PRIDE Consulting proudly presents the first-ever district-level analysis of Pakistan’s labour markets!
Our new report, “District Level Analysis of Lead Labour Market Indicators,” uses data from the Labour Force Survey 2020–21 to examine 9 key indicators across 131 districts.
The findings reveal critical insights shaped by:
✅ District-level disparities
✅ Gender dynamics
✅ Rural–urban divides
This groundbreaking work aims to inform targeted, evidence-based policies for inclusive and sustainable employment.
Title of the Report: District Level Analysis of Lead Labour Market Indicators
Acknowledgment: We wish to acknowledge the dedicated efforts of Dr. Umer Khalid and Dr. Shahid Naeem, who not only developed the initial draft but also worked extensively to incorporate feedback, and finalize the Report. We are also grateful to Dr. Sajjad Akhtar for his valuable guidance in designing the methodology for the district rankings and for authoring Chapters 3 and 4, which present the statistical analyses of the provincial and district-level rankings, respectively. Ms. Asia Imtiaz undertook the data compilation and analysis using the LFS 2020–21 dataset. We appreciate Dr. Amtul Hafeez for her thorough initial review of the Report. Finally, we would like to thank Ms. Ina Pietschmann, Senior Labour Economist, for her insightful feedback on the draft, which significantly contributed to improving the quality of the analysis.
This report presents a district level analysis of Pakistan’s labour market dynamics, using a framework of nine lead labour market indicators computed using data from Labour Force Survey 2020-21. The nine indicators include i) labour force participation rate, ii) employment to population ratio, iii) unemployment rate, iv) underemployment rate, v) employment share by sector (agriculture, manufacturing and services), vi) employment share by status (employees, own-account workers and contributing family workers), vii) share of informal sector employment rate, viii) youth unemployment rate and ix) youth not in employment, education or training. The above indicators are analyzed for 131 districts by three dimensions, national level, gender-wise and across rural-urban landscape.
The report employs a ranking methodology to highlight positional variations across districts for each of the nine indicators, utilizing Rank Ordering and Dense Ranking techniques to ensure fair and consistent rankings of ratios, rates and shares. Top ten and bottom ten districts as per the three dimensions are identified and inter-gender and inter-regional rank ordering are compared for the selected districts. A province-wise summary view of the number of top and bottom ranked districts by each of the eight indicators is also presented and analyzed. A separate chapter conducts rank correlation analysis using Spearman’s formula, examining associations between ranked indicators at overall, gender-specific, and urban-rural levels.
Key findings include significant disparities in labour force participation rates across districts, with rural areas generally exhibiting higher participation rates compared to urban areas, partly due to the inclusion of contributing family workers. Employment-to-population ratios showcase stark gender disparities, with male ratios substantially higher than female ratios across districts. Unemployment rates vary widely across districts and regions, with underdeveloped districts paradoxically exhibiting lower unemployment, warranting further investigation.
Underemployment rates and informal sector employment rates also exhibit significant variations across regions, with gender disparities further exacerbating the differences. The analysis highlights the need for targeted interventions in the labour market to reduce disparities and promote balanced employment opportunities, particularly in the underdeveloped regions.
Further analysis delves into employment composition by sector, revealing nuances in the distribution of agricultural, manufacturing, and services sector employment share rankings across districts. While some districts show top ranks for employment shares of certain sectors, others exhibit bottom ranks indicating low minimal shares, underscoring the need for synchronized employment strategies.
The report also sheds light on youth employment dynamics, with youth unemployment rates and rates of youth not in education, employment, or training revealing significant challenges, particularly in underdeveloped regions. Gender disparities in youth unemployment further underscore the need for targeted interventions to enhance access to education and employment opportunities for young females.
The analysis extends the district-level rankings to provincial-level, highlighting disparities in labour market outcomes across Punjab, Sindh, Khyber Pakhtunkhwa, and Balochistan. Despite data limitations, the rankings offer valuable insights for policymakers and researchers to address and target sub-national labour market disparities and promote inclusive economic development.
Overall, the report emphasizes the multifaceted nature of Pakistan’s labour market dynamics, influenced by district disparities, gender dynamics, and rural-urban divides. Addressing these challenges requires targeted interventions tailored to each region’s unique socio-economic context and informed by robust statistical analyses