The presentation is from the one day workshop on ‘Pulses for Nutrition in India: Changing Patterns from Farm-to-Fork’ organized on Jan 14, 2014. The workshop is based on a few studies conducted by the International Food Policy Research Institute under the CGIAR’s Research Program on Agriculture for Nutrition and Health. These studies covered the entire domain of pulse sector in India from production to consumption, prices to trade, processing to value addition, and from innovations to the role of private sector in strengthening the entire pulse value chain. These studies were designed to better understand the drivers of changing dynamics of pulses in the value chain from farm-to-fork, and explore opportunities for meeting their availability through increased production, enhanced trade and improved efficiency.

1. COOLING EFFECT OF PULSE IMPORTS
ON PRICES: THE CASE OF PIGEON PEA
IN INDIA
January 14, 2014
New Delhi
Devesh Roy
Akanksha Negi

2. Scenario of Pulses in India
 India -largest producer and consumer of pulses in the world (FAO,
2008).
 Yet, India’s pulse production- consistently inadequate in meeting
the rising demand.
▫ Subpar pace of increase in production : production fluctuating
between 11 and 14 million tons annually.
▫ Evolving demographic dietary patterns.
▫ Pulses, nutritionally important crop: Dominant sources of plant
based proteins in traditional vegetarian Indian diet.
▫ Heterogeneity in pulses intake: function of tastes and
preferences (amongst other things).
▫ Persistently high prices: result of demand outpacing supply both
on an aggregate level and across variety.
Research Question

3. 3
11:00 AM
Price evolution of pulses

4. 4
11:00 AM
MSP over time (recent data- bit
slower growth in MSP)
URAD
Moong
Tur

5. Unit value of Import vs MSP
Unit value (import) Rs/T
MSP Rs/T
MSP as % of import value
20112009-10 2010-11 2011-12 2009-10 2010-11
12
2009-10 2010-11 2011-12
Peas
15663
15033
20265
0
0
0
0
0
0
Chickpeas 25102
25049
37094
17600
21000 28000
70
84
75
Moong/Ur
105
ad
44795
53450
41941
27600
31700 44000
62
59
Lentils
37566
37754
30861
18700
22500 28000
50
60
91
Tur
125
(Arhar)
42551
33177
30709
23000
30000 38500
54
90
Others
38533
48004
36885
Total
pulses
28343
27044
27028
Import of Pulses
Peas
Moong, Urad, Massor,
others
Tur
Chick peas
Total pulses
Qty in Lakh MT
2009-10 2010-11
2011-12
16.56
15.05
20.23
13.66
8.26
8.38
3.89
3.38
37.50
3.46
1.01
27.78
4.26
2.03
34.91

6. Primer on pulse prices
 Low weightage to Pulses vis-à-vis



cereals and animal source foods
e.g. Milk in Wholesale Price Index.
Experiencing high prices post 2005.
Hypothesis: Under rising prices, Imports cool down domestic prices.
Examples:
 Massive wheat Imports- to the tune of 6 million tons.
 Liberalization of Edible Oil Imports
 Stop gap allowance for Imports -Milk, Sugar and Onions.
 Steady growth in Pulses Imports since 2000: Growing up by as


much as 36 percent
Evolution of Pulses Imports coinciding with persistent increase in
prices: To what extent have imports cooled domestic markets?
This paper is an attempt to fill in this gap in the literature.

7. 7
11:00 AM
Pulses in price index
Year
Low inflation
High weight
1998
High Inflation
Low weight
High weight
Low weight
7 types of
edible oil
Masur
(11.6,0.3)
Rice, wheat
Other coarse
cereals
Arhar (29.5, Moong (11.1, Sugar
0.6)
0.4)
Urad (4,0.5)
Milk
Some fruits
and
vegetables
Gram
(1.9,1.6)
Green pea (21.4,0.5)
Onions
Gur/Khandsa
ri
Bajra

8. 8
11:00 AM
Pulses in price index

9. 9
11:00 AM
Pulses in price index

10. 10
11:00 AM
Pulse in price index
High inflation
High weight
2010
Low inflation
Low weight
High weight
Low weight
Fish
Moong
Rice
Masoor
Milk
Urad
wheat
Sugar
Gram
Arhar
Green Peas

11. 11
11:00 AM
Why Pigeon Pea –Home Scenario
• One of the major pulses in India alongside Chick Peas, Black Gram,
Green Gram and lentils.
• India accounting for 90% of total global area and 93% of world
production (FAO, 2009).
• What happened to Pigeon Pea prices?
▫ The retail price of pigeon pea reached as high as Rs 120 per kg and other
pulses remained above Rs 70 per kg for more than six months (Reddy,
2009).

12. Data and Variables
 Time Period: 2002-2012
 Data Sources
▫ Imports: Customs Dataset
▫ Wholesale Price Index (WPI): Office of the Economic Advisor, Ministry of
Commerce an Industry.
http://www.eaindustry.nic.in/
 Variables:
▫ Weekly Imports (in constant million USD)
▫ Weekly Wholesale price index (WPI)
 We use variables in their log transformations for technical reasons.
Data

13. 13
Pigeon Pea
Presentation of variables: 2002-2012
New long run
Equilibrium?

14. 14
Some Other Cases: Black Matpe, Chick Pea

15. 15
11:00 AM
Lentils, Peas

16. 16
11:00 AM
Some other cases of persistent import
penetration
• Edible oils
• In other cases more stop gap role of food imports in
India – case of sugar, milk, vegetables
• how does it differentiate the cooling effects of
imports on prices?

