AgriLAC’s Guatemala Baseline datasets: Farmer and village level surveys

This dataset compiles socioeconomic, productive, and community-level information from basic grain producers in the eastern and western regions of Guatemala. It is used to characterize their initial conditions, identify productive and social patterns, and enable territorial comparisons, generating ev...

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Main Authors: Reyes Padilla, Byron Alejandro, Lopera Villamarin, Diana Carolina, Quintero Cano, Diana Katherine, Ordoñez Dueñas, Juan Camilo
Format: Conjunto de datos
Language:Inglés
Español
Published: 2025
Subjects:
Online Access:https://hdl.handle.net/10568/179856
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author Reyes Padilla, Byron Alejandro
Lopera Villamarin, Diana Carolina
Quintero Cano, Diana Katherine
Ordoñez Dueñas, Juan Camilo
author_browse Lopera Villamarin, Diana Carolina
Ordoñez Dueñas, Juan Camilo
Quintero Cano, Diana Katherine
Reyes Padilla, Byron Alejandro
author_facet Reyes Padilla, Byron Alejandro
Lopera Villamarin, Diana Carolina
Quintero Cano, Diana Katherine
Ordoñez Dueñas, Juan Camilo
author_sort Reyes Padilla, Byron Alejandro
collection Repository of Agricultural Research Outputs (CGSpace)
description This dataset compiles socioeconomic, productive, and community-level information from basic grain producers in the eastern and western regions of Guatemala. It is used to characterize their initial conditions, identify productive and social patterns, and enable territorial comparisons, generating evidence to inform interventions aimed at strengthening the sustainability of basic grain systems. The data correspond to the baseline of an impact evaluation designed under a Difference-in-Differences (DiD) approach, which will allow the analysis of changes over time between treatment and control groups. This baseline, collected in 2023 with reference to the 2022 agricultural cycle, serves as the starting point for measuring the effects of the intervention in future follow-up rounds (2026–2027 and 2029–2030). Methodology:The data were collected using a multistage sampling design within an impact evaluation framework based on a Difference-in-Differences (DiD) approach. First, treatment communities were identified through consultations with AgriLAC partners to map areas of operational influence, while control communities were selected within the same municipalities but sufficiently distant to avoid spillover effects. A total of 65 communities (35 treatment and 30 control) were selected. In the second stage, households within each community were chosen through simple random sampling, selecting approximately 16 households in treatment areas and 15 in control areas. Baseline data were collected in 2023, referencing the 2022 agricultural cycle, and will serve as the starting point for longitudinal comparisons in later survey rounds. (2025-12)
format Conjunto de datos
id CGSpace179856
institution CGIAR Consortium
language Inglés
Español
publishDate 2025
publishDateRange 2025
publishDateSort 2025
record_format dspace
spelling CGSpace1798562026-01-14T21:24:34Z AgriLAC’s Guatemala Baseline datasets: Farmer and village level surveys Reyes Padilla, Byron Alejandro Lopera Villamarin, Diana Carolina Quintero Cano, Diana Katherine Ordoñez Dueñas, Juan Camilo beans farmers guatemala agrifood systems This dataset compiles socioeconomic, productive, and community-level information from basic grain producers in the eastern and western regions of Guatemala. It is used to characterize their initial conditions, identify productive and social patterns, and enable territorial comparisons, generating evidence to inform interventions aimed at strengthening the sustainability of basic grain systems. The data correspond to the baseline of an impact evaluation designed under a Difference-in-Differences (DiD) approach, which will allow the analysis of changes over time between treatment and control groups. This baseline, collected in 2023 with reference to the 2022 agricultural cycle, serves as the starting point for measuring the effects of the intervention in future follow-up rounds (2026–2027 and 2029–2030). Methodology:The data were collected using a multistage sampling design within an impact evaluation framework based on a Difference-in-Differences (DiD) approach. First, treatment communities were identified through consultations with AgriLAC partners to map areas of operational influence, while control communities were selected within the same municipalities but sufficiently distant to avoid spillover effects. A total of 65 communities (35 treatment and 30 control) were selected. In the second stage, households within each community were chosen through simple random sampling, selecting approximately 16 households in treatment areas and 15 in control areas. Baseline data were collected in 2023, referencing the 2022 agricultural cycle, and will serve as the starting point for longitudinal comparisons in later survey rounds. (2025-12) 2025 2026-01-14T21:21:42Z 2026-01-14T21:21:42Z Dataset https://hdl.handle.net/10568/179856 en es Limited Access Reyes Padilla, B.A.; Lopera Villamarin, D.C.; Quintero Cano, D.K.; Ordoñez Dueñas, J.C. (2025) Characterization of Households and Basic Grain-Producing Communities in Guatemala: A Multilevel Approach for the Eastern and Western Regions. https://doi.org/10.7910/DVN/HWLPUK
spellingShingle beans
farmers
guatemala
agrifood systems
Reyes Padilla, Byron Alejandro
Lopera Villamarin, Diana Carolina
Quintero Cano, Diana Katherine
Ordoñez Dueñas, Juan Camilo
AgriLAC’s Guatemala Baseline datasets: Farmer and village level surveys
title AgriLAC’s Guatemala Baseline datasets: Farmer and village level surveys
title_full AgriLAC’s Guatemala Baseline datasets: Farmer and village level surveys
title_fullStr AgriLAC’s Guatemala Baseline datasets: Farmer and village level surveys
title_full_unstemmed AgriLAC’s Guatemala Baseline datasets: Farmer and village level surveys
title_short AgriLAC’s Guatemala Baseline datasets: Farmer and village level surveys
title_sort agrilac s guatemala baseline datasets farmer and village level surveys
topic beans
farmers
guatemala
agrifood systems
url https://hdl.handle.net/10568/179856
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AT quinterocanodianakatherine agrilacsguatemalabaselinedatasetsfarmerandvillagelevelsurveys
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