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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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The evaluation of the concrete skill possession has been asked from the people surveyed in the range between 1 and 5. It can be noticed that the self evaluation results are rather high, thus there is a reason to believe that overconfidence bias is present in the sample. Similar problems have been addressed also by Allen and van der Velden (2001), who in their research argue that although some of the respondents may suffer from overconfidence bias on average the results should be fairly true.

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Figure 9 Skill dispersion between employers and employees according to concrete skills, created by authors From the graph above it can be seen that the skills that are underprovided by the employees are responsibility, technical knowledge and problem solving abilities. When testing for the mean difference significance, the differences are found to be significant at 95% (see appendix 9). The particular skills have been often mentioned by the industry professionals as the ones mostly lacking, which supports the results from the sample (Troicis, personal Ilze Zumente and Kārlis Putriņš 26 communication, December 2010). Responsibility and problem solving skills can be more attributed to the personalities of employees and support the argument by Sloka (2007), who concluded that employees are often not psychologically ready to start working after school or vocational school graduation. The difference in the demand and supply for technical skills is more related to the specific technical education before the work and has been stressed and is supported by the interviews with vocational schools’ representatives interviewed. Kaspars Troicis (vocational school “Buts”) and Ilgonis Ruņģis (3rd Vocational School of Riga) expressed their concern about the old-fashioned technologies available in the educational institutions and their incompatibility with the real-life technique. Moreover, they have expressed the gap in the communication between employers and vocational school representatives, which results in a situation, when it is not clear for the educational party particularly which technical skills and to what extent are demanded by the employers in the labor market (Ruņģis, personal communication, January 2011).

It should also be noted that Latvian language skills are slightly underprovided, while Russian skills are significantly overprovided by the labor force. The result for Russian language skills difference is significant at 99%. The situation about the language knowledge is mostly the heritage from the recent history of the country and is mostly attributable to the older workers, who seem to prefer and master Russian over Latvian language. Among the younger employees, Russian is mastered at much lower level, which corresponds to the actual situation in the country, when less and less younger people speak Russian.

Other skills that are overprovided by the employees are time planning and adaptability.

Time planning difference is significant at 90 %, while difference in means for adaptability slightly fails to present a significant result at 90% (89%). According to interviews with the employers participating in the survey, lower level employees are more aimed to perform similar duties everyday and thus are not asked to be highly adaptable to changes. Also time planning is mainly done by the managers and thus is not asked from the employees. The results, however, show that employees feel ready and skilled enough to plan their own working time although it is not asked in their job descriptions.

Some skills like communication abilities, team work, planning and learning can be seen as being sufficiently mastered by employees and responding to the needs of the employers Ilze Zumente and Kārlis Putriņš 27 presenting fairly matching skills requirements. No significant differences in the means for these abilities are found.

Regression analysis In order to measure the impact from skills mismatch on the economic returns, a model developed by Duncan and Hoffman in 1981 and later used by Sgobbi & Suleman (2009) has been applied. The model estimates OLS regression in order to capture the explanatory effect of various skills mismatch types on the wage rate (Duncan & Hoffman, 1980) and thus should present whether the presence of a skills mismatch has a direct effect on the wage rate of the employees. The full model with all the explanatory variables used takes the following form.

Ilze Zumente and Kārlis Putriņš 28 exceedingly high correlations (above 0.5) are found, thus all variables as specified above are chosen for the analysis.

Firstly, a model specification with the classical “human capital” variables is tested.

Because of the low explanatory power of 0.09, the control variables (set of dummies) for industries are added. Explanatory power of R-Squared of 0.38 is reached. Although the majority of the variables do not provide statistically significant results, the signs of coefficients are in line with the previous academic work- positive coefficients are found for men dummy, years of experience in the field and age.

In the third model specification, dummy variables for wrong skills, skills surplus and skills shortage are added. The base variable of skills match is not included in order to provide a basis for comparison. The explanatory power increases to 0.47, which means that approximately 47 percent of the variation in the wage rate variable can be explained by the explanatory variables included. The R-Squared can be seen as reasonable for the regression undertaken and is approximately twice higher than in the regression by Sgobbi &Suleman (2009). This can be explained by the industry effect inclusion in the regression, which is considered to be important determinant of the differences among the wage rates as supported by the first two regression specifications tested. All in all, the increase in the explanatory power from 0.38 to 0.47 after the skills mismatch inclusion shows that the variables indeed have a determining effect on wages.

Significant coefficients for the cosmetics, electronics, food, construction, metal, textile, telecommunication and other manufacturing sectors predict positive wage effect for employees working in these industries in comparison to the base dummy assigned to chemicals industry.

The coefficient for men dummy is still positive while the age variable loses its explanatory power and approaches zero. None of the demographic and human capital coefficients seem to present statistically significant effect.

The main results of interest are in line with predictions. Skills mismatch in either skills shortage, skills surplus or wrong skills indeed results in wage penalty. Moreover, coefficients for all skills mismatch types present statistically significant estimates at 99%. Based on the results, all hypotheses are accepted and it can be concluded that any type of skills mismatch will result in a significant wage penalty.

