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This paper analyzes the dynamics of the labor market in Latin America during the COVID-19 pandemic. After a decade of a virtuous circle of growth with the creation of formal jobs, the pandemic has had an considerable impact on the region’s labor market, generating an unparalleled increase in the proportion of the inactive population, considerable reductions in informality, and, in contrast, smaller fluctuations in formal jobs. In this context, the formal sector, given its lower flexibility, became a "social safety net" that preserved the stability of employment and wages. Based on the findings presented in this paper, it is projected that, starting in 2021, informality will grow to levels higher than those of the pre-COVID-19 era–with 7.56 million additional informal jobs–as a result of the population returning to the labor market to compensate for the declines in incomes. According to the simulations presented, postponing or forgiving income tax payments and social security contributions conditional on the generation of formal jobs could reduce the growth of informality by 50 to 75 percent. Achieving educational improvements has the potential to reduce it by 50 percent.

Fitting Susceptible-Infected-Recovered (SIR) models to incidence data is problematic when not all infected individuals are reported. Assuming an underlying SIR model with general but known distribution for the time to recovery, this paper derives the implied differential-integral equations for observed incidence data when a fixed fraction of newly infected individuals are not observed. The parameters of the resulting system of differential equations are identifiable. Using these differential equations, we develop a stochastic model for the conditional distribution of current disease incidence given the entire past history of reported cases. We estimate the model parameters using Bayesian Markov Chain Monte-Carlo sampling of the posterior distribution. We use our model to estimate the transmission rate and fraction of asymptomatic individuals for the current Coronavirus 2019 outbreak in eight American Countries: the United States of America, Brazil, Mexico, Argentina, Chile, Colombia, Peru, and Panama, from January 2020 to May 2021. Our analysis reveals that the fraction of reported cases varies across all countries. For example, the reported incidence fraction for the United States of America varies from 0.3 to 0.6, while for Brazil it varies from 0.2 to 0.4.

Generally, research and studies about commodities focus on price trends, analysis in terms of international competitiveness, market position structure, rate of net exports, market share, and concentration index. This paper has developed an analysis of the most influential agricultural commodities traded from Colombia to European Union, which are bananas, coffee, and palm oil. Analyzing the economic and commercial effects in two traditional agricultural commodities from Colombia (bananas and coffee) with the rise of palm oil as a commodity in the trade relation with its partner; the European Union. The structure draws from the overview of general aspects and the behavior of Colombian foreign trade, as diversification of export products and trade partners, to focus on the characteristics of the trade relationship between the European Union and Colombia. The aim is analyze the proportional relation between bananas, coffee, and palm oil exported to the EU, according to three indicators, the volume of production, exports share, and trade value, from 2008 until 2019, identifying the trends before and after the implementation of the free trade agreement. Finally, with the coefficient correlation, determine the agricultural commodity that has the strongest and positive relationship with the total agricultural exports value from Colombia to the European Union.