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Education-Job Mismatch: Implications for Individual Earnings and Aggregate Output

• Original Research
• Published: 02 April 2022
• Volume 163 , pages 723–752, ( 2022 )

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• Balzhan Serikbayeva 1 &
• Kanat Abdulla   ORCID: orcid.org/0000-0002-4205-9700 1  

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Based on the nationally representative micro-level dataset, the present paper investigates the prevalence of education-job mismatches and their effects on individual and aggregate earnings in Kazakhstan. The analysis shows that the incidence of education-job mismatches varies across both individual and employment characteristics, and, in particular, across industries. We find that relative to being well-matched, vertical and horizontal mismatches have negative effects on individual earnings, while the penalty for being both vertically and horizontally mismatched is the greatest. Importantly, the study develops a theoretical model explaining the link between productivity and mismatch and quantifies the aggregate productivity gains that would result from reducing the levels of education-job mismatches in the labor market. The counterfactual analysis suggests that the country’s output will increase on average by 11.3% if the level of education-job mismatch is reduced across all industries.

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The gender pay gap in the USA: a matching study

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The influence of education on health: an empirical assessment of OECD countries for the period 1995–2015

The terms “education-job mismatch” and “educational mismatch” are used interchangeably throughout the paper.

This study except for the part on the effects of educational mismatch on aggregate output is part of the PhD thesis.

In the current paper we use the terms “vertical mismatch” and “overeducation” interchangeably. The rationale for excluding two other categories of responses on the vertical mismatch question is provided in Sect. 4 .

Source: The Bureau of National Statistics (BNS).

Source: World Bank, World Development Indicators databank.

We think of \(\tau _{jM}\) as representing a friction due to a particular type of educational mismatch that affects the cost of choosing a particular industry of employment. As such, \(\tau _{jM}\) can reflect productivity changes experienced by different types of mismatched workers in different industries. For example,a librarian might be less productive as an applications developer than as a database administrator.

The derivation of the result can be found in Hsieh et al. ( 2019 ).

Some other studies that used an augmented Roy model include Hsieh et al. ( 2019 ) and Abdulla ( 2019 ). While these papers focus on the role of gender and racial differences in employment in explaining observed gaps in earnings, the focus of the current study is on the impact of education-job mismatch on productivity.

Efficiency units are the total amount of human capital available for production, which is a product of the number of workers who possess human capital and their skill level.

We have included Table 11 in the Appendix which illustrates the sample size before and after dropping missing income observations from the analysis across survey years as the main variable that affects the sample size is earnings. Starting from 2016, income isn’t reported by many observations. Since the study investigates individuals who are strongly attached to the labor market and those with non-zero earnings, we exclude individuals with missing income and zero values.

Tenge is the national currency of Kazakhstan, which was introduced in 1993.

The skill intensity of the industries is determined using the average education level of workers across industries. The industry groups are defined according to the average education level of workers as follows: lower-skill industries with the average years of education less than or equal to 13 years; higher-skill industries with the average years of education above 13 years. The industry groups defined by skill level are given in Table 10 .

While higher educational attainment is generally associated with better labor market outcomes, some studies find OLS estimates of the returns to education to be biased due to endogeneity and use the instrumental variable approach to address the issue. However, due to data availability constraints, we could not implement the IV method in the present study.

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Appendix A: Description of the data

See Fig. 1 .

Rates of education-job mismatches across age and education categories

See Tables 6 , 7 , 8 , 9 , 10 , 11 and 12 .

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Serikbayeva, B., Abdulla, K. Education-Job Mismatch: Implications for Individual Earnings and Aggregate Output. Soc Indic Res 163 , 723–752 (2022). https://doi.org/10.1007/s11205-022-02912-x

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Accepted : 22 February 2022

Published : 02 April 2022

Issue Date : September 2022

DOI : https://doi.org/10.1007/s11205-022-02912-x

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THE PERCEIVED EFFECT OF QUALIFICATION MISMATCH ON EMLOYEE JOB PERFORMANCE

This research deals on the perceived effect of qualification mismatch on employee job performance in Seedvest Limited. The company continues to employ people from the labour market irrespective of their academic background. This paper therefore sought to determine the effects of qualification mismatch on job performance of Seedvest Limited employees. This study adopted a descriptive design. The population of interest to this study was the entire 89 staff of Seedvest Limited through a stratified sampling technique, Primary data was collected by administered a structured questionnaire. Data collected were analyzed by the use of descriptive statistics and presented as percentages and frequencies. The information was presented by use of table and in prose-form. The study revealed that a majority of employees of Seedvest Limited were qualification mismatch, therefore has effect on their performance on the job. The study found that additional training help majority of the employees to align their skill and job requirement in order to be productive as expected from the company management. While the Training and Development unit administered various training sessions to bridge the identify skill gap. Based on the study findings, there is need to discontinue employment and placement of employees with a mismatch between their field of education and their job and that, employees should always be recruited and placed on roles that match their levels and fields of education. There is also need for learning needs assessment for employees already in employment; this is a sure way of ensuring better job performance of employees.

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