India's Potential Growth Rate: A Harrod-Domar Perspective Including Technological Progress.....

The Harrod-Domar (H-D) model, a foundation of growth theory, posits that the potential growth rate (𝐺𝑝) of an economy is determined by its savings rate (s) and the efficiency of capital investment, expressed as the Incremental Capital-Output Ratio (ICOR or 𝑣). Specifically, the model holds that 𝐺𝑝=𝑠/𝑣. In the context of India, this model implies that to sustain higher, non-inflationary, long-term growth, the country must boost its savings and improve the productivity of its capital. While the traditional model assumes constant technology, integrating capital-saving and labour-saving technology adjustments—which alter the ICOR and labour productivity—provides a more nuanced, modern interpretation of India’s potential, which is currently estimated to be around 6.5% to 7% in the medium term.

The Core Harrod-Domar Framework for India

The potential growth of the Indian economy is fundamentally linked to its investment rate (Gross Fixed Capital Formation or GFCF) and the productivity of that capital.

•           Data Profile (2023-25): Recent data shows India’s Gross Fixed Capital Formation Rate (GFCFR) hovering around 31% to 34.5% of GDP.

•           ICOR (2018-2025): The ICOR, which measures capital inefficiency (higher means lower efficiency), has averaged around 5.2 to 5.3 in recent years.

•           Potential Growth Calculation: Using the formula  

                                                            Gp=s/v                                                            

With a 34% investment rate and an ICOR of 5.2, India’s potential growth rate is calculated to be roughly 6.5%.

Incorporating Technological Progress

Technological progress significantly alters the standard H-D model, enabling a higher growth rate for a given savings rate by reducing the required capital per unit of output or enhancing labor efficiency.

1. Capital-Saving Technologies

Capital-saving technology improves the efficiency of capital, effectively reducing the ICOR (𝑣).

•           Impact on India: Increased digitalization (e.g., UPI, digital infrastructure), AI, and automation in manufacturing reduce the amount of physical capital needed to produce an additional unit of output.

•           Effect on Growth: If AI and advanced manufacturing lower the ICOR from 5.2 to 4.5, for example, the same 34% investment rate could drive a higher potential growth rate is appproximately equal to 7.5 % reducing the "knife-edge" instability of the model.

•           Data Trend: While investment has been high, inefficiencies and regulatory delays have occasionally increased the ICOR (reaching up to 8.5 in FY13), acting as a drag on potential growth.

2. Labour-Saving Technologies (and Productivity Enhancements)

While often associated with replacing workers, labor-saving technology in a developing country like India mainly manifests as increased labor productivity or “efficiency of labor.”

•           Impact on India: The adoption of modern technology in agriculture and services reduces the labor required per unit of output, increasing output per worker.

•           Effect on Growth: In the context of India's large, relatively low-skilled workforce, labor-saving technology (such as mechanization) must be balanced with capital-intensive technology to prevent structural unemployment. When successful, it boosts the Total Factor Productivity (TFP) component, enhancing the numerator of the H-D model indirectly by increasing overall economic capacity.

•           Data Trend: India’s shift toward services (high-tech IT, finance) demonstrates this, where labor productivity is much higher than in traditional sectors, allowing the economy to exceed the 6.5% mark in specific, favourable environments.

Recent Trends and Potential

•           Current Potential: India's potential growth rate is currently seen around 6.5% to 7.0%.

•           Positive Influences: Robust public sector investment in infrastructure has boosted capacity, while the tech sector (contributing 7.3% to GDP in FY24) provides a strong, capital-efficient, high-productivity boost.

•           Negative Factors: The aging of older capital stock and the high cost of adopting new, cutting-edge technologies might create a "replacement cost" issue, offsetting some gains from technological progress.

According to the Harrod-Domar model, India's potential growth rate is fundamentally a product of its ability to sustain a high savings-to-investment ratio, currently at a robust 34.5% of GDP, and its capital efficiency. While the traditional model suggests a 6.5% potential, the inclusion of technological progress, particularly capital-saving digital infrastructure (like AI and digitization), acts as a significant accelerator, allowing India to maintain a higher growth ceiling (6.5%–7.0%) than otherwise possible. To sustain a higher potential, India must continue to lower its ICOR through structural reforms and efficient technological adoption, reducing the capital needed for growth and maximizing the output from its expanding labor force. 

The Trajectory to Viksit Bharat: India’s Path from Developing to Developed Economy.....

As of early 2026, India stands at a defining juncture in its economic history, having established itself as the world’s fourth-largest economy in nominal terms. While its aggregate GDP, estimated at around $4.1 trillion to $4.5 trillion, places it behind only the United States, China, and Germany, India remains a "lower-middle-income" country. The core challenge, and the ultimate goal for becoming a "developed economy" (Viksit Bharat) by 2047, lies not in aggregate size but in drastically lifting its per capita income. India’s per capita GDP is estimated at approximately $2,800–$3,000 for 2025–2026, positioning it around 136th–144th globally. This discrepancy highlights that while the nation is becoming an economic powerhouse, the average prosperity per person requires substantial, sustained growth over the next two decades.

