PPCR-GEF

WELL-BEING INDEX ELMARL PROJECT

2015-2017

TAJIKISTAN

First draft submitted: 13th Jan. 2018

Second draft submitted: 5th Feb. 2018, 22nd Feb. 2018

Final draft submitted: 12th March. 2018

Prepared by Christine ORIOL

Based on quantitative and qualitative data collected by ZERKALO ANALYTICS

For the Committee for Environmental Protection of the Republic of Tajikistan

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CONTENTS

Abbreviations ...... 6 Glossary ...... 6 Executive summary ...... 7 Introduction ...... 9 1. A Well-being index to assess adaptation and coping strategies to climate change ...... 9 1.1 Context ...... 9 1.1.1 Sub-components of the ELMARL project ...... 9 1.1.2 State of the project by 31.12.2017 ...... 10 1.2 Chronological and theoretical framework for the construction of the index ...... 10 1.2.1 Chronological steps ...... 10 1.2.2 Theoretical framework: The 3-D notion of well-being ...... 12 1.3 A rural Tajik lens on well-being: definition of well-being in ELMARL context: ...... 13 1.3.1 Domains of well-being ...... 13 1.3.2 A complex approach of well-being to fit into a climate change resilience framework . 14 1.3.3 Chosen indicators ...... 15 1.3.4 Indicators left out ...... 17 1.4 Method of calculation of the well-being index ...... 18 1.5 Evaluation of the increase of Well-Being in the context of ELMARL project ...... 20 2. Concise methodology of the qualitative and quantitative surveys ...... 20 2.1 Methodology of the quantitative survey ...... 20 2.1.1 A panel survey based on a stratified randomized sample ...... 20 2.1.2 Sample composition ...... 22 2.1.3 Survey conduction ...... 24 2.1.4 Analysis of the collected data ...... 25 2.1.5 Limits to the survey methodology ...... 27 2.2 Methodology of the qualitative survey ...... 28 2.2.1 Focus group methodology ...... 28 2.2.2 Sample constitution ...... 28 2.2.3 Survey conduction: qualitative data collection ...... 29 2.2.4 Analysis of the collected data ...... 29 2.2.5 Limits to the survey ...... 30 3. Analysis of the surveys: evolution of well-being from 2015 to 2017 ...... 30 3.1 Assessment of the targeted indicator: increase of well-being: percentage of the population experiencing an increase of 20% of well-being ...... 30

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3.1.1. Overall result of the targeted indicator...... 30 3.1.2 Detailed analysis of the targeted indicator ...... 31 3.2 Assessment of the evolution of wellbeing per domain ...... 32 3.2.1 Health: towards better health conditions for the less healthy ...... 32 3.2.2 Money and Workplace: A ‘buzzing countryside’ at work ...... 35 3.2.3 Living conditions ...... 44 3.2.4 Food availability and nutrition improvement ...... 48 3.2.5 Reinforced social cohesion and more leisure time ...... 50 3.2.6 Safety ...... 55 3.2.7 Subjective well-being...... 56 3.3 Limitations to the taken approach and survey ...... 57 4. Conclusions on the results of the surveys ...... 58 4.1 General conclusions ...... 58 4.2 Domain-related conclusions ...... 58 4.3 District related conclusions ...... 59 4.4 Final conclusions ...... 59 4.5 Lessons learnt on the Well-Being index ...... 60 4.5.1 Positive aspects of a well-being index ...... 60 4.5.2 Comparison with the indicator of “Listening to Tajikistan” ...... 60 4.5.3 Further improvements ...... 61 ANNEXES ...... 62 Annex 1 Questionnaire for the well-being index ...... 63 Annex 2: Sample for the low and high land survey ...... 69 Annex 3 Population pyramid of Tajikistan 2016...... 72 Annex 4 List and location of focus groups- qualitative research ...... 73 Annex 5 List of codes ...... 74 Annex 6: List of priority domains of well-being by focus groups participants ...... 75 Annex7 Cantril ladder measure of life satisfaction for life ...... 76 Annex 8 Selected case studies...... 77

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List of Figures

Figure 1 Questions, methodology and outputs for index construction ...... 11 Figure 2 The 3-D conception of well-being ...... 12 Figure 3 Domains of well-being by priority ranking ...... 13 Figure 4 Picture of well-being values for Tajik rural citizens ...... 14 Figure 5 Summary of the Resilience Framework ...... 15 Figure 6 Domains of well-being after weighting ...... 19 Figure 7 Table of districts within the scope of the survey ...... 21 Figure 8 Location of the districts in which the well-being survey has been conducted ...... 21 Figure 9 Composition of the sample ...... 22 Figure 10 Details of the sampled households in link with ELMARL project in the low and high lands . 22 Figure 11 Details of the sampled households in link with ELMARL project in the middle hills ...... 23 Figure12 Repartition of sampled households per district in the low and high lands ...... 23 Figure 13 Repartition of the respondents for the in-project group (Low and High lands) ...... 23 Figure 14 Repartition of the respondents for the out of project group (low and highlands) ...... 24 Figure 15 Training of enumerators in Zerkalo office ...... 24 Figure 16 Field surveying (Zerkalo’s pictures) ...... 24 Figure 17 Periods of conduction of the well-being survey ...... 25 Figure 18 Comparison of gender representativeness in the endline middle hills sample ...... 27 Figure 19 Location, type and number of focus groups of the qualitative survey ...... 29 Figure 20 Number of respondents to the qualitative survey ...... 29 Figure 21 Well-being evolution in the Low and High Lands in % 2015-2017 ...... 31 Figure 22 Well-being evolution in the Middle Hills in % 2015-2017 ...... 32 Figure 23 Health conditions of respondents in 2015 and 2017, low and high lands (in %) ...... 32 Figure 24 Dynamics of evolution of health status from 2015 to 2017, low and high lands (in points) 33 Figure 25 Dynamics of evolution of health status in Hamadoni district (in points), 2015 to 2017...... 33 Figure 26 Health status of the family members of the respondents in real value in low and high lands ...... 34 Figure 27 Variation of health status (no one was sick in the relatives over the last month) in all districts (in points) ...... 34 Figure 28 Variation of the work situation in and out of the project (in points) in the low and high lands ...... 37 Figure 29 Variations of employment status between 2015 and 2017 in the high and low lands (over 649 respondents) ...... 38 Figure 30 Variation of a positive appreciation of land quality (“good” quality) in all sampled districts low and high lands between 2015-2017 (in points) ...... 39 Figure 31 Variation of waiting time per respondent for irrigation water in Hamadoni district 2015- 2017 (in points) ...... 40 Figure 32 Variation of the waiting time for irrigation water in project districts 2015-2017 ...... 40 Figure 33 Variation of availability of irrigation water between 2015 and 2017 (category: largely available) ...... 41 Figure 34 Variation of availability of irrigation water between 2015 and 2017 (category: not enough irrigation water) ...... 41 Figure 35 Increase of purchasing power 2015-2017: I could buy all what I needed but without extra (in points) ...... 42 Figure 36 Variation of purchasing power extremes between 2015 and 2017 for in project households in project districts (in points) ...... 42

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Figure 37 Evolution of households who own savings between 2015-2017 in low and highland sampled districts (in points) ...... 44 Figure 38 Variation of the number of people per room between 2015 and 2017 (overcrowded cases ...... 45 Figure 39 Variation in the number of people per room between 2015 and 2017 (categories from 1 to 2 people per room) (in points) ...... 45 Figure 40 Variation towards a “very bad” road condition 2015- 2017 in all districts (in points) ...... 46 Figure 41 Evolution (in points) of the percentage of households who take between 0 to 1 hour to fetch drinking water every day...... 46 Figure 42 Evolution of time spent per day to fetch water, for the category “3 hours and more” 2015- 2017 (in points) ...... 47 Figure 43 Quality of drinking water (baseline 2015, mean % of households) low and high lands ...... 47 Figure 44 Quality of drinking water (endline 2017, mean % of households) low and high lands ...... 48 Figure 45 Percentage of households cultivating vegetables in their garden in 2015 (%) ...... 48 Figure 46 Percentage of increase (%, from 2015 to 2017) of the number of households who are growing vegetables next to their house ...... 49 Figure 47 Period of consumption of home produced vegetables (2015 to 2017) in-project districts .. 50 Figure 48 Number of households stating having relaxed or not over the last month in all sampled districts in the low and highlands ...... 51 Figure 49 Variation of leisure time in and out of project scope from 2015 to 2017 (answer= yes, in points) ...... 51 Figure 50 Number of households helping or not their neighbor over the last month ...... 52 Figure 51 Evolution of number of households helping their neighbor (2015-2017, in points) ...... 52 Figure 52 Percentage of households knowing that there was a hashar in their village recently (in %), in 2017 ...... 52 Figure 53 Evolution of the percentage of the number of households who are aware of the happening of a hashar (2015-2017 in points) ...... 53 Figure 54 Men and women networks in the implementation of ELMARL project ...... 54 Figure 55 Variation of the reported feeling “completely safe” across districts 2015-2017 (in points) 55 Figure 56 Variation of the reported feeling “in danger” across sampled districts 2015-2017 ...... 55 Figure 57 Evolution of the “suffering category” of individuals (2015-2017) ...... 56 Figure 58 Evolution of the “struggling category” of individuals (2015-2017) ...... 56 Figure 59 Evolution of the “thriving category” of individuals (2015-2017) ...... 57

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Abbreviations CAWMP Community Agriculture and Watershed Management Project (2004-2012) CEP Committee for Environmental Protection CIG Community Interest Group ELMARL Environmental Land Management and Rural Livelihoods IG Implementation Group GEF Global Environmental Facility PAD Project Appraisal Document PUG Pasture User Group PUU Pasture User Union PPCR Pilot Project for Climate Resilience TJS Tajik Somoni, Tajik national currency WUA Water User Association WUG Water User Group USD United States Dollar, currency

Glossary

In-project population: population who is living in the villages where some subprojects have been implemented through ELMARL. The in-project population is subdivided into direct beneficiaries and indirect beneficiaries.

Off-project population/control group/ out of project household: population who is living in the villages where ELMARL has not been implemented.

Direct beneficiary: person who has been a direct receiver of a subproject grant, being part of a CIG group or of a PUU or WUA.

Indirect beneficiary: person who is living in the villages where ELMARL subprojects have been implemented, but without being a direct beneficiary. Practically, their names do not appear on any subproject implementation lists.

Collective project: any project at the village level which involved some form of collective organization and had a collective impact. This denomination encompasses infrastructure projects concerning water management (drinking water rehabilitation, irrigation channel cleaning, water gates), road construction (village road rehabilitation…), electricity access and pasture management through PUUs.

New Deal: refers to the period in the USA from 1933 to 1938 under President Roosevelt. “The New Deal was a series of federal programs, public work projects, financial reforms and regulations enacted in the United States during the 1930s in response to the Great Depression. These programs included support for farmers, the unemployed, youth and the elderly” 1.

Hashar: is a Tajik word referring to volunteer community work, in which all male inhabitants of one area get together to work voluntarily. It usually concerns work that is useful for the whole community (road construction, irrigation channel cleaning…)

Havli: inner yard of a rural household and not visible from the outside.

High lands, middle hills (also named mid lands), low lands: these agro-ecological zones have been determined prior to the project implementation, according to their relief and terrain (respectively: mountains, hills and plains.)

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Executive summary

. As an indicator to assess the impact of the Environmental Land Management and Rural Livelihoods (ELMARL) project implemented by the Committee for Environmental Protection (CEP) of the Republic of Tajikistan with the financial support of the PPCR-GEF project in the Republic of Tajikistan, the well-being index was developed to follow a population through time and assess the changes of well-being of the target population while it was being supported in the implementation of small-scale projects aimed at increasing their resilience towards climate change

. The index has been developed based on a participatory approach at the early stages of the ELMARL project implementation and hence reflects the perception of well-being of the Tajik population. Based on a series of 56 questions, the index is calculated through a system of coding and weighting, which allows to closely reflect the Tajik concept of well-being.

. Based on the baseline assessment conducted in 2015, the main target indicator was defined and stated that a well-being increase of at least 20% of well-being for 50% of beneficiaries could be reached.

. Using a calculation method which averages the positive increases of well-being across the in- project population; more than half (53%) of the in-project population (low and high lands) has increased its well-being by 25% in average. 53% of the in-project households have increased their well-being against 46% of the off-project households.

. ELMARL project managed to switch the trend from “business as usual in a poor economic context” and to help more than half of the in-project population to increase its well-being. There is clear evidence that ELMARL has been beneficial for all its beneficiaries, in terms of well-being increase: In-project households have seen their well-being increase by four more points than the off-project households.

. Within the in-project sample, well-being has increased of 20% at least for 31% of the most direct beneficiaries of ELMARL project. The result of the endline assessment conducted in December 2017 in the low and highlands (over a sample of 650 households) shows that 31% of the households who are direct beneficiaries of the project report an increase in their well-being by at least 20% over a two-year period (2015-2017),

. This increase of well-being concerns a larger majority of women than men: 25% of the women (22% for men) have increased their well-being of 20% or more, and 33% of the women (28% for men) have increased their well-being of 15% or more;

. These figures do not include the results of the survey conducted in the Middle Hills. In the middle hills and over the one-year period, 16.1% of the direct beneficiary households have reported an increase of well-being of 20% or more. The data cannot be aggregated with the data from the low and highlands. The shortness of the evaluated period does not allow to get the full picture of the impact on well-being, but indicates a positive trend;

. The large scale of the well-being survey has not supplied sufficient geographically- focused data for detailed analysis, but allows on the contrary to look at larger trends across districts. This scale of analysis would have been relevant in the case of the implementation of a systematic state program, but proved incomplete for a less systematic approach, such as the ELMARL project. This limitation may have hampered the quantitative visualization of the full impact of ELMARL at the household level;

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. The lack of formal lists of beneficiaries at the beginning of the project implementation led to an underrepresentation of the direct beneficiaries of ELMARL project in the endline survey, which undermined the real impact of the project on the well-being of the target population.

. To bring more evidence of ELMARL impact on the well-being of the population, a qualitative survey was conducted and involved 125 respondents gathered in focus groups.

. The qualitative survey brought key additional information about well-being in regards to the resilience to climate change framework. Elements of information such as social cohesion and knowledge increase are crucial for the resilience capacity of the rural population;

 ELMARL project has acted as a shock absorber for households in a context of national economic crisis; the purchasing power of in-project households has remained stable while it was dropping for off-project households;

. ELMARL project has been decisive in providing employment opportunities to women in the countryside.

. The analysis of the focus groups gave evidence that ELMARL project has launched a New Deal in rural Tajikistan. As focus group participants have been stating it “the people woke up”, jobs have been created, social cohesion is been reinforced, abandoned land is being put back into use, and there is a greater abundance and diversity of food in the households.

. In that regard, and based on the given definition of resilience to climate change as a “capacity to cope with shocks and stresses and to sustain transformations needed to reduce poverty under global change, including climate change”2, the well-being index shows that the beneficiary population has increased its resilience to climate change. Household assets have improved, as well as self-governance: the process of organizing into groups and managing their own projects has increased the household’s capacity to decide and adapt to external factors.

2 Development and Application of a Resilience Framework to Climate Change Adaptation D Mark Smith Director – Global Water Programme, IUCN, Switzerland 8

Introduction

The Government of Tajikistan has received $17.675 million in grants from the Pilot Program for Climate Resilience (PPCR), the Global Environmental Facility (GEF) and the International Development Association (IDA) to implement the Environmental Land Management and Rural Livelihoods Project (ELMARL) (2013-2018). The Committee for Environmental Protection (CEP) through its Implementation Group (IG) is implementing the project. The project became effective on October 3, 2013 and has been under implementation for over four years, while all activities are expected to be finished by the closing date of May 31, 2018.

The project objective is to enable rural households to increase their productive assets in ways that improve natural resource management and resilience to climate change in selected climate vulnerable sites. Groups of households are participating in the project by being recipients of small grants that support farm production, land resource management and small-scale rural infrastructure.

