Agronomic Weather Measures in Econometric Models of Crop Yield with Implications for Climate Change

By Michael J. Roberts, W. Schlenker, Jonathan Eyer. 2013

194 citations recorded by the source corpus.

Subfields: Ecology, Evolution, Behavior and Systematics, General Agricultural and Biological Sciences, Soil Science

View Paper: https://www.semanticscholar.org/paper/73a93c4a9b378418f6539cf8439a7da8e5c22ea0

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Ecology, Evolution, Behavior and Systematics

1. Andrew Crane-Droesch
2. Minpeng Chen
3. Junjie Zhang
4. Peng Zhang

In General Agricultural and Biological Sciences

1. Andrew Crane-Droesch
2. Minpeng Chen
3. Junjie Zhang
4. Peng Zhang

In Soil Science

1. Andrew Crane-Droesch
2. Minpeng Chen
3. Junjie Zhang
4. Peng Zhang

Citations in the corpus

• Temperature and Human Capital in India (2020, unknown): “11Our results are robust to excluding indicators for rainfall and humidity (Roberts, Schlenker and Eyer, 2013).”
• Economic Impacts of Climate Change on Agriculture: The Importance of Additional Climatic Variables Other than Temperature and Precipitation (2017, methodology): “Following Roberts et al. (2012), we calculate average humidity during the two warmest months–July and August–for rice and corn.”
• Machine learning methods for crop yield prediction and climate change impact assessment in agriculture (2018, methodology): “Indeed, work has indicated important roles for VPD and soil moisture (Roberts et al 2012, Lobell et al 2013, Anderson et al 2015, Urban et al 2015) in explaining and building upon the baseline parametric specification.”