Current Position (2025-2026) and Recent Growth

India has maintained its status as the world's fastest-growing major economy, with real GDP growth rates frequently exceeding 6.5% to 8%.

Nominal GDP Per Capita (2025-26): Estimated to be around $2,818 to $3,051.

Global Ranking: 4th largest economy (Nominal GDP), but roughly 144th in per capita terms.

Trajectory: The per capita income has more than doubled from approximately $1,000 in 2009 to over $2,000 by 2019. The current growth is driven by massive infrastructure expansion, digital public infrastructure (UPI), and a young working population.

Growth Expected and Trajectory to a Developed Economy (2030-2047)

To reach the status of a developed nation (defined generally as a high-income country by the World Bank, currently requiring a per capita GNI over $13,846), India needs to sustain high growth rates for 20-25 years.

Intermediate Goal (2030): Per capita income is projected to approach $4,000–$4,500, transitioning India into the upper-middle-income category. By this time, India is projected to be the 3rd largest economy, surpassing Japan and Germany.

Long-Term Goal (2047): To be considered a developed economy by 2047, the 100th anniversary of independence, projections indicate that India must achieve a per capita income of approximately $13,000–$18,000, and potentially as high as $26,000 in optimistic scenarios.

Growth Required: This requires a compound annual growth rate (CAGR) of 8% to 9.25% in dollar terms for the next two decades, which is significantly higher than the present trend.

Key Drivers of Growth and Structural Changes

To achieve this, the Indian economy is pivoting from a reliance on the service sector to a balanced growth model:

Manufacturing Expansion: The manufacturing sector's share of GDP is targeted to rise to 25% by 2047, up from ~17%.

Demographic Dividend: With a median age of 31, India has a significant working-age population advantage.

Infrastructure & Digitalisation: Sustained capital expenditure (CAPEX) by the government is enhancing productivity.

Formalisation: The continued formalisation of the economy, through initiatives like GST, aims to increase tax-to-GDP ratios and expand the formal workforce.

India’s path to becoming a developed economy is both plausible and challenging. While the country is on track to become the world's third-largest economy by 2028, bridging the gap from a lower-middle-income nation to a high-income nation by 2047 requires increasing the per capita GDP by more than five times the current value. The trajectory necessitates consistent,, high-digit growth in per capita income, supported by manufacturing growth, skill development, and rising female labour force participation. If these structural reforms are successfully implemented, India could transform from a developing economy into a high-income country within the next 25 years.

2022-23 as Base Year: A Structural Analysis.....

The Government of India’s decision to revise the base year for GDP, Index of Industrial Production (IIP), and Consumer Price Index (CPI) to 2022-23 has drawn scrutiny, particularly regarding the use of 2022-23 as a base year for inflationary metrics. Since the implementation of the Flexible Inflation Targeting (FIT) framework in 2016, the Reserve Bank of India (RBI) is mandated to maintain headline CPI inflation at 4% with a tolerance band of +/- 2%. A "normal" base year for inflation should ideally reflect price stability near this 4% target. However, choosing a year where inflation was near the 6% upper limit, driven by global supply shocks, raises questions about the legitimacy of this base year for long-term comparative analysis.

The Problem with 2022-23 as a Base Year

The fiscal year 2022-23 saw retail inflation elevated, averaging 6.7 per cent, driven largely by post-pandemic recovery, supply chain disruptions, and the impact of the Russia-Ukraine war.

Deviation from Target: The 6.7% average in 2022-23 represents a period of high inflation, not a "normal price-level" scenario. Using this as a base means subsequent years, even if inflation falls to 4% or 5%, will appear artificially low or stable, masking underlying price pressure.

Abnormal Economic Context: As noted in economic studies, a base year should not be a period of significant shocks, such as the immediate post-pandemic period. The 2022-23 period was characterized by elevated fuel and food prices—a "supply shock" rather than a sustainable economic equilibrium.

Alternative Years: Compared to 2022-23, years like 2017-18 and 2018-19 (with CPI at 3.6% and 3.4% respectively) or even 2019-20 (5.8%) would have provided a more stable base closer to the 4% target.

Rationale for Choosing 2022-23

Despite the high inflation, the government chose 2022-23 to update the base year from 2011-12 to align with "newNormal" economic trends.

Reflecting Structural Changes: The primary reason is that the 2011-12 base year was outdated and did not capture the post-COVID economy, which saw a rapid increase in digital services, formalization of the economy, and changes in consumer consumption patterns.

Post-Pandemic Consumption Pattern: The 2022-23 Household Consumption Expenditure Survey (HCES) revealed new, updated spending habits.

International Standards: Regularly updating to a recent year helps maintain compatibility with global best practices, even if the year itself was not entirely stable.

Structural Differences in Inflation: 2017-19 vs. 2022-23

The inflation experienced in 2017-19 was structurally different from that in 2022-23, requiring different policy responses.

2017-19 (Slowdown and Services Inflation): In 2018-19, inflation was driven primarily by services, while goods inflation was quite low at 2.6 per cent. Inflation was relatively low, closer to the 4% target, allowing for a neutral monetary policy stance.

