India’s Contemporary Macroeconomic Themes

In this descriptive study, we first analyze what the medium term future looks like for the Indian economy in a post-pandemic world, both in the context of an uncertain global environment and also in the context of India's own structural problems. We also highlight the structural challenges and opportunities for the Indian economy—what are the obstacles in India’s growth trajectory going forward, and what can be done to overcome them as India maneuvers through a complex global environment where geopolitics dominate trade, climate change concerns become critical and authoritarian regimes may increasingly lose favor with foreign investors and corporations. The objective is to provide a broad assessment of the factors that need to be critically addressed in order for India to not only achieve and sustain a high rate of growth but also to make the leap to a high income country and create adequate jobs.

A number of recent studies have highlighted that in the twenty-first century, India is slated to become the global growth leader, maintaining relatively high growth rates over several decades. This is estimated to result in India becoming the second largest economy in terms of its size of GDP as measured in PPP terms by 2039–40 and the largest economy by 2051–52 (EY, 2023). Even in market exchange rate terms, India is estimated to become the second largest economy by 2075 (Goldman Sachs, 2022). This robust growth performance is largely dependent on the interface of India’s unfolding demographic dividend with its saving and investment rates. Saving rate tends to be high when dependency rate is low and the available population in the working age group is productively employed. In this paper, we have highlighted that the demographic profile in the next few decades is expected to be noticeably different across Indian states. States that are at present considered relatively more developed in economic terms are also the states that would be aging ahead of the states that are presently less developed. To some extent, the growing discrepancy in the age profiles of different states would be moderated by inter-state migration. Using the differential features of the evolution of age structure across states, policymakers both at the central and state levels can orient their policies to maximize overall and state-specific growth by finetuning over time, their expenditure prioritization with respect to education, health, and skill building. In terms of urbanization and spread of infrastructure facilities also, suitable messages can be derived for optimal allocation of infrastructure investment across space and over time.

India needs to sustain post-Covid fiscal improvements reflected in buoyant revenue growth, reduced pressure on expenditure and a reduction in public debt and deficits. However, the debt ratio of the general government (Union and States) remains at an elevated level. A targeted reduction in debt and deficit, a compositional shift of the Union government’s capital expenditure, and a state specific rebalancing of the FRBM framework may help fasten the process of fiscal recovery and growth.

This paper examines the relationship between government revenue, expenditure, and economic growth for Indian States in a panel framework while also identifying the drivers of States’ primary expenditure. On the one hand, the study confirms a long run relationship between revenue and expenditure thereby supporting ‘fiscal synchronization’ hypothesis whereas on the other, the existence of a long run association between expenditure and economic growth is detected providing support to the ‘Wagner's law’. Given the importance of primary expenditure in the overall expenditure, the study finds that the States’ primary expenditure has a persistent effect, with past decisions on primary expenditure influencing current-year decisions. States pursue countercyclical expenditure policy in case of positive and negative output gaps, with more pronounced countercyclicality during negative output gap periods. Regarding the States’ sensitivity to their debt levels, the study finds States responding to the level of debt countercyclically in case of positive output gap. The study recommends increasing capital expenditure and debt reduction during phases of positive output gaps to ensure long-term fiscal sustainability of Indian States.

Assessing the revenue implications of GST on Indian state finances cannot be contained to compare the revenue stream which is subsumed into GST with State GST collection alone. Since GST subsumes many taxes from state tax bases, comparing the revenue performance of taxes which are outside the GST framework would be equally important. Moreover, in the federal system revenue implication of shortfall in tax collection of the federal government is also likely to spill-over to sub-national finances in terms of lower tax devolution. Sustaining revenue streams of state governments is important for sustainable Public Finance Management (PFM) and therefore a comprehensive assessment of state finances before and after GST would be important. This paper attempts to fill the gap in exiting literature by assessing the revenue of 18 major states during pre- and post-GST periods.

This study addresses an important policy issue pertaining to the determination of equalization transfers to Indian States. It measures the revenue expenditure needs and own revenue fiscal capacity of States normatively and determines the equalization transfers in four alternative scenarios. The estimated amounts of equalization transfers for all 29 States range from ₹ 3,73,956 crore to ₹ 14,77,282 crore. These findings will be useful to policymakers and other researchers to design more effectively the transfers policy besides general-purpose transfers to address the resource gap such that the Indian States can provide a standard level of public services.

