Scale Without Deepening: India’s Export Transformation[1]

The Global Financial Crisis (GFC), the COVID-19 pandemic and now the Middle East war have reshaped the way major economies are approaching their trade and investment policies. For example, the United States of America is attempting to rebuild domestic manufacturing capacity, China is trying to lead global science and technology investment and Europe its defence production. Trade and investment barriers have resurfaced after decades of steady liberalisation.

The global economy has entered a new normal marked by rising protectionism strategic realignments and deepening geopolitical fragmentation. In this environment, India’s trade performance, particularly its exports, faces renewed stress and uncertainty. Economic reforms initiated during the early 1990s brought about a decisive shift in India’s integration with the global economy, opening domestic markets and embedding Indian firms more deeply into Global Value Chains (GVCs).

This paper examines India’s merchandise export performance through the lens of export deepening. Export deepening refers to the extent to which export growth is accompanied by greater domestic value capture, movement into more complex products, stronger capability accumulation, broader market diversification, and upgrading within global value chains. These dimensions are important because they influence not only the scale of exports but also the quality and durability of export-led growth.

India’s economic and trade performance has unfolded across seven analytically distinct phases shaped by turning points such as the Asian Financial Crisis, the export boom of the 2000s, the GFC, the prolonged post-2012 slowdown, and the COVID-19 shock and its aftermath. Each period impacted India’s economic performance, its export composition, market orientation, and import dependence. An era-based analysis makes these patterns visible in a way that aggregate analysis does not.

Drawing on trade, value-added and global value chain data, the paper argues that India’s export expansion has delivered substantial scale but more limited deepening. While export composition and market reach have evolved significantly, progress in domestic value capture, product complexity, diversification and upgrading within global production networks has been uneven. The result is an export transformation that is noteworthy for its scale, but less so for the extent of its structural deepening.

1. Research Questions

Despite a substantial body of work on India’s post-liberalisation growth, the existing literature has important gaps. Studies acknowledging the role of trade openness in India’s economic trajectory tend to operate at the aggregate level, examining exports and imports primarily in their relationship to GDP growth (Panagariya, 2008; Nayar, 2006). Sector-level analyses exist but are largely cross-sectional or confined to specific industries such as software and pharmaceuticals (Lall, 2001; Chandra, 2010).

Fewer studies trace how India’s export composition has evolved simultaneously across sectors, how domestic value addition and import dependence have shifted over time, and how geographic diversification patterns have responded to changes in trade arrangements. The role of free trade agreements (FTAs) in shaping export geography and the question of why FTA utilisation has remained structurally low also remains under-examined despite its growing policy relevance. Finally, the structural implications of the post-COVID new normal have not yet been assessed within a long-run, post-1991 Indian context.

This paper addresses these gaps through a framework that combines commodity-level patterns, geographic shifts, and structural analysis across seven post-reform eras.

The analysis is organised around three research questions.

1. How has India’s merchandise export performance evolved across major commodity groups since 1991, and what patterns emerge in terms of value addition, and concentration across the seven eras?
2. How has the geographic composition of India’s exports shifted across countries and regions over this period, and to what extent have trade agreements and regional partnerships influenced export concentration and diversification?
3. What structural challenges have emerged in the recent new normal era (2023–25), particularly rising protectionism, supply-chain concentration, and policy volatility, and how do they impact the sustainability of export performance built up over earlier eras?

We observe that India has achieved substantial export scale since 1991 without building commensurate resilience.

Its export basket remains concentrated in a small number of sectors with divergent value-addition profiles; its geographic reach has deepened but with narrowing number of partners; and its integration into global value chains has created import dependencies that amplify rather than absorb external shocks.

The remainder of the paper is organised as follows. Section 2 outlines the data sources and methodology. Section 3 presents the analytical framework and era segmentation. Sections 4, 5, and 6 address the three research questions in sequence. Section 7 concludes with synthesis, policy implications, and directions for further research.

2. Data Sources and Methodology

This study draws on four complementary official datasets to analyse India’s trade performance across commodities, geographies, and value-added structure. Each source serves a distinct analytical function, and their combined use allows the paper to move between long-run aggregate trends and granular product-level analysis within our era-based framework.

Aggregate export and import values, along with principal commodity group data, are drawn from the Reserve Bank of India (RBI) balance of payments and trade statistics. The RBI series provides a consistent long-term data from the post-liberalisation period onwards and is used here primarily to compute era-wise compound annual growth rates (CAGRs), identify compositional shifts in the export basket, and compare the relative pace of export and import growth across eras. It has also been used for analysing the geographic concentration of import and export markets.

To assess value capture and import dependence within exports, the paper uses the OECD Trade in Value Added (TiVA) database. TiVA’s measures of Domestic Value Added (DVA) and Foreign Value Added (FVA) embodied in exports are used to evaluate how different sectors integrate into global value chains and how dependent export performance is on imported inputs. TiVA data allow for consistent cross-sector and cross-temporal comparisons that gross trade statistics cannot provide, as two sectors with identical export values can reflect entirely different levels of domestic economic activity depending on their import content. It has also been used for understanding how well India has been integrated into the Global Value Chains through the Upstreamness[2] and Downstreamness[3] metrics across the eras.

Detailed product-level export and import data are drawn from TradeStat, India’s official trade statistics database compiled under the Harmonised System (HS) classification. Data at the 2-digit, 4-digit, and 8-digit HS levels are used to analyse changes in export composition, product concentration, and unit value trends. Unit values are derived by comparing value and volume CAGRs within each sector: higher value growth, compared to volume growth, indicates improving unit realisations. This methodology is used as a proxy for export quality and/or pricing power. An increase in unit realisation can also reflect product mix changes within a broad HS chapter.

Where required for contextual analysis — particularly in assessing global trade fragmentation, tariff conditions, and geopolitical risk in Section 6 — the paper draws on supplementary datasets from the World Trade Organization, UNCTAD, the International Trade Centre (Trade Map), Global Trade Alert, and the World Bank.

Limitations. TiVA data are available only through 2022, meaning value-added patterns for the new normal era (2023–25) cannot be directly measured and are inferred from earlier structural trends. TradeStat product-level data with consistent granularity are available from 2017 onwards, limiting the pre-2017 product analysis to broader compositional patterns using RBI commodity categories. We have also flagged the constraints that affect specific findings in the relevant sections.

3. Analytical Framework

The framework introduces two key ideas that are used throughout the analysis. The first is the distinction between India’s capital- and technology-intensive export segment and its labour- and land-intensive segment. This helps in understanding how different export sectors react differently to external shocks. The second is classification of export sector into four strategic groups — market-and-regulatory arbitrage, assembly-integration, capability-anchored, and cost-compression. Each group reflects a different way of participating in global markets and face a different set of challenges. These ideas are introduced here and applied in Sections 4, 5, and 6.