2022-23 (Supply Side & Global Shock): The 2022-23 inflation was dominated by "supply-side pressures" in essential commodities (fuel and food). High prices for goods like Wheat (due to a heatwave and crop shortfall) and Sunflower Oil (due to the Ukraine conflict) drove the 6.7% rate.

Examples of Differences:

Food Inflation Structure: 2017-19 saw moderated food prices following good monsoon years. In contrast, 2022-23 saw a sharp spike in pulses and wheat, with food inflation being high (often crossing 7-8%), driven by structural supply chain issues, not high demand.

Fuel Pass-Through: In 2022-23, the surge in global crude oil prices was partly mitigated by government tax cuts, keeping domestic fuel inflation from hitting even higher levels, whereas in 2017-19, oil prices were moderate.

Using 2022-23 as a base year for inflation is arguably flawed from a "normal price level" perspective, as it was a period of high inflation near the upper limit of the target band. The decision to use this year seems to be driven by the need to capture updated, post-pandemic consumption patterns and digital trends, rather than a desire to represent a "stable" price base. While it improves the structural accuracy of the consumption basket, it risks creating a "high base effect," making future inflation figures look deceptively moderate compared to the 2022-23 peak, thus misrepresenting true inflationary pressure compared to the 4% target.

The Illusion of Scale: Why India’s High-Speed Growth Masks Low-Income Reality.....

India is currently celebrated as the world's fastest-growing major economy, with real GDP growth rates often hovering around 7-8%. However, this impressive percentage growth rate is largely a function of a "small base effect"—the mathematical reality that a 7% increase on a small number yields a much smaller absolute addition to wealth than a 2% increase on a massive base. While India is the world's 4th or 5th largest economy by nominal GDP, its 1.4+ billion population means this wealth is spread thin. Consequently, high growth on a small base often results in less absolute wealth accumulation than low growth in developed nations, highlighting that India's overall GDP remains very low relative to its population.

1. The Mathematics of "Small Base" vs. "Large Base"

The crux of the issue is that percentage growth is misleading without context of the starting base.

India's Scenario (Small Base): If India’s GDP is $4 trillion (approx. 2025) and it grows at 8%, the GDP increases by roughly $320 billion.

Developed Economy Scenario (Large Base): If a country with a $20 trillion GDP (like the USA) grows at just 2%, its GDP increases by $400 billion.

Data Example: India's per capita GDP was approximately $2,694 in 2024, whereas Japan's was over $32,000 and Germany's over $56,000.

Conclusion: Even though India is growing faster, the absolute amount of new wealth generated per person is far lower than developed peers, making it harder to pull the population out of low-income brackets quickly.

2. High Growth on Small Base: The "Illusion of Magnitude"

India's high growth rate is frequently driven by post-pandemic recovery (a low base) or catch-up growth, rather than sustained, high-productivity manufacturing.

Example of Base Effect: Following COVID-19, a 24% contraction in Q1 FY21 created a very low base, making subsequent 20% growth figures appear astronomical, even though the economy was merely recovering.

The Reality: Despite being the 4th largest economy, India's per capita income ranks it around 136th globally. The high growth rate often serves to boost the overall economy, but it does not immediately translate to high individual income.

3. Large GDP Base in Low Growth Regime (Developed Economies)

Developed nations (e.g., USA, Japan, Germany) often have 1-3% growth, which is considered low. However, because their GDP base is already high, this low growth represents a massive influx of new capital and wealth.

Example: A 2% growth for a $20 trillion economy = $400 billion.

Why it's better: This wealth contributes to higher living standards, better public infrastructure, and higher wages, even with sluggish percentage growth.

4. Population Scale: Why India's GDP Feels Smaller

India's total GDP is high, but the "GDP per capita"—the true indicator of individual prosperity—is very low due to the 1.4+ billion population.

The Paradox: India can become the 3rd largest economy, but if its population grows, the average income per person still lags behind emerging peers like Vietnam or the Philippines.

Employment Drought: A significant portion of the workforce (about 46%) is still engaged in low-productivity agriculture. A high percentage growth in the organized service sector often does not generate enough employment for the massive population, leading to "jobless growth."

5. The Role of Nominal vs. Real Growth

Recent trends show that while real GDP growth (adjusted for inflation) is high, nominal GDP growth (not adjusted) has been lower, indicating that inflationary pressure is reducing the real purchasing power of the income generated.

Example: If real GDP grows at 8% but the GDP deflator (a measure of inflation) falls sharply, tax collections and corporate revenues—which are calculated in nominal terms—might not actually increase as much as expected.

India’s high economic growth rate on a small base is a positive, yet deceptive, indicator of prosperity. It signifies progress but masks a low overall GDP per capita compared to the massive population. While rapid growth is necessary to catch up, the "base effect" implies that even with high growth, it will take decades for India to match the per capita wealth of developed nations. To truly shift from a "big economy" to a "rich economy," India must focus on shifting its massive workforce from low-productivity sectors to high-productivity manufacturing and services to ensure the wealth generated translates into a higher standard of living for every citizen.

The Narrative Economy: How Government Communication Shapes Economic Destiny....

