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1 – 3 of 3Muhammed Ashiq Villanthenkodath, Mantu Kumar Mahalik and K. Mohamed Ismail Yasar Arafath
This empirical study explores the role of tourism development (TD) in India's environmental degradation. Since sustainable eco-tourism is essential for India, whose long-term…
Abstract
Purpose
This empirical study explores the role of tourism development (TD) in India's environmental degradation. Since sustainable eco-tourism is essential for India, whose long-term economic prosperity also depends on robust tourism growth. Hence, this study offers specific policy proposals for sustainable tourism based on the simulated outcomes.
Design/methodology/approach
The study employed the quarterly data from 1995Q1–2018Q4 for empirical validation. Moreover, the autoregressive distributed lag (ARDL) approach, Toda and Yamamoto (TY) causality model and wavelet coherence are also used to analyse the role of TD in India's environmental degradation.
Findings
The ARDL bounds test confirms the long-run relationship between the series. The long-run results from the ARDL model also indicate the driving role of TD in India's environmental degradation. In addition, the usage of the wavelet coherence method confirms the changes in TD that leads to changes in India's pollution level at different frequencies and periods, especially in the long run.
Research limitations/implications
Since this analysis is India-specific, these findings may lack generalizability to other developing economies. Therefore, researchers are encouraged to examine the impact of tourism growth on the natural environment in other countries either in a panel or time-series framework.
Practical implications
This study suggests crucial implications for checking the pollution sands from TD without sacrificing tourism-led economic growth. This would be possible if the usage of green energy in India's transport sector is promoted.
Originality/value
This is the first study that analyzes the impact of TD on environmental degradation in the ARDL, wavelet coherence, TY frameworks for enabling the Indian economy for a sustainable tourism practice.
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Magda Kandil, Muhammad Shahbaz, Mantu Kumar Mahalik and Duc Khuong Nguyen
Using annual data from 1970 to 2013 for China and India, this paper aims to examine the impact of globalization and financial development on economic growth by endogenizing…
Abstract
Purpose
Using annual data from 1970 to 2013 for China and India, this paper aims to examine the impact of globalization and financial development on economic growth by endogenizing capital and inflation and drawing comparisons between the two fastest growing emerging market economies.
Design/methodology/approach
In the long run, co-integration test results indicate that financial development increases economic growth in China and India.
Findings
The results also reveal that globalization accelerates economic growth in India but, surprisingly, impairs economic growth in China, as it increases competition for exports. The results furthermore disclose that acceleration in capitalization and inflation, as a proxy for aggregate demand, are positively linked to economic growth in China and India.
Originality/value
Causality test results indicate that both financial development and economic growth are interdependent. In contrast, causality runs from higher economic growth to increased globalization in India, while the results do not support long-term causality between globalization and economic growth in China.
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Mantu Kumar Mahalik, Debashis Acharya and M. Suresh Babu
– The purpose of this paper is to investigate empirically the price discovery and volatility spillovers in Indian spot-futures commodity markets.
Abstract
Purpose
The purpose of this paper is to investigate empirically the price discovery and volatility spillovers in Indian spot-futures commodity markets.
Design/methodology/approach
The study has used four futures and spot indices of Multi-Commodity Exchange, Mumbai. The study also employs vector error correction model (VECM) and bivariate exponential Garch model (EGARCH) to analyze the price discovery and volatility spillovers in Indian spot-futures commodity market.
Findings
The VECM shows that agriculture future price index (LAGRIFP), energy future price index (LENERGYFP) and aggregate commodity index (LCOMDEXFP) effectively serve the price discovery function in the spot market implying that there is a flow of information from future to spot commodity markets but the reverse causality does not exist. There is no cointegrating relationship between metal future price index (LMETALFP) and metal spot price index (LMETALSP). Besides the bivariate EGARCH model indicates that although the innovations in one market can predict the volatility in another market, the volatility spillovers from future to the spot market are dominant in the case of LENERGY and LCOMDEX index while LAGRISP acts as a source of volatility toward the agri-futures market.
Research limitations/implications
The results are aggregate in nature. Further study at disaggregated level will provide further insights on behavior of specific commodity prices and the price discovery process.
Originality/value
The paper provides useful information about the evolution and structures of futures commodity trading in India, related literature and relevant methodology concerning the hypotheses.
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