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There is vast disparity in public expenditure on science, technology and environment (STE) across various Indian states. Public expenditure on STE is crucial in maintaining symmetric growth, social cohesion and sustainable development. Literature on this topic is scarce, which prompted the investigation of club convergence of STE public expenditure. In particular, the purpose of this paper to study the club convergence of STE public expenditure in the case of 20 Indian states during the period from 1987–1988 to 2019–2020.

This study applies the clustering algorithm to identify club convergence, advanced by the Phillips and Sul test, which enables identification of multiple steady states or club convergence, unlike beta and sigma convergences.

The findings of this paper show that all Indian states do not converge towards single steady states. This suggests a disparity in STE public expenditure across Indian states. Moreover, the findings favour three clubs that have their own unique transition paths. The results of this study are supported by the robustness check.

The findings suggest that the allocation of public expenditure on STE can be made based on club convergence to achieve social cohesion, sustainable development and millennium development goals across states.

Although several previous studies have investigated the convergence of public expenditure by considering either aggregate public expenditure or health/education expenditure, literature on the convergence hypothesis of STE public expenditure, particularly across Indian states, is scarce. Moreover, this paper is unique, as it examines multiple steady states or club convergence. Finally, this paper contributes to policymaking by suggesting which states should be given a push to achieve social cohesion and sustainable development.

The purpose of this study is to examine whether the electricity consumption patterns across Indian states do converge.

This study considers 18 Indian states spanning over the period 1970-1971 and 2014-2015, using the recently developed Phillips and Sul panel convergence technique that accounts the multiple steady states.

The results provide the following insights. First, the authors find evidence of convergence in electricity consumption among all Indian states. This suggests that electricity consumption patterns for Indian states are converging to a common steady state. Second, to provide broader insights, we further investigate the convergence in electricity consumption among user groups such as agriculture, industry, commercial, domestic and miscellaneous. The results reveal that commercial, domestic and miscellaneous groups are also converging. Third, the non-convergence patterns in agriculture and industry enable us to investigate the possibility of clubs or the multiple common steady states. The results indicate the occurrence of three clubs in case of agriculture and two clubs in case of the industry. Fourth, this study also inspects the relative speed of convergence among the user groups. The results reveal the higher speed of convergence in case of the domestic user group.

The findings enable policymakers to formulate an appropriate energy policy to accommodate the future electricity demand across Indian states and prioritize low electricity consumption states so that they receive a greater share.

This is the first study that examines the convergence in electricity consumption across Indian states at aggregate and user groups using a new panel club convergence technique.

The main purpose of this paper is to examine the convergence hypothesis of House Price Index (HPI) in the case of 18 major Indian cities for the period 2014–2019.

To attain the authors main goal, this study applies a clustering algorithm advanced by Phillips and Sul. This test creates a club of convergence based on the growth of the cities in terms of HPI.

The study findings show the existence of two convergence clubs and one non-convergent group. Club 1 includes the cities with high HPI growth, whereas club 2 comprises of cities with least HPI growth. Cities belonging to the non-convergent group are neither converging nor diverging.

This study findings will benefit home buyers, sellers, investors, regulators and policymakers interested in the dynamic interlinkages of house price (HP) among Indian cities.

The majority of the studies are conducted in the case of China at the province or city levels. Furthermore, in the case of India, none of the studies has investigated the HP club convergence across Indian cities. Therefore, the present study fills this research gap by examining the HP club convergence across Indian cities.

The purpose of this paper is to examine the nexus between financial integration and export diversification.

The authors consider 96 economies spanning over the period 1995-2014. To provide broader insights, the authors categorize 96 economies into developed, developing, high and low diversified panels. Both volume and equity-based measures of financial integration are used. The generalized method of moments (GMM) method is used to analyze the link between financial integration and export diversification.

The results derived from GMM indicate that financial integration is a vital factor of export diversification. Further, the findings reveal similar conclusions for developed, developing, high and low diversified panels.

The outcome of this study suggests that promoting the financial integration of markets by lowering the restrictions on capital inflows helps countries to lower the risk and diversify their exports.

Though there exists enormous literature on export diversification, the nexus between financial integration and export diversification is limited. The present study bridges this research gap.

The purpose of this study is to examine the club convergence of Financial integration (FI) in the case of 60 countries from 1970 to 2015. FI plays a vital role in economic growth through sharing the risk between countries, cross-border capital association, investment and financial information. It also leads to the efficient allocation of capital and capital accumulation, thereby improving the systematic growth and productivity of the economy. Literature on examining the convergence hypothesis of FI is scarce.

This study applies the clustering algorithm to identify club convergence, advanced by the Phillips and Sul test, which enables the identification of multiple steady states or club convergence, unlike beta and sigma convergences.

The findings indicate the non-convergence when all 60 countries were taken together. This highlights that the selected countries' have unique transition paths in terms of FI. Hence, the authors implement the clustering algorithm, and the estimation shows that 56 countries are categorised into three different clubs. However, for the rest of four countries, the results are sort of ambiguous, favouring neither convergence nor divergence.

On the basis of three country clubs, Club 1 presents the model countries such as the Netherlands, Singapore and Switzerland. The Club 2 and Club 3 countries can start making moves towards the model countries by making policy adaptations for trade, finance and business facilitation.

The existing literature provides a plethora of studies investigating the convergence of stock markets, exchange rates and equity markets, but studies on the convergence of FI, particularly across the countries, are scarce. This study contributes by bridging this gap. The study is unique in its type as it takes into account the multiple steady states or club convergence. This study also contributes in policymaking by suggesting Club 1 countries (the Netherlands, Singapore and Switzerland) as the model ones for the FI.

