Inflation-adjusted sectoral contributions to economic growth in India: A historical and policy-oriented analysis (1954-2023)

Introduction

India's economic development since independence reflects a major shift from an agrarian foundation to a diversified, multi-sector economy. Over time, policy reforms, technological progress, and deeper global integration have reshaped the composition of Gross Domestic Product, redefining the roles of agriculture, manufacturing, trade, finance, and public services (Rodrik, 2016; Dasgupta & Singh, 2005) [12,5] . Assessing these sectoral shifts through inflation-adjusted measures has become essential for understanding real economic progress and long-term structural change (Barro, 1995) [11] . In the period immediately after Independence, India's economy leaned heavily on farming. Most of the national output came from agriculture, and government programmes were mainly directed at stabilising food supplies and improving the rural economy. Although the Green Revolution altered production patterns quite dramatically (Sasmal, 2015; World Bank, 2018) [14,16] , the system could not keep pace with the combination of rising population and expanding urban centres. Over time this imbalance pushed policy makers to think beyond an agriculture-led structure and consider a broader industrial base (Goldar & Das, 2023) [8] . A more noticeable transition appeared during the 1980s and later in the reform decade of the 1990s. The licence-permit framework, which had shaped economic activity for years, gradually became a constraint on growth (Rodrik & Subramanian, 2005) [13] . When the 1991 balance-of-payments crisis unfolded, the government had little option but to revise long-standing rules. The resulting reforms opened domestic markets, invited foreign investment, and eased restrictions on industrial activity (Bajpai, 2002; Baumol, 1990) [10,3] . These changes encouraged new investment, and export-related manufacturing gradually secured a more substantial place in the economy (Chakravarty & Mitra, 2009) [4] . From the early 2000s, the centre of gravity shifted again-this time toward the services sector. The rise of IT and related services linked India with global production networks, largely because firms were able to draw on a reasonably skilled workforce and improving digital facilities (Dasgupta & Singh, 2005; Krishna & Das, 2016; Abbas et al., 2023) [5,9,1] . Around the same time, newer digital technologies, including AI, machine learning and IoT applications, started influencing not only advanced manufacturing but also more traditional areas. A familiar example is agriculture, where precisionbased tools began to support better crop management (Vaghela & Patel, 2018) [15] . The pandemic disrupted these patterns abruptly. Supply chains faltered, and routine business operations slowed, reminding policymakers of the importance of digital infrastructure and resilient production systems (Balakrishnan & Parameswaran, 2022; World Bank, 2020) [2,18] . Initiatives such as Digital India and Atmanirbhar Bharat were framed partly in response to these weaknesses, and they became particularly relevant in an environment of fluctuating prices where inflation-adjusted analysis turned essential (Das et al., 2019) [6] . In recent www.extensionjournal.com years, environmental concerns have become more prominent. Rapid industrial and urban expansion has created pressures on land, water and energy resources. This has led to increasing interest in cleaner energy, greener industrial processes and technologies that reduce ecological harm (World Bank, 2019; Krishna & Das, 2016) [17,9] . The spread of renewable energy projects, electric-mobility initiatives and circular-economy practices are a few visible outcomes of this shift (Das et al., 2019; Vaghela & Patel, 2018) [6,15] . Against this evolving backdrop, analysing sectoral performance in inflation-adjusted terms helps in understanding the real direction and pace of structural change (Barro, 1995; Balakrishnan & Parameswaran, 2022) [11,2] . This study examines the inflation-adjusted contributions of major sectors to India's economic growth from 1954 to 2023 using a robust econometric framework. The findings offer insights into the pace and drivers of structural change and help inform policy strategies as India advances into an era defined by digital innovation, sustainability, and deeper global integration (Das et al., 2019; Rodrik, 2016) [6,12] .

