Introduction
The report explores global employment trends from 2000 to 2019 using data from the World Bank's World Development Indicators. It aims to identify shifts in employment types, the relationship between employment data and GDP, and significant changes across countries. The focus is on six countries, including developing (Brazil, China, India) and developed (United States, United Kingdom, Japan) nations.
Aims
The main goal is to analyze employment trends by type and industry, assess employment-to-population ratios, and explore GDP's influence on employment. The study aims to highlight the structural changes over time and identify correlated indicators using Principal Component Analysis (PCA).
Methods
The research follows the ASSERT model: asking questions, searching for data, structuring the data, visualizing answers, and storytelling. Various visualizations, such as line charts, bar charts, scatter plots, and PCA, are employed to analyze trends, proportions, and relationships.
Results
The analysis reveals distinct patterns across countries: Employment-to-Population Ratio: Stable in developed countries, with slight drops in China and India. A noticeable decline in youth employment is observed.
Employment Types: Developed nations show higher wage employment, while self-employment is prevalent in developing countries. Vulnerable employment is decreasing globally, led by China.
Industry Analysis: A shift from agriculture to industry and services, particularly in China and India, with developed countries maintaining low agricultural employment.
PCA Findings: China exhibits the most significant changes in employment, with GDP closely linked to indicators like service employment and wage work.
Conclusion
The findings underscore disparities between developed and developing nations in employment structure and growth. The analysis indicates that economic development influences employment transitions, with service sector growth correlating with higher GDP. Further research could refine data sources and examine additional socioeconomic factors.