Ferrier

Illicit Agricultural Trade: 

Illicit Agricultural Trade Peyton Ferrier Economic Research Service, USDA Washington, DC 2007 Crime and Population Dynamics Workshop Queenstown, MD June 5th 2007 These opinions do not express the views of the USDA. This work is supported by PREISM (Program for Research on the Economics of Invasive Species Management).

Why USDA Cares? Two Risks : 

Why USDA Cares? Two Risks SPS (Sanitary and Phytosanitary) Risk USDA regulated for invasive species Plant Protection Act of 2000, Animal Health Protection Act of 2002 Large Potential Effects Office of Technology Assessment (OTA, 1993) estimates of invasive species at $97 billion from 1906 to 1991 During the 1990’s, APHIS spending on emergency eradication programs increased from $ 232 million to $10.4 billion annually Exotic New Castle disease in California, $160 million to eradicate, depopulation of more than 3 million birds Resource Risk US FWS (endangered, over-harvested species) regulated CITES and Endangered Species Act. Illegal wildlife trade estimated at $7-20 billion globally (Interpol) Second largest type of illegal trade after narcotics

Research Questions : 

Research Questions What goods are smuggled? What are the origins? How much comes in? How responsive to price? “Any effort to describe the international wildlife trade must unfortunately begin with the recognition that this cannot be done with any accuracy” (TRAFFIC, Roe et al, 2002) “..though enforcement personnel know a great deal about what illegal trade activities occur locally, there is less understanding of illegal trade activity nationally, or what might be occurring at other ports…..” (USFWS)

Two Papers Here : 

Two Papers Here Illicit Agricultural Trade Theoretical, premised on price effects of sudden bans Description of Illicit Agricultural and Wildlife Trade and its Regulation Descriptive, based on USDA and US FWS data.

Close to Here…..The Emerald Ash Borer Beetle: 

Close to Here….. The Emerald Ash Borer Beetle In 2003, a Michigan nursery broke quarantine and shipped infested trees to Prince Georges County, MD. After three years of eradication effort, the EAB was again detected in 2006 Sales of firewood and ash products are still under quarantine from PG county.

Examples of intercepted goods: 

Examples of intercepted goods Citrus Cutting with Citrus Canker Intercepted in California Boneless Chicken Feet from Taiwan Live Giant African Snails

Distinctive Features: 

Distinctive Features Restrictions (Quarantines, Trade Bans): vary dramatically across many different goods are often country or region specific are sudden and disruptive Illegal trade: often co-exists with legal trade may have poor public awareness of, concern for risk is technically uncomplicated Trans-shipping and mis-manifesting Involves uncertainty over risk magnitudes (invasibility, health risk).

Distinctive Features: 

Distinctive Features Difficult-to-quantify externalities: depend on small, imprecisely-measured risk probabilities of an invasive species establi values of abstract goods such as biodiversity and habitat preservation Focus is types of goods smuggled, volume of smuggling, more than lost tax revenue or consumer welfare effects.

Economic Model of Agricultural and Wildlife Smuggling: 

Economic Model of Agricultural and Wildlife Smuggling Demand Side Driven by the price difference in excess of ordinary trade costs following a trade ban Supply Side Driven by risk preferences of exporters, fines and punishments, and the probability of getting caught

Slide10: 

S1 S2 S3 D3 D2 D1 ExDem1 = (ExSup2+ ExSup3) ExSup2 ExSup3 21 31 P1 Market 1 Market 2 Market 3 ExDem1 ExSup3 Smuggler’s Payoff = ΔP1-ΔP2 Free Market Equilibrium A pest detection causes a ban on imports from country 2 31 Smuggling if this price difference is greater than the cost of smuggling Ordinary Shipping Costs Market 2 Restricted

The Demand for Smuggled Goods: 

The Demand for Smuggled Goods Smuggling replaces all banned trade ΔP1-ΔP2 (ΔP1 –ΔP2)* Amount of Smuggling Demand for smuggled goods Smuggled Goods Reduced Imports Demand increases as demand and supply are more inelastic (less responsive to price) for any trade partner

The Supply for Smuggled Goods: 

The Supply for Smuggled Goods Certainty Equivalent Utility from P2 Expected Utility of getting P1 Coefficient of risk aversion fine if caught costs to smuggle Firms will smuggle if φi is less than some threshold so that utility under the risky scenario is higher:

The Supply of Smuggled Goods: 

The Supply of Smuggled Goods ΔP1-ΔP2 (ΔP1 –ΔP2)* Amount of Smuggling Demand(ΔP1-ΔP2) Smuggled Goods Distribution of Risk Coefficients Number of Potential Traders Supply of Smuggled Goods Supply(ΔP1-ΔP2)

Background on Data: 

Background on Data Interdictions – goods being sold illegally and intercepted in U.S. markets USDA (SITC) - Smuggling and Interdiction Trade Compliance Inspections – goods found at ports and refused entry by inspectors APHIS PPQ 280 and USFWS LEMIS Random Inspections – goods randomly inspected with varying intensity (AQIM) Agricultural Quarantine Inspection Monitoring

Pros and Cons of Different Data: 

Pros and Cons of Different Data

APHIS Interdictions Data: 

APHIS Interdictions Data

APHIS Interdictions Data: 

APHIS Interdictions Data

APHIS Interdictions Data: 

APHIS Interdictions Data

Slide19: 

USFWS Inspections Data

USFWS Inspections Data: 

USFWS Inspections Data

USFWS Inspections Data: 

USFWS Inspections Data

Some Very Basic Conclusions : 

Some Very Basic Conclusions Illegal trade in agricultural goods seems dominated by the trade in ethnic foods Trade in wildlife goods seems dominated by the trade in luxury items Illegal trade is not small Illegal trade detected in inspections and interdiction data has a high likelihood of coming from Mexico or China

In other work ….: 

In other work …. Optimal Profiling with Learning How random inspections can be used to improve inspection targeting Chris Costello, Mike Springborn, UC-Santa Barbara Port Shopping Importers finding lax ports to avoid inspections David Zilberman, UC-Berkeley ….That’s it

Blank slide: 

Blank slide

USDA Inspections Data : 

USDA Inspections Data *May have come from a few very large shipments

Size of Price Differences: 

Size of Price Differences In general, the price change is smaller if supply and demand (anywhere) is more elastic. Proportion consumed in domestically for each country