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Overview of FAO’s Work on SDGs
Focus – SDG Indicator 2.4.1
Arbab Asfandiyar Khan
Economist
FAO ESS Division
OVERVIEW OF THE GLOBAL INDICATOR
FRAMEWORK
 GIF (232 indicators) endorsed in July 2017
 UNSC is responsible for the SDG monitoring framework
 Custodian international agency is assigned for each indicator
 IAEG-SDG to prepare an initial proposal and oversee this work
through to 2030
• 28 countries representing their respective regions;
• International organizations as observers;
• Meets twice a year (last meeting 5-8 November 2018)
=> The process has been fully led by countries
CLASSIFICATION OF INDICATORS IN THREE
TIERS
 Based on the level of methodological development and the
availability of data
TIER LEVEL OF DEVELOPMENT
I • Established methodology/international standards exist
• Most countries are regularly producing data (>50% of
countries/ population in each region)
II • An established methodology/international standards exist
• Most countries are still not regularly producing data (<50%
of countries/ population in each region)
III • Established methodology/international standards do not
yet exist or are still being tested
STATUS OF SDG INDICATORS UNDER FAO
CUSTODIANSHIP
As of November 2015 (21 SDG indicators)
Goal Indicators
Goal 2 (Food
security, Nutrition,
Sustainable
Agriculture) 2.1.1 2.1.2 2.3.1 2.3.2 2.4.1 2.5.1 2.5.2 2.a.1 2.c.1
Goal 5 (Gender
equality) 5.a.1 5.a.2
Goal 6 (Use of
Water) 6.4.1 6.4.2
Goal 12
(Sustainable
Consumption and
Production) 12.3.1
Goal 14 (Oceans) 14.4.1 14.6.1 14.7.1 14.b.1
Goal 15 (Life on
Land) 15.1.1 15.2.1 15.4.2
Tier # of indicators
I 3
II 5
III 13
STATUS OF SDG INDICATORS UNDER FAO
CUSTODIANSHIP
As of January 2018
Goal Indicators
Goal 2 (Food
security, Nutrition,
Sustainable
Agriculture) 2.1.1 2.1.2 2.3.1 2.3.2 2.4.1 2.5.1 2.5.2 2.a.1 2.c.1
Goal 5 (Gender
equality) 5.a.1 5.a.2
Goal 6 (Use of
Water) 6.4.1 6.4.2
Goal 12
(Sustainable
Consumption and
Production) 12.3.1
Goal 14 (Oceans) 14.4.1 14.6.1 14.7.1 14.b.1
Goal 15 (Life on
Land) 15.1.1 15.2.1 15.4.2
FAO started with 13 Tier III indicators, it now has only 1 left.
Tier # of indicators
I 12
II 8
III 1
GOAL 2 - END HUNGER,
ACHIEVE FOOD SECURITY
AND IMPROVED NUTRITION
AND PROMOTE SUSTAINABLE
AGRICULTURE
GOAL 2 (NO HUNGER) – INDICATORS UNDER FAO
CUSTODIANSHIP
Indicator # Indicator Title Target
2.1.1 Prevalence of undernourishment
2.1
2.1.2
Prevalence of moderate or severe food insecurity in the
population, based on the Food Insecurity Experience
Scale (FIES)
2.3.1
Volume of production per labour unit by classes of
farming/pastoral/ forestry enterprise size
2.3
2.3.2
Average income of small-scale food producers, by sex
and indigenous status
2.4.1
Proportion of agricultural area under productive and
sustainable agriculture
2.4
2.5.1
Number of plant and animal genetic resources for food
and agriculture secured in either medium or long-term
conservation facilities 2.5
2.5.2
Proportion of local breeds classified as being at risk,
not-at-risk or at unknown level of risk of extinction
2.a.1
The agriculture orientation index for government
expenditures
2.a
2.c.1
Indicator of food price anomalies [The proposed
indicator of food price anomalies measures the number
of “Price Anomalies” that occur on a given food
commodity price series over a given period of time.]