The selection, design and implementation of the grants have been supported with facilitation assistance from locally contracted non-government organizations.

As a result of these and other related activities among the key project outcomes from the project one focuses on improvements in the well-being of benefiting households. In the context of sustainable land management projects in Tajikistan, such measures have not been widely used to assess project achievements. The well-being index enables to answer the question of to which extent well-being (that serves in part to reflect household assets, such as human and social capital) has increased thanks to the project’s achievements.

1. A Well-being index to assess adaptation and coping strategies to climate change

1.1 Context

1.1.1 Sub-components of the ELMARL project

The ELMARL project is comprised of three components. Under the first component, small grants provides financing to support rural households in developing their productive assets under two sub-component; component 1.1 enhances the uptake of sustainable village-based rural production and land resource management effort, while sub- component 1.2 provides financial support for larger-scale initiatives in sustainable community land management projects.

The second component tackles the question of knowledge management and institutional support by providing facilitation services and technical and institutional support to rural populations to plan, implement and manage the rural investments.

The third component enables the project management and coordination by encompassing the operating costs of the IG and CEP for its management functions for the implementation of Components 1 and 2.

The well-being index hence looks at the effects of components’ 1 and 2 interactions on the population’s well-being.

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More specifically, the well-being index is thought to allow for in detail analysis of the effects of sub- component 1.1 and 1.2 on household productive assets which enable resilience to climate change.

The sub-component 1.1 aims to promote the adoption of innovative rural production and land management measures, and related small-scale infrastructure investment. Investments are made in three categories that are expected to contribute to household assets and sustainable land management, and increase climate resilience, examples of which are listed below: (i) Farm Production: field and horticultural crop productivity and diversification, livestock production efficiency, agro-processing and market access; (ii) Land Resource Management: pasture management, water management, soil fertility, integrated pest management, and sustainable sloping lands cultivation (including orchards, woodlots, shelter-belts); and (iii) Small-scale rural production infrastructure: irrigation/drainage system rehabilitation, minor transport infrastructure, renewable energy, and energy efficiency measures.

Certain aspects of natural resource and climate change adaptation issues are better addressed at scales beyond the village. Of particular concern, to both sustainable land management and productive rural livelihoods in the context of climate change, are pasture management and on-farm water management.

Therefore, sub-component 1.2 supported larger-scale initiatives in sustainable community land management implemented by members of Pasture User Unions (PUU) and Water User Associations (WUA). While pasture degradation and access are pressing issues in both lowland and upland areas, the consequences of poor water management are especially critical in lowland areas where agriculture depends primarily on irrigation.

1.1.2 State of the project by 31.12.2017

By 31.12.2017, 52'824 households have been reported to have adopted climate change and sustainable land management practices3.

This figure encompasses under the subcomponent 1.1, 24’384 households who are directly supported by the project (they are considered as actively involved in the CIG activities) and 12’240 households who are indirectly supported by the project (they are on the CIG member list but are not actively involved in the implementation of the activities). In total under this component 2'311 CIGs were created, each of which implemented a sub-project.

Under the sub-component 1.2, the number of households who were supported reaches 16,211. The total of 16 WUAs and 8 PUUs supported their members in the implementation of 134 sub-activities.

The number of hectares in project areas covered by effective agricultural, land and water management practices suited to local agro-ecological conditions and climate change resilience reaches 44’010 hectares.

1.2 Chronological and theoretical framework for the construction of the index

1.2.1 Chronological steps The well-being index has been developed following a participative approach.4

3 ELMARL 2nd Semi-Annual 2017 Progress Report – July to December 2017 4 the complete approach is detailed in the Report on Indicator development, ORIOL, December 2015, 42p 10

. Desk review (October 2015)

The construction of the index has been initiated and supported all throughout by a bibliography review. Numerous recent studies exist in the field of well-being, the different methods of calculation and the questions to assess its quality. Nevertheless it remains an indicator mostly used in developed countries to adapt their national policies, as the Easterlin paradox demonstrated that happiness levels and income levels are not correlated once a certain level of income has been reached. Well-being indicators are rarely used in development projects, although, it should be noticed that two studies had been conducted in the region; one concerning well-being in GBAO5 and the other one in Afghan Badakhshan6.

The methodology of constructing the index was designed based on this initial desk review, following the steps described in this table:

Questions Methodology Outputs What are the determinants of well- being according to a Tajik Participatory approach: focus List and ranking of household? groups with beneficiaries of well-being 1 current project and former domains for Tajik What are the main domains that project (CAWMP) households play a role in the well-being of Tajik rural households? How are ELMARL measures and Matrix of direct Focus groups & simple matrix 2 subprojects impacting on these and indirect analysis domains (determinants)? impacts Which questions are the most Field test questionnaires, meeting One final 3 appropriate to highlight the with experts on climate change questionnaire and changes? and monitoring the report “ Figure 1 Questions, methodology and outputs for index construction

. Identification of domains of well-being through focus groups (3-5.11.2015) 6 focus groups were first conducted in three different districts: Jirgatol, Dangara and Farhor, gathering participants in the past CAWMP project to understand the impacts of the projects on their lives, and also with already identified beneficiaries of the current ELMARL project.

The purpose of these focus groups was to identify domains and key dimensions of these domains that would be relevant to the results of ELMARL interventions and to assess the most appropriate evaluation of subjective well-being. As a result, a list of domains of well-being was issued by order of priority according to Tajik households.

. Meetings with experts and participating NGOs (10-25.11.2015): development of indicators Climate change, monitoring and evaluation experts, team leaders of project linked to resources management in rural Tajikistan as well as staff of the participating facilitating NGOs have been consulted on the question of well-being and best indicators to catch changes in well-being in rural areas of Tajikistan. For each well-being domains that were identified, the bibliography review highlighted some indicators used by previous studies or surveys. For most domains, proxy indicators were chosen.

. Questionnaires tested on the field (16-17.11 and 23-25.11.2015) A questionnaire was designed to collect information regarding the various indicators that cover the different domains of well-being.

5 Well-Being of new pastoralists in eastern Pamirs, Tobias Kraudzun, Fanny Kreczi, 2012 6 Improving Quality of Life in Remote Mountain Communities, Nazneen Kanji, Graham Sherbut, Romin Fararoon, and Juanita Hatcher, Mountain Research and Development (MRD), 2012 11

Some information of the questionnaire is mostly informative and aims at providing contextual information to analyze the final indicator of well-being. This information is: age, gender, level of education, work status, place of work. The questionnaire7 was then tested on the field in 2 separate trips, which allowed modifying the questionnaire for the second trip, and testing more questions.

1.2.2 Theoretical framework: The 3-D notion of well-being

The general definition of well-being is “the state of being happy, healthy, or successful (Merriam Webster)”, “the condition of being contented, healthy, or successful” (Collins dictionary), “the state of feeling healthy and happy (Cambridge online dictionary)”. In simple terms, well-being can be described as judging life positively and feeling good. Well-being in studies gets also close to the notion of “quality of life”.

This simple definition does not embrace the concept of well-being in all its dimensions, but a recent approach, the 3-D notion of well-being has been developed8 and provides a solid theoretical framework for the subject of our study. It defines well-being as the conjunction of 3 factors9: material, relational and subjective.

Dimensions of well- Material Relational Subjective being The objectively The resources that a The meanings that observable outcomes person is able to people give to the that people are able to command and the goals they achieve and achieve extent to which they the processes in which What is to be studied are able to engage they engage with others in order to achieve their particular needs and goals It requires satisfaction Material asset Quality-of-life indicators indicators, indicators multidimensional Indicators resource indicators and human agency indicators Through well-being Through well-being Through questionnaire Addressed during and livelihoods and livelihoods on Subjective Well focus groups determinants determinants Being questions questions Figure 2 The 3-D conception of well-being

This grid of understanding well-being has been used during the focus groups, and filled in with a participative method developed in the framework of trade-offs modelling for ecosystem services10. The material and relational aspects of well-being were interrogated during the focus groups to design a list of domains of well-being that were important for the focus group participants. The experience showed that the answers were quite homogenous between the different focus groups participants. This indicator of well-being is based on “a conception of wellbeing that takes account of the objective circumstances of the person and their subjective evaluation of these”11.

7 see in annex 8 IDS in focus policy briefing 9.2 After 2015: ‘3D Human Wellbeing’ June 2009 9 from http://www.ids-uva.nl/wordpress/wp-content/uploads/2011/12/Poster-Wellbeing-Approach.pdf 10 Participatory Modelling Of Wellbeing Trade-Offs In Coastal Kenya, Tools and Processes for Participatory Modelling of Wellbeing Implications Ecosystem Service Tradeoffs: Description and reflection on methods developed and used in the ESPA P-Mowtick project, http://www.espa.ac.uk/files/espa/Participatory%20tools%20and%20processes%20from%20Pmowtick.pdf 12

As for subjective well-being, different techniques can be used (they are described in the report on indicator development), two main ones were tested during the focus group and the Cantril ladder measure of life satisfaction (situated at the end of the well-being questionnaire) was chosen thanks to its simplicity and accuracy.

The ladder of life is an instrument developed to measure satisfaction of life which dates back from 1997, and is divided into two questions12 which ask the respondent to grade its level of life satisfaction from 0 to 10 in the present, and the one expected in the next 5 years. The scores are divided into 3 categories, thriving for scores of 7+ and 8+ for the next five years, struggling for answers between 5-7 and 5-8, and suffering for answers below 4. The measure has proved to be directly linked with health, general wealth, eating habits, and worries.

1.3 A rural Tajik lens on well-being: definition of well-being in ELMARL context:

1.3.1 Domains of well-being

As a result of the focus groups of autumn 2015, a matrix has been developed to present the main domains of well-being and their priority order according to the participants. Differences were observed between groups according to the gender of the group (most of them were not mixed), the location of the focus groups (middle hills or low and highlands)… But overall, while the ranking of priority might be different, the same domains of well-being came back in all focus groups, showing that the population shared the same understanding of what matters to them. Individuals, given the specificities of their own situation (unemployed, divorced, sick and so on) prioritize some domains over others. This conclusion was confirmed by the focus groups conducted during the endline survey, in November 2017, to gather qualitative data, during which the same main domains of well-being were found across various groups.

Health and social cohesion (peace and mutual understanding) remain the two main values that all the population shares and that are very important to them.

Figure 3 Domains of well-being by priority ranking

11Well-being in developing countries: conceptual foundations of the WeD programme, Ian Gough, J. Allister McGregor and Laura Camfield, September 2006, http://www.welldev.org.uk/research/workingpaperpdf/wed19.pdf 12 see in annex 13 ranking domains of life for well-being determinants 1 Health// Water (in mid and lowlands) 2 Peace (at the country level)

3 Money and workplace

4 Living conditions (electricity and water, housing comfort, road) 5 Food 6 Social connections (family and

friendship) 7 Leisure (benefiting from leisure activities and having access to leisure facilities such as sports halls) Safety Education (from kindergarten to university) Environment Figure 4 Picture of well-being values for Tajik rural citizens

1.3.2 A complex approach of well-being to fit into a climate change resilience framework

The chosen approach for the survey has favored a multidimensional vision of the notion of well-being to fit into a climate resilience framework; for which both the qualitative and quantitative surveys brought complementary information.

“In a climate-changing world, the systems of people, economy and nature in which we live will have to have characteristics that make them highly adaptive systems. The reality of systems, where one thing is connected to another, means there are structural or engineered dimensions to climate resilience, but also social and ecological dimensions (Smith, 2011).”13

In regards to this definition of climate resilience and in accordance with the 3-D definition of well- being explained above, it seems important to acknowledge the influence of various factors which go beyond concrete household assets such as land, electricity or a regular income.

The following scheme demonstrates the four main points to examine when speaking about climate change resilience.

13 Development and Application of a Resilience Framework to Climate Change Adaptation, D Mark Smith Director – Global Water Programme, IUCN, Switzerland 14

Figure 5 Summary of the Resilience Framework14

Domains of well-being of the index have hence been chosen because of their link with the resilience capacity of the households to climate change. They both encompass very concrete household assets that are fundamental for adaptation capacity (water access, roads, diversified household assets…), as well as elements which are part of the socio- ecological network in which households live and which are crucial for the good functioning of their resilience capacity (social cohesion for example).

Because ELMARL subprojects are purposefully targeting household assets that have been identified as key for the households and village resilience capacity to climate change, a lot of indicators are related to the main outputs that the subprojects are supposed to deliver (income, work, water access, land…). The preliminary report of component A5: Phase 1 Agriculture & Sustainable Land Management (Final report, 15 December 2011) also gave concise information about which elements are important for a rural household to increase its resilience capacity.

While most of the chosen indicators of the quantitative survey focused on quality of life, infrastructure, income, referring to the first and second points of the above-mentioned resilience framework, the qualitative survey enabled to look and deepen the data on the third and fourth categories, self-organization and learning. When looking at this resilience framework, all mentioned domains make sense and are interlinked, as the population stated it during the focus groups. It may seem that peace or the feeling of safety is a bit far off track, but it is actually a key element in the overall socio-ecological system of rural households.

1.3.3 Chosen indicators15

Health - Respondent’s health status It was chosen to only ask one question related to health self-assessment– the one rating the current health status, as it seemed to be a more objective assessment of the health status.

- Family and relatives’ health status The relatives health status is considered as an important part of the health domain, as it will translates into more time and care for the relatives, and worries.

14 in Ibid 15 the explanation of the choice of indicators including feedback from the field tests is detailed in the report Report on Indicator development, ORIOL, December 2015, 42p 15

Peace and safety One of the main determinants of the well-being for Tajik households is peace – understood as peace at the national level. Because this is beyond the household control and the projects’ realm, it was chosen to narrow the question of peace to the one of safety, and to ask the population whether they are feeling safe in their village. This is understood as feeling safe from natural hazards and from crime.

Money and workplace (divided into household assets, work and income) - Household food production It was decided to ask a direct question “For how long can you feed your family with your own home production?” that would encompass all home production and make the direct link to food security.

- Land It was chosen to use land surfaces as an indicator for well-being. A survey conducted by Lerman and Wolfgramm16 shows indeed a direct correlation between land surfaces and well-being. The total area of all available land includes land that is used to prepare hay or fodder (can be rain-fed land), presidential land, dekhan land (might be collective, individual or family), rented land.

- Irrigation water Two aspects have been interrogated for irrigation water; the first one is access to water and then the received quantity.

- Livestock Livestock numbers are collected for the survey, but without being aggregated to the final well-being indicator.

- Work As income is already examined indirectly with looking at consumption, and because asking for incomes will not provide accurate answers, it seemed more interesting to ask whether the respondent had a job and if the person is satisfied with their occupation (may it be housewife, pensioner or worker).

- Income and migration The question here is how many migrants that are actually in Russia or abroad have sent money over the last six months, to assess the positive impact of cash sent from abroad.

Consumption and purchasing power - Availability of cash to cover monthly expenditures This question allows to grade to which extent the household is earning enough cash to sustain its needs. The level of consumption is a good indicator of the income of the household.

- Buying with credit It can be understood as a sign of lack of immediate cash and hence of a financial burden

- Savings account Savings accounts are rare in rural Tajikistan; as one respondent was stating “from what could we save?” most of the cash goes immediately to consumption. Savings accounts are hence a good indicator of the availability of large amounts of cash.

Living conditions - Housing conditions

16 Discussion Paper No. 8.11, Vulnerability to risk among small farmers in Tajikistan: results of a 2011 survey, Zvi Lerman and Bettina Wolfgramm 16

It is assumed that a house with more rooms and thus more space and intimacy for sleeping is correlated with higher income or wealth. The number of household residents per room is used here as an indirect indicator of comfortable living conditions.

- Drinking water The questions related to water evaluate the time spent on fetching water and the quality of the drinking water.

- Roads One question is added to the questionnaire: “Do you consider that you have good road access to district center?”

Leisure time and community cohesion - Leisure time The question is the following: “Did you enjoy some relaxing time with friends or family (visit to relatives, weddings, birthday parties, sport, and meeting with friends…) this month?”.

