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India clears literacy exam with 80.9%, but gender & urban-rural gaps remain
India clears literacy exam with 80.9%, but gender & urban-rural gaps remain

Time of India

time8 hours ago

  • General
  • Time of India

India clears literacy exam with 80.9%, but gender & urban-rural gaps remain

NEW DELHI: Mizoram (98.2%), Lakshadweep (97.3%), Kerala (95.3%), Tripura (93.7%) and Goa (93.6%) are the top five States/ UTs registering the highest overall literacy rates in India for persons aged seven years and above, according to the Periodic Labour Force Survey (PLFS) 2023-24. The report, released by the National Sample Survey Office under the ministry of statistics and programme implementation, shows that India's overall literacy rate for this age group stood at 80.9%. For persons aged five years and above, the national literacy rate was 79.7%. The disaggregated literacy data across all states and Union Territories was based on nationally representative sampling. The PLFS captures detailed literacy data across age groups (5+ and 7+), gender, and rural-urban categories for all states and Union Territories. For persons aged seven and above, male literacy at the national level was 87.2%, while female literacy stood at 74.6%. For the 5+ age group, male literacy was 85.6% and female literacy was 73.7%. States with the lowest literacy rates in the age 7+ category were Bihar (74.3%), Madhya Pradesh (75.2%), and Rajasthan (75.8%). In the 5+ age group, Bihar again ranked lowest at 73.2%, followed by Madhya Pradesh (73.7%) and Rajasthan (74.9%). by Taboola by Taboola Sponsored Links Sponsored Links Promoted Links Promoted Links You May Like 5 Books Warren Buffett Wants You to Read In 2025 Blinkist: Warren Buffett's Reading List Undo Urban India continues to report higher literacy levels than rural areas. The national urban literacy rate was 88.9% for persons aged seven years and above, compared to 77.5% in rural areas. In states like Madhya Pradesh, the rural literacy rate was 71.6%, while the urban literacy rate stood at 85.7%, marking a gap of over 14 percentage points. Bihar reported a rural literacy rate of 72.1% and urban rate of 83.2%. Rajasthan showed a rural literacy rate of 72.5% and an urban literacy rate of 84.7%. These trends reflect similar urban-rural gaps across northern and central states. The gender gap in literacy remains significant. Nationally, the gap for persons aged seven and above was 12.6 percentage points. Rajasthan had the highest gap at 20.1%, with male literacy at 85.9% and female literacy at 65.8%. In Bihar, the gap was 16.2% (males: 82.3%, females: 66.1%), while in Madhya Pradesh, the difference was 16.1% (males: 83.1%, females: 67.0%). In rural areas, gender gaps tend to be wider. Rural Rajasthan had male literacy at 83.6% and female literacy at 61.8%. Rural Bihar reported 81.5% for males and 65% for females. Rural Madhya Pradesh recorded 80% literacy for males and 62.6% for females. In contrast, the gender gap in better-performing states was smaller. In Mizoram, male and female literacy rates were 99.2% and 97%, respectively. In Kerala, the rates were 96.7% for males and 94% for females. The PLFS 2023-24 highlights that while overall literacy has improved, regional, gender, and rural-urban disparities remain substantial. These variations are more pronounced in states with large rural and tribal populations, where educational access and outcomes continue to lag behind national averages.

Himanshu: India's economy is too complex to afford less than robust statistics
Himanshu: India's economy is too complex to afford less than robust statistics

