Endline Survey Report for the Avansa Agrikultura Project

This publication was prepared independently by Social Impact, Inc. at the request of the United States Agency for International Development.

GABRIELA LEITE SOARES FOR SOCIAL IMPACT

ENDLINE SURVEY REPORT FOR THE AVANSA AGRIKULTURA PROJECT Final Report: December 2020

ENDLINE SURVEY REPORT AVANSA AGRIKULTURA PROJECT December 2020

Submitted to: Candido da Conceicao, Contracting Officer’s Representative, USAID/Timor-Leste Contract No.: AID-486-I-14-00001 / Task Order No.: AID-472-TO-15-00003

DISCLAIMER The author’s views expressed in this publication do not necessarily reflect the views of the United States Agency for International Development or the United States Government.

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CONTENTS

EXECUTIVE SUMMARY....................................................................................................... III BACKGROUND ....................................................................................................................................................... III METHODS .................................................................................................................................................................. III LIMITATIONS ............................................................................................................................................................ III FINDINGS & CONCLUSIONS ............................................................................................................................. IV

FINANCIAL STABILITY ............................................................................................................................................ IV HUNGER & NUTRITION ......................................................................................................................................... V RESILIENCE & EMPOWERMENT .............................................................................................................................. V

INTRODUCTION ................................................................................................................... 1 FINANCIAL STABILITY & ECONOMIC GROWTH: ...................................................................................... 2 HUNGER & NUTRITION ........................................................................................................................................ 2 RESILIENCE AND EMPOWERMENT ................................................................................................................... 2

METHODOLOGY ................................................................................................................... 3 SAMPLING & WEIGHTING .................................................................................................................................... 3 INSTRUMENTS ........................................................................................................................................................... 3 FIELDWORK ............................................................................................................................................................... 4 DATA CLEANING & ANALYSIS ........................................................................................................................... 4 SECONDARY DATA SOURCES ........................................................................................................................... 4 REPORTING CONVENTIONS .............................................................................................................................. 4 LIMITATIONS ............................................................................................................................................................. 5

FINDINGS................................................................................................................................ 7 DEMOGRAPHICS ...................................................................................................................................................... 7 FINANCIAL STABILITY ........................................................................................................................................... 9

PERCENT CHANGE IN AGRICULTURE GDP ........................................................................................................ 9 PERCENT INCREASE IN HOUSEHOLD SAVINGS AND/OR INVESTMENT IN PRODUCTIVE ASSETS ................. 10 DAILY PER CAPITA EXPENDITURE (AS A PROXY FOR INCOME) IN USG ASSISTED AREAS ........................... 15

HUNGER & NUTRITION ..................................................................................................................................... 19 PREVALENCE OF HOUSEHOLDS WITH MODERATE TO SEVERE HUNGER..................................................... 19 PREVALENCE OF CHILDREN 6-23 MONTHS RECEIVING A MINIMUM ACCEPTABLE DIET .......................... 22 MEAN NUMBER OF FOOD GROUPS CONSUMED BY WOMEN OF REPRODUCTIVE AGE ............................... 26

RESILIENCE & EMPOWERMENT ....................................................................................................................... 28 NUMBER OF CO-MANAGEMENT/USER GROUPS FORMED AND ACTIVE ..................................................... 28 PERCENT OF HOUSEHOLDS OVERCOMING SHOCKS THROUGH SUSTAINABLE MEANS............................ 29 PERCENT OF WOMEN REPORTING ADEQUACY ON 80% OF WEAI DOMAINS ........................................ 35

CONCLUSIONS ................................................................................................................... 40 FINANCIAL STABILITY ........................................................................................................................................ 40 HUNGER & NUTRITION ..................................................................................................................................... 41 RESILIENCE & EMPOWERMENT ....................................................................................................................... 41

ANNEX A: SUMMARY TABLES BY GENDERED HOUSEHOLD TYPE ....................... 43 ANNEX B: SUMMARY TABLES BY MUNICIPALITY ..................................................... 45 ANNEX C: SUPPLEMENTARY DATA TABLES – SAVINGS & PRODUCTIVE ASSETS................................................................................................................................................. 47 ANNEX D: SUPPLEMENTARY DATA TABLES – SIX MUNICIPALITIES ................... 51 ANNEX E: BASELINE SAMPLING APPROACH.............................................................. 61 ANNEX F: ENDLINE SURVEY INSTRUMENT ................................................................ 62

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TABLE OF TABLES Table 1: Values for the indicators measured at baseline and endline .......................................................... vii Table 2: Household Demographics ........................................................................................................................ 7 Table 3: WRA Demographics .................................................................................................................................. 8 Table 4: Child Demographics................................................................................................................................... 8 Table 5: Percent Change in Agriculture, Forestry, and Fishing GDP ............................................................. 9 Table 6: Household savings and/or investment in productive assets – 2015 prices ................................. 11 Table 7: Value of savings and productive assets by asset type ....................................................................... 12 Table 8: Savings by Disaggregate ........................................................................................................................... 13 Table 9: Productive Assets by Disaggregate ...................................................................................................... 14 Table 10: Daily per capita expenditure – 2015 prices ..................................................................................... 16 Table 11: Household Expenditures by Item, 2015 Prices ............................................................................... 17 Table 12: Prevalence of Moderate to Severe Hunger...................................................................................... 20 Table 13: Percentage of Children Receiving MAD ........................................................................................... 23 Table 14: Mean Number of Food Groups for WRA ....................................................................................... 26 Table 15: Community Group Participation ........................................................................................................ 28 Table 16: Experience with Shocks ........................................................................................................................ 30 Table 17: Coping Mechanisms ............................................................................................................................... 31 Table 18: Coping Strategy Disaggregates ............................................................................................................ 32 Table 19: WEAI domains, indicators, and definitions of adequacy ............................................................... 35 Table 20: WEAI Adequacy ..................................................................................................................................... 36 Table 21: WEAI Adequacy by Domain ................................................................................................................ 36 Table 22: Gendered Household Differences across indicators ..................................................................... 43 Table 23: Productive assets by analysis category: Baseline and endline ...................................................... 47 Table 24: Household savings and/or investment in productive assets – 2015 prices .............................. 48 Table 25: Value of savings and productive assets by asset type .................................................................... 49 Table 26: Savings by Disaggregate......................................................................................................................... 49 Table 27: Productive Assets by Disaggregate .................................................................................................... 50 Table 28: Productive Asset Value (All Municipalities)...................................................................................... 51 Table 29: Per Capita Expenditure (All Municipalities) ..................................................................................... 52 Table 30: Hunger Prevalence by Disaggregate (All Municipalities) ............................................................... 53 Table 31: MAD Disaggregates (All Municipalities) ............................................................................................ 54 Table 32: WRA Food Group Disaggregates (All Municipalities): 30-day recall ......................................... 55 Table 33: WRA Food Group Disaggregates (All Municipalities): 24-hour recall ...................................... 56 Table 34: Group Participation (All Municipalities) ............................................................................................ 57 Table 35: Prevalence of Shocks (All Municipalities) .......................................................................................... 57 Table 36: Experience with Shocks (All Municipalities)..................................................................................... 57 Table 37: Coping Mechanism Usage (All Municipalities) ................................................................................. 58 Table 38: WEAI Disaggregates (All Municipalities) ........................................................................................... 59 Table 39: WEAI Adequacy by Domain (All Municipalities) ............................................................................ 59 Table 40: Number of sampled aldeias and households for the 48 project sucos ..................................... 61 TABLE OF FIGURES Figure 1: Agriculture, Forestry and Fishing GDP ($M), 2013-2019 .............................................................. 10 Figure 2: Value of assets by range class ............................................................................................................... 14 Figure 3: Calendar from Avansa Agrikultura demonstrating recommended expenses, financial literacy tips ................................................................................................................................................................................ 15 Figure 4: Daily per capita expenditure by range class ...................................................................................... 17

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Figure 5: Comparison of prevalence of moderate to severe hunger over time in Avansa Agrikultura’s monitoring data and SI’s reporting ....................................................................................................................... 20 Figure 6: Prevalence of hunger by month, baseline to endline ...................................................................... 22 Figure 7: Avansa beneficiary farmer displays cauliflower ................................................................................ 23 Figure 8: Prevalence of children receiving a MAD, by gender ....................................................................... 25 Figure 9: Comparison of prevalence of children 6-23 months receiving a MAD over time in Avansa Agrikultura’s monitoring data and SI’s reporting .............................................................................................. 25 Figure 10: Baseline-endline food group consumption among WRA ............................................................ 27 Figure 11: Shock prevalence ................................................................................................................................... 29 Figure 12: Plastic tunnels in Maubisse .................................................................................................................. 30 Figure 13: Coping strategies among all households .......................................................................................... 32 Figure 14: Percent of households using various coping mechanisms by type of shock ........................... 34 Figure 16: Women's input into household decisions ....................................................................................... 37 Figure 15: Avansa beneficiary poses with crops ................................................................................................ 38 Figure 17: Daily per capita expenditure by woman’s input into household decisions ............................. 39 Figure 18: Household savings and/or investment in productive assets by woman’s input into household decisions ................................................................................................................................................. 39 Figure 19: Value of assets by range class ............................................................................................................. 50

ACRONYMS & KEY TERMS FAO Food and Agriculture Organization FNM Female No Male FTF Feed the Future MAD Minimum Acceptable Diet MF Male and Female MNF Male No Female PE Performance Evaluation SI Social Impact URC University Research Co. USAID United States Agency for International Development USD United States Dollar USG United States Government WEAI Women’s Empowerment in Agriculture Index WRA Women of Reproductive Age

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EXECUTIVE SUMMARY

BACKGROUND

The United States Agency for International Development’s (USAID) Avansa Agrikultura Project (Avansa Agrikultura) is a five-year horticulture value chain activity in Timor-Leste implemented by Cardno Emerging Markets and three subcontractors. Avansa Agrikultura aims to address key barriers to economic growth in Timor-Leste, specifically rural poverty, natural resource degradation, food insecurity, and under-nutrition through a horticulture value chain approach.

Social Impact (SI) was initially tasked through the Avansa M&E contract to conduct a baseline and endline survey for the Avansa Agrikultura project. While SI implemented a full population based survey at baseline (2015) including 1,200 households across five municipalities, the Avansa M&E contract was modified between baseline and endline (2020) with the result that SI would no longer implement a full endline survey. Instead, SI would conduct an analysis of endline outcomes of interest using data from Avansa Agrikultura’s own annual household survey (331 households across six municipalities).

This report presents baseline and endline figures for seven outcomes of interest as well as endline values only for two additional indicators that were not measured at baseline. Baseline and endline values for these indicators are displayed in Table 1 below.

METHODS

The sample size for the endline survey was determined based on the number of sucos and beneficiary households that would be feasible for Avansa Agrikultura to enumerate. SI used a phased approach to sample 320 households in 37 sucos from a list of beneficiary households provided by Avansa Agrikultura. SI calculated survey weights for each household based on the inverse probability of selection at each sampling stage and applied these weights during analysis.

The endline household survey instrument was adapted from Avansa Agrikultura’s 2019 household survey. SI worked with Avansa Agrikultura to recommend edits to the survey to ensure comparability between baseline and endline questions, added questions to accommodate the two indicators at endline, and decrease survey duration. Fieldwork was completed by enumerators contracted by the Avansa Agrikultura project between June 25 and July 22, 2020 in the six municipalities in which Avansa Agrikultura worked.

After completing fieldwork, the Avansa Agrikultura team checked and cleaned the data and sent the final dataset to SI for additional cleaning and analysis. SI ran additional checks using Stata statistical software and sought clarification with Avansa Agrikultura on minor issues including potential outliers and duplicate household IDs. The SI team ran the baseline analysis to ensure replicability with what was reported in the baseline report and adapted these analysis files for use at endline. In some cases throughout this report the baseline value presented differs slightly from what was initially reported at baseline; though these cases are explained in detail in the table notes for each indicator, the broad goal for recalculating baseline values was to maximize comparability across survey years.

LIMITATIONS

Differences in baseline and endline methodology. The largest difference between the baseline and endline methodology is the sample size and sampling approach. At baseline, SI conducted a population-based survey of 1,200 households designed to be generalizable to the population of the initial Avansa

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Agrikultura zone of influence.1 Due to changes in contract scope, described above, the sampling methodology at endline was much different. Rather than using census data as the sample frame, as was done at baseline, the sample frame at endline was Avansa Agrikultura beneficiary households. This means that while baseline estimates are generalizable to the general population of the initial Avansa Agrikultura zone of influence in Ainaro, Ermera, Bobonaro, Aileu, and Dili, endline estimates are only generalizable to the beneficiary population in the current Avansa Agrikultura zone of influence in Ainaro, Ermera, Bobonaro, Aileu, Dili, and Liquiçá. Additionally, the much smaller sample at endline of 331 households limits the degree of statistical reliability of many of the disaggregate estimates. Disaggregate estimates with n values lower than 30 should be interpreted with caution.

Timing of data collection. The hunger season in Timor-Leste typically falls in January-February before the harvest begins in March-April. Though both the baseline and endline surveys were conducted at a time when food supplies are still adequate, as recommended by Feed the Future (FTF) for the nutrition indicators, the values presented here may not represent the situation at its worst when supplies are more scarce.2 Baseline data were collected shortly before the hungry season in November, compared to endline data that were collected in July when households typically have better access to food and crops. The timing of endline data collection also coincided with the global COVID-19 pandemic and findings related to COVID-19 are detailed in each report section below.

FTF methodological constraints. Some FTF methodology is extremely time consuming for enumeration, particularly calculations of consumption indicators. Due to the survey’s time constraints, some FTF indicators were assigned to be custom indicators in agreement with USAID/Timor-Leste. For the expenditure indicator, SI adapted the methodology used in two national-level surveys to create a less time-consuming methodology to track households’ expenditure. 3 While these changes decreased survey duration, estimates for the indicators presented in this report are not comparable to other published FTF indicator estimates.

Adaptation of survey. Over the course of implementation, the Avansa Agrikultura team adapted some indicators to better suit the local context. For example, with household expenditures, the team determined that school costs are better asked over a quarterly period rather than monthly, as was the case at baseline. While these types of changes are reflected in Avansa Agrikultura’s monitoring data and annual reports, this report aimed to maximize comparability between baseline and endline calculations. Thus, results in this report should be used in combination with Avansa Agrikultura’s annual reporting, as well as SI’s final performance evaluation, to understand the true impacts of Avansa Agrikultura programming.

FINDINGS & CONCLUSIONS

FINANCIAL STABILITY

The agriculture, forestry and fishing GDP decreased from baseline to endline but trends upward after 2017, suggesting growth. The agriculture, forestry and fishing GDP decreased by 4.7 percent from $300.2 million at baseline (2013) to $286.1 million at endline (2019). Though Avansa Agrikultura began in 2015, the 2013 GDP figure was used as an initial baseline due to the lag in national GDP reporting. Considering only the timeframe of Avansa Agrikultura implementation (2015-2020),

1 Details on the baseline sampling approach can be found in Annex E. 2 Many of the indicators selected for Avansa Agrikultura are adaptations of FTF indicators. 3 SI adapted questions from the Timor-Leste Survey of Living standards and the Timor-Leste Demographic Health Survey.

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GDP is much more stable and even suggests growth in later years, trending from $283 million in 2015 down to $271 million in 2017, but then up to $279 million in 2018 and $286 million in 2019.

Household savings and investment in productive assets increased from baseline to endline. Using productive assets that were asked at both baseline and endline alone, household savings and investment in productive assets increased by 7.5 percent from $1,927.01 at baseline to $2,071.32 at endline.4 Much of this increase was driven by a large increase in savings, while value of owned productive assets decreased from baseline to endline. While savings increased by 400 percent or more among four of the five municipalities, there was no change for savings among Dili households. Including new assets at endline that were not asked at baseline, household savings and investment in productive assets increased much more dramatically, from $1,927.01 at baseline to $2,557.00 at endline, a 32.7 percent increase. Given that many of the newly-asked asset items were agriculture items, it is possible that new ownership of these items was in fact a result of Avansa Agrikultura’s programming; however, given that these items were not asked at baseline, we cannot be certain. Thus, it is likely that the “true” percentage increase in productive assets lies between 7.5 and 32.7 percent.

Daily per capita expenditure decreased slightly from baseline to endline. There was a slight decrease in daily per capita expenditure from $1.63 at baseline to $1.53 at endline, using 2015 prices. However, expenditures differed greatly across types: food expenditures decreased by $0.32, non-food items purchased over the past month decreased by $0.07, and non-food items purchased over the past year increased by $0.30. This relatively large decrease in food expenditures may be due in part to the fact that Avansa Agrikultura heavily encouraged farmers to set aside portions of food for consumption instead of sale, thereby contributing to lower food expenditures at endline. Changes in expenditure differed substantially by municipality as well: households in Aileu and Bobonaro showed increased per capita expenditures, ($0.19 and $0.55 increases, respectively) while expenditures in Ainaro, Dili and Ermera households decreased ($0.19, $0.34, and $0.77 decreases, respectively).

HUNGER & NUTRITION

Food security improved substantially across all demographics from baseline to endline. Prevalence of households with moderate to severe hunger decreased dramatically from 15.49 percent among the general population at baseline to 0.01 percent among Avansa Agrikultura beneficiary households at endline.

Nutrition improved marginally from baseline to endline, though outcomes varied across demographics. Prevalence of children between six and 23 months of age receiving a minimum acceptable diet (MAD) increased from 41.0 percent at baseline to 46.1 percent at endline. However, outcomes differed across municipalities: Dili and Aileu showed substantial increases, Ainaro showed a more marginal increase, and Bobonaro and Ermera showed substantial decreases. The mean number of food groups consumed by women of reproductive age also increased from 6.79 food groups at baseline to 7.53 food groups at endline, of eight food groups total. Unlike the MAD indicator, increases in food groups consumed was consistent across all disaggregates.

RESILIENCE & EMPOWERMENT

Group membership increased substantially from baseline to endline. At baseline, 12 percent of households in the general population in the five original Avansa Agrikultura municipalities

4 Productive assets include items in five categories: livestock, household durable goods, transport, fishing, and farm equipment. A full list of the specific items included in each category can be found in Annex C.

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were a part of a community group; at endline, 100 percent of households were a member of at least a farmer group through Avansa Agrikultura.

Though most households incorporated sustainable means to cope with shocks, only about half of households experiencing shocks relied on sustainable coping mechanisms only. A majority of households (88 percent) experienced a shock in the last year, with half reporting a shock that affected the household’s economic situation only, about two percent reporting a shock that affected the household’s food situation only, and one-third reporting a shock that affected both the economic and food situation. The most frequent shocks experienced were related to too much or too little rain, crop disease, and pests. While most households (78.3 percent) incorporated sustainable means into their coping strategies, only about half (47 percent) of households experiencing shocks relied solely on sustainable means. When dealing with shocks related to rain, crop disease or pests, households most frequently relied on the sustainable methods of income from seasonal work, using savings, and borrowing food. The most used unsustainable methods were harvesting immature crops, cutting back on food, selling assets or livestock, and pulling children from school, though the prevalence of these methods was much less than the sustainable methods.

There was a high degree of input to household financial decision-making among women at endline. Women showed a high degree of financial empowerment in the household at endline, with 98.5 percent of women achieving adequacy on 80 percent of the WEAI domains of production, resources, income, leadership, and time. Though empowerment overall was high, there was variation in the extent to which women had input into decisions. In the production and income domains, only about one-fourth of women had input into most or all decisions while the majority had input into some decisions. In the resources domain, about 42 percent of women had input into most or all decisions regarding borrowing money and 30 percent had input into most or all decisions regarding using borrowed money. Overall, these results imply that women had the highest degree of empowerment as it relates to leadership (group participation) and resources, namely with decisions related to when and whether to borrow money and how to use it.

