental fire-bellied toads, and...
An important practice is to check the validity of any data set that you analyze. One...
An important practice is to check the validity of any data set that you analyze. One goal is to detect typos in the data, and another would be to detect faulty measurements. Recall that outliers are observations with values outside the “normal” range of values of the rest of the observations. Specify a large population that you might want to study and describe the type numeric measurement that you will collect (examples: a count of things, the height of people,...
ADVERTISEMENT
ADVERTISEMENT
ADVERTISEMENT