Növelhető-e a csőd-előrejelző modellek előre jelző képessége az új klasszifikációs módszerek nélkül? (Can the predictive capacity of bankruptcy forecasting models be increased without new classification methods?)

A Bázel–2. tőkeegyezmény bevezetését követően a bankok és hitelintézetek Magyarországon is megkezdték saját belső minősítő rendszereik felépítését, melyek karbantartása és fejlesztése folyamatos feladat. A szerző arra a kérdésre keres választ, hogy lehetséges-e a csőd-előrejelző modellek előre jelző képességét növelni a hagyományos matematikai-statisztikai módszerek alkalmazásával oly módon, hogy a modellekbe a pénzügyi mutatószámok időbeli változásának mértékét is beépítjük. Az empirikus kutatási eredmények arra engednek következtetni, hogy a hazai vállalkozások pénzügyi mutatószámainak időbeli alakulása fontos információt hordoz a vállalkozás jövőbeli fizetőképességéről, mivel azok felhasználása jelentősen növeli a csődmodellek előre jelző képességét. A szerző azt is megvizsgálja, hogy javítja-e a megfigyelések szélsőségesen magas vagy alacsony értékeinek modellezés előtti korrekciója a modellek klasszifikációs teljesítményét. ______ Banks and lenders in Hungary also began, after the introduction of the Basel 2 capital agreement, to build up their internal rating systems, whose maintenance and development are a continuing task. The author explores whether it is possible to increase the predictive capacity of business-failure forecasting models by traditional mathematical-cum-statistical means in such a way that they incorporate the measure of change in the financial indicators over time. Empirical findings suggest that the temporal development of the financial indicators of firms in Hungary carries important information about future ability to pay, since the predictive capacity of bankruptcy forecasting models is greatly increased by using such indicators. The author also examines whether the classification performance of the models can be improved by correcting for extremely high or low values before modelling.

A comparative analysis of school satisfaction and dropout risk of middle school students attending programs for students with emotional handicaps, severe emotional disturbance and general education students attending center schools and satellite schools

This study evaluated school satisfaction as an indicator of dropout risk of students with Emotional Handicaps (EH) and students with Severe Emotional Disturbance (SED). The students attended two different kinds of middle schools in a largely urban school district in South Florida. One hundred eight students in grade 8 (ages 13-16) participated in this study. Participants were administered the National Dropout Prevention Assessment (NDPA). Forty participants with EH and SED attended a special center school. Thirty-one participants with EH and SED attended satellite programs in a regular middle school. Thirty-seven general education participants attended the same regular middle school. Overall school satisfaction scores were generated, as well as three primary factors (school, environment and personal) and 16 subscales (school atmosphere, future income, difficulty level of classwork, teacher relationships, peer relationships, intrinsic interest in classwork, school hours, classwork stress, general attitude towards school, family influence, perceived opportunity for career, future goals, travel distance, leisure time, self-appraisal of performance, and self-esteem).^ Comparison of students with EH and SED revealed that both groups of students were rated at "low risk" of becoming dropouts on the Environmental factor and the Difficulty of Schoolwork subscale. Students with EH were rated at "caution risk" risk on the Travel Distance subscale. Students with SED were rated at "high risk" on this subscale.^ There were no significant differences in school satisfaction and dropout risk between different program delivery models. There were also no significant differences for category of students (EH, SED) by school type (center school, satellite program). All students were rated at "low risk" of dropping out of school.^ There were significant differences between general education students and students with EH and SED attending satellite programs. Students with EH and SED were rated at "caution risk" for dropping out on the Travel Distance and the Leisure Time subscales. Discussion of results, implications for practice and recommendations for further research are included. ^

Liquidity and asset pricing: A comparison between three-factor and three-moment capital asset pricing models

