Youth Practice Project as an object of structural modeling

Abstract

Object: Active measures to promote youth employment are one of the topical areas of state regulation of the labor market in many countries around the world. The purpose of the study is to identify objective and subjective factors that influence the result of the Youth Practice Project of the state program for the development of productive employment and small business to develop recommendations for its improvement.

Methods: We have applied sociological survey methods with subsequent processing of the results by statistical methods and in the PLS-PM program, which allow us to build a structural model describing the relationship between the dependent variables Y and independent variables X based on the partial least squares method. The method allows evaluating complex models of causality with hidden variables that are significant but not observable (for example, motivation, behavioral attitude, etc.). The sociological survey involved 184 project graduates living in cities and regions, after which 1-1.5 years have passed from the project, which is consistent with the requirement for the sustainability of the result.

Findings: The objective parameters of the process in the project have a significant impact on the stability of its final result, and the dependence on subjective factors is statistically insignificant. Passive motivation, when optimizing the parameters of the project process, bringing the workplace and the functionality on it closer to the specialty of the diploma, can change to a more active one and the applicant’s assessment of the results to a positive one.

Conclusions: Employment centers need to pay special attention to the duration of the project and apply an individual approach to the applicant, considering the potential of his personality using modern methods of diagnosing internal competencies.

Introduction

Youth in the modern economy is one of the target groups in the state policy of promoting employment of the population. There are about 1.2 billion young people between the ages of 15 and 24 in the world, and almost 75 million of them are looking for work (Kluve et al., 2014). The youth unemployment rate reflects the dynamics of economic development in a particular country, the demographic structure of the labor market, and the effectiveness of employment policies. The quantitative parameters of youth unemployment across OECD countries can differ by almost 10 times (Figure 1).

The indicators are more favorable in Germany and Japan. Countries with stricter worker protection standards (France) and southern European countries are in a more difficult economic situation, where almost one in three young people are registered as unemployed.

Labor market policies for young workers are primarily based on education and training programs.

Four options of training programs will be applied:

• institutional training (75% or more of study time in educational institutions);
• training in the workplace (75% or more of the time in the workplace);
• alternative training (50% to 50%);
• special apprenticeship support, which is related to encouraging the employer to hire apprentices from target groups, especially young people.

^*Responsible author:

E-mail address: aiman_93@mail.ru

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Despite the emphasis on active measures to promote employment in the labor market, the volume of training programs as a percentage of GDP on average across the OECD for the period from 2009 to 2018 decreased: in 2009 – 0.15%, in 2014 – 0.14%, in 2018 – 0.11% respectively. Although for individual countries the shares can be much higher. So, in Germany in 2018, this figure is 0.18%, in France 0.25%, in Denmark 0.39%. While the Eastern European countries spend nothing or much less on such programs (the Czech Republic 0%, Slovakia 0.03%). It should be noted that the structure of the package of training programs is dominated by the direction of institutional training: in 2009 – 0.11%, 2014 – 0.10%, 2018 – 0.07%.

The fourth direction, similar to the Kazakhstan project “Youth Practice” in the State Program for the Development of Productive Employment and Small Business, occupies an insignificant place in the volume of training programs (Implementation of the “Enbek” State Productive Employment and Mass Entrepreneurship Development Program for 2017-2021). It should be noted that, in the OECD statistics, the direction also includes grants for vocational training for specific disadvantaged groups. In the period from 2004 to 2009, on average across the OECD, the share of this direction as a percentage of GDP was 0.02%, and from 2010 to 2018, it was stable at 0.01%. Although in some countries this value is several times higher. In Austria, its share has steadily increased from 0.02% in 2004 to 0.07% in 2018, respectively. In most countries the share of this direction decreased: in France from 0.08% to 0.05%, in Portugal from 0.08% to 0.03%, in Germany from 0.03% to 0.01%.

These trends reflect the evolution of perceptions about the effectiveness of different areas of employment promotion through training after analyzing and evaluating the results of different projects over a long period.

