Do political connections affect bank leverage? Evidence from some Middle Eastern and North African countries

This study examines the association between political patronage and bank financing decisions in a sample of 34 commercial banks operating in the Middle East and North Africa for the period 2003–2014. We collected information manually about the profiles and biographies of individuals on the boards of banks to identify which banks had political connections, which is the novel contribution of the study. Linear and nonlinear panel data analysis was used to investigate this relationship. The results reveal that politically backed banks tend to be more leveraged. The indirect effect of political patronage on leverage was not found to be large, but was significant through its interaction with profitability; that is, politically backed banks with higher profitability are positively associated with leverage. Our findings imply that the privileges resulting from political ties make banks more profitable, and that this also leads to higher leverage. In line with the related literature, we found that a strong political presence on the boards of banks can be considered an important intangible asset, and one of the factors driving bank financing decisions.

     

The Poisson Maximum Entropy Model for Homogeneous Poisson Processes

Our main interest is parameter estimation using maximum entropy methods in the prediction of future events for Homogeneous Poisson Processes when the distribution governing the distribution of the parameters is unknown. We intend to use empirical Bayes techniques and the maximum entropy principle to model the prior information. This approach has also been motivated by the success of the gamma prior for this problem, since it is well known that the gamma maximizes Shannon entropy under appropriately chosen constraints. However, as an alternative, we propose here to apply one of the often used methods to estimate the parameters of the maximum entropy prior. It consists of moment matching, that is, maximizing the entropy subject to the constraint that the first two moments equal the empirical ones and we obtain the truncated normal distribution (truncated below at the origin) as a solution. We also use maximum likelihood estimation (MLE) methods to estimate the parameters of the truncated normal distribution for this case. These two solutions, the gamma and the truncated normal, which maximize the entropy under different constraints are tested as to their effectiveness for prediction of future events for homogeneous Poisson processes by measuring their coverage probabilities, the suitably normalized lengths of their prediction intervals and their goodness-of-fit measured by the Kullback–Leibler criterion and a discrepancy measure. The estimators obtained by these methods are compared in an extensive simulation study to each other as well as to the estimators obtained using the completely noninformative Jeffreys’ prior and the usual frequency methods. We also consider the problem of choosing between the two maximum entropy methods proposed here, that is, the gamma prior and the truncated normal prior, estimated both by matching of the first two moments and, by maximum likelihood, when faced with data and we advocate the use of the sample skewness and kurtosis. The methods are also illustrated on two examples: one concerning the occurrence of mammary tumors in laboratory animals taking part in a carcinogenicity experiment and the other, a warranty dataset from the automobile industry.     

Explaining Unequal Levels of Social Capital in Tehran

Social capital may act as an asset to serve people in various situations. However, people do not equally enjoy the same level of social capital and there is inequality in distribution of this asset in societies. There is few research within the wider literature exploring the determinants of inequality in social capital. This study measured and decomposed inequality in the distribution of social capital in Tehran using a concentration index approach. Data was gathered through a survey in 2008, the sample included 2484 of over 18-year old residents. Social Capital Integrated Questionnaire was used to measure social capital status, its dimensions (networking, trust, and cooperation) and outcomes (cohesion and political action). Most of social capital dimensions/outcomes were unequally distributed in Tehran, favouring the rich. However, in terms of political action, the poor were more politically active than the rich in Tehran. Decomposition showed that economic status and education had the highest contributions to the observed inequalities. In efforts to move towards a more just society, these findings can inform future policies in Iran to tackle the observed inequalities in social capital.     

Analyzing Accessibility Dimension of Urban Quality of Life: Where Urban Designers Face Duality Between Subjective and Objective Reading of Place

The subject of urban quality of life and the promotion of its concept in particular, has always been the central focus of urban designers. This term is a multi-conceptual and dimensions. However most of the scholars have agreed that the concept consisted from two main dimensions; objective and subjective which these two approaches are used for its measuring. One of the important goals of urban designers is to create urban environment that all citizens have easy access to urban services, as accessibility reflects the quality of an urban environment. The present research intends to measure the public space accessibility by using objective approach in first and then by using the subjective approach for measuring in the study area to compare the results. The results revealed that there are considerable differences between objective and subjective measuring of urban quality of life in a urban space, therefore urban designers can not rely only on the results of objective measuring to understand such spaces for planning, if so, their attitudes towards urban spaces could not be an appropriate guide for explaining the quality of life for urban residents.     

A Multiperiod Audit Staff Planning Model Using Multiple Objectives: Development and Evaluation*

The audit staff planning problem, a specific type of manpower planning problem, has been modeled using goal programming and, more recently, multiple objective linear programming. Prior studies developed single-period models and did not go beyond the model building stage. This study develops a multiperiod audit staff planning model and evaluates the model using a test application involving actual decision makers (partners in public accounting firms). The multiperiod model includes seven objectives to be optimized: profit (to be maximized), late completion of work, work declined, staff augmentation, staff reduction, underutilization of the work force, and shortfall in meeting professional development targets (all to be minimized). Over a four-quarter planning horizon with one “busy season,” the model is subject to constraints with respect to the projected audit work load, ability to substitute personnel and to perform interim audit work, available staff hours (including overtime limitations), supervisory requirements, and professional development targets. Results of the test application showed that the model was capable of producing a range of values for each objective. The participants were exposed to much of that range when making their decisions. The results also showed that all objectives were important and that participants were consistent in choosing their preferred level of each objective over several runs of the model. These results and the reactions of the participants demonstrate that the model is usable by actual decision makers and has potential for a number of specific applications.