A Web-Based Approach to Measure Skill Mismatches and Skills Profiles for a Developing Country: The Case of Colombia..

Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor principal: Rubio, Jeisson Arley Cárdenas
Formato: Electrónico eBook
Idioma:Inglés
Publicado: [Place of publication not identified] : Siglo del Hombre Editores : Siglo del Hombre Editores, 2020.
Temas:
Skilled labor > Colombia.
Labor market > Colombia > Statistics.
Marché du travail > Colombie > Statistiques.
Labor market
Skilled labor
Colombia
Statistics
Acceso en línea:Texto completo
Tabla de Contenidos:
  • Intro
  • Half-Title Page
  • Title Page
  • Copyright Page
  • Author
  • 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
  • 5.1. Introduction
  • 5.2. Measurement of the labour demand: Job vacancies
  • 5.3. Selecting the most important vacancy websites in the country
  • 5.4. Web scraping
  • 5.5. The organisation and homogenisation of information
  • 5.5.1. Education, experience, localisation, among other job characteristics
  • 5.5.2. Wages
  • 5.5.3. Company classification
  • 5.6. Conclusion
  • 6. Extracting More Value from Job Vacancy Information (Methodology Part 2)
  • 6.1. Introduction
  • 6.2. Identifying skills
  • 6.3. Identifying new or specific skills
  • 6.4. Classifying vacancies into occupations
  • 6.4.1. Manual coding
  • 6.4.2. Cleaning
  • 6.4.3. Cascot
  • 6.4.4. Revisiting manual coding (again)
  • 6.4.5. Adaptation of Cascot according to Colombian occupational titles
  • 6.4.6. The English version of Cascot
  • 6.4.7. Machine learning
  • 6.5. Deduplication
  • 6.6. Imputing missing values
  • 6.6.1. Imputing educational requirements
  • 6.6.2. Imputing the wage variable
  • 6.7. Vacancy data structure
  • 6.8. Conclusion
  • 7. Descriptive Analysis of the Vacancy Database
  • 7.1. Introduction
  • 7.2. Vacancy database composition
  • 7.3. Geographical distribution of vacancies and number of jobs

Ejemplares similares