What is the Malta Skills Survey?
The survey was launched on 5 October 2022 in an event held at the Gran Salon in the Archaeological Museum in Valletta. The Minister for Finance and Employment, Hon. Mr Clyde Caruana, was also present.
The Malta Skills Survey was a nationwide study held between October and December 2022. A first of its kind, this was a national stock-taking exercise of Malta’s skills and qualifications among the working age population and will shed light on the skills profile of Malta’s workforce. Its aim was that of producing reliable statistics rooted in data about the skills and competencies. In turn, this will enable skills profiling exercises that, after thorough analysis, will give a strong picture of any existing skills gaps in the national labour force. As such, results from this survey will be a very important tool for policy development and further research purposes.
A total of 130,000 individuals, aged between 15 and 64 years, and living in private households were randomly selected to participate in this survey. This means that the sample was made up of roughly half of the working age population on the Maltese islands.
The sample was made up of 64,565 males and 65,435 females. Of the total sample, 103,062 were Maltese nationals while 26,938 were foreign residents. The eligibility criterion for foreign nationals was based on a five-year threshold. In other words, this survey only covered foreign nationals who have been living in Malta for five years or more. Individuals within the target age group who were currently abroad with the intention to stay abroad for 12 months or more, were also not covered in this survey.
Why is this Survey important?
Given Malta’s limited natural resources, human capital is the most important and abundant resource available to ensure the country’s progress and economic prosperity. Skills profiling of the available workforce is therefore crucial. Data collected through this survey will assist in attracting new business interests tailored to the available workforce, while also providing information on any existing skill gaps. This makes the survey a major source of data for policy makers and researchers.
What was included in the Survey?
- Demographics
- Employment
- Artistic and creative skills
- Construction-related skills
- Agriculture, farming and fishing-related skills
- Tools and machinery-related skills
- Assistance and care-related skills
- Communication and collaboration-related skills
- Information-related skills
- Computer-related skills
- Education and qualifications
- Languages
- Licences
Why is this Survey important?
Given Malta’s limited natural resources, human capital is the most important and abundant resource available to ensure the country’s progress and economic prosperity. Skills profiling of the available workforce is therefore crucial. Data collected through this survey will assist in attracting new business interests tailored to the available workforce, while also providing information on any existing skill gaps. This makes the survey a major source of data for policy makers and researchers.
Introduction
Skills mismatch refers to gaps and imbalances in skills available in the labour market. These include over- or under-qualification, labour market shortages or surpluses for specific qualifications or skills, hiring difficulties, and underemployment or unemployment for specific qualifications or skills. Different groups within the labour force may be affected, and different sectors or occupations may encounter more problems than others (Kriechel & Vetter, 2019).
Qualification mismatch was calculated using Labour Force Survey (LFS) data for 2021. The following core variables were used: highest level of education, field of education, and occupation in the main job. Two main dimensions of qualification mismatch have been analysed, Vertical Mismatch and Horizontal Mismatch. In addition, further analysis on Overall Qualification Mismatch in Malta was conducted. More information relating to the methodology used in this report may be accessed from the following link.Vertical mismatch, also known as level of education mismatch, occurs when the level of education of the person in employment does not correspond to the level of education required to perform one’s job (International Labour Office, 2018).
Thus, a person can be:Over-educated when his/her level of education and training in employment is higher than that required to perform one’s job.
Under-educated when his/her level of education and training in employment is lower than that required to perform one’s job (Eurostat, 2021).
There may be several reasons for vertical skills mismatch. Generally, if no suitable employee is available to hire at the time of an existing vacancy, the employer settles for a person who is under-educated, or the person who is hired settles for the position despite being over-educated (Kriechel & Vetter, 2019).
Figures from the Labour Force Survey (LFS) indicated that more than half of the employed population in Malta (54.3 per cent) experienced a vertical mismatch. The majority of these workers were over-educated for their job (35.1 per cent), while a further 19.3 per cent were under-educated.
