Factors influencing the labour market insertion of undergraduate graduates from Peruvian universities

Pedro Yvan Saenz Rivera, Judith Soledad Yangali Vicente

doi:10.17762/turcomat.v12i3.1921

Pedro Yvan Saenz Rivera, Judith Soledad Yangali Vicente

Open Access

https://doi.org/10.17762/turcomat.v12i3.1921

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Abstract

The objective of the research was to propose that some socio-demographic factors: gender, economic level and parents' education; basic education factors such as the department and type of secondary education management and mainly undergraduate and postgraduate factors measured by the characteristics of the university-career explain the insertion of university graduates in the Peruvian labour market. The quantitative, theoretical and explanatory approach study consisted of the analysis of information received from the Ministry of Education, a sample of 8072 graduates from 2014-2017 from a total of 15 private universities and 35 state universities. We found 50% of graduates employed with adequate hours, wages and tasks, 21% with inadequate employment and the remaining 29% unemployed. Using the multinomial logistic regression model, it was shown that engineering degrees have 4 times the employment opportunity, while graduating from a university in the first places in the Research Ranking favours employment by around 50%, gender, department, family income and the mother's level of education are also factors that condition employment insertion.

Highlights

The International Labour Office ILO (2020) in its report World Employment and Social Outlook: Trends 2020 indicates that there is no correspondence between labour supply and demand, factors such as geographical location and gender of a person determine their probability of finding a job, the female activity rate was only 47%, below that of men with 74%; on the other hand, age is another characteristic of inequality in the labour market, 22% of young people aged 15 to 24 years do not have a job or education
In the first part of the analysis, taking as a reference the methodology indicated in INEI (2020b), we proceeded to classify the graduates into 3 excluding categories of labour market insertion: Unemployed, adequately employed and inadequately employed
In order to test the hypotheses that factors influence labour market insertion, an attempt will be made to fit the data to a multinomial logistic regression model, hereafter MRLM, which is summarised as follows: Considering 3 levels or categories for the dependent variable Labour market insertion, these categories are: Y= 1 (Unemployed); Y=2 (Inadequately employed) and Y=3 (Adequately employed)

Summary

Introduction

The International Labour Office ILO (2020) in its report World Employment and Social Outlook: Trends 2020 indicates that there is no correspondence between labour supply and demand, factors such as geographical location and gender of a person determine their probability of finding a job, the female activity rate was only 47%, below that of men with 74%; on the other hand, age is another characteristic of inequality in the labour market, 22% of young people aged 15 to 24 years do not have a job or education. According to the International Labour Organisation (ILO, 2019) for Latin America and the Caribbean, the youth unemployment rate is three times higher than the adult unemployment rate, and those who find work do so in unfavourable conditions. This report indicates that the unemployment rate in the Oct-Nov-Dec quarter for people with higher education reached 7.2%, exceeding as in other years the unemployment rates of the other categories of educational attainment

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