GOAL 2 comprise of 14 indicators of which FAO is
CORPORATE CAPACITY DEVELOPMENT
ACTIVITIES FOR SDG INDICATORS
2016-18
E-LEARNING COURSES
GLOBAL, REGIONAL AND NATIONAL TRAINING
WORKSHOPS
SDG DATA & COMMUNICATION PORTAL
NEW FAO vision for 2019-2030: Scale up
capacity development support to maximize
country reporting
Hunger
Women’s equal rights
to land ownership
Severity of food
insecurity
Public Investment in
agriculture
Food price volatility
Access rights for
small-scale fisheries
Water stress
2.1.1
2.1.2
2.a.1
2.c.1
14.b.1
6.4.2
5.a.2
E-learning courses published, freely available
online2.5.1 2.5.2
Conservation of plant
and animal genetic
resources
5.a.1
Forest area and
sustainable forest
management
15.1.1 15.2.1
Severity of food
insecurity Food price volatility
Access rights for
small-scale fisheries
2.1.2 2.c.1 14.b.1
E-learning courses published, freely available
online
 Spanish
 French
 Spanish
 French
 Russian
 Spanish
 French
 Russian
 Arabic
E-learning courses under development
Water use efficiency
Productivity and
income of small-scale
food producers
Agricultural
sustainability
Global food losses
Value added of
sustainable fisheries
Fish stocks
sustainability
12.3.1
6.4.1
2.3.1 2.3.2
2.4.1
14.4.1
14.7.1
Coming soon
GLOBAL AND REGIONAL TRAINING
WORKSHOPS 2016-2018
Aims: Enlarge the pool of SDG monitoring
experts
Facilitate South-South cooperation
Facilitate pilot testing of new methods
 40+ training workshops in 2017
and 2018
 120 countries attended one or
more workshops from all regions of
the world
Result: Increased number of reporting coun
By 2030, ensure sustainable food production systems and
implement resilient agricultural practices that increase
productivity and production, that help maintain
ecosystems, that strengthen capacity for adaptation to
climate change, extreme weather, drought, flooding and
other disasters and that progressively improve land and
soil quality
13
TARGET
2.4:
INDICATOR 2.4.1
Defined as the “Proportion of agricultural area under productive and
sustainable agriculture”, which is expressed as:
𝐹𝑜𝑟𝑚𝑢𝑙𝑎 =
𝐴𝑟𝑒𝑎 𝑢𝑛𝑑𝑒𝑟 𝑝𝑟𝑜𝑑𝑢𝑐𝑡𝑖𝑣𝑒 𝑎𝑛𝑑 𝑠𝑢𝑠𝑡𝑎𝑖𝑛𝑎𝑏𝑙𝑒 𝑎𝑔𝑟𝑖𝑐𝑢𝑙𝑡𝑢𝑟𝑒
𝐴𝑔𝑟𝑖𝑐𝑢𝑙𝑡𝑢𝑟𝑎𝑙 𝑙𝑎𝑛𝑑 𝑎𝑟𝑒𝑎
Reflects the multiple dimensions of sustainability
Measured at farm level
Allows measurement of progress towards more productive and sustainable
agriculture
14
STEPS TO DEVELOP THE
INDICATOR
1) Determining the scope
2) Determining the dimensions to be covered (sustainability)
3) Choosing the scale
4) Selecting the data collection instrument(s).
5) Selecting the themes to be covered, choosing a sub-indicator
for each theme.
6) Developing the criteria to assess sustainability performance
for each sub-indicator
7) Deciding the periodicity of monitoring the indicator
8) Developing modality of reporting the indicator
15
SUB-INDICATORS
No. Theme Sub-indicators
1 Land productivity Farm output value per hectare
2 Profitability Net farm income
3 Resilience Risk mitigation mechanisms
4 Soil health Prevalence of soil degradation
5 Water use Variation in water availability
6 Fertilizer risk Management of fertilizers
7 Pesticide risk Management of pesticides
8 Biodiversity Use of biodiversity-friendly practices
9 Decent employment Wage rate in agriculture
10 Food security
Food insecurity experience scale
(FIES)
11 Land tenure Secure tenure rights to land
16
ASSESSING SUSTAINABILITY
LEVELS
17
1. Green: ‘desirable’
2. Yellow: ‘acceptable’
3. Red: ‘unsustainable’
Criteria established by thematic experts, will be fine tuned
in light of results of the proposed tests
Helps measure progress
REPORTING THROUGH A
DASHBOARD
18
Example of results for country X in year Y
Note: This dashboard is only a simulation and is not from real data
NEXT STEPS FOR SDG
INDICATOR 2.4.1
Extended pilots ongoing in Bangladesh
Finalizing documentation
Farm survey questionnaire (PAPI and CAPI versions)
Enumerator’s manual
Calculation procedures
Preparation of training material and e-learning courses is
in progress
Advocacy and training workshops (global, regional and
national) planned in different regions
SDG data & communication portal
Rolling out in countries
19
THANK YOU
http://www.fao.org/sustainable-development-goals/en/
Contact us:
Arbab.khan@fao.org;
Amy.Heyman@fao.org;
Francesco.Tubiello@fao.org;
Education
for all
Anytime
Anywhere
Free of
charge
Transfer of
skills and
competences
Multilingual
500,000
learners
throughout
the world
Public
good
All SDGs
and SDG 4
FAO E-learning Center
www.fao.org/elearning
CRITERIA FOR THE CHOICE
OF THEMES AND SUB-
INDICATORS
22
Policy relevance
Universality
International comparability
Measurability
Cost effectiveness
Minimum cross-correlation
SCOPE
Included within the scope
Crop and livestock production systems
 Non-food crops and livestock (example crops such as tobacco, cotton, and livestock raised for non-food products like sheep for
wool).
