Sistema Regional de Información
en línea para Revistas Científicas de América Latina,
el Caribe, España y Portugal

This paper examines the importance of principals/headteachers in the effectiveness of schools, and aims to contribute to the growing body of literature in this area. The research focuses on a developing country and uses panel data taken from the Young Lives Program in Peru and its School Survey. Educational production functions are used to estimate the impact of principals on the scores of fourth-grade students in mathematics and language. The findings of this study support the international evidence on the importance of principals in school effectiveness, especially in terms of supervision and monitoring.

In this paper we attempt to establish a baseline to understand the profitability of the Pomada fleet that operates in Posorja, province of Guayas in Ecuador, under different policy scenarios. For that purpose, we use primary and secondary data collected from 2008 to 2014. We estimate both the maximum sustainable yield (MSY) and the maximum economic yield (MEY) for the Pomada shrimp fishery. We found that the individual daily catch quota, which was established in 2013 by the same Pomaderos for the Pomada shrimp fishery, is likely to be beyond the sustainable limits by about 750 Kgs.  We discuss how to implement fishery management policies using either MSY or MEY as references. We also simulate how alternative total allowable catch policies could affect the profitability and financial risk of the fishing fleet. Finally, some recommendations are provided to improve the process of data collection, as well as improvements to the methodology, to increase the accuracy, reliability and sophistication of the estimation of both MSY and MEY

The aim of this work is to present a methodology that allows in a simple way to compute the regulatory capital for credit risk. The Vasicek model is a popular one-factor model that derives the limiting form of the portfolio loss. This model will allow calculating different risk measures such as, for example, the expected loss (EL), the value at risk (VaR) and the Expected Shortfall (ES). Due to the difficulty of obtaining real data, simulated data were used. For this study, three different portfolios were proposed: the first was a homogeneous portfolio that had the same weighting among all loans, then a portfolio with unequal weights was considered and finally a mixed portfolio with different weights and different probabilities of default was used. Monte Carlo simulation with 100.000 scenarios served as our benchmark. It was observed that the Vasicek model correctly estimates the results of the homogeneous portfolio. On the other hand, when the portfolio is not homogeneous (portfolio unequal weights and mixed) the Vasicek model correctly estimates the mean (Expected Losses) but underestimates the Value at Risk and the Expected Shortfall. This is because the approximation of the Vasicek model is good on average but not at the extremes.

In this article, we analyze the behavior of the BNDES’ disbursements, investments in machinery and equipment, and the growth rate, from 1953 to 2013. We find that investments in machinery and equipment lead the BNDES’ disbursements through an Error Correction Model (ECM). Also, we show that the BNDES positively affected investment and growth during long-term economic expansions (procyclical performance) and contributed positively to investment but not to growth during long-term economic recessions.

This paper analyzes the financial structure of 162 iberoamerican companies for the period 2009 to 2015. Through multiple regression model is to determine which variables explain the structure of indebtedness of companies in 7 countries (Argentina, Brazil, Chile, Colombia, Spain, Mexico and Peru), in addition to an analysis performed by the main economic sectors. The results overwhelmingly support trade-off theory.

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EJERCICIO

Debido a las altas expectativas de inflación, el Banco Nacional de Serbia ha elegido la estabilidad de precios como el objetivo principal de la política monetaria y la tasa de política clave como el principal instrumento de regulación monetaria. Sin embargo, a pesar de la regla de Taylor claramente definida, la tasa de política clave no siempre sigue el movimiento de la tasa de inflación. En consecuencia, el objetivo de este estudio es evaluar los efectos de la tasa de inflación en la tasa clave de política y la posibilidad de utilizar la regla de Taylor en las condiciones originales de baja inflación. Con base en el objeto definido de la investigación, probamos la siguiente hipótesis: la tasa de inflación tuvo un impacto estadísticamente significativo en la tasa de política clave en todo el período analizado, entre 2007 y 2015. La misma observación se probó para dos subperíodos entre 2007 y 2011 y entre 2012 y 2015. Por lo tanto, se puede concluir que existe un impacto medio estadísticamente significativo de la tasa de inflación en la tasa de política clave, pero la representatividad del modelo podría ser mayor. La falta de reacción de la tasa clave de política monetaria a la inflación enfatiza la necesidad de redefinir los instrumentos de política monetaria y modificar la estrategia de metas de inflación.

Esta investigación busca ampliar la comprensión de la influencia de los 5 Grandes Rasgos de Personalidad en las dimensiones del emprendimiento social (visión social, sostenibilidad, redes sociales, innovación y retorno financiero) para el caso de los emprendedores sociales argentinos y peruanos. Estudios previos han empleado muestras de estudiantes y, mayormente se han enfocado en contextos ajenos al Latinoamericano. Este estudio es original en la medida que analiza una muestra única de empresarios sociales que operan en países donde el emprendimiento social, si bien considerado valioso, no ha sido investigado en profundidad.  Se recopilaron datos de 109 empresarios sociales peruanos y argentinos a través de cuestionarios en línea. Se realizó un análisis factorial exploratorio separado para las variables dependientes y las independientes. Los hallazgos indican que el rasgo Afabilidad es el más influyente en las dimensiones del emprendedor social. El rasgo Apertura influye positiva y significativamente en las dimensiones Creación de redes sociales e Innovación. El rasgo Extraversión influye positivamente en las dimensiones Creación de redes sociales y Retorno financiero. Finalmente, el rasgo Neuroticismo influye significativa y negativamente en la dimensión redes sociales. Además, se encontraron diferencias entre las muestras peruanas y argentinas, que podrían derivarse del contexto cultural y económico.

Effective assessment of a borrower's various credit indexes is key for unravelling the problem of information asymmetry in the context of Peer-to-Peer Lending (P2P). Mitigating adverse selection of high default potential borrowers continues to plague P2P lending platforms. In order to understand which factors determine borrower credit status (ie. loan approval, loan repayment potential, risk of default), this study renders an Artificial Neural Network Model on one of the most popular P2P lending platforms. Our results show that the interest rate, the ratio of loan to income and the loan term are the most important indicators in reflecting the borrower’s credit status, while the frequency of inquiries, the borrowing category have a relatively low degree of importance. This study finds that the borrower’s credit index status is better explained at the lower quantiles and becomes more difficult to discern at higher quantiles. This work also finds that for longer loan terms, the borrower repayment pressure and the default rates rise with higher loan-to-income ratios and higher interest rates. Additionally, we find that higher credit rankings and higher expected returns lead to higher probabilities of defaulting. To reduce the probability of borrower default, this study recommends building lending groups or lending pools, selecting higher income credit candidates and increasing credit limits. To validate our results, we perform robustness tests that modify the learning coefficient and the training-to-validation data ratio in order to show that the empirical results of this paper are robust and effective.