2018/19 that started a new panel. Unlike in Ethiopia, in Nigeria the refresh was partial, with the survey continuing to track 1,425 of the original households. Because there is not yet a second round of data for the refreshed households, we exclude them from the analysis Data cleaning and removal of non-agricultural households yields 9,145 observations from 3,412 distinct households across four survey waves.

In Tanzania, the data come from the 2008/09, 2010/11, 2012/13, 2014/15, 2019/20, and 2020/21 rounds of the Tanzania National Panel Survey (TZNPS) (TNBS, 2011; TNBS, 2012; TNBS, 2015; TNBS, 2017; TNBS, 2021; TNBS, 2023). The sample is representative for the nation, and provides estimates of key socioeconomic variables for mainland rural areas, Dar es Salaam, other mainland urban areas, and Zanzibar. As in Nigeria, the fourth wave (2014/15) was a partial refresh, with data being collected from a sub-sample of the original panel households (known as the extended panel) plus the addition of completely new households (known as the refresh panel). The extended panel households were re-interviewed in 2019/20 in what is known as the Sex-Disaggregated Data, which added improved individual-level data. The refresh panel was followed up with in 2020/21. The 2020/21 survey round also included a booster sample, that will continue to be followed in subsequent rounds. However, since at this time there is only one round of observations for the booster sample, we exclude them from the analysis. Focusing on rural, crop producing households we have 9,916 observations from 4,804 distinct households across five survey waves.

In Uganda, we use the data from the 2009/10, 2010/11, 2011/12, 2013/14, 2015/16, and 2019/20 rounds of the Uganda National Panel Survey (UNPS) (UBOS, 2012; UBOS, 2014a; UBOS, 2014b; UBOS, 2016; UBOS, 2019; UBOS, 2021). The original households were followed for three waves and then starting in 2013/14, a subset of households were cycled out and replaced with new households. This continuous, partial refresh process means that households remain in the sample for different lengths of time, though by 2019/2020 all of the original households have been replaced. The original sample, as well as the refresh, was designed to be representative at the national-, urban/rural- and regional-level. Focusing on rural, crop producing households we have 11,692 observations from 4,003 distinct households across six survey waves.

For the analysis, we combine data from the six countries and all waves to generate a single cross-country panel dataset which includes 54,237 observations from 23,705 distinct households. For estimation, we include two measures of agricultural productivity: yield (kg/ha) of the primary cereal crop and the value (2015 USD/ha) of all seasonal crop productivity on the farm. Summary statistics for these outputs as well as measured input are in Table A3 in the Appendix.

# **3.3 Descriptive Statistics**

Our pre-analysis plan specifies that we will examine 22 different ways to measure precipitation and temperature. These variables and definitions are presented in Table A1 in the Appendix Section 6. For parsimony, we focus all of our analysis in the paper on only four of these 22 variables: (1) total 11