The Goods and Services Tax (GST) that was implemented in July 2017 to simplify and harmonize the domestic consumption tax system has taken a firm root and is a reality. However, the potential gains from the reform are yet to be fully realized, and the reform is still a work in progress. In the last five years, the tax has settled, and there are signs of improvement in revenue collections. There have been many gains from the tax, and these include the unification of many domestic trade taxes and harmonized structure, removal of impediments to trade and reduced transaction cost of inter-state transactions, greater formalization of the economy through digitization, getting rid of inter-state tax exportation by converting the tax from origin-based to destination-based, and more efficient supply chain management. However, much more remains to be done to make it “a money machine”, and to lower the collection, compliance, and distortion costs. The paper details the reform agenda for fully realizing the potential gains from the tax in terms of efficiency and revenues.

In a recent innovative policy reform, India’s corporate income tax system was overhauled with optional lower rates in lieu of giving up complex deductions. However, official data reveals a puzzle wherein larger companies have opted more for the lower optional rates, while smaller ones appear reticent in switching to the optional regime. This paper explores this issue using empirical methods. The evolution of tax rates is tracked through reforms simplifying the tax system in the 1990s, the subsequent conundrum of zero-tax companies leading to the introduction of minimum alternate tax, and the persistence of lower effective tax rates for larger companies. This provides the rationale for a simpler tax regime with lower rates but fewer deductions. The user cost of the capital approach is used to examine the economically relevant tax impact across various sectors and ownership types. The results indicate that in terms of user cost, the various lower tax options are not attractive, and under certain situations may be worse for younger and smaller companies. In light of the analysis, policy options are suggested to improve the scheme so as to achieve the laudable objective of implementing a simple tax regime with lower rates and minimal deductions.

India has witnessed an unprecedented surge in sovereign debt on the back of the pandemic. We outline the costs and risks associated with high debt in India, drawing on experiences across countries as well as India’s own past. We conclude with a discussion of the benefits of reducing debt and possible scenarios that could achieve a sizable reduction over the next decade.

The non-government joint stock corporations have been dominating the Indian economic scene for quite some time now. Yet, the extent of the impact of taxation on corporate behavior remains ambiguous. Whatever be the objective, the way taxation is used for the purpose is simply to alter the relative tax burden between dividends and retained profits of companies. The differential tax burden can be injected through numerous elements in a tax system either at the company level or at the shareholders’ level. In India also the Income tax system contained several elements of tax differentiation aimed at discouraging excessive dividend payments by public limited companies. The present time-series empirical study is an objective attempt to analyze the tax differentiation underlying the Indian income tax system as well as to measure the response of public limited companies to such differentiation. Starting with a relatively simpler version of the general model, the coefficients are estimated by different methods with a view to identifying the correct version of the model. The Cobb-Douglas version of the model does not fit the data satisfactorily. Attempts to correct the lagged dependent bias, and serial correlations have not improved the situation. On the other hand, the CES version, though proved to be a better specification, yielded coefficient estimates which seem to be less stable. Specifically, the manufacturing sector proved to be very sensitive to tax changes. The quantification of the effect by means of simulating the best estimated equations for each group show that much of the effect ln India has been due to the adaptation of the ‘Classical’ system. The effect was highest in 1960–1968 during which time the Classical system was just introduced, the excess dividends taxes were levied, and the rates of personal income taxes had been higher compared to the other sub-periods. An important indication is that the effect of excess dividends taxes by itself is very low, compared to that of personal income tax, which is not fully in agreement with the prevalent view regarding these taxes.

This paper narrates the story of the evolutionary journey of non-performing assets (NPA) in the Indian banking sector. Three distinct phases of the intertemporal behavioral of NPAs of the Indian banking sector can be discerned. First, since the initiation of financial sector reforms till about the beginning of the North Atlantic Financial Crisis (NAFC), NPAs showed a consistent downward trajectory. Second, during 2008–09 through 2017–18 the NPAs showed a distinct spurt. Third, since then, NPAs marked by a downward trend till 2019–20 until the economic disruptions caused by Covid 19. Contrary to the popular perception of treating the second phase of rising NPAs as one emanating exclusively from governance issues in public sector banks (PSBs), four factors have been identified: (a) falling commodity prices; (b) regulatory forbearance; (c) initial exuberance in infrastructure projects punctured by a downward phase of business cycles (leading to substantial debt accumulation of select big corporates); and (b) governance failure in select PSBs. Moving forward, while the pandemic and some of the associated policy measures could reverse the recent downward trends in NPA, more durable policy initiatives like bankruptcy reforms are expected to make significant positive changes in the NPA situation of Indian banks.