In modern economics, perception is reality. While fiscal policies, interest rates, and structural reforms form the skeletal structure of an economy, public perception and expectations constitute its heartbeat. Government communication is not merely a tool for publicity; it is a powerful and tangible policy instrument that influences consumer spending, investor confidence, and corporate investment. By managing expectations, governments can stimulate growth without immediate, direct spending. Conversely, a failure to manage this perception can turn moderate risks into crises by fostering uncertainty, causing economic agents to freeze, hoard, or flee.

Perception Building as a Tool for Economic Growth

Governments use perception building to steer the economy toward desired outcomes by setting a narrative of stability and progress.

Expectations Management: If citizens believe the future is bright, they spend more today; if investors believe a country is stable, they invest. The 2019-20 India Economic Survey emphasized that wealth creation and policy communication (e.g., affordability of a "Thali") directly affect public perception of economic performance.

Building Investor Confidence: Clear, consistent communication reduces risk premiums. When a government communicates a predictable, pro-growth agenda, it attracts Foreign Direct Investment (FDI).

Accelerating Reforms: Proactive communication makes structural reforms (like deregulation, labor reforms) more acceptable, reducing friction during implementation.

Driving Behavioral Changes: During economic downturns, government narratives can encourage "Buy Local" campaigns, boosting domestic industries.

Examples & Precedents:

"Acche Din" & Digital India (India): The proactive, tech-savvy communication by the Indian government (e.g., using apps like GARV to track rural electrification) created a perception of accountability and speed, accelerating the perception of a developing, modernizing economy.

Inflation Targeting (Canada): The Bank of Canada and the government jointly announce inflation targets. This clear, coordinated communication anchors inflation expectations, ensuring stability, which is a vital component of sustainable growth.

Start-up India Initiative: By creating a "Start-up" narrative, the government influenced public perception to see entrepreneurship as a viable career, driving investment into this sector.

Failure to Manage Perception: The Path to Uncertainty

When communication is opaque, inconsistent, or reactionary, it creates an "information vacuum," which is rapidly filled by fear, rumours, and panic.

Information Vacuum & Panic: A delayed response during crises (e.g., financial, health) leads to loss of trust and panic, which can causebank runs or market crashes.

Policy Ambiguity: Unclear fiscal frameworks or changing rules without notice create uncertainty, driving capital flight and widening risk premiums.

Lack of Credibility: When there is a significant gap between the government's narrative (image) and the ground reality, credibility breaks down, rendering future communication ineffective.

Examples & Precedents:

Three Mile Island Disaster (USA, 1979): The U.S. nuclear energy sector was paralyzed for nearly 30 years due to the mishandling of public communication. The government's slow, technical, and inconsistent messaging led to massive public panic, despite low physical health impacts, resulting in a total freeze of new nuclear projects.

2008 Subprime Mortgage Crisis (USA): The failure to manage the perception of risk in the housing market, coupled with ambiguous regulation, led to a worldwide collapse in confidence.

COVID-19 Communication Failure (General): Inconsistent messages about safety protocols and vaccine availability in many countries widened the gap between public anxiety and trust, leading to poor compliance and economic disruption.

Sudden Regulatory Changes: In many emerging markets, sudden changes in taxation or FDI rules, without prior stakeholder communication, have caused foreign investors to sell off assets and halt projects due to the inability to predict future costs.

Perception management and communication are not peripheral; they are foundational to modern governance, serving as "core infrastructure" that bridges policy intent with economic reality. A proactive and credible communication strategy transforms expectations into tangible, high-growth outcomes. Failure to do so, however, creates a poisonous environment of uncertainty, wherein even sound economic policies fail. In the digital age, where narratives are built or broken in seconds, the government must view its communication not just as a tool for popularity, but as an essential, tangible instrument of economic stability and growth.

The Indian Judicial System is a Drag on the Economic Growth....

The inefficiency of India's judicial system acts as a persistent drag on the nation's economic potential, resulting in substantial losses in Gross Domestic Product (GDP). The chronic delays in dispute resolution, estimated to cost the country approximately 1.5% of its GDP annually, impede investment, reduce business confidence, and hinder overall economic development.The inefficiency of the Indian judicial system manifests primarily through massive pendency of cases. As of late 2024, there are over 45 million cases pending across all court levels. The Allahabad High Court, for example, is projected to take approximately 300 years to clear its backlog at the current pace, a stark illustration of the systemic gridlock.

This procedural logjam has profound economic consequences:

Deterred Investment: Businesses, both domestic and international, are hesitant to invest when contractual enforcement and dispute resolution cannot be guaranteed within a reasonable timeframe. The World Bank's "Enforcing Contracts" indicator, within its Ease of Doing Business reports, consistently highlights India's poor performance in this area, noting that resolving a commercial dispute can take years, tying up capital and resources.

Locked-up Capital: Disputes over land, property rights, and debt recovery trap trillions of rupees in assets. An estimated ₹10 lakh crore (approximately $120 billion USD) is currently locked up in various litigations, preventing the productive use of this capital in the economy.

Increased Transaction Costs: Businesses incur high legal fees and opportunity costs waiting for resolutions, effectively an indirect tax on economic activity. The uncertainty associated with legal outcomes makes long-term planning difficult.

