Katerina Dimaki

Characterizations of Bivariate Pareto and Yule Distributions

Abstract This article provides two characterizations of Mardias Type I bivariate Pareto distribution. In particular, it is shown that the distribution of a random vector (X, Y) is uniquely determined as a Mardias Type I bivariate Pareto distribution if its weighted form follows a Mardias Type I bivariate Pareto distribution. Furthermore, this distribution is characterized by a condition on its tail probabilities. Analogous results hold for the bivariate extension of the Yule distribution which can be considered as the discrete analogue of the distribution under study.

The Region and its Multiple Images

Abstract The growth or decline of a region depends on its power to “pull” and retain both business activities and the right blend of people to run them; this pulling power depends on what we call the Image of the region. Hence, it can be argued that, at each point in time, the region “sends out” its Image and, depending on its impact on the receivers (both employers and employees), the region may be considered attractive or non-attractive. The available evidence suggests that all the receivers groups or in other words the potential movers react similarly to a basic set of factors; more precisely, a set of minimum standards, largely common to all the potential movers, must be satisfied if the region is to be considered as a potential choice by any of them. On the other hand, the potential movers may belong to a number of different groups that have a different type of interaction with a region and as result each of these groups is likely to have a different image of the particular region. Hence, a region does not have a single image, but multiple ones. To reconcile these two views we refine the concept of a regions Image by introducing the following two concepts: the Basic Image and the Specific Image. The Basic Image of a given region measures the degree to which the region satisfies a set of basic criteria, common for all movers. A region satisfying those criteria is considered by all potential movers as worth a closer examination and as a potential final choice. On the other hand the Specific Image of a given region, as perceived by a particular group of potential movers, measures the degree to which movers belonging to that particular group consider the region as their best final choice. A detailed exposition of the concept of a regions Basic Image has been presented in some of the authors’ earlier papers. In the present paper emphasis will be placed on a regions Specific Image as perceived by the various groups of potential movers. More precisely: • The groups of potential movers will be determined. • The factors affecting each group will be identified and ways for their measurement will be suggested. • The form of each Specific Image function will be defined. The theoretical findings will be applied to a number of regions and their Basic and Specific Images will be calculated. The main results will be presented and discussed.

A Country’s Process of Development as Described by a Cusp Catastrophe Model

For a long of time a country’s development has been synonymous with its economic growth and GDP per capita has been the main indicator expressing a country’s prosperity. Over the last years, however, economies and societies have been undergoing dramatic changes. Globalization, international integration, technological innovation and mobility of capital have changed the picture and make it extremely difficult to predict the future of countries. Economic changes test the ability of all countries to compete and the gap between leading and lagging countries in terms of growth, income and employment may be widening. Social changes test the ability of states and governments to provide an appropriate social framework for their people. Environmental factors test the ability of national and local governments to manage resources in a sustainable manner and to maintain and improve the quality and safety of life. These changes have led to a modification of the targets of development and to the acceptance that the concept of development has to embody human well-being alongside with economic growth. Sustainable development refers to the ability of our societies to meet the needs of the present without sacrificing the ability of future generations to meet their own needs. Measuring sustainable development means going beyond a purely economic description of human activities; requires integration of economic, social and environmental concerns. In other words, sustainable development means ensuring economic efficiency while respecting social equity and safeguarding ecological integrity. New techniques are required in order to benchmark performance, highlight leaders and laggards on various aspects of development and facilitate efforts to identify best practices. New tools have to be designed so as to make sustainability decision-making more objective, systematic and rigorous. Many tools and methodologies have been used over the past years to measure the progress towards sustainability. The majority of those methodologies make use of a single indicator in order to measure separately the evolution of each component i.e. the economic, the social and the environmental. Our objective in the present paper is to (a) outline the process of a country’s development taking into account all its three dimensions, economic, social and environmental; (b) present a model for quantifying its process of development encompassing all those dimensions; (c) apply the model to Eastern European and Baltic countries and (d) discuss the results.

Measuring the effect of financial incentives on a region’s development: a statistical process control approach

The state of a region’s development may be expressed through its ‘Image’, an index describing the region’s socioeconomic conditions. In this context a region may be seen as a ‘production unit’ and its Image as the outcome of its development process. To improve the conditions of its less developed regions, the State takes measures which may be seen as disorder factors for their development process. Hence, statistical process control techniques may be used in studying regional development issues. In this paper the concept of an area’s Image and a number of SPC techniques are presented and applied to the case of Greece.

The Cusp Catastrophe Model in Describing a Bank's Attractiveness as Measured by its Image

Banking has always been an extremely competitive industry and competition has become tougher over the last years. Every bank has two sides to consider, customers and investors. Customers, however, are clearly the most important part of a bank as they provide the basic raw materials of deposits and the demand for loans, which are the revenue streams of net interest income but also provide the fee income. The bank offers an intermediation service between customers with excess funds and those with a funds deficit. It borrows and lends wholesale funds to keep the two piles in some kind of balance. The drivers of customer behaviour are complex. Understanding the needs of their customers and reacting to the changes of their behaviour, aid banks and financial institutions to face the hard competition. Clearly then, the success of a bank is subject to its ability to attract and retain its customers, and a large part of their business. This ability depends on what is called the image of a bank. In highly competitive sectors, like the banking sector, the image represents an asset which allows firms to differentiate and increase their success chances. However, although its impact on consumer behavior is of primary importance, a banks image is a difficult asset to value and quantify. The concept of image has been given considerable attention in the literature over the past years. Image has been defined as the total impression that an entity makes on the minds of people and as the net result of the interaction of beliefs, ideas, feelings and previous experiences with an institution, which are stored in memory and transformed in concepts. Especially a banks image can be seen as the perception that customers or potential customers have for a specific bank, based on the messages they received by the examined financial institution. Image is a strategic tool since it helps banks to achieve long-term objectives and it can be shown as a source of competitive advantage. The present paper builds on the previous work on the subject and focuses on the definition and measurement of a banks image. It introduces image as a variable which expresses a banks current state of development and future prospects. It identifies the factors affecting this variable, suggests ways of measuring them and uses image as the basis for the building of a non-linear model expressing a banks development. The image of a bank, as defined in this paper, may prove a very useful tool for planning purposes, since it doesn’t only give an early diagnosis of possible changes, sometimes discontinuous, in the banks pattern of progress, but also indicates the reasons for them. Hence, it may be used as the basis for designing appropriate measures to assist a banks evolution. The theoretical findings are applied to a group of banks operating in Greece and the results are presented and discussed.