 Crops grown for fodder or for energy purposes.
Agro-forestry (trees on the farm).
Aquaculture, to the extent that it takes place within the agricultural area. For example,
rice-fish and similar systems.
Both intensive and extensive production systems (including subsistence agriculture).
Excluded from the scope
State and common land used commonly by several agriculture holdings.
Production from gardens and backyards.
Production from hobby farms.
Land used exclusively for aquaculture.
Forest and other wooded lands.
Food harvested from the wild. 23
AGGREGATE INDICATOR (AT
NATIONAL OR OTHER LEVELS)
𝑆𝐷𝐺241 𝑑 = min
𝑛:1−11
(𝑆𝐼 𝑑 𝑛)
𝑆𝐷𝐺241 𝑎+𝑑 = min
𝑛:1−11
(𝑆𝐼 𝑑+𝑆𝐼 𝑎) 𝑛
𝑆𝐷𝐺241 𝑢 = max
𝑛:1−11
(𝑆𝐼 𝑢 𝑛)
SDG241d = proportion of agricultural land area that have achieved the
‘desirable’ level
SDG241a+d = proportion of agricultural land area that have achieved at
least the ‘acceptable’ level
SDG241u = proportion of agricultural area that is ‘unsustainable’
24
PREFERRED INSTRUMENT
FOR DATA COLLECTION
Preferred instrument for data collection is a farm survey
questionnaire
Aligned with efforts supported by FAO to develop farm surveys
as the most relevant instrument for agricultural data (AGRIS)
Questionnaire designed as a module that contain the minimum
set of questions needed to assess 2.4.1.
These questions can be integrated into existing farm surveys
Can be complemented with contextual information from other
data sources
Suggested periodicity: 3 years
17
CONDITIONS FOR USING
ALTERNATIVE DATA SOURCES
Respects the stratification (farm type, agricultural areas,
etc.)
Captures the same phenomenon as the proposed farm
survey
At least same quality as the farm survey
Compliant with international/national standards and
classifications systems internationally comparable
Data available at the same level of territorial
disaggregation as the farm survey
Reference year and periodicity homogenous across the
sub-indicators
20

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Brussels Briefing 54: Asfandiyar Khan '' Where are we on SDG2 implementation: Trends and projections''

  • 1. Overview of FAO’s Work on SDGs Focus – SDG Indicator 2.4.1 Arbab Asfandiyar Khan Economist FAO ESS Division
  • 2. OVERVIEW OF THE GLOBAL INDICATOR FRAMEWORK  GIF (232 indicators) endorsed in July 2017  UNSC is responsible for the SDG monitoring framework  Custodian international agency is assigned for each indicator  IAEG-SDG to prepare an initial proposal and oversee this work through to 2030 • 28 countries representing their respective regions; • International organizations as observers; • Meets twice a year (last meeting 5-8 November 2018) => The process has been fully led by countries
  • 3. CLASSIFICATION OF INDICATORS IN THREE TIERS  Based on the level of methodological development and the availability of data TIER LEVEL OF DEVELOPMENT I • Established methodology/international standards exist • Most countries are regularly producing data (>50% of countries/ population in each region) II • An established methodology/international standards exist • Most countries are still not regularly producing data (<50% of countries/ population in each region) III • Established methodology/international standards do not yet exist or are still being tested
  • 4. STATUS OF SDG INDICATORS UNDER FAO CUSTODIANSHIP As of November 2015 (21 SDG indicators) Goal Indicators Goal 2 (Food security, Nutrition, Sustainable Agriculture) 2.1.1 2.1.2 2.3.1 2.3.2 2.4.1 2.5.1 2.5.2 2.a.1 2.c.1 Goal 5 (Gender equality) 5.a.1 5.a.2 Goal 6 (Use of Water) 6.4.1 6.4.2 Goal 12 (Sustainable Consumption and Production) 12.3.1 Goal 14 (Oceans) 14.4.1 14.6.1 14.7.1 14.b.1 Goal 15 (Life on Land) 15.1.1 15.2.1 15.4.2 Tier # of indicators I 3 II 5 III 13
  • 5. STATUS OF SDG INDICATORS UNDER FAO CUSTODIANSHIP As of January 2018 Goal Indicators Goal 2 (Food security, Nutrition, Sustainable Agriculture) 2.1.1 2.1.2 2.3.1 2.3.2 2.4.1 2.5.1 2.5.2 2.a.1 2.c.1 Goal 5 (Gender equality) 5.a.1 5.a.2 Goal 6 (Use of Water) 6.4.1 6.4.2 Goal 12 (Sustainable Consumption and Production) 12.3.1 Goal 14 (Oceans) 14.4.1 14.6.1 14.7.1 14.b.1 Goal 15 (Life on Land) 15.1.1 15.2.1 15.4.2 FAO started with 13 Tier III indicators, it now has only 1 left. Tier # of indicators I 12 II 8 III 1
  • 6. GOAL 2 - END HUNGER, ACHIEVE FOOD SECURITY AND IMPROVED NUTRITION AND PROMOTE SUSTAINABLE AGRICULTURE
