Local and Regional Procurement Learning Alliance
MONITORING AND ANALYZING PRICES:
11. How are prices changing?
Overview of Monitoring and Analyzing Prices
Objectives of price monitoring and analysis are:
• Identify which prices change and by how much
– Identify when to investigate further (using triggers)
• Identify factors that can cause price changes
– Data sources for these factors
– Analytical tools to evaluate the likelihood of each factor
changing prices
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Food prices can be unstable
Why do prices matter?
• In spatially integrated markets, an increase in prices due
to a large local purchase of food would signal traders to
bring in more supply, bringing prices back down.
• A procurement or distribution is less likely to cause
lasting price impacts in integrated markets
– To understand the degree of spatial integration, we need to track
prices across markets over time
• For definitions and overviews, review LRP Price
Collection Training powerpoints:
– 3 Introduction to Markets.ppt
– 4 Introduction to Prices.ppt
Why do prices matter?
• Do No Harm conditions under USDA pilot
program (2010 Interim Guidelines, p. 27):
– Prevent local and regional purchases that would:
• Have a disruptive impact on farmers
• Unduly disrupt world prices… or [unduly disrupt] normal
patterns of commercial trade with foreign countries
• Significantly increase commodity costs for low- income
consumers
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How are prices changing?
Examine retail prices separately from wholesale prices
1. Convert prices
2. Examine magnitude of price changes
3. Determine when to investigate further (using
triggers)
4. Categorize price changes: use analytical tools and
data to identify possible sources of price changes
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Convert prices
• First, convert prices to standard price per kg (or
price per liter for liquids)
• Different units often have different prices, even
when converted to a standard price per kg
– Small volume purchases tend to have higher
purchase prices per standard unit.
Price/kg = (Price/unit * Number of units) / Weight in kgs
on scale
Or: Price/kg = (Price/unit) / (units/kg)
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Convert prices
Market A
Standard
Unit
Number of
units to
reach at
least 2kgs
Weight on
the scale
Price /
standard
unit
Local rice
price /kg
Trader 1
kg
2
2
50
50
Trader 2
cup
5
2.3
34.5
75
Trader 3
cup
5
2.5
37.5
75
Trader 4
cup
5
2.2
34.5
78
Trader 5
can
4
2.5
43.75
70
Average
70
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Convert Prices
• Evaluate retail and wholesale prices separately
• If a single per unit price is 2-3 times larger or smaller
than other prices for the same commodity in the same
market, enumerator or market analyst should verify that
that reported price is correct
– What could be causing these differences?
• Conversion error
• Misreporting by enumerator (e.g., reporting wholesale price as a
retail price)
• Misunderstanding by trader
– Rule out reporting error before proceeding
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Magnitude of price changes by commodity
• For each commodity:
– For each market, for each period: take average of
converted retail prices across retailers (e.g., per kg)
– For each market, for each period: take average of
converted wholesale prices (e.g., per ton)
• Then, graph.
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Triggers for further investigation
For each commodity:
A. Question: How do prices differ within markets over time?
A. Trigger = large price differences within markets over time
– Inspect graph
– Compute period-to-period price changes (next slide)
B. Question: How do prices differ across spatially distinct
markets over time?
B. Trigger = large changes in price differences across markets over time
– Compare price changes across markets over time
• Will likely vary across markets due to varying transportation costs
and other factors
– Look for outliers
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Triggers:
A. Large change in prices within a market
A. Question: How do prices differ within markets
over time?
• Investigate further if prices change more than
30% from one month to the next month
• Compute period-to-period difference in prices to
determine how large the price differences are.
• Formula: (Current price – Last price)/Last
price
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A. Large change in prices within a market: Example
within a maize market in Kenya – reported prices
Nairobi Mombasa Kisumu
Jul-06
255
273
236
Eldoret
227
Busia
206
Mkt
avg
239.4
Aug-06
242
211
211
247
171
216.4
Sep-06
204
163
188
170
140
173
Oct-06
199
174
190
164
152
175.8
Nov-06
201
179
198
154
155
177.4
Dec-06
193
184
221
163
157
183.6
13
A. Large change in prices within a market: Example
within a maize market in Kenya - inspecting prices
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A. Large change in prices within a market:
Example within a maize market in Kenya
A. Question: How do prices differ within markets
over time?