Literature Review

Understanding inflation-adjusted sectoral contributions is central to analyzing long-term economic development, particularly for an economy undergoing rapid transformation such as India. Foundational theories by Lewis (1954) and Kuznets (1955) provide an early framework for explaining structural change, highlighting the gradual decline of agriculture and the rising role of industry and services as economies develop. Lewis emphasized the movement of surplus labor from agriculture to industry, while Kuznets pointed to organizational shifts that accompany economic progress. Our findings align with these theories but reveal important nuances, particularly the accelerated decline of agriculture after the 1990s reforms and the unusually rapid rise of services, which in some instances bypassed manufacturing-an evolution also noted by Rodrik (2016) [12] . Accurate measurement of sectoral contributions requires inflation adjustment, especially in long-term analyses where price levels vary widely. The use of GDP deflators or CPI-based adjustments is necessary to distinguish real economic change from nominal distortions. Barro (1995) [11] underscores the negative impact of inflation on growth, noting its tendency to reduce macroeconomic stability and investment. Building on this insight, our study applies inflation-adjusted analysis across nearly seven decades to capture the true performance of India's major sectors. This is particularly relevant for periods of high volatility, such as after the 2008 global financial crisis, when real manufacturing output contracted more sharply than nominal figures suggested. Balakrishnan and Parameswaran (2022) [2] further highlight how fluctuations in food and commodity prices shape India's inflation patterns, reinforcing the need for inflation-adjusted sectoral analysis. Our findings extend this literature by providing year-by-year estimates that reveal the declining real share of agriculture and the rising significance of manufacturing and services. India's structural transformation has been extensively documented, showing a long-term shift from agriculture to industry and services. In the 1950s, agriculture accounted for more than half of national output; today, it contributes less than 15%. Early reforms, such as the Green Revolution, improved agricultural productivity but could not prevent the eventual decline of agriculture's GDP share (Dasgupta & Singh, 2005; World Bank, 2018) [5,16] . The 1991 liberalization marked a decisive shift, accelerating globalization and promoting investment in manufacturing and services. Yet, as several scholars note, India's path has differed from classic industrialization patterns. Manufacturing has grown inconsistently, while services-particularly IT and digital activities-have emerged as the dominant driver of growth. Our study confirms this pattern but finds that the transition has been uneven, with agriculture still playing a vital role in employment and income generation despite its declining output share. These structural changes carry significant policy implications. Rodrik (2016) [12] warns of premature deindustrialization in developing economies, including India, where manufacturing has stagnated earlier than expected. At the same time, inflation dynamics-driven largely by food prices, according to Balakrishnan and Parameswaran (2022) [2] -suggest that agricultural supplyside reforms remain essential. Our findings indicate that service-led growth has been concentrated. This suggests the need for policies that expand digital infrastructure, strengthen manufacturing capabilities, and support technology adoption in agriculture. The differentiated impact of inflation across sectors also highlights hidden vulnerabilities: agriculture is often under pressure despite its relatively small weight in inflation calculations, underscoring the need for integrated policy interventions. Recent trends in sustainability further shape the evolving literature. India's commitment to renewable energy, green manufacturing, and resource-efficient production reflects a shift toward a low-carbon growth model (Vaghela & Patel, 2018; Dasgupta & Singh, 2005) [15,5] . Our findings show early signs of this transition, with increasing adoption of renewable technologies and precision farming practices. However, challenges remain, including high capital costs and potential job losses in traditional industries. Balancing economic growth with environmental responsibility will require coordinated policies that integrate sustainability across sectors. Overall, existing research offers substantial insights into structural transformation, but gaps remain. Many studies emphasize historical patterns and theoretical frameworks but provide limited empirical evidence on how recent technological advances and policy interventions are reshaping sectoral growth. There is also limited research on the sectoral implications of the green economy, despite India's growing emphasis on sustainability. Future work should explore the long-term effects of digitalization, environmental policies, and technological innovation on sectoral contributions. Additionally, while inflation adjustment is widely recognized as essential, standardized methods are lacking. Our research underscores the need for more refined, sector-specific inflation models to improve the accuracy of long-term economic analysis.