- Helping the neighbors In rural areas of Tajikistan, helping each other is considered as very important. Respondents were sometimes a bit surprised by the question. One female respondent argued “we live in the mountains; we have to help each other”. Help can take different forms: preparing the wedding, bringing food, lending money, taking care of the children, helping with water provision, some households bring a hose for spring water until their yard and allow their neighbors to take water from there.

- Community work A “hashar” is community work organized by the community and implemented by all community members. The question “did you participate in the hashar?” proved not relevant as the field test showed that when a hashar is organized at the village level, all men take part in it, while the women sometimes will not, depending on whether the work is physical. So the question was transformed to know if the person was actually aware of a hashar in its village. It is a relevant sign of inhabitants cohesion and capacity to organize themselves as a community to solve village issues.

1.3.4 Indicators left out The following indicators have been considered but were finally left out of the well-being index.

Wealth and income An expert from GIZ proposed to collect data on fuel that is used by the household to assess their wealth. As fuel mixes and costs are very different according to geographical areas and given the diversity of regions where ELMARL project is being implemented, it was considered too difficult to analyze.

Housing conditions In rural Tajikistan, housing conditions are quite similar from district to district. Some well-being assessments in other countries would look at flush toilets, etc.… here in the case of rural Tajikistan, it did not seem an accurate indicator.

Consumption power Phone ownership It was decided not to ask the question of phone ownership, as it seemed difficult to draw a direct causality with purchasing power.

TV ownership was removed as an indicator because of large homogeneity of ownership: out of 34 interviews during the test, there were 34 TV owners, of which 2 owning flat screens.

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General appliances The possibility to use cars, fridges or hot water heaters as an indicator of increased purchasing power was considered. But the unpredictability of rural electricity supply does not make it relevant to choose house equipment that is dependent on this energy supply.

Social relations Couple relations Initially the question “Are you satisfied of the relation with your husband/wife?” was asked but the results were all positive (over 34 interviews) so the question was transformed into: “How often did you argue with your husband or wife last week?”. This question was finally abandoned as it was difficult to introduce in the questionnaire and did not bring significant value.

Women role Domestic time to take care of children and relatives The question “How many hours a day do you take care of your relatives and children?” was suggested by a gender expert. The results of the field test seem to indicate that the domestic charge is very unequally spread between family members, since some individuals do not spend any time on caring for others and other individuals spend their whole day. The question was abandoned because of being too difficult to code, and too far from the project’s envisioned impacts.

Also the education of the children and the possibility to have access to a kindergarten was an aspect of well-being that was discussed with the women during focus groups. Again, as it is considered out of project’s main inputs, it was chosen not to delve on this question.

Participation in political and community life Initially the questions did not differentiate between community life and political life. After a second round of testing, this question was considered too gender-biased (only men were answering yes, and was removed).

1.4 Method of calculation of the well-being index

The well-being index is composed of an aggregation of coded indicators which are gathered by each defined domain of well-being. Each answer to a specific indicator is coded numerically, the more positive the answer is to well- being, the more points it brings, this technique can be explained as giving “happiness points” in accordance with how beneficial for well-being is the given answer. The total of all points is calculated per domain and then aggregated to become the final score of well-being. The total score of well-being reaches 78 points.

Domains are then weighted to match the original ranking of well-being domains that came as a conclusion to the focus groups. The weights were distributed so as not to create a huge disparity between domains, while reflecting the importance that the population is giving to each of these domains. Subjective well-being (SBW) was incorporated in the well-being indicator. Studies have shown that income and material wealth are correlated with SBW17 to some extent, depending on the level of wealth of the population, but also that other factors were affecting SBW such as life satisfaction, cultural values… Integrating SWB enables to cover some other aspects of well-being that were not included in all the chosen indicators.

17 Biswas-Diener, R. (2007): 'Material wealth and subjective well-being.' In: Eid, M., & Larsen, R. (Eds.), 'The science of subjective well-being' (307-322) Guilford press. 18

The following paragraph details which indicators are composing the main domains of well-being:

. Health = health status of respondent + health status of the family members

. Money and workplace = total area of land cultivated +quality of the land + waiting time for irrigation water + quantity of irrigation water + satisfaction with occupation + capability to buy what the household needed over the last month + use of credit + savings

. Living conditions = number of person per room + time to fetch drinking water+ quality of drinking water+ quality of road to district center

. Food= growing vegetables in the havli + period during which the family is self-sufficient

. Leisure and social connections= relaxing time with friends or families+ help to the neighbors+ hashar organization in the village

. Safety= safety in the village

 Subjective well-being= feeling of happiness now + optimism towards the future

Each domain is then weighted to reflect the priority order given by the focus group respondents during the index creation.

Finally the well-being index is calculated according to the following formula:

Well-being indicator = health points*2 + money and workplace points*0,35+ living conditions *0,6 + food *1,5 + leisure and social connections*2 + safety *2,5 + subjective well-being*0,3.

subjective well-being health 12% 21% safety 10%

leisure and money and social workplace connections 16% 12% food living 12% conditions 17%

Figure 6 Domains of well-being after weighting

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1.5 Evaluation of the increase of Well-Being in the context of ELMARL project

When the well-being index was initially designed, it came along with the calculation of the potential increase in well-being that the project could expect for its beneficiaries.

In technical terms, for each domain of well-being was calculated the increase in well-being that could result from the project: an overall increase of 20 points could be envisioned, which translated into a 22% increase of the overall well-being of the concerned population. A 20% increase of well-being was forecasted at the time of the index design, for at least 50% of the population (direct and indirect beneficiaries18) of the project.

Looking at the results of the endline survey, it seems that this increase has been adequately forecasted, as more than half of the in-project beneficiaries have reported an overall average increase of 25% (relative increase calculation).

2. Concise methodology of the qualitative and quantitative surveys 19

2.1 Methodology of the quantitative survey

2.1.1 A panel survey based on a stratified randomized sample

The chosen survey method is the panel survey, which creates a pool of respondents, and returns to the same respondents after a period of time to assess the evolution of the sample.

The stratification of the sample has been done following the agro-ecological zones, districts, villages, and gender.

Household sample calculation The number of households to survey is calculated based on the total household population over all surveyed districts, with an online calculator, to allow for representativeness of the sample. Then, the number of households to be interviewed per district is calculated in regards to the sample size and in proportion of the population in each district. A large refusal rate (20%) was calculated to ensure that the sample would remain representative in case of a large number of drop-outs.

Criteria for choice of districts

To evaluate the project impact, it was chosen to survey both districts which were in and out of the project scope and which were covering all the three agro-ecological zones. For the middle hills area, it was found impossible to find an adequate similar district that could operate as a control group. In the lowlands, Hamadoni had been chosen initially as a control group for Farhor district. A change in the project implementation after the well-being index and survey design turned Hamadoni also into a in-project district.

18 also named “in-project” beneficiaries (see glossary) 19 the full and detailed methodology is available in the previous reports. 20

Agro-ecological In-project districts Districts “control group” zones Jirgatol Jirgatol Highlands Tavildara Nurobod

Baljuvon Midlands Khovaling No control group

Faizabad

Kulob Vose

Lowlands Hamadoni Hamadoni

Farhor Hamadoni

Figure 7 Table of districts within the scope of the survey

Criteria for choice of the villages The civil census is not yet computerized in Tajikistan and lists of population are only available in the jamoats’ books. This is the reason why it was chosen to use a sample constituted of villages, and not of individuals. Villages were randomly selected, based on the methodology of probability proportional to size which allows for each individual, regardless of the size of the village, to have the same chance of being interviewed. In each sampled village, seven interviews were conducted, except for the middle hills’ sample, where no control group could be found, and for which fourteen interviews were conducted in each village. Households were selected in the villages with the technique of the random walk which provides guidelines to randomly select households for the interview. Two different sets of guidelines were provided according to the size of the village (+ or – 400 households)20.

Figure 8 Location of the districts in which the well-being survey has been conducted

20 the detailed instructions are available in the manual for enumerators 21

2.1.2 Sample composition

Two different samples for the conduction of the well-being index survey were prepared21, since the low/highland and the middle hills surveys took place at different periods.

General characteristics of the samples The sample used for the well-being survey has the following characteristics:

Initial Drop- Average Agro-eco Final Final % Final % of Average sample out age zones sample size of men women age men size rate women Low and 721 649 10% 45.5% 55.5% 52 50 high lands Middle Hills 210 180 14.3% 46.1% 53.9% 48 48

Figure 9 Composition of the sample

The initial sample size has been reduced due to modifications of the situation of some respondents (death, on a trip, severely ill, in migration, moved to another place, refused to answer to the enumerators). This is visible in the drop-out rate.

The average age is high and not representative of the demographic situation in Tajikistan, where the younger generations are outnumbering the older ones22. It is nevertheless representative of the average age of heads of households in Tajikistan, given the fact that adult children will live with their parents, who will be the decision makers until an advanced age.

Detailed characteristics of the samples23

Low and high lands Number of in-project households Number of off-project households 334 315 Households under a CIG and Households under a CIG or collective project collective project - 216 118

Number of household direct Number of household Number of out of number of beneficiaries (group indirect beneficiaries (no project households who members) group members) household mentioned being part of a group 49 285 301 14 14.7% 85.3% 95.6% 4.4% Figure 10 Details of the sampled households in link with ELMARL project in the low and high lands

This table introduces one of the main challenges of the survey, which was to reach out to the direct beneficiaries. The main difficulty was to conduct a baseline while all subproject groups had not been created yet, and while each district had a different speed of project implementation. Furthermore, some of the respondents were not aware of being part in the project. Also, some respondents (4,4%) mentioned being part in ELMARL project, although they were living in districts where ELMARL was not implemented.

21 see in annex the samples for the low and highlands and for the middle hills surveys 22 see the demographic pyramid in annex 23 for definitions, see the glossary p6 22

Middle hills Number of in-project households Number of off-project households 180 Households under a CIG Households under a CIG and collective project or collective project

73 107 0 Number of household Number of household direct beneficiaries indirect beneficiaries 31 149 17.2% 82.8% Figure 11 Details of the sampled households in link with ELMARL project in the middle hills

Agro- % of respondents ecological Districts In-project Off-project zone Jirgatol 54 46 Tavildara 100 0 Nurobod 0 100 low and Vose 0 100 high lands Hamadoni 12 88 Kulob 100 0 Farhor 100 0 Figure12 Repartition of sampled households per district in the low and high lands

Geographical characteristics of the samples

The respondents of control groups and their in-project mirror groups have been calculated so as to represent the same number of households.

Jirgatol; 17% Tavildara; Farhor; 38% 10%

Hamadoni; 5% Kulob; 30%

Figure 13 Repartition of the respondents for the in-project group (Low and High lands)

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Jirgatol; 15%

Nurobod; Hamadoni 13% ; 38%

Vose; 33%

Figure 14 Repartition of the respondents for the out of project group (low and highlands)

Hamadoni district was initially thought to serve only as a control group. Later on during the project development, one WUA was created in one jamoat, which added some of the respondents into the in-project group.

2.1.3 Survey conduction The surveys have been conducted by Zerkalo Analytics, a company specialized in sociological research based in Dushanbe, which was hired on a tender process.

Zerkalo Analytics was in charge of hiring and training enumerators to work in the districts and to provide a final database for each survey. For the initial baseline survey, the international consultant provided a training session to Zerkalo’s staff to present the project and go into the details on how to go through the questionnaire and ask some questions. A manual for enumerators was created by the international consultant and translated into Tajik. The procedure to collect information related to subjective well-being was, for example, explained in details.

Figure 15 Training of enumerators in Zerkalo office

Figure 16 Field surveying (Zerkalo’s pictures)

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During the two baseline surveys (low and highlands, and middle hills), the work was coordinated by a dedicated national consultant hired for this purpose, while for the endline surveys, this coordination work relied on the IG staff.

Zerkalo’s staff has been operating by using tablets to collect information, which minimizes the risk of entering inaccurate data.

It is important, in the field of well-being, to conduct both baseline and endline surveys during the same period of year, so as to avoid the “season effect” which affects the population’s mood and perception of its own well-being (people are happier in the summer time).

The survey for the low and high lands lasted 14 days (24 days in 2017), and the survey for the middle hills lasted 5 days (6 days in 2017). The prolonged period of field survey for the endline in the low and high lands may have an impact on the quality of the data.

December 2015 August 2016 August 2017 December 2017

Baseline survey Low and High Endline survey (21/12/2015 to lands (1-25.12.2017) 3/01/2016) Baseline survey Endline survey Middle Hills (6-10.08.16) (08-14.08.17) Figure 17 Periods of conduction of the well-being survey

2.1.4 Analysis of the collected data

Key documents and preliminary work for analysis Zerkalo Analytics provided, for each round of survey, a database and a technical report. The databases were provided in both excel and SPSS formats.

The data for Q31 (area of cultivated land) needed to be reviewed in the database of December 2017, as the data was not consistent with the data from 2015 (mistake in the types of land to include and in the unit between hectares and the local unit sotik). Zerkalo contacted the respondents again by phone to check the information.

For each round of the baseline surveys, a report of the main results was provided to ELMARL. For the endline surveys, this report is presenting the main outcomes.

The preliminary and analytical work to operate the database consisted of several steps, identical for the Low and High land database and the Middle Hills database: 1/ cleaning the baseline databases of the individuals who did not answer the endline survey 2/ ordering the respondents of both baseline and endline surveys in the same order 3/ creating one endline database with a copy of the data from 2015 to be able to analyse the evolution 4/ adding a code to differentiate in/off project, collective/no collective, CIG/no CIG 5/ calculating the well-being index and analyzing the variation of well-being between 2015 and 2017. Two techniques have been used to show the trends, which explain the different tables in the discussion part, sometimes showing a variation in percentage, sometimes an evolution in points. In some cases, percentages of categories of the population in the sample were calculated and presented (hence the percentage unit) for both baseline and endline, and then the evolution of these percentages was analyzed, which provided figures whose unit is in points.

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A separate file (excel) was created to calculate and analyze, indicator per indicator, the trend of evolution.

At the end two databases are available: the low and high lands database and the middle hills database, which gather all the information from both baseline and endline surveys (in SPSS file format).

Method of calculation of variation of well-being The evolution of the well-being was calculated according to the following steps:

First method: 1/ calculation of the well-being of the survey respondents => for each survey respondent, their well- being is calculated and reaches a number comprised between 2 and 51.7 (minimum and maximum of the WB indicator).

2/ Then, given following the mathematical justification:

Calling the values of the index of the baseline survey ( represents the value of the index for an individual , where goes from to ) and the values of the same index for the endline survey.

We look for the number so that if each index of each individual knew the same relative increase and would be valued as during the endline survey, then the mean value of the index obtained with the new values of the endline survey would be the same as with . This can be summed up then by24:

which means that the calculation of the mean well-being per group (project beneficiaries/nonproject beneficiaries, middle hills/low and high lands, baseline/endline) is then computed. For each group have been calculated two mean values of well-being, one for the baseline survey and another one for the endline survey.

3/ The variation rate is calculated by using the mean value of the index of well-being of the baseline and endline survey, per each group.

Variation rate of well-being= (endline survey mean WB index-baseline survey mean WB index)/baseline survey mean WB index *100

4/ The variation rates of each group are being compared for the purpose of the analysis.

Second method: This second method computes the variation of well-being for each individual, and then only, calculate the mean of all the variations of WB of all the individuals. This latter method of calculation calculates the absolute increase of well-being, while the first ones looks at the relative increase of well-being.

Both results have been used to illustrate the change in well-being.

24 This equation was provided by PhD Lionel Nguyen Van The – Mathematics Professor at the Institute of Mathematics, Marseille, France, UMR 7373

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2.1.5 Limits to the survey methodology

The survey has several biases:

 Households who state to be part of a group, also named “direct project beneficiaries” are underrepresented. This was impossible to address during the initial stage of survey preparation as no list was ready.

 The sample of group members is male dominated, especially in the middle hills (+30% of men), while the sample of non-group members is female dominated.

