Suchergebnisse

PurposeThe 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.Design/methodology/approachTo 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.Findings 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.Practical implicationsThis study findings will benefit home buyers, sellers, investors, regulators and policymakers interested in the dynamic interlinkages of house price (HP) among Indian cities.Originality/valueThe 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.

AbstractThe study assesses the per capita output (PCO) convergence hypothesis across 33 Indian states/Union‐Territories at the aggregate and sectoral level by using weak‐sigma and clustering‐algorithm convergence tests for the period of 2011–2012 to 2018–2019. Results from the weak‐sigma convergence test show mixed evidence. This suggests that Indian states are not converging to single steady‐state. Further, results revealed the existence of multiple club‐convergence at aggregate and sectoral level after applying the clustering‐algorithm test. Results also show that the service sector is converging faster than the industry and agriculture sectors. Our findings recommend that sector‐specific policies need to be adopted to boost the aggregate PCO at club level.

AbstractThis study investigates the fiscal performance of 21 Indian states for the period 1980–81 to 2017–18. To do so, this study first applies a widely used multidimensional composite index. Second, this study implements data envelopment analysis (DEA) to assess the fiscal performance. The findings reveal that among Indian states, Odisha achieves the first rank and is found to be the best fiscal performing state in recent years. On the contrary, our results indicate that Punjab is the least performing state during 2015–16 to 2017–18. From the policy perspective, least performing states should get more attention from the central government and can adopt the policies of other best performing states, which may improve their fiscal performance.

This paper aims to investigate whether COVID‐19 pandemic causes the spot electricity price discovery of the Indian electricity market. To do so, we use the average daily spot electricity price data for five regions of the Indian electricity market (North, East, West, South, and North‐East). The data is considered from March 15, 2020 to May 02, 2020. The results obtained from cross‐sectional augmented Im, Pesaran and Shin (CIPS) unit root test show the stationary of spot electricity price and COVID‐19 at the level. Additionally, we use the Dumitrescu–Hurlin (DH) panel causality test to examine the causality between spot electricity price and COVID‐19. The results reveal the unidirectional causality which is running from COVID‐19 to the spot electricity price discovery but no other way around. Our findings suggests to the policymakers that across different regions of India (North, East, West, South, and North‐East), the ongoing coronavirus outbreak will further disrupt the electricity market.

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


Design/methodology/approach
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.


Findings
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.


Research limitations/implications
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.


Originality/value
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.

PurposeThe 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.Design/methodology/approachThe paper tests this hypothesis using club convergence technique propounded by Phillips and Sul (2007).FindingsThe 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.Practical implicationsSince 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.Originality/valueWhereas 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.

PurposeThe 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.Design/methodology/approachFirst, 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.FindingsOur 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.Research limitations/implicationsFrom 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.Originality/valueThe study contributes to the existing literature by estimating the exchange rate misalignment for India and its impact on economic growth.

The aim of this paper is to examine the impact of tourism arrivals and tourist expenditure on economic growth in case of four developing countries (Brazil, Russia, India, and China) using annual data from 1995 to 2016. To achieve this objective, we apply Dumitrescu–Hurlin causality test and panel data models. The results indicate that tourist expenditure has a positive impact on economic growth. Further, the results show that tourist arrivals do not have any significant effect on economic growth. The direction of causality shows that tourist expenditure has bidirectional causality with economic growth. The policy suggests that the investment environment must be upgraded through appropriate measures such as deregulation in economic activity; developing the port facilities, road network, railways, and telecommunication facilities; achieving clarity in trade policy and flexibility in labor markets; and setting a suitable regulatory framework and tariff structure and the country must grow in terms of better facilities and infrastructure for tourists.