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Each sequential release of GDP estimates by MoSPI (Ministry of Statistics and Programme Implementation) generates considerable excitement. Yet, perhaps many of us are unaware that each year’s estimates are revised six times over a stretch of three years before they are finalized.

For example, the first estimate of growth for the current year 2023-24, the First Advance Estimate (FAE), would be released in the first week of January 2024. A Second Advance Estimate (SAE) would be released after about a month and a half in end-February 2024. A Provisional Estimate (PE) would be released three months later in end-May 2024.

These three “early estimates” would then be followed by annual revisions spanning nearly a three-year period. The First Revised Estimate (FRE) would be released in end-February 2025; the Second Revised Estimate (SRE) and Third Revised Estimate (TRE) would be released exactly one and two years thereafter, that is, in February 2026 and February 2027, respectively.

Thus, as per the current practice, the final estimates for GDP and GDP growth are available only three years after the end of the respective fiscal year.

This practice raises certain inevitable questions. Does it really need to be such a long-drawn process? Does the release of six different estimates over a three-year period ensure better accuracy? Is there a case to consolidate some of these iterations and move to only three estimates: an early estimate; a provisional estimate; and a revised estimate, spread roughly over a period of a year-and-a-half?

In order to answer these questions, we analysed the data for four recent years for which all the six estimates are available (Table 1).

Three features of the various estimates stand out from this analysis, which then lead to three corresponding recommendations.

First, given the limited time in the interregnum between the FAE and the SAE, the two estimates are very similar. In fact, in two of the four years, the two estimates were identical. The SAE was upgraded by 0.1 percentage points in one year, and downgraded by 0.2 percentage points in another year.

This pattern lends itself to the obvious recommendation that the FAE and SAE should be merged into one estimate. One may simply release these numbers as the Advance Estimate in February, around the time when, as per the current process, the SAE is released.

Second, once all the data available up to two years after the end of the fiscal year has been utilized to prepare the SRE, very little new information is available in the subsequent year. Therefore, unsurprisingly, the SRE and the TRE have also been quite similar to each other.

As can be gleaned from Table 1, the SRE and TRE were identical in one of the four years; the TRE was upgraded by 0.1 percentage point in one year and by 0.2 percentage points in another year; and was downgraded by 0.2 percent in one year. These revisions have not only been rather minor, but in the medium term, they mostly even out, as a result of which the size of the economy is not impacted in any specific direction.

Therefore, doing away with TREs would be largely inconsequential for the accuracy of the estimates, but it would instead make the process shorter, nimbler, and more streamlined.

A final recommendation would be to combine the FRE and SRE into one estimate. The GDP estimates are revised significantly between these two estimates. The SRE, underpinned by more detailed information, is more accurate than the FRE. It would thus be prudent to release the combined estimate at an appropriate time between the two currently designated periods. If the data collection and its compilation can be accelerated with some effort, one could perhaps achieve a reliable revised estimate about 14-15 months after the fiscal year has ended.

A transition step may be go to four estimates first by eliminating the FAE and TRE; and subsequently go to three estimates by merging the FRE and SRE within two years.

Figure 1 graphically depicts the existing and recommended processes of arriving at the GDP estimates.

The final slate would then look as follows: an Advance Estimate, a Provisional Estimate, and a Revised Estimate, all three estimates would be available within a span of 16 months. Simple, precise, and agile.

The writer is director general of NCAER, and a member of the Economic Advisory Council to the Prime Minister of India. Shubhashree Jha contributed to this piece.

The number recently put forth by a government-constituted task force represents, at best, an interim assessment till the final report is out.

The National Council of Applied Economic Research (NCAER) released a report on “Logistics Cost in India Assessment and Long-term Framework” on December 14, 2023. The report is an outcome of a consultative approach adopted by a task force constituted by department for promotion of industry and internal trade (DPIIT) in April 2023. The members of the task force included representatives from the Asian Development Bank, NITI Aayog, ministry of statistics and programme implementation (MoSPI), academia (Asia Pacific School of Logistics & Graduate School of Logistics, Inha University of Korea), logistics industry stakeholders (Indian National Shipowners Association, National Industrial Corridor Development Corporation, Aviapro Logistic Services, All-India Transporters’ Welfare Association, Warehousing Association of India), logistics division of the DPIIT, and NCAER.

