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This is the Stata code and public version of the data used in Bena, Ortiz-Molina, and Simintzi "Shielding Firm Value: Employment Protection and Process Innovation", forthcoming at the Journal of Financial Economics. THIS DATASET IS ARCHIVED AT DANS/EASY, BUT NOT ACCESSIBLE HERE. TO VIEW A LIST OF FILES AND ACCESS THE FILES IN THIS DATASET CLICK ON THE DOI-LINK ABOVE

This dataset is a cross-country convenience sample of primary data measuring crop production and/or area by farm size for 55 countries (representing ~50% of global agricultural production). The harmonized dataset is nationally representative but at subnational resolution, sourced from both agricultural censuses and household surveys. The median year of the data is 2013, with a range from 2001 to 2015. The dataset covers 154 crop species and 11 farm size classes (0-1 ha, 1-2 ha, 2-5 ha, 5-10 ha, 10-20 ha, 20-50 ha, 50-100 ha, 100-200 ha, 200-500 ha, 500-1000 ha, and >1000 ha), and is ontologically interoperable with other global agricultural datasets, such as the Food and Agricultural Organization’s statistical database (FAOSTAT), and the World Census of Agriculture. The data set includes estimates of the quantity of food, feed, processed agricultural commodities, seed, waste (post-harvest loss), or other uses; and potential human nutrition (i.e. kilocalories, fats, and proteins in grams per capita) generated by each farm size class. We explain the details of the data set, the inclusion criteria used to assess each data source, the data harmonization procedures, and the spatial coverage. We detail assumptions underlying the construction of this dataset, including the use of aggregate field size as a proxy for farm size, and crop species omission biases resulting from converting local species names to harmonized names. We also provide bias estimates for commonly used methods for estimating food production by farm size: use of constant yields across farm size classes when crop production is not available, and relying on nationally representative household sample surveys that omitted non-family farms. Together this data set represents the most complete empirically grounded estimate of how much food and nutrition smallholder farmers produce from crops.