Mint

time5 days ago

  • Business
  • Mint

Himanshu: India's economy is too complex to afford less than robust statistics

Recent months have seen a flurry of data and report releases from the National Statistics Office (NSO). While some of these are routine surveys conducted by it, in some cases the NSO has made significant changes in the nature of data made available and the frequency of releases. India's statistical system had come under criticism for denying or delaying access to survey data. We have seen delays in updating the base year for key variables like the Consumer Price Index (CPI) and National Accounts, both of which have a base which is more than a decade old. Improved survey coverage and data-release frequency would help generate confidence in our statistical system. But it is also essential for statistics to serve as inputs for economic analysis and policy formulation. Regular base-year updates for many macro variables are necessary, given the economy's dynamism. Also Read: Headline labour force survey data masks a pressing employment problem The NSO has expanded the coverage of its annual Periodic Labour Force Surveys (PLFS) and also increased the frequency of data releases from quarterly to monthly, starting with April 2025. Going monthly has meant that the NSO had to increase the PLFS sample size by 2.65 times to 272,304 households, together with changes in sampling design for the generation of monthly estimates. A larger sample also lets the NSO release quarterly estimates for rural areas (done only for urban areas so far). PLFS data has been a valuable tool to track trends and patterns in India's workforce structure since 2017-18. Along with their precursor Employment-Unemployment Surveys (EUS), available since 1972-73, PLFS results provide a comparable data series on employment patterns. However, these also remain the only credible source of information on the quality of job and earnings from them. While there are several sources for the wages and earnings of casual workers, EUS-PLFS data-sets are the only source of information on the earnings of regular workers, who account for almost one-third of all workers in the economy. The monthly report for April 2025 released on 15 May is the first of the monthly series. It presents estimates of the Labour Force Participation Rate (LFPR), Workforce Participation Rate (WPR) and Unemployment Rate (UR) by 'weekly status' for rural and urban areas. Also Read: Himanshu: What consumption data reveals of India's economy For the latter, the findings are broadly similar to what was revealed by the quarterly report for October-December 2024. But its rural estimates are significantly at variance with findings of the annual report for 2024, with a lower LFPR and WPR in April 2025, and significantly higher unemployment rate for the 15-29 age group (and also for the country's 15-plus population). While monthly estimates of basic indicators are useful, these are of limited relevance for an economy whose employment structure is very diverse and complex. Unlike rich countries where most workers have regular payroll jobs in non-farm sectors, the Indian workforce relies mostly on informal employment. Even today, almost half of all Indian workers are engaged in agriculture, compared to less than 5% in most developed countries. Variations in the LFPR, WPR and UR are less relevant in an economy with a large proportion of the population vulnerable in terms of job quality and income assurance. If the purpose of the monthly series is to provide meaningful insights into our labour market, it requires detailed data on sectoral shares, the nature of enterprises and earnings from employment. Fortunately, the data lets us generate most of these estimates. The PLFS's re-introduction of land information allows rural analysts to delve deeper. Also Read: TCA Anant: How India's statistical system could win the ongoing war of narratives The principal challenge now relates to how we understand and characterize the labour market. Given the emergence of new employment categories such as gig work and new forms of labour arrangements interlinked with land and credit markets, we need a better understanding of what holds back the creation of quality jobs in the economy. The revamped PLFS series also expands its questionnaire on education and skills, which have emerged as important drivers of changes in the economy's employment structure. While the NSO has stepped up to provide the basic data necessary for us to analyse and understand the complexity of the country's labour market, deeper research is now needed for this move to spell meaningful policy engagement. Research and policy must look beyond basic estimates of the WPR and unemployment rate. Expanding the monthly release to include wages/earnings, job quality and other relevant co-variates would aid the process of analysing India's employment challenge. The author is associate professor at Jawaharlal Nehru University and visiting fellow at the Centre de Sciences Humaines, New Delhi.

India's formal job market expands: Young workforce leads the charge
India's formal job market expands: Young workforce leads the charge

First Post

time6 days ago

  • Business
  • First Post

India's formal job market expands: Young workforce leads the charge

Both manufacturing and service sectors saw an uptick in hiring. The Employees' Provident Fund Organisation (EPFO), which tracks formal employment through payroll data, reported a net addition of 1.46 million members in March 2025 read more The Employees' Provident Fund Organisation (EPFO), which tracks formal employment through payroll data, reported a net addition of 1.46 million members in March 2025. Significantly, young adults aged between 18 and 25 accounted for nearly 59 per cent of these new members, the sign of a robust influx of first-time job seekers into the organised employment sector. This growth aligns with broader positive labour market trends, as evidenced by the latest figures from the Periodic Labour Force Survey (PLFS). The survey indicated an unemployment rate of 5.1 per cent in April 2025 for individuals aged 15 years and above. Notably, the unemployment rate among younger segments (15-29 years) stood slightly higher at 14.4 per cent for females compared to 13.6 per cent for males, largely attributed to a growing number of young women pursuing higher education and vocational training. STORY CONTINUES BELOW THIS AD Further supporting the expansion of the formal employment market, India's white-collar job segment showed signs of revival. The Naukri JobSpeak index reported a 9 per cent year-on-year growth in hiring activity for April 2025, marking a recovery after a slowdown experienced in March. Prominent sectors fueling this rebound included pharmaceuticals, real estate, global capability centers (GCCs), and oil and gas. More from India Why Manipur's Shirui Lily Festival has turned into a flashpoint over identity Both manufacturing and service sectors saw an uptick in hiring. The Purchasing Managers' Index (PMI) employment sub-indices for these sectors remained in expansionary territory for the fourteenth consecutive month, showing sustained confidence and growth momentum. Collectively, these indicators point to a strengthening and increasingly formalized job market in India, driven by young, skilled professionals eager to enter organized employment and a resilient economic backdrop despite global uncertainties.

