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«SKILLS MISMATCH IN LATVIAN MANUFACTURING SECTOR Authors: Ilze Zumente and Kārlis Putriņš ISSN 1691-4643 ISBN 978-9984-842-28-8 November 2011 Riga ...»

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More concretely, the representatives of Riga Vocational School no.3 were interviewed because of the wide range of offered educational possibilities corresponding to the manufacturing industry of Latvia and representatives of learning center “Buts” (similar to vocational school) were asked because of the presence of this learning center in many cities of Latvia. Higher education establishments such as universities and colleges were not covered during the interviews due to the small share of their graduates working in lower level positions (see appendix 3).

As the situation has been noticed also by the Government representatives and a vocational school reform is in plan for the next years in form of attracting the EU funds in order to reduce the amount, but increase the quality of the vocational education, the representatives’ point of view gained via interviews had to be present in the discussion and analysis (Grīnbergs, 2010). The representatives from Ministry of Education and Science responsible for the vocational education were therefore interviewed allowing us to understand and showcase the Government`s position in the skills mismatch situation in the manufacturing sector of Latvia.

The interviews were held in the premises of interviewee during December 2010. In order to gain deeper insights, interviews were semi-structured and included mostly open-ended questions leaving space for deviations from the core topic and allowing for deeper exploration.

No specific set of the questions was used for the interviews because of the different stake-holder parties interviewed. The average time of the interviews was approximately 1 hour in each case.

The insights from the interviews have not been described separately; however, they are referred to while explaining the results and analyzing strategies.

Ilze Zumente and Kārlis Putriņš 18


Data In order to answer the research question of the thesis, a new dataset had to be created as no existing data could be used for this purpose. Various datasets were considered yet concluded not yielding the responses to suit the chosen methodology.

A survey was created and distributed to the lower level employees from companies representing the manufacturing sector of Latvia during the period from 16th December, 2010 to 2nd February, 2011. As mentioned before, the major target occupational groups were ISCO6skilled agricultural and fishery workers, ISCO7- craft and related trades workers, ISCO8 -plant and machine operators and assemblers and ISCO9 representing elementary occupations.

A pilot survey was executed in the beginning of December at the cosmetic production company “Dzintars” and was concluded to be successful as the questions asked were understood correctly and answered in sufficient scope.

The sample was aimed to represent the weighted average number of employees working in any manufacturing sector as part of the whole Latvian manufacturing sector. For example, if the majority of people working in the manufacturing sector are employed in the food industry, also in our sample food industry employees should constitute the largest share of the sample respectively. The preliminary sample distribution as based on the data by CSB for year 2008 can be found in the appendix 4. A sort of stratified sampling technique was applied in order to achieve the aim- subgroups of representative industries were made and particular companies representing the sector were targeted via e-mail addresses found in internet sources like various manufacturing associations, labour unions etc. Preliminary agreements with the companies about the distribution of the surveys were made in case of positive answer to the e-mail sent, so no direct response rate can be calculated. The surveys were sent via e-mail to the companies, were they were printed out on paper and distributed to the lower level employees by their supervisors.

A special survey (appendix 2) was accordingly done by the supervisor. The surveys were later collected back from the enterprises and data was summarized in a spreadsheet. All in all, 201 surveys from lower level employees and 30 surveys from employers were gathered from 30 different size companies representing various fields of the manufacturing sector.

The aim of the sample was partly achieved- no concrete percentages of employees were included in the sample in order not to lose any observations in terms of filled questionnaires, yet Ilze Zumente and Kārlis Putriņš 19 overall answers in a sufficient scope were gathered. The possible bias stemming from the fact that precise sample could not be reached is admitted, however as the major groups and percentages have been included, authors believe in the representativeness of the sample.

Figure 2 The final sample distribution. Created by authors, based on the data base created Moreover not only large, well known companies employing hundreds of people, but also small firms with significantly lower worker count were questioned in order to achieve a possibly true sample. Geographically wise, majority of companies questioned were located in the largest cities of Latvia, yet there were numerous smaller businesses running in small cities in the countryside. As the aim was not to represent the geographical distribution of the companies, no graph summarizing the location of the respondents is presented.

The descriptive statistics from the sample obtained can be seen in the appendix 7. The sample consists of almost equal shares of women and men, distribution being 56% and 44% respectively. The average age of respondents is 38 years and ranges from 19 to 69. On average the respondents have 1 child and 57% of them are married. Finally, the average work experience in the current position ranges from 0.5 to 42 years and is almost 9 years on average. The mean remuneration for the employees questioned is 274 LVL per month after the tax payments.

Skills mismatch type The first aim of the study was to determine whether skills mismatch problem actually exists among the lower level employees working in the manufacturing sector. In order to find it, a method used by Allen and van der Velden (2001) and Green and McIntosh (2007) was employed. According to the compliance to statements presented before the presence of skill Ilze Zumente and Kārlis Putriņš 20 matching type could be determined- person can either have a skills match or a skills mismatch in form of skills shortage, skills surplus or possession of wrong skills.