Collectively, these factors lead to a consensus estimate among economists and institutions like the NITI Aayog and the Confederation of Indian Industry (CII) that judicial inefficiency reduces India's GDP growth by at least 1-1.5% annually.

Assigning Responsibility: Beyond the Government

While the government holds significant responsibility for budgetary allocations and judicial appointments, assigning sole blame to the executive branch is an oversimplification. The primary responsibility for the day-to-day inefficiency lies with a complex interplay of factors within the judicial system itself, and specifically, the Judiciary's own administration and procedural rigidity.

Here is a breakdown of key responsibilities:

1. The Judiciary (Administration and Bar Councils):

The judiciary is largely self-governing in its internal administration, rules of procedure, and case management. The failure to adopt modern case management techniques, the reluctance to mandate continuous working hours, frequent adjournments, and insufficient use of technology are internal administrative failures. The Supreme Court and High Courts have the power to create and enforce rules to expedite trials but have historically been slow to implement radical reforms.

2. The Legal Fraternity (Lawyers and Bar Associations):

A significant portion of the blame rests with certain sections of the legal fraternity. The practice of seeking excessive adjournments, often used as a dilatory tactic by lawyers, is a major contributor to delays. Bar Councils and associations have largely failed to self-regulate this behavior effectively.

3. The Executive and Legislature (Government):

The government is responsible for ensuring sufficient funding and infrastructure. While the budget allocation for the judiciary has historically been low (around 0.2% of GDP), the judiciary itself has also been slow in utilizing allocated funds efficiently or demanding radical infrastructural overhauls.

While the government provides the necessary resources, the judiciary's own administrative structure and procedural inertia are the most responsible non-government factors for the pervasive inefficiency. The lack of accountability for delays within the system itself is a primary impediment to reform. The inefficiency of India's judicial system is not merely a legal or social issue; it is a significant economic constraint. Addressing the estimated 1.5% annual GDP loss requires more than incremental changes. It demands a collaborative effort where the judiciary embraces modernization, implements stringent case management protocols, and holds itself accountable for timely justice delivery. Only through fundamental reform can India unlock its full economic potential and ensure that justice is not just a constitutional right but a tangible reality.

A Data-Driven Comparison of Indian Economic Growth under Manmohan Singh and Narendra Modi.....

The economic performance of India under different political dispensations is a subject of intense debate, often complicated by changes in data calculation methodologies and varying global economic conditions. A balanced comparison of the two tenures, the Congress-led UPA government under Dr. Manmohan Singh (2004-2014) and the BJP-led NDA government under Narendra Modi (2014-present), requires examining real GDP growth rates and real per capita GDP (or per capita income) using consistent data series to provide a clearer picture of wealth creation and distribution.

Real Economic Growth Rates (Real GDP)

During his tenure, particularly in the first term (2004-2009), Dr. Manmohan Singh presided over a period of robust economic expansion, often referred to as a "massive boom". The average annual real GDP growth rate during his entire decade in office (2004-2014) was approximately 7.7%. The period saw India achieve its highest-ever annual GDP growth rate in modern history, reaching over 10% (specifically 10.08% under the new 2011-12 base year methodology) in the fiscal year 2006-07. The economy consistently grew at 8-9% before the 2008 global financial crisis.

Narendra Modi's tenure (2014-present) has been marked by different global and domestic challenges, including demonetization in 2016, the implementation of GST, and the significant impact of the COVID-19 pandemic. The average annual real GDP growth rate under the Modi government is estimated to be lower, around 5.8% to 6.8%, depending on the period and data source used. While the Modi government saw strong growth initially (e.g., 8.2% in 2016-17, revised upwards from earlier estimates), the overall average has been affected by the -5.8% contraction during the pandemic year (2020-21).

In a like-for-like comparison using the same (2011-12) GDP series, data suggests the UPA era generally saw a higher average real GDP growth rate than the NDA era.

Real Per Capita GDP (Per Capita Income)

Per capita income is a critical indicator of the average standard of living and the rise in individual wealth. The growth in real per capita income also indicates whether the benefits of overall economic growth are reaching the populace.

During the Manmohan Singh years (2004-2014), the real per capita income experienced a significant rise, with a total growth of around 250% in nominal terms, and substantial growth in real terms (at constant prices). The average Indian's income grew faster during this decade, at an average rate of 6% annually, than in the subsequent decade.

Under the Modi government (2014-present), the growth in real per capita income has been slower. Estimates suggest the average annual growth has been around 4%. While the nominal per capita income has increased, the pace of increase in real terms has been lower compared to the UPA era. One analysis using 2011-12 constant prices estimated the real per capita income grew by approximately 34.52% from 2014 to 2024, compared to the 250% overall growth during 2004-2014 (which includes nominal figures). This slower growth in per capita income is attributed by some analyses to slower private sector investment and fewer job opportunities being created, particularly in low-skilled sectors like real estate and construction.

The economic narrative of the two periods presents a nuanced picture. Dr. Manmohan Singh's tenure was characterized by a "boom" phase with higher average real GDP growth rates and a faster increase in per capita income, benefiting from the momentum of earlier liberalisation policies and a favourable global environment (initially). Mr. Narendra Modi's tenure, while marked by significant structural reforms and improved macroeconomic stability in areas like inflation control, has seen a lower average real GDP growth rate and a slower rise in per capita income, partly due to major economic disruptions and a challenging global environment including the pandemic. The data suggests that, on average, the Manmohan Singh era outperformed the Modi era on the primary metrics of real economic growth and per capita income growth.