  • 7. GOAL 2 (NO HUNGER) – INDICATORS UNDER FAO CUSTODIANSHIP Indicator # Indicator Title Target 2.1.1 Prevalence of undernourishment 2.1 2.1.2 Prevalence of moderate or severe food insecurity in the population, based on the Food Insecurity Experience Scale (FIES) 2.3.1 Volume of production per labour unit by classes of farming/pastoral/ forestry enterprise size 2.3 2.3.2 Average income of small-scale food producers, by sex and indigenous status 2.4.1 Proportion of agricultural area under productive and sustainable agriculture 2.4 2.5.1 Number of plant and animal genetic resources for food and agriculture secured in either medium or long-term conservation facilities 2.5 2.5.2 Proportion of local breeds classified as being at risk, not-at-risk or at unknown level of risk of extinction 2.a.1 The agriculture orientation index for government expenditures 2.a 2.c.1 Indicator of food price anomalies [The proposed indicator of food price anomalies measures the number of “Price Anomalies” that occur on a given food commodity price series over a given period of time.] GOAL 2 comprise of 14 indicators of which FAO is
  • 8. CORPORATE CAPACITY DEVELOPMENT ACTIVITIES FOR SDG INDICATORS 2016-18 E-LEARNING COURSES GLOBAL, REGIONAL AND NATIONAL TRAINING WORKSHOPS SDG DATA & COMMUNICATION PORTAL NEW FAO vision for 2019-2030: Scale up capacity development support to maximize country reporting
  • 9. Hunger Women’s equal rights to land ownership Severity of food insecurity Public Investment in agriculture Food price volatility Access rights for small-scale fisheries Water stress 2.1.1 2.1.2 2.a.1 2.c.1 14.b.1 6.4.2 5.a.2 E-learning courses published, freely available online2.5.1 2.5.2 Conservation of plant and animal genetic resources 5.a.1 Forest area and sustainable forest management 15.1.1 15.2.1
  • 10. Severity of food insecurity Food price volatility Access rights for small-scale fisheries 2.1.2 2.c.1 14.b.1 E-learning courses published, freely available online  Spanish  French  Spanish  French  Russian  Spanish  French  Russian  Arabic
  • 11. E-learning courses under development Water use efficiency Productivity and income of small-scale food producers Agricultural sustainability Global food losses Value added of sustainable fisheries Fish stocks sustainability 12.3.1 6.4.1 2.3.1 2.3.2 2.4.1 14.4.1 14.7.1 Coming soon
  • 12. GLOBAL AND REGIONAL TRAINING WORKSHOPS 2016-2018 Aims: Enlarge the pool of SDG monitoring experts Facilitate South-South cooperation Facilitate pilot testing of new methods  40+ training workshops in 2017 and 2018  120 countries attended one or more workshops from all regions of the world Result: Increased number of reporting coun
  • 13. By 2030, ensure sustainable food production systems and implement resilient agricultural practices that increase productivity and production, that help maintain ecosystems, that strengthen capacity for adaptation to climate change, extreme weather, drought, flooding and other disasters and that progressively improve land and soil quality 13 TARGET 2.4:
  • 14. INDICATOR 2.4.1 Defined as the “Proportion of agricultural area under productive and sustainable agriculture”, which is expressed as: 𝐹𝑜𝑟𝑚𝑢𝑙𝑎 = 𝐴𝑟𝑒𝑎 𝑢𝑛𝑑𝑒𝑟 𝑝𝑟𝑜𝑑𝑢𝑐𝑡𝑖𝑣𝑒 𝑎𝑛𝑑 𝑠𝑢𝑠𝑡𝑎𝑖𝑛𝑎𝑏𝑙𝑒 𝑎𝑔𝑟𝑖𝑐𝑢𝑙𝑡𝑢𝑟𝑒 𝐴𝑔𝑟𝑖𝑐𝑢𝑙𝑡𝑢𝑟𝑎𝑙 𝑙𝑎𝑛𝑑 𝑎𝑟𝑒𝑎 Reflects the multiple dimensions of sustainability Measured at farm level Allows measurement of progress towards more productive and sustainable agriculture 14
  • 15. STEPS TO DEVELOP THE INDICATOR 1) Determining the scope 2) Determining the dimensions to be covered (sustainability) 3) Choosing the scale 4) Selecting the data collection instrument(s). 5) Selecting the themes to be covered, choosing a sub-indicator for each theme. 6) Developing the criteria to assess sustainability performance for each sub-indicator 7) Deciding the periodicity of monitoring the indicator 8) Developing modality of reporting the indicator 15
  • 16. SUB-INDICATORS No. Theme Sub-indicators 1 Land productivity Farm output value per hectare 2 Profitability Net farm income 3 Resilience Risk mitigation mechanisms 4 Soil health Prevalence of soil degradation 5 Water use Variation in water availability 6 Fertilizer risk Management of fertilizers 7 Pesticide risk Management of pesticides 8 Biodiversity Use of biodiversity-friendly practices 9 Decent employment Wage rate in agriculture 10 Food security Food insecurity experience scale (FIES) 11 Land tenure Secure tenure rights to land 16
  • 17. ASSESSING SUSTAINABILITY LEVELS 17 1. Green: ‘desirable’ 2. Yellow: ‘acceptable’ 3. Red: ‘unsustainable’ Criteria established by thematic experts, will be fine tuned in light of results of the proposed tests Helps measure progress
  • 18. REPORTING THROUGH A DASHBOARD 18 Example of results for country X in year Y Note: This dashboard is only a simulation and is not from real data
  • 19. NEXT STEPS FOR SDG INDICATOR 2.4.1 Extended pilots ongoing in Bangladesh Finalizing documentation Farm survey questionnaire (PAPI and CAPI versions) Enumerator’s manual Calculation procedures Preparation of training material and e-learning courses is in progress Advocacy and training workshops (global, regional and national) planned in different regions SDG data & communication portal Rolling out in countries 19
