Athanasios Tsagkanos

How bureaucracy and corruption affect economic growth and convergence in the European Union: The case of Greece

Purpose - This paper aims to examine the impact of corruption and bureaucracy on economic growth in Greece as measured by the growth rate of per capita GDP. Also, using the mean per capita GDP of the EU as a benchmark, it seeks to investigate the convergence timing of Greece with the EU. Design/methodology/approach - The empirical approach taken is based on beta convergence theory. Findings - The results confirm the negative impact of bureaucracy and corruption on economic growth. However, the corruption exerts a more significant influence on growth than bureaucracy. Also, the timing of convergence of Greece with the EU is found to be 37 years. Originality/value - The robustness of these results is based on the use of a relatively new econometric method which is the Markov conditional bootstrap.

Does the ‘Market for Corporate Control’ hypothesis explain takeover targets?

This study tests the ‘Market for Corporate Control’ hypothesis in a small open economy. The results appear to favour rejection of this hypothesis indicating that acquisitions have not been driven by managerial-disciplinary motives. Moreover, it is found that a logit model outperforms other statistical tests.

Identification of Greek Takeover Targets and Coherent Policy Implications

The main purpose of this paper is the identification of the characteristics of takeover targets in a small open economy like Greece, using the market for corporate control (MCC) hypothesis as theoretical background. Contrary to this hypothesis, the results indicate that the motives for merging or acquisition activities are basically of strategic character. Using a sample of 35 acquired and 105 non-acquired firms, the sampling process was initially performed by a modified methodology of state-based sampling, even if its nature cannot be recognized by the classical maximum likelihood estimator (MLE) of logit model. Subsequently, taking into account the small size of the sample, we develop and use, in the logit context, the bootstrap MLE as an advanced alternative method for reducing inherit bias and inefficiency. The findings remain uniform supporting the strategic motives explanation in actual takeover activities, a fact that clearly illustrates the framework of merger policies followed by the Greek Competition Committee during the period under study.

Predicting Greek mergers and acquisitions: a new approach

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.

Prediction of Greek takeover targets via bootstrapping on mixed logit model

Purpose - The main purpose of this study is to examine the possibility of prediction of Greek takeover targets that belong to the industrial sector, emphasizing the econometric methodology and the prediction test. Design/methodology/approach - The study uses a sample of 51 targets and 290 non-targets exclusively from Greek industry over the period 1997-2005. In order to achieve a better predictive accuracy the paper uses a new econometric methodology, the bootstrap mixed logit and different (more advanced) techniques of prediction test and choice of cutoff values. Findings - The results exhibit that bootstrap mixed logit has significant and valuable predictive ability with respect to the classical conditional logit model. Furthermore, the predictive accuracy is higher than the results of other studies (e.g Palepu and Espahbodi and Espahbodi). Originality/value - The main contribution of this study is the application of the bootstrap mixed logit in analyzing Greek takeovers. The results change the prediction variables as well as the determinants of the takeover target characteristics for the Greek industry. This is meaningful, not only for the investors that seek to increase the value of their fortune through acquisitions, but also for the managers that can detect if their firm might be considered a takeover target.

Corporate failure risk assessment of Greek companies

In this paper, we investigate the determinants of corporate failure risk for the Greek non-financial companies using public accounts. Our motivation stems from the results of a recent international survey revealing that, during the period 2003?2004, Greece showed the biggest in terms of percentage, increase in corporate insolvencies among all the European countries. By exploiting a recent database and a set of variables as possible predictors of corporate failure, we use two competitive logit models comparing their predictive accuracy. Surprisingly, both the models exhibit low failure prediction ability a fact that intensify concerns about the quality of financial reporting of the Greek firms.

The Bootstrap Maximum Likelihood Estimator: the case of logit

The estimation of the parameters of logit model is mostly performed with method of maximum likelihood. However, the classical maximum likelihood estimators are biased and inefficient in appearance of small samples. The jackknife maximum likelihood estimator improves the above problems but still includes serious disadvantages. In this article, the Bootstrap Maximum Likelihood Estimator is developed as an alternative advanced method for reducing the bias and correcting the troubles with inefficiency and nonnormality. The importance of the method is shown through its application on data of Greek mergers and acquisitions.

Growth and volatility in the European Union: a linear or a non-parametric approach?

The paper reports an investigation of the relationship between business-cycle volatility and economic growth in the European Union before (EU-15) and after broadening (EU-25) using cross-sectional models. Results based on the superiority of the pseudo-likelihood ratio test as a more reliable tool for testing the robustness of the model used, indicate that the above relationship is linear only in the case of EU-15.

Asymmetric Exceedance-Time Model: An Optimal Threshold Approach Based on Extreme Value Theory

We propose an innovative asymmetric exceedance-time model with optimal thresholds. This model examines the impact of extreme downside and upside shocks and determines how the duration between past and present extreme shocks affects the dependent variable. We use extreme value theory (peak-over-threshold method) to model extremes, proposing a procedure for the automatic computation of optimal thresholds, at the point where the fitting of the extreme value distribution is maximized. We apply our model to S&P 500 equity index and GBP/USD exchange rate data and show that a strong statistical relation coincides with optimal threshold levels.

Average treatment effect estimators - inefficiency - minimisation of variance

In this paper, we show the inability of a recent average treatment effect estimator (ATE) to catch up the asymptotic semiparametric efficiency bound of Hahn (1998) although it minimises the mean squared error. Additionally, we propose the use of a minimum variance unbiased uniformly estimator of the propensity score in order to minimise the loss of efficiency.