Policymakers in countries that are transitioning away from authoritarian regimes can face challenges in obtaining unbiased information about local conditions—as do researchers and international community representatives working in these countries, including those trying to understand policy change. This information problem is a critical challenge for water security.
As key policy issues related to water resources, climate change, and agricultural supply chains become increasingly globalized, many countries face limited access to local information. Yet, how much, if at all, does such constrained information about local conditions affect the understanding of policies and policy change?
Using the Kaleidoscope Model, we studied feedback data from three distinct communications sources on a water-saving technology (WST) subsidy program in Uzbekistan, a policy that aims to address water scarcity in the context of information asymmetry. The Kaleidscope Model is a framework to understand what conditions are needed to make policy change happen, from agenda setting to evaluation and reform. We found that in evaluating the success (or failure) of the WST subsidy program in Uzbekistan, the source from which feedback is received matters.
Uzbekistan, a landlocked country in Central Asia characterized by arid and semi-arid climate, faces significant water-related challenges. Water resources are primarily supported by surface water coming from the Amu Darya and Syr Darya river systems that originate outside the country. Over 90% of water resources are consumed by agriculture, with the major crops, cotton and wheat, being extremely water intensive. Many farmers use water-intensive irrigation methods, such as furrow irrigation; meanwhile, deterioration in the canal infrastructure, combined with outdated water pumps built and installed during the Soviet Union contribute to water inefficiency. As water has to be lifted from the rivers to irrigation systems with large pumping systems, inefficient water use is also highly energy intensive.
In 2019, a state subsidy program for water-saving technologies was adopted, aiming to cover 450,000 hectares by 2022. This program aims to reduce both water and energy use by providing WST subsidies such as drip irrigation. Farmers implementing these technologies receive financial support and tax exemptions to offset part of the installation costs.
Information ebbs and flows
In Central Asia, with its Soviet legacy of top-down policymaking, information from users may not flow freely up to the relevant actors in the policymaking arena. For this study, we contrasted and compared three information sources on the user side: Official reports and newspapers; in-depth interviews/focus group discussions (FGD); and Telegram chats—a secure messaging and audio calling app that allows large user groups and is commonly used in Central Asian countries. Next, we asked whether differences in quality and content of information from these sources lead to different understandings of policy change, and impediments to adoption.
The three sources of information introduce the possibility of double vision, whereby different images of the same policy change emerge. We compare interpretations of policy change by considering views from above and below as represented by the different information sources. The views from above, captured by official reports and newspapers, might suffer from severe information constraints. The views from below should vary depending on the local conditions and the context of the information-gathering forum. The FGDs arranged by the local government, for example, could still suffer from information constraints even though we speak directly with the users. In contrast, the anonymity of Telegram chats and FGDs that were arranged informally should represent the least information-constrained environment.
To analyze the content of these different forums, we relied on large language model (LLM) techniques. Using data from 21 FGDs of cotton farmers in 15 different districts and 250,000 messages from an online chat forum for farmers spanning a four-year period from 2020 to 2024, the LLM classified the content of the information that farmers shared and sorted it according to its importance and frequency. We then compared and contrasted this content to assess whether any systematic differences would lead to a reevaluation of the conclusions of the KM.
Who says what and where?
We found that the views from above, in official reports, presented the subsidy program as a policy success, and on target to meet its objective. However, the views from below showed a more nuanced picture and demonstrate several important points.
First, across the two forums—FGDs and Telegram—there was a significant overlap in how farmers view WST and problems associated with the subsidy program; however, the distribution varied between forums. Second, we learned from FGDs in particular that not all farmers who install drip irrigation use it. Third, both FGDs and Telegram identified problems with the subsidy program, and many of these problems are out of direct control of farmers. Finally, relative to Telegram chat, FGDs were more likely to report drip irrigation as being too costly, while Telegram entries were more likely to identify problems involving government control. As further evidence of this difference between the FGDs and the Telegram chat, we found that, when FGDs were done in coordination with the local hakimyat (administration), problems identified were fewer in number, and more generic in nature.
Our analysis reveals that while both FGDs and Telegram chats identify a range of barriers to WST adoption, their emphases differ significantly. FGDs primarily highlight technological challenges, whereas Telegram discussions—protected by greater anonymity—emphasize more institutional impediments and critiques of state implementation.
This methodological complementarity proves valuable: Telegram chats capture widespread grievances across the country, while FGDs provide rich contextual understanding of local implementation challenges. As Uzbekistan continues to refine its WST subsidy program, incorporating insights from both anonymous and face-to-face feedback channels will be crucial for developing more effective water conservation policies.
Anton Liutin is a PhD student and Paul Castañeda Dower is an Associate Professor of Agricultural and Applied Economics at the University of Wisconsin-Madison; Muzna Alvi is a Research Fellow with IFPRI’s Natural Resources and Resilience Unit. This post is based on research that is not yet peer-reviewed. Opinions are the authors’.
This work was carried out under the CGIAR Initiative on NEXUS Gains, and with support from the CGIAR Standing Panel on Impact Assessment and the CGIAR Initiative on Fragility to Resilience in Central and West Asia and North Africa, and forms part of the Policy Innovations Program, which are grateful for the support of CGIAR Trust Fund contributors: www.cgiar.org/funders.