Analysing poverty levels in India by comparing various surveys
Analysing poverty levels in India by comparing various surveys

The Hindu

time22-05-2025

  • Business
  • The Hindu

Analysing poverty levels in India by comparing various surveys

Himanshu et al, 'Poverty Decline in India after 2011–12', The Economic and Political Weekly, Vol 60, Issue No: 15, April 12, 2025 A recent paper has estimated that poverty reduction in India slowed down significantly after 2011-12. While poverty levels of 37% in 2004-05 fell to 22% by 2011-12, it has since fallen only by 18% in 2022-23, the paper finds based on its own calculations. The paper, titled 'Poverty Decline in India after 2011–12: Bigger Picture Evidence', authored by Himanshu of Jawaharlal Nehru University, and Peter Lanjouw and Philipp Schirmer of the Vrije University in Amsterdam, noted that India hasn't had an official poverty estimate since 2011-12. In the absence of an official estimate, a number of unofficial and often contradictory estimates have been made, of which this one is the latest. Three methodologies The paper notes that the various contradictory estimates can essentially be clubbed into three broad buckets based on their methodology. The most common approach, it noted, has been to use alternative socio-economic surveys of the National Sample Survey Office (NSSO), since there are significant comparability issues between the Household Consumption Expenditure Survey (HCES) of 2022-23 and 2011-12. There are no intervening surveys, either. The HCES for 2017-18 was scrapped by the government, citing 'methodological issues'. In the NSSO's 71st round, which covered the January-June 2014 period, the government introduced a consumption expenditure measure that was derived from a single question in the survey called the Usual Monthly Per Capita Consumption Expenditure (UMPCE). This UMPCE was used for all subsequent rounds of the NSSO surveys as well as in the Periodic Labour Force Surveys (PLFS). However, as the authors correctly note in their paper, this measure can't be compared to earlier estimates of consumption because it is based on a single question 'with no clear definition of what it comprises'. According to this method, poverty estimates range between 26-30% for 2019-20. The second approach has been used by the economist Surjit Bhalla and his colleagues in 2022 in a paper in which they used Private Final Consumption Expenditure (PFCE) estimates from the government's National Accounts Statistics (NAS) to derive consumption aggregates after 2011-12. This method basically scaled the consumption expenditure data from the HCES 2011–12 based on the implicit growth rate of PFCE after 2011-12. The third broad approach — and the one used by the authors themselves — is to use survey-to-survey imputation methods. This basically means data gaps in one survey can be filled using information from a related base survey. This method, the authors note, has occasionally been used by World Bank researchers to update the World Bank's Poverty and Inequality Platform (PIP) database. Looking at different surveys This approach is significantly prone to somewhat divergent results, based on the different surveys used to complement each other, but are useful in revealing trends in data. For example, the paper notes that one estimate by David Locke Newhouse and Pallavi Vyas used the 2011-12 HCES and the 2014-15 survey on Consumption of Services and Durables to estimate that poverty in India declined from 22% in 2011-12 to 15% in 2014-15. Similarly, Ifeanyi Nzegwu Edochie and their colleagues in 2022, used the 2017-18 survey on Social Consumption on Health to estimate poverty at 10% for 2017–18, which confirmed the trend that poverty had reduced since 2011-12. In 2025, Sutirtha Sinha Roy and Roy van der Weide used a radical approach to apply the survey-to-survey imputation using a private sector survey. They used the Consumer Pyramid Household Survey (CPHS) for 2019 by the Centre for Monitoring Indian Economy (CMIE) along with the 2011-12 Consumer Expenditure Survey (CES). Their estimate was that poverty was around 10% in 2019. Himanshu et al also use this survey-to-survey imputation method. However, the authors note that their strategy differs from previous attempts in three aspects. First, they have used the Tendulkar Committee's poverty lines as opposed to the World Bank's poverty lines. Second, they have used the employment surveys of the NSSO for imputation. The Employment-Unemployment Survey (EUS) is a companion survey to the 2011-12 CES, and is based on similar sampling design and survey implementation procedures. Further, the PLFS, which replaced the EUS in 2017-18, is modelled on the EUS, the authors note. What this essentially means is that the two surveys Himanshu and his colleagues used to impute data are similar in their methodology and parameters, yielding a more accurate fit in the data. Third, the authors note that, unlike the World Bank studies, their own imputation models are estimated at the State level or include State-fixed effects when estimated at the sector level. Their methodology shows that while poverty based on the Tendulkar Committee poverty lines fell sharply between 2004-05 and 2011-12 — from 37% to 22% — it subsequently has fallen only to around 18% by 2022. Based on these estimates, the authors add, the number of poor persons in India fell only slightly since 2011-12, from 250 million persons to about 225 million in 2022–23. Different trends across States State-level trends derived from their methodology suggest differing trends across States over this period. Notably, the authors find that Uttar Pradesh, India's most populous State, seems to have markedly reduced its poverty rate. 'However, in other historically poor States, such as Jharkhand and Bihar, progress was much slower,' they added. 'It is noteworthy that in several of the large central and southern States, such as Maharashtra and Andhra Pradesh, poverty reduction appears to have stagnated.' Importantly, the authors do acknowledge that 'a full resolution of the present debate' on poverty is unlikely to be forthcoming without new government data that can be compared with previous years' data. However, they also try to back up their findings using other data sources that point to the same conclusions. For example, they noted that the growth of India's Gross Domestic Product (GDP), which averaged 6.9% per annum between 2004-05 and 2011-12, slowed to 5.7% between 2011-12 and 2022-23. This, they said, is consistent with a slower decline in poverty reduction after 2011-12. Similarly, they point out that the Wage Rates in Rural India (WRRI) data compiled by the Labour Bureau on real wages points to a slowdown in wage rates. It shows that the annual growth rate of wages fell from 4.13% per year between 2004-05 and 2011-12 to 2.3% per year between 2011-12 and 2022-23. Thirdly, the authors point out that while the absolute number of workers in agriculture declined by 33 million between 2004-05 and 2011-12, and by a further 33 million by 2017-18, this trend has reversed since then with 68 million workers being added to the agriculture sector since 2017–18. One consequence of the rising workforce in agriculture, the authors point out, has been the decline in the growth of agricultural productivity in recent years. Lower productivity leads to lower wages, which leads to higher poverty levels. This paper is hardly going to be the last word on poverty estimates, with many more sure to follow. However, as the authors themselves conclude, there's more than enough evidence to show that poverty reduction efforts need to be accelerated.

