Business cycle and bank loan portfolio performance : empirical evidence from brazilian banks

Este trabalho estuda os efeitos do crescimento econômico e da taxas de juros sobre o desempenho de carteiras de empréstimo dos bancos comerciais brasileiros no período de 2000 a 2010. Os resultados empíricos mostram que o crescimento econômico é o principal "driver" para o desempenho da carteira de crédito. Não foram encontradas evidências estatísticas sginificativas de mudanças na taxa de juros sobre o desempenho das carteiras de empréstimos. Além disso, há evidências empíricas de que o impacto do crescimento econômico sobre o desempenho da carteria de crédito tem efeito defasado de 2 trimestres. Por fim, os resultados mostram que alterações de PIB impactam de forma mais significativa o desempenho da carteira de crédito dos bancos comerciais brasileiros maiores. Devido ao efeito multiplicador do mercado de crédito, quanto maior o banco, maior a expansão relativa de sua carteira de crédito e, conseqüentemente a taxa de inadimplência da carteira, que é agravada pela concentração do mercado de crédito no Brasil.

Factors affecting the technical efficiency of production of the Brazilian banking system : a comparison of four statistical models in the context of data envelopment analysis

This paper uses an output oriented Data Envelopment Analysis (DEA) measure of technical efficiency to assess the technical efficiencies of the Brazilian banking system. Four approaches to estimation are compared in order to assess the significance of factors affecting inefficiency. These are nonparametric Analysis of Covariance, maximum likelihood using a family of exponential distributions, maximum likelihood using a family of truncated normal distributions, and the normal Tobit model. The sole focus of the paper is on a combined measure of output and the data analyzed refers to the year 2001. The factors of interest in the analysis and likely to affect efficiency are bank nature (multiple and commercial), bank type (credit, business, bursary and retail), bank size (large, medium, small and micro), bank control (private and public), bank origin (domestic and foreign), and non-performing loans. The latter is a measure of bank risk. All quantitative variables, including non-performing loans, are measured on a per employee basis. The best fits to the data are provided by the exponential family and the nonparametric Analysis of Covariance. The significance of a factor however varies according to the model fit although it can be said that there is some agreements between the best models. A highly significant association in all models fitted is observed only for nonperforming loans. The nonparametric Analysis of Covariance is more consistent with the inefficiency median responses observed for the qualitative factors. The findings of the analysis reinforce the significant association of the level of bank inefficiency, measured by DEA residuals, with the risk of bank failure.

Groups of services delivered by Brazilian branchless banking and respective network integration models

Over the last decade, Brazil has pioneered an innovative model of branchless banking, known as correspondent banking, involving distribution partnership between banks, several kinds of retailers and a variety of other participants, which have allowed an unprecedented growth in bank outreach and became a reference worldwide. However, despite the extensive number of studies recently developed focusing on Brazilian branchless banking, there exists a clear research gap in the literature. It is still necessary to identify the different business configurations involving network integration through which the branchless banking channel can be structured, as well as the way they relate to the range of bank services delivered. Given this gap, our objective is to investigate the relationship between network integration models and services delivered through the branchless banking channel. Based on twenty interviews with managers involved with the correspondent banking business and data collected on almost 300 correspondent locations, our research is developed in two steps. First, we created a qualitative taxonomy through which we identified three classes of network integration models. Second, we performed a cluster analysis to explain the groups of financial services that fit each model. By contextualizing correspondents' network integration processes through the lens of transaction costs economics, our results suggest that the more suited to deliver social-oriented, "pro-poor'' services the channel is, the more it is controlled by banks. This research offers contributions to managers and policy makers interested in understanding better how different correspondent banking configurations are related with specific portfolios of services. Researchers interested in the subject of branchless banking can also benefit from the taxonomy presented and the transaction costs analysis of this kind of banking channel, which has been adopted in a number of developing countries all over the world now. (C) 2011 Elsevier B.V. All rights reserved.

