Price Monitoring and
Program Flexibility: Lessons
and Challenges
Dina Brick, Giulia Frontini
TOPS Cash Learning Series
15 September 2015
Overview
2
•
MARKit: Price monitoring experiences to date
•
So what if markets change? Examples of program adjustments
•
Case study from DRC: Designing for program flexibility
•
Challenges
MARKit: what it is and
experiences to date
3
MARKit Objectives
1.
Food assistance program managers are guided to determine whether an
intervention is having an adverse impact on markets, or whether external
changes to the market environment call for a change in the strategy of the
intervention.
2.
Price analysis/monitoring is integrated into all types of food assistance
programs.
3.
Price data is analyzed by project managers in real time, and used to make
adjustments to programs.
Why monitor prices?
5
MARKit Includes
Key Question
Get Prepared
Assess the
Risk
Gather
Data
Calculate
Price
Changes
Investigate
the Factors
Adjust if
necessary
What is needed
to be successful
in
implementation
of MARKit?
What is the risk
that the
intervention or
external market
forces will affect
prices?
How do we collect
standard,
comparable price
data?
Are prices
changing? Where
and how?
What factor(s) is
(are) causing the
price changes?
What is the risk
of continuing the
intervention?
How can
negative price
impacts be
mitigated?
Guidance on
resources
needed, advice
on skills and staff
time necessary
Key criteria for
high risk
programs, and a
checklist for
determining risk.
Commodity
identification
guidelines,
standard metrics,
enumeration
processes
Guidance for
tracking price
changes,
recommended
analyses for Low
and High Risk
programs
Potential factors of
price changes,
price analysis tools,
guiding questions
for key informant
interviews
Adaptation
guidelines to
respond to
market impacts
Step 1: Get Prepared
• Understand markets
• Gather information
• Make a resource plan
• Prepare team and materials
Get Prepared
Assess the
Risk
Gather
Data
Calculate
Price
Changes
Investigate
the Factors
Adjust if
necessary
Step 2: Assess the Risk
Risk factors:
1.
Size of intervention(s) relative to size of
market: population
2.
Size of intervention(s) relative to size of
market: volumes
3.
Potential external risk
4.
Timing of intervention in seasonal calendar
5.
Availability of market baseline
6.
Market integration
7.
Market competition
8.
Households reliance on markets for food
purchases
HIGH
RISK
LOW
RISK
Step 3: Gather Data
Type of market
Central market
Local supply/ wholesale market
Intervention markets
“Downstream markets” (if any)
Comparison markets (not necessary if you have good
secondary data for an area, but likely you’ll need
this)
# of markets to monitor
1-2
1-2 for each “marketshed”
3-4 for each “marketshed”
1 for each “marketshed”
1-2 for each “marketshed”
Step 4: Calculate Price Changes
Step 5. Investigate the factors
11
Niger example: seasonality
12
Turkey example: exchange rate
13
So…. How do we know what to do about it?
14
14
So…. How do we know what to do about it?
15
15
The decision to adjust
Once the factors contributing to the price change are identified
and analyzed:
1. Review the relationship between the intervention and the
market system:
• What is the risk that continuing the intervention will
exacerbate the price change or other market distortion?
• If the cause is external, can our program adjust to help
mitigate the price changes?
2. Assess the risk of changing the program: food security
objectives, impact on market actors, transparency, and Do
No Harm.
3. Assess the feasibility of changing the program: is it worth
it?
Contingency planning from the outset
Variation observed
Prices rise and stay
up for more than 1-2
weeks; people can’t
buy as much with
the same amounts
17
Likely cause
Exchange rate has
fluctuated
Possible program options
If markets can still respond to demand, consider
increasing voucher values (add a booklet/ HH?)
