This paper investigates the role of neighbourhood effects in shaping the spatial concentration of manufacturing and service establishments across Indian districts, using unit-level data from the 2013–14 Economic Census. We apply the spatially weighted Ellison–Glaeser index (EGSPAT) developed by Guimarães et al. (2011) to account for inter-district spillovers in measuring industrial agglomeration. At the national level, incorporating spatial dependence does not significantly alter concentration patterns: highly agglomerated industries remain confined to a small number of districts, with limited spillovers to neighbouring areas. In contrast, state-level analysis for India’s three largest employment states—Maharashtra, Uttar Pradesh, and West Bengal—reveals substantial neighbourhood effects. The EGSPAT estimates exceed the standard Ellison–Glaeser index by 8–23 per cent, and districts with excess employment exhibit clear spatial contiguity. These findings highlight the importance of geographic scale in identifying agglomeration dynamics, as national-level measures mask significant within-state spatial dependence. The paper contributes novel evidence for India that spatial spillovers in industrial concentration are primarily a subnational phenomenon, and it underscores the policy relevance of state-level industrial strategies in leveraging localised agglomeration economies.
This paper analyzes the structure of inequality of opportunity in early child health in India using a nationally representative dataset. We use three anthropometric Z-scores which serve as indicators for tracking the progress of countries towards the Sustainable Development Goals. Using a novel Machine Learning algorithm that uses hypothesis tests to partition the data, we uncover granular opportunity structures for three commonly used anthropometric Z-scores as a complex interaction across multiple socio-economic, demographic and behavioral characteristics. We find that the most important circumstances determining inequality of opportunity in child health are household wealth, religion, region, maternal education, and household sanitation practices. We also find that the indicator measuring long run child health displays higher inequality of opportunity relative to indicators capturing short run child health. The results have implications for the creation of targeted social safety net policies.
The disintegration and diffusion of production process across the world, termed as Global Value Chains (GVCs), has enabled various developing countries to participate in world trade. In this scenario, India, with its abundant labour and manufacturing capability has the potential to become a key player in international commerce. The current study based on Koopman et al.’s (2010, 2014) disintegration of gross exports into several value-added components, attempts to assess their individual impacts on labour productivity of India, and determine the importance of GVC networks towards boosting the country’s growth prospects. Panel Vector Autoregression (PVAR) approach is used to analyse annual data from 16 manufacturing industries for the period 2001–2019. The corresponding Orthogonalized-Impulse-Response-Functions (OIRFs) display short-run effects of FVA, while the aggregate DVA fails to impact labour productivity significantly. The OIRFs further document fluctuating effects of shocks to DVA in final and intermediate exports absorbed by direct importers, which persist for some time. The effects of DVA in intermediate exports re-exported to third countries and those returning home, are short lived. The Forecast-Error-Variance-Decomposition (FEVDs) in line with the OIRF plots, identify the DVA in intermediate exports absorbed by direct importers, to explain the maximum variation in labour productivity. The study contributes to the existing literature by identifying that GVCs, in its different stages of production integration, can have differing impacts on the economy. Therefore, analysing GVCs in aggregate may not permit targeted policy formulation for utmost benefit of an economy.
