We examine the significance of fourty-one potential covariates of bitcoin returns for the period 2010–2018 (2,872 daily observations). The principal component-guided sparse regression is employed, introduced by Tay et al. (2018). We reveal that economic policy uncertainty and stock market...

We develop a generalised impulse response function (GIRF) approach to explore the different impacts of aggregate and sectoral shocks within a VAR-GARCH-M model. Using the output of our GIRF analysis, we explore the behaviour of three European countries (Germany, Spain and the UK). We analyse the...

The assumption of linearity is tested using five statistical tests for the US and the Canadian unemployment rates and the employment sectoral shares growth rates; construction, finance, manufacturing and trade. An AR(p) model was used to remove any linear structure from the series. Evidence of...

This study revisits the sectoral shifts hypothesis for the US for the period 1948 to 2011. A quantile regression approach is employed in order to investigate the asymmetric nature of the relationship between sectoral employment and unemployment. Significant asymmetries emerge. Lilien's...

This paper re-examines Lilien's sectoral shifts hypothesis for U.S. unemployment. We employ a monthly panel that spans from 1990:01 to 2011:12 for 48 U.S. states. Panel unit root tests that allow for crosssectional dependence reveal the stationarity of unemployment. Within a framework that takes...

We investigate the effect of uncertainty on investment. We employ a unique dataset of 25000 Greek firms' balance sheets for 14 years covering the period before and after the eurozone crisis. A dynamic factor model is employed to proxy uncertainty. The investment performance of 14 sectors is...

The European north-south divide has been an issue of a long-standing debate. We employ a Global VAR model for 28 developed and developing countries to examine the interaction between the global trade imbalances and their impact within the euro-area framework. The aim is to assess the propagation...