The results from the sample of 201 observations show that there is significant skills mismatch among the lower level employees of the manufacturing sector. Only 24% of the respondents belong to the skills match group and have adequate skills for their current job, which is a close result to the wider study done in Europe by CEDEFOP, who found 21% skills match in the overall economy (CEDEFOP, 2009). Alternatively, 76% of the employees belong to the one of the skills mismatch types. Majority of them or 41% present a skills shortage which means that employees lack the skills needed to perform their every day duties well and additional education should be carried through in order to improve the effectiveness and performance of these employees. 18% of the respondents have too many skills or an excessively high level of the skills for their current workplaces meaning that they cannot fully use the skills that they possess and thus can be considered over-skilled. Finally, 17% of the respondents have obtained wrong skills for the job they are doing and thus cannot effectively perform their duties. This group would also benefit from additional education or trainings or they could be matched to positions better suited for their skill profiles. The final distribution of the skills mismatch types within the sample can be seen in the graph below.

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Figure 3 Skills mismatch type distribution, created by authors When comparing the skills mismatch type distributions between the genders, it can be seen from the graphs below that men employed in the manufacturing sector have more adequate skill levels and higher compliance with the demanded skills. It is supported both- by increased skills match share and increased level of skills surplus among the surveyed men in the sample.

Ilze Zumente and Kārlis Putriņš 21

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Figure 4 Skills mismatch types for women and men separately, created by authors When looking at skill adequacy distribution among age groups, the sample was divided into 4 subgroups according to age. It can be concluded that skills match is more attributable to older respondents- 30% of the respondents in the age group of 55 to 69 have skills match while only 21 % have found the correct skills needed among the youngest respondents in the age group between 19 and 25 years. Motivation for the result is that experienced workers have adjusted their skill sets to market damands or had more time and opportunities to find occupation that fits their skills better. Inverse trend can be seen when looking at skills surplus- 31% of the youngest respondents have exceedingly high skills for their positions while only 10% have skills surplus in the oldest age group. Accordingly, an opposite trend is seen when looking at skills shortage, which increases with years based on the sample. Because of modern equipment and constantly evolving work practices half of workers at age of 56 to 69 find themselves unable to update their skill sets as much as demanded by labor market. Wrong skills are probably the mismatch type the best describing skill set issues for young workers. It is often the case that people do not master skills needed for work. This signals a problem in the education system. Medium age groups are similar to each other and find themselves between two extremes of youth and old workers. The graphs showing the skills mismatch distribution according to the age groups can be seen below.

Ilze Zumente and Kārlis Putriņš 22 19-25 26-39

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Firstly, it can be noted that people tend to mostly agree to the statement that they are given the opportunity to use all their skills and they actually use all their skills in workplace. It supports the previously presented findings that the majority of workers (69%) have adequate skills in terms of skills match or insufficient skills in terms of skills shortage. A strong support (average answer value of 4.19) is given to the statement about the willingness to continue the education and trainings in order to gain additional skills, which is also in line with the previous finding that due to inadequate level of skills, people are willing to gain additional skills to be able to work more effectively.

When dividing the answers according to genders, dispersion can be identified.

4.5 4

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Figure 7 Answer distribution to the general skill assessment questions according to genders, created by authors From the graph above it can be identified that men are more confident about their skills and express significantly less agreement to the statement that they would work more effectively if they had additional skills. It is also supported by the lower level of skills mismatch among the men in comparison to women surveyed as described before. However, men are equally and even a bit more eager to gain new skills showing that the willingness to gain new skills does not directly depend on the lack of concrete skills in the current work position.

Similarly to the analysis according to respondent genders, results for skills mismatch types and compliance to self evaluation statements are presented between four age groups. The Ilze Zumente and Kārlis Putriņš 24

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Figure 8 Answer distribution to the general skill assessment questions according to genders, created by authors When looking at the age group compliance to self-evaluation statements, it can be seen that as expected younger people are more willing to gain new knowledge and additional skills.

Furthermore, as supported by the previously presented results youngest age group also faces the largest skills surplus approved by the lowest agreement to the statement that they can use all their skills in their current workplace. On the other hand, oldest group of respondents indicate that in their current jobs they are able to almost fully use their skill sets. Only statement where results do not increase or decrease marginally to age is respondent thoughts on whether additional skills would improve their work efficiency. Here one can see that greater support to this statement is given by medium age groups. This could be explained by the fact that in the prime and towards the end of carriers workers can estimate the value of additional skills better. Older age group presumably also highly value additional skills, yet because of physical constraints they cannot take full advantage of additional skills. Finally, the oldest group of respondents strongly agrees to the statement that they use all skills; consequently, they are not willing to gain additional skills anymore as suggests the results for final statement.

Specific skill dispersion The second part of the analysis concentrates on specific skill set required in the manufacturing sector. The dispersion between the demand for the concrete skills by the employers and supply of the skill set by the employees is sought. In order to compute the significance of differences, t-tests among means have been calculated (see appendix 9).

Ilze Zumente and Kārlis Putriņš 25 The skill set has been constituted on the basis of previous research, for instance Sgobbi & Suleman (2009), as well as updated based on the suggestions received during personal communication and interviews with the employers. The skill list includes skills like Latvian and Russian language, communication, cooperation, teamwork, responsibility, technical knowledge, standards and procedures, tasks planning, time management, learning skills, adaptability and problem solving. The set has also been partly adjusted according to the previous research by Sloka (2007).

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