Chart 1. Level of education mismatch in Malta
Vertical mismatch by sex, age and citizenship
In 2021 females tended to be more over-educated (39.9 per cent) when compared to their male counterparts (31.7 per cent). The Chart below illustrates the level of education mismatch by sex.
Chart 2: Level of education mismatch by sex
The proportion of persons over-educated for their job decreases with age. In fact, 39.2 per cent of persons between 15 and 34 years were over-educated, decreasing to 36.0 per cent of persons between 35 and 54 years and 20.3 per cent of persons who were 55 years and over. This is illustrated in chart 3.
Chart 3. Level of education mismatch by sex and age group
Differences in vertical mismatch were also seen between Maltese and foreign workers. Foreign workers were more likely to be over-educated for their job (43.4 per cent) when compared to Maltese workers (32.0 per cent).
Chart 4a. Level of education mismatch for Maltese
Chart 4b. Level of education mismatch for migrants
Vertical mismatch by employment characteristics
Level of education mismatch tended to be more prevalent in certain occupation groups and economic activities.
Service and sales workers (59.7 per cent) and craft and related trade workers (36.8 per cent) had a higher share of over-educated workers (39.0 per cent). Conversely, managers (54.4 per cent) and professionals (27.8 per cent) were more likely to be under-educated for their job.
Chart 5a. Level of education mismatch by occupation in main job
Chart 5b. Level of education mismatch by occupation in main job
The highest share of persons who were over-educated in their job worked in public administration, defence, education, human health, and social work activities (41.4 per cent) followed by the other services sector (37.7 per cent).
On the other hand, persons who worked in information and communication (25.4 per cent) and in manufacturing, mining and quarrying and other industry (22.9 per cent) had higher shares of workers who were under-educated for the job.
Chart 6a. Level of education mismatch by economic activity in main job
Chart 6b. Level of education mismatch by economic activity in main job
Over-qualification rate in Malta 2021
Over-qualified workers are defined as employed persons who have attained tertiary education and who work in occupations for which this level of education is not required. The over-qualification rate in Malta has increased over the years, from 12.4 per cent in 2012 to 20.2 per cent in 2021.
(b) break in time series
The over-qualification rate of females was 10.3 percentage points higher than their male counterparts, thus implying that more females with a tertiary qualification were working in occupations where this level of education was not required.
A difference was also evident between Maltese and foreign workers, where the share of foreign workers who were over-qualified for their job was 19.6 percentage points higher than their Maltese counterparts (33.4 per cent and 13.4 per cent respectively).
Over-qualification rate across EU-27 countries (2020)
In 2020, the over-qualification rate for Malta stood at 17.4 per cent, 4.1 percentage points lower than the EU-27 average, thus ranking the 14th out of all European countries. The lowest rate was recorded in Luxembourg (3.9 per cent) followed by Denmark and Croatia (13.4 per cent). The highest rate was recorded in Spain (35.8 per cent) followed by Cyprus (33.2 per cent) and Greece (30.2 per cent).
Chart 8. Over-qualification rate across European countries: 2020
References:
Eurostat. (2021). Skills mismatch experimental indicators: Methodological note. Luxembourg: Eurostat. Retrieved 2022, from https://ec.europa.eu/eurostat/web/experimental-statistics/skills
International Labour Office. (2018). Measurement of qualifications and skills mismatches of persons in employment. Geneva: International Labour Office.
Kriechel , B., & Vetter, T. (2019). Skills mismatch measurement in ETF partner countries. Turin, Italy: European Training Foundation.
doi:10.2816/664496
Horizontal mismatch, also known as field of education mismatch, occurs when there is a discrepancy between a person’s current occupation and their field of education based on the highest level of education that they attained (International Labour Office, 2018; Kriechel & Vetter, 2019).