100% 90% 80% 70% 60% 50% Middle hills men 40% 30% Middle hills women 20% 10% 0% group members % non group members% ENDLINE

Figure 18 Comparison of gender representativeness in the endline middle hills sample

 The survey, as it has been designed, gives a photography at two instants with a one-year (for the middle hills) or two-year (for the low and high lands) interval between the pictures. It implies that micro-events which influence people’s mindsets at a specific moment (mudflow, avalanche, deceased relative…) and local events will seep through the data. This explains why a few local phenomena remain unexplained in the analysis part. This lack of information at villages and districts levels leaves us in the dark to find explanations of the analyzed dynamics. As an example, it would be worth understanding the land politics movement over the last two years in Nurobod district, the demographic evolutions and links with Kyrgyzstan for Jirgatol district…

 The analysis showed that some districts chosen as control groups react to very different dynamics than the district that they are supposed to mirror. Nurobod, for example, is a very good example of a district whose local dynamic differs greatly from Tavildara.

 An initial bias? The sample of in-project households suggests an initial situation with higher levels of well-being than the households who are out of project.

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2.2 Methodology of the qualitative survey

A qualitative survey has been conducted to provide additional insight into the quantitative data.

2.2.1 Focus group methodology25

The focus group technique has been chosen to gather information on how well-being has been transformed by ELMARL project.

The focus group sequence consists of six main questions that progress logically to explore any interrelation between the well-being of the participants of the focus group and the project activities. The full list of questions (including pokes to be used by the moderators) is available in the methodology document. The questionnaire was presented to Zerkalo’s team and reviewed with them. It was then tested on the field in two separate trips. The first one took place in Jirgatol, a one-day resting time between the trips was used to modify the questionnaire, which was then tested a second time in Kulob. A feedback meeting was organized in the field every day after the test focus groups to discuss about possible improvements with Zerkalo’s moderator and field assistant. The questionnaire was then finalized and handed over to Zerkalo, who conducted the trainings to the enumerators, based on the detailed methodology that was provided.

2.2.2 Sample constitution

The sample was designed as a mirror for the quantitative survey. The variables that were taken into account, along the variables in play for the quantitative survey are: - the district and area: projects were more or less successful according to the climate of the area and its location; - the group constitution (relatives, villagers…) and its dynamics: some groups have been constituted of only relatives of a single family, other groups have larger representativeness in the village; - the project’s domain: subprojects encompass a large number of different projects, each domain has its own specificities and successes; - the gender;

The year of start of the activity of the group (CIG, PUU, WUA) was determinant to conduct a focus group with its members, the aim being to assess the impact over a few years. Were chosen focus groups with groups who have started their activity in 2015 or 2016.

To enable analysis of the interactions between group members, two types of focus group were conducted:

- one focus group gathering all leaders of the different groups (if possible divided by gender) at the village level called “general focus groups”;

- one focus group gathering all members of one specific group (gender specific, according to the largest majority), named “ intra-group focus groups”.

Focus groups took place in the same districts where the quantitative survey was conducted, but it was not researched whether actual focus group respondents had also been interviewed in the quantitative survey.

25 the full methodology is available as an independent report. 28

Kulob Farkhor Tavildara Jirgatol Khovaling Baljuvon Faizabad male leaders 1 2 1 1 1 1 women leaders 1 1 1 1 1 1 WUA 1 1 intraCIG 1 1 1 PUU 1 Figure 19 Location, type and number of focus groups of the qualitative survey

2.2.3 Survey conduction: qualitative data collection

Period and number of participants The 5 test focus groups were conducted from Nov, 17th until Nov, 20th, and 19 focus groups were conducted by Zerkalo Analytics from Nov, 27th until Dec, 3rd, 2017.26 125 project beneficiaries took part in the focus group discussion, of which 32 % were women.

Qualitative survey women (%) 32.8 men (%) 67.2 Figure 20 Number of respondents to the qualitative survey

General attitude of the focus group participants A general view on the focus groups shows certain homogeneity of answers: participants generally agree with each other and share the same opinion. Discordant opinions can be sometimes heard between group leaders and group members, but in general, the participants share the same vision and understanding. The attitudes of the participants during the focus groups reflect this cohesion; they are respectful of each other, respectful of the moderators, and ready to discuss and share their opinions. Women have sometimes a harder time opening up and sharing their ideas, which makes the moderator’s work more arduous.

Actual scope of the project The analysis of the terms used by participants when they spoke about their activities in the frame of the project illustrates to whom they connect and whom they interact with. Activities happened at the household level, which implies the extended family and the neighbors, who play a key role in the activity implementation, either by being the trigger of the activity or by helping substantially. Groups are created at the household level (only with family members), or with neighbors, or at a larger scale (several mahallas or neighboring villages) in case of specific projects such as water user associations. The scale of the project is hence mostly at the micro-local level.

2.2.4 Analysis of the collected data Each focus group has been transcribed into Tajik and then translated to English. Each transcription represents 7 to 25 pages of text. The transcriptions were coded according to the main themes of interest (see the list of codes in annex). The translations were of unequal quality, which implied a bit of reinterpretation to catch the full meaning of some sentences.

The coded text has then been gathered in one excel file per theme, allowing hence for thematic analysis.

26 see list in annex. 29

The research question is the following one: How has the well-being of the beneficiaries of ELMARL project evolved through the start from the end of the project? The different domains of analysis are: the scope of change (geographical, social), the nature of change (what changed?) with a focus on the different domains of well-being (work, income, social cohesion, housing conditions, safety, roads and infrastructure, water access and quality…).

2.2.5 Limits to the survey

 some voices may not have been heard: some focus group participants seemed to not feel entirely free to speak and some focus groups that were organized did not respect the rules of women-only or were mixing genders when it was told unnecessary;

 Tajiks are emotional and very hospitable, and as a group, tend to outbid each other in the demonstration of gratitude and in the efforts to please the guests.

3. Analysis of the surveys: evolution of well-being from 2015 to 2017

This section summarizes the interesting points that come out of the analysis of the quantitative and qualitative surveys. A first subchapter looks at the results of the indicator for both the middle hills and the low and highlands while opening the discussion to a broader view of the well-being evolution. A second sub-chapter looks at the evolution of well-being per domain, and, at the same time, per district. It was chosen not to draw specific districts’ portraits, but to keep the analysis together to allow for trends’ comparisons. Both qualitative and quantitative data are mixed in the analysis per domain to support or infer each other. Quantitative data is also visible in the quotes of the focus group participants which time the analysis. Some of these quotes are in approximate English – it was chosen not to modify the initial translation to capture more of the meaning of the initial words- as long as the overall understanding remained possible. A third sub-chapter questions the limitations of the survey in regards to the results.

3.1 Assessment of the targeted indicator: increase of well-being: percentage of the population experiencing an increase of 20% of well-being

3.1.1. Overall result of the targeted indicator

Using a general assessment of well-being across the entire sample allows contextualization of the results. The overall trend of well-being over the entire surveyed population (who is mostly between 45 to 55 years old), whether in or out of the project, is less than optimistic: over half of the population sees its well-being (according to the indicators that have been chosen) in a downward shift;

However, ELMARL project managed to switch the trend and to help more than half of the in-project population (lowlands and uplands) to increase its well-being on average by 25%: 53% of the in- project households have increased their well-being against 46% of the off-project households.

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3.1.2 Detailed analysis of the targeted indicator

Direct beneficiaries in both the middle hills and the low and high lands experience the highest increase of well-being, out of all other surveyed categories. Similarly, it is for households living in villages where CIGs are active that the increase of well-being is the most significant, in comparison to other forms of collective projects.

Group members (respondents who state that they are part of a group (CIG or PUU) report for 31.7% of them an increase of 20% of their well-being. 25.4% of in-project women report a twenty per cent increase of their well-being (against 23.5% for men). In-project households in general have seen their well-being increase by four more points than the off-project households.

In the middle hills as in the low and highlands, women experience a higher increase of well-being than men.  Low and High Lands (over two-year evolution)

Low and High

Lands 2015-2017

Respondent type +20% WB in project 24.5 off project 20 in collective project 24.5 off collective project 20.7 HH living in a village with CIG 25.2 HH living in a village in project but 20.2 without CIG CIG members 31.7 No CIG members 21.3 men in project (%) 23.5 women in project(%) 25.4 Figure 21 Well-being evolution in the Low and High Lands in % 2015-2017

In the villages where the project has been active, 24.5% of the population has experienced a 20% increase of their well-being.

 Middle Hills (over one year evolution)

Middle hills 2016-2017 Respondent type +20% WB in project 9.44 off project - in collective project 8.57 off collective project 10.67 HH living in a village with CIG 9.46 HH living in a village in project but 9.38

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without CIG CIG members 16.13 No CIG members 8.05 men (%) 7.23 women (%) 11.34 Figure 22 Well-being evolution in the Middle Hills in % 2015-2017

In the villages where the project has been active, 9.44% of the population has experienced a 20% increase of their well-being. More women than men report a 20% increase of their well-being.

The one-year period has shown results approximately half that of the two-year survey conducted in the low and high lands. Furthermore, households who live in villages where no collective project has been implemented report a higher increase of well-being. This might be explained by the fact that villages where collective projects are needed experience very low standards of living.

3.2 Assessment of the evolution of wellbeing per domain

The following analysis explains and illustrates, by priority ranking, the impacts on the domains of well-being. Both quantitative and qualitative data analysis are presented together for each theme, allowing for the consolidation of conclusions or the opening of new research questions.

3.2.1 Health: towards better health conditions for the less healthy

Both quantitative and qualitative data analysis follow the same trend: the health status of the in- project households has improved, most notably for the individuals who were complaining of a very poor or poor health condition. Two indicators are analyzed: the health status of the respondent, and the health status of his/her family and relatives.

Indicator for health: Q48- How has been your health this last week? (Very poor, poor, fair, healthy, very healthy)

Overall, the health condition of rural households is improving, as shows the following table. 60

50

40

30 2015 20 2017 10

0 in project off project in project off project in project off project very poor or poor health fair health condition healthy or very healthy

Figure 23 Health conditions of respondents in 2015 and 2017, low and high lands (in %)

The analysis of the dynamics show that in-project districts have benefited from the project action most notably for individuals who had poor health status and were able to improve it to the next level of “fair health condition”.

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20 17 15

10 7 5 5

0 Very-1 poor poor Fair healthy Very healthy -5 -3 -3 -4 -4 -5 -10 -8 in project off project

Figure 24 Dynamics of evolution of health status from 2015 to 2017, low and high lands (in points)

The health of the beneficiaries is said to have improved, mostly thanks to the side effects of their implemented activities. Working, instead of staying idle, is said to have a positive effect on health. “If you are working, your health is improving. My health became better “ man in Baljuvon, orchard project

“Before my health was not so good, because I used to bring fertilizers from remote areas. Now I feel better, because I have a goat. My nerves eased.” project beneficiary in Kulob

“When I watched how they (the fish) swim, my health, especially my nervous system, got better”. man in Baljuvon, fishfarming project

For example, in Hamadoni district, the project, which financed a Water User Association, has enabled individuals to upgrade their health status from “very poor” to “poor” and from “fair” to healthy”.

20 14 15 12 12 10 8 5 0 0 0 Very poor poor Fair healthy Very healthy -5 -1 -10 -6 -15

-20 -18 -25 -21

In project Out project

Figure 25 Dynamics of evolution of health status in Hamadoni district (in points), 2015 to 2017

Other members of Water User Associations also tell that their activities have had positive effects on people’s health. “Water project has a huge impact on health

33

People can prepare food on time, wash their clothes and get better health. Thanks to our activity, people’s health has improved” member of WUA in Kulob

“Our work is good for people’s health” member of WUA in Farhor

Indicator for health: (Q49) Did one or some of your family members and relatives get sick in the last 30 days? (yes/no)

The overall trend goes towards an improvement of the household health status. In-project areas start in better position and keep their advance over the out-of-project households.

400

350

300

250

200 no, no sick family member 150 Yes, sick family member 100

50

0 2015 2017 2015 2017 In project Out project

Figure 26 Health status of the family members of the respondents in real value in low and high lands

Districts in the high lands have experienced a bigger increase of the health status of their family members than in the low lands. “Whatever we produce, the egg and dietary meat is good for health. There is an improvement” woman in Tavildara, turkey raising project 25 20 20 17 18 17 15 12 10 8 6 5 0 0

-5 -3

In project Out project

Figure 27 Variation of health status (no one was sick in the relatives over the last month) in all districts (in points)

34

Being healthy is the most important for Tajiks for their well-being. The overall trend, which goes towards a better health status, is hence favorable to a positive evolution of their well-being.

3.2.2 Money and Workplace: A ‘buzzing countryside’ at work

3.2.2.1 Start-up money: a key decisive input Most information for this paragraph is based on qualitative data.

All discourse about money shows that it is the essential trigger to be able to start an activity.

“The main root is this project. The project gave us money and we first bought a tractor. After construction, we bought more materials. Then we started the construction of dams and gates. The main thing is the money of this project.” Water User Association, Khovaling

“We had a land, but we did not have funds. We needed funds to fence it off with a metal fence, to buy trees, it was not possible for free.” man in Baljuvon

Beneficiaries express clearly that it is the initial investment provided by the project which allow them to overcome a previously insurmountable hurdle. They draw a direct causality link, between the fact that they received money and that they started working: “We were given thirty two thousand (32.000) somoni. We repaired the generator”, man in Jirgatol. “I got money and bought all angora goats for all the money” Woman in Farhor.

The project, by injecting money at the micro-level, to pockets of individuals, managed to give them the capacity to become active and to work. It has provided the necessary impulse to be active.

Then the invested money from the project has also given birth to money that was reinvested in other fields, following the example of the initial investment money from the project. Some project beneficiaries for example fenced more orchards from their own pocket after they did it initially with the project’s inputs.

This initial investment that has been provided by ELMARL project has enabled the population who participated to start imagining new projects, and dream about future plans. It allowed beneficiaries to open the doors to new ideas and prospects. New ideas are popping up, for example to create added value on all animal by-products (enterprise to spin wool, workshop for skin processing, enterprise to process the milk).

At the same time, this has also opened the door to new needs and dreams towards more “modernity” (2-storey house, beds vs kurpatchas27 …)

Indicator of investment: Q39 If yes, where did you take a credit from? (Bank, shop, relatives, friends, mahalla, other). In-project households show a slight increase in buying with credit from a bank between 2015 and 2017, when most of them usually take it directly to the shop. Buying at credit at the shop is often done for the purchase of usual food supplies (oil, flour..) whereas contracting a credit at a bank is typically synonym of bigger purchases.

27 Tajik mattresses piled up to make beds 35

3.2.2.2 Temporary work and being busy is progressing, permanent jobs still hard to find The term work encompasses several meanings:

Temporary and permanent employment First of all, work means being employed, may it be by oneself or by someone else. The project, in that matter, created numerous jobs. Participants make the difference between temporary jobs that were created, and permanent job places. Under ELMARL project were launched some short term renovation activities (road, water channels…), which provided temporary positions for local people.

“During the implementation of water project people were provided with work.” Man in Kulob

Permanent job places mean, for the interviewed population, an occupation with something for a long time. Owning a cow, sheep, running a fish farm or an orchard is considered as having a permanent work position. Permanent job places are important, because they insure constant income.

“I assess permanent work excellent because some of us did not have permanent work before and were unemployed. But under this project they found a job”M in Baljuvon

“I was jobless and found a job.” Man in fish farm, Baljuvon

This understanding has led to the extrapolation that the ELMARL project is a direct employer: “They are members of such program and have job places”

A healthy and happy occupation There is work that means “being active and not staying at home idle”, and this is important for people.

“Before work was not enough, but now everything has improved. I spend my free time in the orchard. 5 years ago there was no garden, we were sitting and loosing time at home” Woman in Kulob

Women mentioned the fact that work was good for their health, it is considered as healthy to move and be active. “As much we work, this will be sport for our body. The physical work has a big benefit to us” Women in Khovaling

Some participants shared their joy to work: “You will work, and you will have a good time.” Woman in Kulob

“Working hard”: revealing a strong work ethics Some participants of the focus groups underline the importance of working hard, which is important in life. “We want to breed cattle. Moderator: How? Woman: With hard work” Member of PUU, Tavildara Some participants explained that they learnt to work. “We learned how to work ...” Men, orchard project, Khovaling

People show a strong motivation to work despite hardships 36

ELMARL project contributed hence to the strengthening of work ethics. Participants also mention the importance of setting an example for the younger generation.

