In today’s data-driven world, understanding employment trends is vital for policymakers, economists, and businesses. Job surveys form the backbone of labour market insights, offering crucial statistics on employment levels, unemployment rates, sectoral participation, and workforce demographics. Over time, the way job data is collected and interpreted has undergone significant changes.
The collection of job statistics increased in response to the growing complexity of labour markets during industrialisation. As societies shifted from agrarian to industrial economies, it was important to understand employment patterns, wage levels, and working conditions. The government recognized that without reliable data, it was impossible to assess the health of the labour market or design effective economic policies.
The first book-keeping of records
This blog traces the evolution of job surveys, with a specific focus on India, while also comparing practices from countries such as the United States, the United Kingdom, and Australia.
Globally, employment surveys began in the early to mid-20th century. The United States started the movement with the launch of the Current Population Survey (CPS) in 1940, which remains a key source of monthly employment and unemployment data. In Japan, labour force surveys began in 1946, and by 1960, Australia was also conducting similar surveys. These early surveys at large relied on household interviews using paper forms and manual methods.
While these approaches provided detailed information on employment status, industry, and occupation, they were also time-consuming and often lagging. Over time, these surveys have evolved into technologically driven processes, consisting of computer-assisted personal interviews (CAPI), telephonic interviews, and online survey platforms. India’s history of job data collection began with the National Sample Survey Organization (NSSO), which conducted its first large-scale employment survey in 1972-73.
Reliability of data collection
These Employment and Unemployment Surveys were conducted once in five years and were considered the standard for employment statistics in India. The surveys collected data based on three different reference periods: usual status (over a year), current weekly status, and current daily status, offering a wholesome view of labour force participation. However, the long gaps between surveys explained that data had become outdated, especially during times of rapid economic transformation or crises such as the COVID-19 pandemic.
One of the major drawbacks of job surveys across countries has been declining response rates. For instance, the UK’s Labour Force Survey reported a significant drop in participation, with Household response rates having fallen from 50% in 2014 to just around 20% in recent years. This decline had compromised data reliability and forced national statistical agencies to explore alternative collection methods.
In India, similar challenges were observed, especially in the informal labour sector, which constitutes nearly 90% of the workforce. While the NSSO surveys provided strong data for formal employment, they often fell behind in reflecting informal and gig economy workers. To address the limitations of non-recurring data collection, India launched the Periodic Labour Force Survey (PLFS) in 2017-18. This marked a major shift from the once in five- year format to an annual survey that included quarterly updates for urban areas.
Periodic Labour Force Survey (PLFS)
The PLFS aimed to deliver more timely and frequent estimates of labour force indicators such as the Worker-population ratio, labour force participation rate, and unemployment rate. A milestone was reached in April 2025 when India released its first-ever monthly job data through the PLFS framework, reporting an unemployment rate of 5.1%. This shift to monthly reporting is a significant development, allowing policymakers and stakeholders to track the labour market fluctuations more closely and respond more effectively. Recognizing the need for a more comprehensive labour overview, India’s Ministry of Statistics and Programme Implementation (MOSPI) recently announced an extension of quarterly PLFS estimates to rural areas beginning in 2025.
This change is expected to enhance the labour market data and provide a better understanding of employment patterns across India’s vast rural economy. The move reflects a growing awareness of the heterogeneity in India’s labour market and the importance of policy interventions accordingly. On an international level, many countries have also changed the outlook of their data collection methods/ practices.
The UK’s Office for National Statistics (ONS) invested £24 million to overhaul its jobs survey infrastructure, introducing digital tools and redesigning questionnaires to improve response rates and data accuracy. Additionally, nations like the United States and Canada have begun integrating data such as tax filings and social security records to complement survey-based estimates. This hybrid approach enables the extraction of real-time labour data while reducing the burden on respondents.
Blind spots left unperturbed
However, this method can miss informal workers or those outside the tax net, which is a major concern in developing countries like India. Emerging technology has further influenced job survey practices in today’s time. Government and private institutions are increasingly exploring big data analytics, using information from online portals, phone usage, and digital payment systems to track employment trends. These data sources offer more frequent insights and can be particularly useful during economic uncertainties. Yet, challenges related to data privacy, representation, and ethical usage remain unresolved and continue to spark debates in both developed and developing nations. Public opinions and perceptions towards labour data are another crucial element. Accurate and timely job statistics not only inform policy decisions but also shape public sentiment and market expectations.
In many countries, discrepancies or revisions in official labour data have led to confusion and dicey thoughts among economists and the general public. For instance, in both the US and UK, data revisions have sometimes created conflicting pictures of the job market, raising questions about survey methodologies and transparency. In India, debates around the accuracy and representativeness of PLFS data have grown, especially when unemployment figures become politically sensitive. Transparent meth odologies, clear communication, and prompt dissemination of data are essential to maintain trust and utility.
Conclusion
The evolution of job surveys represents the broader transformation in how societies measure and understand economic activity. From paper-based interviews to digitally integrated systems, the shift has been both necessary and inevitable. India’s transition from the NSSO’s surveys to the more dynamic PLFS model marks a major step in improving employment data collection.
The introduction of monthly labour statistics and the extension of coverage to rural areas reflect a committee that is more precise and responsive. At the same time, global innovations such as the use of administrative data and big data analytics are reshaping how labour markets are studied and understood. As we move further into the digital age, robust, transparent, and inclusive data systems will be key to crafting policies that ensure economic resilience and equitable growth.
Written by – Suhana Bharti
Edited by – Bhoomi Purohit