Kazakhstan has accumulated quite a long experience in the implementation of the Youth Practice Project, as one of the directions of the state employment program, which has been implemented since 2008. For this direction over the past four years, the average annual costs were equal to 0.01% of GDP. The youth unemployment rate in Kazakhstan, on average for the period 2016–2020, is 3.8%. According to this indicator, the country is close to the group of leaders of the OECD.

The idea of the project is to gain work experience in the specialty of a diploma by a graduate of an educational institution if he cannot find a job on his own. The formal evaluation of the results is carried out as a proportion of those employed after the project. The assessment is not carried out from the standpoint of achieving the goal of the project: employment for a permanent job in the specialty of the diploma.

Monitoring and evaluation of the sustainability of the result in the medium term are not carried out by the Employment Centers, i.e., the status of a graduate in the labor market 1–1.5 years after leaving the project. The assessment of the quality of the social effect for the applicant is also not revealed, although the number of options is over two (satisfied/dissatisfied).

The novelty of our research lies in the identification of factors that affect the outcome of the project both on the part of the project participant (the social effect assigned to them) and on the part of the external environment (employment center, workplace in the project), which allows us to identify a set of internal problems of the project.

Literature Review

The range of research on active employment promotion programs is wide, including research from the standpoint of management in Employment Centers.

Many authors emphasize the role of Employment Centers, which are “boundary spanners” between employers and job seekers (Ingold, 2018). The role of management, which is implemented by the Employment Centers, is revealed in their ability to create and maintain productive relations with the employer, to carry out the initial adaptation of the applicant to the employer's requirements by intra-organizational methods (Ingold, 2020; Bakkeli, Breit, 2021; Willers, 2021).

Public policymakers, managers and researchers are looking at innovative approaches to jobseeker service that enable agencies to be innovative (Adascalitei, Morano, 2016). These effects are believed to be due to improved quality of service at the local level and are due to greater flexibility in tailoring services to individual clients (van Berkel, 2006; Considine et al., 2018).

The hypothesis that active labor market programs will be highly effective is supported in research if employment centers have significant freedom to provide tailor-made services (Harrer et al., 2020). The authors compared on-the-job training participation in the firm and training in other settings in the context of the heterogeneity of the effect by gender and region. Participation significantly improved the earnings and employment rates of participants, with training in a firm more than training in other settings. The authors explain the low efficiency of the Employment Centers by the insufficient possession of the Centers' management in the Activation and Integration Schemes.

Often, the influence of group subjective characteristics of participants (gender, age) in employment programs on the results of the program is investigated. The result of the program is understood as the graduate's employment. For example, longitudinal data analysis shows that employment programs increase fulltime employment opportunities for women, but not men, and are also effective for a younger age group, but not for those over 25 (Hardoy, 2005; Biewen et al., 2012).

Fully reasoned, the authors focus on systemic changes that are necessary for an adequate assessment of the effectiveness of active employment programs. From a results-based management methodology perspective, impact assessment requires reliable administrative and statistical data, econometric models and scale measurements. An important role is played by the methodology of assessment officially recognized by the legislation and the attitude towards its real results (Deborah, 2006; Bartlett, 2014). The conclusions of these authors are confirmed by evaluations of the procedures for the development, implementation and evaluation of program results, including Kazakhstan. Researchers substantiate the inadequacy of the methods used for evaluating programs, which do not disclose the issues of imperfection of their management and the sustainability of their results (Barsoum, 2017; Pritvorova, Bektleeva, 2017).

The importance of developing a reliable evidence base for policy based on long-term program impact assessments is emphasized (Sanderson, 2002). That is, the impact on the employment of program graduates after 1.5–2 years of graduation.

Young people are in the focus of active employment policies in all countries, as evidenced by metastudies that summarize findings from 113 reports on 107 activities in 31 countries (Card et al., 2010; Kluve et al., 2014).

In many countries, youth programs have a positive impact on employment and the possibility of formal employment and full-time employment (Oznur et al., 2021).