Top 10 Indian states/UTs with highest and lowest literacy rates: Mizoram becomes 1st ‘fully literate' state
Top 10 Indian states/UTs with highest and lowest literacy rates: Mizoram becomes 1st ‘fully literate' state

Indian Express

time21-05-2025

  • General
  • Indian Express

Top 10 Indian states/UTs with highest and lowest literacy rates: Mizoram becomes 1st ‘fully literate' state

Literacy Rates of Indian States Full List: India's literacy rate was only 14% at the time of independence, which has increased over the years as more people have received better education. Statista indicates that the country achieved an approximately 76.32 per cent literacy rate in 2022; however, data still falls short of being comprehensive, as there are significant disparities in literacy rates across different states. On Wednesday, May 21, 2025, Mizoram's Chief Minister Lalduhoma declared that the state has achieved 'full literacy' status, surpassing the 95% literacy rate threshold set by the Ministry of Education. Ranked as the third most literate state in India, with a 91.33% literacy rate according to the 2011 Census, Mizoram has recently achieved 98.2%, according to the government statement. Contrastingly, Andhra Pradesh and Bihar recorded the lowest literacy rates in India, standing at 72.6% and 74.3% respectively, for both urban and rural populations, according to the PLFS 2023-24 MoSPI survey. The total literacy rate of India, including all individuals (men and women), aged 7 and above, from rural and urban populations, accounts for 80.9% fn the period 2023-24. To identify potential for intellectual and educational progress, the literacy rate is a crucial indicator of a country's economic progress; according to the Office of the Registrar General of India, a person aged 7 years and above who can read and write with understanding in any language is considered literate. Data source: MoSPI PLFS 2023–24, (Men and Women, 7 years and above, Rural + Urban combined) Data source: MoSPI PLFS 2023–24, (Men and Women, 7 years and above, Rural + Urban combined) Cherry Gupta is an Assistant Manager - Content at The Indian Express. She is responsible for crafting compelling narratives, uncovering the latest news and developments, and driving engaging content based on data and trends to boost website traffic and audience engagement. One can connect with her on LinkedIn or by mail at ... Read More

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