  • 21. Education for all Anytime Anywhere Free of charge Transfer of skills and competences Multilingual 500,000 learners throughout the world Public good All SDGs and SDG 4 FAO E-learning Center www.fao.org/elearning
  • 22. CRITERIA FOR THE CHOICE OF THEMES AND SUB- INDICATORS 22 Policy relevance Universality International comparability Measurability Cost effectiveness Minimum cross-correlation
  • 23. SCOPE Included within the scope Crop and livestock production systems  Non-food crops and livestock (example crops such as tobacco, cotton, and livestock raised for non-food products like sheep for wool).  Crops grown for fodder or for energy purposes. Agro-forestry (trees on the farm). Aquaculture, to the extent that it takes place within the agricultural area. For example, rice-fish and similar systems. Both intensive and extensive production systems (including subsistence agriculture). Excluded from the scope State and common land used commonly by several agriculture holdings. Production from gardens and backyards. Production from hobby farms. Land used exclusively for aquaculture. Forest and other wooded lands. Food harvested from the wild. 23
  • 24. AGGREGATE INDICATOR (AT NATIONAL OR OTHER LEVELS) 𝑆𝐷𝐺241 𝑑 = min 𝑛:1−11 (𝑆𝐼 𝑑 𝑛) 𝑆𝐷𝐺241 𝑎+𝑑 = min 𝑛:1−11 (𝑆𝐼 𝑑+𝑆𝐼 𝑎) 𝑛 𝑆𝐷𝐺241 𝑢 = max 𝑛:1−11 (𝑆𝐼 𝑢 𝑛) SDG241d = proportion of agricultural land area that have achieved the ‘desirable’ level SDG241a+d = proportion of agricultural land area that have achieved at least the ‘acceptable’ level SDG241u = proportion of agricultural area that is ‘unsustainable’ 24
  • 25. PREFERRED INSTRUMENT FOR DATA COLLECTION Preferred instrument for data collection is a farm survey questionnaire Aligned with efforts supported by FAO to develop farm surveys as the most relevant instrument for agricultural data (AGRIS) Questionnaire designed as a module that contain the minimum set of questions needed to assess 2.4.1. These questions can be integrated into existing farm surveys Can be complemented with contextual information from other data sources Suggested periodicity: 3 years 17
  • 26. CONDITIONS FOR USING ALTERNATIVE DATA SOURCES Respects the stratification (farm type, agricultural areas, etc.) Captures the same phenomenon as the proposed farm survey At least same quality as the farm survey Compliant with international/national standards and classifications systems internationally comparable Data available at the same level of territorial disaggregation as the farm survey Reference year and periodicity homogenous across the sub-indicators 20

Editor's Notes

  1. Indicator 2.2.1: Prevalence of stunting (height for age <-2 standard deviation from the median of the World Health Organization (WHO) Child Growth Standards) among children under 5 years of age Indicator 2.2.2: Prevalence of malnutrition (weight for height >+2 or <-2 standard deviation from the median of the WHO Child Growth Standards) among children under 5 years of age, by type (wasting and overweight) Indicator 2.a.2: Total official flows (official development assistance plus other official flows) to the agriculture sector Indicator 2.b.1: Producer Support Estimate [The Percentage Producer Support Estimate (%PSE) represents policy transfers to agricultural producers, measured at the farm gate and expressed as a share of gross farm receipts. Transfers included in the PSE are composed of market price support, budgetary payments and the cost of revenue foregone by the government and other economic agents.] Indicator 2.b.2: Agricultural export subsidies
  2. Determining the scope of the indicator: The choice made for indicator 2.4.1 is to focus on crops and livestock production thus excluding forestry, fisheries and aquaculture. Determining the dimensions to be covered: The choice made for indicator 2.4.1 is to include environmental, economic and social dimensions in the sustainability assessment. Choosing the scale for the sustainability assessment: The choice made for indicator 2.4.1 is farm level with aggregation to higher levels. Selecting the data collection instrument(s). Selecting the themes within each dimension, and choosing a sub-indicator for each theme. The sub-indicators should satisfy a number of criteria (described below). Assessing sustainability performance at farm level for each sub-indicator: Specific sustainability criteria are applied in order to assess the sustainability level of the farm for each theme according to the respective sub-indicators. Deciding the periodicity of monitoring the indicator. Modality of reporting the indicator. The set of sub-indicators are presented in the form of a dashboard. The dashboard described above offers a response in terms of measuring sustainability at farm level and aggregating it at national level.