The results of the study reveal both linear (with one step-by-step training program) and non-linear effects from two-step programs related to youth education (Thomas et al., 2021).

Comparative studies emphasize the dependence of the results of similar youth policy on the labor market on the quality of implementation of specific programs and projects in specific countries (Jale et al., 2019). A targeted and structured policy in Portugal with the active involvement of social partners has been more effective than in Greece. Convergence in policy content does not automatically ensure success but may be compatible with divergence in terms of outcomes (Konstantinos, 2019). The approach to the employment of young people, considering the maximum expansion of the field of opportunities for a young person, is relevant for the present time. That is, not just from the standpoint of employment for any job, but from the standpoint of a stable and desirable career for a young person (Valerie, Ronald, 2016). Recent studies highlight that active employment programs most often provide young people with resources to survive, but rarely help build their capacity to cope. The need for individual services that are based on the motivation and ambition of young people allows us to approach problems with the positions of the development of people's abilities (Vishnevskaya, 2019; Assmann et al., 2021).

Methods

The research methodology is based on a sociological survey of the graduates of the Youth Practice Project 1-1.5 years after its completion. The sample included 184 people living in a large city (Karaganda), a small and medium city (Saran and Shakhtinsk) and a district (Abay district).

The survey results were processed in the PLS-PM program, which allows constructing a structural model describing the correlation between the dependent variable Y and the independent variables X based on the partial least squares method. The method allows evaluating complex models of causal relationships with hidden variables that are significant but not observable (for example, motivation, behavioral attitude, etc.). The advantage of the model is the ability, within the framework of a single construction, to assess the impact of the same number of factors on several variables Y, as well as the correlation between them.

Results

The questionnaire included the following blocks and their constituent elements (Table 1).

Table 1. The structure of the questionnaire and symbols in the PLS-PM model.

The general characteristics of the group of respondents can be represented by the following statistical parameters:

 39% of the members of the group at the time of the survey already have experience of working at 3 places, 25% at 2 places.

 69% at the time of the survey are employed in the status of an official and 7% of unofficial employees, 21% of respondents are unregistered and 2% of a registered unemployed, 1% is self-employed.

 50% are college graduates, 27% are universities, and the rest have both diplomas.

 34.8%, when applying to the project, wanted to get work experience, 29.4% wanted experience in the specialty of a diploma, 25% were attracted by guaranteed wages, 10.8% did not think too much.

 37% live in a large city, 20.1% in small and medium-sized cities, 23.4% in the district center, 19.5% in a village,

 95% graduated from college or university in 2018-2019.

Based on the results of the sociological survey, a structural model was built in the PLS-PM program (Figure 2).

The process of evaluating the resulting model consists of two stages:

1) Model validation: confirmatory factor analysis

2) Testing the structural model: a path analysis.

Stage 1.

Confirmatory factor analysis quantitatively describes the data structure of a model. In the first step, the magnitude of the Outer Loadings of the model is estimated from the standpoint of compliance with the established standards. Most of the coefficients for the independent variables X and the dependent variables Y have values above 0.7. 10 coefficients out of 17 satisfy the requirements, which allow the model to be adequate. Low values are present in blocks of independent variables and indicate that there are many identical values (for example, 5.2 – young people graduated from an educational institution mainly 2-3 years ago), or vice versa, there are many polar values (1.3 – the number of jobs per working life).

In the second step, all variants of test questions are evaluated, i.e., the internal consistency of the test questions in each block is checked and the effect of each question on the latent variable is measured. This assessment is carried out using Cronbach’s Alpha coefficient (Table 2).

Cronbach's Alpha coefficient serves as a measure of the uniformity (internal consistency) of the indicator scores. Coefficient scale: 0.6 – low; 0.7 – satisfactory; 0.8 – good; 0.9 – high.

For four of the five variables in the model, the Cronbach's Alpha scores high, this indicates acceptable fitness statistics.

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To demonstrate the reliability of instruments, indicators are also calculated - rho_A, Composite Reliability, and Average Variance Extracted. The range for all three odds is 0.5.

