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This paper quantifies the significance and magnitude of the effect of measurement error in satellite weather data in the analysis of smallholder agricultural productivity. The cross-country analysis leverages multiple rounds of georeferenced, nationally-representative, panel household survey data that have been collected over the last decade. These data are spatially-linked with a range of geospatial weather data sources and related metrics. The goal is to provide systematic evidence on obfuscation methods, satellite data source, and weather metrics in order to determine which of these elements have strong predictive power over a large set of crops and countries and which are only useful in highly specific settings.
Agriculture is arguably the most climate-sensitive sector of the economy. Growing concerns about anthropogenic climate change have increased research interest in assessing its potential impact on the sector and in identifying policies and adaptation
Literature about the scholarly impact of scientific research offers very few contributions on private sector research, and the comparison with public sector. In this work, we try to fill this gap examining the citation-based impact of Italian 2010-20
This paper examines how subsistence farmers respond to extreme heat. Using micro-data from Peruvian households, we find that high temperatures reduce agricultural productivity, increase area planted, and change crop mix. These findings are consistent
In this paper we study the impact of errors in wind and solar power forecasts on intraday electricity prices. We develop a novel econometric model which is based on day-ahead wholesale auction curves data and errors in wind and solar power forecasts.
Agricultural research has fostered productivity growth, but the historical influence of anthropogenic climate change on that growth has not been quantified. We develop a robust econometric model of weather effects on global agricultural total factor