Avinash Kishore

1. Dynamic Supply Response for pulses in
India: Role of price and non-price factors
Akshay Bhatnagar
Pramod Kumar Joshi
Avinash Kishore
Devesh Roy
May 31st, 2016 , New Delhi

2. Introduction
• Neglected by Green Revolution
• India’s position in the world:
• 33% of area
• 25% of production
• 27% of consumption
• Imports 3 - 4 million tones of pulses every year
• Important source of protein
• Per capita availability decreasing – 60 g/day in 1950 & 31.6
g/day in 2011

3. Increasing domestic supply is critical
• Declining per capita consumption ≄ 𝑑𝑒𝑐𝑙𝑖𝑛𝑖𝑛𝑔 𝑑𝑒𝑚𝑎𝑛𝑑
• Set of international suppliers thin
• Prices spiraled upwards despite a 27% increase in the
imports of pulses in 2014–15 to 4.6 million tons
(Lingareddy 2015).

4. Government tried several schemes to boost
production
• Pulses Development Scheme (4th FYP) (1969-70 to 1973-74)
• National Pulses Development Project (7th FYP) (1985-86 to
1989-90)
• Special Food Grain Production Program (1988-89)
• ISOPOM – (2004)
• NFSM-Pulses (A3P) – (2007-08)
• Special Plan to achieve 19+ Million tonnes of Pulses
production during Kharif (2012-13)

5. • To study the dynamic supply response of pulses
• To study the factors affecting relative area allocation to
pulses
• Price versus non-price factors
• If supply not price responsive- why?
Objectives of our study

6. Preview of results
• Price factors do not account for supply response
• Non-price factors like rainfall deficit significant
• There can be issue of risk premium precluding response
to prices
• Do farmers intensify cultivation instead of increase
cropped area in response to increase in prices?

7. 7
Crops Particulars
(1960-70)
-
(1971-90)
-
(1991-2000)
-
(2000-2010)
Chick Pea
Area -21.64 -18.46 17.68 6.43
Production -9.73 -18.06 39.19 12.3
Yield 14.98 0.51 19.02 5.12
Pigeon Pea
Area 8.26 32.54 -1.89 3.37
Production 10.68 42.6 -5.81 7.64
Yield 2.4 7.32 -3.99 3.91
Total Pulses
Area -8.02 3.31 -0.93 2.25
Production -0.87 10.34 2.15 14.08
Yield 7.97 6.72 3.67 11.23
Wheat
Area +26.11 48.53 15.62 3.18
Production 95.54 171.58 42.55 12.13
Yield 55.13 82.98 23.33 8.73
Paddy
Area 11.88 10.46 8.72 -1.53
Production 33.77 70.56 28.55 10.34
Yield 19.72 54.00 18.54 12.09
(Percentage change)
Comparative Performance of pulses & cereals

8. 0
100
200
300
400
500
600
700
800
0
5
10
15
20
25
30
Yield(kg/ha)
Area&Production(millions) Area, Production & Yield of Pulses (1950-2010)
Area (million ha) Production (million tonnes)
Yield(kg/ha) Linear (Area (million ha))
Linear (Production (million tonnes)) Linear (Yield(kg/ha))

9. Pulse landscape in India
• Not much increase in area and yield over the last 5
decades
• Crowded out by cereals
• Moved away from green revolution belt
• Moved away from irrigated areas
• 87% of pulses are grown in rainfed areas

10. Zone-wise total pulses area
10
0
20
40
60
80
100
'000ha
Northern Zone II
Himachal Pradesh Jammu & Kashmir Uttarakhand
0
1000
2000
3000
4000
5000
'000ha
Northern Zone I
Haryana Punjab Uttar Pradesh

11. 0
500
1000
1500
2000
2500
3000
'000ha
Southern Zone
Andhra Pradesh Karnataka Tamil Nadu
0
10
20
30
40
50
60
'000ha
Kerala
Kerala
Zone-wise total pulses area

12. 0
500
1000
1500
2000
2500
3000
'000ha
Eastern Zone
Bihar Orissa West Bengal Jharkhand
0
1000
2000
3000
4000
5000
'000ha
Western Zone
Gujarat Maharashtra Rajasthan
Zone-wise total pulses area
12

13. Zone-wise total pulses area
0
5
10
15
20
25
30
35
40
'000ha
North Eastern Zone
Manipur Nagaland
0
1000
2000
3000
4000
5000
6000
7000
*000ha
Central Zone
Madhya Pradesh

