Understanding urban distribution systems of coffee: The case of Addis

1. ETHIOPIAN DEVELOPMENT
RESEARCH INSTITUTE
Understanding urban distribution
systems of coffee: The case of Addis
Authors: Thomas W. Assefa and Bart Minten
IFPRI ESSP
Ethiopian Economics Association (EEA) and the Econometric Society
19th Annual Conference of the African Region Chapter of the Econometric Society
12th International Conference on the Ethiopian Economy
July 16-19, 2014
Addis Ababa
1

2. 1. Introduction
• Policy makers in developing and developed countries often
do no trust markets. They therefore often try to regulate and
control them.
• However, no good empirical evidence on these issues and to
what extent markets reward quality
• We look at this issue for the case of coffee in Addis
• Interesting case because of controls in this area as well as
significant quality and price differentiation

3. 1. Introduction
• Focus on three main research questions:
Question 1: Can we trust traders? Do traders cheat with
quality? Do traders cheat with weights?
Question 2: Is quality control effective? By law, all marketed
coffee has to be divided in export and local quality. Only
coffee that is of lower quality is supposed to stay in the
country.
Question 3: Do markets reward quality in these settings?

4. 2. Coffee value chain
Producers
Rural collectors
Urban collectors
Urban distributers
Semi Wholesalers
About 20. Buy from ECX but also buy from urban collectors. Have warehouses.
Semi-wholesalers
About 20-25. Buy from ECX if it is to be used for grounding. Or they buy
from rural collectors. They sell to urban distributors or to roasters.
About 240 semi-wholesalers on “coffee street” in Merkato. They buy from
urban distributors and sell to traditional shops or supermarkets, cafés or
coffeehouses, roasters, or to a smaller extent to consumers
Roasters They buy from urban collectors or from semi-wholesalers. These use mostly
rejected coffee from ECX. They roast and/or ground. They sell to cafés (that
use machines), coffee shops, or retailers.

5. 3. Data and methodology
• Sample semi-wholesalers: 100 randomly selected from the 240 in
Merkato
• Sample retailers:
- 10 sub-cities in Addis: half of them randomly selected (after geographical
stratification)
• All coffee traders in all open markets in the 5 sub cities were visited [104]
• All supermarkets and minimarkets in the 5 sub cities [97 minimarkets and 53
supermarkets]
- 4 kebeles in each sub city from an average of 10 in a sub city are selected
randomly
• 10 regular shops from each kebele [200 regular shops]
• 543 coffee traders were surveyed in October 2013

6. 3. Data and methodology
• Survey collected information on:
- Background of the retailers and the retail shop
- Coffee sales turnover
- Stated coffee quality and price at the time of the survey
• Weight assessment:
- Purchase of 1 kg from all semi-wholesalers; half of the open market traders,
supermarkets, minimarkets; 25% of regular shops
- 262 obs.: weighted with 2 different electronic scales; average used in analysis
• Quality assessment:
- All samples sent to Coffee Liquoring Unit (CLU) for analysis (tasting/raw bean
inspection)

7. 4. Descriptive statistics
Wholesalers Retailers
Standard Standard
Unit Mean Deviation Mean Deviation
Number of coffee
types sold per
trader Number 4.26 1.16 2.29 1.77
Sale prices (Birr/kg) Birr/kg 69.13 9.72 92.84 29.78

8. 4. Descriptive statistics
Region of origin
Wholesalers Retailers
Don’t know 3% 46%
Wollega/Nekempt 32% 6%
Djimma 36% 13%
Harar 1% 1%
Others 28% 6%
Not raw coffee 0% 28%
Washing
Wholesalers Retailers
Don’t know 1% 10%
Washed 23% 13%
Unwashed 77% 46%
Not raw coffee 0% 30%
Form
Wholesalers Retailers
Raw 100% 62%
Roasted 0% 2%
Grounded 0% 35%
Packaging
Wholesalers Retailers
Packed 0% 57%
Loose 99% 42%
Branded 0% 40%

9. 5. Findings
Q1: Can we trust traders?
Q1a: Do traders cheat with quality?
Origin 1. Wholesaler 2. Retailer Total
Understated 21% 18% 20%
Match 13% 5% 10%
Overstated 66% 77% 70%
Total 100% 100% 100%
Origin 0. Traditional 1. Modern Total
Understated 21% 15% 20%
Match 11% 0% 10%
Overstated 68% 85% 70%
Total 100% 100% 100%

10. Q1a: Do traders cheat with quality?
Washing Wholesaler Retailer Total
Understated 3% 3% 3%
Match 90% 89% 90%
Overstated 7% 8% 7%
Total 100% 100% 100%