Methodology

This study examines India's economic growth from 1954 to 2023 using a comprehensive, multi-step methodological framework designed to ensure analytical precision and reliability. The approach integrates systematic data collection, rigorous preprocessing, and advanced econometric analysis to capture the inflation-adjusted contributions of major economic sectors to long-term GDP performance. The dataset was compiled from reputable national and international sources to ensure extensive coverage across nearly seven decades. Sectoral Gross Value www.extensionjournal.com Added (GVA) at current and constant prices was obtained from the National Accounts Statistics (NAS) published by the Central Statistics Office. Additional macroeconomic indicators and GDP deflator data were derived from the Reserve Bank of India's statistical databases. To adjust nominal values for inflation, Consumer Price Index (CPI) data from the Ministry of Statistics and Programme Implementation were used. Collectively, these sources provided accurate and consistent measurements of sectoral performance across agriculture, manufacturing, trade, financial services, and public services. To generate inflation-adjusted sectoral data, nominal GVA values were converted to real terms using CPI and GDP deflators, with 2011-12 selected as the base year in accordance with national accounting standards. Each sector's nominal series was deflated to ensure that comparisons across periods reflect real economic contributions rather than price-level changes. This step was critical given India's historically volatile inflation patterns and the long duration of the study. The empirical analysis relied on time-series econometric modeling to evaluate the relationship between sectoral growth rates and aggregate GDP growth. A multiple regression framework was employed, with GDP growth as the dependent variable and the growth rates of agriculture, manufacturing, trade, financial services, and public services as independent variables. The model took the form: Where  is the GDP growth rate at time t.  , , , , and represent the growth rates of the agriculture, manufacturing, trade, financial services, and public services sectors respectively.  is the intercept term.  is the error term.

Analytical procedures began with summary statistics to understand the distributional properties of all variables, including means, standard deviations, and value ranges. This provided initial insights into the patterns and dispersion of sectoral growth over time. Regression analysis was conducted using ordinary least squares (OLS), complemented by robust standard errors to correct for potential heteroskedasticity. Multicollinearity among explanatory variables was evaluated using the Variance Inflation Factor (VIF). All VIF values were comfortably below the conventional threshold of 10, indicating an absence of significant multicollinearity concerns. To validate the robustness of the model, several diagnostic tests were performed. Residual analysis assessed normality and homoscedasticity through residual-fitted plots, histograms, and Q-Q plots. Autocorrelation was examined using the Durbin-Watson statistic; values near 2.0 indicated minimal serial correlation. Given the long-time span of the dataset, unit root tests such as the Augmented Dickey-Fuller test were applied to verify the stationarity of each series. When necessary, non-stationary variables were differenced to satisfy the assumptions of time-series regression. Graphical analysis complemented the statistical procedures. Trend lines were plotted to visualize long-term movements in GDP and sectoral contributions, highlighting periods of convergence or divergence among sectors. Scatter plots were used to illustrate the strength and direction of relationships between sectoral growth and overall GDP growth, helping identify non-linear patterns and potential outliers. Despite its rigorous design, the methodology is subject to certain limitations. The reliability of findings inevitably depends on the accuracy of the underlying data, which may be affected by revisions or inconsistencies in official sources. Additionally, the regression model does not explicitly incorporate structural breaks, such as major policy shifts, global crises, or technological disruptions, which could influence sectoral dynamics. Nonetheless, the methodological framework adopted here provides a strong basis for analyzing long-term, inflation-adjusted sectoral contributions to India's economic development and offers valuable insights for both researchers and policymakers.

Results

This section presents the conclusions of the study, analyzing the inflation-adjusted sectoral contributions to India's economic growth from 1954 to 2023. The results are organized into several subsections: summary statistics, regression analysis, diagnostic tests, and sectoral trends over distinct historical periods. Each subsection is designed to provide a comprehensive understanding of the dynamics that have shaped India's economic structure over the past seven decades.

Summary Statistics: Table 1 presents the summary statistics for the key variables analyzed in this study: sectoral Gross Value Added (GVA) in agriculture, manufacturing, trade, financial services, and public services, as well as overall GDP. The data cover the period from 1954 to 2023, with all values adjusted for inflation using the GDP price deflator. The summary statistics reveal the substantial variation in sectoral contributions over time, with manufacturing and services (trade, financial, and public) showing significant growth, particularly from the 1990s onwards. Agriculture, once the dominant sector, shows a steady decline in its relative contribution to GDP.