17. Generically, what do we do?
• Conduct an analysis of the cooling effect of imports on prices of pulses.
• need a mapping between the imported item and its counterpart in the
domestic price data.
• Pigeon pea one of the pulses where can be direct one to one mapping.
• Mapping realized using a novel approach of employing the customs data
disaggregated at 8 digit level.
• Several details in customs data but importantly allows date of imports.
Only upon dating, we can match high frequency imports with similar
frequency of price indices.
• Cooling effect is an issue that extends to several other commodities with
import penetration
11:00 AM
Research Question

18. 18
11:00 AM
Vector error correction model
3
∆𝑙𝑛𝑀 𝑡 = 𝑣 𝑀 +∝ 𝑀 𝑧 𝑡−1 +
3
𝜏𝑖∆𝑙𝑛𝑀 𝑡−𝑖 +
𝜑𝑖∆𝑙𝑛𝑃𝑡−𝑖 + 𝜖 𝑀𝑡
𝑖=1
𝑖=1
3
3
∆𝑙𝑛𝑃𝑡 = 𝑣 𝑃 +∝ 𝑃 𝑧 𝑡−1 +
𝛿𝑖∆𝑙𝑛𝑀 𝑡−𝑖 +
𝑖=1
𝜋𝑖∆𝑙𝑛𝑃𝑡−𝑖 + 𝜖 𝑃𝑡
𝑖=1
with 𝛽′ = (1, −0.365), ∝= −0.357, 0.021 , and 𝑣 = (0.0001, 0.0013)
The long run dynamics between Import and Prices are captured by the cointegrating equation:
𝑙 𝑛 𝑀 𝑡 = −0.566 − 0.365𝑙 𝑛 𝑃𝑡

19. 19
11:00 AM
Stationarity
• Both the series are non-stationary
• stationary time series-never wanders too far from the mean.
The effect of errors decay and disappear over time. Things
that happened recently relatively more important than things
that happened a long time ago.
• non-stationary time series- time series that eventually
explodes. Things that occurred a long time ago have large
impact compared to things that occurred more recently
• (random walk if moves up and down)

20. 20
11:00 AM
Impulse response function
• Rather than seeing serial correlation as technical violation of an
OLS assumption, modern view is:
▫ serial correlation as a potential sign of improper theoretical
specification
• leads to ‘dynamic’ regression models i.e. inclusion of lagged
(dependent and independent) variables.
• Greene (2003)- Impulse and unit response functions in time series
models- counterpart - marginal effects in cross-sectional setting.
• Imagine models in equilibrium. An IRF is when the independent
variable goes up 1 unit in one period and back to 0 next period.
• unit response function - when the independent variable goes up 1
unit and remains up one unit for all remaining periods.

21. 21
11:00 AM
Salient findings
• coefficient of prices in the equation is statistically significant implying
imports and prices are related in a negative way.
• The error adjustment by imports in the current period=-0.36- Imports fall
rapidly when away from equilibrium.
• Prices display a somewhat lukewarm adjustment mechanism imports are
flexible whereas prices tend to be sticky in the short run.
• Second since data on imports and prices at a very high frequency, imports
behaviourally tend to be more volatile compared to prices.
• Both the adjustment coefficients significant at 1% level.

22. 22
Impulse Response Functions
Impulse: Imports
Response: Prices
Impulse: Prices
Response: Imports

23. 23
11:00 AM
Take away from impulse responses
• A unitary shock in Ms is associated with a sustained
increase in prices until 20 weeks after which it
stabilizes to a constant impulse
• Is it imports heating markets?
• Not really look at the rate of price change – it
decelerates
• Imports might be cooling by suppressing rate of price
escalation
• There is catch up at half yearly level

24. 24
11:00 AM
Take away from impulse responses:
Continued
• Imports bear on levels of prices with a lag
• Imports bear on price growth comparatively
• Imports have not super-cooled the pigeon pea
markets i.e. have not immediately brought clam in
markets
• Could it be the dominance of intensive margin in
pigeon pea imports?
• Action on extensive margin would it make the
outcome better?

25. 25
11:00 AM
Are Prices causing Imports or Imports
causing Prices?
• Granger Causality: In a bivariate setup, X is said to granger
cause Y if controlling for the past values of Y, lagged values of
X are instrumental in predicting current Y realizations.
• Not a real causality but one leading to another
• No prior basis to assume whether imports granger cause prices
or vice versa.
• In the present bivariate setup, its hard to say conclusively
whether imports are granger causing prices or vice versa.
• This ambiguity has information
• Prices and imports seem to be intertwined as theory and
observations would suggest

26. 26
11:00 AM
Bi-directional causality has important
message
• Prices may have induced imports
• Imports itself might bear on prices through different
channels such as consumer response, agent’s
expectations
• Economic phenomenon often show such bidirectional relationships
• E.g. stock prices and exchange rates in India (Kumar
2009)
• Implication- realize the intertwined nature of imports and
domestic prices

27. 27
11:00 AM
The other side
•
•
•
•
•
Imports do respond to price shocks
Is it timely and is it enough
May be not
On either side five to six months span seems focal
Imports take time and will be so unless more
consistent trade relationships become norm i.e. are
bootstrapped

28. 28
Take home messages for policy
• Imports and prices are intertwined need to be
considered in conjunction
• Clear evidence of imports and prices co-movement
• Roughly imports’ role in cooling pulse markets
reflect the reactionary stance rather than a pro active
disposition
• With status quo in trade policy it can only be
protracted cooling of markets
• Expansion on the extensive margin might speed
things up