Archives: Publication

A digital economy needs a blend of both: algorithms assess client risk profiles and ensure suitable recommendations, human oversight adds value.

The debate pitting robo-advisors against human advisors is often about competition and not so much about complementarity. Today, advice is free-floating. When it comes to financial advice, people prefer a second opinion as it matters to them and their family’s future the most. Hence, it is imperative to take correct, timely, and appropriate decisions.

The multiple channels of information, including suggestions from age-old trusted advisors or insurance agents coupled with low-cost algorithm-based robo advice, makes investors’ decision difficult when they marry it with their personal needs, risk appetite, future sources, avenues of alternative investments, etc. As Philip Fischer observed, “The stock market is filled with individuals who know the price of everything but value of nothing.”

Which one is better, robo or traditional advice? While robo advice is mechanical, quick, precise, and information-based, human advisors, in addition to publicly available market information, amalgamate personal choice, feelings, and intuitive anticipation about the market, and assessment of other alternate investment avenues Robo-advisors may pass the test of technical audit in terms of quality and correct advice, but may fall short of meeting personal needs, risk appetite, choice, and intuitions that are guided by a set of information in the mind of the investors or human advisors.
In a rising market, recent gains feel like proof and we start believing we cannot lose.

In a falling market, fear feels like intelligence and we exit at the worst time. Many people buy after prices have already run up and sell after the fall has occurred. People also hold on to loss-making investment too long because selling feels painful. These patterns are repetitive. That is exactly why right advice matters. Robo-advisors undertake precise calculations and make predictions based on information in the public domain. For many new investors, the real alternative is not a senior wealth manager, but no advice at all, or advice from social media and friends. Digital platforms reduce this effort as they make it easier to start, diversify, and rebalance while helping investors avoid panic decisions.

In India, the investor base is growing rapidly with the advent of digitalisation along with the rise in retail investment. The United Payments Interface processed about 21.70 billion transactions in January, worth roughly around `28.33 lakh crore, and the total demat accounts were reported at 21.6 crore at the end of December 2025. People are entering the digital market through apps for the first time with inadequate knowledge. Simple and low-cost guidance through robo-advisors becomes handy.

Automation does not necessarily remove bias. It may shift bias into product design and platform incentives. Conflicts of interest can still exist through partnerships and revenue models, even if the user interface looks clean. This is where human advisors will continue to matter. It is not only about choosing between two funds, but also helping people during real-life situations such as job loss, medical emergencies, business shocks, etc. Personal finance is not just mechanical portfolio allocation but decisions that factor in context, judgement, and reassurance, especially when stress makes people abandon long-term plans.

There is another added advantage that good human advisors bring—behaviour coaching. Many investors do not lose money because they chose the wrong product, but because they change plans too often. A good advisor acts like a brake—slowing decisions, explaining the trade-offs, yet keeping the focus on goals. Technology can rebalance a portfolio, not fear.

So who wins? Technology is best for repeat tasks like onboarding, profiling, reporting, and rebalancing. Humans are best for nuance, accountability, and decision shaped by income uncertainty, family responsibilities, taxes, health, and emotions. The future is likely to be a combined model.

Will digital advice grow safely, or will it grow mechanically? If digital advice expands without strict rules, we risk replacing old style mis-selling with a new kind of opacity. However, if regulations insist on clear fee disclosure, transparent incentives, auditable suitability logic, and strong grievance redress, robo-advisors can help close the gap and push the market to grow.

India is already moving rapidly towards a digital finance culture. The question is whether advisory models will match that speed with responsibility. Regulators should move from broad principles to practical standards. Making algorithm-based advice auditable, providing incentives, ensuring transparent partnerships, and fixing accountability when advice fails suitability checks will be helpful. Investment platforms must treat trust as part of their product design, not just marketing.

The real question is not whether robo-advisors will outcompete traditional ones, but whether investors will get personalised advice that is easy to access and fully aligned with their intuition, risk appetite, and personal goals as well as being accountable and answerable. While algorithms must assess client risk profiles and ensure suitable recommendations, qualified human oversight adds value. In today’s rapidly digitising economy, a blend of robo advice guided by humans is the need of the hour.

The authors are CS Mohapatra & Depannita Ghosh, Respectively IEPF Chair Professor and Research Analyst at the National Council of Applied Economic Research. Views are personal.