Regression Analysis:

The regression analysis was conducted to determine the impact of sectoral growth rates on overall GDP growth, using a time-series regression model. The outcomes are presented in Table 2, showing the coefficients for each sector's growth rate, along with their statistical significance. The regression analysis indicates that all sectors positively contribute to GDP growth, with agriculture showing the highest coefficient, followed closely by trade and manufacturing. The adjusted R-squared of 0.9546 suggests that the model explains a significant portion of the variance in GDP growth. Notably, the coefficients for manufacturing and trade are particularly strong, reflecting their crucial roles in driving economic expansion, especially in the postliberalization period.

 Diagnostic Tests: Several diagnostic tests were conducted to validate the regression model and ensure the robustness of the results.  Residual Analysis: The residuals were examined to assess normality and homoscedasticity.

Sectoral Trends over Historical Periods

This analysis reviews sectoral contributions across four major historical phases of India's economic development.

1954-1970: Post-Independence Industrialization

Agriculture dominated the economy, contributing nearly half of GDP. Early industrialization emerged through stateled policies promoting heavy industries and self-sufficiency.

Manufacturing remained small but began gaining traction under public-sector-driven initiatives.

1971-1990: Economic Liberalization and Diversification

The late 1970s and 1980s marked growing diversification. Manufacturing, trade, and financial services expanded gradually, driven by early liberalization efforts. Agriculture's share fell to about 30-40%, while trade and finance grew steadily as India moved toward a more open economic structure.

1991-2010: Globalization and the IT Revolution

The 1991 reforms triggered rapid structural transformation. Liberalized trade, investment inflows, and financial market reforms led to strong growth in manufacturing and services, particularly IT and IT-enabled services. Agriculture's contribution declined to around 20-30%, while services emerged as the dominant growth driver. Global integration strengthened the trade sector, with exports becoming increasingly important.

2011-2023: Recent Developments

Manufacturing, trade, and public services expanded further through initiatives such as "Make in India" and rising digitalization. The COVID-19 pandemic disrupted activity in all sectors, but manufacturing maintained a contribution of roughly 25-30%, trade about 20-25%, and financial services continued to grow despite digital competition. Public services strengthened due to higher spending on health and infrastructure. Agriculture's share fell below 15%, indicating ongoing structural transformation despite its importance for rural livelihoods.

Yearly Sectoral Analysis and Graphical Trends

To provide a clearer understanding of sectoral contributions over time, yearly data were analyzed and presented graphically in Figure 2. www.extensionjournal.com  1971-1990: GDP growth began to diverge from agriculture as diversification increased.

 1991-2010: The gap widened sharply due to rapid growth in manufacturing and services.

 2011-2023: The divergence stabilized, with agriculture contributing progressively less relative to overall growth.

These patterns confirm India's long-term structural shift toward industry and services. They also underscore the need to modernize agriculture and integrate it more effectively with high-value sectors to support inclusive development.

Sectoral Involvement in Economic Volatility

A volatility assessment using the standard deviation of GDP growth rates reveals:

Discussion

This study analyzes inflation-adjusted contributions of agriculture, manufacturing, trade, finance, and public services to India's GDP from 1954-2023. The sectoral evolution reveals strong complementarities and highlights the importance of policy support.

 Agriculture: Once the core of the economy, its relative importance has declined as other sectors expanded more rapidly. Yet it remains vital for food security and rural livelihoods.

 Manufacturing: Expanded significantly after 1991 due to deregulation, private investment, and export orientation. Sustaining productivity and technological upgrading remains essential.

 Trade: Benefited from global integration, reflecting India's increasing participation in world markets. Improved logistics and trade facilitation are crucial for future growth.

 Financial Services: Expanded with reforms and digital innovation, improving access to credit and payments.

Regulatory strengthening remains important.