3.1 Conceptual Framework

3.1.1 Commodity Structure and Value Addition

Not all export sectors contribute equally to India’s trade performance or to the domestic economy more broadly. The nature of each sector (particularly its value-addition potential, technology intensity, and dependence on imported inputs) plays a determining role in shaping long-run competitiveness and resilience. Sectors with deeper domestic value creation tend to generate more durable export advantages, because their competitive position rests on accumulated firm capabilities, skilled labour, and supplier networks rather than on price or route contingencies. In contrast, sectors with high foreign value added i.e., where exports are largely assembled from imported inputs create export values without much contribution to domestic income, employment, and productive capacity.

This distinction is studied through measures of domestic value added (DVA) and foreign value added (FVA) embodied in exports. A sector may grow rapidly as an export contributor while simultaneously deepening import dependence, making export performance more sensitive to upstream supply disruptions and price shifts. Analysing commodity-level patterns within an era-based framework allows these underlying structural dynamics to be traced directly rather than inferred from aggregate trends.

3.1.2 Geographic Diversification and Trade Agreements

The geographic distribution of India’s exports is a critical dimension of trade performance because it determines both market opportunities and potential shock-transmission sources. Sectoral diversification and geographic diversification do not necessarily move together: a country can diversify its product basket while concentrating its markets, or vice versa. Identifying which direction India moved and whether the two forms of diversification reinforced or offset each other across eras is important for assessing export resilience.

Trade agreements add another important dimension to the analysis. India has signed several preferential trade agreements with ASEAN (2010), South Korea (2010), Japan (2011), and more recently the UAE and the EU, with the aim of expanding exports by improving access to these markets. However, it remains an open question whether these agreements increased exports or mainly changed the pattern of imports without producing a similar export gain.

3.1.3 Structural Challenges in the New Normal

The third aspect focuses on how changes in India’s trade structure have affected its ability to deal with external shocks. As India has become more integrated into global production networks, its exports have become more dependent on global economic conditions. This is not a cyclical issue but a structural feature of how trade is organized. The type of integration also matters. Sectors that mainly participate in assembly or processing stages of production are more vulnerable to disruptions in supply chains and changes in global demand. In contrast, sectors built on stronger domestic capabilities, technology, or specialized expertise tend to be more resilient and better able to withstand external shocks.

The post-COVID new normal — characterised by rising protectionism, geopolitical fragmentation, and persistent supply-chain uncertainty — makes this distinction necessary. Export sectors that performed well when global trade was expanding and supply chains were optimising for efficiency, face different conditions in an environment that rewards supply-chain security, regulatory adaptability, and geographic diversification of buyer relationships.

3.2 Era Segmentation

The post-1991 period cannot be treated as a single continuous phase because India’s trade as well as economic structure has been fundamentally reshaped at several distinct inflection points.

Seven eras are identified, each defined by a primary inflection event i.e., a shock, policy shift, or structural change significant enough to alter export composition, import dependence, or geographic orientation in a lasting way. The boundaries are set where at least two of the following conditions are met: a discontinuity in aggregate export growth rates; a compositional shift in the export basket exceeding three percentage points across major sectors; a significant change in the direction or magnitude of the trade balance; or a major external event (financial, geopolitical, policy or pandemic-induced) that altered the operating conditions for Indian exporters. The seven eras and their defining characteristics are presented in Table 1 in Section 4.

The segmentation is not intended to suggest that each era was internally homogeneous. Within each phase, individual sectors followed differentiated trajectories, and the analysis in Sections 4 and 5 preserves this heterogeneity.

4. Commodity Analysis

20 key chapters, out of 99 chapters, have been identified for deeper analysis, together accounting for more than 64% of merchandise exports in 2024–25 and representing distinct technological, capital, labour, and competitive characteristics. The analysis in this section combines long-run value-added patterns from TiVA data with detailed HS-level commodity information available from 2017 onwards, and is organised around questions:

1. How have aggregate trade trajectories varied across eras?
2. Which sectors have driven compositional change?
3. How stable is growth across sectors?
4. What is driving export growth — value or volume?
5. How concentrated is performance at the product level?

4.1 Aggregate Trade Performance Across Eras

The table 1 below summarises each era’s export and imports CAGR alongside the key domestic and global trade context.

Table 1 – Era-wise trade growth and economic context (1991–2025)

4.2 Key Export Pillars: Era-by-Era Compositional Shifts

India’s export composition has undergone three distinct structural transitions since liberalisation, each driven by a different combination of global conditions, domestic policy, and sector-specific factors. Table 2 presents the compositional picture across benchmark years.

Table 2 — Evolution of India’s export composition across major sectors (1991–2025)

Era I–II: Labour-Intensive Dominance (1991–2000)

In the immediate post-liberalisation period, India’s export basket was defined by three sectors: textiles and allied products (23.9% of exports in 1990–91), gems and jewellery (16.1%), and agriculture (18.5%). Together these three sectors accounted for 58.5% of merchandise exports which indicates a concentration in labour-intensive, resource-based production with limited technological capability. The sectors benefited from improved market access following WTO commitments and from India’s comparative advantage in low-cost skilled labour. However, they exhibited limited upgrading: export growth in this period was largely cost-driven rather than capability-driven, leaving the basket structurally dependent on wage competitiveness and raw material availability. The Asian Financial Crisis of 1998–99 briefly disrupted regional demand but did not alter the compositional trajectory.

Era III: The Emergence of Petroleum and Engineering (2000–08)

The high-growth boom of 2000–08 fundamentally restructured the export basket. Petroleum products, negligible at 2.9% of exports in 1990–91, grew to 17.4% by 2007–08 — a shift driven by substantial investment in refinery capacity, particularly Reliance Industries’ Jamnagar complex, which transformed India into a net refined product exporter. Simultaneously, chemicals, machinery, and pharmaceuticals each gained meaningful share, reflecting the shift in India’s domestic manufacturing base and early integration into global value chains. Textiles and gems declined sharply in relative terms (from 40% combined in 1990–91 to 24% by 2007–08) marking the first major structural transition of the post-liberalisation period. The import side of this era tells an equally important story: the 22.2% import CAGR substantially outpaced the 17.6% export CAGR, reflecting the crude oil import dependence that petroleum export expansion simultaneously created.

