This paper addresses two issues encountered in the empirical financial distress literature: a-theoretical treatment of leverage and product-market competition as predictors of financial distress hazard; and lack of attention to frailty as a potential source of bias in reported estimates. We...

This paper addresses two issues encountered in the empirical financial distress literature: a-theoretical treatment of leverage and product-market competition as predictors of financial distress hazard; and lack of attention to frailty as a potential source of bias in reported estimates. We...

The existing literature on fiscal policy has mainly employed linear models that found a small fiscal multiplier in developing economies. These findings challenge the importance and e↵ectiveness of fiscal policy for these countries. However, linear models are not capable of distinguishing the...

The existing literature on fiscal policy has mainly employed linear models that found a small fiscal multiplier in developing economies. These findings challenge the importance and effectiveness of fiscal policy for these countries. However, linear models are not capable of distinguishing the...

The existing literature on fiscal policy has mainly employed linear models that found a small fiscal multiplier in developing economies. These findings challenge the importance and effectiveness of fiscal policy for these countries. However, linear models are not capable of distinguishing the...

The existing literature on fiscal policy has mainly employed linear models that found a small fiscal multiplier in developing economies. These findings challenge the importance and e↵ectiveness of fiscal policy for these countries. However, linear models are not capable of distinguishing the...

In this paper, we examine the usefulness of Google Trends data in predicting monthly tourist arrivals and overnight stays in Prague during the period between January 2010 and December 2016. We offer two contributions. First, we analyze whether Google Trends provides significant forecasting...

In this paper, we examine the usefulness of Google Trends data in predicting monthly tourist arrivals and overnight stays in Prague during the period between January 2010 and December 2016. We offer two contributions. First, we analyze whether Google Trends provides significant forecasting...