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In this article, we investigate the effects of tourism indicators on income inequality (IIE) in a sample of 102 countries. We divide the sample countries into 71 developing and 31 advanced economies. Using annual data from 1995 to 2014, we employ panel unit root tests, cointegration, fixed-effects, fully modified ordinary least squares, and causality techniques. Our findings show that tourism indicators have a significant negative impact on IIE in developing economies, while they have an insignificant impact in developed economies. Conversely, economic globalization increases IIE in developing economies, whereas its effect is positive but statistically insignificant in developed countries. From these findings, the study outlines detailed policy and practical implications.

This paper uses the 1990-2010 natural disaster and carbon emissions data of G20 countries to examine the impact of natural disasters and climate change on the natural capital component of inclusive wealth. Our study shows that climate change and GDP have no positive impacts on the growth of natural capital. By contrast, trade openness and natural disaster frequency contribute to the accumulation of natural capital in G20 countries. There is an inverted U-shaped relationship between the growth of natural capital and the magnitude of natural disaster. Natural capital growth is not affected very much by small disasters. By contrast, large disasters tend to make the growth of natural capital fall sharply.

Nowadays, search engine use increasingly reflects investor sentiment, which affects the return on the stock market. In this article, we examine the relationship between Baidu Index sentiment and China's stock market returns. In two different GARCH models, the benchmark model and a Baidu Index extended model, the one-step forward method is used to predict the return of stock market. The study finds that Baidu Index − search volume is a valid indicator for forecasting volatility in China's stock market. The Baidu Index extended model performs better than the benchmark model, both in periods of high volatility and periods of low volatility. These results are quite robust in Shanghai Stock Exchange, Shenzhen Stock Exchange, CSI 300 Index, and CSI 100 Index. This study shows that the investor sentiment reflected in the Baidu Index can be used as a good early warning indicator of China's stock market.

With the global spread of the Coronavirus epidemic, search engine data can be a practical tool for decision-makers to understand the epidemic's trends. This article uses trend analysis data from the Baidu search engine, the most widely used in China, to analyze the public's attention to the epidemic and the demand for N95 masks and other anti-epidemic materials and information. This kind of analysis has become an important part of information epidemiology. We have analyzed the use of the keywords “Coronavirus epidemic,” “N95 mask,” and “Wuhan epidemic” to judge whether the introduction of real-time search data has improved the efficiency of the Coronavirus epidemic prediction model. In general, the introduction of the Baidu index, whether in-sample or out-of-sample, significantly improves the prediction efficiency of the model.

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This paper is the first of its kind to measure the income level of a country’s tourist arrival and empirically examine its impact on economic growth and environmental pollution in a sample of eight Mediterranean countries. The paper undertakes annual data from 1995 to 2014 and employs quantile regression models, autoregressive distributed lag (ARDL) estimations, and a heterogeneity causality test. The empirical results show that the income level of a country’s tourist arrival, across all quantiles, plays an important role in promoting economic development. However, the role of the income level of a country’s tourist arrival on environmental pollution varies with the changes in quantiles. More specifically, income level of a country’s tourist arrival has a positive impact on environmental pollution for the lower quantiles, while it has a negative impact for higher quantiles. The findings from panel ARDL models confirm that the income level of a country’s tourist arrival has positive and negative impacts on economic growth and emissions, respectively. Given these results, these findings provide information to take the necessary actions to ensure sustainable tourism development, i.e., the expansion of the tourism industry without harming the environment in the Mediterranean countries.