The task force was set up with the purpose of arriving at an estimate of the logistics cost incurred by India, which can be relied upon and which is based on the available facts and takes into account industry’s experiences. The NCAER’s 2023 report attempts to achieve this goal. The hitherto available estimates included NCAER’s 8.9% of GDP for 2017-18; CII’s 10.9% of GDP in 2015; and Armstrong and Associates’ 13.0% of GDP in 2016. The A&A estimate is also the most widely circulated number, and became the basis of the National Logistics Policy’s agenda to reduce the logistics cost to global benchmarks by 2030.

But, the NCAER’s new study found that the logistics cost as a percentage of GDP has been a single-digit number since at least 2011-12. That is good news, but does this mean that India already meets the global benchmarks?

While the logistics costs, most commonly expressed as a percentage to GDP, have been estimated for some countries, there is uniformity neither in the methodology of estimation nor on definition of logistics. This means that the constituents of logistics cost can vary across different studies. Most commonly included constituents are transportation, warehousing including cost of carrying inventories, insurance, and administrative cost (the sub-constituents of which can also vary).

This study estimates the cost of most significant constituents of logistics, that is, transportation and warehousing including cost of carrying inventories, using the data published by the government—Supply and Use Tables (SUT) and National Accounts Statistics (NAS). It imputes the cost of the remaining constituents by referring to the NCAER 2017-18 study and assuming that the contribution of the remaining constituents to total cost continues to be the same as it did in 2017-18. Therefore, the study does consider all the constituents of the logistics cost, commonly covered in other countries, through direct or indirect sources.

A quick exercise comparing the transportation and warehousing costs of India with that of the US, using the two countries’ similar sources—that is SUTs—finds that while these constituents were about 6% of GDP for India, the same were just about 3% of GDP for the US, in 2015. With remaining and less prominent constituents added, total cost is less likely to exceed 8-9% for India and 5-6% for US. In contrast, A&A estimated India’s logistics cost to be 13% of GDP and the US’s cost at 8.2% in 2016. These estimates, therefore, appear to be on a higher side across the countries.

Also, the metric of expressing the logistics cost, as a percentage to GDP, is not really an ideal metric. A services-driven economy is expected to have lower logistics cost. Also, an economy dependent predominantly on road transport is expected to have, ceteris paribus, higher logistics cost. Ideally, if the countries strive to reduce their logistics cost, effort should be made towards gradually reducing the absolute cost as a percentage of sales of goods, that is, agriculture and manufactured goods. This can most commonly be achieved, among other ways, through infrastructural development, removal of congestion points, modal shift towards rail and waterway, and reduction in administrative costs. Among these, modal shift towards rail and waterway is very critical not only for reducing logistics cost but also for reducing the carbon footprint.

This task force unanimously concluded that the most appropriate way to estimate logistics costs would be through a comprehensive study, comprising a primary survey and the compilation of relevant secondary data, along with the use of real-time Big Data (e.g., e-way bill data on freight transport costs, FASTag data on the movement of consignments along their routes) to identify bottlenecks (in terms of time and cost). The findings of this comprehensive study should provide (i) a plausible estimate of total logistics costs in India, and (ii) disaggregated information on logistic costs associated with various product groups and supply chains, and across different locations within India. Such disaggregated information would enable policymakers to identify priority areas for reducing logistics costs.

Pending the completion of such a comprehensive study, the 2023 report presented an interim assessment using readily available government data to arrive at a reliable aggregate estimate of India’s logistics costs. This estimate should best be used as a baseline estimate so that the progress of interventions made under the National Logistics Policy can be appropriately tracked.

Munjal and Pohit are the Professors at NCAER, New Delhi. Views are personal.