The mean-variance recovery factor (AVE) is the variance of the indicator elements. The AVE value must be 0.5 or more, but less than the cumulative reliability (CR). That is, the variance due to the design must be greater than the measurement error and greater than the cross-load. Since AVE and the corresponding confidence factors are based on factor loadings, their values vary depending on the factor model. The AVE for a factor or latent variable must also be higher than its squared correlation with any other factor or latent variable.

CR is the Composite Reliability, which determines the overall reliability of a structure. The coefficient is calculated using the squared sum of the standardized factor loadings and the sum of the variance of the errors. The CR value is in the range of 0 to 1. A coefficient equal to 1 corresponds to absolute reliability. CR thresholds: 0.6 – suitable for exploratory studies, 0.7 – for confirmatory studies, 0.8 or higher – this is good reliability for confirmatory studies.

In the third step, collinearity is assessed. Factors that are closely related are deduced from the model since the condition of independence between the explanatory variables is violated. What remains in the model is the factor that, with a sufficiently close connection with the result, has the least tightness of connection with other factors.

Table 3 shows the resulting collinearity statistics. VIF is used to detect multicollinearity. The maximum allowable value of this indicator is 5, and the minimum threshold is 0.2.

The data in Table 3 are in the acceptable range of values, which indicates that there is no multicollinearity between the variables.

In the fourth step, the determination coefficient is formed. The squared multiple correlation is the proportion of the variance of the dependent variable explained by the model under study (independent variables). The relationship between the dependent and independent variables grows as the coefficient approaches one.

R Square Adjusted is the adjusted coefficient of determination. It is used to compare models with different numbers of factors so that the number of factors does not affect the R-squared statistic.

The correlation coefficient obtained in the model for the variable Y1 “Current place of work” is 0.724, that is, about 70% of the variance of this construction is explained by this model (Table 4).

ECONOMY Series. № 1(105)/2022

The model identified two dependent variables, Y1 (current place of work) and Y2 (respondent’s assessment of participation in the project). The “current place of work” is 74% dependent on the factors included in this model. Two hypotheses for determining the influence of independent variables in the model were confirmed, i.e. the relations were found to be statistically significant.

Hypothesis 1 Position in the labor market -> Place of work currently has the strongest relationship of influence, 0.765. The status in the labor market, the level of education, the number of jobs during the working life has a statistically significant effect on the place of work at present (Figure 3).

Since the variable X1 has no connection with the Youth Practice Project, it can be said that the present place of work is determined more by these factors than by participation in the project. This is confirmed by direct statistical structural analysis, according to which 72% of respondents indicated that there is no productive relationship between the current situation in the labor market and participation in the project (24% are unemployed; 48% said they work, but there is no connection with the project).

Hypothesis 3 Parameters of participation in the project -> Place of work has now been confirmed. Although the strength of the connection is less significant – 0.244, confirmation of the hypothesis means that the parameters of participation we have identified (motivation, characteristics of the workplace in terms of compliance with the diploma and functionality of the specialty, duration of stay in the project), have a statistically significant effect on the young person’s place of work at present. Among the totality of signs by which participation in the project was assessed, the most vulnerable factors that reduce the positive impact of the

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Вестник Карагандинского университета

place of practice on the place of work at present are “duration of work in the project” (0.287) and “motivation” (0.313). The problem is manifested in the fact that, according to the survey results, 33.7% of respondents had been practicing for less than 3 months. As for motivation, 36% did not think too much and came to the project because wages are guaranteed. One can also note the low level of labor contracts concluded at the end of the internship (0.550), which, when projected onto the survey results, reveals 64.1% of those who left the project without concluding an employment contract.

Personal data of respondents (place of residence, year of graduation from the last educational institution, total length of service) do not have a significant impact on the current workplace. This proves that the results of the project can be useful for any participant if the trajectory of participation in the project is correctly selected.

