This paper analyzes the prediction power of the economic policy uncertainty (EPU) index on the daily Bitcoin returns. Using the Bayesian Graphical Structural Vector Autoregressive model as well as the Ordinary Least Squares and the Quantile-on-Quantile Regression estimations, the paper finds that the EPU has a predictive power on Bitcoin returns. Fundamentally, Bitcoin returns are negatively associated with the EPU. However, the effect is positive and significant at both lower and higher quantiles of Bitcoin returns and the EPU. In the light of these findings, the paper concludes that Bitcoin can serve as a hedging tool against uncertainty.

This paper reanalyzes the determinants of the CO emissions in France. For this purpose, it considers the unit root test with two structural breaks and a dynamic ordinary least squares estimation. The paper also considers the effects of the energy consumption and the economic complexity on CO emissions. First, it is observed that the EKC hypothesis is valid in France. Second, the positive effect of the energy consumption on CO emissions is obtained. Third, it is observed that a higher economic complexity suppresses the level of CO emissions in the long run. The findings imply noteworthy environmental policy implications to decrease the level of CO emissions in France.

This paper introduces a growth model that considers the indicator of economic complexity as a measure of capabilities for exporting the high value-added (sophisticated) products. Empirically, the paper analyzes the effects of the renewable and the non-renewable energy consumption on the economic growth in the panel data of 29 Organization for Economic Cooperation and Development (OECD) countries for the period from 1990 to 2013. For this purpose, the paper considers the panel autoregressive distributed lag (ARDL) and the panel quantile regression (PQR) estimations. The paper finds that not only the economic complexity, but also both the non-renewable and the renewable energy consumption are positively associated with a higher rate of economic growth.

This paper investigates the predictive power of global geopolitical risks (GPR) index on daily returns and price volatility of Bitcoin over the period July 18, 2010-November 30, 2017. Considering a Bayesian Graphical Structural Vector Autoregressive (BSGVAR) technique, we find that GPR has a predictive power on both returns and price volatility of Bitcoin. The results of the Ordinary Least Squares (OLS) estimations show that price volatility and returns of Bitcoin are positively and negatively related to the GPR, respectively. However, findings from the Quantile-on-Quantile (QQ) estimations state that effects are positive at the higher quantiles of both the GPR as well as price volatility and returns of Bitcoin. Therefore, we conclude that Bitcoin can be considered as a hedging tool against global geopolitical risks.

This paper investigates the effects of uncertainty on tourism spending (direct sales) by USA domestic tourists over the period of 1998Q1–2015Q4. For this purpose, for the first time, the Economic Policy Uncertainty index was used as an independent variable in tourism demand analysis models. Unit root and cointegration tests are applied to account for unknown structural breaks. The empirical findings indicate that a higher level of Economic Policy Uncertainty leads to significant declines in tourism spending in the long run. Copyright © 2016 John Wiley & Sons, Ltd.

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This paper examines the causal relationship between Bitcoin attention (measured by the Google Trends search queries) and Bitcoin returns for the period from January 1, 2013, to December 31, 2017. For this purpose, we employ the Copula-Granger Causality in Distribution (CGCD) test. After implementing various robustness checks, we observe that there is a bi-directional causal relationship between Bitcoin attention and Bitcoin returns with the exception of the central distributions from 40% to 80%. To put it differently, the bidirectional causality mainly exists in the left tail (poor performance) and the right tail (superior performance) of the distribution.

This paper constructs a simple theoretical model to study the implications of globalisation for inequality and redistribution. It shows that when globalisation increases inequality, a policymaker interested in maximising the sum of welfares of all agents increases redistribution. Empirically, the paper examines the effects of globalisation on inequality and redistribution in a panel data set of 140 countries for the period from 1970 to 2012. It finds that both inequality and redistribution have been increasing with globalisation. The results are robust to the inclusion of many different controls and the exclusion of outliers.