# **I. Introduction**

Understanding firms’ needs and constraints in terms of workforce and related skills is key to designing better education and labor market policies. In Kosovo, a perception of skill shortages among firms and an oversupply of labor, especially youth entering the labor market, coexist. Aligning policies, training programs and curricula to the current and future needs of the labor market is challenging in the absence of relevant and real-time data. Data on labor supply and the results of job matches are available from standard surveys such as the Labor Force Survey, while detailed data on job creation and skill needs are often scarce. This paper exploits online vacancy data from the four largest job portals in Kosovo in 2018 to better understand its potential for addressing important information gaps between labor market demand and skills.

The key contribution of this paper is to provide an analysis of skill demand with a high level of granularity and precision, such that our results can directly inform policy making. We conduct a textual analysis of the job descriptions and job titles to identify the incidence of skills, education, and experience requirements across industries. For this purpose, we construct search dictionaries of specific keywords, key phrases and text patterns to approximate demand for skills, education, and work experience with the occurrence of these in job portal ads. For the skill analysis, we develop a skill taxonomy that consists of three layers, providing detailed information on skills in demand. First, we employ a general taxonomy that is in line with the literature on skills to show how demand varies across socio-emotional, cognitive, and technical skills.<sup>2</sup> Second, we disaggregate these three broad types of skills into 15 categories (one cognitive skill, five socio-emotional skills, and nine technical skills) to investigate how demand for specific skills varies across industries and occupations. Third, each of the 15 categories is defined by 152 skill requirements, which offers the highest level of granularity in the analysis of skills in demand. This layer is especially useful for providing youth with information about the skills employers seek, and for informing curricula on the specific skills that are needed in the labor market (e.g., which software or coding language is used in the computer science field). To precisely measure each skill requirement, we build a set of language-specific key words, key phrases and text patterns, which allow to identify the skill requirement in the job descriptions. Notably, such granularity and flexibility in an analysis of skill demand is only possible when using job ads directly and accounting for various possible ways of expressing skills in the text.

The main findings can be summarized as follows. To begin, extraversion, computer and foreign language skills are most in demand across all industries and occupations. Socio-emotional skills as a whole have a high

> 2 The most oft-used framework in the literature of skill formation focuses on cognitive versus non-cognitive skills (Cunha et al., 2006; Heckman et al., 2006; Kautz et al., 2015). However, given that we are interested in the skills required by employers, we focus on job-related skills following the literature on skills at work. Pierre et al. (2014) and World Bank (2018) use a similar categorization, which reflects skills developed later in life from secondary schooling to young adulthood, through general education, technical education or on-the-job training.

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