Era IV–V: Pharmaceuticals and Chemicals Consolidate (2008–19)

The GFC shock of 2008–09 and the subsequent stagnation reshaped the export basket further. Pharmaceuticals and chemicals consolidated their position during this period, supported by India’s established generic drug manufacturing base and growing global demand for affordable medicines. The post-GFC era also saw the early emergence of the automobile and auto-components sector as an export contributor, reflecting growing productive capacity and competitive positioning in emerging markets. Textiles and gems continued to lose relative share, increasingly exposed to wage competition from Bangladesh, Vietnam, and China. The stagnation of 2012–19, with a 1.0% export CAGR, masked sectoral divergence: pharmaceuticals grew steadily, while petroleum exports value fell sharply following the 2014–16 oil price collapse.

Era VI–VII: Electronics Exports Emerge, the Basket Shifts Again (2019–25)

The post-COVID period has produced the most rapid compositional shift: electronics exports increased from 2.7% of exports in 2018–19 to 8.8% in 2024–25. This shift is partly structural and partly policy driven. Apple’s decision to expand iPhone manufacturing in India through contract manufacturers Foxconn and Pegatron, in response to China+1 supply-chain diversification, has concentrated electronics export growth significantly. However, as the DVA analysis in Section 4.5 shows, this growth is predominantly assembly-stage integration, as the foreign value-added content of electronics exports remains high, meaning that this growth has lower domestic economic contribution.

The seven named sectors together accounted for approximately 72.6% of India’s merchandise exports in 2024-25. This indicates that a relatively small set of sectors continues to account for majority of exports, although the composition of this group has shifted away from textiles and gems & jewellery toward petroleum, electronics, machinery, and chemicals.

4.3 Consistency of Export Performance Across Sectors

Sectoral shares capture the composition of export growth but do not convey the consistency of performance over time. Table 3 presents basic descriptive statistics of export growth across major sectors to quantify differences in growth rates and their volatility.

Table 3 — Descriptive statistics of export growth across major sectors (2017-25)

The statistics reveal important differences across India’s major export sectors. Petroleum products, India’s largest export sector, recorded an average growth rate of 21%, but also showed very high volatility, with a standard deviation of 67% and a coefficient of variation of 3.27. The sector’s performance is driven largely by global crude oil prices and trade conditions rather than firm-level capabilities. Electronics, the fastest-growing sector with an average growth rate of 26%, has a much lower coefficient of variation (0.66). However, given its recent emergence and continued expansion, it may be too early to draw firm conclusions about its long-term growth volatility.

Pharmaceuticals exports are one of the most stable contributors to India’s export basket. The sector recorded an average growth rate of 9%, a standard deviation of only 6%, and a coefficient of variation of 0.67. This is consistent with a capability-based competitive advantage built on regulatory expertise, manufacturing quality, and established customer relationships.

Gems and jewellery exports recorded a negative average growth rate (-2%) along with high volatility, suggesting a longer-term decline rather than a temporary downturn. Textiles, with an average growth rate of just 1% and a coefficient of variation of 13.24, highlight the competitiveness challenges facing one of India’s traditional export sectors.

Taken together, these patterns show that export sectors differ significantly in both growth and its consistency. The resilience of India’s export basket, therefore, depends not only on the pace of growth but also on the underlying sources of competitiveness that support lower volatility.

4.4 Value versus Volume: What Is Driving Export Growth?

Aggregate export growth does not distinguish between expansion driven by physical volume and growth arising from improved realisation per unit exported. This distinction is important because volume-led growth reflects scale expansion and cost competitiveness, while value-led growth is more closely associated with product differentiation, quality upgrading, and stronger positioning within global value chains. Where value CAGR consistently exceeds volume CAGR, unit values are rising — a proxy for export quality improvement or favourable price effects. Where volume CAGR substantially exceeds value CAGR, unit realisations are declining, suggesting the sector is competing primarily on cost or processing throughput, or it is simply a commodity play.

Table 4 presents this decomposition for major export sectors using HS chapter-level data from 2017-18 to 2024–25. The analysis is limited to this window because consistent TradeStat volume data at the HS chapter level are available only from 2017 onwards.

Table 4 — Sector-wise value versus volume growth, 2017–18 to 2024–25

The sectoral decomposition reveals considerable variation in the nature of export growth. Electronics stands out as the only major sector exhibiting clear value-led growth — a 25% value CAGR against 9% volume CAGR — suggesting rising unit values consistent with product mix upgrading toward higher-value devices or assemblies. This is partially explained by the compositional shift toward smartphones within the electronics chapter, where Apple-associated assembly commands significantly higher per-unit values than earlier electronics exports. Pharmaceuticals exhibits broadly balanced growth, with volume and value CAGRs closely tracking each other, consistent with its stable and diversified product portfolio.

Petroleum products exhibit volume-led growth – 53% volume CAGR against an 8% value CAGR implies low growth in unit realisation, consistent with the sector’s position as a processing and refining exporter competing on throughput rather than on product differentiation. Automobiles and auto components show a similar pattern. Gems and jewellery and textiles both exhibit declining unit values alongside stagnant or negative volume growth a combination that signals deteriorating competitive positioning.

4.5 Product-Level Concentration Within Export Sectors

Sector-level diversification does not reveal the significant concentration, which is present at the product level. HS-based analysis at the 4-digit and 8-digit levels shows that within each major export sector, a narrow set of products accounts for a disproportionate share of export value. This within-sector concentration compounds the basket-level concentration documented in Sections 4.1 and 4.2.

Table 5  — Product concentration across major sectors, 2024–25

The concentration patterns in Table 5 are striking in several sectors. Petroleum products are dominated by three products i.e., diesel, aviation turbine fuel, and motor gasoline, which together account for 75% of the sector’s exports, effectively making the entire sector’s performance dependent on a narrow-refined product slate and the markets that import it.

In pharmaceuticals, retail medicaments account for 90% of sector exports, and within that category, the top three therapeutic categories together account for only 18% suggesting that while the sector is HS 4-digit concentrated, it retains meaningful product diversity at the 8-digit level.

Electronics is the most concentrated sector of all: smartphones alone account for approximately 55% of telephone parts (HS 8517), which in turn accounts for 59% of total electronics exports indicating a single product category is responsible for approximately one-third of all electronics export value.

The agriculture sector’s concentration in rice (98% of cereal exports, of which 47% is basmati) reflects the narrow product base that makes agricultural export value highly sensitive to bilateral trade relationships and destination-market import policies.

4.6 Domestic Value Addition, Import Dependence and GVC Positioning

The export growth achieved across these eras translates into domestic economic value in very different ways across sectors. Table 6 presents DVA and FVA shares from TiVA data, which capture what proportion of each dollar of exports reflects domestic economic activity versus imported inputs.

