Understanding import diversification: an empirical analysis

This paper analyzes import diversification in an aggregated perspective -- Using a dataset for 60 countries covering the period 1995-2010, we study the main determinants of import diversification -- We expect to contribute to the current literature, taking into account that there have been few empirical studies addressing import diversification and more specifically, at the cross-country level -- We take into account variables classified into four categories: Structural factors, macroeconomic factors, international trade factors and political factors -- We find robust evidence that total factor productivity (TFP), capital stock, real Exchange rates and terms of trade are key drivers of import diversification -- On the other hand, domestic consumption and trade openness exert an effect leading to import concentration -- We interpret this finding, taking into account the theoretical framework provided by the international trade and growth theories

Empirical evidence of S-curves in the Colombian

The Marshall-Lerner condition, the J-curve and S-curve have emerged as theoretical and empirical foundations developed for the study of the interaction between exchange rates and international patterns of bilateral trade -- They have a significant bearing on thedevelopment of public policy, and are of equal interest to the academic and professional communities -- The most recently developed of these theories, the S-Curve, is named after the theorized short-run behavior to be found in the cross-correlation function of the real exchange rate and the trade balance -- Considering this theoretical context, the paper seeks empirical evidence of the existence of the S-Curve in the bilateral trade in commodity and non-commodity goods between Colombia and the United States and Venezuela, its main trading partners, for the yearly quarters between 1994:1 and 2009:4

Mining and Energy Boom, Dutch Disease and Informality in Colombia: a DSGE Approach

The paper develops a Dynamic Stochastic General Equilibrium (DSGE) model, which assesses the macroeconomic and labor market effects derived from simulating a positive shock to the stochastic component of the mining-energy sector productivity. Calibrating the model for the Colombian economy, this shock generates a whole increase in formal wages and a raise in tax revenues, expanding total consumption of the household members. These facts increase non-tradable goods prices relative to tradable goods prices, then real exchange rate decreases (appreciation) and occurs a displacement of productive resources from the tradable (manufacturing) sector to the non-tradable sector, followed by an increase in formal GDP and formal job gains. This situation makes the formal sector to absorb workers from the informal sector through the non-tradable formal subsector, which causes informal GDP to go down. As a consequence, in the net consumption falls for informal workers, which leads some members of the household not to offer their labor force in the informal sector but instead they prefer to keep unemployed. Therefore, the final result on the labor market is a decrease in the number of informal workers, of which a part are in the formal sector and the rest are unemployed.

Value at Risk (VaR) en empresas del sector real en Colombia: caso, Bogotá ELEKTRIKA

La estimación y gestión del riesgo con la evolución del mercado ha tomado gran relevancia, principalmente en el sector financiero y de capitales, no obstante las variables macroeconómicas que afectan el riesgo en el tiempo son cada vez más volátiles y generan un mayor nivel de incertidumbre; se puede presentar en igual medida o con un mayor impacto en empresas del sector real, principalmente en aquellas cuyas condiciones de valoración causan un mayor impacto para los inversionistas, tal es el caso de las Asociaciones Público Privadas, mecanismos de contratación que vinculan al sector privado con el público en el desarrollo de proyectos de mayor nivel, donde se requiere establecer la valoración y cuantificación del riesgo que cada una de las partes está dispuesto a asumir -- Hoy por hoy existen métodos de medición sofisticados que permiten la estimación del Value at Risk (VaR), los cuales han sido desarrollados principalmente por el sistema financiero, sin contar con una aplicación en el sector real -- Es por eso que surge la necesidad de esta investigación para obtener una metodología que permita estimar el VaR bajo los conceptos teóricos de economía, estadística y simulación