Opinion: Nandan Nilekani and Tanuj Bhojwani.

India is on the brink of a transformation that could change its economic and social future.

Before the end of this decade, more Indians will use AI every day than in any other country in the world. What’s more, people in advanced economies will be surprised by the ways the country will use AI. India is on the cusp of a technological revolution that could alter the trajectory of its social and economic future, and in this revolution there are lessons for the rest of the world.

Our prediction hinges on three facts: India needs it, India is ready for it, and India will do it.

India needs it
The concept of “China plus one” has been gaining traction, with its admonition that global companies should not depend inordinately on China for their manufacturing and software needs. India, with its growing infrastructure investments, favorable policies, and young working population, is the most likely beneficiary of this shift. It is perhaps the only country poised to match the scale of China.

With 1.4 billion people, India is closer to a continent than a country. Its population is almost twice that of Europe. But the average age in India is 28, compared with Europe’s 44, which means a higher share of the population is of working age. This is the starting point: India is a very large country of very young people.

This demographic dividend, favorable global trends, and the unlocking of decades of suppressed potential are starting to show returns. Even as the macroeconomic projections for most of the world seem modest or bleak, India remains a bright spot. These young Indians are aspirational and motivated to use every opportunity to better their lives.

What really sets India apart from the West are its unique challenges and needs. India’s diverse population and complex socioeconomic concerns mean that AI there is not just about developing cutting-edge technology. It’s about finding innovative solutions to address pressing problems in health care, education, agriculture, and sustainability.

Though our population is just double the size of Europe’s, we are much more diverse. Indians, like Europeans, are often bi- or multilingual. India recognizes 19,500 dialects spoken by at least 10,000 people. Based on data from the Indian census, two Indians selected at random have only a 36 percent chance of speaking a common language.

This language barrier is complicated by the fact that the official literacy rate in the country hovers near 77 percent, varying vastly between states. This means that roughly 1 in 4 people can’t read or write. Even though the government tries to provide welfare assistance for its most vulnerable, it’s hard to spread awareness about the service and reach the last mile. Filling out a simple form to access welfare can be daunting for someone who is illiterate. Determining eligibility for assistance means depending on someone who can read, write, and navigate the bureaucracy. Actually receiving services means assistance seekers must have an agent helping them who is not misinformed—or worse, corrupt. These barriers disproportionately affect those who need government assistance the most.

We have the ability to solve a lot of problems for our population, but the hard part has always been in the distribution, not the solution. In India, we believe that AI can help bridge this access gap. AI enables people to access services directly with their voice using natural language, empowering them to help themselves. As Canadian writer William Gibson aptly said, “The future is already here—it’s just not evenly distributed.” Nowhere is this more glaringly evident than in India.

The rest of the world has been eyeing AI with curiosity, waiting for real-use cases. In India, we see potential today. While this may be true of many other developing economies, the other important factor is that.

India is ready for it
India’s population isn’t just young, it is connected. According to the country’s telecommunications sector regulator, India has more than 790 million mobile broadband users. Internet penetration continues to increase, and with the availability of affordable data plans, more and more people are online. This has created a massive user base for AI applications and services.

But where India has surpassed all others is in its digital public infrastructure. Today, nearly every Indian has a digital identity under the Aadhaar system. The Aadhaar is a 12-digit unique identity number with an option for users to authenticate themselves digitally—that is, to prove they are who they claim to be.

Further, India set up a low-cost, real-time, interoperable payment system. This means that any user of any bank can pay any other person or merchant using any other bank instantly and at no cost. This system—the Unified Payments Interface—handles more than 10 billion transactions a month. It is the largest real-time payment system in the world and handles about 60 percent of real-time payment transactions worldwide.

With the success of these models, India is embracing innovation in open networks as digital public infrastructure. Take the example of Namma Yatri, a ride-hailing network built in collaboration with the union of auto-rickshaw drivers in Bangalore and launched in November 2022. These drivers have their own app, with a flat fee to use it, no percentage commission and no middleman. The app has facilitated close to 90,000 rides a day, almost as many as ride-hailing companies in the city.