Trade boosts productivity; hence, decomposing aggregate productivity based on major trade theories is essential to understanding the relative significance of each channel on productivity-led growth and its effects on living standards and real income of the nations. This paper uses the most recent control function estimation approaches to provide a more consistent and efficient estimate of the Indian manufacturing firms’ Total Factor Productivity (TFP). Then, the article decomposes aggregate productivity loss of India’s manufacturing due to the decline in trading activities into the inter-industry effect, the technology effect, the continuing-firm effect, and “the joint effects of entering and exiting firms”. When India actively participates in trade, the primary drivers of increased aggregate productivity in the manufacturing sector are the technology and intra-industry effects, with the inter-industry effect contributing by around 24
Based on a welfare-maximization model of skilled migration where education generates a positive externality, I examine whether the early view regarding brain drain’s (BD) negative impact on source countries – and its associated Bhagwati tax ( t ) – is compatible with the recent more optimistic BD-induced brain gain view. I derive BD’s impact on education and welfare, the optimal education subsidy ( s ), and a combination of s and t , when residents’ (emigrants’) weight in the government’s objective function is ( 1-β ), where β ∈ (0, 1) . I find that: i) education, welfare and s are higher (lower) under an open than under a closed economy for 1-β larger (smaller) than the ratio of source-country to host-country income; ii) s and t are policy complements, i.e., given the model’s parameters (such as β ), the impact of an increase in s is also obtainable with an increase in t ; and iii) s ( t ) increases (declines) with 1-β . Two implications and a proposal are: a) The early literature, where t was considered, abstracted from migrants’ welfare (i.e., the 1-β =0 case), which is precisely the case where optimal tax t is largest; b) A second policy instrument is beneficial especially when constraints exist on changes in the other one. Assuming a low emigrants’ value for the government, opening up the economy implies a lower education subsidy, so raising the Bhagwati tax t should be beneficial if, as is typically the case, education is viewed as a right and parents’ and teachers’ organizations as well as the education ministry and bureaucracy make it politically difficult if not impossible to reduce the education subsidy; c) Proposals for collecting the Bhagwati tax is presented.
India’s energy system remains structurally dependent on coal, which continues to account for a dominant share of electricity generation, even as the country has committed to expanding non-fossil energy capacity and reducing the emissions intensity of income. Various fiscal and policy instruments within India, such as the taxation on coal, the phased withdrawal of petrol and diesel price subsidies, and policy support for renewable energy and energy efficiency, target energy use and fuel choice. The paper analyzes the long-run effects of these policies on the shares of fossil fuels within India’s energy structure from 1971 to 2024. Annual time series data is used for different economic and energy variables. The autoregressive distributive lag model is applied to reveal short-run and long-run relationships among variables. Findings show the existence of a non-linear relation between GDP and fossil fuel demand; however, the relation is of an inverted U-shaped pattern. Higher domestic petrol prices, the coal tax, and the times after the Paris Agreement contribute toward lower long-run shares of fossil fuels. Higher coal prices and higher imported coal quantities, however, result in higher fixed shares of fossil fuels. The findings show that fiscal and pricing policies have some but not very significant effects on India’s long-run energy structure change. The findings indicate that even modest carbon-related taxes and subsidy reforms can help reduce fossil fuel reliance in a coal-dependent emerging economy, but that stronger fiscal signals and faster improvements in energy efficiency are necessary to align India’s energy transition with its climate objectives.
This paper uses a detailed input–output (Leontief) price model to quantify the inflationary effects of imposing a carbon tax on the Indian economy. By mapping primary fuel consumption (coal, crude petroleum, natural gas) to I-O sectors and applying fuel-specific emission factors, the analysis traces how tax-induced cost shocks propagate through supply chains to producers’ prices and, ultimately, to the Consumer Price Index. Results show a highly heterogeneous sectoral impact: electricity generation, coke and refined petroleum and basic metals register the largest price increases, while most service sectors see only modest effects. At the aggregate level, the simulated carbon tax raises CPI by roughly 0.6 - 4.1 per cent for carbon prices in the range US10–100 per ton CO₂. Scenario analysis that allows for incomplete pass-through and modest fuel-switching substantially reduces these upper-bound estimates.