Indians are watching more frequently but in shorter, more distracted bursts.

In the late 1980s, when Ramayan aired every Sunday morning on Doordarshan, India paused as one. Streets emptied, tea kettles boiled in unison, and neighbours gathered around a single television set in the mohalla or village chaupal. That screen did not isolate; it assembled. That era was characterised by one channel, one episode, and one shared ending.

Four decades later, abundance has inverted that logic. India today is not merely a digitalised society, it is becoming a screened society. Television and mobile sets are no longer merely a source of entertainment. They have become a conduit for public information, a supplement to schooling, a forum for political messaging, and, increasingly, a substitute for absent public spaces.

The paradox of fragmented attention

Time Use Survey (TUS) data (2019 and 2024) reveals a striking contradiction in how the nation consumes media. While participation in watching television and digital videos has surged from 54.5 per cent to 62.1 per cent, the actual average time spent viewing has dipped from 120.2 to 117 minutes daily. This shift signals the rise of a snackable India. We are watching more frequently but in shorter, more distracted bursts. This transition from deep, dedicated viewing to fragmented snatches, often occurring alongside work or chores, is the direct result of cheap data and the ubiquity of the smartphone.

Rural-urban convergence has limits

Between 2019 and 2024, average participation increased significantly from 48.6 per cent to 56.3 per cent in rural areas, reflecting gains from electrification, broadcast reach, device penetration, and cheaper mobile data. But viewing time has declined among rural residents. On the other hand, urban residents continue to enjoy a systematic advantage, where participation increased to 75 per cent from 68.3 per cent, with a marginal decline in viewing time.

Among children below 15 years in rural India, viewing time declined from about 115 minutes per day in 2019 to 106 minutes in 2024, while urban children consistently averaged close to 125 minutes.

Similar differentials are visible among working-age adults. In the 31–40 age group, rural residents averaged roughly 99 minutes per day in 2024, compared to 108 minutes in urban areas. Even among senior citizens (60+), urban residents recorded significantly higher viewing time — around 175 minutes daily, compared to 147 minutes in rural India. These disparities point to differences not merely in access, but in time availability, infrastructure reliability, and living conditions.

The myth of gender parity

Aggregate figures suggest a narrowing of the male-female divide. In both 2019 and 2024, women’s average viewing time (at 121.7 minutes in 2024 and 127.6 minutes in 2019) substantially exceeded that of men (at 112.8 minutes and 113 minutes, respectively). While participation rate was almost similar in 2019 for both the genders, there is a substantial rise in participation rate among males in 2024, with a modest rise among females.

Age as the most overlooked dimension

The most pronounced variations in viewing time emerge across age groups. The data exhibits a clear life-cycle pattern — high viewing time among children, declining through prime working ages, and rising sharply among older adults. It’s a distinct U-shaped pattern.

In 2024, individuals aged 31–40 years recorded some of the lowest viewing time, around 103 minutes daily, while those aged 60 and above averaged over 158 minutes. For children, high viewing time often compensates for the absence of recreational and playing infrastructure.

As social circles shrink and physical mobility decreases, viewing time rises sharply for those aged 60 and above, who average over 158 minutes daily. For the elderly, the screen has become a vital substitute for social interaction, yet the content available rarely reflects this specialised need.

Policy implications and institutional gaps

India’s policy framework has yet to fully recognise media consumption as a capability, rather than a mere by-product of connectivity. Initiatives under Digital India, educational broadcasting efforts, recreational consumption, and welfare communication strategies often assume a homogeneous audience with uniform access to time and attention.

This assumption sits uneasily with constitutional commitments under Articles 14 and 21A, especially when audio-visual media increasingly mediates education, public information, and civic participation. The absence of time-use sensitivity in policy design risks reinforcing existing inequalities, even as access expands.

It is important to acknowledge progress. The expansion of regional-language content, improvements in rural electrification, and declining device and data costs have meaningfully broadened access. Rural-urban gaps in viewing time, though persistent, are narrower than in the past. Yet inclusion measured by ownership and averages cannot substitute for inclusion measured by effective use and autonomy.

