Economic 

Research

Report

Number 81

United States 

Department 

of Agriculture

Economic 

Research 

Service

The Economics of Agricultural

and Wildlife Smuggling

Peyton Ferrier
www.ers.usda.gov

Visit Our Website To Learn More!

National Agricultural Library

Cataloging Record:

The U.S. Department of Agriculture (USDA) prohibits discrimination in all its programs 

and activities on the basis of race, color, national origin, age, disability, and, where 

applicable, sex, marital status, familial status, parental status, religion, sexual

orientation, genetic information, political beliefs, reprisal, or because all or a part of an 

individual’s income is derived from any public assistance program. (Not all prohibited 

bases apply to all programs.) Persons with disabilities who require alternative means 

for communication of program information (Braille, large print, audiotape, etc.) should 

contact USDA’s TARGET Center at (202) 720-2600 (voice and TDD). 

To file a complaint of discrimination write to USDA, Director, Office of Civil Rights, 

1400 Independence Avenue, S.W., Washington, D.C. 20250-9410 or call (800) 

795-3272 (voice) or (202) 720-6382 (TDD). USDA is an equal opportunity provider 

and employer.

Photo credits: USDA/APHIS and U.S. Fish & Wildlife Service

www.ers.usda.gov/briefing/invasivespecies/

National Agricultural Library Cataloging Record:

Ferrier, Peyton

The economics of agricultural and wildlife smuggling.

(Economic research report (United States. Dept. of Agriculture

 Economic Research Service) ; no. 81)

1. Smuggling—Economic aspects—United States. 2. Wildlife 

smuggling—Mexico. 3. Farm produce—China.

I. United States. Dept. of Agriculture. Economic Research 

Service. II. Title.

HJ6690
United States

Department

of Agriculture

www.ers.usda.gov

A Report from the Economic Research Service

Abstract

The United States bans imports of certain agricultural and wildlife goods that can carry 

pathogens or diseases or whose harvest can threaten wildlife stocks or endanger species. 

Despite these bans, contraband is regularly uncovered in inspections of cargo containers 

and in domestic markets. This study characterizes the economic factors affecting agricultural and wildlife smuggling by drawing on inspection and interdiction data from USDA 

and the U.S. Fish and Wildlife Service and existing economic literature. Findings reveal 

that agricultural and wildlife smuggling primarily include luxury goods, ethnic foods, 

and specialty goods, such as traditional medicines. Incidents of detected smuggling are 

disproportionately higher for agricultural goods originating in China and for wildlife 

goods originating in Mexico. Fragmentary data show that approximately 1 percent of all 

commercial wildlife shipments to the United States and 0.40 percent of all U.S. wildlife 

imports by value are refused entry and suspected of being smuggled. 

Keywords: Smuggling, illicit trade, SPS, quarantine, endangered species, CITES

Acknowledgments

The author thanks Ron Komsa, Scott Sanner, Willy Harris, and Nolan Lemon of USDA’s 

Animal and Plant Health Inspection Service and Craig Hoover of the U.S. Department 

of the Interior’s Fish and Wildlife Service for assistance in understanding the statistics 

and regulatory structure described in this report. Thanks also for the helpful comments 

of Donna Roberts, Craig Osteen, and Barry Krissoff of USDA’s Economic Research 

Service; Lori Lynch of the University of Maryland’s Department of Agricultural and 

Resource Economics; and Holly Ameden of the University of California at Berkeley. 

Any errors are those of the author. 

