Christos Lemonakis

Regional Firm Performance: The Case of Greece

Manufacturing plays a significant role in all economies and are the key generators of employment and income and the drivers of innovation and growth. The scope of the present study is to analyze the performance of the Greek manufacturing firms by sectors (NACE 2 digit sector classification) and by region, based on firm level data. We investigate the effect of certain factors, such as size, age and exports on the efficiency of all manufacturing sectors in Greece. The research is based on financial data of a large sample of 3600 Greek industrial firms, for a time span of 9 years (2003-2011). The empirical research with the use of DEA analysis attempts to rate the 13 Greek regions based on their firm efficiency and explain the reasons behind the differentiation in performance. Further, econometric modeling is used to investigate the effect of age, size and exports on firm level efficiency, for each region. We find that there is a negative effect of exports on efficiency scores, while a positive relation between size and efficiency scores is reported.

Efficiency, competitiveness and exports of agricultural firms in the post-crisis era: evidence from Greece

The agri-food sector is an important sector for Greece and can contribute to the startup of the Greek economy. Therefore, the study covering the period 2004-2011, before and after the 2008 financial crisis in Greece, attempts to investigate the drivers of competitiveness in agricultural firms of Greece in the pre and post financial crisis era and detect differences among the two periods. Using a three-stage methodology, it is attempted to examine the hypotheses of this empirical study. OLS method is used in order to examine the relationship between efficiency, competitiveness and subsidies in agri-firms. The originality of this study is the investigation of the determinants of firm competitiveness measuring it with a competitiveness index and presenting differences between pre-crisis and post-crisis period. In addition, the correlation between efficiency, exports and subsidies on firm competitiveness is examined. The findings of this study have implications for practitioners, managers and policy makers.

Creating a Business Competitiveness Index: An Application to Greek Manufacturing Firms

The purpose of this article is to construct a composite index that reflects firm level competitiveness. The index is used to classify firms in terms of their competitiveness. The study proceeds in identifying the critical factors that influence competitiveness of firms. The research is undertaken on a sample of 980 firms from five important sectors of Greek manufacturers. The period of the study is 1996–2011, covering the pre- and post-economic crisis in Greece. Econometric modeling is used to identify the firm level competitiveness index and the critical factors of firm competitiveness. The findings can help managers, practitioners, and State officials to reinforce the competitive position of firms through the use of appropriate policies and strategies.

Applications to Corporate Default Prediction and Consumer Credit

This chapter illustrates the application of analytical predictive and descriptive techniques for credit risk assessment. To this end, two case applications are presented using data sets involving corporate defaults and credit card loans. The first part is devoted to the prediction of corporate defaults. A data set of 13,414 European small and medium-sized manufacturing enterprises (SMEs) from six countries is considered during the period 2009–2011. The information available for the firms involves their financial characteristics. Corporate default prediction models are constructed with statistical, machine learning, and multicriteria decision making techniques. The analysis of the results covers both the predictive performance of the models, as well as the insights that they provide regarding the factors that affect the default risk for European SMEs. In the second part, a descriptive multivariate clustering approach is employed to obtain analyze credit card loan applications. A publicly available data set of 30,000 cases is analyzed with the k-medoids algorithm to identify clusters of borrowers having similar characteristics. The results are discussed in terms of the common features of the clusters and their level of credit risk.

Data Analytics for Developing and Validating Credit Models

The development of credit risk assessment models in the context of credit scoring and rating, is a data-intensive task that involves a considerable level of sophistication in terms of data preparation, analysis, and modeling. From a data analytics perspective, the construction of credit scoring and rating models can be considered as a classification task, that requires the development of models differentiating the borrowers by their level of credit risk. The model fitting process can be implemented with various methodological approaches, based on different types of models, model fitting criteria, and estimation procedures. This chapter presents an overview of different analytical modeling techniques from various fields, such as statistical models (naive Bayes classifier, discriminant analysis, logistic regression), machine learning (classification trees, neural networks, ensembles), and multicriteria decision aid (value function models and outranking models). Moreover, performance measurement issues are discussed, focusing on the presentation of various popular metrics for evaluating the predictive power and information value of credit scoring and rating models.