When interpreting the results one must be careful because of the often mistake as expressed by Halvorsen & Palmquist (1980), who argue that dummy coefficients in semiIlze Zumente and Kārlis Putriņš 29 logarithmic regressions have to be adjusted in contrary to continuous variables (Halvorsen & Palmquist, 1980). When adjusting the coefficients for the effect, the coefficients of the regression turn out to be -0.1689 for wrong skills, -0.2196 for skills shortage and -0.248 for skills surplus which slightly diminishes the effect as shown by the regression. In terms of real monetary effects, people with wrong skills, skills shortage and skills surplus have by 17%, 21% and 25% lower wage rates respectively. The percentages are significant thus the presence of skills mismatch is found an important determinant of the wage rate and having a real economic effect.

The results are in line with the predictions and previous academic research by for instance Allen & Van der Velden, Falter, Hoppe et al. and others.

The result achieved implies that all three skills mismatch types examined really result in lower wages for people suffering from them. The monetary effects in the range from 17% to 25% are supported by previous studies, who also find similar wage decreases in the presence of skills mismatch. Although the highest wage penalty is associated with skills surplus, which at first might seem rather contradictory, the issue has been addressed also by CEDEFOP, who associate skills surplus with lower motivation and job satisfaction that leads to higher absence rate and shirking resulting in lower wages (CEDEFOP, 2010).

The real life implication of the phenomenon found is that in many cases people, who are employed in the manufacturing sector in Latvia, cannot reach their full potential and suffer from wage penalty not because of the lack of experience or the needed knowledge, but because they do not fit the positions they are working in. The explanation, which has also been supported by industry professionals interviewed, is that in many cases the current economic situation with the very high unemployment rate does not allow for frequent job changes in order to adjust to the needs and wants of the employees, thus many workers are forced to continue their current work although it might be causing a skills mismatch.

Latvian Government strategies

From the results of research and analysis it can be concluded that there are several problems existing in Latvian labor market. This has been also noticed by the Government of Latvia and adequate responses to the issues hindering the growth and wellbeing of Latvian economy have been given. Two general sets of actions are the Concept of raising professional Ilze Zumente and Kārlis Putriņš 30 education attractiveness and Europe 2020 a strategy of smart, sustainable and inclusive growth.

As noted during the personal interviews, among all strategies employed by Latvian Government particularly these two deal specifically with labor market issues and are more comprehensive than the rest (Brante, personal communication, December 2010).

Concept is a set of goals and strategies aimed to improve the image of professional education; it has been developed by Ministry of Education and Science and aimed for completion at 2015 (Ministry of Education and Science, 2009). Europe 2020 is a general EU27 strategy developed by the European Commission and should be complied with in all of European Union member states with the due date set to be the 20th of December, 2020. In the following sections both strategies will be explored and discussed (Ministry of Education and Science, 2011).

Concept The official twofold aim of the Concept is to increase the attractiveness of professional education and bring together social partners to ensure professional education quality. Basically, behind the complicated surface is simple response to address two major issues as determined by the Ministry of Education and Science- prestige of the professional education and professional education compliance to the labor market demands (Ministry of Education and Science, 2009).

As it can be understood from the official objective statement, MoES is planning to raise the prestige of professional education by making it more attractive. There are several actions to be implemented to fulfill the objective. Firstly, MoES emphasizes the importance of elastic professional education demand by introducing the credit point system already present in the universities of Latvia. Credit system allows dividing parts of education program in separate models with individual aims, tasks and desired results. The benefit of having model system is the ease of adjusting the study programs to short term labor market demands, this being a great way to lessen the skill shortages in short period of time. Additionally, credit point introduction ought to improve the evaluation process and allow students’ transition to other study programs smoother.

The second improvement includes qualification level transition from 5 level system to 8 level European qualification infrastructure. By undertaking such changes professional education would not be constrained by only one level, thus improving the flexibility of study programs and enabling variety of individual study program creation.

Ilze Zumente and Kārlis Putriņš 31 The third enhancement is recognition of the unofficially obtained education. Specific procedures have been created to provide skilled people with opportunity to obtain valid qualification without official training. These procedures are designed to be mainly practical knowledge oriented and would take advantage of credit point system mentioned above.

The fourth suggestion from the Concept is to divide professional education in two levels.

The first level would include professional education obtained in 3 years. This level would utilize before mentioned model system and include one or more specialization opportunities. The second level professional education would be available after the first level and require 1 to 2 years to be completed. The focus in the second level would be on in depth studies according to chosen professional direction. This education would also provide advantage to student if he decides to continue his studies in relevant study program at a college or university.

Final point regards professional education establishment differentiation. As noted in the interviews this is supposedly the most critical turning point in Concept. The idea is to pool the resources and establish fewer yet in many ways better education establishments named competency centers. The centers would be scattered across Latvia and specialize in particular professions. The main benefit from closing many professional schools or making them a part of competence center is that modern, up to date technologies could be bought specially for the competence centers. Similarly, only the best teachers would be picked to hold classes in the competence centers. General idea of not spending money on many medium quality establishments, but instead concentrating the funds on few top notch education centers seems bold yet effective (Ministry of Education and Science, 2009). As a proof to this statement, a representative of private professional schools expressed his concerns that public professional education might substantially improve competitiveness by undertaking centralization and resource polling strategy (Troicis, personal communication, December 2010).

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