In an era when the transition to green energy is central to sustainable development strategies, understanding how foreign direct investment (FDI) and trade openness shape renewable energy development in Southern Africa is crucial. This study examines long-run relationships among FDI, trade openness, and renewable energy development in the Southern African Development Community (SADC) from 1990 to 2021. Using fully modified ordinary least squares (FMOLS) and method of moments quantile regression (MM-QR), the analysis moves beyond linear effects to capture nonlinear dynamics and distributional heterogeneity across levels of renewable energy development. The FMOLS results confirm a stable long-run relationship, showing that both FDI and trade openness positively contribute to renewable energy development. However, the nonlinear estimates reveal that these effects are conditional rather than uniform. FDI exhibits an inverted U-shaped relationship with renewable energy, indicating diminishing marginal returns beyond a certain level, while trade openness follows a U-shaped pattern, with renewable energy benefits materializing only at higher levels of trade integration. The MM-QR results show substantial heterogeneity: FDI has a high impact at the lower quantile, whereas trade openness has larger effects at the higher quantile. The findings suggest that FDI and trade openness can support a sustainable growth path in SADC, but their effectiveness depends on domestic conditions, trade composition, and strategic policy design. Policy implications emphasize prioritizing green-oriented FDI, aligning trade policy with clean energy objectives, and strengthening institutional and infrastructural capacity to maximize renewable energy outcomes.
This paper examines how destination-country climate policies and environmental standards influence India’s export competitiveness in carbon-intensive sectors. Using a structural gravity framework estimated through the Poisson Pseudo-Maximum Likelihood with high-dimensional fixed effects (PPMLHDFE), it analyzes India’s export flows in six CBAM-targeted product groups—iron and steel, aluminium, cement, fertilizers, hydrogen-related chemicals, and electricity—to 30 major trading partners during 2002–2023. Results show a differentiated pattern: CBAM alignment in importing countries enhances exports in aluminium, cement, and fertilizers, but restricts trade in hydrogen and electricity. Higher greenhouse gas emissions in destination economies increase Indian export flows, whereas stronger environmental performance (EPI) significantly reduces them, underscoring market-driven decarbonization pressures. These findings reveal a two-speed green trade transition and highlight the urgency for sector-specific decarbonization, MRV upgrading, and carbon-efficiency investments to sustain India’s export growth under tightening climate-aligned trade regimes.
A central paradox of India’s development trajectory is the persistent disconnect between rapid economic growth and low employment generation. This study investigates the structural dynamics underpinning this paradox over the period 1983–2023. Using the large-scale survey datasets from the NSSO Employment-Unemployment Surveys and the Periodic Labour Force Surveys, the study applies the canonical Shapley decomposition framework to disentangle the relative contributions of intra-sectoral productivity changes and inter-sectoral labour reallocations to per capita output growth. Furthermore, it also analyses the structural change index (SCI) and employment elasticity for India. This analysis reveals a pattern of variation in employment as well as gross value added between and within the sub-sectors of India. The results show that productivity plays a crucial role in driving per capita output growth, while the contributions of static and dynamic reallocation are minimal. In dynamic allocation, within-sectoral productivity plays a significant role, revealing that the agriculture and manufacturing sectors contribute the most to overall productivity growth, while sectors such as finance, real estate, and construction make only a minimal contribution. Moreover, the analysis confirms that output growth has not been accompanied by commensurate employment growth, suggesting a decoupling of economic expansion from job creation. The results indicate a persistent decoupling of output growth from employment expansion, reflecting a weak process of structural transformation. These findings underscore the need for targeted policy interventions to promote inclusive growth and generate decent employment opportunities.
The present study attempts to empirically evaluate the efficiency of the Flexible Inflation Targeting (FIT) regime (2015–2022) as compared to the Multiple Indicator Approach regime (1998–2015) of monetary policy of India by constructing efficiency frontiers (When the output inflation variability trade-off is estimated for optimum policy, it is called as Central Bank Efficiency Frontier or Taylor Curve). This requires an estimate of the slope of the Aggregate Supply curve of the economy, the potential output, targeted inflation, and the Central Bank’s inflation aversion parameter as the intermediate parameters. The empirical results reveal that (a) the RBI continues to remain a conservative Central Bank during both the regimes (b) the monetary policy found to be more efficient during the FIT regime, (c) disinflation was costlier during the MIA regime and (d) the inflation expectations anchoring has improved during the FIT regime.