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Table 1: Values for the indicators measured at baseline and endline

Indicator Unit Baseline Endline

Difference Mean/Total Standard Error Mean/Total Standard Error

Financial Stability Indicators Percent change in agriculture GDP (secondary data from General Directorate of Statistics, Ministry of Finance)5 USD $300.2

Million* N/A $286.1 Million (4.7% decrease) N/A ↓

Percent increase in household savings and/or investment in productive assets6 USD $1,927.01* $177.58 $2,071.32

(7.5% increase) $172.51 ↑

Daily per capita expenditure (as a proxy for income) in USG assisted areas USD $1.63* $0.07 $1.54 $0.10 ↓

Hunger/Nutrition Indicators Prevalence of households with moderate to severe hunger Percent 15.49% 0.01% 0.01% 0.01% ↓ Prevalence of children 6-23 months receiving a minimum acceptable diet (Percent) Percent 41.0%* 3.45% 46.13% 5.45% ↑

Mean number of food groups consumed by women of reproductive age Food Groups 6.79* 0.09 7.53 0.05 ↑

Resilience and Empowerment Indicators Community group participation: Farming Percent 65% 1% 100% -- ↑ Community group participation: Water Percent 3% 2% 0.7% 0.5% ↓ Community group participation: Forestry Percent 7% 2% 3.3% 1.0% ↓ Community group participation: Fisheries Percent 9% 3% 0.7% 0.5% ↓ Community group participation: Health Percent 2% 1% 2.6% 0.9% – Community group participation: Credit Percent 10% 3% 10.8% 1.8% – Community group participation: Women Percent 2% 2% 0.3% 0.3% ↓ Community group participation: Youth Percent 0% 0% 0.0% -- – Percent of households overcoming shocks through sustainable means Percent -- -- 47.17% 4.89% –

Percent of women reporting adequacy on 80% of WEAI domains Percent -- -- 98.51% 1.07% – * Indicates baseline value was recalculated at endline and differs from baseline report – see text within each indicator for description of changes.

5 Note: Agriculture, Forestry and Fishing. Not available for agriculture disaggregated. 6 A full list of productive assets can be found in the corresponding section in the body of the report.

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INTRODUCTION The United States Agency for International Development’s (USAID) Avansa Agrikultura Project (Avansa Agrikultura) is a five-year horticulture value chain activity in Timor-Leste implemented by Cardno Emerging Markets and three subcontractors: HIAM Health (Hamutuk Ita Ajuda Malu/Together we help each other), Resonance Global, and the Borlaug Institute. Avansa Agrikultura aims to address key barriers to economic growth in Timor-Leste, specifically rural poverty, natural resource degradation, food insecurity, and under-nutrition. A horticulture value chain approach aimed to increase productivity and relationships between and among farmers, markets, financial institutions, and input suppliers. Through the promotion of sustainable production practices, increased functionality of farmer groups and associations, improved market linkages, and increased availability and access to quality agricultural inputs and services, including access to finance, the project aimed to stimulate and support increased economic activity and growth in targeted rural communities and municipalities.

Avansa Agrikultura supported policy development and the development of an enabling environment relevant to the sector to ensure the sustainability of the project’s gains. Avansa Agrikultura fully integrated two primary Feed the Future (FTF) objectives of inclusive agricultural sector growth and improved nutritional status, particularly for women and children. The project worked in six municipalities via a phased approach: implementation began in Ainaro and Ermera, followed by Bobonaro, Aileu, and Dili. Though not included in Avansa Agrikultura’s initial workplan, Liquiçá was added in 2019.

Avansa M&E, implemented by Social Impact (SI) is a five-year project (April 2015-December 2020) designed to support the USAID Avansa Agrikultura Project and USAID/Timor-Leste Economic Growth Office in its monitoring, evaluation, and collaboration, learning, and adapting efforts. Though this contract, SI was initially tasked with conducting baseline and endline surveys for the Avansa Agrikultura project. While SI implemented a full population based survey at baseline including 1,200 households across five municipalities, the Avansa M&E contract was modified between baseline and endline so that SI would no longer implement a full endline survey, but would conduct an analysis of endline outcomes of interest using data from Avansa Agrikultura’s annual household survey, 331 households across six municipalities in 2020.

This report presents baseline and endline figures for seven outcomes of interest as well as endline values only for two additional indicators that were not measured at baseline. These outcomes of interest were selected in collaboration with Avansa Agrikultura and USAID/Timor-Leste as the most relevant outcomes of interest at the close of the project. The nine total indicators are grouped by three key themes of financial stability and economic growth, hunger and nutrition, and resilience and empowerment, as displayed on the next page:

Avansa Agrikultura Project Purpose: To accelerate inclusive and sustainable economic growth through increased productivity/ profitability of the horticulture value chain and to support nutrition-smart agriculture interventions that support increased food production, agriculture income, and women's empowerment.

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FINANCIAL STABILITY & ECONOMIC GROWTH:

• Percent change in agriculture GDP (secondary data from General Directorate of Statistics, Ministry of Finance)

• Percent increase in household savings and/or investment in productive assets • Daily per capita expenditure (as a proxy for income) in United States Government (USG) assisted

areas

HUNGER & NUTRITION

• Prevalence of households with moderate to severe hunger • Prevalence of children 6-23 months receiving a minimum acceptable diet (MAD) • Mean number of food groups consumed by women of reproductive age (WRA)

RESILIENCE AND EMPOWERMENT

• Community group participation • Percent of households overcoming shocks through sustainable means (Not collected at baseline) • Percent of women reporting adequacy on 80 percent of Women’s Empowerment in Agriculture

Index (WEAI) domains (Not collected at baseline)

The figures presented in the body of the report do not include data from Liquiçá since implementation in this municipality was not planned at baseline and was implemented much later than the other five municipalities. While baseline and endline values are presented for the seven outcomes of interest collected at both baseline and endline, we caution against direct comparison of the figures due to the differing nature in methodology between the two survey years, especially with respect to sampling strategy and sample size. The nuances of the comparability of these figures are described further in the methodology section below. Additionally, this report is not intended to function as an evaluation of the Avansa Agrikultura Activity as the design does not support attribution and does not encompass the entirety of Avansa Agrikultura’s activities. Rather, this report should be used in combination with Avansa Agrikultura’s annual reporting and SI’s final performance evaluation (PE) to understand the impacts of Avansa Agrikultura in Timor-Leste.


METHODOLOGY

SAMPLING & WEIGHTING

The sample size for the endline survey was determined based on the number of sucos and beneficiary households that would be feasible for Avansa Agrikultura to enumerate; Avansa Agrikultura determined that they could enumerate a maximum of approximately 320 households in 37 sucos.

Avansa Agrikultura provided SI with a list of 484 beneficiary households in 42 sucos, from which SI first selected the 37 sucos. Due to the small number of beneficiary households in each suco, SI used a take-all approach among all sucos with more than 10 beneficiary households (16 sucos). SI then randomly selected 19 more sucos from the remaining sucos. From the 37 sampled sucos, SI randomly selected a number of households in each suco proportionate to the size of the suco, along with a set of replacement households in each suco where additional households were available. The total number of households selected was 322, with 129 potential replacements. Avansa Agrikultura completed additional replacement households beyond the 322 sampled in case of data quality issues, making the total number of households surveyed at endline 331.

Prior to analysis, SI calculated survey weights for each household based on the inverse probability of selection at each sampling stage. All analyses were performed using the “svy” command in Stata statistical software, which is designed to handle features of data collected through use of complex survey designs including sampling weights, cluster sampling, and stratification.

INSTRUMENTS

The endline household survey was adapted from two primary sources: Avansa Agrikultura’s 2019 household survey and SI’s 2015 baseline survey. SI compared the two surveys, noting where they differed on question inclusion, wording, and answer choices, with the goal of adapting the 2019 household survey where needed to best compare with the 2015 baseline data. Avansa Agrikultura made minor changes to the survey based on SI’s recommendations to maximize comparability between baseline and endline, including shifting some household items between monthly and yearly expenditures; adding a second module on women’s nutrition to calculate the food groups eaten both in the last 24 hours and in the last 30 days; and making minor changes to answer choices and question wording throughout.

In addition to revisions designed to ensure comparability of baseline and endline questions, SI added a few new groups of questions to accommodate additional indicators not included in previous surveys. These included household experiences with shocks (such as death, loss of income, and diseased livestock and crops), associated coping mechanisms, and women’s household decision-making power.

The endline survey had four groups of respondents: the first being an adult over the age of 18 to answer questions about the household’s demographics, community group participation, income and expenditures, ownership and investments, hunger prevalence, and response to shocks;7 the second group encompassing all WRA (between the ages of 15 and 49) to answer questions on their food consumption; the third group being the primary caretaker of each infant to answer questions about infant nutrition; and the fourth group being the primary female decision-maker in the house to answer questions about their decision-making role in the household.

7 While at baseline, the primary respondent was the “head of household;” this terminology was removed from use within the Avansa Agrikultura project due to gendered stereotypes around this term.


FIELDWORK

The endline survey was implemented by enumerators contracted by the Avansa Agrikultura project with technical support from SI. Specifically, SI supported Avansa Agrikultura’s endline survey by collaborating with USAID and Avansa Agrikultura to select the outcomes of interest included in this report; proposing revisions to the endline survey instrument to ensure comparability of the baseline indicator calculations to endline; proposing additional survey questions to calculate the two new indicators; suggesting cuts to shorten the duration of the survey; providing inputs to Avansa Agrikultura’s enumerator training related to the outcomes of interest indicators; conducting the sampling; reviewing pilot data; and conducting data quality assurance during fieldwork through review of interim datasets and high frequency checks on key variables run in Stata.

Avansa Agrikultura conducted enumerator training between June 25, 2020 and July 2, 2020, with a pilot test of 66 households between July 6-7, 2020. Fieldwork was conducted between July 8-22 in the six Avansa Agrikultura municipalities: Ainaro, Ermera, Bobonaro, Aileu, Dili, and Liquiçá.

DATA CLEANING & ANALYSIS

After completing data collection, the Avansa Agrikultura team checked and cleaned the data and sent the final dataset to SI for additional cleaning and analysis in July 2020. SI ran additional checks on the data supplied by Avansa Agrikultura and sought clarification on potential outliers and duplicate household IDs. Avansa Agrikultura translated open-ended responses from Tetum to English, and SI used these data to recode “other” responses as needed. Data analysis was conducted by the SI headquarters team in August and September 2020 using Stata. The SI team ran the baseline analysis to ensure replicability with what was reported in the baseline report and adapted the analysis files for use at endline. In some cases, the baseline value presented in this report differs slightly from what was initially reported at baseline; though these cases are explained in detail in the table notes for each indicator, the broad goal was to maximize comparability across survey years.

SECONDARY DATA SOURCES

Throughout the report we draw on two secondary data sources to triangulate findings. First, we incorporate qualitative data collected from USAID, Avansa Agrikultura staff, and various beneficiary groups through SI’s final PE, conducted during summer 2020.8 Second, we present comparisons of some indicators with Avansa Agrikultura’s internal monitoring data in cases where data are available and relatively comparable to the outcomes of interest calculations.

REPORTING CONVENTIONS

As mentioned in the introduction above, all figures presented in the body of this report do not include Liquiçá to maintain consistency with the baseline data. However, additional report tables for all six of Avansa Agrikultura’s municipalities, including Liquiçá, can be found in Annex D. Throughout the report, we present indicator values across five standard disaggregates as detailed below.

GENDERED HOUSEHOLD TYPE: A November 2018 research note from the World Bank noted that women in Timor-Leste have lower levels of literacy and less involvement in cash crop production and farmer groups than men. Women ultimately produce 15 percent less per hectare of land than

8 The Final PE Report will be available on USAID’s Development Experience Clearinghouse in December 2020.


men.9 Since the endline survey did not include a full household roster in order to reduce survey duration, SI merged gendered household type classifications into the endline dataset from Avansa Agrikultura’s monitoring data. These classifications are: (1) households that include both male and female adults, 18 years of age or older (MF); (2) households that include female adults, but no male adults (FNM); and (3) households that include male adults, but no female adults (MNF). This approach to conceptualizing household type is distinct from the standard “head of household” approach, which is embedded with presumptions about household gender dynamics and may perpetuate existing social inequalities and prioritization of household responsibilities that may be detrimental to women.

HOUSEHOLD SIZE: The household size variable was determined at endline through a question at the beginning of the survey asking respondents for the total number of members in their household, and grouped into three categories that were used at baseline: (1) households with between one and five members (2) households with between six and 10 members; and (3) households with 11 or more members.

MUNICIPALITY: Municipality was included in the sampling data and verified in the household survey. As described above, data from Ainaro, Ermera, Bobonaro, Aileu, and Dili can be found in the report body, with supplementary data tables including Liquiçá in Annex D.

EDUCATION OF PRIMARY RESPONDENT: Whereas at baseline the education disaggregate refers to level of education of the household head, at endline this disaggregate refers to reported level of education of the primary respondent. The categories are No School, Primary School, and Secondary and Higher. The Secondary and Higher classification encompasses junior high school, senior high school, vocational college, and university.

ANY SHOCK: While not available for baseline, at endline this disaggregate is calculated using questions from the “percent of households overcoming shocks through sustainable means” indicator. A household is determined to have “no shocks” if the household reported not experiencing any of the 16 shocks asked or any other shock in the past year, and “one or more shocks” if the household reported experiencing one or more of the 16 shocks asked or “other” in the past year. The 16 shocks asked are based on the shocks component of the FTF Ability to Recover from Shocks and Stresses Index. Examples of shocks include getting too much or too little rain, crop disease, and death in the family.

LIMITATIONS

DIFFERENCES IN BASELINE AND ENDLINE METHODOLOGY: The largest difference between the baseline and endline methodology is with respect to the sample size and sampling approach. At baseline, SI conducted a population-based survey of 1,200 households designed to be generalizable to the population of the initial Avansa Agrikultura zone of influence.10 Due to changes in contract scope as described above, the sampling methodology at endline was much different. Rather than using census data as the sample frame, as was done at baseline, the sample frame at endline was Avansa Agrikultura beneficiary households. This means that while baseline estimates are generalizable to the general population of the initial Avansa Agrikultura zone of influence in Ainaro, Ermera, Bobonaro, Aileu, and Dili, endline estimates are only generalizable to the beneficiary population in the current Avansa

9 Gavalyugova, D., Caminha, S., Verdial, T., and Perova, E. (November 2018). Women farmers in Timor-Leste: Bridging the productivity gap. http://documents1.worldbank.org/curated/en/709001543605005333/pdf/132609-WP-EAPWomenFarmersFullReportv.pdf. 10 Details on the baseline sampling approach can be found in Annex E.

http://documents1.worldbank.org/curated/en/709001543605005333/pdf/132609-WP-EAPWomenFarmersFullReportv.pdf

http://documents1.worldbank.org/curated/en/709001543605005333/pdf/132609-WP-EAPWomenFarmersFullReportv.pdf


Agrikultura zone of influence in Ainaro, Ermera, Bobonaro, Aileu, Dili, and Liquiçá. Additionally, the much smaller sample at endline of 331 households limits the degree of statistical reliability of many of the disaggregate estimates. Disaggregate estimates with n values lower than 30 should be interpreted with particular caution. Standard error values are presented throughout the report as a measure variance within each estimate.

TIMING OF SURVEY: The hunger season in Timor-Leste typically falls in January-February before the harvest begins in March-April. Though both the baseline and endline surveys were conducted at a time when food supplies are still adequate as recommended by FTF for the nutrition indicators, the values presented here may not represent the situation at its worst when supplies are much more scarce. Baseline data were collected shortly before the hungry season in November, compared to endline data that were collected in July when households typically have better access to food and crops. The timing of endline data collection also coincided with the global COVID-19 pandemic and findings related to COVID-19 are detailed in each section below.

FTF METHODOLOGICAL CONSTRAINTS: Some FTF methodology is extremely time consuming for enumeration. For example, FTF methodology to provide data on consumption expenditure may take up to one hour for only one indicator. Due to the time constraints of the survey, some FTF indicators were assigned to be custom indicators in agreement with the USAID/Timor-Leste. For example, SI used the Oxfam question module on the nutritional status of women (mean number of food groups consumed by WRA) to replace the FTF indicator. This was sourced from the Oxfam 2007 Timor-Leste Food Security Baseline Survey. Additionally, for the expenditure indicator, SI adapted the methodology used in two national-level surveys to create a less time-consuming methodology to track the expenditure of households.


FINDINGS

DEMOGRAPHICS

Table 2 displays demographic characteristics of households at baseline and endline. Most survey respondents at both baseline and endline were men: 88 percent at baseline and 65 percent at. Most households at both baseline and endline had both male and female adults and between six and ten household members. The mean household size, mean number of WRA, and mean number of children per household all increased from baseline to endline. The education level of the primary respondent remained relatively consistent from baseline to endline; the largest change was a decrease in respondents with no education from 50 percent at baseline to 42 percent at endline.

Table 2: Household Demographics

Disaggregate Baseline Endline

Estimate n Estimate n Replacement Rate – 1,200 16.9% 306 Gendered Household Type MF 94.28% 1,133 95.37% 292 FNM 3.9% 40 3.39% 10 MNF 1.82% 27 1.25% 4 Household Size Mean household size 6.71 1,200 7.47 306 Mean number WRA per household 0.97 1,200 1.62 302

Mean number children per household 0.31 1,200 0.40 306

1-5 Members 34.99% 434 26.09% 88 6-10 Members 55.59% 666 57.80% 189 11+ Members 9.41% 100 16.11% 54 Municipality Aileu 13.05% 224 26.73% 82 Ainaro 28.03% 332 21.21% 63 Bobonaro 22.88% 211 24.89% 79 Dili 8.84% 111 10.32% 33 Ermera 27.19% 302 16.85% 49 Education Level No Education 50.02% 592 42.07% 130 Primary School 28.21% 341 30.48% 92 Junior High School 10.29% 136 12.87% 39 Senior High School 9.57% 109 10.86% 34 Vocational College 0.80% 10 1.20% 4 University 1.12% 12 2.51% 7 Primary Respondent Gender Male 88.65% 1,064 64.55% 198 Female 11.35% 136 35.45% 108 Primary Respondent Age Group 18-30 12.09% 150 8.91% 28 31-40 17.61% 219 22.35% 71 41-50 25.55% 303 28.66% 85 51-60 21.28% 250 28.74% 89 61-70 17.73% 206 8.87% 26


Disaggregate Baseline Endline Estimate n Estimate n

71-80 4.47% 56 2.47% 7 80+ 1.16% 16 0% 0

Table 3 displays demographic characteristics of WRA at baseline and endline. The largest difference in education level was WRA with no education: the proportion of WRA surveyed with no education was 63 percent at baseline compared to 24 percent at endline. The proportion of women aged 30-49 was higher at endline than at baseline, at about 51 percent at endline compared to 37 percent at baseline.

Table 3: WRA Demographics


Estimate n Estimate n

Education Level No Education 62.90% 657 23.14% 70 Primary School 17.01% 192 20.66% 60 Junior High School 10.97% 114 20.30% 59 Senior High School 8.82% 95 30.35% 93 Vocational College 0.16% 2 0.61% 2 University 0.14% 3 4.95% 14 Age Groups 15-29 62.75% 649 48.81% 146 30-49 37.25% 414 51.19% 152

Table 4 displays demographic characteristics of children surveyed at baseline and endline. The percentage of male children in the endline sample, at 61 percent, was higher than in the baseline sample, at 52 percent. While the baseline sample was concentrated around children 12-17 months of age, the endline sample was more evenly balanced across age ranges.

Table 4: Child Demographics


Estimate n Estimate n

Gender Male 52.02% 97 61.13% 53 Female 47.98% 97 38.87% 33 Age Groups 6-11 months 22.13% 43 33.66% 28 12-17 months 61.97% 119 39.61% 36 18-23 months 15.90% 32 26.72% 22


FINANCIAL STABILITY

PERCENT CHANGE IN AGRICULTURE GDP

The values for this indicator are sourced from the Timor-Leste General Directorate of Statistics, Ministry of Finance as secondary data. The Food and Agriculture Organization of the United Nations (FAO) conducts a food crop assessment periodically and this provides the estimates for annual crop production that forms part of the GDP calculation. The National Accounts Section of the General Directorate of Statistics uses the FAO crop production estimates for the previous year and adjusts the estimates for the current year, for which GDP estimates are required, based on current expectations of production supplied by the Ministry of Agriculture and Fisheries. Assumptions are also used in the calculations regarding input costs such as seeds, levels of stocks, consumption, and prices. The General Directorate of Statistics does not release the value of agricultural GDP separately; only an aggregated figure is published for agriculture, forestry, and fishing and therefore the disaggregate for agricultural GDP alone is not available for Timor-Leste. Data also cannot be disaggregated by municipality, or any of the other key disaggregates used throughout this report.

