Labor Force Surveys

India’s Jobs Data Just Got a Major Upgrade More than just a survey change. PLFS, India’s Periodic Labour Force Survey tracks who is working, who isn’t, and who’s looking for work. It’s the government’s main tool to understand employment trends across the country. Old job data left rural India in the dark We were planning policy on partial truths. The old PLFS had big flaws: Rural data missing in quarterly reports Out-of-sync annual cycle Too small a sample size Result? We missed seasonal trends, migration shifts, and real-time crises. From April 2025, things changed: Monthly job data for both rural & urban areas Sample size doubled — 1 lakh to 2.72 lakh households Continuity — 75% households repeated monthly, 50% across quarters Richer insights — landholding, income sources, vocational training Why it matters: April 2025 LFPR: 56% overall (Rural 58%, Urban 51%) Female LFPR shocker: Rural 38%, Urban 24% Urban female unemployment: 9% vs 6% for men Youth unemployment: 14% overall; urban young women 24% What monthly data enables: Targeted interventions for women’s employment Reviving failed schemes like Mahila Shakti Kendra Youth-specific job programmes in high-unemployment areas Dynamic rural support like extra MGNREGA days during slumps Think of it as switching from yearly to weekly pantry checks. You spot shortages sooner. You fix them faster. Bottom line: The new PLFS moves India from reactive to proactive in tackling jobs. The only trade-off? We can’t compare it neatly to older datasets. But that’s a small price for sharper, faster, better jobs intelligence. Jobs data isn’t just numbers. It’s livelihoods. And now, it’s real-time. Do you think monthly jobs data will actually lead to better policy? #Jobs #Economy #PLFS #IndiaData #Employment

EY-Parthenon EY Macro Pulse – August Employment via Lydia Boussour Labor conditions not collapsing, but visibly softening 📉 Cracks are increasingly showing in the economy’s main pillar – the labor market – as increasing operating costs and acute policy uncertainty push firms to keep a tight lid on new hiring. The labor market added only 22k jobs last month while the unemployment rate ticked higher to 4.3%, reaching its highest level since October 2021. Notable downward revisions to prior months’ job gains point to a weakening trend with US employment falling in June for the first time since December 2020 and the three-month trailing average of payrolls at a paltry 29k in August. 🏭 Industry details reveal that tariffs and uncertainty are significantly impacting goods-producing sectors and that services industries are not immune. At the government level, federal #job cuts continue to shrink the workforce, with 15k fewer jobs in August and 97k positions lost since January 2025. 📊 The Household Survey painted an equally soft picture, with the unemployment rate rising a tick to 4.3% and breaking out from its narrow range of 4.0% to 4.2% since May 2024. While many firms are choosing to retain their workforce during these uncertain times, performance-based and strategic #layoffs are increasing amidst lingering uncertainty and slowing consumer demand. The labor force participation rate edged higher by 0.1ppt to 62.3% but it remained well below its April 2025 peak of 62.6% as tighter immigration policies are increasingly restraining labor supply. 💵 On the wage front, average hourly earnings rose a moderate 0.3% while wage growth rate moved lower by 0.2ppt to 3.7% y/y. Employers’ continued focus on wage containment amid a slowing economy may lead to a further deceleration in wage growth toward 3.5% by the fall. ⚠️ Recent labor market indicators highlight a fragile balance: labor demand and supply have become subdued, while layoffs are rising. There are now fewer job openings than unemployed individuals and the hiring rate is near its lowest level since 2013. Labor market sentiment has also deteriorated, as shown by the Conference Board’s labor market differential – which tracks the gap between jobs plentiful and jobs hard to get—dropping in August to its lowest level since February 2021. 🔮 Looking ahead, labor market momentum is poised to remain subdued as firms—grappling with softer final demand, higher costs and interest rates, and elevated uncertainty—continue to restrain hiring. Job growth is expected to remain below trend, averaging around 30k per month through year-end and pushing the #unemployment rate toward 4.7% by December. 🏦 With labor market conditions becoming increasingly fragile and #Fed Chair Powell signaling openness to a rate cut in his recent Jackson Hole speech, an “insurance cut” at the September #FOMC meeting appears more than likely.

Singapore’s Labor Force Report is statistically precise – but is it measuring the right things? Every year, the Labor Force Survey arrives with impressive precision. The 2025 Advance Release is no exception: relative standard errors are low, and definitions are strictly ILO-aligned. The MRSD team even added a new section this year on "Global Exposure", tracking the 3.1% of the workforce with overseas experience. But let’s be honest: a report can be reliable in measurement and still miss the deeper strategic picture. While it tells us who is working, it struggles to measure how well we are utilizing our talent. Here is where the data leaves us guessing: 1. The "Under-Employment" Illusion  The report celebrates a drop in under-employment to 1.9%. But be careful: this strictly measures time, not talent. If you have a degree but drive a private-hire car for 40 hours a week, this report considers you "fully employed" because you work more than 35 hours. This metric systematically hides skills under-utilization. 2. Mobility vs. Friction The report tells us job mobility has slowed to 6.2%, attributing it to "worker caution". But without measuring sentiment or barriers, we don't know why. Are people staying because they are happy, or because they are stuck? The number is there, but the narrative is missing. 3. Skills Mismatch We track the rise in PMETs (now 64.2% of residents), but not whether those roles actually utilize the skills workers have trained for. We count credentials, but not competency matches. 4. The Invisible Workforce The survey strictly covers residents. It explicitly excludes migrant workers in dormitories and construction sites. You cannot strategically plan a "Singapore Economy" while statistically ignoring the transient workforce that builds and maintains it. We don’t have a labor force problem. We have a labor fit problem. Singapore needs labor statistics that go beyond compliance and confront structural realities: * Are Singaporeans working below their potential? * Is the drop in mobility due to loyalty or fear? * Are training programs translating into real career pivots? Until we measure "fit" as rigorously as we measure "force", our labor market will remain better documented than it is understood.