However, as the Economic Survey 2025-26 calls for a comprehensive national strategy to combat digital addiction and establishing multi-dimensional metrics to track usage and mental health outcomes, having a balanced approach is the need of the hour. The way forward emphasises a shift toward digital wellness across all age groups, advocating for the introduction of a specialised curriculum in schools, the establishment of offline youth hubs, and the promotion of “digital diets” and detox centres for adults. We also feel that integrating a policy focus on senior citizens (60 and above) is a vital addition to this discourse.

Toward a more equitable media ecosystem

A more calibrated policy response would require three shifts:

• Incorporating time-use data into policy design, particularly in education and public communication.
• Strengthening collective and public viewing spaces, such as libraries and community centres, especially in rural areas.
• Designing content that accounts for interrupted and constrained viewing, particularly for adult women.

India’s screens have become a public institution, but its benefits remain unevenly distributed. The challenge ahead is not merely to expand access, but to ensure that time, attention, and agency are more equitably shared.

Viewing time, measured in minutes, may appear mundane. But in reality, it is a precise indicator of how inequality quietly reproduces itself, after work hours, between chores, and across generations.

Palash Baruah @DrPalashBaruah is a fellow at the National Council of Applied Economic Research (NCAER), Delhi and DL Wankhar is a retired officer of the Government of India. Views are personal.

A background note can be accessed here: OECD: Skills Use in Workplace

Productivity gains depend as much on expanding skills as on aligning firm-level demand and institutional incentives to ensure effective utilisation.

In India’s labour market, where formal credentialing coexists with large informal employment, what institutional or employer-side practices perpetuate skill misuse, and how should policy address the gap between skill supply and productive utilisation?

At the micro level, a skill match exists when a worker’s competencies align with job requirements; mismatches arise when workers are under-skilled, over-skilled, or unable to fully deploy their capabilities. In India, these forms coexist with skills shortages (i.e. an insufficient number of workers) and skills gaps (i.e. workers do not have requisite competencies), reflecting imperfect adjustment between labour supply and employer demand.

Institutional practices contribute to this misalignment. Public sector recruitment often attracts overqualified applicants for limited posts, leading to underutilisation. In MSME-dominated sectors, firms frequently require multi-skilled workers capable of performing tasks beyond narrowly defined roles, yet formal job descriptions and wage structures do not always reflect this demand.

The coexistence of formal credentials with informal employment, such as platform work, further complicates matching. Conversely, informally acquired but uncertified skills may be deployed within formal enterprises without formal recognition .

Recognition of Prior Learning (RPL) seeks to bridge this divide. Policy must therefore strengthen demand-side clarity by identifying firm-level job roles, associated competencies, and wage structures, while encouraging MSMEs to incentivise reskilling. Conducting an Occupational-Wage-Employment Survey (OWES) would anchor these efforts in systematic labour market evidence.

What policy levers are most critical for ensuring that skill development translates into meaningful workplace application in India’s services and manufacturing sectors?

The distinction between acquiring skills and applying them productively at work is central to labour market efficiency. Ensuring their translation into workplace outcomes requires structured engagement between training institutions and firms, particularly in services and manufacturing. Industrial Training Institutes (ITIS) can collaborate with industry to simulate real production environments through shared classrooms and laboratories, while industry professionals serve as guest faculty and teachers undertake industry deputations. Apprenticeships, internships, and placement cells further institutionalise pathways from training to employment.

The government’s ongoing ITI upgradation efforts must be aligned with sectoral needs identified at the firm level. Beyond technical training, counselling and mentoring – from school through college – are essential to guide students toward realistic career trajectories aligned with their abilities and prevailing labour market demand.

Within firms, workplace mentoring, structured on-the-job training, and incentives for employee certification strengthen skill application. Local partnerships between enterprises and training providers can facilitate reskilling and upskilling ecosystems, ensuring that skill supply continuously adjusts to evolving production requirements rather than remaining detached from them.

Effective policy relies on real-time insight into skills utilisation and mismatches. What data ecosystems and governance mechanisms should India prioritise to measure skill use at scale, and how can these be embedded in adaptive policy processes rather than static reporting?

Effective policy on skill utilisation depends on granular, real-time labour market intelligence rather than episodic reporting. The Ministry of Skill Development and Entrepreneurship (MSDE) and the National Council of Applied Economic Research (NCAER) skills gap framework launched in 2025 outlines a seven-step approach: macro analysis of sectoral employment shares and clusters; medium-term growth simulations using input-output models; an Occupational-Wage-Employment Survey of non-agricultural enterprises; vacancy and skills surveys; big data analytics in non-agriculture; district-level analysis of agriculture and allied sectors; and structured stakeholder consultations.

