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Dynamic supply response for pulses in india role of price and non price factors

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Avinash Kishore

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Dynamic supply response for pulses in india role of price and non price factors

  1. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 14. Pigeon pea Production (‘000 tons) across districts of India: 1970 & 2007
  15. 15. Pigeon pea yields (kg/ha) across districts of India: 1970 & 2007
  16. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 26. Thank you !!!!!

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