11. Q1b: Do traders cheat with weights?
Traditional Modern Total
Underweight 58% 67% 60%
Overweight 42% 33% 40%
Total 100% 100% 100%
Wholesaler Retailer Total
Underweight 75% 51% 60%
Overweight 25% 49% 40%
Total 100% 100% 100%

12. Q1b: Do traders cheat with weights?
0
.01.02.03.04
Density
800 850 900 950 1000 1050
Weight_Average
1. Wholesaler
2. Retailer
kernel = epanechnikov, bandwidth = 3.7184
Kernel density estimate

13. Q2: Is quality control effective?
Overall result of quality assessment
Wholesaler Retailer Total
Fit for Grade 2 16% 13% 14%
Fit for Grade 3 1% 1% 1%
Fit for Grade 4 0% 4% 2%
Fit for Grade 5 4% 5% 5%
Fit at Peaberry Coffee type Level 2% 0% 1%
Rejected for grades (but >UG) 41% 36% 38%
Fit at Under Grade Level 33% 31% 32%
Unfit 3% 10% 8%
Total 100% 100% 100%

14. Q3: Does the market reward quality?
• In well-functioning markets, quality is reflected in prices.
• Tested through hedonic pricing regression.
Figure: Kernel distribution of wholesale and retail prices0
.01.02.03.04.05
Density
0 50 100 150 200
a. Sales price
1. Wholesaler
2. Retailer
kernel = epanechnikov, bandwidth = 2.5840
Kernel density estimate

15. Q3: Does the market reward quality?
Hedonic pricing regression results
The Whole
Sample
Sample
Bought
Unit b _star t b _star t
Type of shop
(default=regular shop)
1. Supermarket yes=1 33.857*** 18.89 37.542*** 12.187
2. Minimarket yes=1 6.154*** 5.151 6.17*** 2.873
4.Open market trader yes=1 -3.943*** -3.932 -4.386** -2.299
5. Wholesaler yes=1 -2.958*** -3.05 -5.734*** -3.207

16. Q3: Does the market reward quality?
The Whole
Sample
Sample
Bought
Unit b _star t b _star t
Region of origin (default=Sidama,
[Actual Origin for Samples bought])
1. Wollega/Nekempt yes=1 0.23 0.187 1.922 0.69
2. Djimma yes=1 -0.954 -0.834 -3.398 -1.039
4. Harar yes=1 4.419 1.409 -3.471 -0.614
5. Yirgacheffe yes=1 0.594 0.194 0.506 0.114
7. Teppi yes=1 -1.807 -0.608 -5.867 -1.456
8. Bebeka yes=1 -10.909 -1.548 1.501 0.513
9. Arba Minch yes=1 -4.508 -0.778
10. Reject ECX yes=1 -8.563*** -3.349
11. Other yes=1 -0.328 -0.121 0.112 0.049
12. Blended yes=1 -10.255*** -2.986 -2.148 -0.914
13. Unknown yes=1 0.563 0.46

17. Q3: Does the market reward quality?
The Whole
Sample
Sample
Bought
Unit b _star t b _star t
Washing (default=Washed)
2. Unwashed -11.316*** -11.692 -9.669*** -4.682
3. Missing -8.099*** -4.102
Packaging branding
(default=loose)
2. Branded, packed [transparent] yes=1 44.164*** 6.858 24.107** 2.332
3. branded, packed [non transparent] yes=1 173.492*** 13.831 24.497* 1.726
4. Non_branded_pack_transparent yes=1 38.425*** 6.444 30.695*** 3.089
5. Non_branded_pack_non_transparent yes=1 46.682*** 6.8 31.287*** 2.849
Purity(default=pure)
2. 1 to 5 yes=1 -3.764*** -3.841 -4.936*** -2.869
3. More than 5 yes=1 -9.567*** -8.309 -9.728*** -4.672
4. Not row yes=1 -37.352*** -6.267 -31.564*** -3.241

18. 6. Conclusions
Major findings from the research:
Q1: Can we trust traders?
Answer: Depends. Can be relatively trusted with weights; however,
cheating with not easily observable quality indicators
Q2: Is quality control effective?
Answer: No. There is a flourishing informal market
Q3: Do markets reward quality?
Answer: Depends. 1/ Quality indicators that are not easily observable
not rewarded (origins of coffee); 2/ Indicators that easily observable
rewarded (ECX reject cheaper than others; washed and pure coffee
higher prices; packed and branded coffee higher prices)

19. 7. Implications
Do we need control?
- Given that markets circumvent controls, one might re-consider the
usefulness of using scarce resources spent on controlling them
- if control deemed important, better mechanisms needed
• How do we protect local consumers?
- Modern retail in its current form does not assure quality yet (in
contrast with international evidence); possibly because of early stage
of rollout or because of informality of markets
- Do we need consumer protection organizations? 1/ would be hard to
do in this case, given informal system; 2/ not needed for weights and
observable quality characteristics

20. Thank You