support countries enhance their analysis and monitoring of farm typology & their...

WAW Support countries enhance their analysis and

monitoring of farm typology& their transformations, in support of SDG

Quality of information available on FF is not good enough:• Unit of measure is usually technical: Production vs. livelihood

• Limited information on functional typologies of FFs => required to understand dynamic of rural transformation.

• Data available is usually on food production vs. other functions• functions and overall performance of farms• HH income portfolio including off-farm employment of family members• Environmental performance at farm & landscape level

(From Study on Small-scale Agriculture in the NENA region. FAO, CIRAD, CIHEAM. 2015)

Target 2.3 doubling farmproductivity of small holders &disaggregated monitoring

Target 2.4 sustainable and resilient practices

Why typology studies and monitoring needed ?SP3 rationale and SDG

Statistics often missing or not “useable’ (lost & forbidden census…)

⇒ Such may require better statistical data but also goes beyond, requiring diary, discussions, several surveys etc..

⇒ WAW proposes answers via typology based monitoring

• Goal: Enhance national capacities to analyze and monitor diversity of farms and their transformations to inform policy dialogue

SCALE

GLOBAL

NATIONAL

LOCAL

Country studies

Country « watches »

Improvement on the basis of fieldexperience + network exchanges:

adapt to field needsREGIONAL

Better targeted policy, extension & long term

monitoring

Inclusive process & Policy dialogue Local impacts for long term

WAW national outputs & processesNationally driven and adapted

GLOBAL WAW articulatedto SPs and global

initiatives

Proposing flexible approach

WAW in a nutshell

FF visibility, voice &

empowerment

SO3 Reduce

Rural Poverty

Overview of the diversityof farms

Translate the complexityinto pertinent information for appropriate actions

B. SHORT TERM: STUDIES C. LONG TERM: Enhanced MONITORING

WHAT WE DO:

A. Inception assessment, consultations => agreed vision & project formulation

Typology & transformation studies

consultations & multi-

stakeholders governance

Scenarios & policy analysis

Improved trust &

Permanent dialogue

& governance structure

Recommendations for surveys

Prototype Information system (e.g. tabulated

database)

Collective vision & project document to reinforce

monitoring capacity

PRODUCT INCLUSIVE PROCESS PRODUCT

INCLUSIVE PROCESS

PRODUCT INCLUSIVE PROCESS

?

WAW Secretariat: FAO

VietnamMalawi

France

Madagascar

Brésil

Argentine

Sénégal

Tunisie

Niger

South Africa

El Salvador

US

Philippines

Costa Rica

UE

Uruguay

Cote d’Ivoire

Bulgaria

Diverse network of experts from 9 countries (GREY) and various institutions

Nicaragua

Burundi

7 Country benefiting from current projects (YELLOW) to pilot such work : studies & monitoring system

Where and how

3 from past support, request (green)

Burundi

Presenter

Presentation Notes

The World Agricultures Watch (WAW) Initiative, set in FAO with support of IFAD, CIRAD and France, aims to support an agile network of partners in documenting and building awareness on agricultural structural transformations and their impacts on sustainable development to inform policy dialogue at national and international levels. It notably develops common methods and exchanges to support countries develop two types of deliverables Studies on typology of holdings and transformations Reinforced monitoring systems At the moment, partnership include 6 beneficiary countries in yellow: El El Salvador, Tunisia, Senegal, Niger, Madagascar and Vietnam. In addition, partners (in grey) from Argentina, Brazil, Uruguay, USDA/ERS, Cote d’Ivoire, European Union and Philippines bring their country experience and expertise to the development of methods and exchanges. Other countries expressed interest in developing further typology. In addition, partnership are developed with the Global strategy for improved statistics and the follow up of the International Year of Family farming. => The following parts will present you some illustrations of the kind of work done under the two deliverables

Household / Non-

householdFarm Size &/ or

Access to market;

Commodity specialization

A distinction based on the SNA

Ideally, based on a measure of economic sizeRelevant to aggregate agricultural production and market integration

Based on main product Orientation & commodity diversification

Integrates with existing statistical systemOption: non HH farm distinguished as FF, patronal, corporations by labor use &/or legal status

Do households allocate labor to nonfarm work activities?

Nonfarm income can be used to maintain the farm and family duringtimes of low production or prices, andto expand the farm productive capacityCan distinguish “Hobby farm”/minor

For households, sources of income

An International Typology Classification: Potential Concepts based on extensiveliterature review and expert consultations

Ex. Crop, mixed, animal

Extract GSARS typology presentation ICAS 2016, Neli Georgieva, Ahearns, Even, Saravia

Presenter

Presentation Notes

Notes: Of course, all categories are subject to data availability. This is the major constraint. The top 3 categories (but especially top 2) are relevant for all farms, whether managed by a family or not (e.g., cooperative, corporation). The nonfarm work category is only relevant for households and where the household is jointly “managed” with the farm. Considered highest level of classification (Level 1) distinction between household holdings and non household holdings (compatible with SNA) Option: non HH farm may be distinguished as Family farm, patronal, corporations by labor use & legal status Possible alternatives for next levels: Level 2:Farm size; or Economic size Level 3: Commodity specialization or Access to market; Level 4: Non-farm work (for HH sector) notably to distinguish “Hobby farm / minor agriculture”

Objectives: Operational method to represent diversity & transformation trends, articulating statistics and qualitative data to face data issues

TerritoriesProduction systems

Farm management,labor & marketorientation

NATIONAL TYPOLOGY APPROACH

Common criteria & POVERTY

Who? Where ? How many?Trends

Strategies, performance, transformationsLocal dialogue & action points for policy & interventions

Work and validation with local actors, inclusive governance: inclusive policy dialogue & social legitimacy / validity

SYSTEMIC & DYNAMIC

Type 1

Type 2

Type 3

A1

A2

A3

A..

