Chioma18-fav/nigeria-Labour-Market-analysis

Survey-weighted analysis of Nigeria's labour market using the Nigeria Labour Force Survey (NLFS) Dataset from NBS # nigeria-labour-market-analysis Survey-weighted analysis of Nigeria's labour market using the Nigeria Labour Force Survey (NLFS) Dataset from NBS ## Background and Overview The Nigeria Labour Force Survey (NLFS), published by the National Bureau of Statistics (NBS), is Nigeria's primary source of information on employment, education, occupations, business activities, and other labour market characteristics. This project was undertaken to examine the structure of Nigeria's labour market and identify how demographic, educational, business, and regional characteristics are associated with labour market participation, occupational distribution, and business registration. The objective was to transform the NLFS microdata into meaningful labour market insights that can support evidence-based policymaking, workforce planning, and future labour market research. To achieve this, the project analyzed four consecutive survey quarters (Q3 2024 to Q2 2025), developed survey-weighted labour market indicators, validated selected findings using appropriate statistical methods, and presented the results through an interactive Power BI dashboard. ## Data Structure Overview The analysis was conducted using four consecutive quarters of the Nigeria Labour Force Survey (NLFS): Q3 2024, Q4 2024, Q1 2025, and Q2 2025. Each quarterly dataset contains detailed information describing the socioeconomic and labour market characteristics of individuals across Nigeria. The variables cover multiple aspects of the labour market, including: - Demographic characteristics (age, sex, state, geopolitical zone, and urban/rural residence) - Educational attainment - Employment status - Occupation and industry - Business ownership and registration - Employment type - Survey design variables, including survey weights, primary sampling units (PSUs), and strata To create a unified analytical dataset, the four quarterly datasets were first consolidated in Python before being imported into PostgreSQL. …