Liquidity is an important attribute of an asset that investors would like to take into consideration when making investment decisions. However, the previous empirical evidence whether liquidity is a determinant of stock return is not unanimous. This dissertation provides a very comprehensive study about the role of liquidity in asset pricing using the Fama-French (1993) three-factor and Kraus and Litzenberger (1976) three-moment CAPM as models for risk adjustment. The relationship between liquidity and well-known determinants of stock returns such as size and book-to-market are also investigated. This study examines the liquidity and asset pricing issues for both intertemporal as well as cross-sectional data. ^ The results indicate an existence of a liquidity premium, i.e., less liquid stocks would demand higher rate of return than more liquid stocks. More specifically, a drop of 1 percent in liquidity is associated with a higher rate of return of about 2 to 3 basis points per month. Further investigation reveals that neither the Fama-French three-factor model nor the three-moment CAPM captures the liquidity premium. Finally, the results show that well-known determinants of stock return such as size and book-to-market do not serve as proxy for liquidity. ^ Overall, this dissertation shows that a liquidity premium exists in the stock market and that liquidity is a distinct effect, and is not influenced by the presence of non-market factors, market factors and other stock characteristics.^

Business process quantitative analysis and optimization for service industries

The total time a customer spends in the business process system, called the customer cycle-time, is a major contributor to overall customer satisfaction. Business process analysts and designers are frequently asked to design process solutions with optimal performance. Simulation models have been very popular to quantitatively evaluate the business processes; however, simulation is time-consuming and it also requires extensive modeling experiences to develop simulation models. Moreover, simulation models neither provide recommendations nor yield optimal solutions for business process design. A queueing network model is a good analytical approach toward business process analysis and design, and can provide a useful abstraction of a business process. However, the existing queueing network models were developed based on telephone systems or applied to manufacturing processes in which machine servers dominate the system. In a business process, the servers are usually people. The characteristics of human servers should be taken into account by the queueing model, i.e. specialization and coordination. ^ The research described in this dissertation develops an open queueing network model to do a quick analysis of business processes. Additionally, optimization models are developed to provide optimal business process designs. The queueing network model extends and improves upon existing multi-class open-queueing network models (MOQN) so that the customer flow in the human-server oriented processes can be modeled. The optimization models help business process designers to find the optimal design of a business process with consideration of specialization and coordination. ^ The main findings of the research are, first, parallelization can reduce the cycle-time for those customer classes that require more than one parallel activity; however, the coordination time due to the parallelization overwhelms the savings from parallelization under the high utilization servers since the waiting time significantly increases, thus the cycle-time increases. Third, the level of industrial technology employed by a company and coordination time to mange the tasks have strongest impact on the business process design; as the level of industrial technology employed by the company is high; more division is required to improve the cycle-time; as the coordination time required is high; consolidation is required to improve the cycle-time. ^

A study of stock market fluctuations and their relation to business conditions

Most research on stock prices is based on the present value model or the more general consumption-based model. When applied to real economic data, both of them are found unable to account for both the stock price level and its volatility. Three essays here attempt to both build a more realistic model, and to check whether there is still room for bubbles in explaining fluctuations in stock prices. In the second chapter, several innovations are simultaneously incorporated into the traditional present value model in order to produce more accurate model-based fundamental prices. These innovations comprise replacing with broad dividends the more narrow traditional dividends that are more commonly used, a nonlinear artificial neural network (ANN) forecasting procedure for these broad dividends instead of the more common linear forecasting models for narrow traditional dividends, and a stochastic discount rate in place of the constant discount rate. Empirical results show that the model described above predicts fundamental prices better, compared with alternative models using linear forecasting process, narrow dividends, or a constant discount factor. Nonetheless, actual prices are still largely detached from fundamental prices. The bubblelike deviations are found to coincide with business cycles. The third chapter examines possible cointegration of stock prices with fundamentals and non-fundamentals. The output gap is introduced to form the nonfundamental part of stock prices. I use a trivariate Vector Autoregression (TVAR) model and a single equation model to run cointegration tests between these three variables. Neither of the cointegration tests shows strong evidence of explosive behavior in the DJIA and S&P 500 data. Then, I applied a sup augmented Dickey-Fuller test to check for the existence of periodically collapsing bubbles in stock prices. Such bubbles are found in S&P data during the late 1990s. Employing econometric tests from the third chapter, I continue in the fourth chapter to examine whether bubbles exist in stock prices of conventional economic sectors on the New York Stock Exchange. The ‘old economy’ as a whole is not found to have bubbles. But, periodically collapsing bubbles are found in Material and Telecommunication Services sectors, and the Real Estate industry group.

