Akram Dartoomi; Mostafa Salimifar; SAEED MALEKOSADATI
Abstract
Introduction
One of the most important challenges in the Iranian labor market is the phenomenon of education-job mismatch, which is reflected as the inequality between the educated labor force and the workforce needed in the labor market. This is despite the fact that in recent decades, according ...
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Introduction
One of the most important challenges in the Iranian labor market is the phenomenon of education-job mismatch, which is reflected as the inequality between the educated labor force and the workforce needed in the labor market. This is despite the fact that in recent decades, according to the country's macro policies, too many resources have been allocated to human resources training, especially at higher education level. The presence of such conditions for the employment of higher education graduates and the lack of due attention to the need for acquiring job skills in the labor market have resulted in a higher unemployment rate for the higher education graduates than for other groups. The most important outcome of this phenomenon is the education-job mismatch.
Education-job mismatch appears in two forms in society: vertical mismatch and horizontal mismatch. Vertical mismatch means the level of education or skill of higher education graduates is more or less than the needs of the society. For example, the country needs workers with bachelor's degree, but the workforce may have higher or lower levels of education. Horizontal mismatch means the field of education or skills of workforce does not correspond to the labor market needs. For example, the country needs agriculture-related graduates, while job seekers are educated in other fields. Among the two types of mismatch mentioned, this paper chose to examine the vertical mismatch between education and occupation. It also intended to measure the scope of the mismatch in some cities of the country and to identify some of the most important factors affecting it.
Method
The present paper pursues two main goals. The first one is to measure the mismatch of education and job and the second is to identify the factors affecting it. For this purpose, the paper takes two general steps. In the first step, the research variables are calculated using the data obtained from the Ian’s Population and Housing census. In the second step, the effect of independent variables on the dependent variable, education-job mismatch, is analyzed using an econometric model. It should be noted that econometric models are estimated annually for individual cities of the country.
This paper uses one of the three methods of measuring mismatch: job Analysis, realized matches and self-assessment. Each of these methods has inherent limitations and difficulties, and none has absolute superiority over the other methods. The choice of method depends on the nature and characteristics of the available data. Considering all available data, this paper uses job analysis method. This method makes a relationship between job needs and education levels using ISCO and ISCED classifications.
Thus, having calculated the mismatch by job analysis method, the effects of independent variables on the dependent variable is estimated using the spatial econometric model. The research variables are: Education-Job Mismatch (EJM), Relative Supply of Educated Labor Force (RSEL), Relative Demand of Educated Labor Force (RDEL), Regional Specialization Index (RS), Standardized Unemployment Rate (SU), and share of older (50–70 years old) (X1), female (X2), and rural (X3) workers.
Discussion and Results
The results of this study suggest that due to the different reasons such as economic, social, and political conditions on the one hand and labor market conditions and labor force characteristics on the other hand, the country has faced job-occupation mismatch in different cities in 1996, 2006, and 2011. This phenomenon occurred due to the lack of educated labor force in the labor market and the shortage of supply and excess demand for labor in 1996. However, in 2006, this shortage declined, as the willingness to higher education increased. Finally, in 2011, educated labor force increased significantly and the education-job mismatch resulted in the excess supply and the shortage of demand. In other words, this phenomenon emerged as undereducation in 1996 and overeducation in 2006 and 2011.
Also, the results of spatial econometric model demonstrated that RSEL had significant negative effects on EJM in 1996 and 2006 and insignificant positive effects in 2011. However, RDEL had a positive and insignificant effect on EJM in 1996 and 2006 and significant negative effects in 2011. Other independent variables had positive effects on the education-job mismatch.
Conclusion
In the present paper, using the data obtained from Iranian Population and Housing Census in the years 1996, 2006, and 2011, the education-job mismatch was calculated in the cities of the country and the affecting factors were identified. The results of the research indicate that if the society faces with a shortage of educated workforce, the relative supply of educated labor will reduce the mismatch and the relative demand of educated labor will increases it. Also, when the country faces a surplus of educated workforce, the relative supply of educated labor increases the mismatch and the relative demand of educated labor reduces it. This is while the number of higher education graduates is increasing rapidly leading to the greater education-job mismatch. To resolve the problem and to reduce the mismatch, it is important to improve communication between universities and educational centers with the labor market, and to remove the barriers to job creation, investment in technology and skill sectors, and workforce mobility between different jobs, occupations and geographical areas.