The Pace of Formalization: A Comparative Analysis of the Modi and Manmohan Singh Eras.....

The formalization of an economy, the process of shifting from informal, unregulated sectors to formal, regulated structures, is a key indicator of economic modernization and development. It leads to better tax compliance, improved social security coverage for workers, and more robust data for policy-making. The administrations of both Prime Ministers Manmohan Singh (2004-2014) and Narendra Modi (2014-present) implemented policies that influenced this process, albeit through different approaches and with varying outcomes amidst differing global and domestic economic conditions.

Pace of Formalization: Modi vs. Manmohan Singh

A direct comparison of the pace of formalization is complex due to a lack of a single, universally accepted official metric and changes in data calculation methodologies over time. The "current official formalization is 10%" is much lower than actual estimates (which still show a large informal sector, but not 90%). However, an analysis based on key indicators and the general economic climate of each era provides insight into the relative trends.

Manmohan Singh Era (2004-2014): Growth and Gradual Shifts

The Manmohan Singh era was characterized by a period of robust average annual GDP growth (around 8.1%) driven by liberalization policies and a booming services sector. This period saw:

Organic Growth in Formal Indicators: High growth rates in sectors like automobile sales, retail loans, and income tax collections suggested rising incomes and a growing consumer base, likely indicating a gradual, organic expansion of the formal economy.

Welfare Schemes: The UPA government focused on inclusive growth and launched major welfare schemes like MGNREGA, which, while providing a safety net, were primarily aimed at the rural and informal sectors.

Stable Tax-to-GDP Ratio: The average tax-to-GDP ratio was around 10.4%, with efforts to widen the tax base, though challenges in enforcement persisted.

The formalization during this time was steady, influenced by high economic growth and increasing prosperity that pulled people into formal consumption patterns and employment.

Narendra Modi Era (2014-present): Structural Reforms and Disruptions

The Modi government adopted a more assertive approach with major structural reforms aimed explicitly at formalization, though these were accompanied by significant economic disruptions:

Demonetization and GST: The 2016 demonetization and the implementation of the Goods and Services Tax (GST) were major interventions intended to bring informal transactions into the formal tax net. These measures significantly disrupted the informal sector, forcing many businesses to formalize or close down in the short term.

Digital India and Financial Inclusion: Initiatives like the push for digital payments and Jan Dhan bank accounts (financial inclusion) have created a more traceable economic environment, a prerequisite for formalization.

Improved Tax Compliance: The average tax-to-GDP ratio improved to approximately 11.5% under the Modi government, reflecting better tax compliance and a broader tax base due to the GST.

The Manmohan Singh era saw a higher average GDP growth rate, with formalization proceeding as a byproduct of broad economic expansion. In contrast, the Modi government has actively pursued formalization through structural and often disruptive policies. While the pace of growth in certain real-time economic indicators (like car sales or cement production) was slower under Modi compared to Singh's era, the Modi government's targeted reforms appear to have accelerated the structural shift towards a more formalized economy, despite short-term challenges. For instance, a recent report suggests 171.9 million jobs were added in the decade up to 2024 under Modi, compared to 29 million under the UPA, though the quality and formality of these jobs is a subject of debate. The Manmohan Singh government oversaw a period of high, broad-based economic growth during which formalization occurred organically and gradually. The Modi government's tenure is marked by intentional, high-impact structural reforms like GST and demonetization, which aimed to rapidly formalize the economy. This policy approach, while causing short-term pain to the informal sector, has potentially set the stage for a more tax-compliant and formalized economic structure in the long run. The data suggests that while the overall economic growth was higher under Manmohan Singh, the Modi government has been more aggressive in its direct efforts to expand the formal sector, resulting in a potentially faster pace of structural formalization, even if general economic indicators showed moderation in some areas.

The Data Landscape of an Informal Economy: Expectations for India's 90% Informal Sector.....

The formal economy is characterized by registered businesses, codified labor laws, traceable transactions, standardized contracts, and verifiable data that is collected, recorded, and regulated by government and official institutions. The informal economy, conversely, operates largely outside these structures. When an economy like India has an estimated 90% of its workforce and economic activity residing in this informal sphere, the nature, availability, and utility of "data" diverge significantly from what one would expect in highly formalized nations. The sheer scale of this informality in India does not just mean "missing data"; it signifies a fundamentally different data ecosystem—one that is fragmented, often qualitative rather than quantitative, and difficult to standardize.

What We Could Expect of Data in a 90% Informal Economy

If 90% of an economy operates informally, the expectations for data can be categorized into several key areas: data availability and quality, economic visibility, policy challenges, and alternative data sources.

1. Poor Data Availability and Quality

The most direct expectation is the absence of reliable, official data for the vast majority of economic activity.

Missing Core Economic Indicators: Standard metrics like GDP contributions by specific sub-sectors of the informal economy, precise employment figures, and real-time wage data become estimates at best. National statistical organizations must rely heavily on periodic, large-scale sample surveys rather than routine administrative data.