14. Pigeon pea Production (‘000 tons) across districts of India: 1970 & 2007

15. Pigeon pea yields (kg/ha) across districts of India: 1970 & 2007

16. Changing composition of Indian pulses production basket –
TE 1991
Chickpea
36%
Pigeonpea
19%
Lentil
5%
Blackgram
12%
Greengram
10%
Peas
4%
Others
14%

17. Chickpea
47%
Pigeonpea
16%
Lentil
6%
Blackgram
10%
Greengram
8%
Peas
4%
Others
9%
Changing composition of Indian pulses production basket –
TE 2012

18. Methods
• Arrellano-Bond, difference GMM Estimation
technique specifically designed for "Small T and Large
N
• a linear functional relationship;
• a dynamic left-hand-side variable which depends on its
own past realizations
• Endogeneity and dynamic panel bias

19. Data
• Estimation based on dataset combining two secondary
datasets
• ICRISAT-VDSA Meso Level dataset and plot-level Cost of Cultivation
data from CACP
• VDSA-comprehensive long district-Level panel-data on key
agriculture and socioeconomic variables
• Farm harvest price for each plot/farmer from CACP
combined with crop area in a district from VDSA meso-data
• A Balanced panel of 305 districts in 18 states over 2005-06
to 2011-12.

20. Some motivating statistics
[CELLRANGE]
[CELLRANGE]
[CELLRANGE]
[CELLRANGE]
[CELLRANGE]
[CELLRANGE]
[CELLRANGE]
[CELLRANGE]
[CELLRANGE]
[CELLRANGE]
[CELLRANGE]
[CELLRANGE]
[CELLRANGE]
[CELLRANGE]
0
50
100
150
200
250
300
350
400
450
Area under Pulses in Drought Years & Normal Years
Drought Non Drought

21. Motivating statistics: continued-
variation across districts
0
0.01
0.02
0.03
0.04
0.05
0.06
0.07
0.08
0.09
1966 - 1980 1981 - 1990 1991 - 2000 2001 - 2011
PULSE SHARE
Ambala Bareilly Budaun Gwalior Indore Jhansi
Mainpuri Rampur Saran Shahjahanpur Ujjain
0
0.01
0.02
0.03
0.04
0.05
0.06
0.07
0.08
0.09
1966 - 1980 1981 - 1990 1991 - 2000 2001 - 2011
PULSE SHARE
Bahraich Balangir Bulandshahar Cuddapah Dhanbad Dhenkanal
Ganjam Gorakhpur Keonjhar Nellore Rohtak The Dangs

22. (1)
VARIABLES Normal
regression with
NIA
L.newPPEA_TA -0.155
(0.188)
L2.newPPEA_TA -1.208***
(0.141)
newCOTN_TA -0.000710
(0.157)
newRICE_TA -0.0190
(0.0207)
newRICE_TAI_share -0.000461***
(8.88e-05)
newPPEA_TAI_share -0.00144***
(0.000423)
L.newPPEA_TAI_share 0.000295
(0.000186)
L2.newPPEA_TAI_share -0.00218***
(0.000654)
newN_TC -0.000225***
(7.11e-05)
newP_TC 0.000415***
(0.000141)
drought_12 -0.184
(1.400)
drought_13 -5.688***
(1.964)
drought_14 -4.303*
(2.465)
ln_State_med_FHPCreated1 2.214
(3.784)
L.ln_State_med_FHPCreated1 5.298
(3.994)
L2.ln_State_med_FHPCreated1 1.712
(1.829)
ln_State_med_FHPCreated9 5.274
(4.424)
ln_State_med_FHPCreated21 -4.569
(3.810)
newNIA -0.0464**
(0.0191)
Observations 276
Number of distcode91 138

23. Take away
• Farm gate prices do not seem to affect area under
pulses in a well-specified dynamic model
• Question: Is the supply curve vertical?
• Unlikely
• Conjecture: It is probably piece wise vertical
• Beyond a threshold price change it is upward sloping
• Results are robust to varying lag lengths

24. Policy implications
• Big price increases needed to overcome risk
• Calls also for better transmission of prices to farmers
• Can minimum support prices work?
• Do they cover risk? Are changes in MSP countercyclical?
• Price policies can have limitations

25. Major Findings
• July rainfall – Negatively
associated with relative area
allocation to pigeonpea
• Take soil conservation,
drainage, agronomic measures
to address flooding and
drought problem in pigeonpea
• Developing short duration
varieties in pigeonpea to
compete with cereals
• Big price changes possibly
needed
Policy Implications

26. Thank you !!!!!