Table 5 presents baseline and endline figures for the agriculture, forestry, and fishing GDP. GDP data are historical, so are lagged and normally available a year after data collection/estimation. Due to this lag in reporting, 2013 data are presented for baseline, and 2019 data for endline. Estimates for both baseline and endline are shown in constant (2015) prices to optimize comparability across years. GDP growth rates to previous years are reported as well, given the lag in national GDP reporting.

The agriculture, forestry, and fishing GDP in 2015 prices decreased by 4.7 percent from $300.2 million at baseline to $286.1 million at endline. In 2013, GDP had dropped by 5.2 percent from the previous year, whereas in 2019, GDP had grown by 2.5 percent from the previous year, suggesting an upward trend.

Table 5: Percent Change in Agriculture, Forestry, and Fishing GDP11

Indicator Baseline (2013)

Endline (2019) Difference Percent

Change Estimate Estimate

Production approach: value added by industries at constant prices

$300.2 Million

$286.1 Million

$14.1 Million -4.7%

Production approach: growth rates to previous year

-5.2% 2.5% -- --

Note: The baseline value was previously reported in current (2013) prices as $254 million. Values above are reported in constant (2015) prices to optimize comparability across reporting years.

Figure 1 presents a more granular look at the agriculture, forestry and fishing GDP in Timor-Leste between 2013 and 2019. There was a decrease in agriculture, forestry, and fishing GDP in the early years of Avansa Agrikultura (2015-2017). However, the increase from $271M in 2017 to $286M in 2019 may be indicative of a rebound in the value of agriculture, forestry, and fishing to Timor-Leste’s GDP.

11 Ministry of Finance of Timor-Lese, General Directorate of Statistics. (April 2015). Timor-Leste National Accounts 2000-2013. https://www.statistics.gov.tl/wp-content/uploads/2015/06/A4-NA-2014-OK.pdf; Ministry of Finance of Timor-Lese, General Directorate of Statistics. (October 2020). Timor-Leste National Accounts 2000-2019. https://www.statistics.gov.tl/wp-content/uploads/2020/10/Timor-Leste-National-Accounts-2000-2019-Versaun-Final_201008.pdf.

https://www.statistics.gov.tl/wp-content/uploads/2015/06/A4-NA-2014-OK.pdf

https://www.statistics.gov.tl/wp-content/uploads/2020/10/Timor-Leste-National-Accounts-2000-2019-Versaun-Final_201008.pdf

https://www.statistics.gov.tl/wp-content/uploads/2020/10/Timor-Leste-National-Accounts-2000-2019-Versaun-Final_201008.pdf


Figure 1: Agriculture, Forestry and Fishing GDP ($M), 2013-2019

PERCENT INCREASE IN HOUSEHOLD SAVINGS AND/OR INVESTMENT IN PRODUCTIVE ASSETS

Households were asked questions about their savings, including cash, bank deposits, and valuables such as jewelry, and ownership of productive assets. The assets were weighted according to their original value and a depreciation schedule that assumed a half-life of each good to generate a current estimated value for each.

Table 6 below presents values for total household assets including both savings and productive assets. Values for savings at endline were adjusted to 2015 prices using the Consumer Price Index for Timor-Leste (base year=2015) to maximize comparability from baseline to endline.12 Values for productive assets were not adjusted for inflation; the same assumed prices were used at endline for all assets included in the baseline analysis.

Among all households, total assets (including savings and productive assets) increased by $144.31 from baseline to endline, or 7.5 percent. Total assets increased the most among FNM households and the least among MF households; however, the sample sizes at endline among the FNM and MNF households were very low at ten and four households, respectively, limiting statistical reliability of the endline estimates.

Total assets increased the most among smaller households of one to five members, who saw a 23 percent increase in assets. Differences in total assets varied across municipality. Households in Aileu

12 https://data.humdata.org/dataset/faostat-prices-for-timor-leste.

https://data.humdata.org/dataset/faostat-prices-for-timor-leste


saw the greatest increase, at 91 percent; this finding is consistent with findings in the Avansa Agrikultura midterm PE, which noted that Aileu has a long history of agriculture and has been a USAID target since USAID’s previous agriculture project, Developing Agricultural Communities. Ainaro households saw the second-largest increase, at 50 percent. Households in Dili saw a decrease of 47 percent. Total assets stayed relatively constant in Bobonaro and Ermera.

Though not asked at baseline, endline values for total assets differed between households that had not experienced a shock in the last year and those that had: the total asset value among households who had experienced no shocks was $1,720.56, compared to $2,119.05 among households who experienced at least one shock in the last year.13

Table 6: Household savings and/or investment in productive assets – 2015 prices

Disaggregate Baseline (2015) Endline (2020) Difference

Estimate n Standard Error


USD Percentage

All Households

$1,927.01 1,200 $177.58 $2,071.32 306 $172.51 +$144.31 +7.5%

Gendered Household Type MF $1,990.36 1,133 $187.67 $2,021.41 292 $178.51 +$31.05 +1.56% FNM $900.62 40 $156.22 $3,950.52 10 $745.56 +$3,049.90 +338.64% MNF $846.28 27 $207.99 $787.34 4 $129.37 -$58.94 +6.96% Household Size 1-5 Members $1,706.32 434 $134.73 $2,102.55 84 $372.37 +$396.23 +23.22% 6-10 Members $2,000.40 666 $254.70 $1,965.67 175 $233.43 -$34.73 -1.74% 11+ Members $2,314.00 100 $420.94 $2,417.64 47 $433.05 +$103.64 +4.48% Municipality Aileu $1,583.62 244 $179.42 $2,037.29 82 $312.46 +$1,453.67 +91.79% Ainaro $1,487.69 332 $141.27 $2,233.22 63 $551.63 +$745.53 +50.11% Bobonaro $2,441.43 211 $275.53 $2,362.79 79 $160.44 -$78.64 -3.25% Dili $4,137.23 111 $1,299.58 $2,192.56 33 $335.59 -$1,944.67 -47.00% Ermera $1,392.87 302 $165.93 $1,416.65 49 $278.57 +$23.77 +1.70% Education of Primary Respondent

13 See Page 28 below for further information on shocks experienced and coping strategies.





USD Percentage

No Education $1,931.12 592 $166.03 $2,043.41 130 $248.00 +$112.29 +5.81% Primary School

$2,056.91 341 $425.31 $1,588.03 92 $261.56 -$468.91 -22.80%

Secondary and higher

$1,749.28 267 $137.61 $2,650.98 84 $238.04 +$901.70 +5.18%

Any Shock No shocks - - - $1,720.56 37 $141.19 - One or more shocks

- - - $2,119.05 269 $201.73 -

Note: Baseline value was previously reported as $2,024. However, this figure was revised after finalization of the baseline report to remove a small number of extreme outliers. Though $2,024 appeared in the baseline report, the correct baseline value is $1,927.01.

Table 7 displays the breakdown of total assets at baseline and endline by asset type. Though total assets increased from $1,927.01 at baseline to $2,071.32 at endline, this increase was not uniform across asset types. Households saw a large increase in savings, from $133.62 at baseline to $700.68 at endline. Whereas savings represented only about seven percent of a household’s total assets at baseline, savings represented about 34 percent of a household’s total assets at endline. Among savings types, the greatest change was among cash savings, increasing from $50.16 at baseline to $301.22 at endline. This large difference may be influenced in part by the Government of Timor-Leste’s COVID-19 stimulus program: the government provided households where the head of household’s income was less than $500 per month with $100 per month for two months during spring 2020 in response to the COVID-19 state of emergency. Among savings types, household loan value also increased dramatically from $27.56 at baseline to $57.48 at endline. This change may be due in part to increased access to loans through Avansa Agrikultura-supported savings and loans groups and Avansa Agrikultura-supported cost-sharing of agriculture-related loans. As of endline, the primary lender of agricultural sector loans, Kaebauk, had over 70 active loans out to farmers. Annex C displays am alternate savings and productive assets analysis that includes Kaebauk.

Table 7: Value of savings and productive assets by asset type

Disaggregate Baseline (2015) Endline (2020)

Estimate Percent of Assets


Savings $133.62 6.93% $700.68 33.83% Cash $50.16 3.60% $301.22 21.11% BNCTL Government Bank $26.59 0.31% $64.65 1.81% UBSP (Savings and loan group)

$1.27 0.11% $96.47 7.03%

Moris Rasik $8.78 0.28% $14.64 0.81% Other bank $4.67 0.30% $20.10 0.50% Gold, silver, or other precious metals

$4.39 0.26% $140.03 6.17%

Jewelry $8.73 0.36% $6.09 0.84% Other $1.46 0.09% $0.00 0.00% Loans $27.56 2.34% $57.48 3.05%

Productive Assets $1,793.39 93.07% $1,370.64 66.17%





Fishing $64.04 3.47% $4.55 0.36% Livestock $1,152.14 62.90% $513.02 25.86% Household durables $109.72 12.94% $138.22 12.23% Transport $305.05 7.55% $620.83 16.68% Farm Equipment $162.42 5.49% $94.02 3.54%

Transfers $84.69 - $39.52 - Cash $58.38 - $18.74 - In-kind $26.31 - $20.78 -

Table 8 displays the differences in savings across municipalities and gendered household types. Savings increased the most substantially from baseline to endline among FNM households, though the sample size among these households is low with 40 FNM households at baseline and 10 at endline. While savings increased by 400 percent or more in four of the five municipalities, there was no change in savings among beneficiary households in Dili.

Table 8: Savings by Disaggregate


Estimate n Estimate n USD Percent Gendered Household Type MF $136.40 1,133 $690.01 292 +$553.61 +405.9% FNM $65.29 40 $1,214.29 10 +$1,149.00 +1,759.8% MNF $136.02 27 $123.00 4 -$13.02 -9.6% Municipality Aileu $42.18 244 $565.52 82 +$523.34 +1240.7% Ainaro $160.60 332 $874.41 63 +$713.81 +444.5% Bobonaro $107.32 211 $911.69 79 +$804.37 +749.5% Dili $371.48 111 $371.54 33 +$0.06 +0.02% Ermera $94.46 302 $586.11 49 +$491.65 +520.5%

Contrary to the large increase in savings, households saw a decrease in value of productive assets, from $1,793 at baseline to $1,370 at endline. Among asset types, the greatest change was in livestock: whereas livestock represented about 63 percent of a household’s assets at baseline, this value decreased to about 26 percent at endline. Though ownership of fishing, livestock, and farm equipment decreased, ownership of household durables and transport assets increased. The increase was especially large with transport assets, with the mean value of transport assets owned by a household increasing from $305.05 at baseline to $620.83 at endline. This increase in transport assets was triangulated by qualitative data gathered through the final PE, where five out of 18 farmer focus groups mentioned buying a vehicle of some sort with increased income from the Avansa Agrikultura project. Farmers explained that owning a form of transport allows them to transport produce themselves rather than relying on public transportation and allows them to travel to harder-to-reach areas.

“The results of this horticulture activity do benefit for all members, the children could access to good education, consumed the nutritious foods, built and rehabilitated house, and purchased motorbike. The children of the members of this group majority are study at private schools.” – Aileu Farmer


Table 9 displays the differences in productive assets across municipalities and gendered household types. Productive assets increased substantially among FNM households and decreased among other gendered household types, though the sample size is small among the FNM and MNF types. Productive assets remained relatively constant for households in Aileu and Ainaro; decreased by about one-third for households in Bobonaro and Ermera; and decreased by the largest amount in Dili by about 50 percent.

Table 9: Productive Assets by Disaggregate


Estimate n Estimate n USD Percent Gendered Household Type MF $1,853.96 1,133 $1,331.40 292 -$522.56 -28.2% FNM $835.34 40 $2,736.23 10 +$1,900.89 +227.6% MNF $710.26 27 $664.34 4 -$45.92 -6.5% Municipality Aileu $1,541.45 244 $1,471.67 82 -$69.78 -4.5% Ainaro $1,327.09 332 $1,358.81 63 +$31.72 +2.4% Bobonaro $2,334.11 211 $1,451.11 79 -$833.00 -37.8% Dili $3,765.75 111 $1,821.02 33 -$1,944.73 -51.6% Ermera $1,298.42 302 $830.54 49 -$467.88 -36.0%

Figure 2 below displays the proportion of households that fell within each of seven asset classes, ranging from less than $1,000 in total assets to greater than $10,000. The greatest change from baseline to endline was in the lowest asset class, where the percentage of households falling in the lowest class decreased from 48 percent at baseline to 39 percent at endline. There were slight increases in the next two classes, while the proportion of households falling in the highest four classes remained relatively consistent. The plurality (29.12 percent) of MF households fell into the $1k-$2k asset class, while the majority (73.46 percent) of MNF households were in the <$1,000 asset class. The plurality (32.89 percent) of FNM households were in the $5k-$10k asset classes, followed by 29.33 percent in the $1k-$2k class.

Figure 2: Value of assets by range class


DAILY PER CAPITA EXPENDITURE (AS A PROXY FOR INCOME) IN USG ASSISTED AREAS

Household expenditure totals are used as a proxy for household incomes, based on the assumption that a household’s consumption is closely related to its income. Household consumption and expenditures are often preferred to income when measuring poverty due to the difficulty in accurately measuring income, as expenditure data are less prone to error, easier to recall, and more stable over time than income data.14 For the Avansa Agrikultura household surveys, a per capita daily consumption aggregate is constructed by summing daily values of a household’s food expenditures over seven days, non-food expenditures over the past month, and non-food expenditures over the past year, then dividing the total by the number of household members. Note that in this approach, every household member is assumed to have an equal share of the total consumption, regardless of age and other characteristics.

Figure 3: Calendar from Avansa Agrikultura demonstrating recommended expenses, financial literacy tips

Photo Credit: Nazario Dos Santos, SI Timor-Leste Team

Table 10 below presents values for per capita household expenditures. Endline values were adjusted to 2015 prices using the Consumer Price Index for Timor-Leste (base year=2015) to maximize comparability from baseline to endline.15 Among all households, daily per capita expenditure in 2015 prices decreased slightly from $1.63 at baseline to $1.54 at endline.16 Among gendered household types, daily per capita expenditures increased in FNM and MNF households and decreased in MF households; however, the sample sizes at endline among the FNM and MNF households were very low, limiting statistical reliability of the endline estimates. Regarding household size, households with one to five members saw an increase of $0.16 from baseline to endline, while households with six to ten and 11 or more members both saw decreases, of $0.06 and $0.12, respectively. Households in Aileu and Bobonaro saw an average increase in daily per capita expenditures, while households in

14 Deaton, A. (2008). The analysis of household surveys: A microeconomic approach to development policy. Baltimore, MD: The Johns Hopkins University Press. 15 https://data.humdata.org/dataset/faostat-prices-for-timor-leste. 16 The endline calculation includes only specific items that were asked at baseline ($1.54). When including items that were not asked at baseline, the endline calculation is $1.57. Both sets of items are included in Table 11; items that were not asked at baseline and not included in the endline calculation are denoted with three asterisks, per the table note.

https://data.humdata.org/dataset/faostat-prices-for-timor-leste


Ainaro, Dili and Ermera saw a decrease. Though not asked at baseline, endline values for daily per capita expenditures differed between households that had or had not experienced a shock in the last year and those that had: the mean daily per capita expenditure in households with no shocks was $1.67, compared to $1.52 in households who experienced one or more shocks.17

Table 10: Daily per capita expenditure – 2015 prices




USD

All Households $1.63 1,200 $0.07 $1.54 306 $0.10 -$0.09 Gendered Household Type MF $1.63 1,133 $0.08 $1.48 292 $0.09 -$0.15 FNM $1.32 40 $0.30 $1.76 10 $0.27 +$0.44 MNF $2.63 27 $0.48 $5.84 4 $1.95 +$3.21 Household Size 1-5 Members $2.16 434 $0.15 $2.32 84 $0.28 +$0.16 6-10 Members $1.41 666 $0.08 $1.35 175 $0.05 -$0.06 11+ Members $1.00 100 $0.09 $0.88 47 $0.06 -$0.12 Municipality Aileu $1.44 244 $0.06 $1.63 82 $0.28 +$0.19 Ainaro $1.53 332 $0.10 $1.34 63 $0.11 -$0.19 Bobonaro $1.29 211 $0.09 $1.84 79 $0.05 +$0.55 Dili $1.68 111 $0.22 $1.34 33 $0.12 -$0.34 Ermera $2.11 302 $0.19 $1.34 49 $0.11 -$0.77 Education of Primary Respondent No Education $1.57 592 $0.10 $1.66 130 $0.21 +$0.09 Primary School $1.57 341 $0.10 $1.35 92 $0.09 -$0.22 Secondary and higher

$1.86 267 $0.16 $1.57 84 $0.10 -$0.29

Any Shock No shocks - - - $1.67 37 $0.15 - At least 1 shock - - - $1.52 269 $0.10 -

Note: Baseline value was previously reported as $1.76. This value included monthly loan interest payments. The loan interest section of the endline survey was revised to better fit the local context, and does not ask for loan interest expenditures on a monthly basis; thus the figures presented in this table for both baseline and endline do not include loan interest expenditures.

Figure 4 below presents daily per capita expenditure at baseline and endline by range class. There was a slight decrease in households with daily per capita expenditure of less than $1.00, from 41 percent at baseline to 38 percent at endline, and a more substantial increase in households with expenditure between $1.00-$2.00, from 36 percent at baseline to 43 percent at endline. The proportion of households falling in the higher range classes was relatively consistent between baseline and endline estimates. At endline, 75 percent of MNF households had daily spending over >$4.00, an increase from 24 percent at baseline. FNM and MF households both experienced slight decreases in the $1.00 range class and slight increases in the $1.00-$2.00 range class, consistent with households overall.

17 See Page 28 below for further information on shocks experienced and coping strategies.


Figure 4: Daily per capita expenditure by range class

Table 11 presents the mean value of expenditures for each item in household expenditures. Consistent with the overall decrease in food expenditures, households spent less on all but two food items: eggs/milk and legumes. Mirroring the increase in transport assets noted in the savings and productive assets section above, expenditures on the maintenance of motor cars/motorbikes, vehicles, and bus fares and other transport charges all increased. Findings related to dwelling improvements are triangulated by the qualitative PE data: eight out of 18 farmer groups reported using increased income to improve their dwelling, as reflected in increased expenditures on furniture below. Spending on festivals and ceremonies also increased by 69 percent.