Literature suggests that the measurement of field of study should be limited to persons in employment with at least higher secondary education since those with lower levels of education do not have any specialisation (International Labour Office, 2018). Thus, for this article, horizontal mismatch was computed for persons with a post-secondary level of education (ISCED 4) or higher.
Figures from the Labour Force Survey (LFS) showed that, in 2021, more than half of the employed population with an ISCED 4 qualification or higher in Malta were working in the same educational field (52.4 per cent). This implied that the remaining 47.6 per cent were employed in a different field to what they studied (horizontal mismatch).
Chart 1. Horizontal mismatch in Malta
Horizontal mismatch by sex, age and level of education
The overall mismatch for males and females was equal (47.7 and 47.6 per cent respectively). However, the largest discrepancy between males and females was evident in the 55 years and over age group. Results indicated that males were more likely to work in a field which corresponded to the one they studied (51.4 per cent).
Chart 2. Horizontal mismatch by sex and age group
Discrepancies were also evident by level of education. Field of education mismatch was prevalent among persons with a tertiary level of education (48.1 per cent).
Chart 3. Horizontal mismatch by highest level of education
Horizontal mismatch by employment characteristics
Field of education mismatch tended to be more common in certain occupation groups and economic activities.
In 2021, more than half of workers in the other services sector (63.5 per cent) and wholesale and retail trade, transportation and storage, accommodation, and food service activities (51.2 per cent) were not working in the same field that they studied. Meanwhile, most of those employed in construction (66.9 per cent) and financial and insurance activities (61.7 per cent) were working in the same field they studied (Table 13, Chart 11).
Chart 4. Horizontal mismatch by economic activity in main job
From an occupation perspective, in 2021, the majority of persons who worked as service and sales workers (66.9 per cent) and managers (57.6 per cent) experienced field of education mismatch. On the other hand, most craft and related trades workers (70.8 per cent) and professionals (60.7 per cent) worked in the same field they studied.
Chart 5. Horizontal mismatch by occupation in main job
References:
Eurostat. (2021). Skills mismatch experimental indicators: Methodological note. Luxembourg: Eurostat. Retrieved 2022, from https://ec.europa.eu/eurostat/web/experimental-statistics/skills
International Labour Office. (2018). Measurement of qualifications and skills mismatches of persons in employment. Geneva: International Labour Office.
Kriechel , B., & Vetter, T. (2019). Skills mismatch measurement in ETF partner countries. Turin, Italy: European Training Foundation.
doi:10.2816/664496
This section provides an overview of both horizontal and vertical qualification mismatches in Malta for employed persons with a post-secondary level of education (ISCED 4) or higher. LFS results indicated that the majority of employed persons with this level of education (83.7 per cent) experienced one or both forms of qualification mismatch.
As depicted in Chart 1, 35.3 per cent of the employed population experienced both a vertical and horizontal mismatch. A further 36.1 per cent had level of education mismatch and 12.4 per cent experienced field of education mismatch.
Chart 1. Qualification mismatch by type of mismatch
Overall Qualification Mismatch by sex
Differences in the share of qualification mismatch were reported among males and females. Full qualification mismatch was slightly higher for females when compared to males (35.7 per cent and 34.9 per cent respectively). Meanwhile, males experienced a higher level of education and field of education mismatch, 1.4 and 0.9 percentage points higher than their female counterparts.
Chart 2. Qualification mismatch by type of mismatch and sex
Overall Qualification Mismatch by age
The share of employed persons whose qualification, in terms of level and field, did not match with their occupation increased with age. In fact, 32.7 per cent of the 15 to 34 age group, 36.5 per cent of the 35 to 54 age group and 40.2 per cent of the 55 years and over were working in a job that was not suitable both to their level of education and to the field they studied.
Vertical mismatch was more common among the 35 to 54 age group (39.1 per cent). However, the largest share of persons with a horizontal mismatch were 15 to 34 years old. The share was 3.1 percentage points higher when compared to the 35 to 54 age group.
Chart 3. Qualification mismatch by age group
