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JSTOR_on1341997265 |
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OCoLC |
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20231005004200.0 |
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|a 1236925352
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|a 9789587845457
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|a 331.1109861
|2 23
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|a UAMI
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|a Rubio, Jeisson Arley Cárdenas.
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|a A Web-Based Approach to Measure Skill Mismatches and Skills Profiles for a Developing Country: The Case of Colombia..
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| 264 |
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|a [Place of publication not identified] :
|b Siglo del Hombre Editores :
|b Siglo del Hombre Editores,
|c 2020.
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| 300 |
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|a 1 online resource.
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| 336 |
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|a text
|b txt
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|a 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
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|a 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
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| 505 |
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|a 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
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|a 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
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| 505 |
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|a 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
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|a Skilled labor
|z Colombia.
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|a Labor market
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6 |
|a Marché du travail
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|a Colombia
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|u https://jstor.uam.elogim.com/stable/10.2307/j.ctv1g6q8dv
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|a EBSCOhost
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|n 2746469
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| 938 |
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|a Digitalia Publishing
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|a ProQuest Ebook Central
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