The DVA profile directly inverts the export share story. Agriculture, which has declined from 18% to 9% of exports, generates the highest domestic value content at 95 cents per dollar exported. Textiles, another declining sector, generates 78 cents. By contrast, petroleum products, the sector most responsible for India’s export scale growth, generates just 34 cents of domestic value per dollar exported. Electronics, the fastest-growing sector, generates 63 cents better than petroleum but still below the basket average for declining sectors.

The sectoral shifts discussed in Section 4.2 steadily increased the share of exports coming from sectors with lower domestic value content. Consequently, export growth was accompanied by a decline in the domestic value captured from that growth. In other words, the export basket became larger, but not necessarily more valuable to the domestic economy.

Table 6 tracks how DVA shares have evolved across eras for major sectors

Table 6 — Domestic value-added share across eras, 1995–2022

The era-level trajectory of DVA shares reinforces the compositional argument. Petroleum products’ DVA share fell from 74.5% in 1995 to 34.1% by 2022, tracking the expansion of crude import dependence that accompanied refinery capacity growth. Gems and jewellery’s DVA declined from 91.5% to 64.4%, as the cutting and polishing industry scaled. Textiles’ DVA declined from 97.3% to 77.9%, reflecting the sector’s increasing dependence on imported synthetic fibres and chemicals even though, it is typically characterised as a high-DVA sector.

Only machinery has shown a meaningful increase in DVA share over the period, from a low of 63.7% in 2008 to 71.8% in 2022, consistent with the maturation of India’s domestic capital goods, auto-components, and automobile manufacturing base.

This evolution suggests that export growth has increasingly relied on imported inputs, amplifying exposure to global price movements, supply disruptions, and geopolitical shocks. Some of the decline in DVA could also be due to decline in margins.

GVC positioning: Upstreamness and Downstreamness

The DVA and FVA evidence in Tables 6 and 7 captures what share of export value India retains domestically; a complementary measure captures where India sits in the architecture of global production networks. Upstreamness and downstreamness, measure, how many production stages separate a country’s exports from final consumer demand, and how many stages of upstream input processing are embodied in a country’s exports before they leave its borders, respectively. Together they locate a country’s structural position in GVCs.

A country deepening its GVC integration typically shows rising downstreamness as it absorbs more intermediate inputs into its exports, and its upstreamness may rise or fall depending on whether it is moving toward upstream component production or downstream assembly.

Table 7 presents India’s upstreamness and downstreamness at benchmark years from 1995 to 2022. The pattern is structurally flat across the entire 27-year period. India’s upstreamness has oscillated narrowly between 2.08 and 2.22 with no directional trend. Its downstreamness has been even more stable, remaining centred around 2.10. In neither dimension has India’s aggregate GVC position shifted significantly since liberalisation.

Table 7  — India’s GVC Positioning: Upstreamness and Downstreamness, 1995–2022

The available evidence does not suggest a substantial improvement in India’s aggregate position within global value chains.

The compositional transitions discussed in Section 4.2, which saw petroleum, electronics, and pharmaceuticals displace textiles and agriculture in the export basket, produced no corresponding shift in GVC positioning. This is consistent with the DVA evidence: sectors that gained export share (petroleum at 34 cents DVA per dollar; electronics at 63 cents) operate at similar or lower GVC depth than the sectors they displaced. India’s export basket moved sideways, into sectors with higher export growth but structural shallowness. The comparative analysis with countries that have actively repositioned within GVCs over the same period, are examined in Section 6.2.

Price Movement – Global Commodity markets

Rising foreign value addition in key export sectors also implies increased exposure to external price movements in global commodity markets.

Table 8 – External Commodity prices, IMF (1995 -2022)

Crude oil prices exhibit large cyclical swings, particularly during the global commodity boom of the 2000s, the post-financial-crisis period, and the post-pandemic recovery. Similarly, gold, and silver prices display pronounced upward shifts and volatility over time. For export sectors with high FVA content, such as Petroleum products and Gems & Jewellery, these price movements can materially affect export values and trade balances, even in the absence of significant changes in domestic value capture or export volumes.

5. Geographical Analysis

Section 4 documented how India’s export basket has shifted compositionally across the seven eras. In this section, we examine whether this compositional diversification was accompanied by equivalent diversification across export markets, or whether new sectors simply inherited the geographic footprint of the old ones. The evidence in this section shows that the two forms of diversification have diverged sharply. While India’s export basket became more varied across sectors, the concentration of exports in a small set of destination markets increased over the same period. The share of exports directed to India’s top eight destination countries rose from 33% in 1991–92 to 48% in 2024–25. Import sourcing, by contrast, has diversified.

5.1 Evolution of Export Destinations Across Eras

Since the early 1990s, India’s exports have remained anchored in a small set of destination markets, predominantly advanced economies. Although the share of exports directed toward emerging markets increased during the high-growth phase of 2000–08, these markets supplemented rather than displaced the core destinations. A deeper country level analysis is presented in the section 5.2. Table 9 presents the regional distribution of India’s exports across benchmark years.

Table 9 — Geographic distribution of India’s exports by major partner regions

5.2 Geographic Concentration and Market Dependence – Exports

Table 10 presents the country-level distribution of India’s exports across years for the top eight destination markets.

Table 10 — Geographic concentration of India’s export markets

The top eight country share rose from 33% in 1990–91 to 48% in 2024–25. India’s export geography became more concentrated over three decades of trade liberalisation and sectoral diversification.

The persistence of geographic concentration suggests new export sectors have not helped open new markets, i.e., they are deepening India’s dependence on the same core advanced-economy destinations.

5.3 Commodity–Geography Linkages

Export geography differs across sectors, reflecting product characteristics, buyer requirements, and regulatory frameworks rather than active market diversification strategies. Table 11 shows destination concentration by major export sector.

Table 11 — Export concentration by destination: share of top trading partners

The dominant pattern is a bifurcation between advanced-market-oriented sectors and emerging-market-oriented ones. Pharmaceuticals and electronics are heavily concentrated in the United States and the European Union, markets that offer higher prices and larger volumes but require compliance with stringent regulatory standards (For example, US FDA approval, EU CE certification). The US alone absorbs 43% of India’s pharmaceuticals exports and 42% of electronics exports. This advanced-economy orientation reflects genuine competitive positioning. But it also creates a structural problem. Policy changes or regulatory actions in a single market i.e., US FDA import alerts on Indian pharmaceuticals plants, or US trade restrictions on electronics can materially affect a large share of India’s most dynamic export sectors simultaneously.