“The children begin to feel that they themselves will get involved in this work. They begin to feel this useful work. » man in Tavildara

Work is also a booster of self-confidence (we can work).

This is also fulfilling because people feel that they are were active for their lives.

“One of our neighbors is doing poultry. Another one has sheep and goats. Other one has cow. One of them took money from the organizations and is doing business. It differs a lot in comparison with previous years. “Woman in Khovaling Time gain Some beneficiaries mention that the project activities which put new land back into use have impacted their lives in the sense that some work has become easier: hay is available closer to the homes of the women who do not need to go to the mountains anymore.

Similarly, better road to access the pastures/fields in the mountain reflects into spending less time spent moving with the flocks and during the everyday commute of mountain workers.

Limited scale One participant mentioned that the program is actually too small to provide a real permanent job to all the group members, while acknowledging that it has a positive effect to wake up people and make them work. « 1-2 families find work in 50 hundred square meters. This is no workload from which a person could work permanently” man, Khovaling

The quantitative data backs up the last information, highlighting the limited impact in terms of creating employment.

Indicator of employment: Q20 Do you work? yes, no (unemployed, no (retired), housewife, other). The work situation has not changed significantly between 2015 and 2017, most noticeably; there has been a shift from being unemployed to being retired or a housewife, which is simply another category for someone who is not working.

15.0%

10.0%

5.0%

0.0% In project yes no no (retired) housewife -5.0% (unemployed) Out project

-10.0%

-15.0%

-20.0%

Figure 28 Variation of the work situation in and out of the project (in points) in the low and high lands

37

Women employment on the rise

ELMARL project has been instrumental in providing work for women in rural areas.

Moderator: “Which of the factor did this program affect more? Woman: the job, housewives come to work, they got money, they are doing something in the life” Woman in Baljuvon

“Women are working” Member of PUU Faizabad

“Women work, receive the wages and promote their lives.” Woman in Kulob

It seems that the project has acted as a revealer of the women’s want and capacity to work. They have learnt technical knowledge easily and it unveiled new young potential labor force in the countryside.

Gender analysis of the indicator of employment: Q20 Do you work? yes, no (unemployed, no (retired), housewife, other) Women have increasingly been working, while at the same time, men were losing job positions. Women have also become pensioners or went back to being housewives. Interestingly, for off- project respondents, the variation is inversed: -18% of women have gone from an employed position towards a housewife position (+15 %) or to being pensioner (+4%).

20.0% 16.7% 10.6% 10.0% 4.8% 2.7% 0.0% 0.0% 0.0% 0.0% 0.0% yes no no (retired) housewife other -10.0% (unemployed) -10.0% -20.0%

-30.0%

-40.0% -41.7% -50.0%

In project Man In project Woman

Figure 29 Variations of employment status between 2015 and 2017 in the high and low lands (over 649 respondents)

Two specific case studies have been added in annex to showcase the effect of ELMARL project in bringing rural women on the job market.

3.2.2.3 Increased land productivity thanks to more irrigation water

Several indicators in the quantitative survey, as well as feedback from the focus groups show that the land and agricultural productivity have increased.

Indicator for agricultural productivity: How is the quality of this land? (Q32) (very good, good, ok, poor, very poor)

38

The analysis of the evolution of the quality of the land is facing two main obstacles: First, the quality of land cannot significantly increase over a two-year period, second, the sample of individuals who answered this question has been modified: some have stopped working the land, while others have started, which means that they have not provided data on land during the baseline survey, which distorts the final analysis. Nevertheless, the analysis of the appreciation of the quality of land shows that the overall trend goes towards an increase of the appreciation of the land quality; all districts are witnessing this trend.

60

50

40

30

20 in project 10 off project

0

Figure 30 Variation of a positive appreciation of land quality (“good” quality) in all sampled districts low and high lands between 2015-2017 (in points)

Indicator for money and workplace and agricultural productivity: Q33 How long do you need to wait for irrigation water in the summer time? (days) (non-irrigated land, 10 to 15 days, 5 to 10 days, 0 to 5 days) Patterns are not obvious in the case of the indicator n°33. In some cases, farmers have abandoned their piece of land, others have grabbed a new piece of land, for which no data was existent. In Hamadoni, for in-project households, there has been a decrease in all categories, except for non- irrigated land. It seems that there has been a switch in the use of irrigated lands to non-irrigated lands. One WUA has been created in Hamadoni, which only represents a very small portion of the sampled population in this district, which may explain why the rehabilitation of irrigation infrastructure is not visible in the presented data. In Kulob, Tavildara and Jirgatol districts, the pattern is inversed: a decrease in the use of non-irrigated land which translates into an increase in shorter waiting periods (11 to 15 days and 0 to 5 days). In Farhor district, the situation is different, with an increase for the period of 5 to 10 days and for more than 15 days;

39

60.00 50.00 40.00 30.00 20.00 10.00 0.00 -10.00 non irrigated 15 to 90 days 11 to 15 days 5-10 days 0-5 days -20.00 -30.00

In project Out project

Figure 31 Variation of waiting time per respondent for irrigation water in Hamadoni district 2015-2017 (in points)

30

20

10

0 non irrigated 15 to 90 days 11 to 15 days 5-10 days 0-5 days -10

-20

-30

-40

Kulob Tavildara Farhor Jirgatol

Figure 32 Variation of the waiting time for irrigation water in project districts 2015-2017

For in-project respondents, it is in Kulob and Tavildara that can be observed the most significant impact: a shortened period of waiting for irrigation water as well as a greater part of the land being irrigated. “We have enough water now to grow three harvests a year the water supply is 100% now. The yield has increased, when there is water the yield will increase. Men in WUA in Kulob

“We have greatly benefited from this; we irrigate gardens, vegetable fields” “The land was not irrigated enough. We could not get the harvest, the village where there was water, could not give it. Water has been brought now and most of farms do not feel the need for water neither for drinking nor for irrigation of fields” Men in WUA in Tavildara

Indicator for money and workplace and agricultural productivity: Are you receiving enough irrigation water? (Q34) (Largely enough, enough, not enough)

40

In-project households have significantly benefited from subprojects aiming at increasing irrigation water availability (except for the specific case of Jirgatol). 30.0 25.0 20.0 15.0 10.0 5.0 0.0 -5.0 Jirgatol Tavildara Kulob Farhor Hamadoni -10.0 -15.0 -20.0

in project out of project

Figure 33 Variation of availability of irrigation water between 2015 and 2017 (category: largely available)

Furthermore, the percentage of households complaining of not having enough irrigation water has decreased for in all districts. The change is radical in Tavildara, but remains quite shy in other districts.

0

-5

-10

-15 in project -20 out of project -25

-30

-35

-40

Figure 34 Variation of availability of irrigation water between 2015 and 2017 (category: not enough irrigation water)

Furthermore, some new pieces of land have been put back into use (thanks to fencing). "We returned 1 hectare of unused land to life.” Man in Baljuvon, orchard project

The increase in availability of irrigation water has helped increase the yields of the harvests and has enabled to multiply the number of crops: “I completely provided my family with potatoes, from our own harvested potatoes.” Man in Tavildara, WUA member “We got a benefit as potatoes, watermelon, melon and pumpkin from land, which was useless for a long time” Man in Baljuvon “The main reason is the fact that the dams are built and the farmers receive three harvests per year.” Man in Kulob, WUA member

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3.2.2.4 Income

Indicator of purchasing power: Were you able this month to buy what you needed for the household (oil, flour, sugar, rice, clothes, furniture, medicine, transportation …)? (Q37) The general trend, for households in or out of the project (except Tavildara), is the increase of purchasing power which enables households to go from the category “Not enough (I had to choose the most urgent things)” to the category “yes, normally (I could buy all that I needed but without extra)” 70 60 50 40 30 20 10 0 -10

In project control group

Figure 35 Increase of purchasing power 2015-2017: I could buy all what I needed but without extra (in points)

In-project households benefit from a slight advantage in comparison to off-project households, as Jirgatol and Hamadoni figures show. 8.00 6.00 4.00 2.00 0.00 -2.00 Jirgatol Tavildara Hamadoni Kulob Farhor -4.00 -6.00 -8.00 -10.00 -12.00 -14.00

yes, totally (I could buy all I needed and more) not at all enough (I could not afford the most urgent items)

Figure 36 Variation of purchasing power extremes between 2015 and 2017 for in project households in project districts (in points)

The comparison of the answers for the 2 most extreme categories “yes, totally: I could buy all I needed and more” and “not at all enough: I could not afford the most urgent item” shows that the percentage of households answering either the first or the last answers has been decreasing (except for Tavildara). This can be interpreted as a homogenization of the level of cash income within the households, a sign of lesser disparity in terms of income between households. In Hamadoni, the table shows that the overall level of purchasing power has done a significant positive jump. The amount of income differs largely from household to household: some got a ten-fold increase, some are still waiting for their trees to give fruits in a few years.

42

“What mark would you put for money? Man- Bad. Maybe we will take income after three years when our plants grow up.” Man in Jirgatol, orchard planting

Several participants mention a very modest income which translates into a small increase of living conditions.

The income offered in the frame of the ELMARL activities seems not able to compete with migration income, as most activities have been taken over by the active population of the countryside that is not going to migration: older men and women, who are retired, or women.

One participant mentioned though that he was able to stay in his village and avoid migration.

There are 2 kind of incomes: cash that beneficiaries receive from selling products or services: “I sold a bit of sour milk (chakka) in the market. “ “I earned money. “ Women in Farhor or money that is saved because products or services are available at home now and it is not needed to buy it anymore (cow dung being used as fertilizer, honey, dairy products, meat, vegetables, fruits, lin oil): “I save money for other family needs” man in Baljuvon, speaking about fish and buying food

“this is progress that the money that we could spend for the purchase of kurut we keep it for ourselves” women in Jirgatol, milk processing

The additional incomes are used for various purposes: paying for weddings, education, housing equipment…

“In the past, my parents used to give money. Now I give money for study (from selling dairy products)” woman in Khovaling

“Now it is good. We sell the honey and buy clothes for our children.” Woman in Khovaling

“We have wedding each 5-6 years. There are many such events. We need to do in such way that we can kill one sheep for one wedding.” man in Khovaling

“We bought high-quality carpets, TV. Daughters got married.” member of PUU Tavildara

Indicator of income growth- savings: Do you have savings (apart from livestock and cars)? (No, I have no savings/ Yes, I have savings) (Q40) Savings rates are very low in Tajikistan, in 2015, 95 to 99% of the sampled households were stating not to have any savings. The relative increase that the following table demonstrates in three in-project districts (Jirgatol, Tavildara, Hamadoni) hence concerns a very few individuals (three of them) who have found the means to save money while participating in the project. On the contrary, in Khatlon area, six households out of eleven (2015 baseline survey) have lost their capacity to save cash.

43

8.00 5.88 6.00 4.00 3.03 1.79 2.00 0.00 0.00 0.00

-2.00 -0.99 -0.83 -4.00 -4.17 -3.94 -6.00

In project Out project

Figure 37 Evolution of households who own savings between 2015-2017 in low and highland sampled districts (in points)

Indicator of investment: Q39 If yes, where did you take a credit from? (Bank, shop, relatives, friends, mahalla, other). This question shows that in-project households have been able to sustain their purchasing power while off-project households have seen their use of credits decreased by 20%.

Knowledge New activity/old activity: learning new practices A difference comes out between the beneficiaries who started a new activity and the ones who are pursuing an activity into which they were already engaged. Newcomers have numerous gaps to overcome to successfully manage new activities, including the lack of knowledge, i.e. the management of animal varieties that are ill-adapted to their areas. This is also a source of stress for the beneficiary, and a reason why some activities have not received income. One fisherman mentioned losing half of his new fish when they arrived in the pond, because of difficulty during the transportation or inadequate feeding practices. Some people who received livestock are putting high expectations on its future sales.

Knowledge has been increased: beneficiaries have learnt new skills in link with their activity implementation:

“When the seminars were held, we realized that we do not use the land properly. In the seminars we were told how to make pasture. If this year you feed them in one place, then next year you should feed in another place. Very good work has been accomplished.” member of PUU in Tavildara

“I experimented with pistachio trees” man in Baljuvon

3.2.3 Living conditions

Indicator of living conditions: number of people per room (Q 19) The overall trend shows a diminution of the number of people per room across all districts, except Jirgatol. As described in the table below, cases of households with four and more people per room have been decreasing over the last two years, except for the households who have been off-project in Jirgatol district.

44

10 6 5 0 0 in project out of in project out of in project out of in project-1 in project out of -5 -2 project project project project -6 -6 -5 -10 Jirgatol Jirgatol Tavildara Nurobod-7 Kulob Vose Farhor Hamadoni Hamadoni -15 -12

from 4 to 14 people per room

Figure 38 Variation of the number of people per room between 2015 and 2017 (overcrowded cases

This improvement in living conditions is confirmed by a parallel increase of the number of households who accommodate two people per room.

The following table shows that in all cases, the number of households who accommodate two people per room has increased from 2015 to 2017, except for Jirgatol (who has suffered from specific circumstances) and Hamadoni, which is explained by an upgrade of the living conditions there. Households who had in the past two people per room upgraded their living conditions to fit one person per room.

25 20 15 10 5 0 in project out of in project out of in project out of in project in project out of -5 project project project project -10 Jirgatol Jirgatol Tavildara Nurobod Kulob Vose Farhor Hamadoni Hamadoni -15 -20

2 people per room 1 person per room

Figure 39 Variation in the number of people per room between 2015 and 2017 (categories from 1 to 2 people per room) (in points)

Indicator of living conditions: Do you consider that you have good road access to district center? (Q36) (Yes, good/ok,/no, very bad)

According to the survey respondents, the road condition has improved, except in two districts, Kulob and Hamadoni. The result is surprising for Kulob district, which has benefited from the largest project financial support of all districts (1,8 millions somonis) for road rehabiliation. In Hamadoni, there has been no road rehabilitation supported by ELMARL project.

45

30 20 10 0 -10 -20 -30 -40 -50 -60

in project off project

Figure 40 Variation towards a “very bad” road condition 2015- 2017 in all districts (in points)

Indicator of living conditions: time to fetch water (Q43) How much time do you need to fetch drinking water every day (in hour)? (more than 3 hours, 2h to 2h59 min, 1h to 1h59 min,0 to 59 min)

The effect of ELMARL project on reducing fetching water time, so in bringing drinking water source closer to the beneficiaries home is obviously demonstrated by the following table.

60 50 40 30 20 In project 10 Out project 0 -10 -20 -30 -40

Figure 41 Evolution (in points) of the percentage of households who take between 0 to 1 hour to fetch drinking water every day

However, some households have seen their fetching water time increase, namely in Jirgatol, Kulob, and Hamadoni, and this, also in districts where ELMARL project has been operating. It seems that households, who already did not have good access to drinking water, have, to some extent, less benefited from the construction of drinking water infrastructures. A case study of a village in Farhor has been added in annex to showcase the change in drinking water facilities that ELMARL subproject have brought.

46

25 20 15 10

5 In project 0 Out project -5 -10 -15 -20

Figure 42 Evolution of time spent per day to fetch water, for the category “3 hours and more” 2015-2017 (in points)

Indicator of living conditions: local electricity production (Q41) Is there a local unit of electricity production in your village? (yes/no) In 2015 (baseline data), eleven households were mentioning the presence of local electricity production units in their village. In 2017, this number has dropped to five electricity production units. This indicator is not part of the aggregated well-being index, and this, from the beginning, as ELMARL project has not been focusing its efforts on local electricity production.

Indicator of living conditions: quality of drinking water (Q43) What is the quality of the drinking water that you collect? (Very poor, poor, ok, good, very good) In 2015, 50% of the households stated having good quality drinking water, households being within the project areas being better off for the 2 extremes (very poor and very good quality).