Emotional intelligence and leadership in organizations: A meta-analytic test of process mechanisms

The present study—employing psychometric meta-analysis of 92 independent studies with sample sizes ranging from 26 to 322 leaders—examined the relationship between EI and leadership effectiveness. Overall, the results supported a linkage between leader EI and effectiveness that was moderate in nature (ρ = .25). In addition, the positive manifold of the effect sizes presented in this study, ranging from .10 to .44, indicate that emotional intelligence has meaningful relations with myriad leadership outcomes including effectiveness, transformational leadership, LMX, follower job satisfaction, and others. Furthermore, this paper examined potential process mechanisms that may account for the EI-leadership effectiveness relationship and showed that both transformational leadership and LMX partially mediate this relationship. However, while the predictive validities of EI were moderate in nature, path analysis and hierarchical regression suggests that EI contributes less than or equal to 1% of explained variance in leadership effectiveness once personality and intelligence are accounted for. ^

The role of emotional intelligence in college students' success

The purpose of this study was to determine if higher academic performance was positively correlated to higher emotional intelligence among traditional age male and female college students enrolled in an Introduction to Business course at a large multi-campus state college in Florida. The Bar-On 2004 (Emotional Quotient Inventory) EQ-i 133-item inventory was used to assess students’ emotional intelligence. Within the scope of this ex-post facto study, a quasi-experimental design was included to further determine if emotional intelligence could be increased through the inclusion of a curricular component on emotional intelligence. Four groups of students (N=111) participated in the three-phase study over two semesters. The first phase (pre-intervention) was limited to students with an established GPA and an attempted-to-completed credit hour ratio within the institution (N=82). Results showed a slight positive correlation between the two factors and the students’ emotional intelligence pretest assessment scores. The second phase of the study involved establishing a control and an experimental group in each of two semesters to compare the attainment of overall emotional intelligence scores as measured by the EQ-i. The third phase of the study examined four measures of academic success (GPA, the attempted-to-completed credit hour ratio, grade in the business course, and persistence in college) to determine if these factors were positively correlated with the students’ posttest EQ-i scores. The study also included a research question to determine if significant differences in overall EQ-i scores existed between male and female students during the three phases. Findings from the study indicated that (a) there was a slight positive correlation in the pre-intervention stage between emotional intelligence and traditional measures of academic success specifically, GPA and the attempted-to-completed credit hour ratio; (b) curricular intervention made a significant difference at the p <.05 level, with an .5 effect size, in one semester but failed to meet that threshold in the following semester with the second pair of groups; (c) at the post-intervention phase, the four measures of traditional academic success yielded a low positive correlation with the students’ emotional intelligence assessment scores, and (d) female students showed significant gains in their overall EQ-i scores.

Assessing the impact of business group diversification on the internationalization of their affiliates: The case of Latin American firms

This dissertation explored the capacity of business group diversification to generate value to their affiliates in an institutional environment characterized by the adoption of structural pro-market reforms. In particular, the three empirical essays explored the impact of business group diversification on the internationalization process of their affiliates. ^ The first essay examined the direct effect of business group diversification on firm performance and its moderating effect on the multinationality-performance relationship. It further explored whether such moderating effect varies depending upon whether the focal affiliate is a manufacturing or service firm. The findings suggested that the benefits of business group diversification on firm performance have a threshold, that those benefits are significant at earlier stages of internationalization and that these benefits are stronger for service firms. ^ The second essay studied the capacity of business group diversification to ameliorate the negative effects of the added complexity faced by its affiliates when they internationalized. The essay explored this capacity in different dimensions of international complexity. The results indicated that business group diversification effectively ameliorated the effects of the added international complexity. This positive effect is stronger in the institutional voids rather than the societal complexity dimension. In the former dimension, diversified business groups can use both their non-market resources and previous experience to ameliorate the effects of complexity on firm performance. ^ The last essay explored whether the benefits of business group diversification on the scope-performance relationship varies depending on the level of development of the network of subsidiaries and the region of operation of the focal firm. The results suggested that the benefits of business group diversification are location bound within the region but that they are not related to the level of development of the targeted countries. ^ The three essays use longitudinal analyses on a sample of Latin American firms to test the hypotheses. While the first essay used multilevel models and fix effects models, the last two essays used exclusively fix effects models to assess the impact of business group diversification. In conclusion, this dissertation aimed to explain the capacity of business group diversification to generate value under conditions of institutional change.^

