Managing Wheat Price Volatility in India Christophe Gouel, Madhur - PowerPoint PPT Presentation

Managing Wheat Price Volatility in India Christophe Gouel, Madhur Gautam & Will Martin 18 September 2014

Food security in India • Food security: top priority for policy makers • Addressed through 3 pillars: – Availability: R&D, subsidized inputs (electricity, fertilizer, seeds, water, credit) and guaranteed prices. – Access: largest food schemes in the world • Targeted, quantity-constrained, releases of food to low income consumers • Set to expand under new Food Security Bill: 820 million people should receive subsidized food. – Stability: stable prices through active trade and storage policies.

Food security in India • Comprehensive and reinforcing policy instruments: – Trade policies insulate domestic markets – MSP is defended by public procurement and stockpiling. – Public stocks used to supply the Public Distribution System. – Discretionary disposal of remaining stocks to stabilize prices. • Problems: – Hinders development of a private marketing network • 60% of marketed surplus are procured. – Costly and ineffective: • Very high food subsidy bill ($15 billion) • Households that are entitled can buy half of quota (Khera, 2011) • Grain stocks deteriorate – inadequate facilities or held too long

India’s wheat market

From importer to exporter 5 Net trade (X-M, million ton) 0 -5 1960 1970 1980 1990 2000 2010 Market year

Stable Production 0.25 100 90 0.2 80 70 0.15 60 50 0.1 40 30 0.05 20 10 0 0 Output Variability (5 year rolling Std. Dev. - left axis) Share of Area Irrigated (% - right axis)

Real 2005 Thousnd Rupees/MT 10 12 14 16 0 2 4 6 8 1990 1991 1992 1993 Stable domestic market Domestic Price 1994 1995 1996 1997 1998 1999 Import Parity 2000 2001 2002 2003 2004 2005 Export Parity 2006 2007 2008 2009 2010 2011 2012

100 200 300 400 500 600 700 800 900 0 Jan-00 May-00 Sep-00 Jan-01 May-01 Sep-01 Total Stock (Wheat + Rice) vis-à-vis Buffer Norms and Strategic Reserve Jan-02 May-02 Sep-02 Jan-03 May-03 Sep-03 Grain stocks vs norms Buffer+Strategic Reserve Jan-04 May-04 (Lakh Tonnes, Jan 2000 - Aug 2014) Sep-04 Jan-05 May-05 Sep-05 Jan-06 May-06 Sep-06 Jan-07 May-07 Sep-07 Jan-08 May-08 Total Rice + Wheat Sep-08 Jan-09 May-09 Sep-09 Jan-10 May-10 Sep-10 Jan-11 May-11 Sep-11 Jan-12 May-12 Sep-12 Jan-13 May-13 Sep-13 Jan-14 May-14

Questions • What are the implications of current policies? – For India and the world market • Can a model identify better policies? – What is the optimal mix of storage and trade policies? • Can simple rules yield similar results?

Modeling India’s Wheat Market

Key features • 2-country stochastic rational-expectations partial equilibrium model – India ( 𝑗 ) & the Rest of the World ( 𝑥 ) – Production, consumption, storage & trade • A social welfare function that penalizes deviations of prices from the steady state. • Design of optimal policy under commitment and optimal simple rules.

Producers & Consumers Producers respond to expected prices : − 𝛺 r 𝐼 𝑢 r , 𝑠 r 𝑠 r 𝜗 𝑢+1 max Π 𝑢|𝑢+1 = 𝜀𝐹 𝑢 𝑄 𝑢+1 𝐼 𝑢 where 𝐼 planned output, 𝜀 discount factor, 𝜗 a random shock to output, 𝛺 the production cost function. FOC: = 𝛺 𝑠′ 𝐼 𝑢 𝑠 . 𝑠 𝑠 𝜀𝐹 𝑢 𝑄 𝑢+1 𝜗 𝑢+1 Consumers respond to current prices: r ≡ 𝑒 𝑠 𝑄 𝑢 r𝛽 𝑠 , 𝐸 r 𝑄 𝑢 where 𝑒 𝑠 > 0 is a scale parameter and 𝛽 𝑠 ≥ 0 is the demand elasticity.

