--- title: "Djanibekov, Tadjiev, Petrick document SUSADICA farm survey data in Kazakhstan and Uzbekistan; CC BY 4.0 licensed data for public reuse" sdDatePublished: "2026-08-25T15:26:00Z" source: "https://www.iamo.de/fileadmin/documents/dp204.pdf" topics: - name: "agriculture" identifier: "medtop:20000210" - name: "water" identifier: "medtop:20000437" - name: "scientific research" identifier: "medtop:20000735" locations: - "Uzbekistan" - "Kazakhstan" --- Djanibekov, Tadjiev, Petrick document SUSADICA farm survey data in Kazakhstan and Uzbekistan; CC BY 4.0 licensed data for public reuse Leibniz Institute of Agricultural Development in Transition Economies Documentation of the SUSADICA Farm Survey Data on Irrigated Agriculture in Kazakhstan and Uzbekistan (2019 and 2022) DISCUSSION PAPER 2026 #204 Nodir Djanibekov, Abdusame Tadjiev, Martin Petrick The series Discussion Papers is edited by: Prof. Dr. Linde Götz (IAMO) Dr. Ivan Đurić (IAMO) Prof. Dr. Thomas Herzfeld (IAMO) Dr. Judith Möllers (IAMO) Prof. Dr. Daniel Müller (IAMO) ISSN 1438-2172 ISBN 978-3-95992-197-8 AUTHORS Nodir Djanibekov is a researcher and a deputy head at the Department of Agricultural Policy, IAMO. He obtained his PhD from the Center for Development Research (ZEF), University of Bonn, Germany. Prior to joining IAMO, he was a researcher in the German-Uzbek development research project on the restructuring of land and wa- ter use in Uzbekistan. His research explores how agri- cultural policies, (in)formal institutions, and behavioral factors shape farmers’ decisions on land-water use, and the adoption, adaptation, and resilience outcomes, with a particular focus on irrigated areas of Central Asia. He leads the research group on rural community resilience (CARe) and serves as a contact person for IAMO’s Central Asia International Research Group. . Email: Djanibekov@iamo.de Abdusame Tadjiev joined IAMO in January 2019 as a doctoral researcher in the Department of Agricultural Policy, working within the framework of the SUSADICA project, funded by the Volkswagen Foundation. He earned his doctorate at the Martin Luther University Halle-Wittenberg in 2024. He studied Agricultural Economics at Samarkand Agricultural University, Uzbekistan, where he also worked as an assistant professor. His research interests focus on the adoption of sustainable agricultural practices in irrigated areas of Central Asia. He investigates the role of behavioral economics in understanding farmers' decision-making, with particular attention to behavioral factors such as risk and time preferences. Email: Tadjiev@iamo.de Martin Petrick is a professor of agricultural, food and environmental policy at Justus Liebig University Giessen, Germany, and a member of the Centre for international Development and Environmental Research (ZEU) as well as the Centre for Sustainable Food Systems (ZNE) at Justus Liebig University. He is also a Visiting Researcher at the Leibniz-Institute of Agricultural Development in Transition Economies (IAMO) in Halle (Saale). Before he was Deputy Head of the Department Agricultural Policy at IAMO and a professor at Martin Luther University Halle-Wittenberg. Email: Martin.Petrick@agrar.uni-giessen.de This publication is distributed under the terms of the Creative Commons Attribution 4.0 International License (CC BY 4.0). The full license text can be found at: https://creativecommons.org/licenses/by/4.0/ CITATION Djanibekov, N., Tadjiev, A., Petrick, M. 2026. Documentation of the SUSADICA Farm Survey Data on Irrigated Agriculture in Kazakhstan and Uzbekistan (2019 and 2022). Halle (Saale), Germany, IAMO Discussion Paper No. 204, Halle (Saale): IAMO. Cover photo: Draft printed SUSADICA questionnaire used for piloting in 2022 © Nodir Djanibekov Djanibekov, Tadjiev, Petrick – Documentation of the SUSADICA farm survey data III ABSTRACT This Discussion Paper documents the SUSADICA farm survey dataset and accompanying metadata to support transparent reuse and reproducible empirical research. It explains how the dataset was produced, structured, cleaned, harmonized, and prepared for public release, allowing users to understand variable meanings, data collection procedures, and processing decisions prior to reuse. The dataset comprises two survey waves conducted in 2019 and 2022 in irrigated farming regions of Kazakhstan and Uzbekistan. The documentation describes the cross-country design, sampling approach, geographic coverage, respondent definition, and the use of the data as pooled cross-sections or, for re-interviewed farms, as a farm-level panel. It also outlines the thematic scope of the surveys, including farm production choices, investment behavior, adoption of sustainable agricultural practices, socio-demographic and behavioral characteristics, and perceptions of land use rights and decision-making autonomy. This documentation presents the metadata package as an integrated set of outputs, including a README file, curated Stata datasets, cleaning and harmonization scripts, a detailed codebook, multilingual questionnaires, and user-oriented training materials. Particular attention is given to questionnaire documentation, CAPI implementation, module structure, skip logic, missing-value interpretation, and wave-to-wave changes. Finally, it summarizes the data management workflow and provides an overview of peer-reviewed publications based on the SUSADICA data. KEYWORDS Farm survey microdata; Reproducibility; Data reuse; Irrigated agriculture; Central Asia Djanibekov, Tadjiev, Petrick – Documentation of the SUSADICA farm survey data IV CONTENTS 1 Introduction .................................................................................................................................... 1 2 Overview of the SUSADICA Data Reuse package .......................................................................... 3 3 Sample design ................................................................................................................................. 5 3.1 Survey overview and design .................................................................................................... 