A4

A1

A2 A

3

A..

A1 A

2

A3A4A

5

A..

TERRITORIES

2. STATISTICS 3. SURVEY REFERENCE FARMS

National

1. METHODS

QUANTITATIVE

Farm incomeOff farm income

Comparable to FADN typology based system

Presenter

Presentation Notes

In the WAW approach we think that the typology is a relevant method to represent the diversity of farms and their past trends. In order to face data issues, we propose a method which articulate quantitative and qualitative data. To select indicators to do the typology we propose main domains and the country choose what is the most relevant and suitable to their own context. Then with statistic data, at national scale, a first typology is done. It allows to have a gobal overview of the agriculture in the countrt: who are the farmes, where they are, and how many are they in each type? After that, to have more relevant information, we suggest to select for each main type, farms of reference which are reprensentative and thenaks to more qualitative data capture the strategies, the performance and the transformations of each type. It’s a dynamic part of the typology. Of course, each step of the approach is done with the local actors and not by us directly in order to creat a inclusive policy dialogue .

A B C D E F

Tables, maps, portraits to assess characteristics,& initiate dialogue to prioritize local assessment with actors

Niger Typology from Rulis data base

Agric income (green)Total income (blue)

CFA

% 75% 5 5 2 4 8

NEXT: national policy dialogue and Local dialogue & assessment of reference farms in specific territory

Presenter

Presentation Notes

Here it’s a the work initiated in Niger : it’s a typology based on the Rulis database. With the combinaison of the agricultural income and the total income we obtain 6 types and we compare it to 2 different thershold: yhe national poverty line and the national food security thershold. Then, with further analyse, we could describe the type thanks to other indicators, assess characteristics on diagramm and visualize them on maps.

Example of a National Typology in Salvador

Inclusive process & dialogue led to consensual Distinguishing Criteria and Thresholds for El Salvador Typology as well as agreed recommendations on data to capture farm types

Example of a National TypologyDistinguishing Criteria and Thresholds for El Salvador Typology – ctd.

Data base adapted & connection with Rulis

GLOBAL

NATIONAL

REGIONAL

LOCAL

Statistics : data allow comparisonbetween countries

Local survey, national statistic

Nationally representative data

Locally representative data

Ex: Niger RULIS

Ex: Tunisie ; Salvador ; Madagascar: Nationally owneddatabase

RULISMore countries

Concrete recommendations for qualifiers / typology domains

Base for the typology

National cleaned database

Technical suport

- Farm management and labor use: who is operating and working the farm? Is there a status (FF & SNA distinction)

- Production system and « OTEX » - Link with the market, % sales- Share between off/on farm income- Income classes: add more « absolute » comparable, compared to nat. Or int. poverty line,

minimal income etc.- …- Be able to combine qualifiers & more friendly display

Need to involve national policy makers incl. PO and smallholder representatives!

Some recommendations to articulate rulis with country work

Thank you

El Salvador, typology training

Tunisia, launching seminar Senegal, launching seminar

Study tour in France with all the country

FADN: Exemple of typology based monitoring• Farms from sample and from the observation field (structural survey) are stratified similarly through the typology• Individual ponderation for each farm of the sample to calculate average results

Ex: Niger Pertinent indicators missing for the WAW typology

• % of the household where a member participate in a cooperative or a farmer's group (RLM & dataportraits)

• % of farms using superficial/deep/other water irrigation (dataportraits)• % of household using motorized equipment (RLM)• % of household using building (RLM & dataportraits)• Average annual amount of private transfer/credit/international remittance/social

assistance per capita (dataportraits)• Age of the holder (RLM & dataportraits)• Agriculture training background of the household headed (RLM & dataportraits)• Agricultural own-account and contributing family workers/hired labor/seasonal

workers , share of total agricultural employment (%) (RLM & dataportraits)• Average distance from the nearrest daily/weekly market AND health facilities

(dataportraits)• % of the production sold (RLM & dataportraits)• Area of temporary crops harvested (RLM & dataportraits)• Crop farm households using chemicals/organic/inorganic fertilizer (RLM &

dataportraits) • Value of food produced/worker (RLM & dataportraits)• Mean yield of each main crop (RLM & dataportraits)• Worker / household size (RLM & dataportraits)

Presenter

Presentation Notes

We underlight here some indicators which are missing for the Niger typology and which could facilitate the typology building for other country.

Need of Farm Typology at International & National levels: GSARS rationale

• Rapid structural changes• Need for policy makers to carefully consider the diversity of

holdings and their transformations in the context in which they operate

• Multi-faceted policy challenges, incl. challenges exogenous to agriculture => multidimensional typology needed:

• Which contribute the most to aggregate production?• Which are the most food insecure?

• Contemporary issues such as sustainability, food safety and nutrition, gender equity, and food insecurity, SDG

Extract GSARS typology presentation ICAS 2017, Neli Georgieva, Ahearns, Even, Saravia

Why typology studies and monitoring needed ?

support countries enhance their analysis and monitoring of farm typology & their...

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