Passenger vehicles and motorcycles show a more geographically distributed pattern across emerging markets reflecting Indian automobile’s positioning as cost-competitive suppliers to developing markets. Agriculture, particularly rice, is distributed across the Middle East and Africa at lower concentration, though as Section 4.5 noted, its near-total concentration in a single product (basmati) creates its own challenges.

5.4 Contrast with Import Diversification

The divergence between export and import geography is significant. While export market concentration has increased, import sourcing has diversified at regional level considerably across the same period. A deeper analysis at Country level is discussed in table 13 under section 5.5. Table 12 presents the regional distribution of India’s imports.

Table 12 — Geographic distribution of India’s imports by major partner regions

5.5 Geographic Concentration and Market Dependence – Imports

The top seven country share rose from 34.7% in 1990–91 to 52.5% in 2024–25. India’s import geography became increasingly concentrated despite the expansion of its global trade relationships.

Table 13— Geographic concentration of India’s Import markets

The rise in concentration was driven primarily by China and, more recently, Russia. Rather than diversifying its sources of supply, India increasingly relied on a small group of countries for a growing share of its imports. This suggests that integration into global markets has been accompanied by greater dependence on a limited number of key supplier economies, particularly for industrial inputs, capital goods, and energy products.

This divergence between import and export geography has two important implications. First, India’s import relationships have undergone a much stronger geographic reorientation than its export relationships. While imports have shifted decisively towards Asia, particularly China, exports remain heavily concentrated in OECD markets, which still account for half of India’s export basket.

Second, the growing mismatch between where India sources its imports and where it sells its exports creates distinct channels of external vulnerability. Supply-side shocks are increasingly linked to developments in Asian production networks, while demand-side shocks remain closely tied to economic conditions in OECD markets. As a result, disruptions to supply chains and changes in export demand may originate from different regions and affect the economy through separate transmission channels.

5.6 Role of Trade Agreements and Market Access

India has entered into a series of preferential trade agreements over the past two decades with ASEAN (2010), South Korea (2010), Japan (2011), and more recently the United Arab Emirates (2022) in pursuit of improved market access and export diversification. The post-agreement trade data, examined across four complementary dimensions i.e., aggregate bilateral flows, India’s market penetration in partner economies, sectoral decomposition, and the partner’s own global trade position reveals a consistent pattern.

Every agreement deepened the bilateral trade deficit. India’s share of partner import markets either stagnated or fell below pre-FTA baselines. The agreements generated asymmetric outcomes. Imports responded rapidly to tariff reduction, but exports did not.

5.6.1 Aggregate bilateral outcomes: deficits across all three partnerships

Table 15 presents India’s bilateral export and import flows with each FTA partner for reference years from 2007 to 2025, along with the resulting bilateral balance. The trajectory across all three partnerships is unambiguous.

Table 14 — India’s Bilateral Trade with FTA Partners: Exports, Imports, and Balance (USD billions)

India’s deficit with ASEAN reached USD -51.2 billion in 2025, from USD -7.2 billion in 2007. The Japan deficit widened from USD -3.2 billion to USD -14.8 billion over the same period; Korea’s from USD -3.0 billion to USD -15.1 billion.

The export cover ratio (India’s exports to a partner divided by India’s imports from the same partner), a measure of partner dependence shows a declining trend. With ASEAN, this ratio deteriorated from 0.77 in 2010 to 0.41 by 2025. With Japan, it fell from 0.58 in 2010 to 0.31 in 2024. In both cases, the pre-FTA ratio was substantially higher than the post-FTA equilibrium. It indicates that the agreements generated significantly stronger import responses than export responses.

5.6.2 Market penetration: India’s share of partner import demand has not grown

Aggregate deficit data captures the scale of trade imbalance but cannot determine whether India’s competitive position in partner markets has improved or deteriorated. Table 15 addresses this through a more precise measure. India’s share of each partner’s total imports from the world, computed across benchmark years alongside the absolute size of the partner import market and the ASEAN export cover ratio.

Table 15 — India’s Market Penetration in FTA Partner Import Markets (%; partner import market in USD billions)

ASEAN’s total merchandise import market expanded from USD 953 billion in 2010 to USD 2,095 billion in 2025. India’s exports to ASEAN during the same period grew from USD 23 billion to USD 36 billion underperforming ASEAN market growth across every sub-period. India’s share of ASEAN’s import market peaked at 2.82% in 2017, seven years after the FTA, before falling to 1.72% by 2025 below the pre-FTA baseline.

In Japan and Korea, India has never exceeded a 1% share of the partner’s import market despite fifteen years of preferential access. For context, China supplies approximately 20–25% of both Japan’s and Korea’s import requirements and Vietnam and other ASEAN members supply 4–10%. India’s share, at sub-1%, reflects the supply-side gap between Indian export capability and the composition of advanced Asian economy import demand. Preferential tariffs cannot bridge such gap.

5.6.3 Sectoral decomposition: what the deficits consist of, and what the surpluses reveal

Table 16 presents the five largest bilateral deficit sectors and the five largest surplus sectors in India’s trade with ASEAN as of 2024, together with ASEAN’s own global trade position in each chapter to examine whether India’s deficit reflects a global competitiveness reality or a specifically Indian supply failure.

Table 16 — India–ASEAN Bilateral Trade: Deficit and Surplus Sectors, USD Billion, with ASEAN’s Global Position (2025)

Three findings are of prominence. ASEAN, led by Vietnam, Malaysia, Singapore, and Thailand, runs a world surplus exceeding USD 110 billion in electrical machinery and electronics. It is among the most globally competitive export regions in this chapter. India’s bilateral deficit with ASEAN in electronics is not an India-specific problem and it reflects the broader global structure of comparative advantage.

However, this is also compounded by a domestic policy paradox. India’s PLI-supported electronics assembly ramp-up, the smartphone manufacturing expansion discussed in Section 4.2, has intensified rather than reduced import dependence on ASEAN electronics intermediates. India’s electronics imports from ASEAN rose from USD 1.9 billion in 2010 to USD 15.2 billion in 2025. The assembly-integration strategy, as described in Section 4.5, creates a structural pattern in which expanded assembly output requires expanded upstream imports, and ASEAN is the primary upstream supplier. Until Indian electronics integration progresses from assembly-stage to component-stage, PLI will continue to generate ASEAN import growth as its proximate economic effect.

Second, the palm oil deficit (HS 15, −USD 8 billion) is structurally irreversible through trade policy. India’s domestic edible oil production cannot meet consumption demand at any tariff level consistent with food security objectives, and ASEAN — principally Indonesia and Malaysia — holds a natural comparative advantage in tropical oil production that cannot be replicated.