We can now reach more people with the same budget,
so consider increasing the number of beneficiaries
Our intervention:
Increase the number of vendors, or include vendors
vendors and markets
from nearby supply markets
have limited capacity,
Stagger voucher distributions so that fewer
and so the market can’t beneficiaries receive them at once, to enable vendors
respond to increased
to restock
demand
Consider mixed modalities, and couple vouchers with
distributions of key commodities
Add more vendors to the project
Provide small grants to vendors to temporarily
increase their stocks
Vendor collusion or
Hold meeting with village council to determine
other vendor actions
appropriate action; may include awareness-raising or
banning certain vendors from the project
Work with village councils and set a price ceiling for
key goods; post these widely, and revise them weekly
Supply chain is
Work with vendors to bring in goods via a different
damaged, due to
supply chain
insecurity, road blocks, Replace vouchers with distributions for key
or other supply shock
commodities
Case Study: DRC
18
DRIVE I - Background
19
•
Project Name: Displaced and Returnee Populations Invite Recovery in
Eastern DRC
•
Donors: USAID (OFDA & FFP)
•
Scope: Non-Food-Item, Food Assistance, Cash-for-Work
•
Duration: Phase I: May 2014–July 2015 / Phase II: Aug. 2015–July 2016
•
Direct beneficiaries: 13,000 HHs (78,000 individuals)
•
Zones of intervention: 4 provinces (North & South Kivu, Katanga, Maniema)
•
Assistance modalities: 3 rounds of vouchers, direct distribution, mixed.
Phase I:
–
66% of beneficiaries assisted through voucher fairs
–
$45 food vouchers / half a food basket calculated on a 6 persons HH
–
$75 NFIs vouchers / standard NFI kit
Modality Response Tree
Humanitarian Crisis
& Needs Assessment
Strong needs, context & market
assessments allow for a more
tailored response to identified
needs on the ground.
Feasibility Study
& Market Study
1
2
3
Direct
Distribution
Cash Based Assistance
(Voucher fairs)
Mixed
Modality
MONITORING
Market Tools
21
•
Market Registration – Size, profile, existence of banking services,
cellular coverage, etc.
•
Market Study – Profile of vendors, capacity to meet increase in
demand, prices, market integration, competition, etc.
•
Feasibility Study – beneficiaries preferences, access to markets,
perception on commodities’ availability and prices, preferred
assistance modalities, perceived risks linked to cash based assistance.
•
MARKit (price monitoring) – monitoring of key commodities before,
during and after DRIVE intervention
DRIVE staff carry out food price
monitoring in Lubumbashi’s Kenya
market. February 2015.
22
Results – Kato, Katanga Province
900
Summary of findings:
800
RICE
700
600
500
Kato-rice
400
Lwanza-rice
300
Kilwa-rice
200
Lub-rice
100
• Significant price changes for a
few commodities in multiple
markets (Scenario C Seasonality, local supply shocks,
global food prices, policies)
0
800
BEANS
700
600
500
Kato-bean
400
300
200
100
0
23
Lwanza-bean
• As per KII results changes are
linked to commodities’ low
availability due to :
• Insecurity in the area of
production (beans)
• Planting season (rice)
Kilwa-bean
Lub-bean
• Price change not attributable to
DRIVE’s intervention; CRS to
consider direct distributions for
future activities
Achievements
•
Large scale data collection of market price data in an emergency
context
•
Monitoring of 15 markets linked to DRIVE areas of intervention
•
Monitoring of food commodities: beans, rice, maize, cassava,
vegetable oil, palm oil and salt
•
Monitoring of non-food-items including child clothing, taurpalins,
cover, matress and jerrycan
•
Review of tools, data collection and analysis methodology
•
Integration of ICT4D (Information, Communication and Technologies
for Development)
•
Identification and training of market focal points for timely data
collection
Beneficiaries receive NFIs during
Kamango’s direct distribution
activities, July 2015.
25
DRIVE’s voucher fairs in Katanga
Province, January 2015.
26
Challenges
•
Scope: multiple markets, multiple areas of intervention, NFI & food
commodities
•
DRC’s markets profiles (fair system, external vendors, etc.)
•
Limited human and financial ressources
•
Limited staff capacity (ex.: to carry out real time analysis to inform
programmatic changes, regular price monitoring, etc.)
•
Organization’s capacity to respond to MARKit findings and results
(ex.: alter program modality mid-course, etc.)
•
Data quality and validity
•
Lack of existing secondary data
•
What is good enough?
Next Steps & Lessons Learned – DRIVE II
•
Increase financial and human resources to carry out market
monitoring activities (ex.: hiring of one dedicated market staff, etc.)
•
Continued training of DRIVE II teams on price data collection and
analysis
•
Pre-positioning of food and NFIs to ensure timely food distributions /
review of internal systems and procedures for eventual modality
changes mid-program
•
Carrying out of large scale market assessment to review tools,
methodology and ICT4D integration
•
Co-facilitation of Market Working Group (Food Security Cluster) in
North Kivu Province for greater information sharing
•
Collecting cost-efficiency/ cost-effectiveness data