Methodology and steps for computing indicators and 2.3.2

(1)

Naman Keita Office of Chief Statistician

Methodology and steps for computing indicators 2.3.1 and 2.3.2

Online training on SDG Indicators 2.3.1 & 2.3.2

17/18/19 August 2021

(2)

RECALL FROM SESSION 1 DAY 1 (AIDA

KHALIL)

(3)

Goal 2: Zero Hunger

Target 2.3: “By 2030, double the agricultural productivity and incomes of small-scale food producers, in particular women, indigenous peoples, family farmers, pastoralists and fishers, including through secure and equal access to land, other productive resources and inputs, knowledge, financial services, markets and opportunities for value addition and non-farm employment”

• Indicator 2.3.1: The volume of production per labour unit by classes of farming/pastoral/forestry enterprise size (Tier II)

• Indicator 2.3.2: The average income of small-scale food producers, by sex and indigenous status (Tier II)

(4)

Goal 2: Zero Hunger (2)

• Both indicators were initially classified in Tier III: “No internationally established methodology or standards are yet available for the indicator, but methodology/standards are being (or will be) developed or tested”

• Lack of a methodology mainly linked to the lack of a common and clear international definition of the target population – i.e. the small-scale food producers

• Methodology proposed by the FAO covers 3 areas:

• Identification of the target population

• Computation of indicator 2.3.1

• Computation of indicator 2.3.2

(5)

SDG INDICATOR 2.3.1:

Labour Productivity of

Small-scale Food Producers

(6)

SDG indicator 2.3.1 – Methodology

CONCEPT OF AGRICULTURAL PRODUCTIVITY

• Standard definition of productivity: “Productivity is commonly defined as a ratio of a volume measure of outputs to a volume measure of input use.” (OECD Manual for Measuring Productivity, 2001)

• Productivity measures the amount of output produced by an economic unit (country, industry, sector, farm or other economic operators) given a set of resources and inputs.

• Productivity can be measured for a single economic entity, such as the farm or commodity, a group of farms, at any geographical scale depending on the purpose of the inquiry.

• More information in the Technical Report Series of FAO, “Productivity and Efficiency Measurement in Agriculture: Literature Review and Gaps Analysis”.

(7)

SDG indicator 2.3.1 – Methodology

CONCEPT OF AGRICULTURAL PRODUCTIVITY

• The above concept can be formalized for agriculture sector as follow:

Agricultural productivity (Prod) is the ratio of outputs (O) to inputs (X), expressed either in volumes (value in constant price) or, when possible, in physical quantities (kg, tons,

etc.).

• For any period, t:

𝑃𝑟𝑜𝑑

_𝑡

= 𝑂

_𝑡

/𝑋

_𝑡

(Guidelines for the measurement of productivity and efficiency in agriculture

published in the framework of the Global Strategy to Improve Agriculture and Rural Statistics in 2018 (GSARS, 2018))

(8)

SDG indicator 2.3.1 - Computation

• Indicator 2.3.1 monitors productivity as “The volume of production per labour unit by classes of farming, pastoral, forestry enterprise size.”

• This results in the following formula :

𝑨𝒈𝒓𝒊𝒄𝒖𝒍𝒕𝒖𝒓𝒂𝒍 𝑳𝒂𝒃𝒐𝒖𝒓 𝑷𝒓𝒐𝒅𝒖𝒄𝒕𝒊𝒗𝒊𝒕𝒚 = 𝑽𝒐𝒍𝒖𝒎𝒆 𝒐𝒇 𝑷𝒓𝒐𝒅𝒖𝒄𝒕𝒊𝒐𝒏 𝑳𝒂𝒃𝒐𝒖𝒓 𝒊𝒏𝒑𝒖𝒕

• In order to standardize and aggregate different agricultural activities, the volume of production is quantified by taking the monetary value of the agricultural output (revenues) expressed in constant PPPs.

• Depending on the source of the data, different formulas can be

used to compute Agricultural Productivity.

(9)

SDG indicator 2.3.1 – Computation

FORMULA WITH NO SAMPLING WEIGHT

This applies when data is collected through:

• Complete enumeration census or survey

• Sample survey using self-weighted design:

• Example for a two-stage design, self-weighting is achieved by selecting clusters (e.g. enumeration areas) with probability-proportional to-size (PPS) at the first stage and at the second stage, a fixed number of units (holdings for example) within a cluster (selected EA) is selected (e.g., always select n=5 at the 2^nd

stage).