  3. Determining the scope of the indicator: The choice made for indicator 2.4.1 is to focus on crops and livestock production thus excluding forestry, fisheries and aquaculture. Determining the dimensions to be covered: The choice made for indicator 2.4.1 is to include environmental, economic and social dimensions in the sustainability assessment. Choosing the scale for the sustainability assessment: The choice made for indicator 2.4.1 is farm level with aggregation to higher levels. Selecting the data collection instrument(s). Selecting the themes within each dimension, and choosing a sub-indicator for each theme. The sub-indicators should satisfy a number of criteria (described below). Assessing sustainability performance at farm level for each sub-indicator: Specific sustainability criteria are applied in order to assess the sustainability level of the farm for each theme according to the respective sub-indicators. Deciding the periodicity of monitoring the indicator. Modality of reporting the indicator. The set of sub-indicators are presented in the form of a dashboard. The dashboard described above offers a response in terms of measuring sustainability at farm level and aggregating it at national level.
  4. For each sub-indicator, criteria to assess sustainability levels are developed. The concept of sustainability implies an idea of continuous progress and improvement towards better performances across all themes, and such performances can therefore be more or less sustainable. In order to capture the concept of continuous progress towards sustainability, a ‘traffic light’ approach is proposed, in which three sustainability levels are considered for each sub-indicator: Green: desirable Yellow: acceptable Red: unsustainable. While a certain level of subjectivity is unavoidable, this approach allows identification, for each theme, of conditions of critical unsustainability (red), conditions that can be considered ‘ideal’ and, in between, intermediate conditions that are considered ‘acceptable’ but would need to be scrutinized in terms of possible improvements. This approach also acknowledges the trade-offs existing between sustainability dimensions and themes, and the need to find an acceptable balance between them. Each sub-indicator is assessed at the level of the agricultural holding. The sustainability level is then associated with the agricultural land area of the agricultural holding. All sub-indicators for a given agricultural holding therefore refer to the same agriculture land area.
  5. Reporting the indicator The final step in the sustainability assessment process is to aggregate the farm data and report the results at sub-national and national level. In order to report results at subnational level, that level of geographical disaggregation should be a planned sampling domain of the farm survey to which the farm data can be extrapolated. Dashboard The revised methodology proposes to focus on a dashboard presenting the different sub-indicators separately. The dashboard offers several advantages, including the possibility of combining data from different sources and clarity about the main causes of unsustainability: countries can easily visualize their performance in terms of the different sustainability dimensions and themes, and therefore understand where policy efforts can be focused (see below).   Example of dashboard for SDG Indicator 2.4.1 Computation of results and construction of the dashboard is performed for each sub-indicator separately: for each sub-indicator, aggregation at national level is done by summing the agricultural land area of all agricultural holdings by sustainability category (red, yellow or green), and reported as a percentage of the total agricultural land area of the country (minus the common land, as discussed earlier).
  6. Several aspects need to be carefully considered prior to using alternative data sources. First of all, it should be demonstrated that the alternative source gives results of at least same quality as the surveys and ensure international comparability. In order to produce consistent and reliable data as per recommended periodicity, it is advised that the use of alternative data sources may be considered when the available datasets fulfill the following criteria: Can be reflected in or attributed to agricultural land area in the country, considering different farm typologies and agricultural regions; Can be associated with the country’s agricultural productions systems, particularly crops, livestock and the combinations in between; Capture the same aspect/phenomenon as the proposed farm survey (as described in the sub-indicator metadata sheets) with at least a documented same quality, considering scientific standards Are representative of the situation at the national level (with respect to agricultural land area) taking into account main agricultural region types; Are compliant with international/national standards and classifications systems in order to ensure the indicator to be internationally comparable; Data are available at the same level of territorial disaggregation as the farm survey. The ways and means to adjust for under-coverage and non-coverage (when needed) should be clearly devised and described; Data collection year and periodicity are homogenous across the sub-indicators. Finally, using different data sources implies that mechanisms should be put in place at the country level to coordinate regularly the flow of required information generated by various institutions. Alternative data sources may also be used to complement and/or validate farm survey data. This combined approach has the potential to improve the validity and soundness of results, in particular in countries that have well-established monitoring systems and that are able to produce quality information consistently over time. The information from other sources may be used and leveraged in different ways depending on quality and regularity of its collation. For example: Replace farm survey questions, when alternative sources of information are available and respond to the criteria listed above. Complement farm survey questions, by providing additional contextual information helpful to interpret the results. Crosscheck the farm survey results to identify any inconsistencies and ensure the robustness of the indicator. This validation exercise can be done ex-post or during the data collection by providing the external data to the enumerators before going to the field. In this way, the enumerators can probe whether the responses to the farm survey are consistent with the a priori external knowledge. In any case, it is recommended that countries complement the farm survey with a monitoring system that can measure the impact of agriculture on the environment (soil, water, fertilizer and pesticide pollution, biodiversity) and on health (pesticides residues in food and human bodies). This will provide additional information and help crosschecking the robustness of indicator 2.4.1 with regard to the environmental dimension of sustainability.