–
–
By inspection, prices are much higher in July than in
September.
Compute month-to-month price changes
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A. Large change in prices within a market: Example
within a maize market in Kenya
Nairobi Mombasa Kisumu
Jul-Aug
Change
Aug-Sep
Change
Sep-Oct
Change
Oct-Nov
Change
Nov-Dec
Change
Eldoret
Busia
Mkt
avg
-5%
-23%
-11%
9% -17%
-10%
-16%
-23%
-11%
-31% -18%
-20%
-2%
7%
1%
-4%
9%
2%
1%
3%
4%
-6%
2%
1%
-4%
3%
12%
6%
1%
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3%
A. Large change in prices within a market:
Example within a maize market in Kenya
A. Question: How do prices differ within markets
over time?
– By computation: Compute period-to-period difference
in prices to determine how large the price differences
are: (Current price – Last price)/Last price
– Trigger is 30%
– The price of maize in Eldoret fell by more than 30%
between August and September
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A. Large change in prices within a market:
Example within a maize market in Kenya
What could be causing this change?:
• Unique to the community?
– Is there something happening in Eldoret that is different from
other markets (e.g., infrastructure disruption)?
• Unique to the commodity?
– Is this price change specific to maize or are all (monitored)
prices falling quickly in Eldoret?
• Unique to the time period?
– Did the same price pattern occur in earlier years (i.e., is it
recurring, perhaps seasonal)?
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A. Large change in prices within a market:
Example within a maize market in Kenya
Further investigate:
•
Unique to the community?
– Use key informant discussions to assess whether that change is
likely to continue impacting prices. Discussed in more detail in
next ppt.
•
Unique to the commodity?
– Identify possible factors related to that commodity (e.g., local
release of stock). Discussed in more detail in next ppt.
•
Unique to the time period?
– Compute seasonal price index
– Examine for seasonal flow reversals
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A. Large change in prices within a market: Seasonal
Price Index
To examine impact of seasonality on Kenyan markets:
Formula:
1. Take average by month and by year across all markets (or group
of markets, if investigating a particular region)
2. Take average by month across years for these markets
3. Take overall average for these markets (across months and
across years)
4. Divide monthly average by overall average
• When the ratio is above 1, prices are higher in this season
• When the ratio is below 1, prices are lower in this season
5. Ground-truth seasonal price index through creation of seasonal
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calendar for maize
A. Large change in prices within a market: Seasonal
Price Index
Jan Feb
Mar
Apr May
Jun
Jul
Aug
Sep
Oct
Nov
Dec
2006 206
224
215
229
251
245
239
214
174
176
177
184
2007 184
191
184
185
194
199
207
205
199
200
213
214
2008 227
230
258
284
355
359
341
335
341
349
353
340
2009 315
357
396
390
404
377
374
390
372
353
362
369
Avg 233
250
263
272
301
295
290
286
271
269
276
277
Overall
avg
274
Index 0.85 0.91 0.96 0.99 1.10 1.08 1.06 1.04 0.99 0.98 1.01 1.01
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A. Large change in prices within a market:
Seasonal Price Index
Low prices in Jan – Mar; High prices in May-Aug
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A. Large change in prices within a market: Seasonal
Price Index - Eldoret
To examine impact of seasonality on prices in a single market:
Formula:
1. Report market price for a single market
2. Take average by month across years
3. Take overall average (across months and across years)
4. Divide monthly average by overall average
• When the ratio is above 1, prices are higher in this season
• When the ratio is below 1, prices are lower in this season
5. Ground-truth seasonal price index through creation of seasonal
calendar for maize
23
A. Large change in prices within a market: Seasonal
Price Index - Eldoret
Jan
Feb
Mar
Apr
May
Jun
Jul
Aug
Sep
Oct
Nov Dec
2006 180
184
185
200
220
236
227
236
173
164
154 163
2007 154
151
157
187
189
199
197
196
191
200
208 210
257
319
311
280
304
361
310
287 234
2008-
-
-
2009 230
308
381
375
382
382
406
455
417-
Avg 188
214
241
255
278
282
278
298
286
225
Overall
avg
328
216 234
249
Index 0.75 0.86 0.97 1.02 1.11 1.13 1.11 1.19 1.14 0.90 0.87 0.94
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A. Large change in prices within a market:
Seasonal Price Index – Eldoret
Examine seasonal price patterns per market
• Low prices in Oct – Mar; High prices in May-Sept
• More variability than across averaged Kenyan markets
25
A. Large change in prices within a market: Seasonal
flow reversals - Eldoret
• Eldoret faces more variability in prices than other Kenyan markets
• Common trend for outlying production areas, which may have lower
prices during post-harvest and higher prices during lean seasons
than urban areas
• Traders evacuate products from outlying areas to urban areas for
storage during post-harvest, and move them back to outlying areas
during lean seasons, incurring storage and transportation costs,
driving prices in rural areas up during lean season
• Therefore, there may be divergence between urban and outlying
area price patterns.
• Use historical prices to compute ratio between outlying area prices
and urban prices
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A. Large change in prices within a market: Seasonal
flow reversals - Eldoret
• Seasonal flow reversals may be responsible for greater price
variability in Eldoret relative to Nairobi, when:
• The lean season in Eldoret coincides with the ratio being above 1
(indicating that food is more expensive in Eldoret than Nairobi)
• The harvest season in Eldoret coincides with the ratio being below
1 (indicating the food is cheaper in Eldoret than Nairobi)
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Trigger:
B. Large change in price differences across markets
over time
B. Question: How do prices differ across spatially distinct
markets over time?
– By inspection, compare prices across markets
• Will likely vary somewhat across markets due to varying
transportation costs and other factors
– Examine historical patterns to assist in identification
of divergence
• Is the pattern of the difference relatively consistent over
time?
• If so, markets are said to be spatially well-integrated; if
not, what may be causing prices to change in one
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market but not in another?
B. Large change in price differences across markets:
maize markets in Kenya
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B. Large change in price differences across
markets: Inspection of Kenyan markets in
Kenya
B. How do prices differ across spatially distinct markets
over time?
– Eldoret’s prices differ from the standard pattern.
Eldoret’s prices increase in August, whereas prices
are falling in other markets. And, in September,
Eldoret’s prices fell faster than in other markets.
– Kisumu’s prices differ from the standard pattern too,
but not as dramatically. Kisumu’s prices increase
faster in December than other market prices.
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B. Large change in price differences across
markets: Inspection of Kenya markets
B. How do prices differ across spatially distinct
markets?
– No rule of thumb for trigger
– Consider historical data:
• Is the current pattern divergent from historical pattern?
• Are changes in the current pattern proportionally much
larger than previous patterns?
• If yes to either of these, consider changes to factors that
may be influencing prices
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How are prices changing?: Categorize price
changes
• Are large month-to-month price changes
observed for a single commodity? For many
commodities?
– Repeat computations for each commodity
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How are prices changing?: Categorize price
changes
• What is the scale of price change?
– Global, regional or national price changes
– Localized price changes
• In procurement areas?
• In distribution areas?
• Single market price changes (e.g., Eldoret)?
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How are prices changing?: Categorize price
changes
•Categorize price change by number of affected communities
and number of commodities
–If price changes occur for many commodities, it may be due to changes
in cost of commerce (e.g., inflation, fuel price changes)
–If price changes occur for a single commodity, it may be due to
commodity-specific shocks or policy changes
–If prices change for a single market, may indicate insecurity, localized
transport issues, trader collusion
–If prices change for many markets, may indicate national-level factors
•Begin to brainstorm: have any factors that influence prices
changed?
–Next: frequent factors that cause prices to change
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