Unlike Western countries, which have legacy systems to overhaul, India’s tabula rasa means that AI-first systems can be built from the ground up. The quick adoption of digital public infrastructure is the bedrock for these technologies. Such infrastructure generates enormous amounts of data, and thanks to India’s Account Aggregator framework, the data remain under the citizens’ control, further encouraging public trust and utilization. With this solid footing, India is well positioned to lead the charge in AI adoption.

India will do it
In September 2023, the Indian government, in collaboration with the EkStep foundation, launched the PM-Kisan chatbot. This AI chatbot works with PM-Kisan, India’s direct benefit transfer program for farmers, initiated in 2019 to extend financial help to farmers who own their own land. Access to the program, getting relevant information, and resolving grievances was always a problem for the farmers. The new chatbot gives farmers the ability to know their eligibility and the status of their application and payments using just their voice. On launch day more than 500,000 users chatted with the bot, and features are being released slowly to ensure a safe and risk-managed rollout.

These steps are part of an encouraging trend of early adoption of new technology by the Indian government. But the trend extends beyond the government. India’s vibrant tech ecosystem has taken off as well, a direct offshoot of its booming IT exports—currently at nearly $250 billion a year. Next to those from the US, the largest number of developers on GitHub, a cloud-based service for software development, are from India. This sector not only innovates but also widely adopts digital public infrastructure. The effect is cyclical: start-ups feed the growing tech culture and, in turn, leverage the data to build more precise and beneficial AI tools. India’s dynamic start-up ecosystem, moreover, is actively working on AI solutions to address various challenges.

AI can be a game changer in education as well, helping close the literacy gap. AI technologies are uniquely positioned to help students learn in their native languages, as well as learn English. AI’s applications are useful not only for students; they extend to teachers, who are often overwhelmed by administrative tasks that detract from teaching. As AI takes over routine tasks in government and start-ups, the roles of teachers and students evolve, and they form dynamic partnerships focused on deep learning and meaningful human interaction.

What India needs is a strategic plan to chase down the most important opportunities for AI to help. The trick is not to look too hard at the technology but to look at the problems people face that existing technology has been unable to solve. And organizations such as EkStep have stepped up with a mission called People+AI. Instead of putting AI first, they focus on the problems of people. This has led to surprising new uses unique to India.

India’s emerging status as a technological powerhouse, combined with its unique socioeconomic landscape, puts it in a favorable position to be the world’s most extensive user of AI by the end of this decade. From streamlining education to aiding in social protection programs, AI has the potential to deeply penetrate Indian society, effecting broad and meaningful change.

Nandan Nilekani is the chairman and cofounder of Infosys and founding chairman of UIDAI (Aadhaar) and Tanuj Bhojwani is head of People+AI.

Opinions expressed in articles and other materials are those of the authors; they do not necessarily reflect IMF policy.

A growth trajectory of 6.5 to 7.5 %, centred around 7 %, is reasonable in the coming years, barring the eventuality of simultaneous external shocks.

In view of its robust growth of 7.7 per cent during the first half of the current fiscal year, the Reserve Bank of India (RBI) has upgraded the full-year growth forecast for the Indian economy to 7 per cent. The erstwhile estimates by multilateral agencies and the private sector, which have hitherto varied between 6.3 and 6.5 per cent, are also likely to get revised soon to align more closely with the RBI’s estimate.

What explains this resilience of the Indian economy? Besides global demand for goods and services, the Indian economy is largely impacted by five key shocks: Deficient or erratic rainfall; a sharp increase in the price of oil; political or policy uncertainty; macroeconomic instability, including any originating in the financial sector; and global risk aversion resulting in abrupt withdrawals of capital flows and an increase in the cost of external finance.

The Indian economy has become relatively more immune to each one of these shocks.

