Posted: October 27th, 2022

Assessment 3: Individual Assignment

BUSINESS STATISTICS
Assessment three: Individual Assignment
Directions:
That is a person task with a complete of 40 marks. The allocation of marks is as follows:
Statistical Assessment with Excel File: 32
Skilled Report: eight
Whole: 40
Report Construction
The response have to be offered within the type of knowledgeable report with not more than 10 pages (excluding the quilt web page).
The construction of your skilled report should embrace:
A Title,
An Govt Abstract,
An Introduction,
Assessment, and
Conclusions.
Submission
It’s essential to submit an digital copy of your task on Canvas. See the hooked up Template of your submission for extra particulars.
Excel Work
This task requires the usage of Microsoft Excel. Utilizing Knowledge Assessment Device-Pack will help tremendously in getting by the task necessities.
That you must submit the Excel file alongside together with your report. The excel file must be clear and thoroughly organized and should present all workings underlying the Skilled report and related statistical Assessment. Will probably be handled as an appendix to your report, i.e., not included within the web page rely.
DO NOT depart references to the excel workbook throughout the Skilled report as responses to the questions. You will have to take related outcomes out of your Excel workbook and incorporate them into your report. The report must be standalone.
Presentation Directions:
Your written skilled report ought to adjust to the next presentation requirements:
Typed utilizing a regular skilled font sort (e.g. Instances Roman), 12-point font measurement.
1.5-line spacing, numbered pages, and clear use of titles and part headings.
Delivered as a Phrase (.doc or .docx) or PDF (.pdf) file.
Checked for spelling, typographical and grammatical errors. The place related, spherical to three decimal locations.
With all related tables and charts, the report ought to be not more than 10 pages lengthy.
Downside Description:
This can be a additional Assessment of the public-private pay hole for people with related productive traits within the Australian inhabitants. Mahuteau et al. (2017) report that (1) on common public sector staff earn about 5.1% extra hourly wages than these within the personal sector and (2) that this wage premium (comparatively increased wages in public sector) is barely increased for females than males. Systematic remuneration variations for workers with related productive capabilities probably has each effectivity and fairness penalties.
To be able to estimate the extent of discrimination within the job market the place public servants with the an identical labour market traits as their personal counterparts obtain totally different wages, you’ll estimate a set of linear regression fashions.
Since that is an extra Assessment on the public-private pay hole, the content material within the Introduction part of your report could overlap with the one within the Group Assignment submitted earlier. Nonetheless, you might be inspired to develop/supply new background supplies.
You’ll use the identical dataset as in Assignment 2. The info are drawn from the 2019 Family, Earnings and Labour Dynamics in Australia (HILDA) survey. The pattern used for Assessment contains 219 full-time Australian staff within the age group 21-65.
The dataset values may be interpreted and be used to create applicable variables as follows:
Employee’s Wages: the variable wage data hourly earnings in AU dollars of full-time staff [note the unit of measurement]
Sector: Private and non-private sector identification information may be transformed right into a dummy variable named as “public”, with 1 representing public worker else zero for personal worker.
Gender: utilizing the gender identification information, create a dummy variable male that identifies male worker as 1 and feminine as zero.
Instructional attainment: the dummy variable diploma = Sure (1) if the person has a bachelor’s diploma or increased qualification, and = No (zero) for decrease than diploma .
Age: is the numerical information sort reflecting the age of an worker.
Marital Standing: the dummy variable married = Sure (1) if the person is married and No (zero), in any other case.
Find the information file (IndividualBusStats.xls) on CANVAS.
REQUIREMENT:
Earlier than estimating the regression equation, conduct an general preliminary Assessment of the connection between staff’ wages and
sector,
gender,
instructional attainment,
age and
marital standing.
Use tables and/or applicable graphs for the specific variables (male, public, diploma, married) and the numerical variable (age).
Interpret your findings by evaluating the earnings of the counterparts based mostly on every of those dummy variables and in addition clarify the sort of relationship you observe between staff’ earnings and age?
(5 marks)
Use a easy linear regression to estimate the connection between staff’ earnings and the variable public (Mannequin A). It’s possible you’ll use the Knowledge Assessment Device Pack. Primarily based on the Excel regression output:
Write down the estimated regression equation,
Perform any related two-tailed speculation take a look at of the slope coefficient utilizing the crucial worth strategy, on the 5% significance degree, displaying the step-by-step workings/diagram in your report.
Interpret your speculation take a look at outcomes.
(three marks)
Use the next a number of regression mannequin to discover the connection of staff’ earnings with variables associated to sector, gender, instructional attainment, age and marital standing
Mannequin B: Wages=ß_0+ß_1 public+ß_2 male+e
Mannequin C: Wages=ß_0+ß_1 public+ß_2 male+ß_3 age+e
Mannequin D: Wages=ß_0+ß_1 public+ß_2 male+ß_3 age+ß_3 schooling+e
Mannequin E: Wages=ß_0+ß_1 public+ß_2 male+ß_3 age+ß_4 schooling+ß_5 married+e
Primarily based on the Excel regression outputs, choose the very best mannequin and clarify why it’s the greatest.
Write down the estimated equation for the very best mannequin and interpret the slope coefficients,
Primarily based on the very best mannequin, perform any related two-tailed speculation checks for every particular person slope coefficient utilizing the p-value strategy, on the 5% significance degree.
Perform an general significance take a look at utilizing the p-value strategy.
Rigorously interpret your speculation take a look at ends in c) and d).
Are your regression findings close to public-private wage hole broadly in keeping with these reported within the research of Mahuteau et al. (2017)?
(9 marks)
Examine the coefficients of public variable in Mannequin A and Mannequin E. Clarify rigorously why the outcomes are totally different, relating your dialogue to sector wage discrimination.
(four marks)
Primarily based on the Mannequin E, predict the earnings of a 40-year-old male, college certified and married public employee. Subsequent, predict the earnings of a feminine employee with the identical traits.
(2.5 marks)
Primarily based on the end in Question Assignment 5, how will your end in Question Assignment 5 change if the male/feminine employee is 50 years previous? Clarify with none calculation.
(2.5 marks)

One other conclusion from Mahuteau et al. (2017) is that the wage premium (comparatively increased wages) for the employees within the public sector is barely increased for females than males. Conduct applicable regression analyses to look at whether or not your findings based mostly on 2019 information are broadly in keeping with these reported within the research.
(four marks)
In case you may request extra information to check the components that affect staff’ earnings, what additional variables would you request? Focus on two such variables, explaining why you select them and the way every of your proposed variables may very well be measured within the regression mannequin. [You could draw evidence from journal articles, newspapers, etc]
(2 marks)
(5 + three + 9 + four + 2.5 + 2.5 + four + 2 = 32 marks)
(Skilled report = eight marks)
Reference:
Mahuteau, S, Mavromaras, Okay, Richardson, S & Zhu, R 2017, Public–personal sector wage differentials in Australia, Financial Report, vol. 93, pp. 105-121.

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