Third, the surplus sectors in Table 16 reflect India’s comparative advantage in Asian markets. Pharmaceuticals (HS 30) stands apart as the one sector where India runs a consistent, growing, and capability-anchored surplus with ASEAN. The bilateral pharmaceuticals surplus expanded from $176 million in 2006 to USD 1.2 billion in 2025 and India’s share of ASEAN’s pharmaceuticals import market, at approximately 2.7%, exceeds India’s overall ASEAN import market share of 1.72%. This is significant because pharmaceuticals competitiveness rests on accumulated firm capabilities, regulatory expertise, and manufacturing quality standards rather than on tariff preferences. Meat (HS 02), fish (HS 03), and vehicles (HS 87) complete a surplus portfolio that is largely primary-commodity-led.

The Japan and South Korea bilateral deficits follow a different structural logic. As shown in Table 17, India’s deficit with Japan (USD -14.7 billion in 2025) is concentrated in industrial machinery (HS 84, USD -3.3 billion), specialised chemicals including inorganic compounds (HS 28, USD -2.2 billion), copper products (HS 74, USD -2.1 billion), electrical equipment (HS 85, USD -1.9 billion), and iron and steel (HS 72, USD -1.7 billion). These are sectors where Japan retains genuine technological comparative advantage and where Indian domestic production cannot substitute at equivalent specification. Notably, India’s copper deficit with Japan has grown from negligible levels in 2010 to its third-largest bilateral deficit chapter by 2025, driven by India’s expanding electronics manufacturing and renewable energy installation, both of which require high-purity copper products for which Japan is a premium global supplier. The India–Japan CEPA reduced tariffs on copper imports, facilitating the import expansion without generating the reciprocal Japanese investment in Indian copper processing that the agreement’s design anticipated.

Table 17 — India–Japan Bilateral Trade: Deficit and Surplus Sectors, USD Billion, with Japan’s Global Position (2025)

Composition of India’s deficit with Korea, as shown in Table 18, is similar in industrial structure, with electronics (HS 85) and machinery (HS 84) accounting for the dominant deficit share alongside petrochemicals and steel.

Table 18 — India– S Korea Bilateral Trade: Deficit and Surplus Sectors, USD Billion, with S Korea’s Global Position (2025)

5.6.4 Partner world trade context: a reframing of India’s bilateral deficits

A dimension absent from conventional assessments of India’s FTA outcomes is the partner’s own global trade position. Where a partner runs a large world surplus in a given HS chapter indicates it is globally competitive in that product. When such world export creates India’s bilateral deficit, it reflects comparative advantage rather than Indian market access failure. Conversely, where India runs a deficit against a partner who is itself a net global importer in the same category, the deficit signals a genuine supply-side failure. Table 19 presents this partner-world context for benchmark years.

Table 19 — Partner World Trade Balance in Context (USD billions)

Two patterns in Table 19 are noteworthy for interpreting the FTA outcomes. ASEAN’s export surge redirected substantial volume toward India’s recovering, import-absorbing economy, and India’s PLI-supported assembly activities simultaneously ramped up component imports from the same suppliers. India absorbed ASEAN’s export surplus rather than competing with it.

Japan’s world trade balance swung from a USD 75.7 billion surplus in 2010 to a USD 153 billion deficit in 2022, as energy import costs and manufacturing relocation eroded Japan’s overall export position. Despite this deterioration in Japan’s global competitiveness, India’s bilateral deficit with Japan continued to widen from USD -3.5 billion to USD -10.0 billion over the same period. Even as Japan’s aggregate export power declined, India’s structural dependence on Japanese capital goods, electronics components, and specialised chemicals deepened. The bilateral deficit with Japan, on this reading, is driven by what India cannot produce domestically.

Korea presents a parallel case. Korea’s world surplus compressed from USD 95 billion in 2017 to a deficit of USD 47.8 billion in 2022, yet its bilateral surplus with India continued to grow, as Korean industrial exporters redirected output toward India’s growing manufacturing import demand. India has increasingly become a demand sink for Korean industrial output precisely as Korean exporters sought alternative markets for displaced production.

The mechanism behind the asymmetric outcome

The sectoral and market-share evidence offers five distinct structural explanations for why India’s FTAs with ASEAN, Japan, and Korea have produced asymmetric outcomes i.e., expanding import flows without generating significant export gains.

• Supply-side mismatch: India’s export basket does not align with partner import demand. India’s highest-value export sectors i.e., petroleum products, pharmaceuticals, textiles face limited demand in ASEAN, Japan, and Korea relative to the partner’s total import mix. No tariff preference can bridge this structural gap.
• Rules of origin lock-out: India’s FTA rules of origin require high domestic value thresholds that many Indian exporters cannot meet, particularly in chemicals, and engineering goods where imported inputs constitute a significant share of production cost. Exporters default to MFN rates rather than navigating complex preferential procedures. The Asian Development Bank estimates India’s FTA utilisation rate at 5–25%.
• Non-tariff barrier persistence: Japan and Korea maintain high non-tariff barriers in agricultural products (sanitary and phytosanitary standards, labelling requirements, product approval timelines) that effectively restrict India’s agricultural export access despite tariff elimination. India’s largest actual surplus sectors with Japan (fish, apparel, oilseeds) face non-tariff compliance costs that limit volume expansion.
• Investment–trade sequencing failure: The Japan CEPA and Korea CEPA were premised on FDI inflows accompanying tariff liberalisation with the expectation that Japanese and Korean manufacturers would invest in India and generate exports. Investment has been modest relative to expectations, and where it has occurred (automotive, electronics), it has generated import-intensive assembly operations rather than capability transfers that enable export competitiveness.
• Absence of downstream reciprocity in supply chains: Unlike ASEAN–China or ASEAN–Japan supply chain integration, where bilateral trade reflects genuine production network linkages, India–ASEAN, India–Japan, and India–Korea trade remains predominantly unidirectional. India buys capital goods and intermediates. It does not participate in the production networks that would create two-way manufactured goods trade. Without this network integration, the FTA framework operates as a one-way tariff reduction rather than a bilateral trade architecture.

Taken together, the geographic evidence confirms the structural pattern established in Section 4: India has deepened its bilateral trade integration without broadening its market penetration. Geographic concentration in export markets has increased alongside sectoral diversification. FTA partnerships have deepened import dependence without generating equivalent export responses. India’s share in relatively proximate, and preferentially accessible Asian import markets i.e., ASEAN, Japan, and Korea, has stagnated or declined. The implication is that market access liberalisation without domestic supply-side development in production capability, compliance infrastructure, and rules of origin, favour import expansion over export penetration. The question of how this export engine performs under the conditions of the new normal is taken up in the following section.

