Does It Pay to Graduate from an 'Elite' University in Australia?

Carroll, David; Heaton, Chris; Tani, Massimiliano

doi:10.1111/1475-4932.12492

Cited by 15 publications

(9 citation statements)

References 21 publications

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“…Completion of a Creative Arts degree, however, was not a good financial investment for either men or women. The importance of choice of discipline over other factors, such as choice of university, has been emphasised in other studies of the economic benefits of attending university in Australia (Carroll, Heaton, & Tani, 2019; Koshy, Seymour, & Dockery, 2016; Norton & Cherastidtham, 2018).…”

Section: Resultsmentioning

confidence: 99%

Is a university degree still a worthwhile financial investment in Australia?

Corliss

Daly

Lewis

2020

Australian Journal of Education

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Since 2006 there have been significant changes in the labour market for university graduates, most notably the Global Financial Crisis of 2007 and the subsequent downturn in gross domestic product growth, and a huge expansion in university places. This article presents estimates of the monetary returns in Australia associated with the completion of bachelor degrees in 2016 for a range of fields of study and compares them to the estimates for 2006. The results show that for the median person, there are still good monetary incentives to complete these degrees and the private rate of return compares favourably with the long-term real bond rate. However, the article also concludes that the return to an individual investing in bachelor education had mostly declined in the period 2006–2016. There is, again, considerable variation between disciplines and for some, completion of a bachelor degree does not yield positive returns. The key factors determining the monetary rate of return are the discipline of the degree and the graduates’ subsequent labour force status. Graduates in full-time employment in most disciplines avoided being among those with low (or negative) rates of return. In addition, there is some evidence of skills mismatch and over skilling among the lowest paid university graduates.

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Section: Resultsmentioning

confidence: 99%

Is a university degree still a worthwhile financial investment in Australia?

Corliss

Daly

Lewis

2020

Australian Journal of Education

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“…Consequently, graduates of such institutions may enjoy greater opportunities and financial rewards than their peers from less distinguished institutions. Thus, the academic community has investigated the potential impact of attending a top-tier university on an individual's earning capacity, with Carroll et al (2019) concluding that such attendance can yield significant monetary gains immediately post-graduation. In addition, media reports, such as those authored by Mishra (2020), Majumdar andAlawadhi (2019), andBasu (2018), serve to underscore the significant influence of premier institutions, where learners receive a superior education relative to non-premier institutions and are likelier to secure high-paying jobs.…”

Section: Theoretical Background and Constructsmentioning

confidence: 99%

Dissecting the compensation conundrum: a machine learning-based prognostication of key determinants in a complex labor market

Jaiswal

Gupta²,

Tiwari

2023

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PurposeAmidst the turbulent tides of geopolitical uncertainty and pandemic-induced economic disruptions, the information technology industry grapples with alarming attrition and aggravating talent gaps, spurring a surge in demand for specialized digital proficiencies. Leveraging this imperative, firms seek to attract and retain top-tier talent through generous compensation packages. This study introduces a holistic, integrated theoretical framework integrating machine learning models to develop a compensation model, interrogating the multifaceted factors that shape pay determination.Design/methodology/approachDrawing upon a stratified sample of 2488 observations, this study determines whether compensation can be accurately predicted via constructs derived from the integrated theoretical framework, employing various cutting-edge machine learning models. This study culminates in discovering a random forest model, exhibiting 99.6% accuracy and 0.08° mean absolute error, following a series of comprehensive robustness checks.FindingsThe empirical findings of this study have revealed critical determinants of compensation, including but not limited to experience level, educational background, and specialized skill-set. The research also elucidates that gender does not play a role in pay disparity, while company size and type hold no consequential sway over individual compensation determination.Practical implicationsThe research underscores the importance of equitable compensation to foster technological innovation and encourage the retention of top talent, emphasizing the significance of human capital. Furthermore, the model presented in this study empowers individuals to negotiate their compensation more effectively and supports enterprises in crafting targeted compensation strategies, thereby facilitating sustainable economic growth and helping to attain various Sustainable Development Goals.Originality/valueThe cardinal contribution of this research lies in the inception of an inclusive theoretical framework that persuasively explicates the intricacies of a machine learning-driven remuneration model, ennobled by the synthesis of diverse management theories to capture the complexity of compensation determination. However, the generalizability of the findings to other sectors is constrained as this study is exclusively limited to the IT sector.

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“…We employ these as proxies for an individual's ATAR to control for academic ability in a given university x field x year cohort. Although imprecise, this measure can control for varying ability among groups of students enrolled across different fields, which is otherwise a significant source of unobserved heterogeneity among students (Carroll, Heaton, & Tani, 2018). The average ATAR is comparable across men and women but varies between teachers and non-teachers.…”

Section: Insert Table 1 Herementioning

confidence: 99%