60

50

40

30 in project mean off project mean 20

10

0 Very poor poor ok good very good

Figure 43 Quality of drinking water (baseline 2015, mean % of households) low and high lands

In 2017 70% of the households in all sampled districts (in-project and off-project) state to have access to good quality drinking water.

47

80 70 60 50 40 in project mean 30 off project mean 20 10 0 Very poor poor ok good very good

Figure 44 Quality of drinking water (endline 2017, mean % of households) low and high lands

The quality of the drinking water for households in project areas has concentrated on two categories (OK and good quality), which comes from the loss of quality for very good sources, and in increase in quality for “poor” drinking water. The identification of the reasons for the loss of the water quality would require further research. The project seems not to have been able to reach a few remaining households who have access only to very poor quality of water. Within the project scope of action, the biggest improvement happens in the highlands: Tavildara and Jirgatol witness a significant increase in the quality of their drinking water, while low lands (Khatlon) are suffering from a decrease of their water quality.

3.2.4 Food availability and nutrition improvement

Indicator of food access and nutrition: do you grow vegetables in the land next to your havli? Q46- (yes/no) In 2015, 98 to 100% of the households from the high lands (in the project areas) were cultivating vegetables in their home gardens. In the low lands, a lot less households were doing so, i.e. between 70% to 90%.

Farhor 90 66 Kulob/vose 85 70 Hamadoni 71 88 Tavildara/Nurobod 100 95 Jirgatol 98

0 20 40 60 80 100 120

Out project In project

Figure 45 Percentage of households cultivating vegetables in their garden in 2015 (%)

In 2017, the situation in the high lands has not changed significantly, but the low lands have seen an increase in the number of households who start growing vegetables in their garden. Now, 94% of the

48 households in Hamadoni grow vegetables in their home garden. The trend is more significant for households who are within project districts.

40 33 35 28 30 25 22 20 15 14 15 9 10 6 4 5 0 -5 -3

In project Out project

Figure 46 Percentage of increase (%, from 2015 to 2017) of the number of households who are growing vegetables next to their house

A comparison with off-project districts shows that more households located in-project districts grow food in their home garden. The qualitative research also shows that more food is available for households who took part in the project, as a lot of horticultural subprojects have been implemented successfully.

“Now there is everything, carrot, cabbage, pickles, even meat.” Member of WUA, Kulob

Indicator of food access and nutrition: Q47 For how long can you feed your family with your own home production (potatoes, onions, carrots)? (only during the vegetables season, up to 3 months, up to 6 month, the whole year)

The general trend shows a reduction of period of self-sufficiency on home produced vegetables. Fewer households rely on their home grown production for periods of one year, while more households are consuming their own vegetables only during the growing period. This can be explained partially by the fact that new home growers have started to grow vegetables in their garden, so they still are at the beginner stage.

Only during the 2015 vegetables season 14%

up to 6 months or the whole year 36%

Up to 3 months 50%

49

2017 up to 6 months or Only during the the whole year vegetables season 33% 27%

Up to 3 months 40%

Figure 47 Period of consumption of home produced vegetables (2015 to 2017) in-project districts

The qualitative research sheds light on the effect of subprojects entailing livestock keeping, which is not visible in the quantitative research. The focus group participants tell about the numerous benefits that they have received from their newly owned livestock. Through the project activities, the availability of nutritious food for the whole family but more importantly for children has increased: “The meat of the turkey is dietary, and eggs were used and eaten” Woman in Tavildara, turkey raising project

“The change is that the children are now provided with milk and dairy products” Woman in Farhor

“Thanks to our cattle, our table cloth became full of milk, oil, sour milk” (Woman, Khovaling)

The produced food at home implied monetary savings, what is produced is not needed to be bought. Several participants explain their improved ability to welcome guests, which largely contributes in return to an improved social status. Some participants mentioned that the advantage is to have some products available at home when they are not available on the market.

“Before we used to go to the district center and sometimes we could not find it” woman in Jirgatol, milk processing

3.2.5 Reinforced social cohesion and more leisure time

Indicator of social cohesion and leisure: Q50 Did you enjoy some relaxing time with friends or family (visit to relatives, weddings, birthday parties, sport, meeting with friends…) in the last 30 days? (yes/no)

In-project households have seen a sharp increase in their leisure time from 2015 to 2017.

50

400

350

300

250

200 relaxing time 150 no relaxing time 100

50

0 2015 2017 2015 2017 In project Out project

Figure 48 Number of households stating having relaxed or not over the last month in all sampled districts in the low and highlands

All in-project districts except Hamadoni have experienced an increase of their leisure time.

50

40

30

20 In project 10 Out project 0

-10

-20

-30

Figure 49 Variation of leisure time in and out of project scope from 2015 to 2017 (answer= yes, in points)

Indicator of social cohesion and leisure: Q51 .Did you help your neighbors in the last 30 days? (yes/no)

In general, households in and off districts have been increasingly helping their neighbors. In Tavildara, the figure remains unchanged over the years (70% of the households have been helping their neighbor over the last month). The maximum neighbor solidarity is in Hamadoni (95% of housholds) and the minimum in Farhor (42%).

51

400 350 300 250 200 No 150 Yes 100 50 0 In project Out project In project Out project 2015 2017

Figure 50 Number of households helping or not their neighbor over the last month

50 40 30 20 In project 10 Out project 0 -10

Figure 51 Evolution of number of households helping their neighbor (2015-2017, in points)

Indicator of social cohesion and leisure: Q52 Was there any community work organize recently in your village? (yes/no) In-project households have a better chance of knowing that a “hasha” is taking place. There might also be an initial bias here since it is likely that the more active population of the village got engaged in a CIG and wrote a project proposal to access funding whereas those members of society who are less connected to influent society members will likely not have participated. 90 82 80 70 70 58 57 60 47 50 40 26 29 30 24 20 20 10 0

In project Out project

Figure 52 Percentage of households knowing that there was a hashar in their village recently (in %), in 2017 52

In low lands and Jirgatol, the percentage of households aware of hashars has increased (or the number of hashars has increased). In Hamadoni and Tavildara/Nurobod, it has on the contrary decreased, but in lesser extent for in- project households.

50 40 30 20 10 In project 0 Out project -10 -20 -30 -40 -50

Figure 53 Evolution of the percentage of the number of households who are aware of the happening of a hashar (2015- 2017 in points)

ELMARL project gave impetus for stronger cooperation between villagers by asking for group creation and by providing grants for collective infrastructure. The qualitative research shows that the project contributed to create a common sense of purpose amongst residents of the engaged communities. “The first benefit of the program is that we gathered our forces. We organized one group” Man in Khovaling, orchard project Some of the hashars were so meaningful to the local population that too many workers showed up on the construction site and that they had to take turns to work. “The people did the work themselves 10 people worked one day and the other 10 people worked the next day. There were so many people; the work was not enough for everyone Now water is distributed equally to everyone.” Member of Water User Association in Kulob

Cohesion has improved at different levels: . between neighbors: gifts of food, helping each other, sharing knowledge and outputs, sharing cow dung as fertilizer; “My neighbors help with loading the goods. We give them honey” man in Kulob “Whoever asks we teach them. “ PUU member, Faizabad “We are also providing milk and sour milk for the neighbors, families who have shortage” Woman in Farhor And they also have been sharing knowledge: they taught or got taught, found local experts to be taught, and beneficiaries got an aura of knowing more and sharing advice, neighbors came to ask them for advice.

. between group members: sharing equally the outputs of the activity; “We divided harvest and bee families equally between the 7 members of our group” Man in Tavildara

. in the community and between villages: as an example, the Water User Association has equally regulated the access to water for farmers. This has been evaluated as a key intervention by the beneficiaries.

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Gathering forces for bigger projects Groups also started to collect money on their own initiative for work of collective scale (road improvement)

« When we created a group, before we received money, we also had necessity in contribution of this people in order to provide with all conditions. For example, construction of canal, we had to give money to tractor driver. Before we started, one of us gave money, one of us gave equipment, one of us dug the canal. By this, we finished all this work. Everything has happened according to the words of head of the group.”

Willingness to share the benefits Some beneficiaries mention that they would be willing to contribute to larger community projects with the income that they received from the activity initiated with ELMARL.

“If there will be an additional income then of course we can make a contribution to other spheres. Not fully, but we can make a contribution in a certain amount, we can help. For example, the road is the most important thing” Woman in Tavildara There is a general understanding that benefits that have been earned need to be shared, and this, mostly amongst women. “So that not only I ate, but we together.” woman in Farhor

Tensions appeared Some examples showed that some group leaders did not share equally the attracted resources but favored individual or familial interest (ex: water supply in front of the leader house). Furthermore voices of discontent were difficulty heard with the focus group method.

Women and institutions The analysis of the institutions with which the women are interacting during the project activity implementation shows that they have little contact with any kind of formal or informal institutions (mahalla, jamoat, hashar…). These terms do not appear in their discourse when they mention their activities.

The implementation of the activities did not significantly challenge the society structure, in which women are less connected, and have little link with village institutions. This can possibly contribute to the inequality of resources distribution.

mahalla, dekhan neighbor farm, water men women relatives association, other villages, cities, children

Figure 54 Men and women networks in the implementation of ELMARL project

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3.2.6 Safety

Safety feeling has worsened in all sampled districts, except for Tavildara. During the process of the index development, the focus groups showed that safety is often understood as being safe from war, in contrast to the civil war in 1992-97. Further discussions with focus group participtans also opened this narrow definition. According to the participants ’understanding, safety also referred to crime (robbery, theft) as well as to feeling safe from natural disasters. It seemed an important contribution to the well-being index as ELMARL subprojects were initially encompassing adaptation measures to natural disasters.

10 5 0 -5 -10 in project -15 off project -20 -25 -30 -35 -40

Figure 55 Variation of the reported feeling “completely safe” across districts 2015-2017 (in points)

20

10

0

In danger in project -10 In danger off project

-20

-30

-40

Figure 56 Variation of the reported feeling “in danger” across sampled districts 2015-2017

The feeling of danger has increased, especially in Jirgatol, and the increase of the perception of being in danger is noticeably higher in districts that are off project. Given the quite stable inner political context, it can be interpreted as an increased feeling of vulnerability to natural disasters. The winter 2016-2017 indeed was marked by numerous avalanches, mudslides, which have sometimes damaged the work accomplished by beneficiaries. A look at the financial data also shows that very few projects aiming at reducing natural disasters (forest planting, riverbank restoration,) have been implemented. They represent barely 1%28 of the total funding allocated to subprojects.

On safety, the focus groups of the qualitative research did not provide insightful data regarding the evolution of their safety.

28 own calculation based on M&E financial data 55

3.2.7 Subjective well-being

Subjective well-being refers to the feeling of happiness and satisfaction of one person about its own life. Respondents of the quantitative survey had to grade their current and future life situation on a 10-point scale (0 the worst, 10 the best). It is an important aspect of well-being because it brings the own judgement of one person, with all its history and background, about its own life. It helps bring subjectivity in this question of life satisfaction.

Subjective well-being evolution (Q55, Q56) Only two districts have seen the individual in the category “suffering” (people whose well-being is at high risk) increase their subjective well-being (Tavildara and Hamadoni, for the in-projects). These respondents have poor ratings of their current life situation (4 and below) AND negative views of the next five years (4 and below). They are more likely to report lacking the basics of food and shelter, more likely to have physical pain, a lot of stress, worry, sadness, and anger. In all other districts, the category of individuals who are suffering has increased, the increase being more significant for off-project individuals.

30 21 20 17 15 9 10 6 0 1 0

-10 -12 -20

-30 -27 In project Out project

Figure 57 Evolution of the “suffering category” of individuals (2015-2017)

30 27 24 25 20 20 15 12 10 6 4 5 0 -5 -4 -10 -8 -15 -20 -17

In project Out project

Figure 58 Evolution of the “struggling category” of individuals (2015-2017)

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25 21 20 18 15 8 10 6 5 2 0 -5 -2 -2 -4 -10 -6

In project Out project

Figure 59 Evolution of the “thriving category” of individuals (2015-2017)

Tavildara and Kulob experience an increase in the subjective well-being of their households, Farhor, Jirgatol and Hamadoni a decrease.

3.3 Limitations to the taken approach and survey

The well-being index presents some limitations, and the results should be interpreted in light of external factors impacting well-being.

Macro level scale Its large scale has not favored an analysis close to the project beneficiaries, but allows to look at larger trends across districts, which could lead to overgeneralization, and brings up questions that can only be answered with more local knowledge. The scale of analysis here would have been relevant for a systematic state program, but proved incomplete for a less systematic approach.

Control groups Control groups are not always representative of the in-project districts that they were supposed to mirror. Other project interventions in control groups may have created noise which blurred the analysis. True controls are difficult to find in the country as numerous projects are being implemented not necessarily in coordination with other implementing institutions.

An early endline survey The endline survey had to be conducted before the end of the ELMARL project, but this time limit does not match with the necessary time for most of activities of the subprojects to deploy their effects. Numerous subprojects are agricultural projects and imply several years of activities before giving benefits for the beneficiaries.

Economic crisis in Tajikistan The survey took place in a period of economic crisis in Tajikistan, whose economy is highly vulnerable to external shocks. The Russian recession, following the decline of oil prices, has impacted the remittances flow in Tajikistan, for which remittances represents 36.6% of its GDP29. Between January and September 2015, remittance levels were 65 % lower than levels during the same time period in 2014. In 2016, remittance flows decreased by 14.5%30. The depreciation of the Tajik somoni has impacted the purchasing power of households, while the national bank crisis was severely affecting trust and the business climate in the country. “According

29 Central Bank of Russia, External Sector Statistics, accessed November 28, 2016, www.cbr.ru/statistics/?PrtId=svs. From IFPRI, Global food policy report, 2017 30 Ibid. 57 to the country’s National Bank, the official exchange rate of somoni against the US dollar decreased by 12 percent in 2017 (the decline was 10.8 percent in 2016)”31.

4. Conclusions on the results of the surveys

4.1 General conclusions

. The large scale and broad nature of the well-being survey has not favored an analysis close to the project beneficiaries, but allows to look at larger trends across districts. This scale of analysis would have been relevant for a systematic state program, but proved incomplete for a less systematic approach, such as the ELMARL project. This limitation may have hampered the quantitative visualization of the full impact of ELMARL;

. The qualitative survey brought key additional information about well-being in regards to the resilience to climate change framework. Elements of information such as social cohesion and knowledge increase are crucial for the resilience capacity of the rural population;

. ELMARL project managed to switch the trend from “business as usual in a poor economic context” and to help more than half of the in-project population to increase its well-being on average by 25% (53% of the in-project households have increased their well-being against 46% of the off-project households). And there is clear evidence that ELMARL has been beneficial for all its beneficiaries, in terms of well-being increase: In-project households have seen their well-being increase by four more points than the off-project households.

. Within the in-project population, well-being has increased of 20% at least for 30% of the most direct beneficiaries of ELMARL project.

. The closer the beneficiary is to the source of the grant, the more impact it has on its well-being. Indirect beneficiaries report lower increases in well-being from ELMARL project than direct ones.