6. The New Normal and Structural Challenges

The post-COVID global trade environment differs significantly from the liberalising and efficiency-driven framework that shaped India’s earlier trade eras. As a result, many of the challenges that developed during those periods have become increasingly important in determining how India’s export structure will perform under prolonged external shocks and uncertainty.

6.1 A Structurally Different Global Trade Environment

Since the late 2010s, global trade has become more restrictive. However, this shift has not operated primarily through higher tariff rates. World average applied tariffs have remained broadly stable, edging down slightly from 4.5% pre-2015 to 3.8% post-2020. Instead, the expansion of non-tariff barriers, industrial policy measures, export controls, and regulatory interventions has altered the effective conditions of market access in ways that are harder to navigate and harder to anticipate than conventional tariff barriers. Table 20 shows the scale of this changing trade environment.

Table 20 — Global trade fragmentation and restrictive measures

The count of trade-restrictive measures globally rose from an average of 389 per year pre-2015 to over 3,103 post-2020. This represents a fundamental change in the operating environment for exporters. Under a tariff-based regime, exporters can plan around known costs. Under a non-tariff barrier and discretionary policy regime, the cost of accessing a market is uncertain making export strategies that depend on stable market access conditions structurally more fragile.

For India specifically, this shift is consequential because its two most important destination markets the United States and the European Union account for 50% of exports and are also the most active users of non-tariff trade instruments. The EU’s Carbon Border Adjustment Mechanism (CBAM), being phased in through 2026, will impose carbon costs on Indian steel, aluminium, and chemical exports. US Section 301 tariffs, safeguard measures, and the growing use of national-security-linked trade restrictions create uncertainty for Indian pharmaceuticals and electronics exporters. The opacity and discretionary nature of these instruments amplify the structural challenges that arises from India’s geographic concentration in these markets.

6.2 Supply-Chain Realignment and the Limits of China+1

The reconfiguration of global supply chains following the pandemic, and intense US–China strategic competition, has created opportunities for alternative manufacturing locations to absorb production capacity shifting out of China. Whether India has captured these opportunities proportionately is a question the data addresses directly.

Comparative evidence suggests India has captured only a limited share of supply-chain reallocation relative to peers. Vietnam and Mexico have both recorded strong gains in export market share and rising manufacturing FDI, with integration occurring through deep manufacturing rather than assembly stages — generating high domestic value capture alongside export volume growth. India’s gains have been more modest and more narrowly concentrated, predominantly in electronics assembly, where PLI-linked smartphone manufacturing has driven volume growth, and in petroleum refining, where route reorientation following Russia–Ukraine provided a windfall that is contingent on geo-politics rather than capability-driven. Table 21 presents the comparative picture.

Table 21 — Supply-chain realignment and export integration: select countries

Note: DVA classifications (“High,” “Low to Medium”) are qualitative assessments based on OECD TiVA data for available countries. Vietnam and Mexico TiVA DVA shares are sourced from OECD (2022); India’s is from Section 4.6 of this paper. China’s classification reflects its comprehensive upstream-to-assembly integration across most manufacturing sectors.

India’s assembly-stage positioning in Table 21 can be explained through the upstreamness and downstreamness measures introduced in Section 4.6. Table 22 presents both metrics for China, India, the United States, Vietnam, and Mexico at reference years from 1995 to 2022. The comparative picture helps in assessing the China+1 realignment.

Table 22 — GVC Positioning Across Peer Economies: Upstreamness and Downstreamness, 1995–2022

The comparison reframes the China+1 opportunity for India. Vietnam’s rising downstreamness and upstreamness indicate that its integration into global value chains extended beyond assembly into broader manufacturing and intermediate goods production, allowing export growth to be accompanied by capability accumulation. China followed a similar upgrading path, moving into higher-value stages of production over time. India, by contrast, showed almost no change in either measure despite major shifts in its export basket. The evidence suggests that the key question was not whether India could attract export-oriented manufacturing, but whether participation in global value chains could translate into a stronger position within those chains. So far, export expansion has not been accompanied by a comparable structural repositioning.

6.3 Persistent Geopolitical Disruptions and Emerging Regulatory Risks

Geopolitical shocks have become more frequent, more overlapping, and more structurally embedded in the post-COVID period.

For India, the Russia–Ukraine conflict produced contradictory trade effects. The reorientation of global energy flows following Western sanctions enabled India to purchase Russian crude at discounted prices. This dynamic supported India’s export performance in 2022–23, but it depends on the continuation of Russia’s exclusion from Western markets, India’s willingness to absorb the geopolitical costs of this trade, and the absence of secondary sanctions pressure from Western partners. All three conditions show the exposure to external conditions.

Beyond the Russia dimension, three emerging regulatory and geopolitical risks are directly relevant to India’s concentrated export sectors.

First, US semiconductor export controls and allied technology restrictions create uncertainty for India’s electronics manufacturing ambitions. Second, US FDA import alerts, which have periodically suspended or restricted Indian pharmaceuticals plants from the US market, represent a shock that can affect sector-level exports given the high geographic concentration of pharmaceuticals sales in the US. Third, the EU’s CBAM, as noted in Section 6.1, will impose verifiable carbon costs on Indian export sectors including steel, aluminium, fertilisers, and chemicals, sectors that collectively account for a meaningful share of India’s industrial goods exports and that have not yet undergone the decarbonisation investments needed to compete under a carbon-cost regime.

The common theme across these risks is that they originate in destination-market policy decisions, not in Indian supply-side failures, and they are, therefore, not addressable through domestic competitiveness improvements alone. This makes India’s geographic concentration in a small number of advanced-economy markets not merely a diversification concern but a structural risk.

6.4 Stress on India’s Dual Export Structure

As introduced in Section 3.1, India’s export basket operates across two different segments: capital- and technology-intensive exports on one side, and labour- and land-intensive exports on the other.

Capital- and technology-intensive exports i.e., petroleum products, electronics, and pharmaceuticals are predominantly oriented toward advanced economies and deliver the majority of India’s headline export scale. But as the DVA analysis in Section 4.6 showed, their domestic value capture varies enormously: pharmaceuticals at 69%, electronics at 63%, and petroleum at 34%.

Labour- and land-intensive exports i.e., textiles, garments, gems and jewellery, and agriculture exhibit higher average domestic value capture but face a separate set of stresses. Despite domestic value addition averaging 79% across these sectors, they have been systematically losing export share. Textiles face sustained wage competition from Bangladesh, Vietnam, and Ethiopia.