Table 11: Household Expenditures by Item, 2015 Prices

Item Baseline (2015) Endline (2020) Difference

Estimate na Standard Error


USD

Food Items All Food $1.07 1,197 $0.05 $0.75 306 $0.05 -$0.32 Cereals $0.38 958 $0.03 $0.32 276 $0.03 ↓ Tubers $0.03 299 $0.00 $0.01 52 $0.00 ↓ Fresh Fish $0.04 460 $0.00 $0.03 137 $0.01 ↓ Tinned Fish $0.03 477 $0.00 $0.01 85 $0.00 ↓ Fresh Meat $0.06 300 $0.00 $0.04 64 $0.01 ↓ Tinned Meat $0.01 110 $0.00 $0.00 14 $0.00 ↓ Eggs*

$0.04 576 $0.00 $0.02 187 $0.00

– Milk* $0.02 125 $0.01 Vegetables $0.07 639 $0.01 $0.01 62 $0.00 ↓ Legumes $0.01 141 $0.00 $0.01 88 $0.00 – Fruit $0.01 81 $0.00 $0.00 18 $0.00 ↓ Oil $0.10 997 $0.01 $0.08 295 $0.00 ↓ Sugars $0.08 1,104 $0.01 $0.05 300 $0.00 ↓ Spices $0.07 1,008 $0.01 $0.03 297 $0.00 ↓ Beverages $0.02 242 $0.00 $0.01 48 $0.00 ↓ Alcohol $0.04 195 $0.01 $0.02 65 $0.00 ↓ Tobacco $0.08 905 $0.01 $0.07 241 $0.00 ↓ Water*** - - - $0.00 22 $0.00 n/a Non-Food Items – Past Month Non-Food Items $0.41 1,194 $0.03 $0.34 305 $0.03 -$0.07


Item Baseline (2015) Endline (2020) Difference



USD

Personal care items $0.04 1,161 $0.00 $0.03 300 $0.00 ↓ House cleaning products

$0.01 358 $0.00 $0.00 94 $0.00 ↓

Health and medical treatment

$0.02 630 $0.00 $0.01 121 $0.00 ↓

School fees and textbooks

$0.13 830 $0.01 $0.04 108 $0.01 ↓

Stationary, newspapers and postage

$0.00 179 $0.00 $0.00 5 $0.00 –

Maintenance of motor car/motorbike**

$0.05 113 $0.02 $0.07 121 $0.01 ↑

Petrol/Diesel for vehicles

- - - $0.04 135 $0.00 n/a

Bus fares and other transport charges

$0.02 347 $0.00 $0.04 148 $0.00 ↑

Entertainment $0.00 15 $0.00 $0.00 24 $0.00 – Payments to household servants

$0.00 6 $0.00 $0.01 11 $0.00 ↑

License fees (vehicles) $0.00 5 $0.00 $0.00 8 $0.00 – Clothing and footwear $0.11 786 $0.01 $0.07 210 $0.01 ↓ Telephone credit*** - - - $0.02 294 $0.00 n/a Electricity $0.01 471 $0.00 $0.00 30 $0.00 ↓ Gas $0.00 25 $0.00 $0.00 0 $0.00 – Petrol and kerosene $0.01 183 $0.01 $0.00 5 $0.00 ↓ Wood for cooking*** - - - $0.00 1 $0.00 n/a Non-Food Items – Past Year Non-Food Items $0.16 993 $0.01 $0.45 300 $0.06 +$0.30 Furniture $0.01 440 $0.00 $0.01 123 $0.00 ↑ Tax and insurances $0.00 6 $0.00 $0.00 0 $0.00 – Electrical equipment $0.01 268 $0.00 $0.03 201 $0.00 ↑ Household goods $0.01 812 $0.00 $0.01 171 $0.00 – Festivals and ceremonies

$0.10 498 $0.01 $0.17 277 $0.02 ↑

Vehicle $0.02 64 $0.00 $0.11 84 $0.05 ↑ Renting land*** - - - $0.01 21 $0.00 n/a Building/repairing fishponds***

- - - $0.00 7 $0.00 n/a

Other $0.00 3 $0.00 $0.11 92 $0.02 ↑ a Number of households with non-zero expenditures in each category * Spending on eggs and milk was combined at baseline and asked separately at endline ** Not included in overall expenditure calculation *** Asked at endline and not at baseline, thus not included in overall expenditure calculation


“These [Avansa] activities really increased the farmers income to sustain the family, and some income could use for traditional ceremony.” – Ermera Farmer

Contrary to the overall quantitative findings on expenditures, farmers in the PE frequently spoke about increased income as a result of Avansa Agrikultura activities. One Ermera farmer said, “The income that we get from selling vegetables help[s] us to send our children to school, buy food and our household needs.” Though the quantitative data show a decrease in expenditures on school fees, food and expenditures overall, these results may be complicated by several factors. First, the result follows closely the overall trend in Timor-Leste in agricultural GDP over time, which saw a 4.7 percent decrease between 2013 and 2019. Second, changes in per capita daily expenditure differed greatly across expenditure types: average food expenditure decreased by $0.32, while non-food items purchased over the past month decreased by $0.07, and non-food items purchased over the past year increased by $0.30. This relatively large decrease in food expenditures may be due in part to the fact that Avansa Agrikultura heavily encouraged farmers to set aside portions of food for consumption instead of sale, further detailed in Hunger & Nutrition. With increased production at farms and more consumption of famers’ own food, it is likely that farmers spent less on food purchases. Indeed, the largest decreases in per capita daily expenditure among food items were vegetables and cereals, decreasing by 6 cents each. Third, the per capita expenditures for items bought over past year increased (+$0.30), but items bought in the past week decreased (-$0.32), as did items bought in the past month (-$0.07); this may further substantiate the effects of COVID-19 on expenditure calculations. Finally, the average household size grew from 6.71 members at baseline to 7.47 members at endline, which would lower expenditures per capita if household expenditures remained constant.

HUNGER & NUTRITION

PREVALENCE OF HOUSEHOLDS WITH MODERATE TO SEVERE HUNGER

The household hunger score was generated using responses from a series of questions about hunger events, such as times during the past month when the household did not have enough to eat. The total responses were added together to generate a frequency of hunger events. If this number was two or three, the household was determined to have moderate hunger. If the number was greater than three, the household was determined to have severe hunger.

Table 12 provides a comparison between baseline and endline levels of hunger, comparing households with little to no hunger with households who had either moderate or severe hunger. At endline, only 0.01 percent of households experienced moderate or severe hunger, compared to 15.5 percent of households at baseline – a decrease of 15.48 percentage points. Only one of the 306 households surveyed at endline met the criteria for moderate hunger, and zero households met the criteria for


severe hunger. The substantial decrease in moderate to severe hunger was consistent across gendered household type, household size, municipality, education level, and shock prevalence.

Though the decrease in household hunger is substantial, of importance to note is the different time in which the baseline survey was conducted compared to endline. The hungry period in Timor-Leste is typically in January-February before the first maize harvest. Baseline data were collected shortly before the hungry season in November, compared to endline data that were collected in July when households typically have better access to food and crops. This difference in timing may have contributed in part to the seemingly large decrease in hunger.

“Food security for the beneficiaries is very good for the beneficiaries’ group because farmers start to store their food to consume as well. The project also helps farmer to consume varieties of foods compare to before the project intervention.” – Avansa Municipal Coordinator

Qualitative findings from the final PE triangulate this more tempered effect: seven out of 15 farmer groups reported an increase in their consumption, mentioning both being able to buy more food due to increased income and eat the vegetables they grow due to increased production. The overall decrease in hunger prevalence over time is also reflected in Avansa Agrikultura’s monitoring data, as shown for available survey years in Figure 5 below.

Figure 5: Comparison of prevalence of moderate to severe hunger over time in Avansa Agrikultura’s monitoring data and SI’s reporting

Table 12: Prevalence of Moderate to Severe Hunger


Difference Estimate n Standard Error


Municipalities

All Households 15.49% 1,200 0.01% 0.01% 306 0.01% -15.48% Gendered Household Type MF 15.77% 1,133 1.53% 0.01% 292 0.01% -15.76% FNM 4.53% 40 3.50% 0.00% 10 - -4.53% MNF 14.00% 27 6.26% 0.00% 4 - -14.00%





Household Size 1-5 Members 13.96% 434 2.1% 0.00% 84 - -13.96% 6-10 Members 15.96% 66 1.79% 0.01% 175 0.01% -15.95% 11+ Members 18.44% 100 4.6% 0.00% 47 - -18.44% Municipality Aileu 17.27% 244 2.85% 0.00% 82 - -17.27% Ainaro 11.94% 332 2.43% 0.00% 63 - -11.94% Bobonaro 7.83% 211 2.52% 0.00% 79 - -7.83% Dili 19.12% 111 5.54% 0.07% 33 0.08% -19.05% Ermera 23.56% 302 2.81% 0.00% 49 - -23.56% Education Level No Education 18.90% 592 2.25% 0.02% 130 0.02% -18.88% Primary School 12.67% 341 2.36% 0.00% 92 - 12.67% Secondary and higher18

11.33% 267 2.29% 0.00% 84 - -11.33%

Any shock No shocks - - - 0.00% 37 - - At least 1 shock - - - 0.01% 269 0.01% - Hunger Level Little to no hunger 84.51% 1,012 1.48% 99.99% 305 0.01% +14.58% Moderate hunger 15.35% 185 1.48% 0.01% 1 0.01% -15.34% Severe hunger 0.15% 3 0.09% 0.00% 0 - -0.15%

While the household hunger scale questions above represent a measure of hunger in the month preceding the survey, both the baseline and endline surveys asked about food security during each month in the past year. Respondents were asked if in the past 11 months, there were any months during which their household did not have food to meet your family needs. Figure 6 below presents the frequency of “yes” responses to this question by month, comparing frequencies at baseline and endline.

Consistent with the hungry period in Timor-Leste described above, households reported the highest levels of hunger at both baseline and endline during January and February. While Figure 6 displays a sharp increase in hunger in January from 33 percent at baseline to 64 percent at endline and a sharp decrease in hunger in February from 32 percent at baseline to 13 percent at endline, the endline figures should be interpreted with caution considering the small number of households that reported hunger in any of these months at endline (12 households).

18 Secondary and higher includes Junior and Senior High School, University, and Vocational School.


Figure 6: Prevalence of hunger by month, baseline to endline

Note: Endline n = 12, Baseline n = 158

COVID-19: To understand the potential effects of COVID-19 on household hunger, the survey asked if the household’s food situation had changed in the past month compared to an average month or due to COVID-19. Ninety-eight percent of households said their food situation was the same as an average month and only one household said their food situation was worse. Seventy-nine percent of households said COVID-19 did not change their food situation and an additional ten percent said they had sufficient food, so the question of change was irrelevant. Ten percent mentioned facing restrictions in either buying food or selling produce, impacting their food situation. These quantitative findings are consistent with qualitative data, where farmers mentioned decreased income due to COVID-19 but did not indicate that they were unable to feed their families during the pandemic. USAID noted in a qualitative interview that the project’s food security monitoring showed positive adaption to the state of emergency.

PREVALENCE OF CHILDREN 6-23 MONTHS RECEIVING A MINIMUM ACCEPTABLE DIET

This indicator measures the proportion of children 6-23 months of age who receive a MAD, apart from breast milk. The MAD indicator measures both the minimum feeding frequency and minimum dietary diversity as appropriate for various age groups. If a child meets the minimum feeding frequency and minimum dietary diversity for their age group, and breast-feeding group and breastfeeding status, then they are considered to receive a MAD.

Minimum dietary diversity for breastfed children 6-23 months is defined as four or more food groups out of the following seven food groups:19

1. Grains, roots and tubers 2. Legumes and nuts 3. Dairy products (milk, yogurt, cheese) 4. Flesh foods (meat, fish, poultry and liver/organ meats) 5. Eggs 6. Vitamin-A rich fruits and vegetables 7. Other fruits and vegetables

19 World Health Organization. (2010). Indicators for assessing infant and young child feeding practices: Part II Measurement. http://apps.who.int/iris/bitstream/10665/44306/1/9789241599290_eng.pdf.

http://apps.who.int/iris/bitstream/10665/44306/1/9789241599290_eng.pdf


Minimum meal frequency for breastfed children is defined as two or more feedings of solid, semi-solid, or soft food for children six to eight months, and three or more feedings of solid, semi-solid or soft food for children 9-23 months. Minimum meal frequency for non-breastfed children is defined as four or more feedings of solid, semi-solid, soft food, or milk feeds for children 6-23 months. For non-breastfed children to receive a MAD, at least two of these feedings must be milk feeds.

Figure 7: Avansa beneficiary farmer displays cauliflower

Gabriela Leite Soares, SI Timor-Leste Team

At baseline, 41.0 percent of children 6-23 months received the MAD in the anticipated zone of influence. This increased by 5.83 percentage points to 46.13 percent at endline. This baseline to endline increase was consistent across most disaggregates, apart from children of respondents with a secondary or higher education, who experienced a 0.83 percentage point decline, and households with one to five members, who experienced a 5.4 percentage point decrease in MAD; however, these groups showed relatively high prevalence at baseline, so there was less room for improvement among these groups. At endline, the children of respondents with a primary school education had a higher prevalence of MAD compared with respondents with no education or higher education. When accounting for household size, children in households of six to ten members had lower prevalence of MAD while children in households of 11+ members had higher prevalence of MAD.

Changes in MAD were different across municipalities as well, with those closest to Dili showing the largest increases. Children of respondents who had not experienced a shock in the last year had a higher prevalence of MAD than children of respondents who had experienced a shock.

Table 13: Percentage of Children Receiving MAD




All Children 41.0% 285 3.45% 46.13% 86 5.45% +5.83% Gendered Household Type MF 40.89% 1 3.44% 46.13% 86 5.45% +5.24% FNM 0% 1 - 0% 0 0% - MNF 100% 283 - 0% 0 0% -





Household Size 1-5 Members 47.70% 72 6.76% 42.30% 14 10.40% -5.4% 6-10 Members 39.04% 173 4.49% 40.16% 50 7.69% +1.12% 11+ Members 37.99% 40 9.43% 62.08% 22 10.26% +24.09% Municipality Aileu 35.58% 58 6.82% 60.67% 22 6.06% +25.09% Ainaro 34.36% 86 6.00% 41.26% 27 6.31% +6.9% Bobonaro 45.08% 53 7.19% 32.81% 14 6.2% -12.27% Dili 40.74% 20 14.41% 81.27% 11 10.72% +40.53% Ermera 46.75% 68 7.41% 16.71% 12 10.72% -30.04% Education Level No Education 37.76% 149 4.97% 43.00% 36 7.72% +5.24% Primary School 45.32% 58 9.06% 51.09% 30 9.89% +5.78% Secondary and higher

45.28% 78 6.47% 44.45% 20 11.9% -0.83%

Child Age 6-11 months - - - 63.47% 28 6.7% - 12-17 months - - - 48.07% 36 10.31% - 18-23 months - - - 21.43% 22 9.76% - Hunger Little to no hunger 36.51% 250 3.57% 46.12% 85 5.46% +9.61% Moderate to severe hunger

61.09% 45 8.43% 100% 1 - +38.91%

Shocks Experienced shocks - - - 45.77% 78 5.71% - Did not experience shocks

- - - 49.77% 8 12.82% -

When disaggregated by the gender of the child, MAD increased in both girls and boys from baseline to endline, as seen in Figure 8. At both baseline and endline, girls had higher prevalence of MAD than boys. This is consistent with other research: a 2018 report commissioned by University Research Co. (URC), found that stunting, where children are substantially below height-for-age benchmarks, may be higher in boys than girls.20 The report noted that boys are likelier to “have slightly higher nutritional requirements than girls,” and are generally more mobile than girls. In Timor-Leste, according to the report, boys were breastfed for one month less than girls, on average. The URC report also found similar disparities in nutrition indicators across municipalities.

20 University Research Co. LLC. (2018). Addressing Stunting in Timor-Leste: An Assessment Report. Accessed at: https://www.urc-chs.com/sites/default/files/urc-Addressing-Stunting-Timor-Leste-Assessment-Report-1809.pdf.

https://www.urc-chs.com/sites/default/files/urc-Addressing-Stunting-Timor-Leste-Assessment-Report-1809.pdf

https://www.urc-chs.com/sites/default/files/urc-Addressing-Stunting-Timor-Leste-Assessment-Report-1809.pdf


Figure 8: Prevalence of children receiving a MAD, by gender

The overall increase in prevalence of children between 6-23 months receiving a MAD over time is also reflected in Avansa Agrikultura’s monitoring data, as shown for available survey years in Figure 9 below. Interestingly, the monitoring data show a marked increase in years three and four, followed by a decline between years four and five.

Figure 9: Comparison of prevalence of children 6-23 months receiving a MAD over time in Avansa Agrikultura’s monitoring data and SI’s reporting

The quantitative findings above are largely triangulated by qualitative PE data. While child nutrition was not a specific target of Avansa Agrikultura’s interventions, improving nutrition and dietary diversity was a broad project goal. However, Avansa Agrikultura senior staff admitted that some activities started relatively late and may have been less impactful because they did not have adequate time to take hold, including some interventions targeting child nutrition. In its sixth year, Avansa Agrikultura worked to introduce a cookbook and recipes for nutritious porridge and cakes for young children, but one farmer group in Ainaro noted that these foods are not likely to be continued since they were not something farmers ate and children did not enjoy the taste.

COVID-19: Of the 89 households with children in this age group (6-23 months), only three said that COVID-19 changed the types of food that their child ate. One mentioned that carrots and potatoes


were not available due to market closures. The other 86 households reported that their children either had sufficient food to eat or that COVID-19 did not change the food that the child ate.

MEAN NUMBER OF FOOD GROUPS CONSUMED BY WOMEN OF REPRODUCTIVE AGE

For this indicator, survey respondents were asked how often they consumed a range of food groups within the last 30 days. WRA were asked to indicate if they ate foods made from grains, white roots/tubers/plantains, pulses/nuts and seeds, milk and milk products, meat and poultry, fish and seafood, eggs, dark green leafy vegetables, vitamin A-rich fruits and vegetables, and other fruits and vegetables. The responses were then averaged to determine the mean number of food groups consumed by WRA.

The mean number of food groups consumed by WRA increased from 6.79 at baseline to 7.53 at endline. FNM households and households in Ainaro and Aileu all achieved gains larger than one food group from baseline to endline.

Mean number of food groups consumed by WRA increased the most among households with one to five members and the least among households with 11 or more members. Of the municipalities, households in Bobonaro experienced the smallest increase, at 0.33 food groups; however, Bobonaro had the highest mean number of food groups at baseline at 7.12. Households with secondary and higher education had the lowest mean at baseline (6.64) but increased by the most (0.98) to 7.62 food groups at endline.

Table 14: Mean Number of Food Groups for WRA




All Households 6.79 1,063 0.09 7.53 298 0.05 +0.74 Gendered Household Type MF 6.79 991 0.08 7.52 286 0.06 +0.73 FNM 6.76 64 0.40 7.81 12 0.08 +1.05 Household Size 1-5 Members 6.71 256 0.12 7.51 65 0.07 +0.8 6-10 Members 6.76 639 0.10 7.51 171 0.07 +0.75 11+ Members 7.01 168 0.21 7.59 62 0.10 +0.58 Municipality Aileu 6.40 63 0.35 7.42 86 0.04 +1.02 Ainaro 6.61 511 0.12 7.75 76 0.06 +1.14 Bobonaro 7.12 270 0.11 7.45 60 0.10 +0.33 Dili 6.87 149 0.23 7.64 31 0.06 +0.77 Ermera 6.45 70 0.27 7.38 45 0.16 +0.93 Education Level No Education 6.89 542 0.10 7.53 128 0.06 +0.64 Primary School 6.72 271 0.15 7.43 82 0.09 +0.71 Secondary and higher

6.64 250 0.14 7.62 88 0.08 +0.98

Hunger





Little to no hunger - - - 7.53 297 0.05

Moderate to severe hunger - - - 8.0 1 -

Shocks Experienced shocks - - - 7.54 274 0.05 -

Did not experience shocks

- - - 7.33 24 0.18 -

Note: The baseline value was previously reported as 4.45, where food groups consumed rarely in the past 30 days were not counted. At endline, the food groups questions were binary (yes/no); thus, the baseline value here is recalculated to include food groups rarely consumed to optimize comparability between baseline and endline.

Figure 10 below displays the proportion of WRA who consumed each food group at baseline and endline. The most frequently consumed food groups were grains/tubers and leafy greens at both baseline and endline. Endline values are the same or higher than baseline values for all food groups, with legumes increasing by the largest amount (31 percentage points).

Figure 10: Baseline-endline food group consumption among WRA

The quantitative findings presented above are largely triangulated by qualitative data collected as part of the final PE. Respondents from one of Avansa Agrikultura’s implementing partners discussed leading trainings with women to educate them on nutrition, adding additional food groups to their meals, and empowering them to make decisions on food consumption in their households. This specific training emphasized that women who are pregnant or breastfeeding need to eat first, before other members of the household, so they can support the child. Additionally, six farmer groups of 18 interviewed in five municipalities mentioned receiving nutrition training from Avansa Agrikultura. There was also at least one farmer group whose primary focus was growing food to eat and improve nutrition instead


of to sell. This group was majority-women and their motivation for starting the group was the identification of many malnourished children in their communities.

“We began to understand the importance of nutritional values and how it can support our daily activities.” – Nutrition-focused farmer group member on nutrition after receiving Avansa’s training

COVID-19: Like previous hunger and MAD indicators, the vast majority of the over 300 WRA surveyed reported that COVID-19 did not impact the food that they ate. Twenty women reported some change in food. The most frequent change, noted by 12 women, was difficulty buying or accessing food due to the state of emergency and shop closures.


NUMBER OF CO-MANAGEMENT/USER GROUPS FORMED AND ACTIVE

Table 15 displays the number of co-management or user groups formed and active at baseline and endline. Since at endline all households were a member of a farmer group as beneficiaries of Avansa Agrikultura, farming groups were excluded here from both the baseline and endline analysis, and we present values for this indicator disaggregated by group type.