4.2 Domain-related conclusions

. There are a few domains where both quantitative and qualitative data show a concordance of conclusions even though remains a few exceptions: linked to the project’s intervention, health has been improved, as well as women employment, land productivity (land quality, but most significantly the waiting time for irrigation water), the quality of drinking water, leisure time, helping the neighbors, the number of people sharing rooms has decreased;

. some domains have remained stable, without showing any modifications: work situation and income – the purchasing power of the in-project households remained similar, although it decreased in off-project households, which can be interpreted as ELMARL playing the role of shock absorber;

. Other domains receive mixed results in terms of improvement: community work have been decreasing in a few districts, drinking water fetching time has not progressed equally between districts (some faraway places have been forgotten), and road conditions improved in only 2 districts;

31 https://www.azernews.az/region/127100.html 58

. There are a few domains that show a negative trend across most districts: safety (its definition encompasses national security as well as natural disasters and crime) has worsened, subjective well-being has worsened (although people tend to grow happier as they get older), the local electricity production situation has decreased;

. There are no domains of well-being that ELMARL has unanimously (over all in-project districts, for all the in-project population) been improving, backed up by both quantitative and qualitative data;

. social cohesion has greatly improved, and the importance of being together and working together is a key output coming from the majority of the focus group participants;

. The hope and energy that was transferred to the active population from ELMARL is also well demonstrated in the survey; nicknaming ELMARL project ‘a rural Tajik New Deal’ is not exaggerated. “The people woke up” Man in Khovaling, women in Kulob

. ELMARL project has been an eye-opener for its beneficiaries: “I would like this program to act in future more and we didn’t have imagination about this program. Now we have imagination and saw many benefits” Women in Khovaling

. Knowledge has increased amongst beneficiaries and self-governance capacity is being reported as increasing as well. Created CIGs have indeed become aware of their own capacity to solve local problems, and of the mechanisms and necessary organization to collectively solve them.

4.3 District related conclusions

. There is a large variety and heterogeneity of situations all across the different sampled districts and individuals. Many peculiarities exist for each district, due to its own history, external and internal influences, and to individuals, which makes it impossible, due to ELMARL variety of subprojects, to address all themes simultaneously, and to show a homogenous increase; For example, a project on improving availability of irrigation water in Kulob has very different effects than a project that provides angora goats to women in Jirgatol.

. Tavildara seems to have very positively benefited from ELMARL project in comparison to other districts where the results are more mixed. In earlier studies, Tavildara was assessed as one district that was both most food insecure and vulnerable to climate change32;

. Jirgatol seems to be going against trends shared across all other districts, there is some specificities there than would need to be explored;

4.4 Final conclusions

. The comparison of both quantitative and qualitative data enables to consolidate the collected information and to draw firm conclusions on ELMARL positive impacts on the well- being of the population in regards to building resilience to climate change;

32 Wolfgramm, B., Stevenson, S., Lerman, Z., Zähringer, J., Liniger, H., (2011) PPCR: Tajikistan, Component A5, Phase 1: Agriculture and Sustainable Land Management, 59

. Direct effects on ELMARL project are already visible, and long-term effects (such as soil erosion limitation, disaster risk reduction) should be monitored in the future,

4.5 Lessons learnt on the Well-Being index

4.5.1 Positive aspects of a well-being index

. The well-being index was the trigger to generate the concept of well-being according to rural Tajiks. It provides one of the most accurate methods to detect the finest changes in life dynamics in Tajikistan.

. The advantage of the well-being index is to give us the broad picture to look at. There has been an effect – and this is reflected in the increase of well-being, but the sum of the micro pictures shows that all effects did not converge over the two years in the same direction. Time will be needed to homogenize the impact;

. The index development process has been the occasion to challenge understanding of well- being amongst the staff working on the topic;

. the combination of qualitative and quantitative methodologies is key to get the full picture;

. the Cantril ladder of life is a very helpful and functional tool to assess subjective well-being, even in rural areas

. the well-being index was key in highlighting the importance of social cohesion (or working together at the community level) in the process of coping with climate change; ELMARL project, by asking the population to create working groups, has launched a human dynamic which is the pivot on which further collective action can be organized towards climate change adaptation and resilience.

4.5.2 Comparison with the indicator of “Listening to Tajikistan”

The indicator “listening to Tajikistan” is following a different approach in measuring well-being. The evolution of well-being is observed by looking at the correlation of subjective well-being (how do you feel today?) with a variety of indicators.

This approach was proposed for this survey as well after the first baseline survey (it was called “abridged well-being indicator”), but the proposition was not retained. This approach is mathematically sound and presents the objective value of well-being indicators without the human subjectivity. In comparison, the chosen method in this particular survey, which is based on what individuals say what matter to them, provides a different priority ranking of the domains of well-being.

Finally the Listening to Tajikistan survey does not aim at aggregating all data into one single indicator but analyses all factors every two weeks to be able to catch trends.

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4.5.3 Further improvements

. Allow for construction of a strong sample from the beginning of the survey: predetermined beneficiaries (geographical location, number, age…), reliance on computerized census list, strong administrative follow-up of the beneficiaries, identity card for project beneficiaries…

. It should be completed with sociological research once the endline survey has been conducted and analyzed: quantitative data analysis opens numerous research questions

. Setting a target for well-being should be done purposefully and realistically, by keeping in mind existing ranges of increase in well-being in other countries

. It could be relevant to select the most meaningful indicators from the ones proposed here (10 maximum).

. Adequately select the sampled population to match with the project scale.

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ANNEXES

1. Questionnaire for the well-being index 2. Sample for the low and high land survey and the middle hills survey 3. Pyramid of ages in Tajikistan 2016 4. List and location of focus groups of the qualitative survey 5. List of codes for qualitative survey analysis 6. List of priority domains of well-being by focus groups participants (qualitative survey) 7. Cantril subjective well-being questionnaire 8. Selected case studies

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Annex 1 Questionnaire for the well-being index

Hello. My name is ______. I am a representative of the “Committee for Environmental Protection of the Republic of Tajikistan”. Currently, in the framework of a project supported by the World Bank to help adaptation to climate change for rural communities, we are conducting a statistical survey. The main purpose of the survey is «to determine the level of well-being of households in Tajikistan”. Your household was randomly selected along with hundreds of other households, which live in Tajikistan. Your participation in this survey is completely voluntary.. If you agree, we would like to request you to allocate time and take part in this survey. We guarantee confidentiality of your answers. All your given responses will be processed and presented only in the summary statistical form.

0. Do you agree to take part in this survey? 1 Yes 2 No… go to the next household

1. Region

1 Khatlon 2 District of Republican Subordination (РРП)

2. District

1 Jirgatol 2 Tavildara 3 Nurobod 4 Vose 5 Hamadoni 6 Kulob 7 Farhor

3. Jamoat 4. Type of settlement: 1 urban 2 rural

5. Name of the village/town 6. Date 7. Interviewer’s name 8. Household identification number 9. Respondent’s gender: 1 Man 2 Woman

10. Name and Surname

11. Phone number

12. Are you a member of the projects’ group? 1 Yes 63

2 No – go to question 15

13. From which group? 1 Common Interest Group (CIG ) 2 Pasture Users group (PUG) 3 Water Union Association (WUA)

14. What is the name of your group?

15. How old are you?

16. What is your education level? 1 did not attend school 2 primary (1-4) 3 uncomplete primary (5-8(9)) 4 secondary (9-10(11)) 5 technical secondary school 6 university 7 doctorate

17. What is your marital status? 1 Single 2 Married 3 Widowed 4 Divorced

18. How many people live in your house?

19. How many rooms do you have in your house (including kitchen and excluding the bathroom)?

20. Do you work? 1 yes ….go to 21 2 no (unemployed) ….go to 22 3 no (retired) go to 22 4 housewife go to 22 5 other

21. Where do you work? 1 Agriculture 2 Private sector 3 Public sector 4 Migration 5 Other

22. Does your spouse work? 1 yes ….go to 23 2 no (unemployed) ….go to 24 3 no (retired) go to 24 4 housewife go to 24 5 other

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23. Where does your spouse work? 1 Agriculture 2 Private sector 3 Public sector 4 Migration 5 Other

24. Are you satisfied with your occupation? 1 yes, a lot 2 yes 3 not so 4 not at all

25. Have you received money from migration over the last 6 months? 1 yes 2 no… go to 27

26. How many people have sent you money?

27. How much cattle (bull, cow, calf) do you have?

28. How many sheep and goats do you have?

29. How much poultry do you have?

Q29A.How much beekeeping HONEY do you have?

30. Do you cultivate some land (except from havli land?) (with crops such as fruits, cotton, grain, cereals, vegetables, hay…) 1 Yes 2 No…go to question 35

31. What is the total area of land that you cultivate? (all lands: fields, presidential, orchards, hay, rented land, dekhan land) in ha

32. How is the quality of this land? 1 very good 2 good 3 ok 4 poor 5 very poor

33. How long do you need to wait for irrigation water in the summer time? (days) 99 if non irrigated land

34. Are you receiving enough irrigation water? 1 Largely enough 2 enough 3 not enough

35. How safe do you feel in your village (from natural hazards, crime and violence)?

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1 Completely safe 2 Safe 3 In danger

36. Do you consider that you have good road access to district center? 1 Yes, good 2 Ok 3 no, very bad

37. Were you able this month to buy what you needed for the household (oil, flour, sugar, rice, clothes, furniture, medicine, transportation …)? 1 yes, totally (I could buy all I needed and more) 2 yes, normally (I could buy all that I needed but without extra) 3 not enough (I had to choose the most urgent things) 4 not at all enough (I could not afford the most urgent items)

38. Did you buy something using a credit this month? 1 Yes 2 No

39. If yes, where did you take a credit from? 1 Bank 2 Shop 3 relatives, friends, mahalla 4 other

40. Do you have savings (apart from livestock and cars)? 1 Yes 2 No

41. Is there a local unit of electricity production in your village? 1 Yes 2 No …go to 43

42. Do you use this electricity produced in the village? 1 Yes 2 No

43. How much time do you need to fetch drinking water every day (in hour)?

44. What is the quality of the drinking water that you collect? 1 very good 2 good 3 ok 4 poor 5 very poor

45. Do you have land in your havli? 1 Yes 2 No … go to question 48

46. Do you grow vegetables in the land next to your havli?

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1 Yes 2 No … go to question 48

47. For how long can you feed your family with your own home production ( potatoes, onions, carrots)? 1 only during the vegetables season 2 up to 3 months 3 up to 6 months 4 the whole year

48. How has been your health this last week? 1 very healthy 2 healthy 3 fair 4 poor 5 very poor

49. Did one or some of your family members and relatives get sick in the last 30 days? 1 Yes 2 No

50. Did you enjoy some relaxing time with friends or family (visit to relatives, weddings, birthday parties, sport, meeting with friends…) in the last 30 days? 1 Yes 2 No

51. Did you help your neighbors in the last 30 days? 1 Yes 2 No

52. Was there any hashar organize recently in your village? 1 Yes 2 No

53. Were there any community meetings (at jamoat or mahalla level or mosque) to discuss some problems in the last 30 days? 1 Yes 2 No… go to 55 99 doesn’t know

54. If yes, did you take part in them? 1 Yes 2 No

55. Imagine a ladder with steps numbered from zero at the bottom to 10 at the top. The top of the ladder represents the best possible life for you and the bottom of the ladder represents the worst possible life for you. Circle the number that represents your answer.

55 a. On which step of the ladder would you say you personally feel you stand at this time?

10 – Best possible life 9

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8 7 6 5 4 3 2 1 0 – Worst possible life 99 doesn’t know

55 b. On which step do you think you will stand about five years from now?

10 – Best possible life 9 8 7 6 5 4 3 2 1 0 – Worst possible life 99 doesn’t know

Thanks a lot for your participation!

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Annex 2: Sample for the low and high land survey

District Jamoat village

1 1 JIRGATOL Vahdat Kaltabuloq 2 2 JIRGATOL Jirgatol Jirgatol 3 3 JIRGATOL Jirgatol Zamkon 4 4 JIRGATOL Yangishahr Julerak 5 5 JIRGATOL Yangishahr Qashqaterak 6 6 JIRGATOL Yangishahr Balkh 7 7 JIRGATOL Sartalo Qazaqtar 8 8 JIRGATOL Alghah Sarghoi

9 1 TAVILDARA Tavildara Sari dasht 10 2 TAVILDARA Sangvor Lairon 11 3 TAVILDARA Sangvor Darai Sebak 12 4 TAVILDARA Childara Chashmai Kabud 13 5 TAVILDARA Вахиё Vujon 14 1 KULOB Dahana Faizobod 15 2 KULOB Dahana Khonobod 16 3 KULOB Dahana Safar Amirshoev 17 4 KULOB Dahana Taniyol 18 5 KULOB Ziraki Korezi Poyon 19 6 KULOB Ziraki Bakhtobod 20 7 KULOB Ziraki Ziraki 21 8 KULOB Ziraki M. Ghaffor 22 9 KULOB Ziraki Zarqala 23 10 KULOB Zarbdor Kuhnashahr 24 11 KULOB Zarbdor Sari-osiyob 25 12 KULOB Zarbdor Vatansho Shamsov 26 13 KULOB Zarbdor Panjosiyobi-bolo 27 14 KULOB Zarbdor Panjosiyobi-poyon 28 15 KULOB Kulob Chorbogh 29 16 KULOB Kulob Laghmon 30 17 KULOB Kulob Tudakavsh 31 1 FARHOR Dehqonariq Bobosafoli Poyon 32 2 FARHOR Dehqonariq Guliston 33 3 FARHOR Gulshan Gushan 34 4 FARHOR Gulshan Buston 35 5 FARHOR Ghalaba Nurmat Safarov 36 6 FARHOR Ghalaba Vahdat 37 7 FARHOR Vatan Kuhandiyor 38 8 FARHOR Vatan Shahrteppa 39 9 FARHOR Vatan Kuhdoman 40 10 FARHOR Ghairat Tojikiston 1 41 11 FARHOR Ghairat Nekmanzar

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42 12 FARHOR Ghairat Bohdur Davlatov 43 13 FARHOR Zafar Somoniyon 2 44 14 FARHOR Zafar Sakhovat 45 15 FARHOR Farkhor Alovudin 46 16 FARHOR Farkhor Ittifoq 47 17 FARHOR Darqad Muhojirobod 48 18 FARHOR Jamoati Dehoti Darqad Jamoati Dehoti Darqad 49 19 FARHOR Jamoati Dehoti Darqad Jamoati Dehoti Darqad 50 20 FARHOR Darqad Mehrobod 51 21 FARHOR Darqad Darqad 52 22 FARHOR 20 - Solagii Istiqloliyat Sayora 53 23 FARHOR 20 - Solagii Istiqloliyat Mehnatobod 54 24 FARHOR 20 - Solagii Istiqloliyat Panj 55 1 JIRGATOL CONTROL Qashod Qarasoi 56 2 JIRGATOL CONTROL Pildon Pildoni miyona 57 3 JIRGATOL CONTROL Pildon Chubai 58 4 JIRGATOL CONTROL Muksu Sasiqbuloq 59 5 JIRGATOL CONTROL Muksu Qarakenja 60 6 JIRGATOL CONTROL Muksu Chorgul 61 7 JIRGATOL CONTROL Lyakhsh Oqsoi NUROBOD 62 1 Муджихарф CONTROL Зорони-Калон NUROBOD 63 2 Муджихарф CONTROL Охангарон NUROBOD 64 3 Муджихарф CONTROL Чинораки поён NUROBOD 65 4 Муджихарф CONTROL Шодмони NUROBOD 66 5 Муджихарф CONTROL Дегдонак NUROBOD имени Изагулло Халимова 67 6 CONTROL (Яхакюст) Дара 68 1 VOSE CONTROL Aral Okhjar 69 2 VOSE CONTROL Aral Shurqishloq 70 3 VOSE CONTROL Aral Hulbek 71 4 VOSE CONTROL Aral Zarkamar 72 5 VOSE CONTROL Aral Shurak 73 6 VOSE CONTROL Mehnatobod Voseobodi kalon 74 7 VOSE CONTROL Mehnatobod Arpataguldi 75 8 VOSE CONTROL Mehnatobod Gulisoy 76 9 VOSE CONTROL Pakhtaobod Kaduchi 77 10 VOSE CONTROL Pakhtaobod Qainar 78 11 VOSE CONTROL Pakhtaobod Sopkadili 79 12 VOSE CONTROL Pakhtaobod Beshariq 80 13 VOSE CONTROL Pakhtakor Kaftarkhona 81 14 VOSE CONTROL Pakhtakor Sarichashma 82 15 VOSE CONTROL Pakhtakor Kuchabogh 83 16 VOSE CONTROL Pakhtakor Osmonbika 84 17 VOSE CONTROL Pakhtakor Pushyoni bolo

