- For the agricultural variables, we focus on the “main” (or long) growing season of each country, that is, the datasets contain agricultural inputs and outputs that were used and produced during the main agricultural season. As such, the minor agricultural seasons, for the surveys sometimes record agricultural production data, are not covered in the HP. The exception is Uganda, which has a bimodal rainfall pattern in many areas. Here, two growing seasons are observed in each survey wave.

- The plot and plot-crop datasets contain only plots observations for years in which (i) they are cultivated in the long or main growing season and (ii) they contain a recorded harvest quantity for at least one crop. Perennial crops such as fruit or tree crops are excluded from the dataset. A harvest quantity of zero is only included if there is recorded evidence of an exogenous shock on the plot, such as a natural disaste <mark>r. Other cases, such as non-response, are dropped from the dataset. A</mark> s a result, the plot and plot-crop samples contain a subset of all the plots listed in raw data.

- <mark>A set of key agricultural input and output variables are valued both in LCUs as well as US dollars, to facilitate cross-country analysis. The valuation consists of calculating the sale or purchase price of the various categories of each input and output variable in each wave. Precise crop variety categories such as maize or teff are used for the calculation of output values. Categories of fertilizer types are used to calculate inorganic fertilizer prices, categories of men, women and children workers are used to calculate hired labor wages, and categories of crop types and improved status of seeds are used to calculate seed values. To account for the highly noisy nature of the price estimates, median EA-level input and output prices are calculated within each category (e.g. median EA-level maize price per kg, median hourly wage of male agricultural workers). If the number price observations are below a threshold of 10, median prices are calculated across the next larger administrative unit. If the number of observations in that larger administrative unit is also below 10, the next larger unit is chosen, and this process is repeated up to the national level. The prices are then multiplied by the output and input quantities recorded on the plot, which have themselves been converted to standardized quantity units such as kilograms. The resulting variables are in local currency units (LCUs). We provide another set of variables which are converted into USD using an exchange rate at the year of the survey and deflated to 2020 dollars values. T</mark> he CPI and exchange rate data are drawn from <mark>World Bank collections of development indicators and consist of yearly time series, made available through the World Bank Open Data Initiative.</mark>

- “Main crop” types are defined to facilitate inter-country comparisons with the plot-level dataset. Each crop is classified into the following categories: barley, wheat, rice, sorghum, maize, millet, perennials (including fruit and tree crops), legumes, root crops, nuts and a catch-all “other” category. In case users want to define their own categories, the exact names of the crops (i.e., as they appear in the raw data) are maintained in the plot-crop dataset.

- The plot-level dataset in Uganda is effectively at the _parcel_ level, as GPS measurements were obtained at this level of granularity. This also allows users to merge across seasons, since parcels

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