Table 15: Community Group Participation

Group Type Baseline (2015) Endline (2020)



All Households Water 3% 1,200 2% 0.7% 306 0.5% -2.3% Forestry 7% 1,200 2% 3.3% 306 1.0% -3.7% Fisheries 9% 1,200 3% 0.7% 306 0.5% -8.3% Health 2% 1,200 1% 2.6% 306 0.9% +0.6% Credit 10% 1,200 3% 10.8% 306 1.8% +0.8% Women 2% 1,200 2% 0.3% 306 0.3% -1.7% Youth 0% 1,200 0% 0.0% 306 -- --

Note: Baseline value was previously reported as 12%. This value included farming groups, though farming groups have been omitted in this table as described above. Membership across all types of groups was relatively consistent from baseline to endline. The largest change was in fisheries group membership, which decreased from nine percent at baseline to about one percent at endline. This decrease may be explained in part by the endline sampling of only households that were members of farmer groups as Avansa Agrikultura beneficiaries. The most common group type was credit groups at both baseline (ten percent of households) and at endline (10.8 percent of households). None of the four MNF households reported belonging to a community group, and only one of the ten FNM households reported belonging to a community group (credit).


PERCENT OF HOUSEHOLDS OVERCOMING SHOCKS THROUGH SUSTAINABLE MEANS

Though not collected and reported at baseline, this indicator was adapted from the FTF Ability to Recover from Shocks & Stresses Index and intended to provide insight into Avansa Agrikultura’s goal of improving sustainability and resiliency in the target communities. Respondents were asked if their household experienced a variety of shocks in the last 12 months, such as too much/too little rain, disease/pest issues affecting crops, and illness or deaths in their family. They were then asked if these shocks impacted their economic situation or food consumption and how they coped with each shock.

Figure 11 displays the prevalence of shocks experienced across households at endline. The most common shock experienced was lack of rain, experienced by 42 percent of households (130 total), followed by pests affecting crops and too much rain.21 The least common shocks experienced were issues related to livestock inputs, losing land, and stealing of livestock and crops – all were experienced by only three households each. Among MNF households, the most common shock experienced was too little rain, at 74 percent, followed by too much rain, crop pests, and being unable to sell products. Among FNM households, the most common shock experienced was also too little rain, followed by crop pests and livestock disease.

Figure 11: Shock prevalence

21 Livestock disease was also prevalent. Further information on the swine flu outbreak can be found at https://www.thepigsite.com/articles/two-epidemics-threatening-timor-leste-covid-19-and-african-swine-fever and https://www.abc.net.au/news/rural/2020-07-07/coronavirus-is-helping-australia-fight-african-swine-fever/12427004.

https://www.thepigsite.com/articles/two-epidemics-threatening-timor-leste-covid-19-and-african-swine-fever

https://www.abc.net.au/news/rural/2020-07-07/coronavirus-is-helping-australia-fight-african-swine-fever/12427004


“We also have difficulty with access to water! So our farmers here are having a tougher time to grow diverse types of vegetables. And that makes us less competitive compared to Aileu and Ermera.” -Bobonaro beneficiary

Crop pests and challenges with water were brought up during PE qualitative interviews as well. Respondents in four out of the five municipalities mentioned that farmers struggle during the dry season or have difficulty accessing water. Avansa Agrikultura’s endline household survey data showed that only 18.2 percent of beneficiary households owned a water pump at endline, either motorized, auto, or other. Fifty percent of the sample owned at least one of the following mechanisms for water access: motorized water pump, irrigation package, water pump (auto), water pump (other), water tank, other irrigation, or plastic mini dam. Beneficiaries recommended in PE interviews that Avansa Agrikultura expand training to cover pesticide and pest management, farming during the rainy season, and farming during the dry season, indicating that these are all common shocks experienced that require new coping strategies. The inability to sell products, experienced by 20 percent of households, was mentioned as an impact of the COVID-19 state of emergency.

Figure 12: Plastic tunnels in Maubisse

Table 16 details the number and types of shocks experienced at endline by key disaggregates. Eighty-eight percent of households experienced some form of shock in the last 12 months; the mean number of shocks across all households was about two. Ainaro and Aileu experienced the greatest number of shocks, at around 2.75 shocks per household, while Bobonaro experienced the fewest at 0.86 shocks per household.

Table 16: Experience with Shocks

Disaggregate Endline (2020)

Estimate n Standard Error Did not experience shocks 11.98% 37 5.51% Experienced shocks 88.02% 269 5.51% Mean number of shocks 2.05 306 0.26 Types of Shocks No shock 11.03% 30 3.5% Economic shock 50.82% 136 5.15% Food shock 1.89% 5 0.87% Both shocks 36.26% 98 3.86% Gendered Household Type (mean number of shocks) MF 2.06 292 0.25



Estimate n Standard Error FNM 1.84 10 0.67 MNF 1.51 4 0.25 Household Size (mean number of shocks) 1-5 Members 1.75 84 0.38 6-10 Members 2.08 175 0.24 11+ Members 2.44 47 0.22 Municipality (mean number of shocks) Aileu 2.74 82 0.14 Ainaro 2.75 63 0.19 Bobonaro 0.86 79 0.10 Dili 2.08 33 0.42 Ermera 1.80 49 0.21 Education level (mean number of shocks) No Education 1.85 130 0.34 Primary School 2.14 92 0.21 Secondary and higher 2.24 84 0.25

Households were then asked how they coped with each of the top three shocks reported. These coping strategies were divided into either sustainable or unsustainable means, as detailed in Table 17.

Table 17: Coping Mechanisms

Sustainable Unsustainable

• Relied on income from seasonal work • Bartered for goods/services • Used money from savings accounts • Borrowed money or food from friend/relative • Purchased food/resources on credit • Used social mechanism (such as rotating credit)

• Sold land • Sold assets/livestock • Cut back on food consumption • Harvested immature crops • Pulled children from school to work

Figure 13 displays the breakdown of coping strategies among all households. A plurality of households used only sustainable coping mechanisms to deal with shocks reported (47 percent), followed by 31 percent using both sustainable and unsustainable coping mechanisms, and 17 percent using only unsustainable coping mechanisms.


Figure 13: Coping strategies among all households

Table 18 displays the coping strategies by gendered household type, education, and household size. Using only sustainable means was most common in households with 11 or more members and MF households. Using only unsustainable means was most common in households with one to five members. Households in Aileu had the lowest levels of using only unsustainable means and over 50 percent of households in Bobonaro and Ermera used only sustainable means, however sample sizes within each coping category across disaggregate categories are relatively low and should be interpreted with caution.

Table 18: Coping Strategy Disaggregates

Disaggregate Unsustainable means only

Sustainable means only Both Other

Estimate n Estimate n Estimate n Estimate n All Households 17.48% 239 47.17% 239 31.13% 239 4.22% 239 Gendered Household Type MF 16.53% 38 47.85% 108 31.23% 73 4.4% 10 FNM 32.64% 2 34.13% 2 33.23% 2 - 0 MNF 51.26% 2 26.54% 1 22.2% 1 - 0 Household Size 1-5 Members 29.06% 18 47.28% 28 22.08% 15 1.58% 1 6-10 Members 15.68% 21 43.34% 56 35.55% 49 5.44% 7 11+ Members 6.53% 3 58.96% 27 30.32% 12 4.18% 2 Municipality Aileu 3.63% 2 46.56% 30 49.81% 31 - 0 Ainaro 27.50% 18 32.57% 20 28.75% 18 11.18% 7 Bobonaro 20.20% 9 66.40% 27 13.40% 7 - 0 Dili 24.37% 6 39.16% 10 24.70% 8 11.77% 3 Ermera 16.24% 7 55.43% 24 28.33% 12 - 0 Education No Education 24.62% 23 49.35% 46 21.79% 23 4.23% 4 Primary School 10.08% 8 45.65% 35 40.65% 31 3.63% 3 Secondary and higher

15.94% 11 45.81% 30 33.35% 22 4.9% 3


Figure 14 displays how households coped with the four most commonly cited severe shocks: too much rain, too little rain, diseased crops, and pest issues with crops. Sustainable means are shown in blue, unsustainable means are shown in red, and other mechanisms are shown in light blue. The most used coping strategies were using savings and using income from seasonal work. These findings are consistent with the PE qualitative data, where 16 out of 18 farmer groups indicated an increase in income from farming. One farmer in Bobonaro went further to explain the effects of increased income on shock exposure, saying “farming and livestock help us to secure our income in case we experienced crop failure.”

COVID-19: Forty-eight percent of households (128 total) said that the shocks they experienced were exacerbated by COVID-19. Almost all households in Ainaro (89 percent) reported feeling an added impact of COVID-19 on the shocks they experienced, whereas Bobonaro households had a relatively lower level (21 percent).

“During COVID-19 our income decreased by 50% because we cannot sell our product in the market in Dili, despite our production went as normal.” – Bobonaro farmer

Households whose shocks were exacerbated by COVID-19 were then asked to explain the effects of COVID-19 on their economic or food situation in an open-ended survey question. Households most frequently reported that they either had sufficient food to feed their family (about one-third); experienced demand-side issues, such as price increases for food and restricted access to grocery stores (about one-fifth); and experienced supply-side issues, such as being unable to sell their products and generate income to buy necessities (about three-fourths). These COVID-19-related findings are triangulated in the qualitative PE data: nine out of 16 farmer interviews mentioned losing income during COVID-19 and seven mentioned decreased demand for produce.


Figure 14: Percent of households using various coping mechanisms by type of shock


PERCENT OF WOMEN REPORTING ADEQUACY ON 80% OF WEAI DOMAINS

The women’s empowerment in agriculture index (WEAI) is a measure originally developed to track changes in women’s empowerment and inclusion in the agriculture sector that occur as a result of FTF programming. The WEAI is administered to the primary adult male decisionmaker and the primary adult female decisionmaker in each household to compare empowerment of men and women. The primary adult male and female decisionmakers self-identify as the man or woman who makes more social and economic decisions than other men or women in the household. The WEAI is collected via multiple survey modules across five domains that are used to calculate two sub-indices that make up the WEAI. Through this process, indicators are used to measure whether an individual reaches a certain threshold for that indicator, defined as achieving adequacy.22

The data collection and analysis methodology for the WEAI is time intensive and complex and this indicator was not collected at baseline; therefore rather than collecting the full WEAI at endline, we used an abbreviated set of WEAI questions to gain insight into women’s empowerment in agriculture at endline.

Table 19: WEAI domains, indicators, and definitions of adequacy

Domain Indicator WEAI Definition of Adequacy Avansa Agrikultura Definition of Adequacy

Production Input in productive decisions

Adequate if, for at least one activity, an individual decides alone; OR participates and has input into some, or most or all decisions regarding the activity; OR someone else decides but feels she/he could decide to a medium or high extent if she/he wanted to

Adequate if primary female decisionmaker reports input into some, or most or all decisions regarding income generation activities (asked in aggregate rather than by activity)

Resources

Ownership of assets

Adequate if individual owns—alone or jointly—at least one large asset or at least two small asset types

N/A – did not ask due to time constraints

Access to and input into decisions on credit

Adequate if individual—alone or jointly—makes decisions about at least one source of credit accessed by her household

Adequate if primary female decisionmaker reports input into some, or most or all decisions regarding borrowing money and the use of that money (asked in aggregate rather than by loan type)

Income Control over use of income

Adequate if individual participates in and has input in some, most, or all decisions about income generated from an activity; OR she/he makes decisions, has input in decisions, or feels she/he could make decisions (if desired) about employment or major household expenditures (excluding minor expenditures)

Adequate if primary female decisionmaker reports input into some, or most or all decisions regarding the use of income from income generating activities (asked in aggregate rather than by activity or loan)

Leadership Group membership

Adequate if individual is an active member of at least one group

Adequate if individual is an active member of at least one group

22 For more information, please refer to the Instructional Guide for the Abbreviated Women’s Empowerment in Agriculture Index.

http://www.ifpri.org/publication/instructional-guide-abbreviated-womens-empowerment-agriculture-index-weai




Domain Indicator WEAI Definition of Adequacy Avansa Agrikultura Definition of Adequacy

Time Workload Adequate if individual worked less than 10.5 hours during the previous day

Adequate if individual worked less than 10.5 hours during the previous day including employment, business, domestic work, cooking, etc. (asked in one question rather than the full WEAI time use module in 15- or 30-minute increments for preceding 24 hour period)

Table 20 below summarizes overall adequacy. Overall, 98.5 percent of women reported adequacy on 80 percent of WEAI domains. The mean number of domains (out of five) where a woman was determined to be adequate was 4.83.

Table 20: WEAI Adequacy


Estimate n

All Households

Mean # of Domains 4.83 65

Overall Adequacy 98.51% 65

Gendered Household Type

MF 98.49% 63

FNM 100% 1

Municipality

Aileu 96.64% 30

Ainaro 100% 6

Bobonaro 100% 6

Dili 100% 7

Ermera 100% 16

Table 21 presents a more granular breakdown of responses in each domain. Though empowerment was consistently high across all domains, as displayed in Figure 15 below, there was more variation in responses within each domain. In the production and income categories, only about one-fourth of women reported having input into most or all decisions, with a much greater proportion having input into some decisions. Under resources, slightly more women had input into most or all decisions, with 42.14 percent having input to most or all decisions on when to borrow money, and 30.34 percent having input into most or all decisions on how to use borrowed money.

Table 21: WEAI Adequacy by Domain


Estimate n Production Overall Adequacy 97.1% 243 No decision 0.39% 1 No input or input in few 2.85% 7 Input into some decisions 69.33% 169



Estimate n Input into most or all 27.43% 66 Income Overall Adequacy 99.2% 243 No decision 0.73% 2 No input or input in few 0.79% 2 Input into some decisions 73.26% 175 Input into most or all 25.22% 64 Resources Overall Adequacy 94.7% 76 Borrowing

No decision 1.24% 1 No input or input in few 4.05% 3 Input into some decisions 52.57% 40 Input into most or all 42.14% 32

Money Use No decision 1.24% 1 No input or input in few 1.26% 1 Input into some decisions 67.16% 51 Input into most or all 30.34% 23

Leadership Overall Adequacy 99.2% 240 Time Overall Adequacy 95.8% 263 Average Hours Working 6.77 263

Figure 15 presents a visual breakdown of the four decision-related components of the indicator. As described above, the highest proportion of women with input into most or all decisions was in the borrowing domain (42 percent).

Figure 15: Women's input into household decisions


Figure 16: Avansa beneficiary poses with crops

Women were a key target of Avansa Agrikultura’s interventions. Some of the women-focused interventions included women-only farmer groups and women-only savings and loan groups. In qualitative interviews from the final PE, seven stakeholders including four Avansa Agrikultura staff, two farmer groups, and a government stakeholder noted the high impact of financial training on women; according to a farmer group head in Bobonaro, “finance literacy benefit women the most, because women are the one who keep the money.” In general, beneficiary groups frequently discussed the theme of “becoming independent” as a result of Avansa Agrikultura interventions. Just over one-fourth of 44 beneficiary groups mentioned becoming independent or more independent as a result of Avansa Agrikultura interventions. The transformation was more pronounced among groups with women, with ten of 29 groups reporting that the project’s activities had enabled them to become more independent.

“The training that I participated through Avansa enabled me to gain new practical skills for my business in growing vegetables. As a result, I am able to support my family even after the passing of my husband. Prior to joining this activity, I struggled to support my family financially… I am [now] able to send my children to higher education in Dili and build this house.” – Aileu farmer

To assess the extent to which a household’s financial situation differed based on a woman’s input into household decisions, we looked at both expenditures and savings across the top two categories of decision-making, as the number of women falling in the two lowest categories is too low to reliably examine trends. As displayed in Figure 17, households of women who had input into most or all decisions regarding production activities and the use of income from these activities had higher daily per capita expenditure than households of women with input into some decisions. This trend was the inverse for decisions in the resources domain of borrowing and money use: households of women who had input into most or all decisions regarding whether to borrow money and how to use it had lower daily per capita expenditure than households of women with input into some decisions. This overall trend was the same with savings and assets as displayed in Figure 18, where households of women with higher input into decisions related to production activities and the use of income from these activities had higher total assets, and households of women with lower input into decisions related to borrowing money and the use of that money had lower total assets.23

23 The figures used in Figure 18 include all asset items asked at endline, and align with the analysis presented in Annex C.


Figure 17: Daily per capita expenditure by woman’s input into household decisions

Figure 18: Household savings and/or investment in productive assets by woman’s input into household decisions


CONCLUSIONS

FINANCIAL STABILITY

The agriculture, forestry and fishing GDP decreased from baseline to endline but trends upward after 2017, suggesting growth. The agriculture, forestry and fishing GDP decreased by 4.7 percent from $300.2 million at baseline (2013) to $286.1 million at endline (2019). Though Avansa Agrikultura begin in 2015, the 2013 GDP figure was used as an initial baseline due to the lag in national GDP reporting. Considering only the timeframe of Avansa Agrikultura implementation (2015-2020), GDP is much more stable and even suggests growth in later years, trending from $283 million in 2015 down to $271 million in 2017, but then up to $279 million in 2018 and $286 million in 2019.

Household savings and investment in productive assets increased from baseline to endline. When considering only productive assets that were asked at both baseline and endline, household savings and investment in productive assets increased by 7.5 percent from $1,927.01 at baseline to $2,071.32 at endline. Much of this increase was driven by a large increase in savings, while the value of owned productive assets decreased from baseline to endline. Interestingly, while savings increased by 400 percent or more among four of the five municipalities, there was no change in savings among Dili households and, similarly, Dili showed the largest decrease in productive assets; these differential outcomes in Dili may be due in part to a lack of retention of Dili-based farmers, discussed in the final PE. When including the new productive assets that were added to the endline survey, household savings and investment in productive assets was much higher at endline, increasing by 32.7 percent from $1,927.01 at baseline to $2,557.00 at endline. Given that a majority of the 19 additional items added to the questionnaire were agriculture items, it is possible that ownership of these items is new relative to baseline and related to Avansa Agrikultura’s programming; however, given that households were not asked if they owned these items at baseline, we cannot conclude that savings and assets increased by this larger margin. Rather, it is likely that the “true" increase lies between 7.5 and 32.7 percent. There is evidence that these additional savings may be of use to households as a means to cope with shocks as households frequently drew on savings to cope with shocks, especially shocks related to crop pests or disease, and rain. Though quantitative data show little change in group membership from baseline to endline, respondents of the final PE discussed the success of savings and loans groups through Avansa Agrikultura which may be related to the large increase in savings among beneficiary households.

“Avansa implement[s] complete value chains. Starting from establishing farmers’ group, then train them on how to increase their production, link them to market, encouraging women and youth in doing business. In addition, the nutritional product also helps farmer not only to increase their production to sell in the market but also to consume a nutritional diets. All these intervention[s] contribute to improve income.” – Avansa Agrikultura municipal coordinator

Daily per capita expenditure decreased slightly from baseline to endline. There was a slight decrease in daily per capita expenditure from $1.63 at baseline to $1.53 at endline (in 2015 prices). However, expenditures differed greatly across types: average food expenditure decreased by $0.32, non-food items purchased over the past month decreased by $0.07, and non-food items purchased over the past year increased by $0.30. This relatively large decrease in food expenditures may be due in part to the fact that Avansa Agrikultura heavily encouraged farmers to set aside portions of food for consumption instead of sale. With increased production at farms and more consumption of their own food, it is likely that farmers spent less on food purchases. This encouragement of crop consumption is reflected in the substantial improvements in the hunger and nutrition indicators and was triangulated by PE findings. Changes in expenditure overall differed substantially by municipality:


households in Aileu and Bobonaro showed increased per capita expenditures, ($0.19 and $0.55 increases, respectively) while households in Ainaro, Dili and Ermera showed decreases ($0.19, $0.34 and $0.77 decreases, respectively). Aileu and Bobonaro had the lowest per capita expenditures at baseline, so it is possible that households in these municipalities had the most to gain from Avansa Agrikultura interventions which contributed to the larger change in these areas.

HUNGER & NUTRITION

Food security improved substantially across all demographics from baseline to endline. Prevalence of households with moderate to severe hunger decreased dramatically from 15.49 percent among the general population at baseline to 0.01 percent among Avansa Agrikultura beneficiary households at endline. Though it is likely that the differing month of the survey, November at baseline compared to July at endline, accounts for some portion of this large change, it is reasonable to conclude that prevalence of hunger decreased substantially from 2015 to 2020. Though the survey design limits conclusions of attribution, the quantitative results presented in this report combined with the final PE results suggest that Avansa Agrikultura may have played a role in this change: qualitative interview respondents of the PE discussed a shift from cultivating crops only for sale to cultivating crops for both sale and household consumption.