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HAMADONI 85 1 Даштигуло CONTROL Даштигуло HAMADONI 86 2 Даштигуло CONTROL Файзабад HAMADONI 87 3 Даштигуло CONTROL Файзабад HAMADONI 88 4 Даштигуло CONTROL Тагноб HAMADONI 89 5 Панджруд (Калинин) CONTROL Анджиркон HAMADONI 90 6 Панджруд (Калинин) CONTROL Сафаров Гадой HAMADONI 91 7 Панджруд (Калинин) CONTROL Кодараи 2 HAMADONI 92 8 Кахрамон CONTROL Садбарго HAMADONI 93 9 Кахрамон CONTROL Пушкин HAMADONI 94 10 Кахрамон CONTROL Кахрамон HAMADONI 95 11 Мехнатабад CONTROL Гулабад HAMADONI 96 12 Мехнатабад CONTROL Навобод HAMADONI 97 13 Мехнатабад CONTROL Мехнатабад HAMADONI 98 14 Мехнатабад CONTROL Гулистон HAMADONI 99 15 Мехнатабад CONTROL Гулрез (Олимтой) HAMADONI ## 16 имени Турдиева CONTROL Обшорон (Советабад) HAMADONI ## 17 имени Турдиева CONTROL Богистон (Бешкаппа) HAMADONI ## 18 Чубек CONTROL Хаётинав HAMADONI Мехрвари миёна (Окмазори ## 19 Чубек CONTROL Миёна) HAMADONI ## 20 Чубек CONTROL Ориён (Чапаев) HAMADONI ## 21 Панджоб CONTROL Сайроб HAMADONI ## 22 Панджоб CONTROL Сайроб

Sample of the middle hills

Villages District jamoat Baljuvon Baljuvon Khaibarchashma Baljuvon Baljuvon Kuchabuloq Baljuvon Tojikiston Solmolidasht Baljuvon Saif Rahim Zardoludasht Baljuvon Safar Amirshoev/Satarmush Chorbogh Baljuvon Sari Khosor Shahidon KHOVALING Khovaling Tursunzoda KHOVALING Khovaling Habibullo Faizullo KHOVALING Lohuti Sadbargo

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KHOVALING Jombakt Gulzor KHOVALING Jombakt Chuqurak KHOVALING Sari Osiob Zardaki KHOVALING Shugnov Darai Devlokh FAIZOBOD Dustmurod Aliyev Jonvarsuz FAIZOBOD Dustmurod Aliyev Kenjaobod FAIZOBOD Qalai Dasht Elok

Annex 3 Population pyramid of Tajikistan 2016

source: https://www.cia.gov/library/publications/the-world- factbook/geos/ti.html#popPyramidModal

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Annex 4 List and location of focus groups- qualitative research

nb of nb of duration participants nb of nb of focus code district type of group focus to focus men women groups group group 1 FQ1 Faizobod PUU 6 5 1 1h25 2 KL1 Kulob male leaders 5 5 0 2h 3 KL2 Kulob women leaders 3 1 2 2h30 4 KD3 Kulob WUA 8 8 0 2h 5 FS1 Farkhor male leaders 6 5 1 1h05 6 FS2 Farkhor women leaders 5 0 5 1h40 7 FG3 Farkhor male leadesr 8 8 0 3h 8 TY1 Tavildara male leaders 5 5 0 1h51 9 TY2 Tavildara female leaders 4 1 3 1h10 10 TS3 Tavildara intragroup 8 6 2 1h38 11 JQ1 Jirgatol male leaders 8 8 0 0h53 female 12 JQ2 Jirgatol 4 0 4 0h40 leaders/intragroup 13 JM3 Jirgatol intragroup 8 0 8 0h44 14 KS1 Khovaling male leaders 9 9 0 2h47 15 KS2 Khovaling female leaders 4 0 4 1h05 16 KS3 Khovaling WUA 9 8 1 2h50 17 BO1 Baljuvon male leaders 8 6 2 2h 18 BS2 Baljuvon female leaders 6 0 6 1h 19 BK3 Baljuvon CIG 5 4 1 2h50 20 FQ1 Fayzabad PUU 6 5 1 0h47 Total 125 84 41 % 100 67.2 32.8 test focus groups 1 KS2 Kulob female 4 0 4 1h10 2 KZ3 Kulob WUA 8 3 5 1h40 3 KZ4 Kulob mix 10 7 3 2h 4 Jj1 Jirgatol male leader 7 7 0 1h25 5 Jirgatol first/non calculated

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Annex 5 List of codes

HUMAN AND GEOGRAPHICAL EXTENT OF IMPACT- EXT

TYPE OF PEOPLE EXT-PEO TYPE OF INSTITUTIONS EXT-INSTI GEOGRAPHICAL PLACES EXT-GEO

SOCIAL INTERACTIONS -SOC

FUNCTION SOC-FUN SHARING /BARTER SOC-SHA RELATIONS BETWEEN MEMBERS OF THE COMMUNITY SOC-REL

DIFFERENCES - DIFF

NO CONSENSUS DIFF-NOC CONSENSUS DIFF-CON DIFFRENCES BETWEEN GROUPS OF PEOPLE/INDIVIDUALS DIFF-PEO

ACTIONS -ACT ACTION VERBS ACT-VER MONEY TRIGGER ACT-MON

EFFECTS -EFF WATER EFF-WAT WORK EFF-WOR INCOME EFF-INC FOOD EFF-FOO HEALTH EFF-HEA LONG TERM EFF-LON LIVING COND EFF-LIF WOMEN EFF-WOM BEFORE-AFTER BEF-AFT AGRI PRODUCTIVITY EFF-AG KNOWLEDGE EFF-KNO OTHER EFF-OTH

JUDGEMENT -JUDG

POSITIVE JUDGEMENT JUDG-POS NEGATIVE JUDGEMENT JUDG-NEG MIDDLE JUDGEMENT JUDG MID

GAPS –GAP

KNOWLEDGE GAP-KNO MONEY/FUND GAP-MON WATER GAP-WAT OTHER GAP-OTH

FUTURE PLANS

WITHOUT PROJECT FUT-SEL WITH PROJECT FUT-PRO

EMOTIONS-EMO PRIDE EMO-PRI HAPPINESS EMO-HAP THANKFULNESS EMO-THA ANGER EMO-ANG

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Annex 6: List of priority domains of well-being by focus groups participants

JJ1 KL1 KL2 KD3 FS1 FS2 FG3 TY1 TT2 TS3 JQ1 JQ2 JM3 KS1 KS2 KS3 BO1 BS2 BK3 FQ1 Mutual Health Health Job Health Money Roads Health Labor Health Health Health Health Health Health Health Health Peace Health Peace 1 understanding Education of Peace and permanent Understand Peace Money Job Good family Clean water Health Peace Peace Family Family Peace Money Money Health Peace Health 2 children Unity job ing Peace and Peace and disciplined Full time Living Food Access to education Good family Money Money Work Leisure Family Education Peace Peace Money Tranquility Money 3 security prosperity children job condition Health, Desciplined Children Security Living condition Water peace and Finance Money Money Money children wih honor Land Money Food Money 4 tranquility High and and dignity Productive Place of standard of Food Peace Family lands work life Tranquility Education and peace Salary

Job

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Annex7 Cantril ladder measure of life satisfaction for life

Imagine a ladder with steps numbered from zero at the bottom to 10 at the top. The top of the ladder represents the best possible life for you and the bottom of the ladder represents the worst possible life for you. Circle the number that represents your answer.

1. On which step of the ladder would you say you personally feel you stand at this time? 10 – Best possible life 9 8 7 6 5 4 3 2 1 0 – Worst possible life

2. On which step do you think you will stand about five years from now? 10 – Best possible life 9 8 7 6 5 4 3 2 1 0 – Worst possible life

Scoring: . Thriving -- wellbeing that is strong, consistent, and progressing. These respondents have positive views of their present life situation (7+) and have positive views of the next five years (8+). They report significantly fewer health problems, fewer sick days, less worry, stress, sadness, anger, and more happiness, enjoyment, interest, and respect.

. Struggling -- wellbeing that is moderate or inconsistent. These respondents have moderate views of their present life situation OR moderate OR negative views of their future. They are either struggling in the present, or expect to struggle in the future. They report more daily stress and worry about money than the "thriving" respondents, and more than double the amount of sick days. They are more likely to smoke, and are less likely to eat healthy.

. Suffering -- wellbeing that is at high risk. These respondents have poor ratings of their current life situation (4 and below) AND negative views of the next five years (4 and below). They are more likely to report lacking the basics of food and shelter, more likely to have physical pain, a lot of stress, worry, sadness, and anger. They have less access to health insurance and care, and more than double the disease burden, in comparison to "thriving" respondents. 76

Annex 8 Selected case studies

1. Bakery workshop in Khovaling, showcasing a business activity benefiting to women

2. A solar-powered kindergarten in Jirgatol, showcasing an educational facility employing women

3. Improved drinking water supply, Gulshan, Farhor, showcasing a success in bringing drinking water to households

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1. Bakery workshop. CIG Laziz, Khovaling (middle hills)

Background The village “March 8th” was established in 1984 after Khovaling separated from Vose district. The village encompasses 94 households and 734 residents. The village PRA was conducted on 24th January, 2016 within ELMARL project where the community active members and household representatives participated to analyze common needs and plan solutions. According to the analysis, the main source of income of the villagers is entrepreneurship, labor migration, and agriculture. There is no pastureland near the village and livestock is kept in the household plots and fed by purchased fodder. Women constitute 52 % of the village population with only 5 percent engaged in governmental and entrepreneurial activities. Therefore, the creation of income generating activities for rural women was one of the priority plans for the community development and women empowerment within ELMARL project. During the PRA it was reported that the village does not have forest resources and the need for wood is high as each household uses wood for cooking and baking. Villagers supported the idea to establish a bakery shop with electric oven in the village. It was supposed that in this way, villagers would save wood and women would get paid jobs within their own village. Moreover, wheat is the main crop produced in the village and there is no need to buy it.

Visit of the bakery Bonokhonov Faizali is an active, enthusiastic young man who agreed to lead the CIG Laziz in establishing a bakery workshop in the village. “I live in Khovaling but work in a bakery in Dushanbe so had experience in working bakery production. There was always a plan and a need to establish a bakery in my village but due to shortage of financial resources we could not do it. “ Mr. Faizali mentioned that during winter there is demand only for 5 types of products. Bread is always in demand as villagers love it a lot. Earlier bread was brought from Vose district which cost 2,50 somoni due to transport expenditure. Now all villagers may buy locally produced fresh bread for 2 somoni only. This small enterprise in 7 working hours produces 180 loafs of bread, 400 pcs of various biscuits, 250 pieces cookies and cupcakes. Their daily cash income is up to 400 somoni.

Now 6 women are working part-time at the bakery and earn 350 somoni per month. At the moment there are 5 types of produces prepared. The bakery is working well now, villagers are happy because they will not be out of bread. “The girls are trained to bake different types of sweets. So they are mainly engaged in the production process. I distribute the products to the shops and get orders for the next day. Our products are well treated in the market and there is always demand for bread and sweets. Therefore we plan to increase the production and prepare more varieties of sweets“ explains Mr. Faizali.

Lady working in the bakery “We did not have a job because there was not such workshop, even a tailor shop in the village. So we were all the time engaged in home work. Now there is an opportunity to earn money and support my family. It feels very good to contribute to family budget and have my own money for some personal needs. “

The CIG also planted trees to use them for fire when needed. But it was informed that the bakery is fully equipped with electric machines and oven, as there is no electricity shortage in the village. “In warm seasons we plan to increase the production and engage more women and girls in the bakery. Due to festivals, weddings and other events the demand for bakery products increase. We also plan to train the girls for baking cakes which will also be a good progress in the business”.

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The CIG has also started packaging of their products and plan to present them in the festivals. “There was a little input and the needed community mobilization to properly use available resources. And we did it successfully.”

2. Creation of a solar-powered kindergarten in Lakhsh, Jirgatol, high lands

Yormazor village is one of the villages in the highland of Lakhsh district located 4 km away from the center of the district. There are 292 households residing in the village. Village dwellers are active in community life, but without external support it was difficult to plan and implement community development activities.

Participatory rural appraisal within ELMARL project mobilized community people to identify and prioritize development needs. Parvinoz is one of the active women in the village who raised the issue of unavailability of proper conditions for preschool education for children. Children of preschool age spend most of the day in the street where there is high risk of car accidents. The villagers realized the difficulty but due to lack of financial resources could not improve condition of an old school building for kindergarten purposes. Therefore villagers supported the idea to renovate the building and install solar panel for water heater.

During the PRA Parvinoz raised the issue of children’s safety and importance of preschool education. The proposed plan was unanimously supported by other villagers, who agreed to complete the work within the community.

According the head of the CIG Parvinoz Makhmadieva, “it was easy to prepare a proposal when we already knew what was required. We got an approval from the district chairman to use a building of the old school which was abandoned for the last three years. Rehabilitation and thermal insulation of the building was planned in details with CIG members and with involvement of an engineer. Shortage of electricity was the main difficulty in the village particularly during the cold season. Therefore we decided to install a solar panel for the water heater and rooms light which was essential for the kindergarten.”

CIG Nushin completed the planned work in three months including building rehabilitation, thermal insulation, installation of the water heater and the solar panel. This is a new experience for the village to use renewable energy and is a good lesson for future reduction of tree cutting.

Today there are 30 children of preschool age who are enrolled in two batches of the kindergarten. School teachers now do not worry about their children when they are teaching in the school. Housewives got more free time to do housework as their children are not running in the streets. Moreover three women in the village got permanent jobs in the kindergarten. Parvinoz, who is a supervisor in the kindergarten says that this project is both very energy efficient and convenient. Electricity fees are not as high as it was, and used only for heating, while the thermal insulation helps to keep the rooms warm.

Now rural children have the opportunity to learn and grow in an appropriate classroom.

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3. Improved drinking water supply, Gulshan, Farhor, lowlands

Ayniddin Mirzoev, Director of “Obi Nushoki” LLC, which was established in August 2007, is implementing a subproject on drinking water supply. This is the only private company in Tajikistan that is operating in the field of drinking water supply in rural areas. There are 9 people are working in the company. Ayniddin Mirzoev has been working in the Project for the third year and continues his activities to the present day. The activity of “Obi nushoki” in this project shows that 5 subprojects are being implemented in 5 jamoats of Gulshan in Farkhor district, and it took responsibility for the quality control and their implementation.

Prior to the subproject implementation, meetings at rural level, then meetings in the room of jamoat were held and the Community Interest Groups were established. The Project contribution amounted to TJS 147,000, i.e. 68%. According to the subproject schedule, polyethylene pipelines were purchased to replace old ones in villages with a length of 7184 m (110 mm1230 m, 90 mm- 2648 m and 76 mm-3306 m). At the same time, rural people also contributed to the pipelines laying in the amount of TJS 70,829, which is 32% of the total cost. “At present, drinking water has been improved. More than 108 new created households, where initially a water supply system was not available, were provided with drinking water. Gulshan villages were provided with 11 external systems under the Project, and 748 people were supplied with drinking water. Until 2015, 176 households used a calculator while on-farm water supply system was functioning, and now water meters have been installed in 273 households for the economical water consumption. During the subproject implementation, 2,574 people were provided with drinking water.” – says Mirzoev.

Mirzoev Ainiddin has been working in the field of drinking water supply for 11 years already. Consequently, he controls the introduction of this system in five villages of Gulshan. At the same time, collection of fees for services from the population carried out every month, annually is 100- 110%, which indicates the good functioning of the system. When we talked with Mirzoev, he was working and said that 37 000 m of pipes of 63-70s years of the last century were installed in this jamoat. “Today, all these pipes should be replaced, because they almost worn out. It's very good that with the project contribution we replaced more than 7 km of pipes with new plastic pipes. Now, in cooperation with state enterprises, we are going to replace more 5 km of pipes” - said Mirzoev. Along with the existing problems, Ayniddin intends to provide all the population of Gulshan jamoat with drinking water and expresses gratitude to the project in supporting this activity.

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