Every policymaker in India appears worried about job growth. But jobs are still not a big part of RBI's policymaking process. In fact, we don’t have reliable estimates of how monetary policy impacts job creation. Indian policymakers have long been content with once-in-five-year updates of workforce numbers provided by the quinquennial rounds of the National Sample Survey (NSS). Economists held that most Indians were too poor to be unemployed. In other words, the informal labour market was considered to be a residual sector, always offering ‘work’ to those who lacked regular ‘jobs’. The Indian definition of employment included informal work arrangements. Official unemployment rates remained low and stable, even as ‘disguised unemployment’ levels stayed high. It was only in the late 2000s that the idea of a high-frequency labour-market tracker gained ground. The Indian economy had moved into a faster lane by then and the salaried class had grown substantially. The issue of jobs—as opposed to work—had started gaining political traction. The National Statistical Commission (NSC) appointed a committee headed by Amitabh Kundu to prepare a roadmap for conducting a periodic labour force survey (PLFS). The Kundu committee report, submitted in 2010, recommended quarterly updates for urban India and annual updates for the countryside. After field trials in three states and several rounds of deliberation, the PLFS survey was finally launched in 2017-18. Unfortunately, the survey report got mired in controversy even before it was released. The PLFS has come to be used widely by policymakers since then. The lags with which the data was released have declined over time. The National Statistical Office (NSO) is planning to come up with a monthly PLFS series soon. This series could be a useful input for the central bank’s policy decisions in the months and years to come. However, the new series should be subjected to adequate quality checks and cross-validation before it is used as a policy target. High-frequency updates from other surveys such as the ASI, ASUSE and the upcoming services survey (ASSSE) could be useful complements to the monthly PLFS series in the future. The NSO should also review the reliability of administrative datasets such as EPFO. To provide a clear and comprehensive view of the labour market, the NSO and NSC should jointly evaluate how far different labour-market indicators track each other, and how far they track other high-frequency indicators. Jobs have become an important part of India’s electoral and fiscal policy discourse. They will become a part of the country’s monetary policy calculus only when the official statistical system provides high-quality labour-market data at high frequency. Full article: https://lnkd.in/gTwJVQMy

At Data For India, our Measurement vertical (https://lnkd.in/ga5e7eDD) has gained an engaged following, and with good reason. Indian data is impressive in its history, scope and quality, but writing around the history of datasets, changes in methodology and their implications is sparse. Our latest publication by Pramit Bhattacharya and Nandlal Mishra attempts to map India's Periodic Labour Force Surveys, which must be one of the most widely used and studied national labour datasets in the world. We look at the evolution of the PLFS, changes in methodology, key uses of the data and debates around the survey. We hope it is useful to anyone who works with or wants to work with labour data on India. https://lnkd.in/gz2JznE9

The Bureau of Labor Statistics Monthly Job Report: it’s based on two surveys the establishment & household. The survey in question is the former. It’s based on a 121K survey from non-farm private employers & government agencies comprising 631K worksites. The response rate has recently slipped below 60% down from pre pandemic rate of 70% and well below the 80% rate typical over a decade ago. The survey has a +/- of 100K each month. Typically with a three month window the response rate for a single monthly survey time improves to 90% which is why there are ongoing rolling revisions that are rarely as large as the downward 258K revision in June. The numbers are not rigged and they are the gold standard internationally.

Between 2016 and 2024, Latin America and the Caribbean experienced a steady shift toward a more educated labor force 🌎💼, reflecting returns of investment in human capital. 🔍 Our latest Regional Jobs Update: Insights from Labor Force Surveys in Latin America and the Caribbean by The World Bank analyzes trends among individuals aged 15 and older, examining their educational attainment and employment status. Key findings include: 📈 Tertiary education is on the rise – The share of the population with at least a university degree grew at a 5.1% annually. 🎓 Secondary education gains continue – The group with only high school completion grew at a slower but steady pace of 2.8% annually. 📉 Low education levels are declining – The share of the population without a completed high school education fell by 1.3% annually. 📘 Want to explore more insights? Access the full report below: English:  https://lnkd.in/enjDFfCX   Spanish: https://lnkd.in/efKpZYjN   #EndPoverty #LaborIncome #Inequality #Disparities #LatinAmerica #TheWorldBankGroup #RegionalUpdates 

From April 2025, the PLFS has gone monthly - giving us regular rural and urban labour market data. This means key employment data for April 2025 is already out. Why is this a good move? Because we can now track real-time effects of policies, economic shocks (like supply chain disruptions), and structural transitions (such as the shift towards a green economy). Personally, I’m most interested in how unemployment rates move in relation to labour force and workforce participation rates, and in the month-on-month shifts in women’s employment - which have shown a rising trend in recent years. Of course, the full picture will emerge only with the annual report in August 2026, when we’ll get detailed insights on sectoral employment, the distribution across self-employed, salaried, and casual workers, and earnings. What do you think?