Implementación de cópulas para la estimación del valor en riesgo

La dependencia entre las series financieras, es un parámetro fundamental para la estimación de modelos de Riesgo. El Valor en Riesgo (VaR) es una de las medidas más importantes utilizadas para la administración y gestión de Riesgos Financieros, en la actualidad existen diferentes métodos para su estimación, como el método por simulación histórica, el cual no asume ninguna distribución sobre los retornos de los factores de riesgo o activos, o los métodos paramétricos que asumen normalidad sobre las distribuciones. En este documento se introduce la teoría de cópulas, como medida de dependencia entre las series, se estima un modelo ARMA-GARCH-Cópula para el cálculo del Valor en Riesgo de un portafolio compuesto por dos series financiera, la tasa de cambio Dólar-Peso y Euro-Peso. Los resultados obtenidos muestran que la estimación del VaR por medio de copulas es más preciso en relación a los métodos tradicionales.

Parametric pension reform and the intensive margin of labor supply, evidence from Colombia

We analyze the effect of a parametric reform of the fully-funded pension regime in Colombia on the intensive margin of the labor supply. We take advantage of a threshold defined by law in order to identify the causal effect using a regression discontinuity design. We find that a pension system that increases retirement age and the minimum weeks during which workers must contribute to claim pension benefits causes an increase of around 2 hours on the number of weekly worked hours; this corresponds to 4% of the average number of weekly worked hours or around 14% of a standard deviation of weekly worked hours. The effect is robust to different specifications, polynomial orders and sample sizes.

Productivity growth in electric energy retail in Colombia. A bootstrapped malmquist indices approach

This paper offers a productivity growth estimate for electric energy commercialization firms in Colombia, using a non-parametric Malmquist bootstrap methodology. The estimation and methodology serve two main purposes. First, in Colombia Commercialization firms are subject to a price-cap regulation scheme, a non-common arrangement in the international experience for this part of the industry. Therefore the paper’s result suggest an estimate of the productivity factor to be used by the regulator, not only in Colombia but in other countries where commercialization is a growing part of the industry (renewable energy, for instance). Second, because of poor data collection from regulators and firms themselves, regulation based on a single estimation of productivity seems inappropriate and error-prone. The nonparametric Malmquist bootstrap estimation allows an assessment of the result in contrast to a single one estimation. This would open an opportunity for the regulator to adopt a narrower and more accurate productivity estimation or override an implausible result and impose a productivity factor in the price-cap to foster the development of the industry.