Two Stage Least Square Model Output for Climate-Smart Agriculture and Poverty in Ethiopia

An econometric model output investigating the effect of Climate-Smart Agriculture adoption on multidimensional poverty reduction. The data is based on a cross-sectional survey of 416 smallholder farmers in the Siltie Zone, Central Ethiopia, using GSEM, 2SLS, and PSM analytical approaches. The dataset was authored by Jemil Yasin Shifa and last updated on May 4, 2026.

Use Cases

• Replicating the econometric analysis of CSA adoption effects based on the described 2SLS model.
• Studying the relationship between agricultural practice intensity and multidimensional poverty indices.
• Analyzing potential endogeneity in agricultural adoption studies using the provided instrumental variable approach.
• Benchmarking poverty reduction outcomes for policy interventions promoting Climate-Smart Agriculture.

Strengths

• Dataset is licensed under CC-BY-4.0, allowing for broad reuse and sharing.
• Analysis is based on a specific sample of 416 smallholder farmers, providing a concrete scale.
• The study addresses potential endogeneity, a common econometric challenge, using multiple analytical approaches.

Limitations

• Row count and column-level documentation are unknown, which limits suitability assessment.
• The dataset is very small at 17.5 KB, indicating limited scope, likely containing only model outputs or summary statistics.
• Freshness should be verified as the last update date is in the future (2026).

Provenance

Source

Jemil Yasin Shifa via figshare

Collection Method

Cross-sectional data collected from smallholder farmers using a multi-stage sampling procedure.

Time Range

null

Freshness

Last updated 2026-05-04 17:36:12; freshness should be verified.

Geography

Siltie Zone, Central Ethiopia