“Before we didn’t consume lots of vegetable since we have to buy from the local market but now since we grow ourselves we can consume and don’t need to buy from the local market anymore.”– Ainaro Farmer

Nutrition improved marginally from baseline to endline, though outcomes varied across demographics. While the nutrition indicators did not show as large a change from baseline to endline as household hunger, there were more marginal improvements in both prevalence of children receiving a diet of minimum diversity and mean number of food groups consumed by WRA. Overall, the prevalence of children between six and 23 months of age receiving a MAD increased from 41.0 percent at baseline to 46.1 percent at endline. However, outcomes differed across municipalities; Dili and Aileu showed substantial increases, Ainaro showed a more marginal increase, and Bobonaro and Ermera showed substantial decreases. These differential effects may be due in part to households closest to Dili having better access to healthier, more diverse food. The mean number of food groups consumed by WRA increased as well from 6.79 food groups at baseline to 7.53 food groups at endline of eight food groups total. Unlike the MAD indicator, increases in food groups consumed was consistent across all disaggregates. Among food groups, the largest increases in frequency of consumption were legumes (31 percentage point increase) and eggs (17 percentage point increase). Respondents of the final PE discussed the benefits of various Avansa Agrikultura trainings on nutrition, adding food groups to their meals, and empowering women to make decisions on food consumption in the household. Respondents referenced at least one women’s farmer group that focused primarily on the nutrition aspect of farming, driven by the identification of malnourished children in their communities.


Group membership increased substantially from baseline to endline. At baseline, 12 percent of households in the general population in the five original Avansa Agrikultura municipalities were a part of a community group; at endline, 100 percent of households were a member of at least a farmer group through Avansa Agrikultura. Membership in Avansa Agrikultura farmer groups may have contributed to many of the positive outcomes described above and in the final PE report.

Though most households incorporated sustainable means to cope with shocks, only about half of households experiencing shocks relied on sustainable coping mechanisms only. A majority of households (88 percent) experienced a shock in the last year. Interestingly, 50.8


percent of households reported a shock that affected the household’s economic situation only, while only 1.9 percent reported a shock that affected the household’s food situation only; 36.3 percent of households reported a shock that affected both the economic and food situation. The most frequent shocks experienced were related to too much or too little rain, or crop disease, or pests. While a majority of households (78.3 percent) incorporated sustainable means to their coping strategy, only about half (47 percent) of households experiencing shocks relied on sustainable means only. When dealing with too much or too little rain, households most commonly relied on the sustainable methods using of income from seasonal work, and to a lesser extent using savings and borrowing food. The most commonly used unsustainable method was harvesting immature crops (seven percent) followed by pulling children from school (three percent). When dealing with disease or pests in crops, cutting back on food and selling assets or livestock were more commonly used in addition to income from seasonal work and savings, though the number of households who experienced these crop-related shocks was small. The use of unsustainable means differed across municipality: Ainaro had the highest proportion of households relying on unsustainable means only (27.5 percent) compared to only 3.6 percent in Aileu, though the number of households in each of these disaggregate categories is low as well. As evidenced in the financial stability section above, Avansa Agrikultura’s savings and loan groups may have played a role in increasing savings that households then relied on to cope with shocks.

There was a high degree of input to household financial decision-making among women at endline. Women showed a high degree of financial empowerment in the household at endline, with 98.5 percent of women achieving adequacy on 80 percent of the WEAI domains of production, resources, income, leadership, and time. Though empowerment overall was high, there was variation in the extent to which women had input into decisions: in the production and income domains, only about one-fourth of women had input into most or all decisions while the majority had input into some decisions, whereas in the resources domain, about 42 percent of women had input into most or all decisions with regard to borrowing money and 30 percent had input into most or all decisions with regard to using borrowed money. Though this indicator was not collected at baseline for comparison, results of the quantitative data combined with the qualitative data in the final PE suggest that women-focused Avansa Agrikultura interventions, especially those related to financial training and savings and loans, may have contributed to the high degree of empowerment seen at endline.


ANNEX A: SUMMARY TABLES BY GENDERED HOUSEHOLD TYPE The following set of tables summarizes values presented in the body of the report to facilitate holistic comparison of all indicators across gendered household types.

Table 22: Gendered Household Differences across indicators




MF Households % increase in household savings and/or investment in productive assets

$1,990.36 1,133 $187.67 $2,021.41 292 $178.51 +$31.05 +1.56%

Daily per capita expenditure $1.63 1,133 $0.08 $1.48 292 $0.09 -$0.15

Prevalence of households with moderate to severe hunger

15.77% 1,133 1.53% 0.01% 292 0.01% -15.76%

Prevalence of children receiving a MAD 40.89% 1 3.44% 46.13% 86 5.45% +5.24%

Mean # of food groups consumed by WRA 6.79 991 0.08 7.52 286 0.06 +0.73

% of households overcoming shocks through sustainable means

- - - 47.85% 108 4.59% -

% of women reporting adequacy on 80% of WEAI domains

- - - 98.49% 64 1.1% -

FNM Households % increase in household savings and/or investment in productive assets

$900.62 40 $156.22 $3,950.52 10 $745.56 +$3,049.90 +338.64%

Daily per capita expenditure $1.32 40 $0.30 $1.76 10 $0.27 +$0.44


4.53% 40 3.50% 0.00% 10 - -4.53%

Prevalence of children receiving a MAD 0% 1 - 0% 0 0% -



- - - 34.13% 2 19.54% -


- - - 100% 1 - -

MNF Households





% increase in household savings and/or investment in productive assets

$846.28 27 $207.99 $787.34 4 $129.37 -$58.94 +6.96%



14.00% 27 6.26% 0.00% 4 - -14.00%

Prevalence of children receiving a MAD 100% 283 - 0% 0 0% -

Mean # of food groups consumed by WRA 7.85 8 14.8% - - - -


- - - 26.54% 1 22.88% -


ANNEX B: SUMMARY TABLES BY MUNICIPALITY The following set of tables summarizes values presented in the body of the report to facilitate holistic comparison of all indicators across municipalities.




Aileu % increase in household savings and/or investment in productive assets

$1,583.62 244 $179.42 $2,037.29 82 $312.46 +$1,453.67 +91.79%



17.27% 244 2.85% 0.00% 82 - -17.27%




- - - 46.56% 30 5.49% -


- - - 96.64% 30 96.64% -

Ainaro % increase in household savings and/or investment in productive assets

$1,487.69 332 $141.27 $2,233.22 63 $551.63 +$745.53 +50.11%

Daily per capita expenditure $1.53 332 $0.10 $1.34 63 $0.11 -$0.19


11.94% 332 2.43% 0.00% 63 - -11.94%




- - - 32.57% 20 8.75% -


- - - 100% 6 - -

Bobonaro % increase in household savings and/or investment in productive assets

$2,441.43 211 $275.53 $2,362.79 79 $160.44 -$78.64 -3.25%



7.83% 211 2.52% 0.00% 79 - -7.83%

Prevalence of children receiving a MAD 45.08% 53 7.19% 32.81% 14 6.2% -12.27%







- - - 66.40% 27 10.2% -


- - - 100% 6 - -

Dili % increase in household savings and/or investment in productive assets

$4,137.23 111 $1,299.58 $2,192.56 33 $335.59 -$1,944.67 -47.00%



19.12% 111 5.54% 0.07% 33 0.08% -19.05%




- - - 39.16% 10 6.13% -


- - - 100% 7 - -

Ermera % increase in household savings and/or investment in productive assets

$1,392.87 302 $165.93 $1,416.65 49 $278.57 +$23.77 +1.70%



23.56% 302 2.81% 0.00% 49 - -23.56%

Prevalence of children receiving a MAD 46.75% 68 7.41% 16.71% 12 10.72% -30.04%



- - - 55.43% 24 5.91% -


- - - 100% 16 - -


ANNEX C: SUPPLEMENTARY DATA TABLES – SAVINGS & PRODUCTIVE ASSETS Table 23 provides an overview of all productive assets included in the analysis of the percent increase in household savings and/or investment in productive assets indicator. The column titled “New at Endline?” is used to denote items that were not included in the baseline survey and were newly added to the endline survey. The figures for this indicator included in the report body do not include the items that were new at endline; the tables in this section that follow present values for this indicator including these 19 new items in the analysis.

Table 23: Productive assets by analysis category: Baseline and endline

ANALYSIS CATEGORY ITEM NEW AT ENDLINE?

Livestock

Buffalo Cattle Sheep Goats Pigs Chicken Duck/Geese/Other Poultry Horses Fish - Mujair YES Fish - Lele YES Fish - Mas YES Fish - Nila YES

Household durables

Fridge Stove Washing Machine Sewing Machine Generator Computer Solar Panel Mobile Phone

Transport

Truck or pickup Car or minivan Motor Bike Bicycle Canoe or Boat Boat Engine Tiga Roda YES

Fishing Fishpond Fishing net

Farm equipment

Motorized rice mill Motorized rice thresher Rice weeder Motorized maize sheller Motorized maize grinder Hand coffee pulper


ANALYSIS CATEGORY ITEM NEW AT ENDLINE?

Motorized coffee pulper Hand-tractor Large tractor Motorized water pump Back pack sprayer Plough or harrow pulled by tractor Plough pulled by oxen/buffalo Push cart with wheels Ox cart Plastic mulch (m2) YES Plastic mulch (roll/packet) YES Plastic tunnels (m2) YES Netting (m2) YES Plastic tunnel frame (packet, frame and plastic)

YES

Mini-tiller YES Wheelbarrow YES Other tools (shovel, machete, etc.) YES Irrigation package YES Water pump (auto) YES Water pump (other auto) YES Water tank YES Other irrigation YES Plastik mini damn YES

Table 24: Household savings and/or investment in productive assets – 2015 prices




USD Percentage

All Households $1,927.01 1,200 $177.58 $2,557.00 306 $194.53 $629.99 +32.7% Gendered Household Type MF $1,990.36 1,133 $187.67 $2,507.78 292 $207.29 $517.42 +26.0% FNM $900.62 40 $156.22 $4,338.28 10 $850.59 $3,437.66 +381.7% MNF $846.28 27 $207.99 $1,485.57 4 $74.01 $639.29 +75.5% Household Size 1-5 Members $1,706.32 434 $134.73 $2,693.34 84 $521.03 $987.02 +57.8% 6-10 Members $2,000.40 666 $254.70 $2,408.75 175 $204.43 $408.35 +20.4% 11+ Members $2,314.00 100 $420.94 $2,878.23 47 $446.09 $564.23 +24.4% Municipality Aileu $1,583.62 244 $179.42 $2,737.49 82 $355.38 $1,153.87 +72.9% Ainaro $1,487.69 332 $141.27 $2,720.10 63 $488.93 $1,232.41 +82.8% Bobonaro $2,441.43 211 $275.53 $2,887.79 79 $435.31 $446.36 +18.3% Dili $4,137.23 111 $1,299.58 $2,663.05 33 $344.36 -$1,474.18 -35.6% Ermera $1,392.87 302 $165.93 $1,511.66 49 $296.25 $118.79 8.5% Education of Primary Respondent





USD Percentage

No Education $1,931.12 592 $166.03 $2,451.14 130 $264.60 $520.02 +26.9% Primary School $2,056.91 341 $425.31 $2,026.98 92 $293.21 -$29.93 -1.5% Secondary and higher

$1,749.28 267 $137.61 $3,308.06 84 $260.32 $1,558.78 +89.1%

Any Shock No shocks - - - $2,447.15 37 $499.77 - - One or more shocks

- - - $2,567.86 269 $199.19 - -

Note: Baseline value was previously reported as $2,024. However, this figure was revised after finalization of the baseline report to remove a small number of extreme outliers. Though $2,024 appeared in the baseline report, the correct baseline value is $1,927.01.

Table 25: Value of savings and productive assets by asset type


Estimate Percent of Assets Estimate Percent of Assets

Savings $133.62 6.93% $716.28 28.0% Cash $50.16 3.60% $301.22 21.11% BNCTL Government Bank $26.59 0.31% $64.65 1.81% UBSP (Savings and loan group)

$1.27 0.11% $96.47 7.03%

Moris Rasik $8.78 0.28% $14.64 0.81% Other bank $4.67 0.30% $20.10 0.52% Gold, silver, or other precious metals

$4.39 0.26% $140.03 6.17%

Jewelry $8.73 0.36% $6.09 0.84% Kaebauk - - $15.60 0.87% Other $1.46 0.09% $0.00 0.00% Loans $27.56 2.34% $57.48 3.05%

Productive Assets $1,793.39 93.07% $1,840.72 72.0% Fishing $64.04 3.47% $27.63 0.92% Livestock $1,152.14 62.90% $513.02 20.66% Household durables $109.72 12.94% $138.22 9.93% Transport $305.05 7.55% $630.97 14.83% Farm Equipment $162.42 5.49% $530.87 18.05%

Transfers $84.69 - $39.52 - Cash $58.38 - $18.74 1.65% In-kind $26.31 - $20.78 2.72%

Table 26: Savings by Disaggregate


Estimate n Estimate n USD Percent Gendered Household Type MF $136.40 1,133 $706.36 292 $569.96 +417.9% FNM $65.29 40 $1,214.29 10 $1,149.00 +1759.8%



Estimate n Estimate n USD Percent MNF $136.02 27 $123.00 4 -$13.02 -9.6% Municipality Aileu $42.18 244 $580.95 82 $538.77 +1277.3% Ainaro $160.60 332 $894.89 63 $734.29 +457.2% Bobonaro $107.32 211 $917.94 79 $810.62 +755.3% Dili $371.48 111 $386.32 33 $14.84 +4.0% Ermera $94.46 302 $610.29 46 $515.83 +546.1%

Table 27: Productive Assets by Disaggregate


Estimate n Estimate n USD Percent Gendered Household Type MF $1,853.96 1,133 $1,801.42 292 -$52.54 -2.8% FNM $835.34 40 $3,123.98 10 $2,288.64 +274.0% MNF $710.26 27 $1,362.57 4 $652.31 +91.8% Municipality Aileu $1,541.45 244 $2,156.55 82 $615.10 +39.9% Ainaro $1,327.09 332 $1,825.22 63 $498.13 +37.5% Bobonaro $2,334.11 211 $1,969.85 79 -$364.26 -15.6% Dili $3,765.75 111 $2,276.73 33 -$1,489.02 -39.5% Ermera $1,298.42 302 $901.38 49 -$397.04 -30.6%

Figure 19: Value of assets by range class


ANNEX D: SUPPLEMENTARY DATA TABLES – SIX MUNICIPALITIES Whereas data presented in the body of the report includes only the five original Avansa Agrikultura municipalities (Aileu, Ainaro, Bobonaro, Dili, and Ermera), the tables in this section present data for all six current municipalities, including the five listed previously and Liquiçá.

SAVINGS & ASSETS

Table 28: Productive Asset Value (All Municipalities)




USD Percentage

All Households

$1,927.01 1,200 $177.58 $2,310.07 331 $272.07 +$383.06 +19.88%

Gendered Household Type MF $1,990.36 1,133 $187.67 $2,274.84 317 $285.75 +$284.48 +14.29% FNM $900.62 40 $156.22 $3,950.52 10 $744.65 +$3,049.90 +338.64% MNF $846.28 27 $207.99 $787.34 4 $129.21 -$58.94 -6.96% Household Size 1-5 Members $1,706.32 434 $134.73 $2,223.29 88 $384.12 +$516.97 +30.30% 6-10 Members

$2,000.40 666 $254.70 $2,077.96 189 $257.64 +$77.56 +3.88%

11+ Members

$2,314.00 100 $420.94 $3,283.20 54 $898.36 +$969.20 +41.88%

Municipality Aileu $1,583.62 244 $179.42 $2,037.29 82 $312.07 +$453.67 +28.65% Ainaro $1,487.69 332 $141.27 $2,233.22 63 $550.96 +$745.53 +50.11% Bobonaro $2,441.43 211 $275.53 $2,362.79 79 $160.24 -$78.64 -3.22% Dili $4,137.23 111 $1,299.58 $2,192.56 33 $335.18 -$1,944.67 -47.00% Ermera $1,392.87 302 $165.93 $1,416.65 49 $278.23 +$23.78 +1.71% Liquiçá - - - $5,163.41 25 $2,177.09 - - Education of Primary Respondent No Education $1,931.12 592 $166.03 $2,131.97 139 $242.71 +$200.85 +10.40% Primary School

$2,056.91 341 $425.31 $2,185.36 101 $651.04 +$128.45 +6.24%

Secondary and higher

$1,749.28 267 $137.61 $2,720.97 91 $249.68 +$971.69 +55.55%

Any Shock No shocks - - - $1,692.37 38 $150.56 - - One or more shocks

- - - $2,389.05 293 $313.66 - -


PER CAPITA EXPENDITURE

Table 29: Per Capita Expenditure (All Municipalities)




USD

All Households $1.63 1,200 $0.07 $1.51 331 $0.10 -$0.12 Gendered Household Type MF $1.63 1,133 $0.08 $1.45 317 $0.08 -$0.18 FNM $1.32 40 $0.30 $1.76 10 $0.27 +$0.44 MNF $2.63 27 $0.48 $5.84 4 $1.94 +3.21 Household Size 1-5 Members $2.16 434 $0.15 $2.29 88 $0.27 +$0.12 6-10 Members $1.41 666 $0.08 $1.33 189 $0.05 -$0.07 11+ Members $1.00 100 $0.09 $0.88 54 $0.06 -$0.11 Municipality Aileu $1.44 244 $0.06 $1.63 82 $0.28 +$0.19 Ainaro $1.53 332 $0.10 $1.34 63 $0.11 -$0.19 Bobonaro $1.29 211 $0.09 $1.84 79 $0.05 +$0.55 Dili $1.68 111 $0.22 $1.34 33 $0.12 -$0.35 Ermera $2.11 302 $0.19 $1.34 49 $0.11 -$0.77 Liquiçá - - - $1.14 25 $10.68 - Education of Primary Respondent No Education $1.57 592 $0.10 $1.62 139 $0.20 +$0.04 Primary School $1.57 341 $0.10 $1.32 101 $0.09 -$0.25 Secondary and higher

$1.86 267 $0.16 $1.56 91 $0.09

-$0.30

Any Shock No shocks - - - $1.65 38 $0.16 - At least 1 shock - - - $1.49 293 $0.10 -


HUNGER

Table 30: Hunger Prevalence by Disaggregate (All Municipalities)




All Households 15.49% 1,200 0.01% 0.58% 331 0.42% -13.91% Gendered Household Type MF 15.77% 1,133 1.53% 0.6% 317 0.43% -15.17% FNM 4.53% 40 3.50% 0.0% 10 - -4.53% MNF 14.0% 27 6.26% 0.0% 4 - -14.0% Household Size 1-5 Members 13.96% 434 2.1% 0.0% 88 - -13.96% 6-10 Members 15.96% 66 1.79% 0.51% 189 0.51% -15.46% 11+ Members 18.44% 100 4.6% 1.77% 54 1.74% -16.67% Municipality Aileu 17.27% 244 2.85% 0.0% 82 - -17.27% Ainaro 11.94% 332 2.43% 0.0% 63 - -11.94% Bobonaro 7.83% 211 2.52% 0.0% 79 - -7.83% Dili 19.12% 111 5.54% 0.07% 33 0.08% -19.04% Ermera 23.56% 302 2.81% 0.0% 49 - -23.56% Liquiçá - - - 7.41% 25 2.79% - Education Level No Education 18.90% 592 2.25% 1.39% 139 1.03% -17.51% Primary School 12.67% 341 2.36% 0.0% 101 - -12.67% Secondary and higher

11.33% 267 2.29% 0.0% 91 - -11.33%

Any shock No shocks - - - 0.0% 38 - - At least 1 shock - - - 0.65% 293 0.47% - Hunger Level Little to no hunger 84.51% 1,012 1.48% 99.42% 328 0.42% +14.91% Moderate hunger 15.35% 185 1.48% 0.58% 3 0.42% -14.77% Severe hunger 0.15% 3 0.09% 0.0% 0 - -0.15%


MAD

Table 31: MAD Disaggregates (All Municipalities)