The assessment of participation in the project (Y2) is described by the model factors by 46%. According to the results of hypothesis verification, the current place of work and the parameters of participation in the project have a significant impact on the assessment of participation in the project.

Hypothesis 7 Current place of work -> Assessment of participation in the project. The strength of the connection between the project assessment and the current place of work is 0.214, P Values = 0.048, almost at the border of statistical significance. The fact is that the assessment of participation in the project tends to a large extent to a positive spectrum of opinions, regardless of the final result of participation in the project as an employment contract. Only a quarter of the participants find a permanent job as a result of the project, but approximately 70% of the participants assess their experience of participation in the project as positive, including expanding the range of contacts.

Hypothesis 4 Parameters of participation in the project -> Assessment of participation in the project is confirmed. The bond strength with the parameters of participation in the project is strong 0.620. This is determined because almost 74% note the full or significant correspondence between the place of work and the functions performed in the project and the specialty of the diploma.

The situation in the labor market is negatively associated with the assessment of participation in the project -0.124, although the value is statistically insignificant. The negative sign of the coefficient is formed since 50% of participants have a college education and it is this group that forms the negative spectrum. They come to the program after 1-2 years of absence from the labor market or casual employment (according to the law; it is possible to come within 3 years after graduation) and therefore the effectiveness of this group is low.

Discussions

We agree with opinion 5 that intermediaries between employers and jobseekers - Employment Centers – play a significant role in increasing the social impact and productive outcome of the Youth Practice project. The most problematic aspect of the project is the short participation period of fewer than 6 months. It should be noted that this factor depends on the careful work of the Center and the individual approach to the participant. There are significant differences in the practice of the Centers: some Centers give the participant the chance to continue working after a funding interruption at the end of the calendar year, while others do not. We also support authors 6, 7 who talk about preparing the applicant for the employer, which also largely depends on the Center. Comparing the managerial styles of different centers makes sure that within the same project there can be different results of the centers.

We also became convinced of the importance of employment centers using methods of activating young people, as indicated by researchers in papers 10-11. Insufficient equipment of the Centers, for example, tests for the psychological competence of the applicant, do not allow him to choose a fully adequate place of practice, considering personal characteristics. Some problems lie on the side of the program itself, as indicated in source 20. Provisions of the program that reduce the social effect are territorial restrictions on the employment of young people in the project, as well as the inability to change employers at least once during the period of participation.

Conclusions

The Youth Practice project is one of the directions of the State Program for the Development of Productive Employment and Small Business, which is intended to give practical experience to a university or college graduate. Spending in this area is roughly in line with the current OECD averages with GDP.

The assessment of objective and subjective factors affecting the sustainability of the project results as a contract for permanent work 1–1.5 years after graduation was carried out by us using the PLS-PM structural model.

The most significant influence on the result is exerted by objective factors (the correspondence of the workplace in the project and the functionality of the specialty according to the diploma, the duration of stay in the project) and the subjective factor is motivation to work. There are problems in this block in terms of the length of stay in the project, because 33% stay in the project for less than half of the term. Motivation is also low in 35% of participants, they are inactive. This emphasizes the importance of an individual approach to each participant, the search for an acceptable option for him in terms of internal psychological competencies and the initial adaptation of the applicant, adaptation to the employer. The latter requires from the employees of the Employment Center close contact with the employer and preliminary acquaintance of the young person with the peculiarities of the workplace in his organization.

The positive contact between the assessment of participation in the project by the applicant and the place of work in the project suggests that some young people move from passive motivation to more active if the functionality of the workplace corresponds to the diploma and the terms of practice are maintained for 6 months or more.

There is a problem in that 72% of participants, one year after leaving the project, indicate that there is no connection between their current position in the labor market (the current place of work was acquired with no connection with the project or the respondent is unemployed) and participation in the program. If we consider that the personal data of the respondents (place of residence, year of graduation from the last educational institution, general work experience) do not have a significant impact on the result of the project, then this confirms the conclusion that the results of the project can be useful for any participant if the trajectory of participation is correctly selected.

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