 Public Services: Gained prominence due to increased investments in health, education, and infrastructure, essential for human development and regional equity.

Sectoral Shifts and Economic Implications

The analysis reveals a clear structural transformation in India's economy, characterized by a shift from agriculture to manufacturing and services. This transformation reflects broader economic trends observed in many developing countries as they industrialize and modernize. The declining share of agriculture in GDP and the increasing importance of manufacturing and services highlight the need for policy interventions that support this transition while addressing the challenges faced by agriculture and other sectors. The divergence between GDP growth and agriculture growth over time emphasizes the need for a balanced approach to economic development. While industrial and service sectors have driven growth, agriculture remains a critical component of the economy, particularly for rural livelihoods and food security.

Policies should focus on modernizing agriculture through technology and infrastructure investments, while also promoting the progress of other sectors to confirm a wellrounded and resilient economy.

Policy Implications and Recommendations

 Agriculture Modernization: Given agriculture's declining relative contribution to GDP, there is a pressing need to invest in technology and infrastructure to boost productivity.

Modernizing agricultural practices, improving irrigation systems, and enhancing market access can help stabilize agriculture's contribution and support rural development. Additionally, integrating agriculture with other sectors, such as agro-processing and agribusiness, can create value-added opportunities and strengthen its role in the economy.  Manufacturing Expansion: To sustain the growth of the manufacturing sector, policies should focus on diversifying within the industry, promoting high-value and technology-intensive sectors. Employing an approach that focuses on the support of research and development activities and the development of innovation as well as the enhancement of industrial structure is critical for sustaining competitiveness in the marketplace. The same policies must be designed to also tackle the low productivity of labor as well as the low-level skills of the labor force so that they can fit the demands of industries.  Trade Facilitation: To strengthen trade practices, it is important to also strengthen trade facilitation infrastructure www.extensionjournal.com and policies, as well for the growing trade sector. Investments in the logistics industry, the ports sector, and other trade facilitation measures can improve the global competitiveness of India. Proposals focusing on trade policy should also seek to foster a balanced export-import interaction to effectively deal with trade deficits and aid in protecting local industries against unfair competition.  Financial Services Innovation: In relations of economic growth, financial inclusion that utilizes digital banking and the services of fintech innovators is powerful. Policies must be designed to encourage and facilitate the development of digitally based financial services whilst reinforcing the legal frameworks and upholding equitable opportunities for everyone to access financial products. Furthermore, dealing with financial instability as well as effective of the financial system is also quite important in upholding the strength of the financial sector.  Public Services Investment: To develop human capital and sustain economic growth, enhanced investments in the public services sector are of utmost importance. Improving healthcare services as well as education and the building of infrastructure can enhance the living standards of the population and reduce the problem of social inequalities.

Upcoming Research Directions

Upcoming research could discover the impression of specific policy interventions on sectoral growth, providing deeper insights into effective economic planning. The contribution made by sectors concerning the impact of emerging technologies, digitalization processes, and global economic trends may offer a better understanding of forming economic strategy in the future. One more opinion that can explain the processes occurring in the economy is the interdependence of sectoral growth with the other factors of the economy; e.g., employment and income distribution throughout the economy. As a summary of certain conclusions of this research, the analysis of the sectorial composition of GDP and its determinants over time and concerning the level of inflation should be the focus. Addressing specifically the changing sectoral composition and their implication, there is a requirement for more specific strategies that will be geared towards creating incentives for growth and mitigating the constraints faced by targeted sectors. Policymakers can use past experiences to plan policies that will balance current imbalances and work towards long-term sustainable development.

Conclusion

The results of this study highlight the profound changes in the sectoral composition of India's GDP over the past seven decades. The inflation-adjusted analysis reveals the critical roles played by manufacturing and services in driving economic growth, mainly in the post-liberalization era. At the same time, the declining share of agriculture underscores the ongoing structural transformation of the economy. These conclusions have significant implications for policymakers, who must navigate the challenges of maintaining balanced growth while addressing the needs of sectors that are vital for rural livelihoods and overall economic stability.

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