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COVID-19 Pandemic: Global Labour Market Data
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About
This dataset presents modelled estimates from ILOSTAT detailing the impact of the COVID-19 pandemic on global employment. It provides crucial insights into how working hours and employment figures were affected, primarily focusing on data from 2020. The information was gathered from various datasets within the ILOSTAT website's COVID-19 monitoring section, offering a critical resource for understanding the early labour market repercussions of the pandemic.
Columns
- country: The name of the country.
- total_weekly_hours_worked(estimates_in_thousands): Estimated total weekly hours worked by employed persons.
- percentage_of_working_hrs_lost(%): The percentage of working hours lost when compared to a baseline from the fourth quarter of 2019.
- percent_hours_lost_40hrs_per_week(thousands): The percentage of hours lost, expressed as full-time equivalent employment losses based on a 40-hour work week, calculated by dividing weekly hours lost due to COVID-19 by 40.
- percent_hours_lost_48hrs_per_week(thousands): The percentage of hours lost, expressed as full-time equivalent employment losses based on a 48-hour work week, calculated by dividing weekly hours lost due to COVID-19 by 48.
- labour_dependency_ratio: The ratio of dependants (persons aged 0 to 14 plus persons aged 15 and above who are either outside the labour force or unemployed) to total employment.
- employed_female_25+_2019(estimates in thousands): Estimated number of employed females aged 25 and over in 2019, covering both paid employment and self-employment.
- employed_male_25+_2019(estimates in thousands): Estimated number of employed males aged 25 and over in 2019, covering both paid employment and self-employment.
- ratio_of_weekly_hours_worked_by_population_age_15-64: The ratio of total weekly hours worked to the population aged 15-64.
Distribution
The dataset is provided as a CSV file, named
employment_data.csv, with a size of 24.78 kB. It contains 9 columns and consists of 283 records or rows, with each country representing a unique value. Data files are typically in CSV format and sample files are updated separately to the platform.Usage
This dataset is ideal for:
- Analysing the global impact of COVID-19 on employment patterns.
- Studying labour market dynamics and changes in working hours during a global crisis.
- Modelling economic consequences of pandemics on national workforces.
- Researching gender-specific employment trends among the older working population (25+).
- Informing policy development related to employment recovery and social protection.
- Conducting social science research and survey analysis on global social issues.
Coverage
The dataset offers global geographic coverage, presenting country-level employment data. The time range for most estimates is 2020, with baselines for hours lost calculations set to the fourth quarter of 2019. Data for employed females and males is specifically for 2019. The demographic scope includes employed persons, the population aged 15-64, dependants (0-14 and 15+ outside the labour force or unemployed), and employed females/males aged 25+.
License
CC0: Public Domain
Who Can Use It
This dataset is valuable for a wide range of users, including:
- Academics and researchers in economics, sociology, and public health, for in-depth studies on pandemic effects.
- Government agencies and policymakers for assessing labour market damage and designing intervention strategies.
- International organisations focusing on global development and social welfare.
- Data scientists and analysts building models for employment forecasting and impact assessment.
- Journalists and advocacy groups reporting on social issues and advocating for labour rights.
Dataset Name Suggestions
- ILOSTAT Global Employment Impact: COVID-19 (2020)
- COVID-19 Pandemic: Global Labour Market Data
- World Employment Statistics: ILOSTAT COVID-19
- Hours Lost & Employment: Global COVID-19 Data
- International Labour Organisation: COVID-19 Employment Estimates
Attributes
Original Data Source:COVID-19 Pandemic: Global Labour Market Data
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