Using a Bayesian model for bankruptcy prediction : a comparative approach

The purpose of this study is to examine the impact of the choice of cut-off points, sampling procedures, and the business cycle on the accuracy of bankruptcy prediction models. Misclassification can result in erroneous predictions leading to prohibitive costs to firms, investors and the economy. To test the impact of the choice of cut-off points and sampling procedures, three bankruptcy prediction models are assessed- Bayesian, Hazard and Mixed Logit. A salient feature of the study is that the analysis includes both parametric and nonparametric bankruptcy prediction models. A sample of firms from Lynn M. LoPucki Bankruptcy Research Database in the U. S. was used to evaluate the relative performance of the three models. The choice of a cut-off point and sampling procedures were found to affect the rankings of the various models. In general, the results indicate that the empirical cut-off point estimated from the training sample resulted in the lowest misclassification costs for all three models. Although the Hazard and Mixed Logit models resulted in lower costs of misclassification in the randomly selected samples, the Mixed Logit model did not perform as well across varying business-cycles. In general, the Hazard model has the highest predictive power. However, the higher predictive power of the Bayesian model, when the ratio of the cost of Type I errors to the cost of Type II errors is high, is relatively consistent across all sampling methods. Such an advantage of the Bayesian model may make it more attractive in the current economic environment. This study extends recent research comparing the performance of bankruptcy prediction models by identifying under what conditions a model performs better. It also allays a range of user groups, including auditors, shareholders, employees, suppliers, rating agencies, and creditors' concerns with respect to assessing failure risk.

Macroeconomic News and Exchange Rates: Evidence of Unstable Effect

Although the link between macroeconomic news announcements and exchange rates is well documented in recent literature, this connection may be unstable. By using a broad set of macroeconomic news announcements and high frequency forex data for the Euro/Dollar, Pound/Dollar and Yen/Dollar from Nov 1, 2004 to Mar 31, 2014, we obtain two major findings with regards to this instability. First, many macroeconomic news announcements exhibit unstable effects with certain patterns in foreign exchange rates. These news effects may change in magnitude and even in their sign over time, over business cycles and crises within distinctive contexts. This finding is robust because the results are obtained by applying a Two-Regime Smooth Transition Regression Model, a Breakpoints Regression Model, and an Efficient Test of Parameter Instability which are all consistent with each other. Second, when we explore the source of this instability, we find that global risks and the reaction by central bank monetary policy to these risks to be possible factors causing this instability.

The Compliance Costs of Taxes on Businesses and Individuals a Review of the Evidence

This Paper Reviews the Literature on the Compliance Costs Incurred by Businesses and Individuals Because of One Or More Taxes. It Presents Both the Main Characteristics, Such As Sample Size, Interview Techniques and So On, and the Key Findings of the Nineteen Studies Reviewed. in General, One Can Conclude That Simpler Taxes Lead to Lower Compliance Costs.

Why Have Aggregate Skilled Hours Become So Cyclical Since the Mid-1980's?

This paper documents and discusses a dramatic change in the cyclical behavior of aggregate hours worked by individuals with a college degree (skilled workers) since the mid-1980’s. Using the CPS outgoing rotation data set for the period 1979:1-2003:4, we find that the volatility of aggregate skilled hours relative to the volatility of GDP has nearly tripled since 1984. In contrast, the cyclical properties of unskilled hours have remained essentially unchanged. We evaluate the extent to which a simple supply/demand model for skilled and unskilled labor with capital-skill complementarity in production can help explain this stylized fact. Within this framework, we identify three effects which would lead to an increase in the relative volatility of skilled hours: (i) a reduction in the degree of capital-skill complementarity, (ii) a reduction in the absolute volatility of GDP (and unskilled hours), and (iii) an increase in the level of capital equipment relative to skilled labor. We provide empirical evidence in support of each of these effects. Our conclusion is that these three mechanisms can jointly explain about sixty percent of the observed increase in the relative volatility of skilled labor. The reduction in the degree of capital-skill complementarity contributes the most to this result.

The Effect of Public Spending on Consumption: Reconciling Theory and Evidence

Recent empirical evidence from vector autoregressions (VARs) suggests that public spending shocks increase (crowd in) private consumption. Standard general equilibrium models predict the opposite. We show that a standard real business cycle (RBC) model in which public spending is chosen optimally can rationalize the crowding-in effect documented in the VAR literature. When such a model is used as a data-generating process, a VAR estimated using the artificial data yields a positive consumption response to an increase in public spending, consistent with the empirical findings. This result holds regardless of whether private and public purchases are complements or substitutes.

Estimating Nonlinear DSGE Models by the Simulated Method of Moments

This paper studies the application of the simulated method of moments (SMM) for the estimation of nonlinear dynamic stochastic general equilibrium (DSGE) models. Monte Carlo analysis is employed to examine the small-sample properties of SMM in specifications with different curvature. Results show that SMM is computationally efficient and delivers accurate estimates, even when the simulated series are relatively short. However, asymptotic standard errors tend to overstate the actual variability of the estimates and, consequently, statistical inference is conservative. A simple strategy to incorporate priors in a method of moments context is proposed. An empirical application to the macroeconomic effects of rare events indicates that negatively skewed productivity shocks induce agents to accumulate additional capital and can endogenously generate asymmetric business cycles.

Caracterización de la utilización de innovación en el sector bancario: Una aproximación hacia la adquisición de ventajas competitivas

Investigación exploratoria mixta siguiendo un método deductivo con la que se logró caracterizar el grado de utilización de innovación en el sector bancario y su utilidad en la adquisición de ventajas competitivas con la ayuda de del modelo del Radar de Innovación.