• This type of design is frequently used in many developing countries

agricultural surveys.

(10)

SDG indicator 2.3.1 – Computation

FORMULA WITH NO SAMPLING WEIGHT

• Given i agricultural activities, including crops, livestock,

fisheries and forestry production, and j [1,…,n] small-scale food producers defined in the previous session yesterday as a subset of all N [1,…,k] food producers,

• The SDG indicator 2.3.1 must be computed using the following formula:

• 𝑆𝐷𝐺 2.3.1 = 𝐼

_2.3.1^𝑡

=

σ_𝑗=1^𝑛 (^{σ𝑖 𝑉𝑖𝑗}^{𝑡 𝑝}^𝑖𝑗

𝑡 𝐿𝑑𝑗𝑡 ) 𝑛

(11)

SDG indicator 2.3.1 – Computation

FORMULA WITH NO SAMPLING WEIGHT

where:

 𝑉

_𝑖𝑗^𝑡

is the physical volume of agricultural product i produced by the small-scale food producer j during year t;

 𝑝

_𝑖𝑗^𝑡

is the constant sale price received by the small-scale food producer j for the agricultural product i during same year t;

 𝐿𝑑

_𝑗^𝑡

is the number of labour days utilized by the small- scale food producer j during year t;

 𝑛 is the number of small-scale food producers as identified

above.

(12)

SDG indicator 2.3.1 – Computation

• All values in local currency units need to be

converted in Purchasing Power Parity Dollars (PPP

$).

• Information on PPP dollars is available from the

World Bank World Development Indicators, at

http://data.worldbank.org/indicator/PA.NUS.PP

P

(13)

SDG indicator 2.3.1 – Computation

WITH SAMPLING WEIGHT

When data is coming from a sample survey (not self- weighted design or complete enumeration) sampling weight should be considered in computing the indicators.

A (possible) formula to be used is:

(14)

SDG indicator 2.3.1 – Methodology

WITH SAMPLING WEIGHT

where:

 𝑉

_𝑖𝑗^𝑡

is the physical volume of agricultural product i produced by the small-scale food producer j during year t;

 𝑝

_𝑖𝑗^𝑡

is the constant sale price received by the small-scale food producer j for the agricultural product i during same year t;

 𝐿𝑑

_𝑗^𝑡

is the number of labour days utilized by the small- scale food producer j during year t;

 𝑤

_𝑗

is the sampling weight for producer j

(15)

VOLUME OF PRODUCTION FROM AGRICULTURAL ACTIVITIES

• Agricultural activities include those generated by crop, livestock, fisheries and forestry.

CROP PRODUCTS (VALUE IN PPP)

Crop sold

Crop for own consumption

Crop used for feed

Crop stored

Crop used for by products

Crop given as gift

Crop saved for seed

Crop used for paying labour

Crop used for paying rent and/or inputs

Crop exchanged in sharecropping agreement.

LIVESTOCK PRODUCTS (VALUE IN PPP).

Livestock sold (live animals)

Livestock gifts given away

Livestock products sold

Livestock products self-consumed

Livestock products self-used

Livestock products used as pay (for other goods for example)

Livestock products used to repay credit.

(16)

VOLUME OF PRODUCTION FROM AGRICULTURAL ACTIVITIES

FISHERY PRODUCTS (VALUE IN PPP)

• captured fresh fish sold

^,

• captured and processed fish sold,

• captured fresh fish for own consumption,

• captured and processed fish for own consumption (dry fish for example),

• traded fresh fish sold,

• traded processed fish sold.

(17)

VOLUME OF PRODUCTION FROM AGRICULTURAL ACTIVITIES

FORESTRY PRODUCTS (VALUE IN PPP)

• forestry products sold,

• forestry products used for paying inputs,

• forestry products given out in sharecropping agreement,

• forestry products for own consumption,

• forestry products stored,

• forestry products used for paying labor,

• forestry products used for paying rent,

• forestry products used for paying inputs,

• forestry products given out in sharecropping agreement.

(18)

LABOUR INPUT

• Different types of labour to be considered: all forms of paid and unpaid labour, including:

• family labour,

• hired labour (temporary and permanent workers) and

• exchange labour.

