scholarly journals Essential work and emergency childcare: Identifying gender differences in COVID-19 effects on labour demand and supply

2020 ◽  
Author(s):  
Jordy Meekes ◽  
Wolter H.J. Hassink ◽  
Guyonne R.J. Kalb
Keyword(s):  
Gender Differences ◽  
Essential Work ◽  
Labour Demand ◽  
Demand And Supply

Estimating Labour Supply in Policy-Oriented Regional Planning Models

1992 ◽  
Vol 24 (12) ◽  
pp. 1781-1797 ◽  
Author(s):  
D E Fuller
Keyword(s):  
Population Structure ◽  
Regional Planning ◽  
Labour Supply ◽  
Traditional Approach ◽  
Labour Force ◽  
Labour Demand ◽  
Regional Models ◽  
Demand And Supply ◽  
Planning Models ◽  
The Relationship

The importance of integrating policies concerned with the demand and supply of labour within growing regions has long been recognized. However, there are important theoretical deficiencies associated with orthodox methods. In the traditional approach to operational urban and regional models it is claimed that the relationship between labour demand and labour supply is functional and one sided, that is, the growth of labour demand causes population growth and leads to an assured level of labour supply. However it is argued that in the development of regional labour-force policies aimed at recognized objectives, estimates of the number and characteristics of persons available to the labour force are at least as important as estimates of the structure of labour demand. A change in the traditional theoretical framework is therefore necessary to allow for the influence of a particular population structure upon the supply of labour—in aggregate as well as to different occupational submarkets. Presentation of a more independent treatment of methods aimed at estimating the ‘availability’ (and the ‘requirements’) of labour also allows for the possibility, and consequences, of imbalance in the labour market to be recognized.

Unemployment in Ghana: a cross sectional analysis from demand and supply perspectives

2015 ◽  
Vol 6 (4) ◽  
pp. 402-415 ◽  
Author(s):  
William Baah-Boateng
Keyword(s):  
Household Survey ◽  
Baseline Survey ◽  
Labour Demand ◽  
Cross Sectional ◽  
Data Set ◽  
Demand And Supply ◽  
Content Type ◽  
Cross Sectional Analysis ◽  
Nationally Representative ◽  
Sectional Analysis

Purpose – The purpose of this paper is to analyse the causes of unemployment in Ghana from both labour demand and supply perspectives based on most recent cross sectional data set from one nationally representative household survey and a baseline survey for Millennium Development Support. Design/methodology/approach – A logit regression estimation technique is applied to two different household survey data sets of 2008 and 2013 to capture the effect of labour demand and supply on unemployment. Findings – Using education and age as capability variables to represent supply factors, unemployment is found to increase with education, and declines with age, confirming higher unemployment rate among the youth, than the old. The paper also observes strong influence of demand factors on unemployment based on relatively higher incidence of unemployment fulltime jobseekers relative to part-time jobseekers and seekers of formal or wage-employment and self-employment or SMEs compared with those seeking any job. Other factors such as the individual’s reservation wage, marital status, sex and poverty status as well as their rural-urban location are also found to cause unemployment in Ghana. Practical implications – Unemployment as a result of the inability of individuals to obtain a job of their choice in the midst of strong economic growth in Ghana suggests weak employment content of growth. In contrast, an increasing phenomenon of unemployment with education also reflects a problem of skill mismatch between skills churn out by education and training institutions and skills requirement by firms in the labour market. Originality/value – The originality of the paper and its contribution to existing literature largely emanate from the inclusion of demand factors in a cross sectional analysis of causes of unemployment.

scholarly journals Better understanding of the labour market using Big Data

2021 ◽  
Vol 20 (3) ◽  
pp. 677-692
Author(s):  
Alena Vankevich ◽  
Iryna Kalinouskaya
Keyword(s):  
Big Data ◽  
Labour Market ◽  
Labour Demand ◽  
Demand And Supply ◽  
Internet Users ◽  
New Information ◽  
Study Results ◽  
Effective Decision ◽  
Effective Decision Making

Motivation: As the result of digitalisation of the economy, the number of Internet users is increasing, which leads to an increase in the number of vacancies posted on online platforms and services. The description of vacancies includes information about skills and competencies, which is the source of additional data for the labour market analysis. This information cannot be received through the analysis of statistical and administrative data. Therefore, it is important: — to learn how to evaluate new information sources, and use the data they generate; — to develop tools that people and organizations will use for finding an employee or a vacant post. The study focuses on the analysis and forecast of labour demand in the context of skills and competencies, which significantly enriches and adds to the information about the labour market and facilitates effective decision-making. Aim: The main goals of this article are the following: (1) identification of the methodological approaches in the labour market analyses using Big Data; (2) assessment of the labour demand and labour supply in the context of skills and competencies listed in the vacancy description posted on job portals; and (3) determination of the matches (mismatches) between skills and competencies in order to help the companies and individuals get better employment and education. Empirical data used in the research were collected from the description of job vacancies (16 401 vacancies) and CVs (227 215 CVs) from the most popular open job portals in Belarus through the scraping approach and classified according to the ESCO and ISCO codes. Quantitative analysis by the means of artificial intelligence was used in the research. Results: The study results revealed that the information about the volume and structure of skills and competencies obtained by scraping data from vacancy descriptions and Cvs, which are posted on online portals, allows for more precise diagnostics of labour demand and supply and overcoming of bilateral information asymmetry in the labour market. Based on the analysis, the parameters of scarcity and excess in competencies for individual occupations in the labour market are determined (the level of the correlation ratio between applicants’ competencies and those requested by employers in the context of occupations (four digits according to the ISCO classification) is less 0.8; the deviation of the ranks of competencies listed in CVs and vacancy descriptions according to the ESCO groups of skills/competencies and a sign of revealed deviations). The methodology is developed to set areas for necessary knowledge acquisition (by the analysis of competencies listed in CVs and vacancy descriptions at the 3rd and 4th digit level of ISCED classification) and skills (by the analysis of competencies at the 2nd digit level in ESCO groups). The paper illustrates limitations in using Big Data as an empirical database and explains the measures to eliminate those limitations.

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