The impact of friends on newly immigrant children's emotional and behavioral adjustment

Immigration disrupts an individual's support network; however, the stresses of the immigration process increase the need for social support. The presence of social support becomes essential for immigrant children and adolescents to cope with these important transitional circumstances. Friends are both sources of social support and models for behavior. Furthermore, friendship networks are known to have a significant influence on youths' functioning. Literature suggests that peer relations become more important in adolescence and friend support is related to child and adolescent well-being. Thus, friend relationships may be particularly important for immigrant youths who experience disruption in their friendship networks during the process of migration to another country. In addition to friendship networks and support, friend characteristics also need to be taken into consideration as important factors for immigrant youth adjustment. My study involved analyses of the effects of friend support and friend problem behaviors on emotional and behavioral functioning for elementary, middle, and high school age newly immigrant children and adolescents. ^ Immigrant children and adolescents (N = 503) were interviewed at schools by interviewers fluent in participants' languages. Structural Equation Modeling (SEM) analyses revealed that friend support and friend problem behaviors were related to children's self-esteem and externalizing behaviors. In addition, friend problem behavior alone predicted children's psychological symptoms and depression scores. Furthermore, age/grade was found to be a moderator for the relation between friend problem behavior and immigrant youth behavioral adjustment such that compared to elementary and high school cohorts, middle school youths showed more externalizing behaviors when they had friends performing problem behaviors. ^ Results supported the idea that both friend support and friend behavior are related to newly immigrant youths' emotional and behavioral adjustment. This study informs further research and interventions concerning the development of programs to facilitate immigrant youths' adjustment by revealing friendship factors related to their adaptation.^

Bankruptcy Situation Model in Small Business: The Case of Restaurant Firms

The purpose of this paper is to describe and discuss the current bankruptcy prediction models. This is done in the context of pros and cons of proposed models to determine the appropriate factors of failure phenomenon in cases involving restaurants that have filed for bankruptcy under Chapter 11. A sample of 11 restaurant companies that filed for bankruptcy between 1993 and 2003 were identified from the Form 8-K reported to the Securities and Exchange Commission (SEC). By applying financial ratios retrieved from the annual reports which contain, income statements, balance sheets, statements of cash flows, and statements of stockholders’ equity (or deficit) to the Atlman’s mode, Springate model, and Fulmer’s model. The study found that Atlman’s model for the non-manufacturing industry provided the most accurate bankruptcy predictions.

A Study of Stock Market Fluctuations and their Relations to Business Conditions

Most research on stock prices is based on the present value model or the more general consumption-based model. When applied to real economic data, both of them are found unable to account for both the stock price level and its volatility. Three essays here attempt to both build a more realistic model, and to check whether there is still room for bubbles in explaining fluctuations in stock prices. In the second chapter, several innovations are simultaneously incorporated into the traditional present value model in order to produce more accurate model-based fundamental prices. These innovations comprise replacing with broad dividends the more narrow traditional dividends that are more commonly used, a nonlinear artificial neural network (ANN) forecasting procedure for these broad dividends instead of the more common linear forecasting models for narrow traditional dividends, and a stochastic discount rate in place of the constant discount rate. Empirical results show that the model described above predicts fundamental prices better, compared with alternative models using linear forecasting process, narrow dividends, or a constant discount factor. Nonetheless, actual prices are still largely detached from fundamental prices. The bubble-like deviations are found to coincide with business cycles. The third chapter examines possible cointegration of stock prices with fundamentals and non-fundamentals. The output gap is introduced to form the non-fundamental part of stock prices. I use a trivariate Vector Autoregression (TVAR) model and a single equation model to run cointegration tests between these three variables. Neither of the cointegration tests shows strong evidence of explosive behavior in the DJIA and S&P 500 data. Then, I applied a sup augmented Dickey-Fuller test to check for the existence of periodically collapsing bubbles in stock prices. Such bubbles are found in S&P data during the late 1990s. Employing econometric tests from the third chapter, I continue in the fourth chapter to examine whether bubbles exist in stock prices of conventional economic sectors on the New York Stock Exchange. The ‘old economy’ as a whole is not found to have bubbles. But, periodically collapsing bubbles are found in Material and Telecommunication Services sectors, and the Real Estate industry group.

