A Web-Based Approach to Measure Skill Mismatches and Skills Profiles for a Developing Country:. Jeisson Arley Cárdenas Rubio
such as wages, occupations, education, etc., to understand biases, errors, and inconsistencies within the database. The evaluation of external validity was particularly challenging because countries like Colombia do not have vacancy censuses (or anything similar) to compare information collected from job portals. Despite several obstacles, this book provides and applies a methodology framework to evaluate the vacancy database. It implements a detailed comparison between official information available in the country (i.e. household surveys) and vacancy data results, such as vacancy, employment, new hires, unemployment, occupational structures and their dynamics over the study period. This comparison enables the understanding of possible biases (e.g. over/underrepresentation of certain occupational groups) in the vacancy database (Chapter 8).
Based on the validation results, another methodological contribution of this document is 8) proposing and estimating skill mismatch measures that consider the advantages and limitations of job portals and household surveys. Specifically, the study demonstrates how household surveys can be combined with vacancy data to produce relevant (volume- and price-based) skill shortage indicators, such as percentage change in unemployment by sought occupation, percentage change in median real hourly wage, among others. Importantly, 9) this book makes an important contribution to the discussion about skill mismatch measures by considering informality. As will be discussed in Chapter 9, informality is a signal of labour market imbalance. A considerable portion of employment growth might be explained because people cannot find a formal job and have to choose informal jobs. Thus, skill shortage indicators need to control for informality to avoid misleading results.
Based on the above methodology, this book also makes relevant empirical contributions by providing a detailed labour market analysis that reveals important characteristics of the Colombian labour demand (e.g. demanded skills and occupational trends). Importantly, it determines skill mismatches (i.e. skill shortages) in Colombia based on information from job portals and household surveys. Specifically, the analysis of the vacancy database evidences that 1) data collected from job portals are representative of a considerable set of non-agricultural, non-governmental, non-military, and non-self-employed (“business owners”) occupations; 2) most of the vacancies in Colombia correspond to middle- and low-skilled occupations (such as “Sales demonstrators”); 3) in alignment with the most demanded occupations, the most demanded skills are “Customer service,” “Work in teams,” etc.; and, most importantly, 4) information from job portals can be used to identify new or specific job titles (e.g. “TAT vendors,” “Picking and packing assistants,” etc.) and skills (e.g. “Siigo,” “Perifoneos,” etc.) for the Colombian context.
Based on the advances made towards homologating vacancy and household survey information (e.g. coding both databases according to ISCO-08), a comprehensive analysis of labour demand and supply information is conducted at the occupational level (Chapter 9), for the first time in Colombia. Another important contribution of this analysis consists of 5) showing in detail population groups with higher (lower) informality and unemployment rates. For instance, domestic cleaners and helpers and motorcycle drivers face the highest informality, while environmental engineers and geologists and geophysicists face the highest unemployment rate in the country. In addition, 6) it also estimates skill shortages using job portals and vacancy information. For instance, it evidences that 30 occupations show signals of skill mismatches, while indicating that Structured Query Language (SQL), database management, and JavaScript are the most demanded skills for one of those occupation groups (“Web and multimedia developers”).
Briefly, skill mismatches arise when there is a misalignment between the demand and supply of skills in the labour market (UKCES 2014). As will be discussed in Chapters 2 and 3, numerous multidisciplinary studies have pointed out the importance of these phenomena in labour market outcomes, such as unemployment and informality, among others. Skill mismatches can occur in the job search process (e.g. skill shortages) or in the workplace (e.g. skill gaps). Given that the term “skill mismatches” encompasses different dimensions and considering available data to analyse an economy such as Colombia (i.e. job portals and household surveys), this book focuses on studying skill shortages. This concept refers to issues that arise in the job searching process when jobseekers do not have the proper skills required in vacancies posted by employers (Green, Machin, and Wilkinson 1998).
A proper labour market analysis system to identify possible skill shortages and current employer skill requirements is paramount for a country such as Colombia with high and persistent unemployment and informality rates (DANE 2017a). According to the Colombian statistics office (National Administrative Department of Statistics; DANE for its acronym in Spanish), in the last two decades unemployment and informality rates were around 12.5% and 49.4%, respectively. A vast number of factors, such as rigid wages, comparatively high non-wage costs, etc., could explain these labour market outcomes. However, as will be discussed in Chapters 2 and 3, theoretical and empirical evidence shows that mismatches between demanded skills and those offered is a main cause of unemployment and increased informality rates in Colombia (Álvarez and Hofstetter 2014; ManpowerGroup, n.d.; Arango and Hamann 2013). Workers, the government, as well as education and training providers are not properly anticipating employer requirements. Consequently, the labour supply lacks skills in relation to what employers are demanding in order to fill their vacancies.
Despite evidence that suggests that there is a high incidence of skill shortages in the Colombian labour market, education and training providers, workers, and the government can do little to reduce imperfect information regarding human capital requirements due to a lack of proper information to develop well-orientated decisions and public policies (González-Velosa and Rosas-Shady 2016). On the one hand, the cost of conducting household or sectoral surveys (traditional sources of information) is relatively high in terms of resources and time. On the other hand, these data sources usually fail to provide detailed and updated information about skills and occupational requirements. These issues have discouraged countries (especially those with low budgets) from collecting information on and analysing human capital needs.
For instance, the Colombian office for national statistics (DANE) periodically conducts household and sectoral surveys that provide valuable insights about the characteristics of the Colombian workforce, job training, selection and hiring practices, productivity, etc. However, due to sample constraints and the relatively high operational cost of conducting these surveys (e.g. the job of interviewers and statisticians, etc.), the data collected do not convey detailed information about employer requirements—the occupational structure demanded—nor about the skills required for each position. Thus, the characteristics and dynamics of labour demand remain relatively unknown.
Consequently, to fill these critical information gaps, it is vital to seek new ways of analysing labour demand that can consistently complement existing surveys (e.g. household surveys). Big Data have become a trendy field because it deals with the analysis of large data sets, in real time, from different sources of information (Edelman 2012; Reimsbach-Kounatze 2015). Using job portals and Big Data techniques to analyse employer requirements constitutes an alternative that has attracted the attention of researchers and policymakers. Employers post a considerable number of vacancies on online job portals along with detailed candidate requirements (job title, wages, skills, education, experience, etc.), which provides quick access to a large amount of relevant information for the analysis of labour demand. This online data can provide key insights about labour demand that previously were not accessible for proper analysis (Kureková, Beblavy, and Thum 2014).
Collecting, processing, and analysing information from job portals through reliable and consistent statistical processes is challenging because data are dispersed across different websites and the information is not categorised or standardised for economic analysis. Additionally, the discussion regarding the use of Big Data sources, such as job portals for labour market analysis, is flawed (Kureková, Beblavy, and Thum