The implication is that India’s two export segments are not complementary. They are both simultaneously under stress, through different channels. Table 23 documents the primary stress channels by sector.

Table 23  — Sectoral exposure to external shocks under the new normal

6.5 Export Growth Strategy Under Structural Fragmentation

The four export growth strategies introduced in Section 3.1, i.e., price-and-route arbitrage, assembly-integration, capability-anchored, and cost-compression helps understanding how India’s different export segments will perform under conditions of structural fragmentation. Table 24 elaborates each strategy’s defining features, typical sectors, and primary outcome drivers.

Table 24 — Export Growth Strategies and drivers under the new normal

The price-and-route arbitrage strategy, exemplified by petroleum products, is inherently the most fragile under the new normal. Export performance in this strategy is primarily a function of global commodity prices and trade route availability, both of which are determined externally and are subject to rapid reversal. The Russia–Ukraine petroleum windfall produced export scale gains in 2022–23 that are contingent and are already partially reversing in the 2023–25 new normal data, as the 0.10% export CAGR reflects.

The assembly-integration strategy, currently defining India’s electronics trajectory, offers higher durability than arbitrage-led integration but remains structurally mobile. The policy question for India’s electronics sector is whether PLI-linked investment will progress from assembly-stage to component-stage and then to design-stage integration i.e., a functional upgrading trajectory that Vietnam has partially achieved in certain electronics sub-sectors. Without this progression, India’s electronics export growth remains contingent on buyer-firm diversification decisions that can be reversed or redirected to alternative assembly locations.

The capability-anchored strategy, best represented by pharmaceuticals and, automotive components and automobile products, is the most resilient of the four. Competitive position in this strategy rests on accumulated firm capabilities, regulatory expertise, supplier network depth, and established buyer relationships, all of which are slow to build and slow to displace. This strategy’s primary risk under the new normal is the increasing application of destination-market regulatory risk, as discussed in Section 6.3. But this is a different kind of risk than commodity price or Global Value Chain mobility risk, and it is in principle addressable through firm-level and industry-level investment.

The cost-compression strategy, represented by textiles, garments, and gems, faces the most structurally unfavourable combination: falling export share, intensifying cost competition, and limited policy levers available at the national level. Wage competitiveness can only partially be manufactured by policy. It requires underlying productivity improvements that are slow to materialise and difficult to sustain against peers with lower absolute wage floors.

The overall picture that emerges is that India’s export basket is disproportionately weighted toward the two relatively fragile strategies, i.e., arbitrage and assembly and less toward the two more durable ones i.e., capability-anchored and, potentially, a revitalised cost-compression strategy anchored in productivity rather than wage competition alone. Addressing this imbalance is the challenge for India’s trade architecture in the new normal.

7. Conclusion

This paper argues that India’s export expansion has delivered substantial scale without comparable deepening. While exports expanded rapidly, the evidence suggests more limited progress in domestic value capture, diversification, capability accumulation, and repositioning within global value chains.

The era-based analysis shows that shifts in export composition and market orientation have not been accompanied by broad-based diversification across products, destinations, or value chains. Instead, export growth has become progressively concentrated in a narrow set of sectors and markets, many of which exhibit high import dependence and limited domestic value capture.

Under the current “New Normal” of trade fragmentation, this structural configuration becomes particularly important. Sectors that drive export scale, such as petroleum products and electronics, operate largely through price- or assembly-led integration into global value chains and are therefore highly sensitive to external shocks, regulatory changes, and supply-chain disruptions.

At the same time, sectors with higher DVA, including Textiles, Gems & Jewellery, and Agriculture, face intensifying cost competition, and stagnant market access. The coexistence of these distinct export strategies implies that aggregate export growth no longer provides a reliable signal of underlying competitiveness or economic robustness.

The findings also suggest that India’s limited gains from supply-chain realignment and trade agreements are not primarily the result of insufficient market access, but rather of the nature of domestic production and firm-level integration into global value chains. CEPAs / FTAs have expanded trade volumes, yet they have not materially altered export geography or improved trade balances. Similarly, participation in China+1 supply-chain shifts has increased export throughput without generating proportional increases in domestic value capture or functional upgrading.

For businesses, these results underscore the limits of export strategies centred on assembly, processing, or price arbitrage alone. Export growth that is not supported by deeper domestic supplier networks, process capabilities, and product differentiation remains exposed to sudden reversals driven by external policy or geopolitical shocks. Firms that anchor competitiveness in higher domestic value addition and regulatory adaptability are likely to be better positioned under conditions of persistent trade uncertainty.

From a policy perspective, the analysis implies that export performance should be evaluated less in terms of aggregate growth targets and more in terms of resilience, value capture, and structural diversification. Industrial and trade policies that prioritise downstream assembly or scale expansion without strengthening upstream manufacturing depth risk reinforcing the very vulnerabilities exposed by the New Normal. A trade strategy oriented toward capability building, rather than market access alone, is more likely to sustain export performance in an increasingly fragmented global economy.

In short, India’s export outcomes are increasingly shaped by external contingencies rather than internal capabilities. India needs to focus on driving export growth through increasing DVA shares, product diversification into more complex products, and reduced geographic concentration, particularly in high-growth sectors. Without such shifts, export expansion is likely to remain cyclical, externally driven, and structurally fragile. Subsequent research will examine how firm-level behaviour, industrial ecosystems, and policy design interact to determine whether India’s trade structure and performance can transition from scale-driven integration to capability-led competitiveness.

Note: Generative AI tools were used in a developmental editing role during revision of this article. The author remains responsible for all ideas, interpretations, examples, and final content.

[1] The paper has benefited from Prof. Anil K Sood’s guidance in formulating the research problem and approach to analysis.

[2] Upstreamness of a country/sector measures the distance of its productions from the final demand. Far from final use indicate High Upstreamness. Antràs et al. (2012), Measuring the Upstreamness of Production and Trade Flows, American Economic Review Papers & Proceedings 102(3): 412-416.

[3] Downstreamness of a country/sector measures the distance from the factors of production (sources of value-added). Far from the source of value-added indicate High Downstreamness. Antràs, P., and Chor, D. (2013), Organizing the Global Value Chain, Econometrica 81(6): 2127-2204

[4] Exports and Imports of Merchandise trade, Direction of Foreign Trade (Table 135, Direction of Foreign Trade – US Dollar, Handbook of Statistics on Indian Economy, RBI)

[5]  China represents China + Hong Kong

[6] disintegration of the Soviet Union and the COMECON trade bloc

[7] Year of FTA entry into force. ASEAN: 2010; Japan: 2011; Korea: 2010.