Emotional Intelligence and Leadership in Organization: A Meta-analytic Test of Process Mechanisms

The present study – employing psychometric meta-analysis of 92 independent studies with sample sizes ranging from 26 to 322 leaders – examined the relationship between EI and leadership effectiveness. Overall, the results supported a linkage between leader EI and effectiveness that was moderate in nature (ρ = .25). In addition, the positive manifold of the effect sizes presented in this study, ranging from .10 to .44, indicate that emotional intelligence has meaningful relations with myriad leadership outcomes including effectiveness, transformational leadership, LMX, follower job satisfaction, and others. Furthermore, this paper examined potential process mechanisms that may account for the EI-leadership effectiveness relationship and showed that both transformational leadership and LMX partially mediate this relationship. However, while the predictive validities of EI were moderate in nature, path analysis and hierarchical regression suggests that EI contributes less than or equal to 1% of explained variance in leadership effectiveness once personality and intelligence are accounted for.

Decoding Spontaneous Emotional States in the Human Brain.

Pattern classification of human brain activity provides unique insight into the neural underpinnings of diverse mental states. These multivariate tools have recently been used within the field of affective neuroscience to classify distributed patterns of brain activation evoked during emotion induction procedures. Here we assess whether neural models developed to discriminate among distinct emotion categories exhibit predictive validity in the absence of exteroceptive emotional stimulation. In two experiments, we show that spontaneous fluctuations in human resting-state brain activity can be decoded into categories of experience delineating unique emotional states that exhibit spatiotemporal coherence, covary with individual differences in mood and personality traits, and predict on-line, self-reported feelings. These findings validate objective, brain-based models of emotion and show how emotional states dynamically emerge from the activity of separable neural systems.

Forces of agglomeration and dispersal in rural business networks: a social network analysis

Two concepts in rural economic development policy have been the focus of much research and policy action: the identification and support of clusters or networks of firms and the availability and adoption by rural businesses of Information and Communication Technologies (ICT). From a theoretical viewpoint these policies are based on two contrasting models, with clustering seen as a process of economic agglomeration, and ICT-mediated communication as a means of facilitating economic dispersion. The study’s conceptual framework is based on four interrelated elements: location, interaction, knowledge, and advantage, together with the concept of networks which is employed as an operationally and theoretically unifying concept. The research questions are developed in four successive categories: Policy, Theory, Networks, and Method. The questions are approached using a study of two contrasting groups of rural small businesses in West Cork, Ireland: (a) Speciality Foods, and (b) firms in Digital Products and Services. The study combines Social Network Analysis (SNA) with Qualitative Thematic Analysis, using data collected from semi-structured interviews with 58 owners or managers of these businesses. Data comprise relational network data on the firms’ connections to suppliers, customers, allies and competitors, together with linked qualitative data on how the firms established connections, and how tacit and codified knowledge was sourced and utilised. The research finds that the key characteristics identified in the cluster literature are evident in the sample of Speciality Food businesses, in relation to flows of tacit knowledge, social embedding, and the development of forms of social capital. In particular the research identified the presence of two distinct forms of collective social capital in this network, termed “community” and “reputation”. By contrast the sample of Digital Products and Services businesses does not have the form of a cluster, but matches more closely to dispersive models, or “chain” structures. Much of the economic and social structure of this set of firms is best explained in terms of “project organisation”, and by the operation of an individual rather than collective form of “reputation”. The rural setting in which these firms are located has resulted in their being service-centric, and consequently they rely on ICT-mediated communication in order to exchange tacit knowledge “at a distance”. It is this factor, rather than inputs of codified knowledge, that most strongly influences their operation and their need for availability and adoption of high quality communication technologies. Thus the findings have applicability in relation to theory in Economic Geography and to policy and practice in Rural Development. In addition the research contributes to methodological questions in SNA, and to methodological questions about the combination or mixing of quantitative and qualitative methods.