Umar Ahmed

This study aims to examine the demand-driven factors that attract foreign tourists to India. This study used an advanced gravity model to examine the factors that drew demand from 15 major foreign tourist destination countries from 1995 to 2018. Descriptive statistics, correlation, OLS, and panel GMM are the statistical tools used in data analysis. The results indicate that the per capita income of India and the countries of origin, the size of the Indian population, and a favorable visa policy all contribute to attracting foreign tourists to India. Meanwhile, the high cost of living in India compared to foreign tourist countries, terrorist incidents, and long distances between India and these countries are some of the factors that discourage foreign tourists from visiting India. The results of the study are robust and compelling and have significant implications for policymakers and the industry. Based on the findings, the study suggests that the Indian government should reduce the cost of living, especially for foreign tourists, by exempting them from paying goods and services tax and other taxes at the departure airport by showing the bill. In addition, security is an issue where the government should ensure the safety of foreign tourists.

Type of the article: Research Article

Abstract
This study aims to examine the impact of technological innovation on the carbon emissions of the G20 economies while accounting for the moderating role of economic policy uncertainty. To analyze the relationship between emissions and technological innovation in the presence of economic vulnerabilities, the study used the annual data from 2000 to 2023. Panel and quantile regression are used to test the heterogeneous relationship. The results reveal that research and development expenditure (R&D) has a positive and statistically significant impact on emissions at certain quantiles, suggesting that innovation alone may not uniformly contribute to emission reductions. Economic policy uncertainty is documented to have a heterogeneous relationship with emissions, wherein it reduces emissions at lower quantiles, with a positive relationship exhibited at higher quantiles. Similar results are obtained when economic policy uncertainty and R&D interact and are able to reduce emissions at all levels, as shown by quantile regression. The results provide valuable implications for policymakers, emphasizing the importance of fostering innovation while managing policy uncertainty to achieve carbon mitigation goals across varying emission levels within the G20.