Credit Scoring and Rating

Credit scoring usually refers to models and systems that provide a numerical credit score for each borrower, mostly for internal use by financial institutions and corporate clients. Credit ratings provide risk classifications for corporate loans, bond issues, and countries (e.g., sovereign credit ratings). This chapter describes the basic characteristics of both schemes. The presentation begins with a discussion of the different contexts of scoring and rating (through the cycle and point in time assessments, issuer ratings and issue-specific ratings, behavioral—profit scoring and social lending). Then, the main modeling requirements are outlined, and the model development process is explained. The chapter closes with a brief discussion of the credit rating industry, focusing on the major credit rating agencies (CRAs), who play a crucial role due to the globalization of the financial markets and the wide range of debt issues, which pose challenges to their monitoring and risk assessment for investors, financial institutions, supervisors, and other stakeholders.

Conclusions and Future Research

Credit risk measurement and management is an active area of research that combines elements from various disciplines. As new forms of credit gain ground (e.g., from traditional corporate and consumer loans to crowdfunding, social lending, etc.) and tighter regulatory requirements are imposed (Basel accords and new reporting and accounting standards such as IFRS 9), new opportunities and challenges arise for practitioners and researchers.

Introduction to Credit Risk Modeling and Assessment

Credit is a fundamental tool for financial transactions in the private and public sector, providing the liquidity needed for all forms of economic activity for consumers and corporate activities. This chapter sets the basis for understanding the concepts and aspects of credit risk management and the current practices in this field. The discussion starts with a presentation of the recent trends in credit provision, and an outline of the regulatory framework. Then, some fundamental factors that create uncertainties are outlined, and the main elements of credit risk modeling are identified, namely the estimation of the probability of default, loss given default, and exposure at default. The requirements set by the Basel Capital Accords regarding these elements are discussed and different modeling schemes are outlined, including judgmental approaches, data-driven empirical models, and financial models. The chapter closes with some financial measures for assessing the loan profitability, such as risk-adjusted return on capital.

Demystification of the glass ceiling phenomenon: Gender stereotyping and successful managers’ personality traits in Greece

Purpose The purpose of this paper is to examine the gender role phenomenon and the stereotyping of requisite managers’ personal characteristics in the Greek society of today. Design/methodology/approach Data were collected quantitatively based on the informants’ perceptions on successful managers’ personality traits and according to the informants’ personality characteristics. Questionnaires were administered online to two separate convenience samples. Reliability analysis (Cronbach’s α) was employed for scale refinement, while intraclass correlation coefficient (r’) and t-test analysis examined the similarity of respondents’ responses across the items of the refined scale. Findings The results indicate that gender role stereotypes are challenged. It seems that the perceived managers’ personality is comprised of both agentic/masculine and communal/feminine characteristics and this perception is not perceived differently by men and women. This debates on whether the “glass ceiling” exists due to other determinants. Originality/value The study contributes to the literature on gender role stereotyping research and perceptions of managerial personality characteristics in Greece.

History of Greece’s Debt Crisis and the Banking Policy

Two centuries of Greek debt emergencies highlight the traps of depending on outside financing. Since its autonomy in 1829, the Greek government has defaulted four times on its outside creditors, and it was safeguarded in every crisis. Firstly, this chapter demonstrates that cycles of outside crises and reliance are a perpetual topic of Greek present-day history—with rehashing designs: before the default, there is a time of substantial acquiring from remote private loan bosses. Secondly, it analyzes the period from 2008 in more detail to present and the role that the banks play in four times defaults. As reimbursement challenges emerge, foreign governments venture in, help to reimburse the private leasers, and request spending cuts and alteration programs as a condition for the authority bailout advances. Political obstruction from abroad mounts and a drawn out scene of obligation shade and monetary autarky takes after. At present, there is considerable evidence to suggest that a substantial haircut on external debt is needed to restore the economic viability of the country. Even with that, a policy priority for Greece is to reorient, to the extent possible, toward domestic sources of funding.