In this study, the linkage between tourism activity and economic development in 21 European countries is analyzed. The data are collected on an annual basis and cover the years from 1995 to 2017. The main purpose is to investigate empirically if there is a long-run connection between tourism...

This study attempts to evaluate the energy and carbon footprint within the framework of international environmental treaties and the efforts made by 11 large polluting countries to mitigate climate change. The econometric methodology accounts for the presence of cross-sectional dependence while...

This paper examines the effect of financial development on countries' production efficiency levels. By applying a probabilistic framework it develops robust (Order-m) time-dependent conditional nonparametric frontier estimators in order to measure 87 countries' production efficiency levels over...

In this paper, we study the estimation and inference of the threshold model with hybrid local stochastic unit root regressors. Our main contribution is to propose an estimator that generalizes the threshold model with various forms of nonstationary regressors and to obtain its limiting...

We fit U.S. stock market volatilities on macroeconomic and financial market indicators and some industry level financial ratios. Stock market volatility is non-Gaussian distributed. It can be approximated by an inverse Gaussian (IG) distribution or it can be transformed by Box-Cox transformation...

In this paper, we examine the effect of emissions, as measured by carbon dioxide (CO 2), on economic growth among a set of OECD countries during the period 1981-1998. We examine the relationship between total factor productivity (TFP) growth and emissions using a semiparametric smooth...

An area of very active research in econometrics over the last 30 years has been that of non- and semi-parametric methods. These methods have provided ways to complement more-traditional parametric approaches in terms of robust alternatives, as well as preliminary data analysis. The present...

We examine the significance of fourty-one potential covariates of bitcoin returns for the period 2010-2018 (2872 daily observations). The recently introduced principal component-guided sparse regression is employed. We reveal that economic policy uncertainty and stock market volatility are among...

This paper examines the behaviour of Bitcoin returns and those of several other cryptocurrencies in the pre and post period of the introduction of the Bitcoin futures market. We use the principal component-guided sparse regression (PC-LASSO) model to analyze several sample sizes for the pre and...