DOI: 10.5281/zenodo.5796561
title: Household Survey - Impacts of large-scale land acquisitions on smallholder agriculture and livelihoods in Tanzania

description: <strong>** Article & Dataset Currently Under Review **</strong> <strong>Dataset Overview</strong> Our household dataset is associated with a pre-print article "Impacts of large-scale land acquisitions on smallholder agriculture and livelihoods in Tanzania". The household survey is designed for the purposes of policy evaluation with selection of households based on proximity to large-scale land acquisitions (treatment) and a set of households in similar socio-ecological contexts with no association to large-scale land acquisitions (control). Households were selected as a random sample in 35 villages surrounding LSLAs who provided responses to a questionnaire covering household income, assets, farming practices, health, food-security, and energy-use. Two datasets are provided. First, the "hh_dataset_rep.csv" providing household responses for variables used in this study. Second, the "hh_crops_rep.csv" provides detail on crops cultivated by each household, self-reported yields and farm-gate prices. Each variable is described in the "variable_descriptoin.xlsx". In addition to the datasets, we provide replication code for this study "lsla_mechanisms_rep.Rmd" as an R-Markdown file. <strong>Article Abstract</strong> Improving agricultural productivity is a major sustainability challenge of the 21<sup>st</sup> century. Large-scale land acquisitions (LSLAs) have important effects on both well-being and the environment in the Global South, but their impacts on agricultural productivity and subsequent effects on farm incomes or food-security are under-investigated. Prior studies lack data or methods to investigate the mechanistic nature of household change in agricultural practices that may vary due to LSLA conditions. To overcome this challenge, we use a novel household dataset and a quasi-experimental design to estimate household level changes in agricultural value driven by LSLAs in Tanzania. In addition, we use a causal mediation analysis to assess how contract farming arrangements, land loss, and adoption of new farming technologies around LSLAs influence agricultural productivity. We find that households near LSLAs produced 19.2% (95% CI: 3.5 – 37.2%) higher agricultural value, primarily due to increased crop prices and farmer selection of high-value crops. Importantly, effect sizes are positively and negatively mediated by different mechanisms. The presence of contract farming explains 18.1% (95% CI: 0.56%, 47%) of the effect size in agricultural value, whereas land loss reduces agricultural value by 26.8% (95% CI: -71.3%, -4.0%). We also estimate whether improvements in food-security and household incomes occur in proximity to LSLAs, as anticipated with higher agricultural value. However, we do not find increases in agricultural income and food security, which may be due to higher crop prices in proximity to LSLAs. Our results stand in contrast to assumptions that technological spillovers occur through LSLAs and are principal drivers of agrarian change, holding important implications for agricultural transformations. Instead access to output markets through contract farming enables greater agricultural value whereas land loss negatively affects the agricultural value of households. Governance strategies should focus on limiting negative impacts related to the loss of smallholder land rights enabling greater access to contract farming.