(19)

LABOUR INPUT

• Computation of the labour input: different approaches are available to measure this denominator:

 Number of workers,

 Number of days worked,

 Number of hours worked.

• The most accurate measure of labour volume seems to be the number of hours worked in a year

• However, problems of data availability make the annual number of working days the most viable option.

• Even this information is not widely available as discussed later

(20)

SDG indicator 2.3.1 – Methodology CHALLENGES

• Despite the availability of a detailed methodological note, few

countries have been able to produce data needed to compile SDG 2.3.1 up to know.

• Some of the major challenges include:

NUMERATOR

• The need for holding/farm level micro data for all variables used for the computation of 2.3.1 => integrated surveys (such as FAO AGRIS or WB LSMS/ISA) or administrative sources (farm registry).

• Example when crop cutting is used, production is derived from yield data but this is available at a domain level, not for individual holdings=> Use of

proxies such as farmers declaration or affect same yield to all holdings in a domain?

• Farm gate prices for each products is required but not always available=>use of proxies such as rural market prices or other sources?

(21)

SDG indicator 2.3.1 – Methodology CHALLENGES

• Many agricultural production surveys have limited coverage in terms of agricultural activities (crop, livestock, fishery, forestry).

• Livestock (numbers and/or products), fishery and forestry are often missing in agricultural surveys

• The computation should keep consistency between the Numerator (activities included) and the Denominator (corresponding labour input)

• When computing the indicator, the metadata should

indicate what activities are included.

(22)

SDG indicator 2.3.1 – Methodology CHALLENGES

DENOMINATOR

• Labor is a difficult variable to measure accurately in agricultural surveys and may be costly:

• high presence of seasonal and part-time workers,

• labor of family members, and

• long collection time among others.

• High risk of non sampling error which could lead to inconsistencies.

• => Other factor productivity to be considered instead of Labour?

(the same formula can be adapted).

(23)

0 5 10 15 20 25 30 35 40

Burkina Faso 2014

Ethiopia 2015

India 2012

Malawi 2013

Mali 2014

Niger 2014

Nigeria 2016

Panama 2008

Tanzania 2013

Uganda 2013

Agricultural output per labour day, (PPP$ per day worked)

Non-small-scale producers Small-scale producers

(24)

SDG indicator 2.3.1 – Methodology CHALLENGES

• WHAT IS THE SITUATION IN

BANGLADESH AND WHAT ARE THE CHALLENGES AND POSSIBLE

SOLUTIONS FOR COMPUTING SDG

2.3.1?

(25)

SDG INDICATOR 2.3.2:

Income of Small-scale Food Producers

(26)

SDG indicator 2.3.2 - Methodology

• Indicator 2.3.2 refers to “the average income of small- scale food producers, by sex and indigenous status.”

• The computation of on-farm income of the agricultural holding adopted by FAO includes:

Income from cropping activities;

Income from livestock;

Income from fishery;

Income from forestry.

(27)

SDG indicator 2.3.2 - Methodology

• These income components refer to gross income (Y) that is defined as the operating surplus (i.e. revenues (R) minus operating costs (C)) without taking into account the depreciation of assets as such information is usually not available from most data sources. In formula:

𝒀 = 𝑹 − 𝑪 + 𝚫𝑺 i.e.

Gross Income = Revenues – Costs + (Stock Variation, when available)

• All the monetary variables should be expressed in constant PPP and deflated,.

(28)

SDG indicator 2.3.2 – Computation NO SAMPLING WEIGHT

• Given i agricultural activities, including crops, livestock, fisheries and forestry activities, and j [1,…,n] small-scale food producers defined as in the first section as a subset of all N [1,…,k] food producers, the SDG indicator 2.3.2 must be computed using the following formula:

• =

^σ^𝑗=1

𝑛 𝑤_𝑗 σ_𝑖𝑉_𝑖𝑗^𝑡𝑝_𝑖𝑗^𝑡 −𝐶_𝑖𝑗^𝑡

σ_𝑗=1^𝑛 𝑤_𝑗

where:

• 𝑉_𝑖𝑗^𝑡 is the physical volume of agricultural product i sold by the small-scale food producer j during year t;

• 𝑝_𝑖𝑗^𝑡 is the constant sale price received by the small-scale food producer j for the agricultural product i during year t;

• 𝑐_𝑖𝑗^𝑡 is the production cost of agricultural product i supported by the small- scale food producer j during year t;

• 𝑛 is the number of small-scale food producer.