  7. Policy relevance: the indicator must be easily understood (reasons why it is selected) and the results easily interpreted by policy makers (is agricultural sustainability decreased and why? Which policies needs to be implemented to address the issue?). Universality: the indicator must be relevant for all countries in the world, both developing and developed. International comparability: the way indicators are computed must ensure comparability across countries in order to ensure global reporting. Comparability, however, does not necessarily mean the use of absolute standards. For instance, agricultural wages may be compared with the national minimum wage rate, even if these wage rates vary from one country to another. Similarly, compliance with national environmental standards or nationally recognized certification systems can be considered in computing environmental sub-indicators, even if national criteria vary from one country to another. Measurability: many themes are important sustainability issues but their measurement is difficult, complex or would involve costs that cannot be sustained in the framework of a regular monitoring exercise. To the extent possible, alternative measures have been proposed to maintain indicators that are considered relevant while offering feasible measurement solutions. Cost effectiveness: cost effectiveness is related to measurability. The cost associated with indicator measurement have systematically been considered in relation with the accuracy and reliability of the results obtained through different measurement options. Minimum cross-correlation between subindicators: In selecting a limited set of themes and sub-indicators, efforts were made to reduce cross-correlation between different sub-indicators. High cross-correlation between sub-indicators would imply that two or more sub-indicators capture the same sustainability theme. In this case, the inclusion of one single sub-indicator, instead of several, would be sufficient to adequately measure agricultural sustainability performances.
  8. Determining the scope of the indicator: The choice made for indicator 2.4.1 is to focus on crops and livestock production thus excluding forestry, fisheries and aquaculture. Determining the dimensions to be covered: The choice made for indicator 2.4.1 is to include environmental, economic and social dimensions in the sustainability assessment. Choosing the scale for the sustainability assessment: The choice made for indicator 2.4.1 is farm level with aggregation to higher levels. Selecting the data collection instrument(s). Selecting the themes within each dimension, and choosing a sub-indicator for each theme. The sub-indicators should satisfy a number of criteria (described below). Assessing sustainability performance at farm level for each sub-indicator: Specific sustainability criteria are applied in order to assess the sustainability level of the farm for each theme according to the respective sub-indicators. Deciding the periodicity of monitoring the indicator. Modality of reporting the indicator. The set of sub-indicators are presented in the form of a dashboard. The dashboard described above offers a response in terms of measuring sustainability at farm level and aggregating it at national level.
  9. Aggregation In addition to the dashboard, the methodological note endorsed by the IAEG-SDG indicates that the sub-indicators are to be aggregated into one single indicator at country level, so as to help conveying the messages about performances and progress towards sustainable agricultural through a single measure. At country level, such aggregated indicator can easily be derived from the dashboard. Respecting the ‘traffic light’ approach, the following values can be calculated:   𝑆𝐷𝐺241 𝑑 = min 𝑛:1−11 ( 𝑆𝐼 𝑑 𝑛 ) where: SDG241d = proportion of agricultural land area that have achieved the ‘desirable’ level SId n = proportion of sub-indicator n that is classified as ‘desirable’ min refers to the minimum level of SId n at national level across all 11 sub-indicators SDG241d is the proportion of agricultural area for which all sub-indicators are green. 𝑆𝐷𝐺241 𝑎+𝑑 = min 𝑛:1−11 (𝑆𝐼 𝑑 + 𝑆𝐼 𝑎 ) 𝑛 where: SDG241a+d = proportion of agricultural land area that have achieved at least the ‘acceptable’ level SId n = proportion of sub-indicator n that is classified as ‘desirable’ SIa n = proportion of sub-indicator n that is classified as ‘acceptable’ min refers to the minimum level of (SId n + SIa n) at national level across all 11 sub-indicators SDG241a+d is the proportion of agricultural area for which all indicators are either green or yellow, an acceptable situation, but that could be improved.   𝑆𝐷𝐺241 𝑢 = max 𝑛:1−11 ( 𝑆𝐼 𝑢 𝑛 ) where: SDG241u = proportion of agricultural area that is ‘unsustainable’ SIu n = proportion of sub-indicator n that is classified as ‘unsustainable’ max refers to the highest value of SIu n across all 11 sub-indicators at national level SDG241u = is the proportion of agricultural area for which at least one sub-indicator is unsustainable, and is therefore classified as unsustainable. The performances of countries over time can be measured by the change in the value of SDG241d and SDG241a+d. An increase over time indicates improvement, while decrease indicates degradation.
