A Web-Based Approach to Measure Skill Mismatches and Skills Profiles for a Developing Country:. Jeisson Arley Cárdenas Rubio

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      Author

      Jeisson Cárdenas Rubio is a labour economist who works at the Institute for Employment Research in the United Kingdom. He has worked as a consultant for the World Bank, the Inter-American Development Bank, the National Administrative Department of Statistics, the Ministry of Labour in Colombia, among other institutions. He has a PhD in Employment Research from the University of Warwick. His research has focused on measuring the possible effects of Coronavirus in the Colombian labour market, analysing housing prices in Colombia with internet data, investigating diesel market integration in France, and discussing the issue of labour demand analysis in Colombia.

      Contents

       List of Figures

       List of Tables

       Acronyms and Abbreviations

       1. Introduction

       2. The Labour Market and Skill Mismatches

2.1. Introduction

2.2. Basic definitions

2.2.1. Labour supply

2.2.2. Labour demand

2.2.3. Informal economy

2.2.4. Skills

2.3. How the labour market works under perfect competition

2.3.1. Labour demand

2.3.2. Labour supply

2.3.3. Market equilibrium

2.4. Market imperfections and segmentation

2.4.1. Segmentation

2.4.2. Imperfect market information

2.5. Conclusion

3. The Colombian Context

3.1. Introduction

3.2. The characteristics of the Colombian labour market

3.2.1. Labour supply

3.2.2. Labour demand

3.3. Skill mismatches in Colombia

3.4. An international example of skill mismatch measures

3.5. Lack of accurate information to develop well-orientated public policies

3.6. Conclusion

       4. The Information Problem: Big Data as a Solution for Labour Market Analysis

       4.1. Introduction

       4.2. A definition of Big Data

       4.3. Big Data on the labour market

       4.3.1. Labour supply

       4.3.2. Labour demand

       4.4. Potential uses of information from job portals to tackle skill shortages

       4.4.1. Estimating vacancy levels

       4.4.2. Identifying skills and other job requirements

       4.4.3. Recognising new occupations or skills

       4.4.4. Updating occupation classifications

       4.5. Big Data limitations and caveats

       4.5.1. Data quality

       4.5.2. Job postings are not necessarily real jobs

       4.5.3. Data representativeness

       4.5.4. Limited internet penetration rates

       4.5.5. Data privacy

       4.6. Big Data in the Colombian context

       4.7. Conclusion

       5. Methodology

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