Stocks & trade Private storers arbitrage prices intertemporally 𝑠 ≥ 0 ⊥ 𝑄 𝑢 𝑠 + 𝑙 𝑠 − 𝜀𝐹 𝑢 𝑄 𝑢+1 𝑠 𝑇 𝑢 ≥ 0, where 𝑇 𝑠 is private stocks & 𝑙 𝑠 storage costs. Trade based on spatial arbitrage opportunities 𝑥 ≥ 0 ⊥ (𝑄 t 𝑁 ≥ 𝑄 𝑢 𝑥 +𝜄 𝑥,𝑗 )𝑈 𝑢 𝑗 𝑌 𝑢 i ≥ 0 ⊥ 𝑄 𝑢 𝑗 ≥ 𝑄 𝑢 𝑥 − 𝜄 𝑗,𝑥 𝑈 𝑢 𝑌 𝑌 𝑢 w ith 𝑌 𝑠 exports from r , 𝜄 𝑠,𝑡 transport cost 𝑠 to s , 𝑈 𝑢 𝑌 & 𝑈 𝑢 𝑁 the power of the export & import tax.

Availability and market Availability (state variable) r ≡ 𝑇 𝑢−1 r r 𝑠 . 𝐵 𝑢 +𝐼 𝑢−1 𝜁 𝑢 Market clearing 𝑠 + 𝑌 𝑢 𝑡 = 𝐸 𝑠 𝑄 𝑢 𝑠 + 𝑇 𝑢 𝑠 + 𝑌 𝑢 𝑠 for 𝑡 ≠ 𝑠. 𝐵 𝑢 Core laissez-faire model 𝑠 , and eight response 2 state variables, 𝐵 𝑢 𝑠 , for 𝑠 ∈ 𝑗, 𝑥 . 𝑠 , 𝑇 𝑢 𝑠 , 𝐼 𝑢 𝑠 , 𝑌 𝑢 variables, 𝑄 𝑢

Welfare Welfare: sum of surpluses + loss function. 𝑗1+𝛽𝑗 𝑗2 𝑐 𝑗 𝐼 𝑢 𝑗 = [−𝑒 𝑗 𝑄 𝑢 𝑗 − 𝑏 𝑗 𝐼 𝑗 − 𝑢−1 𝑢 𝑗 𝐼 𝑗 𝑥 𝑢 1+𝛽 𝑗 ] + [𝑄 𝑢 𝜗 𝑢 2 ] + 𝑗 2 ] − 𝑙 𝑗 + 𝑄 𝑗 𝑇 𝑢 𝑗 − 𝑄 𝐿 𝑗 𝑇 𝑢−1 𝑗 𝑗 ] − [𝐷𝑝𝑡𝑢 𝑢 𝑗 ] [− [𝑄 𝑢 2 𝑄 𝑢 𝑢 Where Cost is the sum of public storage costs and trade policy costs; 𝑗 2 ] represents the dislike of policy makers for price stability . 𝑗 − 𝑄 𝐿 [− 2 𝑄 𝑢 /𝑄 , where 𝛿 , 𝑆 & 𝜉 are values of the K value specified with 𝐿 = 𝛿 𝑆 − 𝜉 𝐸 𝑄 budget share, relative risk aversion & income elasticity (Turnovsky et al., 1980, Econometrica ).