The purpose of this paper is to examine the convergence analysis of public debt among Indian states using annual data from 1990‒1991 to 2014‒2015.

The paper tests this hypothesis using club convergence technique propounded by Phillips and Sul (2007).

The results reveal the existence of debt divergence for overall Indian states. States are formed into four clubs on the basis of their level of debt, and three clubs support the hypothesis of club convergence. Further, the total public debt decomposes into three compositions such as market loans, bank loans and loans and advances from the central government. The existence of convergence is found for market loans and bank loans; however, the presence of divergence is found in case of loans and advances for overall states.

Since public debt plays an important role for fiscal health of the Indian states, findings of this study suggest to squeeze the fiscal consolidation further for Indian states whose debts as a percentage to gross state domestic product are on the higher side. Further, the examination of debt convergence helps to manage debt level among the states because heavy dependence on public debt could retard investment and economic growth.

Whereas bulk of empirical studies emphasize on examining the linkage between public debt and economic growth, and issue on debt sustainability across Indian states, examination of convergence of debt and its compositions (markets borrowings, bank loans and loans and advances from the central government) among the Indian states is scanty.

The purpose of this study is to examine the fiscal sustainability issue by dividing the fiscal deficit into high and low regimes using the quarterly data from 1997: Q1 to 2013: Q3. Further, we obtain the optimum level of public debt at which fiscal sustainability can be achieved.

This study uses the Markov Switching-Vector Error Correction Model (MS-VECM) for examining fiscal sustainability and threshold regression model to obtain the optimum level of debt.

The results derived from MS-VECM reveal the evidence in favor of fiscal sustainability during low fiscal deficit periods. Similarly, using a threshold regression model, the optimum public debt as a percentage to GDP seems to be around 21 per cent on a quarterly basis, beyond this level, public debt hurts economic growth.

From the policy front, the government of India should cut down the fiscal deficit only if debt reaches beyond a threshold level.

Noting that the vast literature has focused on examining the fiscal sustainability in India, the novelty of this study is to examine the fiscal sustainability by considering high and low deficits regimes using a non-linear approach.

This paper investigates the per-capita output club convergence in case of 120 countries for the period 1995–2015. Further, we disaggregate per-capita output into three broad sectors such as agriculture, industry, and service and investigate the convergence hypothesis.

The paper tests this hypothesis using the Phillips and Sul panel club convergence technique.

Our findings are as follows: (1) our results indicate the evidence of output divergence for the full sample; (2) when countries are divided into different clubs, the results exhibit the sign of per capita output club convergence both for aggregate and three major sectors. Further, this study confirms that industry's per capita output is the main driver for aggregate per-capita output club convergence in case of club 1. For club 2, agriculture's per capita output is a primary source for aggregate per capita output club convergence. Likewise, in the case of clubs 3 and 4, we find the service sector's per capita output is the main component for aggregate per-capita output club convergence; (3) both the service and industry sectors are major drivers for aggregate per-capita output club convergence.

This study suggests to the policymaker that sector-specific policies need to be adopted to boost the per-capita output growth by improving the performance of each of the sectors across the countries.

Notwithstanding, there are many studies that examine the output convergence using a notion of beta and sigma convergence, but studies regarding per capita output club convergence both at the aggregate and sectoral level are scanty.

The purpose of the paper is to examine the impact of exchange rate misalignment on economic growth in India using annual data from 1980 to 2014.

First, misalignment is measured, which is defined as the deviations of the actual real exchange rate (RER) from its equilibrium level. The equilibrium real exchange rate (ERER) is estimated using the auto-regressive distributed lag (ARDL) model by considering key macroeconomic fundamentals of the determinants of RER. Zivot and Andrews’ unit root with structural break is used to test the stationarity property of data. The impact of exchange rate misalignment on economic growth has been examined using ARDL and variance decomposition techniques.

Our results find an overvaluation of the exchange rate till 2000, and thereafter, an undervaluation of the exchange rate prevails in India. Further, the result indicates that an increase in exchange rate misalignment leads to a decrease in economic growth and vice versa. Moreover, a positive misalignment (overvaluation) hurts the economic growth and a negative misalignment (undervaluation) promotes the economic growth.

From the policy perspective, the results highlight that India needs to maintain an appropriate exchange rate which can reduce the RER misalignment. It is better for the Reserve Bank of India (RBI)’s intervention to smoothen the fluctuations of the exchange rate to avoid the inefficiency in the allocation of resources. However, to minimize the RER misalignment, the intervention should be conducted only in the short run.

The study contributes to the existing literature by estimating the exchange rate misalignment for India and its impact on economic growth.

This paper aims to investigate whether improvement in human capital can foster energy conservation by reducing the energy consumption in India using annual data from 1980 to 2014. Further, this study examines the relationship between human capital and various forms of energy consumption such as electricity, coal, natural gas, hydrocarbon gas and petroleum consumption.

To attain the objective, the study investigates this relation through the auto-regressive distributed lag model (ARDL) technique to find a long-run and short-run relationship. Second, to check the robustness of the results, the authors use alternative econometric methods such as dynamic ordinary least squares and fully modified dynamic ordinary least squares.

The results reveal a negative relationship between human capital and energy consumption, which implies that improvement in human capital lowers the energy consumption and various forms energy consumption, except for petroleum consumption. The results derived from ARDL show that there exists a long-run and short-run association between human capital and energy consumption. The results are consistent across the econometric techniques.

Because G20 countries including India aim at reducing carbon emission to a certain level, this study provides an insight that by emphasizing on human capital, India can reduce energy consumption, which would foster energy conservation.

To the best of the authors’ knowledge, this the first study in India which attempts to examine the effect of human capital on energy consumption and its various forms.