A web-based approach to measure skill mismatches and skills profiles for a developing country : : the case of Colombia /

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A web-based approach to measure skill mismatches and skills profiles for a developing country : : the case of Colombia / / Jeisson Cárdenas Rubio.

Several interdisciplinary studies highlight imperfect information as a possible explanation of skill mismatches, which in turn has implications for unemployment and informality rates. Despite information failures and their consequences, countries like Colombia (where informality and unemployment rat...

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Bibliographic Details
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Cárdenas Rubio, Jeisson,
Place / Publishing House:Bogotá : : Editorial Universidad del Rosario,, 2020.
Year of Publication:2020
Language:Spanish
Physical Description:1 online resource (xx, 449 pages) :; illustrations
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Table of Contents:
  • PGINA LEGAL
  • 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
  • 2.3. HOW THE LABOUR MARKET WORKS UNDER PERFECT COMPETITION
  • 2.4. MARKET IMPERFECTIONS AND SEGMENTATION
  • 2.5. CONCLUSION
  • 3. THE COLOMBIAN CONTEXT
  • 3.1. INTRODUCTION
  • 3.2. THE CHARACTERISTICS OF THE COLOMBIAN LABOUR MARKET
  • 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
  • 4.4. POTENTIAL USES OF INFORMATION FROM JOB PORTALS TO TACKLE SKILL SHORTAGES
  • 4.5. BIG DATA LIMITATIONS AND CAVEATS
  • 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
  • 5.6. CONCLUSION
  • 6. EXTRACTING MORE VALUE FROM JOB VACANCY INFORMATION
  • 6.1. INTRODUCTION
  • 6.2. IDENTIFYING SKILLS
  • 6.3. IDENTIFYING NEW OR SPECIFIC SKILLS
  • 6.4. CLASSIFYING VACANCIES INTO OCCUPATIONS
  • 6.5. DEDUPLICATION
  • 6.6. IMPUTING MISSING VALUES
  • 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
  • 7.4. LABOUR DEMAND FOR SKILLS
  • 7.5. DEMAND BY SECTOR
  • 7.6. TRENDS IN THE LABOUR DEMAND
  • 7.7. WAGES
  • 7.8. OTHER CHARACTERISTICS OF THE VACANCY DATABASE
  • 7.9. CONCLUSION
  • 8. INTERNAL AND EXTERNAL VALIDITY OF THE VACANCY DATABASE
  • 8.1. INTRODUCTION
  • 8.2. INTERNAL VALIDITY
  • 8.3. EXTERNAL VALIDITY
  • 8.4. CONCLUSION
  • 9. POSSIBLE USES OF LABOUR DEMAND AND SUPPLY INFORMATION TO REDUCE SKILL (...)
  • 9.1. INTRODUCTION
  • 9.2. LABOUR MARKET DESCRIPTION
  • 9.3. MEASURING POSSIBLE SKILL MISMATCHES (MACRO-INDICATORS)
  • 9.4. DETAILED INFORMATION ABOUT OCCUPATIONS AND SKILL MATCHING
  • 9.5. CONCLUSIONS
  • 10. CONCLUSIONS AND IMPLICATIONS
  • 10.1. INTRODUCTION
  • 10.2. CONCEPTUAL CONTRIBUTIONS
  • 10.3. CONTRIBUTIONS TO METHODOLOGY
  • 10.4. EMPIRICAL CONTRIBUTIONS
  • 10.5. IMPLICATIONS FOR PRACTICE AND POLICY
  • 10.6. LIMITATIONS
  • 10.7. FURTHER RESEARCH
  • 10.8. CONCLUSIONS
  • REFERENCES
  • APPENDIX
  • APPENDIX A: EXAMPLES OF JOB PORTAL STRUCTURES
  • APPENDIX B: TEXT MINING
  • APPENDIX C: DETAILED PROCESS DESCRIPTION FOR THE CLASSIFICATION OF COMPANIES
  • APPENDIX D: MACHINE LEARNING ALGORITHMS
  • APPENDIX E: SUPPORT VECTOR MACHINE (SVM)
  • APPENDIX F: SVM USING JOB TITLES
  • APPENDIX G: NEAREST NEIGHBOUR ALGORITHM USING JOB TITLES
  • APPENDIX H: ADDITIONAL TABLES.

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