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This paper develops a novel Bayesian heterogeneous panel vector autoregressive model (B-HP-VAR) that quantifies the impact of geopolitical risk shocks on the tourism industry of 14 emerging market and developing economies (EMDE). We find that increasing geopolitical tensions have a persistent negative effect on tourism demand in most of these countries, as shown by our impulse response estimates. Furthermore, evidence from forecast error variance decomposition reveals that geopolitical risk shocks in many EMDE economies constitute the main driver of tourism demand. Analysis from historical decompositions demonstrates that geopolitical tensions have been particularly influential in driving tourism demand in Ukraine, Russia, Turkey, China, Indonesia, Thailand, Colombia, and Mexico. Our main findings are robust to several perturbations to the benchmark specification. Our results have several important implications for policymakers in their efforts to strengthen the ability of the tourism industry to absorb shocks from geopolitical tensions. [ABSTRACT FROM AUTHOR]

This paper proposes a novel asymmetric jump model for modeling interactions in discontinuous movements in asset prices. Given the jump behavior and high volatility levels in cryptocurrency markets, we apply our model to cryptocurrencies to study the impact of various types of jumps occurring in one cryptocurrency's price process on the discontinuity component of the realized volatility of other cryptocurrencies. Our model also allows us to assess the impact of co-jumps. Using high-frequency data to compute the daily realized volatility, we show that downside, upside, and small jumps observed in cryptocurrencies negatively affect the jump component of other cryptocurrencies' realized volatility, while large jumps have the opposite effect. We further find significant asymmetric effects between small and large as well as between downside and upside jumps for several cryptocurrencies. Moreover, we find evidence of co-jumping behavior, which can trigger future jumps. The practical implications of our findings are also discussed. Finally, we extend our analysis to study the effects of jumps in mainstream financial assets on cryptocurrencies' jump behavior and find that upside and downside jumps observed in the S&P 500 index negatively impact cryptocurrency jumps. [ABSTRACT FROM AUTHOR]

The purpose of the present study is to identify the factors affecting the non-performing loans rate (NPL) of Eurozone’s banking systems for the period 2000-2008, just before the beginning of the recession. In our days, Eurozone is in the middle of an unprecedented financial crisis, calling into question the soundness of the banking systems of European countries. Looking at both macro-variables (e.g. annual percentage growth rate of gross domestic product, public debt as % of gross domestic product, unemployment) and micro-variables (e.g. loans to deposits ratio, return on assets, return on equity), we investigate which factors determine NPL on aggregate level. Overall, our findings reveal strong correlations between NPL and various macroeconomic (public debt, unemployment, annual percentage growth rate of gross domestic product) and bank-specific (capital adequacy ratio, rate of nonperforming loans of the previous year and return on equity) factors.

Traditional bankruptcy literature focuses on commercial enterprises for identifying the strongest variables and models to predict the bankruptcy outcomes. In this study, for the first time, we exploit a large dataset of European bankrupt and healthy social enterprises (SE's) in order to identify the crucial factors that affect the survival of this growing and distinguishable legal form. Combined with the goal of achieving optimal predictive accuracy, we rely on Random Utility Models (RUM) emphasising a new methodology: the Bootstrap Mixed Logit (BMXL). In contrast to what has been found for commercial enterprises, empirical results here indicate that certain organisational features such as the board and workforce size may have a different impact on the probability of SE's bankruptcy. [ABSTRACT FROM AUTHOR]

In this article, we examine the success rate of the memorandum in two peripheral eurozone countries (Ireland and Greece) that had significant differences in organisational structures and their development models. For this reason, we measure the quantile dependence between the returns of corporate bond investors and exchange rates employing a novel econometric methodology, the cross‐quantilogram. In Ireland, our key findings exhibit a higher rate of absorbing of structural reforms which contributes to more steady reinforcement of the enterprises, whether the European economy is stronger than the US or not. In contrast, Greece where the structural reforms are more intense, show a similar picture over a period longer than that of Ireland and only when the European economy goes beyond the US economy. [ABSTRACT FROM AUTHOR]

Byline: Athanasios Tsagkanos, Antonios Georgopoulos, Costas Siriopoulos In this paper, we investigate the possibility of predicting takeover targets in Greece, which is an incipient market for acquisitions. Our work is based on recursive partitioning techniques, that is decision-tree models, given that takeover likelihood models (such as logit) are not robust over time (Powell, 1997). However, we adopt a new technique with respect to Espahbodi and Espahbodi (2003), the machine learning algorithm J4.8 that is a new application in the sector of mergers and acquisitions. The results show that J4.8 outperforms the classical regression tree, although the predictive accuracy is not promising.