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totales del petróleo intemperizados en suelos y sedimentos (Biodegradation modeling of sludge bioreactors of total petroleum hydrocarbons weathering in soil and sediments)

This study combines three rounds of surveys with remote sensing to measure long-term impacts of a randomized irrigation program in the Dominican Republic. Specifically, Landsat 7 and Landsat 8 satellite images are used to measure the causal effects of the program on agricultural productivity, measured through vegetation indices (NDVI and OSAVI). To this end, 377 plots were analyzed (129 treated and 248 controls) for the period from 2011 to 2019. Following a Differencein-Differences (DD) and Event study methodology, the results confirmed that program beneficiaries have higher vegetation indices, and therefore experienced a higher productivity throughout the post-treatment period. Also, there is some evidence of spillover effects to neighboring farmers. Furthermore, the Event Study model shows that productivity impacts are obtained in the third year after the adoption takes place. These findings suggest that adoption of irrigation technologies can be a long and complex process that requires time to generate productivity impacts. In a more general sense, this study reveals the great potential that exists in combining field data with remote sensing information to assess long-term impacts of agricultural programs on agricultural productivity.

The need to enhance food security while reducing poverty along with the growing threat imposed by climate change clearly reveal that it is imperative to accelerate agricultural productivity growth. This paper estimates micro-level production models to identify the major factors that have contributed to productivity growth in El Salvador, including irrigation, purchased inputs, mechanization, technical assistance, and farm size, among others. The econometric framework adopted in this investigation is grounded on recent panel data stochastic production frontier methodologies. The results obtained from the estimation of these models are used to calculate Total Factor Productivity (TFP) change and to decompose such change into different factors, including technological progress, technical efficiency (TE), and economies of scale. The findings imply that efforts are needed to improve productivity in both technological progress and technical efficiency where the latter is a measurement of managerial performance. This in turn indicates that resources should be devoted to promoting the adoption and diffusion of improved technologies while enhancing managerial capabilities through agricultural extension.

Este análisis de seguimiento complementa los resultados obtenidos en el estudio: “Retos para la Agricultura Familiar en el contexto del COVID-19: Evidencia de Productores en ALC”. Para esto, se recolectó información de la misma muestra analizada para los meses de Febrero a Mayo pero esta vez para el período comprendido entre Agosto y Noviembre del 2020. Específicamente, esta Fase 2 del análisis busca identificar los problemas que han persistido o se han acentuado en la agricultura familiar de ALC a causa de la pandemia, así como medir el nivel de inseguridad alimentaria de los pequeños productores. Los resultados de este estudio muestran que la mayoría de los agricultores familiares se encuentran en una situación de inseguridad alimentaria y que varios de los problemas encontrados en la Fase 1 de la encuesta persisten 6 meses después del inicio de la pandemia. Específicamente, la continua exposición a la crisis parece haber incrementado los efectos negativos sobre la producción agropecuaria y los ingresos de los hogares rurales.