Transaction Costs in Emerging Markets:
A Study of India’s Apple Trade
Satish Y. Deodhar (IIM-A)
Barry Krissoff (ERS, USDA)
Maurice Landes (ERS, USDA)
What we want to tell?
• Of course, imports grow due to rise in
incomes and fall in tariff rates
• However, reduction in transaction costs
matter a lot
And, to show this ..
• We take a preview of India’s apple imports,
domestic supply, marketing cost and
margins, and price integration
• And, hint at FDI in retail and wholesale
markets
India: An Emerging Market
• Sustained high GDP growth rates
– 9 percent in recent past (2006-2007)
• Rising middle-class segment
– 250-400 million apple consumers
– 50 to 100 million imported-apple consumers
• Rapid growth in food demand expected
– Particularly in high value horticultural products
such as apple
Change in Import Regime
• In 1999 significant liberalization in
agricultural trade regime
• Policy now guided by WTO precepts
• QRs converted to tariffs
• Generally high WTO bound rates
• Applied rates are lower
• However, high rates on apples
– Bound rate = applied rate = 50%
Tariff Rates on Select Fresh Fruit,
India
Percent
India: Applied Tariffs
55
50
45
40
35
30
25
20
15
10
5
0
Imports Scenario
• Imports account for less than 1.5% of domestic
supply (about 25,000 tons)
• Imports mainly from USA, Australia, China, and
New Zealand in that order
3,000
2,500
Tons
2,000
1,500
1,000
500
0
Sept02
Oct
Nov
Dec
Jan-03
Feb
Mar
Apr
May
Jun
Months
Australia
China
New Zealand
USA
Jul
Aug03
Domestic Supply
Production is about 1.5 million tons
– US = 4 million; China = 20 million
• Low yield at about 6 tons/ha
– US = 26 tons/ha; China = 10 tons/ha
• Low production growth: about 1%
– US = -3%; China = 5%
• Impediments
– Old root stock (red delicious), erratic monsoon
rainfall, mountainous terrain
– Producers bear all price risk
– No cold chain, lack of grading, poor road
transport
Anti-Hail Nets
Mountainous Terrain
Ready to Upset the Apple Cart!
Domestic Fruit Prices
Apples are generally the most expensive fruit in the market…
Wholesale Price Comparison for Major Indian Fruits, 2003 season, Rs/kg.
January
April
October
Apples
Bananas
Grapes
Mangoes
Oranges
Bangalore
31.73
5.22
22.54
--
20.92
Calcutta
25.66
3.57
25.59
--
13.94
Chennai
59.49
4.65
18.92
--
18.71
Delhi
27.83
5.14
27.99
--
21.13
Mumbai
35.87
5.87
21.43
--
25.06
Bangalore
39.26
5.26
23.55
--
20.77
Calcutta
36.84
3.80
24.04
10.52
13.67
Chennai
64.75
4.73
21.57
23.44
16.64
Delhi
28.42
8.53
24.21
19.34
20.88
Mumbai
--
5.50
27.53
16.41
27.16
Bangalore
34.78
5.28
--
--
--
Calcutta
23.81
3.26
--
--
--
Chennai
36.40
4.74
--
--
11.25
Delhi
25.68
4.10
--
--
15.02
Mumbai
32.15
5.87
--
--
18.11
Domestic Market Not Well Integrated
• Regional markets are not well integrated
– Confirmed by error correction model
• Full transmission of price changes occurs in
about 2 weeks in some cities
• Other markets are poorly integrated
• Lack of efficient transport & direct
procurement from growers limits price
arbitrage between Delhi & other markets
• Cascading trader margins
Domestic Marketing Cost and Margins
November 2003, Rs per box of 20 kgs
Net price received by grower
Expenses incurred by growers on:
Picking, grading, packing, & handling
Packing materials
Freight up to market
Commission of commission agent
Realisation at wholesale market, Delhi
Expenses of wholesale trader
Wholesale trader’s margin
Sub-wholesaler margin
Retailer’s expenses
Retailer’s margin
Consumer price, Delhi
295
118
20
45
20
33
Trader Margins account for 46% of the final consumer price
413
6
84
101
65
231
900
Import Marketing Cost and Margins
May 2003, Rs per box of 20 kgs
Import unit price, CIF
Expenses incurred by importer on:
Tariff
Clearing
Freight
Commission of agent
Importer’s margin
Realisation at wholesale market, Delhi
Expenses of wholesale trader
Wholesale trader’s margin
Sub-wholesaler margin
Retailer’s expenses
Retailer’s margin
Consumer price, Delhi
510
434
255
20
70
89
165
1,109
23
198
199
5
466
2,000
Trader Margins account for 51% of the final consumer price
Import Prospects
• Drivers of import demand
– GDP growth
– Tariff (customs duty) reduction
– Transaction cost (trader margins) reduction
• Assumptions
– Price elasticity of demand = -1.0
– Income elasticity of demand = 1.5
– GDP growth rate = 6% p.a.