First, the agriculture sector is less impacted by routine deficiency or erratic patterns in rainfall. This is due to crop diversification, expanded irrigation networks, and the availability of more advanced and accurate weather information, which allows for a timely policy response to shocks. This is not to say that we have overcome all the challenges emanating from climate change or weather-related events, but simply that when confronted with the same shocks as witnessed before, agricultural growth, productivity, and resilience are now higher than before.

Second, the Indian economy has achieved more insulation from sharp increases in oil prices. The oil intensity of gross domestic product or GDP (consumption of oil per unit of GDP) has been declining consistently. This trend is likely to continue as the country moves towards renewables, and with increased economic prosperity, the economy transitions toward less energy-intensive activities such as services. This insulation is partly the reason why it has been possible to maintain the current account deficit below 2 per cent of GDP over the last five years, and why it has been seemingly disconnected from global oil prices. Interestingly, with the reduced importance of oil as a source of energy worldwide, sharp spikes in oil prices may themselves become less frequent in coming years.

Third, in India’s mature democracy, elections in recent years have been conducted without any contention, as the electorates have been delivering decisive mandates. The recently concluded Assembly elections in five states further confirmed the trend that the days of a hung Parliament, hung Assemblies, or complex alliances seem to be over. This phenomenon will strengthen the perception of political and policy stability in the country, providing a more conducive environment for long-term investments.

Fourth, macroeconomic stability and a safe and efficient financial sector matter for growth. India has done well on both counts. The banking sector has fully emerged from a decade-long shadow of distressed balance sheets. Under the watchful eyes of the banking regulator, the RBI, and their partial owner, the government, the sector has supported economic growth by attaining double-digit credit growth. The non-banking parts of the financial sector have also stabilised after the mini-crisis they experienced during 2019-20.

Be that as it may, hereon, the competing objectives of growth and risks need to be balanced keenly, with neither being compromised for the sake of the other. Consumer finance is an important segment of an economy that is steadily becoming more prosperous and inclusive. It is imperative to find ways to manage the risks better and ensure that consumer finance and private consumption growth are not impaired as engines of growth in the pursuit of safety.

Finally, despite implementing prudent policy frameworks, the emerging markets economies remain susceptible to the reversals of external capital flows for reasons beyond their control. India lost nearly $40 billion worth of portfolio flows during 2021-22. Leveraging past experiences, and using the cushions built during quiet times, the RBI and the government now respond promptly to these shocks. This has further insulated the real economy from the disruptive impacts of such reversals.

All these factors do not imply that the economy is completely insulated from all kinds and severity of shocks or extreme events, whether occurring singly or simultaneously. All it means is that the economy has become much more resilient to isolated shocks of the magnitudes seen in the past.

Immunity to known shocks will likely continue to strengthen in coming years as the economy becomes more prosperous. Yet, new challenges will also emerge: An inevitably ageing population; climate-related events; technology and skills replacing labour in labour-intensive activities; and a heavily indebted world, in need of deleveraging. It would serve India well to focus on accelerating sustainable growth while continuing to reduce its susceptibility to existing and emergent shocks.

So, what might the growth numbers eventually look like during this year and the next?

Drawing from the statistical regularities highlighted by past data, GDP growth this year may turn out to be even higher than 7 per cent. These regularities are as follows: First, during the decade before Covid, the growth rate in the second half of the fiscal year lagged behind that in the first half of the year by only about an average 0.5 percentage points. Second, about 48 per cent of the economic activity was generated during the first half of the year, and the remaining 52 per cent in the second half.

Combining these two observations with the fact that no new shocks or adversities are likely to materialize during the rest of this year, one could conceive growth of about 7 per cent during the second half of the year, yielding an annual growth rate of about 7.4 per cent.

In view of its increased resilience, barring the eventuality of multiple shocks hitting the Indian economy simultaneously, a growth trajectory of 6.5 to 7.5 per cent, centered around 7 per cent, seems like a reasonable baseline scenario for next year too.

The writer is director general of NCAER, and a member of the Economic Advisory Council to the Prime Minister of India. Ayesha Ahmed contributed to this piece