5 3.2 Geographic coverage ............................................................................................................... 5 3.3 Target population and eligibility ............................................................................................. 7 3.4 Sampling approach in 2019 ..................................................................................................... 8 3.5 Follow-up strategy in 2022 and panel construction ................................................................ 9 3.6 Informed consent .................................................................................................................. 10 4 Questionnaire documentation ..................................................................................................... 12 4.1 Questionnaire implementation ............................................................................................. 12 4.2 Field piloting of survey instrument ....................................................................................... 13 4.3 Questionnaire structure in 2019 ........................................................................................... 13 4.4 Changes in questionnaire structure in 2022 ........................................................................ 15 5 Data preparation for reuse ........................................................................................................... 16 5.1 Dataset structure, identifiers, and cross-wave comparability conventions .......................... 16 5.2 Cleaning and harmonization procedures applied during preparation .................................. 17 5.3 Variable retention and consistency of derived measures ..................................................... 19 6 Publications based on the SUSADICA data .................................................................................. 19 Acknowledgements .............................................................................................................................. 24 References ............................................................................................................................................ 25 Annex A. SUSADICA data-cleaning and harmonization in the script file ............................................ 28 Annex B. Example of mapping of survey questions available only in one wave ............................... 34 Djanibekov, Tadjiev, Petrick – Documentation of the SUSADICA farm survey data V LIST OF TABLES Table 1 Number of interviewed farmers by districts in 2019 and 2022 .......................................... 9 Table 2 Publications based on the SUSADICA farm survey data .................................................... 22 LIST OF FIGURES Figure 1 Map of study regions and districts ...................................................................................... 6 Djanibekov, Tadjiev, Petrick – Documentation of the SUSADICA farm survey data 1 1 Introduction This document provides the technical documentation for the SUSADICA farm survey data collected in two waves, 2019 and 2022, in two selected irrigated farming regions of Uzbekistan and Kazakhstan. The documentation follows the logic of established farm survey documentation practice, where survey context, instrument, sample design, field implementation, and data management decisions are described in sufficient detail to make the dataset reusable by third parties and reproducible in empirical workflows (see e.g. Bjärkefur et al., 2021; Petrick, 2001; Wilkinson et al., 2016). Thus, the purpose of this documentation is to enable reliable secondary use of the SUSADICA farm survey dataset by making the full “data lifecycle” transparent, from study design and questionnaire implementation to data processing, harmonization across waves, and the structure of the released data files. The documentation is written to provide clear guidance on what the data represent, how the data were collected, and what transformations were applied before the data publication for open access. This documentation supports reuse and reproducibility in the following ways by: 1. describing the geographic setting of the surveys and the target population, so that users can judge external validity and define appropriate populations for inference. 2. documenting transparently the questionnaire structure and the main topical modules, including changes between 2019 and 2022 that affect comparability and pooled analysis. 3. reporting the sampling approach and the re-interview strategy in 2022, including the achieved panel overlap at district level, which is essential to decide between cross-sectional and longitudinal designs. 4. explaining how the raw data were cleaned and harmonized, including unit corrections, plausibility checks, and procedures to restore verified original 2019 values where pooling created inconsistencies. 5. accompanying the released dataset with reproducible scripts (Stata do-files), versioning conventions, and standardized metadata that allow users to reproduce the delivered analysis-ready dataset from the curated inputs. The data preparation, including this documentation were carried within the SUSADICA Data Reuse project1. This documentation is written to align the released data with the FAIR principles, findable, accessible, interoperable, reusable (see e.g. Wilkinson et al., 2016), and to provide users with the information needed to responsibly work with an anonymized microdata product. The main document contains two Annexes to provide more detailed information on the description of data cleaning procedure (Annex A. SUSADICA data-cleaning and harmonization in the script file), and the questionnaires structure (Annex B. Example of mapping of survey questions available only in one wave). 1 SUSADICA Data Reuse project: https://www.iamo.de/en/research/research-projects/details/susadica-data- reuse Djanibekov, Tadjiev, Petrick – Documentation of the SUSADICA farm survey data 2 The primary intended use of the SUSADICA s