IFPRI- prices of pulses and their contribution in food inflation


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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.

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IFPRI- prices of pulses and their contribution in food inflation

  1. 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. 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. 3 11:00 AM Price evolution of pulses
  4. 4. 4 11:00 AM MSP over time (recent data- bit slower growth in MSP) URAD Moong Tur
  5. 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. 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. 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. 8 11:00 AM Pulses in price index
  9. 9. 9 11:00 AM Pulses in price index
  10. 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 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. 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. 13 Pigeon Pea Presentation of variables: 2002-2012 New long run Equilibrium?
  14. 14. 14 Some Other Cases: Black Matpe, Chick Pea
  15. 15. 15 11:00 AM Lentils, Peas
  16. 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. 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. 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. 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. 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. 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. 22 Impulse Response Functions Impulse: Imports Response: Prices Impulse: Prices Response: Imports
  23. 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. 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. 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. 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. 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. 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