The metamorphosis in monetary policy framework in India from ‘credit planning’ to adoption of ‘inflation targeting’ in 2016 is a long journey. The RBI’s conduct of monetary policy has been largely successful in contributing to overall macroeconomic stability. Nevertheless, there is a need for adequate deliberation and analysis on issues pertaining to pursuing single objective of price stability under ‘inflation targeting’ versus financial stability considerations; response to negative supply shocks; resolving ‘impossible trinity’ related trilemma, and the current monetary operating procedure without money, etc. to find convincing answers. This may help consequent strengthening of monetary policy effectiveness.

Despite the rapid pace at which digitalization has permeated various sectors of the economy, the assessment of its macroeconomic implications remains scarce in extant literature. This exploratory article provides a generalized perspective on the impact of ongoing digitalization on key economic indicators related to productivity and economic growth, inflation dynamics, financial markets, and currency demand. Deriving insights from contemporary literature in the field, we posit that the unprecedented advancements in technology can contest various postulates of conventional macroeconomic theory, thereby warranting agile policymaking to recalibrate the economy for the new digital order. This synoptic piece aims to encourage theoretical and empirical research works on the evolving issues of digitalization from the context of developing and emerging market economies.

In the context of the adoption of flexible inflation targeting regime in India since 2016, it is necessary to understand the effectiveness of monetary transmission mechanism. The paper investigates if there are any asymmetries in the monetary transmission during different regimes and verifies the role of financial frictions in such asymmetries, if it exists. Using Markov-Switching Vector Autoregression (MS-VAR) models, our results suggest that there are asymmetries in the monetary transmission mechanism during highly volatile and low-volatile regimes with respect to its effects on both output and inflation. It also finds that financial frictions do influence the extent and effectiveness of the policy transmission process in India. From a policy perspective, while the Reserve Bank of India (RBI) may continue to target inflation during high-volatile regimes, it could have output growth as an additional target during the low-volatile regimes.

Cash and debt management in India has undergone substantial change between 1993 and 2000. The unlimited and automatic issuance of ad hoc Treasury bills by the government to the RBI under the administrative arrangement since 1955 at fixed and low discount rates, not only diluted control over money supply but also encouraged fiscal profligacy. Dr. Rangarajan, in his various research-based studies, argued about the need for central bank to have control over money supply which will further lead to price stability. The empathetic assertions, logically argued and followed by academic rigour, led to discontinuation of automatic monetisation through ad hoc Treasury bills in a phased manner starting with an agreement in 1993 and complete cessation in 1997. This elimination of automatic monetisation led to a stronger control of money supply by the RBI. Further, scientific method of computing deficits was adopted by the government of India which transparently depicted the gap in government finances. This helped in encouraging fiscal discipline and resorting to auctions to raise resources for the government. The Fiscal Responsibility and Budget Management Bill, 2000 was another step in ensuring fiscal discipline and financial stability.

There is no consensus on social cost of carbon or marginal abatement cost of greenhouse gases for climate change mitigation, even though greenhouse gases are a global public bad. Some countries use different values of social cost of carbon in deciding policies for climate change mitigation. Using National Action Plan on Climate Change (NAPCC) and nationally determined contributions (NDCs) under the Paris Agreement, India uses sector-specific policies for climate change mitigation. These policies are reviewed and we note that even though these policies helped in achieving the targets they do not raise revenue and may not minimize the aggregate mitigation cost. As 61 countries have adopted carbon tax system or emission trading system, as there are doubts about achieving emission reduction to achieve the 1.5 °C increase in average global temperature by using NDCs by 2030, and as some developed countries which have either carbon tax or emission trading demand border taxes on goods imported from countries which do not have carbon taxes or lower levels of carbon taxes, India may have to prepare for an introduction of the carbon tax system or emission trading system soon.

This paper examines the empirical evidence of flypaper effects on the ecological fiscal spending in India. Using the panel data models, we analyze whether the intergovernmental fiscal transfers, or the states’ own income determine the expenditure commitments on ecology at the State level. The econometric results show that the intergovernmental fiscal transfers rather than the states’ own income determines ecological expenditure at subnational levels in India. The results hold, when the models are controlled for ecological outcomes and demographic variables.

In recent years, the discussion on distributional analysis for social justice has increasingly focused on inequality in opportunities and basic life chances rather than inequality in earnings. A suitable framework for analyzing equality of opportunity is that of Roemer (Theories of distributive justice. Harvard University Press, 1993) with the idea that any outcome is the fruit of aspects within individual responsibility, i.e., individual effort, and aspects beyond individual control, e.g., family background characteristics. The contribution of this paper is threefold; (i) to consider wellbeing in the work domain as a multifaceted concept and model it through a latent variable model; (ii) to estimate and analyze the inequality of opportunity (IOp) in work wellbeing in a multidimensional setting, taking into account the endogeneity of effort; and (iii) to apply the model to Indian data to estimate the shares of circumstances like religion, caste, household size, land, age, place of residence, and years of schooling, in the inequality of opportunity in work wellbeing. We also compare these shares with those obtained for a unidimensional outcome, across regions and over time.