To execute this, a core methodological shift is required: instead of asking firms only about generic “skills,” policymakers must map actual tasks performed within each job role, ideally aligned to detailed National Classification of Occupations (NCO) codes. Working backwards from task profiles to required competencies enables more precise matching. Such data should feed into a dynamic Labour Market Information System capable of informing training curricula, wage benchmarks, and regional planning. International systems such as O*NET provide a reference point. India’s National Career Service dashboard offers a foundation but requires further modernisation to support adaptive policy design.

Dr. Bornali Bhandari: is Professor at NCAER. View are personal.

Little emphasis on project preparation, resorting to asset monetisation sans guardrails, narrow financing base are pain points.

The Union Budget has reaffirmed India’s reliance on public capital expenditure as the central pillar of its growth strategy. Public investment has expanded rapidly over the past five years. Central government capital expenditure has risen sharply in both absolute terms and as a share of GDP, marking a clear break from the fiscally constrained post-2012period. This sustained push has helped crowd in private investment.

However, execution capacity has not scaled up at the same pace. Project monitoring data continue to show a sizeable pipeline of stalled or delayed infrastructure projects, with time overruns and cost escalations remaining widespread. Land acquisition challenges, regulatory clearances, weak project preparation and financing stress are repeatedly cited as binding constraints, particularly in highways and urban infra-structure. The divergence between rising allocations and uneven out-comes suggests that India’s infrastructure challenge is now less about spending levels and more about delivery systems.

Three structural gaps in infrastructure finance merit closer attention. First, India does not lack project announcements; it lacks bankable projects. Too often, projects are launched before land is secured, demand risks are rigorously assessed, or revenue and risk-sharing frame works are clearly defined. The result is predictable: delays, cost overruns and growing risk aversion among long-term investors.

A professionally managed and adequately funded project preparation framework — covering feasibility studies, environmental and social safeguards, and financial structuring — can materially improve execution quality. International experience shows that relatively small up-front investments in preparation significantly reduce downstream fiscal and contractual stress. Without this foundation, higher capital out-lays risk translating into stranded assets.

Non-debt instrument

Second, asset monetisation has emerged as an important non-debt financing instrument, particularly in the transport sector. Recycling capital from mature, revenue-generating assets into new infrastructure can ease fiscal pressures while sustaining investment momentum.

But credibility is key. Transparent valuation, competitive bidding, service-quality safeguards and clear ring-fencing of proceeds for fresh capital formation are essential to ensure monetisation strengthens, rather than undermines, public balance sheets. Absent these guardrails, monetisation risks being perceived as a short-term fiscal expedient rather than a durable financing strategy.

Third, despite the scale of infrastructure spending, India’s financing base remains relatively narrow. Banks and budgetary resources still dominate, while long-term domestic investors — pension funds, insurance companies and provident funds — play a limited role.

Expanding the use of long-dated, inflation-linked infrastructure bonds, strengthening pooled municipal finance mechanisms and providing regulatory clarity for institutional investment in infrastructure funds would better align financing tenors with asset lifecycles.

Recent RBI data indicate that States have increased capital expenditure as a share of GDP in recent years, reflecting a welcome shift towards growth-enhancing spending. However, aggregate improvement conceals wide inter-State variation in fiscal space, project readiness and execution capacity. Many States continue to face weak project pipelines, limited own-source revenues and rising committed expenditures. In this context, Central support — through long-tenor, concessional loans for State capital expenditure — would yield stronger results if increasingly linked to measurable improvements in project preparation, financial re-porting and user-charge frameworks.

One of the most under-emphasised aspects of India’s infrastructure strategy is operations and maintenance. Inadequate lifecycle funding leads to rapid asset deterioration, eroding economic returns and raising costs.

Climate risks compound this challenge. Floods, heat stress and extreme weather events are shortening asset lives and increasing maintenance burdens. Integrating maintenance planning, climate-resilient design standards and risk-sharing mechanisms into infrastructure finance frameworks would significantly improve value for money and protect public investment.

The challenge now is institutional: ensuring that projects are prepared better, financed smarter and maintained properly across both the Centre and the States.

The writer is Senior Fellow at NCAER, New Delhi. Views expressed are personal. 