This paper examines how participation in global value chains (GVCs) shapes countries’ greenhouse gas (GHG) emissions, distinguishing between the environmental implications of forward (upstream) and backward (downstream) integration. Using a new dataset that combines the OECD Inter-Country Input–Output tables, Trade in Value Added indicators, and GHG footprint data for 75 economies and 45 sectors from 1995 to 2020, the analysis traces emissions embodied in both domestic production and bilateral trade flows. An additive Logarithmic Mean Divisia Index (LMDI) decomposition reveals that rising output has been the principal driver of growing production-based emissions, while improvements in emission intensity have only partly offset scale effects. Fixed-effects and instrumental-variables regressions show that forward GVC participation is consistently associated with lower domestic emissions, whereas backward participation exhibits no systematic effect. A PPML gravity model of emissions embodied in bilateral trade demonstrates that forward participation reduces trade-embedded emissions across most sectors, while backward participation yields heterogeneous outcomes—lowering emissions in agriculture, mining, and utilities but raising them in manufacturing and services. The results highlight that environmental gains arise most reliably when countries specialise in upstream, technology-intensive tasks, while downstream final production may increase emissions through scale and logistics effects. The paper concludes by discussing policy strategies that support functional upgrading, facilitate technology diffusion, and enable developing economies to balance the employment benefits of backward participation with long-term environmental objectives.
This paper models the trade-off between the creative generation of ideas in a team of managers with diverse religious backgrounds against their discomfort from dealing with colleagues with different religious identities. This is done by operationalizing the important concept of managerial engagement. The paper identifies the features of the optimal religious mix that a secular owner of a competitive firm would choose for the management team. Generally, this optimum entails a tendency towards firm segregation of management by religion. It is seen that competition—especially domestic—entrenches the tendency towards this segregation. Aspects of globalization that would encourage more diversification by religion are identified. The role played by anti-religious discrimination laws in promoting diversity is discussed. It is argued that such laws, by spurring profitable organizational innovation, can be more efficacious in generating religious diversity in private management teams.
After the inception of WTO in 1995, in line with the negotiations under the General Agreement on Trade in Services (GATS), the barriers to trade in services gradually came down. However, the impediments on different modes of international trade in services displayed diverging patterns. On one hand, various newer barriers on movement of skilled professionals (Mode 4) have been witnessed in recent times, in the form of visa and work permit restrictions etc. Conversely, a growth in online service deliveries (Mode 1) is being witnessed. Considering data for 89 countries over 2014–2022, the current study examines the underlying drivers of online service imports, taking into account the role of heterogeneity in digital regulations between trading partners in an adapted gravity framework. The underlying drivers of service exports under Mode 1 and commercial establishment (Mode 3) have also been analyzed for selected countries. The results demonstrate that greater connectivity in a country encourages higher trade in the digitally enabled components of services. This effect however could be dampened in the presence of wider heterogeneity in digital regulations between the trading countries, with the negative impact being stronger for middle-income nations. The empirical results underline the need for improving coherence in cross-country digital regulations.
As countries embrace the circular economy approach to reduce virgin resource use and minimize waste generation, international trade plays a critical role in achieving circularity through trade that encourages recycling and resource recovery, but carries the risk of waste dumping when environmental regulatory enforcement is poor in importing countries. Considering the case of India, we examine the factors determining the pattern of ferrous scrap imports during 1996–2021, and test for circularity through secondary steel production as well as the waste haven effect. Beginning with an OLS regression analysis, followed by instrumental variable estimation, and the Poisson-pseudo maximum likelihood estimation, we find robust evidence that Indian secondary steel production has been a significant determinant of ferrous scrap imports, and detect a waste haven effect for imports from rich non-OECD countries. We conclude that India is advancing the circular business model within the country while extending environmental services to the rest of the world for minimizing waste, and fostering resource efficiency. However, given the evidence of waste haven effect, India needs a strong environmental policy with the circularity business model to protect against hazards and adverse impact of ferrous waste recycling and reuse.