Indian economy is passing through a critical phase of economic development due to the reversal of its structural transformation. The number of youth joining the labor force after completion of education and training is at the rise. This results in an upsurge in educated youth job seekers and growth of passive unemployment in India. Since the growth of youth population has already started shrinking, urgent measures are necessary to achieve the sustainable development goals. In this context, a structured industrial policy for the promotion of micro- and small enterprises along with infrastructure development and emigration and remittances policies is necessary.

Although forecasting models have been built for the Indian economy as a whole or its fiscal sector, there are few forecasting exercises for state economies and government finances. This paper develops a forecasting framework for projecting state-level fiscal imbalances as measured by fiscal deficit and government debt relative to respective GSDPs in the medium term. For this purpose, a panel modeling approach within a dynamic multi-equation model has been used. Since state-wise economic aggregates are not available in adequate detail, we take advantage of the linkages between state-level fiscal and economic variables and the corresponding variables at the central level or at the consolidated level of center and states. The model consists of 10 equations where five are stochastic and five are identities. The model is estimated for India’s 17 medium and large (ML) states. The sample period covers 2003–04 to 2019–20, that is, 17 years while the forecast period covers 2020–21 to 2025–26. The model reliably predicts variables in the COVID-affected year of 2020–21. Model properties are studied with respect to the quality of in-sample estimation. Using this framework, we identify Punjab, Rajasthan, Kerala, West Bengal, and Haryana as states that are headed toward larger fiscal imbalances in the medium-term requiring policy corrections.

Machine learning—a tool primarily belonging to the statistical, physical, and technological streams—has found its way into the economic sciences too. This paper attempts to conduct a brief review of literature with respect to some of the machine learning tools being used in macroeconomic forecasting, in particular, in DSGE models. The DSGE models have found widespread applicability owing to their firm theoretical micro-foundations in the Real Business Cycle school. Despite their practicality and applicability, these models drew criticism following the global financial crisis broadly due to structural drawbacks of (i) actual economic agents rarely exhibit rational expectations (ii) structure of markets rarely following the efficient market hypothesis, and (iii) aggregation of the behavior of the representative agent to derive macro-processes being true only under restrictive assumptions. This was further augmented by econometric issues of overfitting, simplifying yet false and non-testable identification restrictions, structural (and not practical) specification of the model, etc. The machine learning techniques are applied to attain the objective of reducing dimensionality, and better predictive performance. We then exposit the detailed specifications of two machine learning techniques utilized in studies which implemented the DSGE using machine learning tools, viz., random forests and support vector machines (SVMs), which are used in the classification of the data used in DSGE models. The machine learning techniques applied to classify the data in a DSGE model across studies include the random forests, SVMs, neural networks, logistic regressions, etc. The paper concludes with the implications that the introduction of the machine learning techniques has on DSGE models, and the policy implications thereof.

Business Groups continue to be a major contributor to the Indian economy and hence their influence on economic performance has intrigued researchers. It has often been argued that the unique business structure of group firms, leads to the formation of an internal capital market that renders the member firms certain advantages compared to their stand-alone counterparts. Firms in a business group can invest in each other’s business ventures and help other member firms in meeting their obligations. Therefore, during times of crisis, group-affiliated firms are likely to have better chances of surviving. Our study examines this hypothesis by deploying an empirical framework to show how the benefits of internal capital markets to group-affiliated firms amplify during an economic downturn. The results show that when economic conditions are challenging, group-affiliated firms have lesser chances of facing financial stress as opposed to stand-alone firms. Further, the study provides evidence that the intra-firm transfer increases during the crisis and that the reliance on trade credit and external loan tend to reduce for group-affiliated firms vis-à-vis stand-alone firms during the crisis.

India’s external sector recovered magnificently from the crisis of 1991, after economic reforms were put in place. However, of late, the health of India’s external sector raises some concerns. In this paper, we focus on the performance of India’s merchandise exports. The assessment of export performance is done in the context of (i) price competitiveness of India’s exports; (ii) level of economic activity in the rest of the world; (iii) composition and diversification of exports; (iv) import intensity and technology embedded in exports; and, (vi) direction of exports. The econometric analysis dealing with the determinants of exports uses quarterly data for the period 1996-97Q1 to 2021-22Q4, as the quarterly GDP data for India for the period prior to this are not available. The paper uses the time-series analysis: Unit Root Tests, Cointegration, and Vector Error Correction methods in the econometric analysis.