A global panel dataset of agricultural technology intensity and rural social welfare indicators, 2000–2020

This dataset describes a balanced country–year panel dataset assembled to support econometric analysis of the relationship between agricultural technology adoption and rural social welfare outcomes. The panel covers 142 countries over the period 2000–2020 (2,925 observations) and is structured around the Agricultural Technology Intensity Index (ATII), a composite measure derived as the first principal component of four standardised technology sub-indicators: agricultural tractor density (tractors per 1,000 ha arable land), fertilizer intensity (kg per ha arable land), pesticide application (tonnes per 1,000 ha cropland), and irrigated-area share (% of cropland). The ATII explains approximately 50% of the joint variation in these four indicators (PC1 eigenvalue ≈2.00). Social welfare outcomes include the prevalence of moderate or severe food insecurity (FIES, 2015–2020), rural poverty headcount ratio (at the $3.65/day 2017 PPP threshold), agricultural employment share, and log agricultural value added per worker. Five control variables capturing country-level economic and structural conditions are included alongside World Bank income-group and regional classifications for all 142 countries. Raw data are retrieved automatically from four freely accessible APIs (FAOSTAT, World Bank WDI, World Bank PIP, and ILO ILOSTAT) via a documented Python pipeline. An R analysis script implementing two-way fixed-effects regression, Callaway–Sant'Anna (2021) continuous difference-in-differences estimation with treatment cohort discretisation, and instrumental-variables (2SLS) estimation is provided alongside the dataset. The deposit enables full replication of all results reported in the associated research article and supports independent secondary analyses across agricultural economics, development economics, and food-systems research.