Lack of Firm-Level Data: Data on business formation, revenue, expenditure, and investment for millions of small, unregistered enterprises (e.g., street vendors, home-based workers, small-scale agriculture) are virtually non-existent in official registries.

Untaxed and Untracked Transactions: Because transactions are often cash-based and unregistered, administrative data gathered from tax receipts (like the Goods and Services Tax, or GST) captures only a fraction of the total economic flow, leading to a significant "dark figure" of economic activity [1].

2. Limited Economic Visibility and Inaccurate Policy Making

The lack of reliable data creates a visibility problem for economists and policymakers, leading to expectations of:

Inaccurate Official Narratives: Official economic growth figures may underrepresent the true economic resilience or vulnerability of the informal sector. The data fails to tell the full story of how most citizens live and work.

Ineffective Policy Calibration: When the data on the primary labor market is sparse, government interventions—whether minimum wage laws, credit availability schemes, or social security programs—struggle to effectively reach the intended beneficiaries. Policies designed for the formal sector often fail to translate to the needs of informal workers.

Vulnerability Assessment Difficulties: It becomes nearly impossible to accurately assess the impact of sudden shocks (like a pandemic or a natural disaster) on the most vulnerable populations without real-time, accurate data on their livelihoods and savings.

3. Fragmentation and Siloed Information

The existing data in such an economy is expected to be fragmented across different sources.

Siloed Data Sources: Instead of unified data systems, information is likely scattered across various local government bodies, non-governmental organizations (NGOs) focused on specific worker groups (e.g., waste pickers' unions), microfinance institutions, and academic research projects.

Reliance on Alternative and 'Big Data': There is an increased reliance on "proxy data" or "alternative data." This might include satellite imagery for agricultural tracking, mobile phone data for population movement and commerce patterns, or digital payment data from financial technology (FinTech) firms operating in the space. These sources offer new insights but come with their own biases and privacy concerns.

4. The Emergence of 'Qualitative' Data Importance

In the absence of robust quantitative data, qualitative research methods become crucial.

Case Studies and Ethnography: The data that is available often comes from in-depth case studies, ethnographic research, and localized surveys conducted by researchers to understand the nuances of informal markets, supply chains, and social networks. This data provides rich context but is not easily scalable or generalizable to the national level.

In an economy where 90% of activity is informal, the expectation of data must be fundamentally managed. The data ecosystem will be characterized by significant gaps, measurement challenges, and a reliance on fragmented, often non-traditional data sources. The journey toward greater formalization, as seen in recent initiatives in India like the push for digital payments and labor registries (such as the e-Shram portal), is essentially a journey to create better data. Until that formalization is achieved, policymakers must navigate a challenging landscape where broad national statistics tell an incomplete story, necessitating innovative approaches to data collection and a nuanced understanding of the vast, complex, and data-sparse informal reality.

If Savings from Russian Oil is Used to Provide Interest Subsidy or Subvention.....

 India, a major oil importer, has leveraged geopolitical shifts since February 2022 to purchase substantial volumes of discounted Russian crude oil. This pragmatic energy strategy has resulted in significant savings on the nation's overall import bill, estimated at least $17 billion between April 2022 and June 2025. While these savings have primarily accrued to state-owned and private refiners' profit margins and helped stabilize the nation's macro-economic indicators (such as the trade deficit and inflation), the proposition is to re-channel these "excess" funds into targeted interest subsidy and subvention schemes to directly enhance the competitiveness of critical domestic industries.

How Interest Subsidies Enhance Competitiveness

Interest subvention (subsidy) is a policy mechanism where the government bears a part of the interest burden on loans for specific sectors, effectively reducing the final interest rate for borrowers. Channeling the Russian oil savings into such programs would increase competitiveness through several key mechanisms:

Lowering the Cost of Capital: Reducing borrowing costs directly improves the viability of business operations and new investments, making Indian goods and services more price-competitive both domestically and globally.

Improving Liquidity: MSMEs, which often operate on thin margins and face working capital constraints, benefit immensely from cheaper credit, enabling them to procure raw materials, manage production cycles, and meet operational expenses without financial strain.

Stimulating Investment and Modernization: Affordable credit encourages businesses to invest in new technologies, upgrade machinery, and expand operations, which are crucial for enhancing efficiency and scaling up to compete with international players.

Promoting Targeted Sectoral Growth: Funds can be directed to priority sectors, such as labor-intensive exports (textiles, gems, and jewelry), to maximize job creation and foreign exchange earnings.

Data and Examples

India has existing frameworks for interest subvention, which provide clear examples of their impact:

Export Promotion Mission (NIRYAT PROTSAHAN): The government has already launched this scheme, with a total outlay of ₹25,060 crore (for FY 2025–26 to FY 2030–31), which includes a base interest subvention of 2.75% on pre- and post-shipment export credit for eligible MSMEs. This initiative aims to reduce the cost of export finance and improve global competitiveness.

Impact Data: The previous Interest Equalisation Scheme (IES) effectively brought down actual borrowing rates for MSMEs from a range of 9-12% to about 5-7%, significantly reducing financial pressure on exporters. This historical data demonstrates the direct positive effect of such schemes.