All Households 41.0% 285 3.45% 48.07% 91 5.68% +7.07% Gendered Household Type MF 40.89% 1 3.44% 48.07% 91 5.68% +7.18% FNM - 0 - - 0 - - MNF 100% 113 - - 0 - - Household Size 1-5 Members 47.70% 35 6.76% 42.3% 14 10.37% -5.10% 6-10 Members 39.04% 66 4.49% 43.7% 53 7.68% +4.66% 11+ Members 37.99% 13 9.43% 61.06% 24 10.54% +23.07% Municipality Aileu 35.58% 21 6.82% 60.67% 22 6.05% +25.09% Ainaro 34.36% 29 6.0% 39.90% 28 6.65% +5.54% Bobonaro 45.08% 24 7.19% 32.81% 14 6.18% -12.27% Dili 40.74% 9 14.41% 81.27% 11 8.43% +40.53% Ermera 46.75% 31 7.41% 16.71% 12 10.7% -30.04% Liquiçá - - - 1.00 4 - - Education Level No Education 37.76% 59 4.97% 44.48% 37 7.77% +6.72% Primary School 45.32% 22 9.06% 52.88% 33 9.44% +7.56% Secondary and higher

45.28% 33 6.47% 46.86% 21 11.44% +1.58%

Child Gender Boy - - - 44.73% 56 5.71% - Girl - - - 53.35% 34 7.57% - Age 6-11 months - - - 64.64% 29 6.63% - 12-17 months - - - 51.23% 38 10.01% - 18-23 months - - - 23.59% 24 10.25% - Hunger Little to no hunger 36.51% 250 3.57% 48.06% 90 5.68% Moderate to severe hunger

61.09% 45 8.43% 100% 1 -

Shocks Experienced shocks - - - 47.91% 83 5.97% - Did not experience shocks

- - - 49.77% 8 12.79% -


WRA

Table 32: WRA Food Group Disaggregates (All Municipalities): 30-day recall




All Households 6.79 1,063 0.09 7.52 316 0.05 +0.72 Gendered Household Type MF 6.79 991 0.08 7.5 304 0.08 +0.72 FNM 6.76 64 0.40 7.81 12 0.05 +1.05 MNF 7.85 8 0.15 - - - - Household Size 1-5 Members 6.71 256 0.12 7.51 69 0.06 +0.80 6-10 Members 6.76 639 0.10 7.49 179 0.07 +0.73 11+ Members 7.01 168 0.21 7.6 68 0.9 +0.59 Municipality Aileu 6.40 63 0.35 7.42 86 0.04 +1.02 Ainaro 6.61 511 0.12 7.75 76 0.06 +1.15 Bobonaro 7.12 270 0.11 7.45 60 0.10 +0.32 Dili 6.87 149 0.23 7.64 31 0.06 +0.78 Ermera 6.45 70 0.27 7.38 45 0.16 +0.92 Liquiçá - - - 7.31 18 0.18 - Education Level No Education 6.89 542 0.10 7.54 133 0.06 +0.65 Primary School 6.72 271 0.15 7.41 89 0.09 +0.69 Secondary and higher

6.64 250 0.14 7.58 94 0.08 +0.94

Hunger Little to no hunger

- - - 7.52 313 0.05 -

Moderate to severe hunger

- - - 7.51 3 0.01 -

Shocks Experienced shocks

- - - 7.53 292 0.05 -

Did not experience shocks

- - - 7.33 24 0.18 -


Table 33: WRA Food Group Disaggregates (All Municipalities): 24-hour recall



All Households 5.36 316 0.14 Gendered Household Type MF 5.32 304 0.14 FNM 6.21 12 0.41 Household Size 1-5 Members 5.31 69 0.23 6-10 Members 5.42 179 0.15 11+ Members 5.24 68 0.24 Municipality Aileu 4.74 86 0.08 Ainaro 5.80 76 0.12 Bobonaro 5.55 60 0.06 Dili 5.86 31 0.22 Ermera 5.26 45 0.16 Liquiçá 5.26 18 0.22 Education Level No Education 5.37 133 0.19 Primary School 5.20 89 0.18 Secondary and higher 5.49 94 0.19 Hunger Little to no hunger 7.52 313 0.05 Moderate to severe hunger 7.51 3 0.01 Shocks Experienced shocks 5.34 292 0.15 Did not experience shocks 5.56 24 0.24


GROUPS

Table 34: Group Participation (All Municipalities)

Group Type Baseline (2015) Endline (2020)



All Households Water 3% 1,200 2% 2.4% 331 1.5% -0.6% Forestry 7% 1,200 2% 3.2% 331 1.0% -3.8% Fisheries 9% 1,200 3% 0.6% 331 0.6% -8.4% Health 2% 1,200 1% 2.5% 331 1.4% +0.5% Credit 10% 1,200 3% 10.2% 331 4.7% +0.2% Women 2% 1,200 2% 0.3% 331 0.3% -1.7% Youth 0% 1,200 0% 0% 331 - -

SHOCKS

Table 35: Prevalence of Shocks (All Municipalities)

Shock Prevalence Endline

Estimate n Standard Error Too much rain 31.80% 103 10.19% Too little rain 40.92% 137 8.23% Erosion of your land 2.02% 6 0.98% Losing your household's land 0.86% 3 0.67% Sharp increases in the price of food 5.39% 18 1.60% Someone stealing or destroying household members' belongings 1.88% 6 0.8%

Not being able to access inputs for your crops 7.63% 25 1.89% Disease affecting your crops 27.42% 94 4.9% Pests affecting your crops 34.43% 117 6.23% Someone stealing crops from your household 1.15% 4 0.49% Not being able to access inputs for your livestock 1.12% 4 0.91% Disease affecting your livestock 20.67% 67 3.75% Someone stealing animals from your household 1.49% 5 0.93% Not being able to sell the crops, livestock or other products your household produces for a fair price 19.91% 65 3.71%

A household member experiencing a severe illness 2.25% 7 0.75% Death of a family member 13.14% 43 3.8%

Table 36: Experience with Shocks (All Municipalities)



Did not experience shocks 11.3% 38 5.12% Experienced shocks 88.66% 293 5.12% Mean number of shocks 2.12 331 0.25




Types of Shocks No shock 10.10% 30 3.31% Economic shock 51.07% 149 4.72% Food shock 1.73% 5 0.8% Both shocks 37.09% 109 3.61% Gendered Household Type (number of shocks) MF 2.14 317 0.25 FNM 1.84 10 0.66 MNF 1.51 4 0.24 Household Size (number of shocks) 1-5 Members 1.82 88 0.38 6-10 Members 2.16 189 0.23 11+ Members 2.52 54 0.22 Municipality (number of shocks) Aileu 2.74 82 0.14 Ainaro 2.75 63 0.19 Bobonaro 0.86 79 0.10 Dili 2.08 33 0.42 Ermera 1.80 49 0.21 Liquiçá 3.06 25 0.36 Education level (number of shocks) No Education 1.91 139 0.33 Primary School 2.25 101 0.20 Secondary and higher 2.32 91 0.24

Table 37: Coping Mechanism Usage (All Municipalities)


Sustainable means only Both Other

Mean n Mean n Mean n Mean n All Households 16.57% 44 47.78% 124 31.46% 84 4.18% 11 Gendered Household Type MF 15.68% 40 48.42% 121 31.56% 81 4.34% 11 FNM 32.64% 2 34.13% 2 33.23% 2 - 0 MNF 51.26% 2 26.54% 1 22.2% 1 - 0 Household Size 1-5 Members 27.39% 18 47.43% 30 23.7% 17 1.49% 1 6-10 Members 15.49% 23 45.02% 64 34.56% 52 4.93% 7 11+ Members 5.62% 3 56.44% 30 32.44% 15 5.49% 3 Municipality Aileu 3.63% 2 46.56% 30 49.81% 31 - 0 Ainaro 27.5% 18 32.57% 20 28.75% 18 11.18% 7 Bobonaro 20.2% 9 66.4% 27 13.4% 7 - 0 Dili 24.37% 6 39.16% 10 24.7% 8 11.77% 3



Sustainable means only

Both Other

Mean n Mean n Mean n Mean n Ermera 16.24% 7 55.43% 24 28.3% 12 0 0 Liquiçá 7.73% 2 53.77% 13 34.7% 8 3.83% 1 Education No Education 23.66% 24 49.23% 50 23.19% 26 3.91% 4 Primary School 8.96% 8 46.67% 40 40.08% 34 4.29% 4 Secondary and higher

15.72% 12 47.07% 34 32.77% 23 4.43% 3

WEAI

Table 38: WEAI Disaggregates (All Municipalities)


Estimate n Standard Error All Households Mean # of Domains 4.78 69 5.41% Overall Adequacy 98.6% 69 1.02% Gendered Household Type MF 98.58% 68 1.05% FNM 100% 1 - Municipality Aileu 96.64% 30 1.05% Ainaro 100% 6 - Bobonaro 100% 6 - Dili 100% 7 - Ermera 100% 16 - Liquiçá 100% 4 -

Table 39: WEAI Adequacy by Domain (All Municipalities)


Estimate n Standard Error Overall Adequacy 96.96% 259 1.27% No decision 0.37% 1 0.37% No input or input in few 3.03% 8 1.26% Input into some decisions 69.32% 180 3.01% Input into most or all 27.28% 70 2.64% Income Overall Adequacy 98.89% 259 0.57% No decision 0.69% 2 0.49% No input or input in few 1.10% 3 0.56% Input into some decisions 71.8% 183 3.66% Input into most or all 26.41% 71 3.62% Resources Overall Adequacy 93.9% 81 2.81%



Estimate n Standard Error Borrowing

No decision 1.16% 1 1.19% No input or input in few 3.78% 3 1.71% Input into some decisions 55.68% 45 9.02% Input into most or all 39.38% 32 9.11%

Money Use No decision 2.31% 2 1.74% No input or input in few 1.18% 1 0.88% Input into some decisions 68.16% 55 5.12% Input into most or all 28.35% 23 5.32%

Leadership Overall Adequacy 99.37% 258 0.48% Time Overall Adequacy 93.53% 281 2.44% Average Hours Working 6.94 281 0.25


ANNEX E: BASELINE SAMPLING APPROACH

SAMPLE SIZE24

SI sampled aldeias and households from all 48 sucos selected by Avansa Agrikultura for project activities. In Project Years 1 and 2, the project is working in 19 of these sucos. For Project Year 3 and beyond, the project intends to expand to other sucos within the list of 48 sucos, and will consolidate the work for the sucos already targeted in Project Years 1 and 2.

If the project reaches all 48 sucos, out of a total of 160 sucos in the five Municipalities, this will represent 30% of all sucos in the five municipalities.

SI required a sample size of 770 households to measure the indicators with an estimated confidence level of 95% and a confidence interval of +/-5%. However, some indicators required data to be collected from targeted sub-groups, for example women with children who are 6-23 months of age. Because not all households would be expected to have children in this age category, to achieve this level of confidence for this target group would have required a sample size of 3,400 households. A survey of this size would have been prohibitively expensive.

To reduce data collection costs, SI collected data from 1,200 households from the 48 sucos to provide the desired level of precision for all indicators except for the indicator referring to children between 6-23 months of age. This sample size was predicted to yield 132 children between 6-23 months of age within the sampled households, and a margin of error (or confidence interval) for this indicator of +/- 8.5% at the 95% confidence level, or +/-7% at the 90% confidence level.

SAMPLING APPROACH

SI used a two-stage clustered sampling approach. First, 180 aldeias were randomly sampled from the 48 target sucos. Second, seven households in each sampled aldeia were randomly selected from the list of households provided by the aldeia chief. In addition to interviewing households (including household head and female decision maker), SI also collected data from the suco and/or aldeia chief on community characteristics, such as whether there were active community groups with crop buying agreements with local traders, or groups implementing natural resource management practices.

Table 40: Number of sampled aldeias and households for the 48 project sucos

District Sucos Aldeias Households Aileu 9 37 244 Ainaro 11 50 332 Bobonaro 11 31 211 Dili 3 17 111 Ermera 14 45 302

48 180 1200

24 Javis, P., Correia, A., Ximenes, H., Duthie, M., Youngblood, N., Ramdan, A., Samosir, M., & Nalle, S. (2016, May 4). Baseline survey report for the Avansa Agrikultura Project. Social Impact, Inc. for USAID/Timor-Leste. https://pdf.usaid.gov/pdf_docs/PA00M3FQ.pdf.

https://pdf.usaid.gov/pdf_docs/PA00M3FQ.pdf


ANNEX F: ENDLINE SURVEY INSTRUMENT Avansa 2020 Survey

HOUSEHOLD Household number Group name

Household Location Municipality (select one): Aileu; Ainaro; Bobonaro; Dili; Ermera Postu Administrative (select one): Aileu; Laulara; Lequidoe; Remexio; Ainaro; Hato-Builico; Hato-Udo; Maubisse; Atabae; Balibo; Bobonaro; Cailaco; Lolotoe; Maliana; Atauro; Cristo Rei; Dom Aleixo; Metinaro; Nain Feto; Vera Cruz; Atsabe; Ermera; Hatulia; Letefoho; Railaco

Suco (select one): [List of sucos]

Aldeia (select one): [List of aldeias] Start of Survey- Introduction

Good Morning/ afternoon, my name is ……….. We are conducting a survey of USAID’s Avansa Agrikultura project’s beneficiaries. The purpose of the survey is to evaluate if the support provided has helped to improve the lives of beneficiaries across the horticultural value chain. This valuable information will help the project to adjust future activities to better serve beneficiary needs. Your household was selected to participate in this survey as according to our project staff, between August 2019 - now, you participated in one or more of USAID’s Avansa Agrikultura activities. The questions usually take up to 40 minutes. All of the answers you give will be confidential and will not be shared with anyone other than members of our survey team. Your participation in the survey is voluntary, but we hope you will agree to answer the questions since your views are important. If I ask you any question you don't want to answer, just let me know and I will go on to the next question or you can stop the interview at any time. In case you need more information about the survey, you may contact the person listed on the cart that has already been given to your household. Do you have any questions? May I begin the interview now?

Information selected respondent First name Middle name Last name Gender Year of birth

• Male • Female

Education • Primary • Junior HS • Senior HS • VocTech • University • No formal education

Phone number Household member details

Total household members: Of the ${calc_hh_members_total} household members, how many are female (including children)? Of the ${constraint_hh_wra} female household members, how many are woman of reproductive age (WRA)?


Avansa 2020 Survey Of the ${calc_hh_members_total} household members how many are male (including children)? There are ${calc_hh_members_total} household members of which ${hh_wra} are WRA. Of the remaining ${calc_hh_members_remaining1} household members how many are under 6 months (0 to 5 months old)? There are ${calc_hh_members_total} household members of which ${hh_wra} are WRA and ${hh_baby} are less than 6 months old. Of the remaining ${calc_hh_members_remaining2} household members how many are between 6 and 23 months old?

Based on your inputs the household has the following members: Total: ${hh_members_total} Female: ${hh_female} WRA: ${hh_wra} Male: ${hh_male} Baby: ${hh_baby} Infant: ${hh_infant} If this information is correct, please continue with the survey, if not then change the previously entered values.

GROUPS In the past year, did your household participate in any community groups? [Do NOT include religious and political groups, or the farmer group that the household is part of - List up to three by name] How many groups did the household participate in (up to 3) Group 1 - Name of group: Group 1 - What is the principal focus of this group? Select one.

• Farming • Water • Forestry • Fisheries • Health • Credit • Women • Youth • Other

Group 1 - Other focus, explain ________ Group 2 - Name of group: Group 2 - What is the principal focus of this group? Select one. [same options as Group 1] Group 2 - Other focus, explain: ________ Group 3 - Name of group: Group 3 - What is the principal focus of this group? Select one. [same options as Group 1] Group 3 - Other focus, explain: ________

HOUSEHOLD INCOME In this section information will be collected to estimate the household’s annual income. The section is devided into two parts: passive income (like benefits) and active income (from employment). Active Income Types


Avansa 2020 Survey In addition to agricultural production, what are other sources of income? Select multiple.

Agricultural labour Livestock (live animal sales, milk, meat, etc) Trade: Buying and selling goods (street vending, shop keeping) Construction/Skilled labor (carpentry, metal work etc) Regular formal job (Employee of government, non-governmental organization or private) Handicraft small business Wood/charcoal sales Non-timber forest products (bamboo, mushroom etc) Fishing/hunting Food processing and selling Other

o Other type of active income, explain____________ None

What is the total annual active income? Passive Income Types Does the household receive any passive income? Select one.

• Yes • No

Select passive income types (select multiple): Veterans' payments from the Government Child-support funds Support for elders – tercera edade Support for disabled Support to single parent families - bolsa da mae Retirement payment Portuguese-times employees retirement payments Donations or support received from Government or donors Scholarships from the Government or other donors Gifted money from family – domestic Gifted money from family – international Rental Income Other

o Define the "Other" passive income type: What is the total passive income per year? The household total income from passive and active sources is $${total_income} which is $${total_income_per_member} per family member per year. If this is correct, please continue with the survey. If not, please change previously entered values. SECTION: HOUSEHOLD EXPENDITURE In the next section questions about expenditure will be asked to estimate the total household expenditure per year. I'm going to start by asking about your weekly spending. In the last WEEK how much did your household spend on the following items?

Cereals (wheat, rice, maize for FOOD) Tubers (potatoes, cassava etc. for FOOD) Fresh fish Tinned or dried fish

In the last WEEK how much did your household spend on the following items? Fresh meat Tinned or dried meat Eggs Milk Vegetables


Avansa 2020 Survey Legumes and nuts Fruit, including tinned fruits Oil and fat Sugar Ingredients & spices

In the last WEEK how much did your household spend on the following items? Water Beverages and non-alcoholic drinks Alcoholic drinks Tobacco and betel (including lime etc)

Summary of weekly expenditure Based on your inputs for weekly expenditures the spending per category is: Food: $${calc_exp_food_week} per week , $${calc_exp_food_month} per month, $${calc_exp_food_year} per year Beverages: $${calc_exp_drink_week} per week, $${calc_exp_drink_month} per month, $${calc_exp_drink_year} per year Alcohol: $${calc_exp_alc_tob_week} per week, $${calc_exp_alc_tob_month} per month, $${calc_exp_alc_tob_year} per year Tobacco: $${calc_exp_tob_week} per week, $${calc_exp_tob_month} per month, $${calc_exp_tob_year} per year If any of the above values sound right, please continue with the survey. If not, please change previously entered values. Monthly Expenditures on Goods and Services In the last MONTH how much did your household spend on the following items?

Personal care items House cleaning products Health and medical treatment School fees and text books Stationary, newspapers and postage Maintenance of motor car / motorbike Petrol/ Diesel for vehicles Bus fares and other transport charges Entertainment Payments to household servants License fees (vehicles) Clothing and footwear Telephone credit

Monthly Expenditures Utilities In the last MONTH how much did your household spend on the following items?

Electricity Gas Petrol and kerosene Wood for cooking

Summary of monthly expenditure Based on your inputs for monthly expenditures the spending per category is: Goods & Services: $${calc_exp_gs_month} per month , $${calc_exp_gs_year} per year Utilities: $${calc_exp_utilities_month} per month , $${calc_exp_utilities_year} per year If any of the above values sound right, please continue with the survey. If not, please change previously entered values. Annual Expenses


Avansa 2020 Survey In the last YEAR (August 2019 to July 2020) how much did your household spend on the following items?

Furniture Tax and insurances Electrical equipment (e.g. radio, TV - DO NOT include farm equipment) Household goods (e.g. pots and pans) Festivals and ceremonies Vehicle (car, motorbike etc.) Renting land Building/repairing fishponds Other

Explain what other costs are: Summary of annual expenditure Based on your inputs for annual expenditures the household is estimated to have spent $${calc_exp_annual} in the last 12 months on annual expenditures. SECTION: COMPARING EXPENDITURE TO INCOME In this section a comparison is made between reported household income and expenditure. From previous inputs it is estimated that the household has a total estimated annual income of $${total_income} and total estimated annual expenditures of $${calc_total_annual_exp}. SECTION: LOANS, SAVINGS & TRANSFERS Now we’re going to ask about money that you have given and money that you have lent. What type of outstanding loans does the household have? Select multiple; generates ${ListLabel9}

Bank loan Trader or Shop loan MFI Loan Family/Friends Other loan

o Define what the 'other' loan type is: None

Loan Type: ${ListLabel9} What is the total size of the loan? How much do you need to pay back (loan amount plus cost of loan)? What is the length/duration of the loan in months? What is the purpose of the loan/What was the loan used for? Select multiple.