The result is a persistent gap in labour force participation. Despite recent improvements, women’s participation remains well below its potential, especially in urban areas and in higher-productivity sectors.

India has begun to acknowledge an inconvenient truth about its economy: growth cannot be sustained without bringing more women into paid work. The Union Budget 2026 reflects this realisation in part through investments in the care sector and allied health services. But it still stops short of confronting the central macroeconomic blind spot—unpaid care work that holds back female labour force participation (FLFPR).

Women’s work sustains households, enables labour markets to function, and underpins economic activity, yet it remains largely invisible in national accounting. Until this invisibility is corrected, India’s efforts to raise FLFPR will remain partial and fragile.

The care burden GDP ignores

Time-use data makes the imbalance stark. According to the Economic Survey 2025–26, over 40 per cent of women of working age are engaged in caregiving activities, compared to just over 21 per cent of men. Women spend nearly 140 minutes a day on caregiving and over six hours daily on unpaid work overall, almost three times as much as men. This unpaid labour does not show up in GDP, but its economic value is substantial. In effect, the economy is being subsidised by women’s unpaid time, and this subsidy comes at the cost of their participation in paid work.

The result is a persistent gap in labour force participation. Despite recent improvements, women’s participation remains well below its potential, especially in urban areas and in higher-productivity sectors.

To its credit, the Union budget does take steps towards recognising care as an economic concern. Paragraph 54 announces the creation of a strong care ecosystem, with 1.5 lakh caregivers to be trained in the coming year. Paragraph 53 commits to expanding training capacity for allied health professionals, with a target of adding 100,000 professionals over five years.

These measures matter. Care services and allied health are female-intensive sectors. Formal training and certification can convert informal, poorly paid work into stable employment while easing care pressures within households. But these initiatives operate at the margins of a much larger problem. What the Budget does not do is to recognise care itself as productive economic activity or treat its unequal distribution among women and men as a macroeconomic constraint. Care remains framed as a sectoral intervention, not as a structural foundation of labour markets.

What the evidence tells us

Recent macroeconomic research strengthens the case for a more fundamental shift. A paper for NCAER, co-authored by the writer and Prof Ratna Sahay and published in the Economic and Political Weekly, models the impact of redistributing unpaid care work and formalising part-time employment. The findings are striking: equalising the care burden between men and women, combined with legally protected part-time work, could raise India’s female labour force participation rate by around six percentage points.

This is not a marginal gain. A six-point increase would bring millions of women into the workforce, boosting output, household incomes, and fiscal revenues. The mechanisms are straightforward. When care responsibilities are shared more evenly and flexible, formal work options exist, and women are far more likely to enter and remain in paid employment. India’s labour laws and macro policy framework still assume a worker unencumbered by care, an assumption that fits male employment patterns far more than female ones.

Including unpaid care work in national accounts would not merely improve measurement; it would change incentives. If care were recognised as economic output, investments in childcare, eldercare, and disability care would appear not as social spending but as productivity-enhancing infrastructure.

This shift would also strengthen the case for public provision. International evidence shows that investment in care services generates high employment multipliers, particularly for women. It also frees up time for paid work, creating a virtuous cycle of participation, income growth, and tax revenues. At present, India relies heavily on households, and within them, women, to absorb the costs of care. This model depresses labour supply, reinforces gender inequality, and limits growth. Treating care as a public good rather than a private obligation would align social policy with macroeconomic objectives.

Raising female labour force participation is often framed as a social goal. But it is a growth imperative. As India’s demographic dividend matures and labour shortages emerge in key sectors, excluding women from the workforce is no longer economically tenable. The Budget’s care-related initiatives are a start, but they need to be embedded within a broader strategy that includes publicly funded childcare and eldercare services at scale; legal recognition of formal, protected part-time work; incentives for employers to support care-compatible work arrangements; and systematic measurement of unpaid care in national accounts. 

Without these, gains in FLFPR will remain contingent on individual households’ ability to cope rather than on durable institutional support.

India’s growth story increasingly depends on women’s work, paid and unpaid alike. But as long as unpaid care remains invisible in GDP and marginal in policy design, women’s participation will stay constrained. Recognising care as economic infrastructure is not about symbolism; it is about unlocking labour supply, productivity, and long-term growth. 

The writer is Associate Fellow, NCAER. Views are personal.