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An Approach Paper on Indo-US Trade in Wheat and Mango A Game Theoretic Framework Satish Y. Deodhar (IIM-A) Siddharth Rastogi (IIM-A) International Agricultural.

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Presentation on theme: "An Approach Paper on Indo-US Trade in Wheat and Mango A Game Theoretic Framework Satish Y. Deodhar (IIM-A) Siddharth Rastogi (IIM-A) International Agricultural."— Presentation transcript:

1 An Approach Paper on Indo-US Trade in Wheat and Mango A Game Theoretic Framework Satish Y. Deodhar (IIM-A) Siddharth Rastogi (IIM-A) International Agricultural Trade Research Consortium meetings January 6-9, 2008

2 Synopsis Motivation for the study Literature Review Product Choice Methodology: A Game Theory Approach Data scouting Potential for Policy Implications

3 Motivation WTO: Quota & tariffs going down in ag trade NTBs: SPS issues coming to the fore –Sanitary and phytosanitary (SPS) measures –There is a separate SPS agreement under WTO What do SPS restrictions on imports do? –Protect producers from negative externalities arising from invasive pest, weeds, organisms –However, it also protects domestic producers from foreign competition! Thus, impact assessment becomes important But how to go about doing it?

4 Literature Review FAO (2001): Lists six types of impacts –Impact on production, price & market, trade, food security & nutrition, human health & environment, and, financial cost Surveys and interviews –E.g., Mutasa & Nyamandi (1998) Taking inventory of SPS restrictions & cases –E.g., Wilson & Otsuki (2001) Price Wedge models –Calvin & Krissoff (1998) –Japanese apple imports into US

5 Literature Review … Gravity Models –Study of bilateral flows to identify NTB related trade restriction –E.g. Otsuki, Wilson, and Sewadeh (2000) Iso-Risk framework –E.g., Bigsby (2001). Pest Risk = Eco. Impact times Probability of pest Introduction Cost-Benefit analysis –Studies on banana and avocado E.g., James and Anderson (1998), Peterson and Orden (2006) –Measure compliance cost and expected net welfare changes

6 Limitations Some studies measure only qualitative impact Some use SPS case statistics – not based on science/economics Some other measure only the trade restriction or expansion Yet others look at cost of compliance and expected welfare, but use single commodity, single country framework Reality is a little different

7 Strategic Interaction Countries get engaged in bilateral negotiations Countries get engaged in multilateral negotiations (WTO rounds) Strategic give-and-take across commodities –E.g., agree to reduce subsidies against geographic indications for wine Thus, studies in isolation for each commodity and country may not represent true picture Policy choices are interdependent

8 Trade in Wheat and Mango Wheat: –US production and exports are about 50 and 25 million tonne –In 2007 India imported 6.7 million tonne –None from US ! (Phytosanitary restrictions) Mango: –India’s production and exports are 10 and 0.8 million tonne (2006) –US imported mangoes worth $233 million but none from India –Fear of Fruit fly and weevil

9 President Bush –During his trip to promote bilateral trade in 2006: –“By the way Mr. Prime Minister, the US is looking forward to eating Indian mangoes.” –Probably what he really meant was: –“By the way Mr. Prime Minister, the US is looking forward to sending some US wheat to India.”

10 Dominant Strategy Equlibrium and Prisoners’ Dilemma USA India Import Ban Complete Import Liberalization Import Ban0, 0U, X-Y Complete Import Liberalization A-B, VU+(A-B), (X-Y)+V

11 If Net welfare is positive for imported good, –Complete liberalization is dominant solution If Net welfare is sufficiently negative for imported goods i.e., U+A-B <0, V+X-Y<0 –Import ban is the dominant solution If Net welfare is negative for imported goods, but U+A-B and V+X-Y are positive –Prizoners’ dilemma occurs –Repeated game signals might work

12 Payoffs with partial liberalizataion and spillover effects USA INDIAINDIA Complete Ban, n=0 Partial Liberalization 0<n<1 Complete Liberalization n=1 Complete Ban, m=00, 0nU, n(X-Y-Z)U, (X-Y-Z) Partial Liberalization 0<m<1 m(A-B-C), mV nU+m(A-B-C), mV+n(X-Y-Z) U+m(A-B-C), mV+(X-Y-Z) Complete Liberalization m=1 (A-B-C), V nU+(A-B-C), V+n(X-Y-Z) U+(A-B-C), V+(X-Y-Z)

13 Data Analysis for the payoffs Risk Assessment –Need to get probabilities of pest invasion, crop loss, spillovers –Estimate magnitudes of losses Risk Management –Evaluate mitigation options –Evaluate liberalization degree

14 Overview of Pest Risk Analysis Griffin (2000)

15 Possible Data Sources International Agencies –UNCTAD database on Trade Control Measures –WTO disputes database –International Plant Protection Convention databases –International Portal on Food Safety, Animal & Plant Health In India –Plant Quarantine Organization of India –Agricultural statistics from Ministry of Agriculture –FICCI Agribusiness Information Center In US –US department of agriculture (USDA) –Animal and Plant Health Inspection Service (APHIS).


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