On the impact of disproportional samples in credit scoring models: An application to a Brazilian bank data

Statistical methods have been widely employed to assess the capabilities of credit scoring classification models in order to reduce the risk of wrong decisions when granting credit facilities to clients. The predictive quality of a classification model can be evaluated based on measures such as sensitivity, specificity, predictive values, accuracy, correlation coefficients and information theoretical measures, such as relative entropy and mutual information. In this paper we analyze the performance of a naive logistic regression model (Hosmer & Lemeshow, 1989) and a logistic regression with state-dependent sample selection model (Cramer, 2004) applied to simulated data. Also, as a case study, the methodology is illustrated on a data set extracted from a Brazilian bank portfolio. Our simulation results so far revealed that there is no statistically significant difference in terms of predictive capacity between the naive logistic regression models and the logistic regression with state-dependent sample selection models. However, there is strong difference between the distributions of the estimated default probabilities from these two statistical modeling techniques, with the naive logistic regression models always underestimating such probabilities, particularly in the presence of balanced samples. (C) 2012 Elsevier Ltd. All rights reserved.

Comparing fiscal multipliers across models and countries in Europe. National Bank of Belgium Working Paper No. 278, March 2015

This paper employs fifteen dynamic macroeconomic models maintained within the European System of Central Banks to assess the size of fiscal multipliers in European countries. Using a set of common simulations, we consider transitory and permanent shocks to government expenditures and different taxes. We investigate how the baseline multipliers change when monetary policy is transitorily constrained by the zero nominal interest rate bound, certain crisis-related structural features of the economy such as the share of liquidity-constrained households change, and the endogenous fiscal rule that ensures fiscal sustainability in the long run is specified in terms of labour income taxes instead of lump-sum taxes.

Annual report of the Bank Examiner of the State of Maine of the condition of the savings banks, trust and banking companies, loan and building associations and foreign banking companies having license to do business in the state.

Description based on: 42nd (1898).

Diversification : an opportunity for the New England textile industry, a report to the Federal Reserve Bank of Boston, the Massachusetts Department of Commerce, the Rhode Island Development Council, the Business Development Company of Rhode Island /

Mode of access: Internet.

Multilateral development bank opportunities for U.S. business : tapping into a $45 billion market.

Mode of access: Internet.

Konjunktúraingadozások az Egyesült Államokban 1970-2010 - Értelmezési nehézségek = Business cycles and recession patterns in the US economy and in the G7

Lehet-e beszélni a 2011-ig felgyülemlett empirikus tapasztalatok tükrében egy egységes válságlefolyásról, amely a fejlett ipari országok egészére általában jellemző, és a meghatározó országok esetében is megragadható? Megállapíthatók-e olyan univerzális változások a kibocsátás, a munkapiacok, a fogyasztás, valamint a beruházás tekintetében, amelyek jól illeszkednek a korábbi tapasztalatokhoz, nem kevésbé az ismert makromodellek predikcióihoz? A válasz – legalábbis jelen sorok írásakor – nemleges: sem a válság lefolyásának jellegzetességeiben és a makrogazdasági teljesítmények romlásának ütemében, sem a visszacsúszás mértékében és időbeli kiterjedésében sincsenek jól azonosítható közös jegyek, olyanok, amelyek a meglévő elméleti keretekbe jól beilleszthetők. A tanulmány áttekinti a válsággal és a makrogazdasági sokkokkal foglalkozó empirikus irodalom – a pénzügyi globalizáció értelmezései nyomán – relevánsnak tartott munkáit. Ezt követően egy 60 év távlatát átfogó vizsgálatban próbáljuk megítélni a recessziós időszakokban az amerikai gazdaság teljesítményét azzal a célkitűzéssel, hogy az elmúlt válság súlyosságának megítélése kellően objektív lehessen, legalább a fontosabb makrováltozók elmozdulásának nagyságrendje tekintetében. / === / Based on the empirical evidence accumulated until 2011, using official statistics from the OECD data bank and the US Commerce Department, the article addresses the question whether one can, or cannot, speak about generally observable recession/crisis patterns, such that were to be universally recognized in all major industrial countries (the G7). The answer to this question is a firm no. Changes and volatility in most major macroeconomic indicators such as output-gap, labor market distortions and large deviations from trend in consumption and in investment did all, respectively, exhibit wide differences in depth and width across the G7 countries. The large deviations in output-gaps and especially strong distortions in labor market inputs and hours per capita worked over the crisis months can hardly be explained by the existing model classes of DSGE and those of the real business cycle. Especially bothering are the difficulties in fitting the data into any established model whether business cycle or some other types, in which financial distress reduces economic activity. It is argued that standard business cycle models with financial market imperfections have no mechanism for generating deviation from standard theory, thus they do not shed light on the key factors underlying the 2007–2009 recession. That does not imply that the financial crisis is unimportant in understanding the recession, but it does indicate however, that we do not fully understand the channels through which financial distress reduced labor input. Long historical trends on the privately held portion of the federal debt in the US economy indicate that the standard macro proposition of public debt crowding out private investment and thus inhibiting growth, can be strongly challenged in so far as this ratio is neither a direct indicator of growth slowing down, nor for recession.