Potential Funding: India saved an estimated $8.2 billion in FY 2023–24 alone from Russian oil imports when discounts were wider. Rerouting a portion of such large sums could substantially bolster the NIRYAT PROTSAHAN fund or similar schemes, making them more impactful and sustainable.

Reinvesting the savings from Russian oil imports into interest subsidy and subvention programs presents a powerful, pragmatic strategy to enhance India's economic competitiveness. Instead of allowing the gains to remain concentrated in corporate profits or solely buffer general government finances, this approach would directly inject capital support into the productive sectors of the economy. By lowering the cost of credit for MSMEs and exporters, India can foster a more resilient, dynamic, and globally competitive industrial base, leading to sustained export-led growth and job creation. This policy action would effectively translate a geopolitical advantage into long-term domestic economic strength. Using the savings from importing discounted Russian oil to provide interest subsidies would significantly boost India's economic competitiveness by stimulating key sectors, particularly Micro, Small, and Medium Enterprises (MSMEs) and exports, by lowering borrowing costs, increasing liquidity, and encouraging investment. 

The RBI's Credibility and the Private Sector Response.....

The Reserve Bank of India (RBI) operates within a flexible inflation-targeting (FIT) framework, which aims to anchor inflationary expectations and ensure price stability while also supporting economic growth. While the RBI's forecasts have shown occasional significant misses, particularly concerning volatile food and fuel prices, recent data suggests the central bank has built considerable credibility. The private sector, in turn, is heavily influenced by the RBI's official stance, contributing to a self-reinforcing economic environment, though private investment remains a key variable for sustained, long-term growth.

The RBI's Credibility in Forecasting

The RBI's forecasting performance has been a mix of successes and challenges. The institution uses a comprehensive framework involving various models, historical trends, and expert consultations, and its officials maintain that there is no systematic bias in its projections.

Successes: Since the adoption of the FIT regime in 2016 (with a target of 4% CPI within a 2-6% band), inflation has become better anchored, and the central bank has been successful in managing price volatility during various shocks. A cross-country analysis of inflation forecast errors suggests that India's errors are in line with other emerging economies, often linked to the high share of food in the CPI basket.

Challenges/Misses: The RBI has faced criticism for significant forecasting errors, especially related to the volatility of food prices and external shocks. For example, the central bank failed to foresee the sharp disinflation that followed demonetization in 2016, which led to a high real interest rate regime that hampered investment. More recently, the RBI's quarterly GDP and inflation projections have sometimes deviated significantly from actual outcomes, leading some private economists to question the accuracy of its near-term forecasts.

How the Private Sector Follows Official Forecasts

The RBI's communications and forecasts play a crucial role in shaping market expectations, which can lead to a self-fulfilling prophecy.

Anchoring Expectations: The central bank's communication of its future inflation trajectory and policy stance is a primary driver of private sector inflation expectations. Private forecasters and businesses adjust their own expectations and decisions based on the RBI's stated outlook and the perceived future interest rate path, thus helping to reinforce the central bank's desired outcome.

Monetary Transmission: When the RBI maintains an accommodative stance and signals future rate cuts based on its forecasts, banks and financial institutions adjust their lending rates and credit conditions, which in turn influences private investment and consumption decisions.

Recent Examples and Data

Growth Forecasts (2025-2026): In December 2025, the RBI revised its GDP growth projection for FY 2025-26 upwards to 7.3% from an earlier 6.8% estimate, reflecting a robust domestic economy driven by strong private consumption and public investment. This optimistic outlook was echoed and reinforced by several international agencies, strengthening overall market sentiment.

Inflation Forecasts (Late 2025): In late 2025, India experienced exceptionally low CPI inflation, falling below 1% in November. While some private economists predicted even lower inflation (e.g., Deutsche Bank's forecast of 0.7% for a specific quarter), the RBI's more cautious projection of around 2% for the same period was seen as a way to maintain policy credibility and not prematurely declare victory over inflation. The RBI's decision to maintain the repo rate in the face of falling inflation demonstrated its commitment to the medium-term target of 4%, which helped anchor long-term expectations.

Private Capex Response: Despite a conducive environment of low inflation and supportive financial conditions engineered by the RBI, private sector capital expenditure (capex) has remained muted in recent quarters, with the government driving most investment. This suggests that while the private sector is influenced by the RBI's signals, it also awaits stronger, sustained demand visibility before committing to large-scale investments, indicating a nuanced interaction between official forecasts and private decision-making.

The RBI holds significant credibility in managing the overall macroeconomic environment in India, primarily through its commitment to the inflation-targeting framework, which has successfully anchored long-term price expectations. While its near-term forecasts can be subject to errors, especially due to external supply-side shocks inherent in an emerging market economy, the central bank's communication and projections heavily influence the private sector's outlook. The private sector largely aligns its expectations with the RBI's guidance, creating a self-reinforcing cycle of economic sentiment and activity. However, the transmission of monetary policy and the translation of positive sentiment into large-scale private investment remain key areas that determine the ultimate success of the RBI's forecasts in reinforcing sustainable economic growth.