Food Health care Education expenses Agriculture (seeds, tools like plough, etc) Purchase livestock Invest in business House construction/maintenance Invest in household assets (e.g. motorcycle, cookstove, etc) Funeral/wedding/traditional ceremonies Pay debt Other, specify___________________

Savings Do you or any member of the household have savings in any form? How much is the current value of such assets (in USD)

Cash at home savings Bank account savings Community savings and loan groups Moris Rasik


Avansa 2020 Survey Kaebauk/Tuba Rai Metin Other MFI Gold, silver or other precious metals Jewelry Others

Please specify what the 'other' savings type is: The household has a total savings of $${calc_savings_total}. If this is correct, please continue with the survey. If not, please change previously entered values. Transfers given and loans How much money have members of this household given to persons who are not household members in the past 11 months? How much money have members of this household loaned to persons who are not household members in the past 11 months? What is the approximate value in cash of the assistance given to persons who are not household members in food or other goods in the past 11 months? SECTION: OWNERSHIP & INVESTMENT In this section questions are asked about household asset ownership and investment. The items are broken down into the following categories: 1. Agriculture Inputs & Items 2. Household Items 3. Transport items 4. Animals First you have to select the items (one or more) from each item list. Based on your selection, further questions will be asked related to these items. Make sure that you select all items from the lists that the household owns or has purchased between August 2019 and July 2020. SECTION: OWNERSHIP & INVESTMENT- Agriculture Inputs & Items


Avansa 2020 Survey Which agriculture input items does the household own or did the household purchase between August 2019 and July 2020? Select multiple; generates ${ListLabel3}

Plastic Mulch (m2) Plastic Mulch (Roll/Packet) Plastic Tunnels (m2) Netting (m2) Plastic Tunnel Frame (packet, frame and plastic) Mini-Tiller Hand-tractor Large tractor Push cart with wheels Ox cart Wheelbarrow Other tools, (shovel, machete etc) Back pack sprayer Motorized rice mill Motorized rice thresher Rice weeder Motorized maize sheller Motorized maize grinder Hand coffee pulper Motorized coffee pulper Plough or harrow pulled by tractor Plough pulled by oxen/buffalo Irrigation package Motorized water pump Water pump (auto) Water pump (other auto) Water tank Other irrigation Plastik mini dam Fishing net Fishpond None

How many ${ListLabel3} do you own currently? What is the estimated value/cost of one ${ListLabel3} in USD? How many ${ListLabel3} did you buy from August 2019 - July 2020 for investment or to use? Did you purchase the ${ListLabel3}(s) together with other households? Select one.

• Yes • No

How many households purchased the ${ListLabel3}(s) together? How much did your household contribute to the purchase of the ${ListLabel3}(s)? SECTION: OWNERSHIP & INVESTMENT- Household Items


Avansa 2020 Survey Which household items does the household own or did the household purchase between August 2019 and July 2020? Select multiple; generates ${ListLabel4}

Refrigerator Freezer Gas/electric cooking stove Washing machine Sewing machine Generator Solar panel Computer Mobile Phone TV TV with DVD player Radio DVD player Stereo None

How many ${ListLabel4}(s) do you own currently? What is the estimated value/cost of one ${ListLabel4} in USD? How many ${ListLabel4}(s) did you buy from August 2019 - July 2020 for investment or to use? SECTION: OWNERSHIP & INVESTMENT- Transport Items Which transport items does the household own or did the household purchase between August 2019 and July 2020? Select multiple; generates ${ListLabel5}

Truck or pickup Car or minivan Motor bike Tiga Roda Bicycle Canoe or boat Boat engine None

How many ${ListLabel5}(s) do you own currently? What is the estimated value/cost of one ${ListLabel5} in USD? How many ${ListLabel5}(s) did you buy from August 2019 to July 2020 for investment or to use? SECTION: OWNERSHIP & INVESTMENT- Animals Which animals does the household own or did the household purchase between August 2019 and July 2020? Select multiple; generates ${ListLabel6}

Chickens (female) Rooster (male) Other poultry (ducks etc) Pigs Sheep Goats Horses or donkeys Cows - female cattle Bulls - male cattle Male Buffalo Female Buffalo Fish - Mujair Fish - Lele Fish - Mas Fish - Nila

How many ${ListLabel6}(s) do you own currently?


Avansa 2020 Survey What is the estimated value/cost of one ${ListLabel6} in USD? How many ${ListLabel6}(s) did you buy from August 2019 to July 2020 for investment or to use? SECTION: OWNERSHIP & INVESTMENT- Land Purchased Did the household purchase any land from August 2019 - July 2020 for investment or to use? Select one.

• Yes • No

How many pieces/parcels did the household purchase? What was the width of the land in meters? What was the length of the land in meters? How much did the household pay for the piece of land? What was/is the land used for? Select multiple.

Land for growing irrigated rice crops Land for growing rain fed crops Land for other purposes

Explain what the other land use is: The land size in square meters is ${calc_land_parcels_purchased_m2}. If this is not correct please update the values entered in the previous section. SECTION: HUNGER PREVELANCE In this section we're going to ask a few questions about the prevalence and times that you have faced hunger in your household In the past month was there ever no food to eat in your house because of lack of resources to get food? Select one.

• Yes • No

How often did this happen in the past month? Select one. • Rarely (1-2 times) • Sometimes (3-10 times) • Often (more than 10 times)

In the past month did you or any household member go to sleep at night hungry because there was not enough food? Select one.

• Yes • No


In the past month did you or any household member go a whole day and night without eating anything at all because there was not enough food? Select one.

• Yes • No


How does your household’s food situation in the past month compare to an average (or normal) month for you? Select one.

• Yes • No

How, if at all, has COVID-19 changed your household’s food situation?


Avansa 2020 Survey In the past 11 months (Aug 2019 – July 2020), were there any months during which your household did not have food to meet your family needs? Select one.

• Yes • No

What months of the previous 12 months did you not have food to meet your family's needs? Select multiple.

August 2019 September 2019 October 2019 November 2019 December 2019 January 2020 February 2020 March 2020 April 2020 May 2020 June 2020 July 2020

SECTION: WRA NUTRITION Ask if you can take a picture if this person is not a WRA. If it is allowed, please take the picture. If not, continue with the interview. GPS location - Take a GPS point at the interview location (house of respondent) - make sure you are outside and wait until saving until the accuracy is 12m or less. This is the end of the first section. Now we’re going to continue with the section on nutrition with WRA. As you know, women and children's health and nutrition are very important especially if a woman is, or is going to be, a mother. Our program collects this information to try and measure nutrition and diets of women, children and mothers. This helps us to better respond to the needs of our members. The section on WRA is very brief, and then the final section is on child nutrition. Please answer the following questions for each women aged 15-49 in household who are available today to survey. In the Household Section you said that there are ${hh_wra} WRA in the household. How many of these woman are available for an interview? Woman of reproductive age

Name First Name Last Year of birth: Education level (select one):

• Primary • Junior HS • Senior HS • VocTech • University • No formal education

I would like to ask you to describe everything that you ate or drank yesterday during the previous day or night, whether you ate it at home or anywhere else. Please include all foods and drinks, any snacks or small meals, as well as any main meals.


Avansa 2020 Survey ASK FOR EACH OF THE FOOD GROUPS IF HAD SOMETHING TO DRINK OR EAT CONTAINING THE FOOD GROUP WHEN: - woke up - later in the morning - at mid-day - during the afternoon - in the evening - before going to bed or during the night

Foods made from grains: Porridge, bread, rice, pasta/noodles or other foods made from grains. Select one.

• Yes • No

White roots and tubers and plantains: White potatoes, white yams, manioc/cassava/yucca, cocoyam, taro or any other foods made from white-fleshed roots or tubers, or plantains. Select one.

• Yes • No

Pulses (beans, peas and lentils): Mature beans or peas (fresh or dried seed), lentils or bean/pea products, including hummus, tofu and tempeh. Select one.

• Yes • No

Nuts and seeds: Any tree nut, groundnut/peanut or certain seeds, or nut/seed butters or paste. Select one.

• Yes • No

ASK FOR EACH OF THE FOOD GROUPS IF HAD SOMETHING TO DRINK OR EAT CONTAINING THE FOOD GROUP WHEN: - woke up - later in the morning - at mid-day - during the afternoon - in the evening - before going to bed or during the night

Milk and milk products: Milk, cheese, yoghurt or other milk products but NOT including butter, ice cream, cream or sour cream. Select one.

• Yes • No

Organ Meat: Liver, kidney, heart or other organ meats or blood-based foods, including from wild game. Select one.

• Yes • No

Meat and poultry: Beef, pork, lamb, goat, rabbit, wild game meat, chicken, duck or other bird. Select one.

• Yes • No

Fish and seafood: Fresh or dried fish, shellfish or seafood. Select one. • Yes • No

Eggs: Eggs from poultry or any other bird. Select one. • Yes • No


Avansa 2020 Survey AS FOR EACH OF THE FOOD GROUPS IF HAD SOMETHING TO DRINK OR EAT CONTAINING THE FOOD GROUP WHEN: - woke up - later in the morning - at mid-day - during the afternoon - in the evening - before going to bed or during the night

Dark green leafy vegetables: List examples of any medium-to-dark green leafy vegetables, including wild/foraged leaves. Select one.

• Yes • No

Vitamin A-rich vegetables, roots and tubers, for example: Pumpkin, carrots, squash or sweet potatoes that are yellow or orange inside. Select one.

• Yes • No

Vitamin A-rich fruits, for example Ripe mango, ripe papaya. Select one. • Yes • No

Other vegetables. Select one. • Yes • No

Other fruits. Select one. • Yes • No

Now, for the questions you answered "no" to, I would like to ask the same questions again. But this time, I would like to know whether you ate or drank them during the last 30 days, whether you ate it at home or anywhere else. Please include all foods and drinks, any snacks or small meals, as well as any main meals. ASK FOR EACH OF THE FOOD GROUPS IF THE RESPONDENT HAD SOMETHING TO DRINK OR EAT CONTAINING THE FOOD GROUP: -during the last 30 days.

Foods made from grains: Porridge, bread, rice, pasta/noodles or other foods made from grains. Select one.

• Yes • No

White roots and tubers and plantains: White potatoes, white yams, manioc/cassava/yucca, cocoyam, taro or any other foods made from white-fleshed roots or tubers, or plantains. Select one.

• Yes • No

Pulses (beans, peas and lentils): Mature beans or peas (fresh or dried seed), lentils or bean/pea products, including hummus, tofu and tempeh. Select one.

• Yes • No

Nuts and seeds: Any tree nut, groundnut/peanut or certain seeds, or nut/seed butters or paste. Select one.

• Yes • No


Avansa 2020 Survey Milk and milk products: Milk, cheese, yoghurt or other milk products but NOT including butter, ice cream, cream or sour cream. Select one.

• Yes • No

Organ Meat: Liver, kidney, heart or other organ meats or blood-based foods, including from wild game. Select one.

• Yes • No

Meat and poultry: Beef, pork, lamb, goat, rabbit, wild game meat, chicken, duck or other bird. Select one.

• Yes • No

Fish and seafood: Fresh or dried fish, shellfish or seafood. Select one. • Yes • No

Eggs: Eggs from poultry or any other bird. Select one. • Yes • No

Dark green leafy vegetables: List examples of any medium-to-dark green leafy vegetables, including wild/foraged leaves. Select one.

• Yes • No

Vitamin A-rich vegetables, roots and tubers, for example: Pumpkin, carrots, squash or sweet potatoes that are yellow or orange inside. Select one.

• Yes • No

Vitamin A-rich fruits, for example Ripe mango, ripe papaya. Select one. • Yes • No

Other vegetables. Select one. • Yes • No

Other fruits. Select one. • Yes • No

How, if at all, has COVID-19 changed the types of foods you eat? Ask if you can take a picture of ${wra_name_proper}. If it is allowed, please take the picture. If not, continue with the interview. SECTION: INFANT NUTRITION (6-23 months) This section contains questions on the nutrition of children. In the Household Section you said that there are ${hh_infant} infants in the household. For how many infants are you going to enter individual nutrition details in the next section? This section contains questions on the nutrition of male children of 6 - 23 months old - The set of questions should be asked for EACH of the infants SEPERATELY! Start with the youngest child - the questions will start automatically for the succeeding child until complete. Individual Infant Nutrition Details Infant ${RecKeyInfant} of ${infant_repeat_count} First name of infant: Last name of Infant: How many months old is the infant?


Avansa 2020 Survey What gender is the infant? Select one.

• Male • Female

Has the infant ever been breastfed? Select one. • Yes • No • Don’t know

Was ${infant_name_proper} breastfed yesterday during the day or at night? Select one. • Yes • No • Don’t know

Sometimes babies are fed breast milk in different ways, for example by spoon, cup or bottle. This can happen when the mother cannot always be with her baby. Sometimes babies are breastfed by another woman or given breast milk from another woman by spoon, bottle or some other way. This can happen if a mother cannot breastfeed her own baby.

Did ${infant_name_proper} consume breast milk in any of these ways yesterday during the day or at night? Select one.

• Yes • No • Don’t know

Medicines and Vitamins Was ${infant_name_proper} given any vitamin drops or other medicines yesterday during the day or at night? Select one.


Was ${infant_name_proper} given [oralit or a home-made version] yesterday during the day or at night? Select one.


Liquids and soft foods Now I would like to ask you about liquids or foods ${infant_name_proper} had yesterday during the day or at night. I am interested in whether ${infant_name_proper} had the item even if it was combined with other foods. Did ${infant_name_proper} drink or eat any of the following:

Plain water? Select one. • Yes • No • Don’t know

Commercially produced infant formula? Select one. • Yes • No • Don’t know

Any fortified baby food such as Cerelac, Sun? Select one. • Yes • No • Don’t know


Avansa 2020 Survey Any (other) porridge or gruel? Select one.


Milk such as tinned, powdered, or fresh animal milk? Select one. • Yes • No • Don’t know

Tea or coffee? Select one. • Yes • No • Don’t know

Any other liquids? Select one. • Yes • No • Don’t know

Carbs Did ${infant_name_proper} drink or eat any of the following:

Bread, rice, noodles, or other food made from grains like corn powder porridge? Select one. • Yes • No • Don’t know

Pumpkin, carrots, squash or sweet potatoes that are yellow or orange inside? Select one. • Yes • No • Don’t know

White potatoes, cassava, or any other foods made from roots? Select one. • Yes • No • Don’t know

Any dark green, leafy vegetables? Select one. • Yes • No • Don’t know

Fruits Did ${infant_name_proper} eat any of the following:

Ripe mangoes or papayas? Select one. • Yes • No • Don’t know

Any other fruits or vegetables? Select one. • Yes • No • Don’t know

Protein Did ${infant_name_proper} eat any of the following:

Liver, kidney, heart or other organ meats? Select one. • Yes • No • Don’t know


Avansa 2020 Survey Any meat, such as beef, pork, lamb, goat, chicken, or duck? Select one.


Eggs? Select one. • Yes • No • Don’t know

Fresh or dried fish or shellfish? Select one. • Yes • No • Don’t know

Any foods made from beans, peas, lentils, or nuts? Select one. • Yes • No • Don’t know

Cheese, other milk products? Select one. • Yes • No • Don’t know

Fats Did ${infant_name_proper} eat any of the following:

Any oil, fats, or butter, or foods made with any of these? Select one. • Yes • No • Don’t know

Any sugary foods such as chocolates, sweets, candies, pastries, cakes, or biscuits? Select one. • Yes • No • Don’t know

Any other solid or semi-solid food? Select one. • Yes • No • Don’t know

How many times did ${infant_name_proper} eat solid, semisolid, or soft foods yesterday during the day or at night? (If 7 or more times, record '7'. If don't know, record '8'.) How, if at all, has COVID-19 changed the types of foods that ${infant_name_proper} eats? SECTION: WOMEN'S EMPOWERMENT IN AGRICULTURE The primary female decisionmaker is the woman who makes more social and economic decisions than other women in the household. (Examples: food crop farming, livestock raising, household expenditures, food for daily consumption.) The primary decisionmaker does NOT refer to the household head – as long as there are at least one adult male and one adult female in the household, there will be one primary male and one primary female decisionmaker. Is the primary female decisionmaker (age 18 or older) present and available for an interview? If she is present, you will proceed to ask her specific questions that only she should answer. Select one.

• Yes • No • Other

If she is present but you cannot interview, explain why: ____________________


Avansa 2020 Survey Did your household participate in any income generation activities in the past 12 months? Income activities are any active income activities, any activities that earn the household money. For example, if a household member has a job, this is an income earning activity. Or if a household member sells fruit at the market, this is an income activity. If the household received active income, then the household participated in income generating activities. Select one.


How much input did you have in decisions about these activities? Select one. • No input or input into very few decisions • Input into some decisions • Input into most or all decisions • No decision made

How much input did you have in decisions on the use of income generated from these activities? Select one.

• No input or input into very few decisions • Input into some decisions • Input into most or all decisions • No decision made

Has anyone in your household taken any loans or borrowed cash/in-kind in the past 12 months? Select one.


How much input did you have in the decision(s) to borrow money? Select one. • No input or input into very few decisions • Input into some decisions • Input into most or all decisions • No decision made

How much input did/do you have in the decision about what to do with the money? Select one. • No input or input into very few decisions • Input into some decisions • Input into most or all decisions • No decision made

Which of the following types of groups are active in your community? Select multiple. Agriculture producer's group Water users group Forest users group Credit/microfinance group Mutual help or insurance group Trade and business association Civic group Local government Religious group Other women's group

• Explain what the activities are of the Other Woman's Group: None


Avansa 2020 Survey Of which of these groups, if any, are you an active member? Select multiple. Agriculture producer's group Water users group Forest users group Credit/microfinance group Mutual help or insurance group Trade and business association Civic group Local government Religious group Other women's group

• Explain what the activities are of the Other Woman's Group: None

This question is related to how many hours per day you work. On an average day, how many hours to you spend working? Examples are: Employment, business, domestic work, cooking, etc.: SECTION: SHOCKS Next I will ask you some questions about other kinds of difficult times that people face. In the past 12 months, did your household face difficult times as a result of any of the following events? Select multiple

Too much rain Too little rain Erosion of your land Losing your household's land Sharp increases in the price of food Someone stealing or destroying household members' belongings Not being able to access inputs for your crops Disease affecting your crops Pests affecting your crops Someone stealing crops from your household Not being able to access inputs for your livestock Disease affecting your livestock Someone stealing animals from your household Not being able to sell the crops, livestock or other products your household produces for

a fair price A household member experiencing a severe illness Death of a family member Other

o Specify other shock: None

Did any of these events have a negative effect on your household's economic situation or food consumption? Select one

• Yes - on economic situation • Yes - on food consumption • Yes - on both economic situation and food consumption • No

Of the difficulties you selected, I am going to ask you to rank up to 3 (depending on how many you selected) in terms of severity of their effect on your household's economic situation or food consumption. Then I will ask you about the strategies that your household may have used to deal with each one.


Avansa 2020 Survey Shock 1: Select one

• Too much rain • Too little rain • Erosion of your land • Losing your household's land • Sharp increases in the price of food • Someone stealing or destroying household members' belongings • Not being able to access inputs for your crops • Disease affecting your crops • Pests affecting your crops • Someone stealing crops from your household • Not being able to access inputs for your livestock • Disease affecting your livestock • Someone stealing animals from your household • Not being able to sell the crops, livestock or other products your household produces for

a fair price • A household member experiencing a severe illness • Death of a family member • ${shocks_other}

What strategies did your household use to deal with this difficulty? Select multiple Relied on income from seasonal work Bartered for goods/services Used money from savings accounts Sold land Sold assets/livestock Cut back on food consumption Borrowed money or food from friend/relative Purchased food/resources on credit Harvested immature crops Pulled children from school to work Used social mechanism (such as rotating credit) Other

o Specify other mechanism: Shock 2: [Same options as Shock 1]

What strategies did your household use to deal with this difficulty? [same options as Shock 1] Shock 3: [Same options as Shock 1]

What strategies did your household use to deal with this difficulty? [same options as Shock 1] Were any of these shocks exacerbated by COVID-19?

• Yes • No

Please briefly explain the effects of COVID-19 on your household's economic or food situation:

Endline Survey Report for the Avansa Agrikultura Project

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Transcript of Endline Survey Report for the Avansa Agrikultura Project