(29)

SDG indicator 2.3.2 – Computation SAMPLING WEIGHT

• The following formula should be used:

• 𝑆𝐷𝐺 2.3.2 = ^σ^𝑗=1

𝑛 𝑤_𝑗 σ_𝑖 𝑉_𝑖𝑗^𝑡𝑝_𝑖𝑗^𝑡 −𝐶_𝑖𝑗^𝑡 σ_𝑗=1^𝑛 𝑤_𝑗

where:

• 𝑉

_𝑖𝑗^𝑡

is the physical volume of agricultural product i sold by the small-scale food producer j during year t;

• 𝑝

_𝑖𝑗^𝑡

is the constant sale price received by the small-scale food producer j for the agricultural product i during year t;

• 𝑐

_𝑖𝑗^𝑡

is the production cost of agricultural product i supported by the small-scale food producer j during year t;

• 𝑤

_𝑗

is the sampling weight for producer j.

(30)

Crop Income

Revenues (+) Costs(-)

A. Crop production

Crop sold Inputs paid in cash

Crop for own consumption Land Rent

Crop used as feed Technical assistance/extension costs

Crop stored Crop saved for seed

Crop used for byproducts Crop used for paying labour

Crop given as gift Crop used for paying rent

Crop saved for seed Crop used for paying inputs

Crop used for paying labour Crop given out in sharecropping agreement

Crop used for paying rent Crop wasted

Crop used for paying inputs

Crop given out in sharecropping agreement Crop wasted

B. By-products production

By-product sold Crop used for by-products

By-product used for barter or in kind payment Total value of input purchased, incl. reimbursed in kind By-product used for own consumption

By-product given as gift

C. Sharecropping activities Crop received in sharecropping agreements

(31)

Livestock Income

Revenues (+) Costs(-)

A. Livestock activities: change in the cash value of the stock at the average price

Livestock sold (alive) Livestock bought

Livestock gifts given away Livestock additional expenditures Crop used as feed

Technical assistance/extension costs B. Livestock products and by-products production

Livestock products sold Livestock products additional expenditures Livestock products self-consumed Livestock products used to pay other goods Livestock products self-used [also a cost in

crop, e.g. dung used as fertilisers] Livestock products used to repay credit Livestock products used to pay other goods

Livestock products used to repay credit C. Livestock stock variation

= Closing/End-of-Year value – Initial/Beginning-of-Year value (if available)

(32)

Fisheries and Forestry income

Revenues (+) Costs (-)

A. Fish-catching and processing activities Captured fresh fish sold

Captured and processed fish sold

Captured fresh fish for own consumption Captured and processed fish for own consumption

Fishing gear expenditures Hired labour expenditures

B. Trading activities Traded fresh fish sold

Traded processed fish sold

Fresh fish purchases

Processed fish purchases Other related costs

C. Rental of fishery gears

Revenues (+) Costs (-)

Income from forestry production Income from forestry services

Input costs (seedlings, fertilisers, hired labour, etc.)

Machine rental costs Land rental costs

Other related costs Fisheries income

Forestry income

(33)

SDG indicator 2.3.2 – Methodology CHALLENGES

• Some of the data challenges related to this indicator include:

• Scarcity of cost of production surveys and the lack of detailed data on cost of production for crops, livestock, fishery and forestry products

• Lack of detailed price data for calculation of holding level

revenue and income.

(34)

Indicator 2.3.2: Average Income of Small-scale Producers (PPP$ per year)

0 1000 2000 3000 4000 5000 6000

All producers Small scale producers

(35)

SDG indicator 2.3.2 – Methodology CHALLENGES

• WHAT IS THE SITUATION IN

BANGLADESH AND WHAT ARE THE CHALLENGES AND POSSIBLE

SOLUTIONS FOR COMPUTING SDG

2.3.2?

(36)

Thank you

For more detailed information on Indicator 2.3.1 and 2.3.2

http://www.fao.org/sustainable-development-goals/indicators/231/en/

http://www.fao.org/sustainable-development-goals/indicators/232/en/