AERE Reading Group Seminar series | The Mismeasure of Weather: Using Remotely Sensed Weather in Economic Contexts by Jeffrey Michler
Invites you to an AERE Reading Group seminar
University of Arizona
The Mismeasure of Weather:
Using Remotely Sensed Weather in Economic Contexts.
Tuesday 11 April 2023
11:00pm – 12:00pm
Zoom: 848 9750 5196
Abstract: The availability of weather data from remote sensing products has greatly reduced the cost of including rainfall, temperature, and other weather variables into econometric models. Weather variables are a common instrumental variable to predict a wide variety of economic outcomes. They are also an important input into modelling crop yields for rainfed agriculture. The frequent use of remote sensing weather data in econometric applications has only recently been met with a critical assessment of the suitability and quality of this data in economics. We quantify the significance and magnitude of the effect of measurement error in remote sensing weather data in the context of smallholder agricultural productivity. The analysis leverages 17 rounds of nationally-representative, panel household data from six countries in Sub-Saharan Africa. Guided by a pre-analysis plan, we produce 90 linked weather-household datasets that vary by the remote sensing weather product. By varying the data, along with the econometric model, we quantify the magnitude and significance of measurement error coming from different remote sensing measurement technologies. We find substantial amounts of non-classical measurement error based on remote sensing products. In extreme cases, the data drawn from different remote sensing products result in opposite signs for coefficients on weather metrics, meaning that precipitation or temperature drawn from one product purportedly increases crop output while the same metrics drawn from a different product purportedly reduces crop output. This finding has practical implications for the use of remote sensing weather data in econometric applications, as researchers can essentially show any relationship between weather and an outcome of interest simply by judicially choosing the “right” remote sensing weather product. We conclude with a set of best practices for researchers looking to use remote sensing weather data in economic contexts.
For further information contact: AERE Reading Group Seminar Coordinator Alastair Fraser (firstname.lastname@example.org)