Backward linkages in global value chains (GVCs) could potentially enable developing economies to boost exports through lower costs or higher productivity by leveraging foreign value added in their exports (FVAX). However, the benefits may vary across industries and development levels. This paper examines how FVAX influences manufacturing exports, focusing on heterogeneity by R D intensity (high-tech vs. low-tech) and country development (developed vs. developing). Possible endogeneity is addressed by employing an instrumental variable approach. The paper finds a suggestive evidence of positive FVAX effect on exports. In particular, low-tech industries in developing countries, and high-tech industries in developed countries benefit from these gains. These findings highlight the potential of low-tech sectors in developing economies to support export-led growth, offering insights for trade policy and industrial strategies.
Our paper is about a crucial yet often neglected policy issue regarding human capital formation in poor economies. Although increasing the supply of human capital in terms of rapid expansion of educational institutions and increased enrolment is essential, failing to pair it with complementary investments that stimulate demand for skills may lead to unintended adverse outcomes. Skill formation is frequently observed as a supply-side concern without emphasizing the equally important role of demand-side dynamics. It is commonly assumed that a greater supply of skilled labour will lead to higher demand driven by a fall in skilled wages. However, in a small open economy with fixed minimum wages for unskilled workers, the return to capital and skilled wages effectively gets pegged due to traded goods prices being disciplined by the world prices. Hence, skilled wages cannot fall sufficiently to absorb a growing supply of educated workers without the complementary investment, particularly a shift of capital toward skilled-intensive production. As a result, the economy experiences underemployment and a growing informal sector in order to absorb increasing surplus labour. Also, it is important to note that if a return to capital can’t increase, fresh private investment is not likely to happen, and this calls for a big push by public investment. In our paper, first, we provide motivating empirical evidence with a cross-section of countries, which suggests that if education and investment go hand in hand, the unemployment rate falls; otherwise, it may increase. Then, taking this cue, our rigorous theoretical model suggests that greater education for the hitherto employed unskilled group may generate educated unemployment within the group and increase unemployment of the uneducated outside the group, leading to underemployment through the expansion of the informal sector. Both effects are due to a shortage of complementary investment in production activities, which is often the consequence of policymaker’s choice of policies motivated by electoral success. Hence, our study highlights how the scarcity of capital or the lack of investment in productive activities can nullify the good impact of human capital accumulation.
In recent years, environmental degradation has emerged as a prominent issue worldwide and gained the attention of environmentalists due to its long-term detrimental impacts on agricultural output, food availability, water supply, and earnings. The current study aims to examine the dynamic asymmetrical relationship between technology innovations (TI), carbon dioxide (CO2) emissions, human capital, renewable energy, natural resources, and farm productivity in India. Using time-series data spanning from 1991 to 2021, this study used the non-linear autoregressive distributed (NARDL) model. The findings of the NARDL model reveal that CO2 emissions and natural resources have negative and significant effects on farm productivity in India in the long and short run. The positive and negative shocks in human capital and Technological Innovations have positive and significant impacts on farm productivity in the long and short run. Wald test conforms to the asymmetrical association between predictors and outcome variables. Based on the empirical analysis, some critical policy suggestions emerged. Moving toward sustainable farm productivity in India, there is a pressing need to improve environmental quality, provide skills to labor, and disseminate information among the farmers regarding climate-resilient seed varieties to cope with climate change.
Fertility convergence, a potential outcome during fertility transition, has been examined in previous studies primarily through conventional convergence tests within Indian states. However, the recent rise of the ‘club-convergence hypothesis’ in convergence studies paves the way for studying the club convergence pattern of fertility. Therefore, this study aims to find the club convergence of fertility rates across Indian states. Our findings reveal that although not all states converge, two convergence clubs emerge alongside some divergent states. Further, we find the determinants of forming such convergence clubs, where we conclude factors such as the adoption of family planning methods, mean years of the first marriage of women, and wealth inequality significantly impact the formation of higher order convergence clubs.