Likely Outcomes
Scenario
1. Status
Quo
2. Tariff
Reduction
3. Margin
Reduction
4. ( 2 & 3)
Import Trader Imports by* Cumulative*
Tariff Margins 10th Year
Imports
50%
51%
52,082
364,327
25%
51%
55,130
385,651
50%
21%
66,417
464,600
25%
21%
69,465
485,925
* Base year 2003. Base year imports 22,000 ton
To Conclude ..
• Of course, income growth and tariff
reduction will increase imports
However
• Reduction in transaction cost may be very
critical in increasing imports.
– FDI in retail and wholesale market may be the key
to reducing transaction cost
– Already happening to some extent with Walmart
tying-up with Bharti group
– Shop Rite (SA), selling imported apples only at
Rs. 70
Model Equations and estimations
∆Yt = β1 + δYt-1 + αi Σ ∆Yt-1 + et
Yt = a01 X t + a11 X t -1 + a12 Yt -1 + et .
(a01 +a11 )

DYt = a01 DXt +(1 -a12 ) 
Xt -1 -Yt -1  + et .
 (1 -a12 )

k -1
k -1
i =0
i =1
DYt = a00 + ai1 DXt -i + ai 2 DYt -i + m0 [m1 Xt -k -Yt -k ]+ et ,
where
m0 = (1 -
k
a
i =1
i2
)
k
and
m1 =
 ai 1
i =0
m0
.
Stationarity Test for Wholesale Apple Prices
Prices
Phillips-Perron Test*
Bangalore Market
I (0)
-3.4098
I (1)
-11.343
I (0)
-2.1249
I (1)
-8.8227
I (0)
-1.7410
I (1)
-10.204
I (0)
-3.3919
I (1)
-8.5721
Mumbai Market
Kolkata Market
Delhi Market
* All
I(0) statistics were insignificant and all I(1) price series were significant at 1%. We
also used Augmented Dickey Fuller test. Results were similar if not identical
.
Pairwise Cointegration Test of Apple Prices
Independent variable
Phillips-Perron Test
Dependent
variable
Bangalore
Mumbai
Kolkata
Delhi
Mumbai
-5.0577*
Kolkata
-6.0628*
Delhi
-3.6218
Bangalore
-3.7663
Kolkata
-5.7100*
Delhi
-2.5926
Banaglore
-4.5672*
Mumbai
-5.5744*
Delhi
-2.2124
Bangalore
-3.5841
Mumbai
-3.7807**
Kolkata
-3.7162
* Significant at 1 percent, ** barely significant at 5 percent.
Error Correction Model for Bangalore-Mumbai Wholesale
Prices
Variable
Estimated
coefficient
T-Ratio
∆ Mumbai
0.512553
4.942379
Lag ∆ Mumbai
0.491419
4.082613
2Lag ∆ Mumbai
0.014614
0.10793
Lag ∆ Bangalore
-0.53769
-4.52354
2Lag ∆ Bangalore
-0.28854
-2.13489
3Lag Mumbai (m1)
0.485094
4.184314
3Lag Bangalore (m0)
0.416772
3.261569
Constant
565.1429
3.205162
R-square = 00.45268
Adjusted R-square = 0.3972
Error Correction Model for Kolkata-Mumbai Wholesale Prices
Variable
Estimated
coefficient
T-Ratio
∆ Mumbai
0.526279
6.397178
Lag ∆ Mumbai
0.348977
3.149225
2Lag ∆ Mumbai
0.347016
2.716818
Lag ∆ Kolkata
-0.51106
-4.08421
2Lag ∆ Kolkata
-0.35146
-2.34657
3Lag Mumbai (m1)
0.715076
8.487148
3Lag Kolkata (m0)
0.443729
2.829072
Constant
193.0658
2.412387
R-square = 0.44052
Adjusted R-square = 0.3802