How can strategic philanthropy contribute to innovation for companies

This investigation proposes to explore the existing link between a strategic conception of philanthropy and innovation. Indeed, the nature of the research question relies on an unexplored field in the CSR and Innovation management academic literature. It starts with the interest to know which the benefits are for a firm encouraged to invest strategically in philanthropy. In this regard, the analysis contributes in fitting this gap by following different objectives in an exploratory perspective. Throughout the research it will be analyzed the concept and the current and past contributions on the different branches of innovation (product innovation, managerial innovation, technological innovation), to accentuate the relation between an accurate strategic approach to philanthropy and the impact on the organizational value. Indeed, analyzing philanthropic innovation may provide insights about business opportunities and notions related to social investments and profit. That aspect includes the link between those strategic decisions that a firm can use to maximize those investments as it was part of their core business. It also proves the existing link between CSR and innovation, and the possibilities that the enterprises have towards this subject.

Aseguramiento para la población pobre: una herramienta de protección financiera

La financiación de los sistemas de salud en los países en desarrollo mediante esquemas de aseguramiento, presenta el desafío estructural de la informalidad de los mercados laborales. Ni el esquema de financiamiento comunitario ni el del subsidio a la oferta, parecen ofrecer una garantía de acceso a los grupos más vulnerables. Pero la extensión de esquemas de seguro subsidiado también implica mayores presiones sobre el gasto social. Este artículo es una revisión de la literatura sobre el tema, en el cual se revisan experiencias internacionales de los tipos mencionados, y se analiza su relevancia para Colombia.

Auge minero-energético, enfermedad holandesa e informalidad en Colombia: un análisis a partir de un modelo DSGE

El presente trabajo desarrolla un modelo macroeconómico de equilibrio general dinámico y estocástico (DSGE), con el fin de analizar los efectos macroeconómicos que se derivan de simular un choque positivo al componente estocástico de la productividad del sector minero-energético. Este hecho genera un aumento generalizado de los salarios en el sector formal y en el recaudo tributario, incrementando el consumo total de los miembros del hogar. Esto genera un incremento del precio de los bienes no transables relativo al precio de los bienes transables, disminuyendo la tasa de cambio real (apreciación) y provocando un desplazamiento de los recursos productivos, desde el sector transable (manufacturero) al no-transable, seguido de un aumento en el PIB y empleo formal de la economía. Esto hace que el sector formal agregado absorba trabajadores desde el sector informal a través del subsector formal no-transable, lo que disminuye el PIB informal. En consecuencia, el consumo neto de los miembros informales disminuye, lo que incentiva a que algunos miembros del hogar no se empleen en el sector informal y prefieran quedarse desempleados. Por lo tanto, el resultado final sobre el mercado laboral es una disminución de los trabajadores informales, de los cuales una parte se encuentra en el sector formal, y la parte restante está en condición de desempleo.

The welfare cost of macroeconomic uncertainty in the post-war period

Lucas (1987) has shown the surprising result that the welfare cost of business cycles is quite small. Using standard assumptions on preferences and a fully-áedged econometric model we computed the welfare costs of macroeconomic uncertainty for the post-WWII era using the multivariate Beveridge-Nelson decomposition for trends and cycles, which considers not only business-cycle uncertainty but also uncertainty from the stochastic trend in consumption. The post-WWII period is relatively quiet, with the welfare costs of uncertainty being about 0:9% of per-capita consumption. Although changing the decomposition method changed substantially initial results, the welfare cost of uncertainty is qualitatively small in the post-WWII era - about $175.00 a year per-capita in the U.S. We also computed the marginal welfare cost of macroeconomic uncertainty using this same technique. It is about twice as large as the welfare cost ñ$350.00 a year per-capita.

The welfare cost of macroeconomic uncertainty in the post-war period

With standard assumptions on preferences and a fully-fledged econometric model we computed the welfare costs of macroeconomic uncertainty for post-war U.S. using the BeveridgeNelson decomposition. Welfare costs are about 0.9% per-capita consumption ($175.00) and marginal welfare costs are about twice as large.

Estrutura a termo da taxa de juros no Brasil e previsibilidade de ciclos econômicos

O objetivo deste trabalho é caracterizar a Curva de Juros Mensal para o Brasil através de três fatores, comparando dois tipos de métodos de estimação: Através da Representação em Espaço de Estado é possível estimá-lo por dois Métodos: Filtro de Kalman e Mínimos Quadrados em Dois Passos. Os fatores têm sua dinâmica representada por um Modelo Autorregressivo Vetorial, VAR(1), e para o segundo método de estimação, atribui-se uma estrutura para a Variância Condicional. Para a comparação dos métodos empregados, propõe-se uma forma alternativa de compará-los: através de Processos de Markov que possam modelar conjuntamente o Fator de Inclinação da Curva de Juros, obtido pelos métodos empregados neste trabalho, e uma váriavel proxy para Desempenho Econômico, fornecendo alguma medida de previsão para os Ciclos Econômicos.

Modelos de ciclos reais de negócios aplicados à economis brasileira

O objetivo deste trabalho é testar modelos clássicos de real business cycles para a economia brasileira. Em um primeiro estágio busca-se fatos estilizados, o que foi feito através da escolha de séries adequadas e da separação dos componetes cíclicos e da análise dos ciclos resultantes. Os parâmetros dos diversos modelos foram estimados utilizando o Método Generalizado dos Momentos (MGM). Estes parâmetros foram utilizados para construir diversas economias artificiais que, após simulação, foram confrontadas com os dados da economia brasileira. Entre todos testados, o modelo que melhor se adequou aos dados foi de cash in advance com taxação distorciva. Entretanto, alguns fatos estilizados importantes, como por exemplo o excesso de volatilidade do consumo, não foram adequadamente reproduzidos pelos modelos testados.