  10. Data collection instrument An earlier version of the methodology suggested a combination of different data collection instruments to monitor the various sub-indicators. In the consultations undertaken, however, several countries did highlight the difficulties in combining data from different sources and requested that this be avoided to the extent possible. This revised methodology is based on the farm survey as main data collection instrument for all sub-indicators, but it also discusses the possibility of using a combination of different data sources as an alternative option for those countries wishing to do so. By focusing on the agricultural holding and the agricultural land area associated with it, the farm survey offers the most relevant data collection tool for Indicator 2.4.1. This decision is in line with countries’ efforts, supported by FAO, to develop farm surveys as the most appropriate tool for generating agricultural statistics. It also benefits from the FAO work in developing the Agricultural Integrated Survey (AGRIS) programme, which has been recently finalized. The decision to focus on farm survey has implications on the type of information that it is possible to capture in order to cover the different dimensions of sustainability. While farm surveys are well suited to measure the economic dimension of sustainability, they may not be the ideal tool for measuring environmental and social sustainability in terms of impact/outcomes. Typically, environmental impacts of agriculture are measured through monitoring systems like remote sensing, soil and water sampling, or other tools associated with a specific area, rather than with a single agricultural holding. For several environmental themes, it is unlikely that farmers would be able to assess the environmental impact of their farming practices on issues like fertilizer pollution or pesticide impact. Using a farm survey instrument, instead of environmental monitoring systems, therefore implies moving from measuring outcome/impact to assessing farmers’ behavior. Whenever possible, however, the revised methodology continues to focus on measuring outcomes. The sub-themes under the social dimension are usually best captured through household surveys. While in the majority of cases, especially in developing countries, agricultural holdings are closely associated with a given household, this is not always the case, and therefore capturing the social dimension of sustainability through a farm survey poses certain challenges. Annex 1 also lists the minimum set of data items needed to produce the relevant information for the sub-indicator. Moreover, questionnaire modules that contain the minimum set of questions needed to measure each sub-indicator at farm level have also been designed. These questions can be integrated into existing farm surveys for ensuring a comprehensive assessment of indicator 2.4.1.
  11. Several aspects need to be carefully considered prior to using alternative data sources. First of all, it should be demonstrated that the alternative source gives results of at least same quality as the surveys and ensure international comparability. In order to produce consistent and reliable data as per recommended periodicity, it is advised that the use of alternative data sources may be considered when the available datasets fulfill the following criteria: Can be reflected in or attributed to agricultural land area in the country, considering different farm typologies and agricultural regions; Can be associated with the country’s agricultural productions systems, particularly crops, livestock and the combinations in between; Capture the same aspect/phenomenon as the proposed farm survey (as described in the sub-indicator metadata sheets) with at least a documented same quality, considering scientific standards Are representative of the situation at the national level (with respect to agricultural land area) taking into account main agricultural region types; Are compliant with international/national standards and classifications systems in order to ensure the indicator to be internationally comparable; Data are available at the same level of territorial disaggregation as the farm survey. The ways and means to adjust for under-coverage and non-coverage (when needed) should be clearly devised and described; Data collection year and periodicity are homogenous across the sub-indicators. Finally, using different data sources implies that mechanisms should be put in place at the country level to coordinate regularly the flow of required information generated by various institutions. Alternative data sources may also be used to complement and/or validate farm survey data. This combined approach has the potential to improve the validity and soundness of results, in particular in countries that have well-established monitoring systems and that are able to produce quality information consistently over time. The information from other sources may be used and leveraged in different ways depending on quality and regularity of its collation. For example: Replace farm survey questions, when alternative sources of information are available and respond to the criteria listed above. Complement farm survey questions, by providing additional contextual information helpful to interpret the results. Crosscheck the farm survey results to identify any inconsistencies and ensure the robustness of the indicator. This validation exercise can be done ex-post or during the data collection by providing the external data to the enumerators before going to the field. In this way, the enumerators can probe whether the responses to the farm survey are consistent with the a priori external knowledge. In any case, it is recommended that countries complement the farm survey with a monitoring system that can measure the impact of agriculture on the environment (soil, water, fertilizer and pesticide pollution, biodiversity) and on health (pesticides residues in food and human bodies). This will provide additional information and help crosschecking the robustness of indicator 2.4.1 with regard to the environmental dimension of sustainability.