Unpacking current policies

Key policies • Capture the essence of discretionary policies by modeling them as simple rules. • Price-insulating policies – Used to insulate from changes in world prices 𝑁 = 𝛽 𝑁 𝑄 𝑢 𝑥 + 𝜄 𝑥,𝑗 𝛾 𝑈 𝑌 = 𝛽 𝑌 𝑄 𝑢 𝑥 − 𝜄 𝑗,𝑥 𝛾 𝑈 t 𝑢 – 1 + 𝛾 is the level of price transmission • Purchase to defend the Minimum support price: 𝐻+ ≥ 0 ⊥ 𝑄 𝑢 𝑗 − 𝑁𝑇𝑄 ≥ 0. Δ 𝑇 𝑢 – The MSP assumed to be equal to the steady-state price

Stockholding policy • Releases to supply the PDS: 𝐻− = min Θ, 𝑇 𝑢 𝐻 + Δ 𝑇 𝑢 𝐻+ . Δ 𝑇 𝑢 – If stock levels are not enough, PDS is supplied by open-market purchases. • When stocks exceeds the level 𝑇 𝐻 = 25 million tons, they are exported (possibly with a subsidy) 𝑇 𝐻 = max 0, 𝑇 𝑢 𝐻 𝐻 + Δ𝑇 𝑢 𝐻+ − Δ𝑇 𝑢 − − 𝑇 𝐻 . 𝑌 𝑢 • Public stock level is an additional state variable: 𝑇 𝐻 . 𝐻 = 𝑇 𝑢−1 𝐻+ − Δ𝑇 𝑢−1 𝐻− − 𝑌 𝑢−1 𝐻 𝑇 𝑢 + Δ𝑇 𝑢−1

Parameter Values Parameter Value India’s Demand Elasticity -0.3 ROW Demand Elasticity -0.12 Wheat budget share % 10 Supply Elasticity 0.2 Private Storage Cost per ton $22 Public Storage Cost per ton (source: FCI) $87 Trade Costs per ton - Import $65 -Export $35 Standard deviation of production shocks in 3.5 India and in ROW %

Estimating trade insulation insulation • Neglecting trade costs and assuming trade: 𝑄 𝑗 = 𝛽𝑄 𝑥1+𝛾 . • Prices likely cointegrated, so estimation in level would capture their long-run dynamics, not short-run price insulation. • Estimate using an error-correction model • 𝜸 = −𝟏. 𝟖𝟕 .

Solution methods • Rational expectations storage models do not have closed form solutions. • The solution is approximated by numerical methods – Projection methods: grid of points on state variables on which the model has to hold exactly. – Spline interpolation between grid points. • RECS solver (http://www.recs-solver.org/)

Impacts on welfare Laissez- Trade Storage Both faire policy policy Δ Mean price% -2.8 0.01 -3.3 Price CV (%) 14.4 10.7 10.1 3.1 Ave. Public storage 0 0 4.2 10.4 Ave. Private storage 0.10 0.02 0 0 RoW Price CV (%) 20.7 24.0 19.6 23.3 Contributions to India's Welfare (% of consumption expense) Cons Surplus 2.4 -1.3 2.1 Prod Surplus -2.7 1.4 -2.2 Storage cost 0.0 -2.2 -3.7 Trade cost 0.08 0.0 0.13 Reduction in volatility cost 0.4 0.3 0.7 Total India welfare 0.2 -1.8 -3.0

Impacts of optimal policies & optimal simple rules

Fully optimal Policies • Identify an active policy to maximize welfare – Model chooses trade tax & public storage levels • State-contingent policies (depend on current availability in the 2 regions and on history of the states: policies under commitment). • Analyze for different degrees of preference for price stability • Allow to identify the best policy options, but – Very complex policies • Policies are function of variables that are not observable (e.g., Lagrange multipliers).

Optimal simple rules • Compare with Simple – and potentially more tractable – rules for policy – Rules of public behavior with simple feedback between observables and interventions. – Optimal: rules’ parameter are determined to maximize welfare • Optimal Simple Rules: – Degree of Price insulation ( 𝛾 < 0 : % of insulation) – Constant subsidy to private storage ( 𝜂 : % of physical storage costs) • Public storage costs too high; cannot justify a storage policy. • Provide incentives to more cost-effective private storers.