Methods, Models & Systems for Dealing with Some Business, Management & Engineering Problems

This keynote presentation will report some of our research work and experience on the development and applications of relevant methods, models, systems and simulation techniques in support of different types and various levels of decision making for business, management and engineering. In particular, the following topics will be covered. Modelling, multi-agent-based simulation and analysis of the allocation management of carbon dioxide emission permits in China (Nanfeng Liu & Shuliang Li Agent-based simulation of the dynamic evolution of enterprise carbon assets (Yin Zeng & Shuliang Li) A framework & system for extracting and representing project knowledge contexts using topic models and dynamic knowledge maps: a big data perspective (Jin Xu, Zheng Li, Shuliang Li & Yanyan Zhang) Open innovation: intelligent model, social media & complex adaptive system simulation (Shuliang Li & Jim Zheng Li) A framework, model and software prototype for modelling and simulation for deshopping behaviour and how companies respond (Shawkat Rahman & Shuliang Li) Integrating multiple agents, simulation, knowledge bases and fuzzy logic for international marketing decision making (Shuliang Li & Jim Zheng Li) A Web-based hybrid intelligent system for combined conventional, digital, mobile, social media and mobile marketing strategy formulation (Shuliang Li & Jim Zheng Li) A hybrid intelligent model for Web & social media dynamics, and evolutionary and adaptive branding (Shuliang Li) A hybrid paradigm for modelling, simulation and analysis of brand virality in social media (Shuliang Li & Jim Zheng Li) Network configuration management: attack paradigms and architectures for computer network survivability (Tero Karvinen & Shuliang Li)

Dynamical models for computer viruses propagation

Nowadays, digital computer systems and networks are the main engineering tools, being used in planning, design, operation, and control of all sizes of building, transportation, machinery, business, and life maintaining devices. Consequently, computer viruses became one of the most important sources of uncertainty, contributing to decrease the reliability of vital activities. A lot of antivirus programs have been developed, but they are limited to detecting and removing infections, based on previous knowledge of the virus code. In spite of having good adaptation capability, these programs work just as vaccines against diseases and are not able to prevent new infections based on the network state. Here, a trial on modeling computer viruses propagation dynamics relates it to other notable events occurring in the network permitting to establish preventive policies in the network management. Data from three different viruses are collected in the Internet and two different identification techniques, autoregressive and Fourier analyses, are applied showing that it is possible to forecast the dynamics of a new virus propagation by using the data collected from other viruses that formerly infected the network. Copyright (c) 2008 J. R. C. Piqueira and F. B. Cesar. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.