Peyton Ferrier, pferrier@ers.usda.gov

The Economics of Agricultural 

and Wildlife Smuggling

Economic 

Research 

Report 

Number 81

September 2009
ii

The Economics of Agricultural and Wildlife Smuggling / ERR-81

Economic Research Service/USDA

Contents

List of Acronyms . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . iii

Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . iv

Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1

The Economics of Agricultural and Wildlife Smuggling . . . . . . . . . . . . . . . 3

Analysis of Agricultural and Wildlife Smuggling . . . . . . . . . . . . . . . . . . . 12

Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22

References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23

Recommended citation format for this publication:

Ferrior, Peyton. The Economics of Agricultural and Wildlife Smuggling, 

ERR-81, U.S. Dept. of Agri., Econ. Res. Serv. September 2009.
iii 

The Economics of Agricultural and Wildlife Smuggling / ERR-81

Economic Research Service/USDA

List of Acronyms

AMS Agricultural Marketing Service (USDA)

APHIS Animal and Plant Health Inspection Service (USDA)

AQAS Agricultural Quarantine Activities System

AQIM Agricultural Quarantine Inspection Monitoring 

CBP Customs and Border Protection (DHS)

CITES Convention for the Trade of Endangered Species

DHS U.S. Department of Homeland Security

EAN Emergency Action Notice

ESA Endangered Species Act

FDA Food and Drug Administration (U.S. Department of Health 

 and Human Services)

FWS U.S. Fish and Wildlife Service (U.S. Department of the 

 Interior)

GAO Government Accountability Office

LEMIS Law Enforcement Management Information System 

OTA Office of Technology Assessment 

PPQ Plant Protection and Quarantine 

SITC Smuggling Interdiction and Trade Compliance 

 group (of APHIS) 

SPS Sanitary and Phytosanitary 

USDA U.S. Department of Agriculture

WADS Work Activities Data System

WTO World Trade Organization 
iv

The Economics of Agricultural and Wildlife Smuggling / ERR-81

Economic Research Service/USDA

Summary

The United States bans imports of certain agricultural and wildlife goods 

that may pose unique risks to the environment or the agricultural economy. 

Despite these bans, contraband is regularly discovered during inspections of 

cargo containers and found for sale in domestic markets. Very little is known 

about the size and scope of such smuggling. 

What Is the Issue?

Banned agricultural goods can carry diseases, pathogens, foreign organisms, 

or contaminants that threaten the health of humans, animals, and plants; the 

environment; and the trade status of U.S. exports. Trade in banned wildlife goods may also endanger the survival of a species. Yet, banned goods 

still appear in U.S. markets. This study examines agricultural and wildlife 

smuggling—its specific characteristics, including estimations of its size and 

scope; its responsiveness to economic incentives; and regulations and efforts 

to reduce its risks.

What Did the Study Find?

Agricultural and wildlife smuggling primarily involves luxury items and 

jewelry made from animal parts; ethnic foods, such as szechuan peppers and 

tropical fruits; and specialty goods, including traditional medicines. These 

types of items are also likely to command high prices relative to their cost 

and size. Small amounts of smuggled goods occasionally move over pedestrian and personal vehicle pathways, but commercial volumes of smuggled 

goods are likely to be transported through international shipping channels. 

Among all countries exporting to the United States, incidents of detected 

smuggling are more prevalent with goods shipped from Mexico (wildlife) 

and China (agricultural). However, both countries are major trade partners 

with the United States, and U.S. imports from both have increased dramatically over the last 25 years. Interdictions of meat products are particularly 

high from China. Inspections data reveal that Mexico has the highest amount 

of refused shipments of fruits and vegetables, though it is also the leading 

exporter of these products to the United States. Mexico and Russia have the 

highest rates of refusal of wildlife goods. Refused goods from Mexico typically include live animals, of which birds are a particular concern due to their 

potential for spreading diseases and pathogens. Differences in smuggling 

prevalence rates across countries are attributed to differences in the types of 

goods affected by trade prohibitions, the visibility of smuggled goods, and 

the targeting of enforcement resources. 

Based on fragmentary inspections data, wildlife smuggling accounts 

for approximately 1 percent of commercial wildlife shipments to the 

United States and 0.4 percent of the total value of U.S. wildlife imports. 

Fragmentary interdiction data show that agricultural smuggling is small, 

accounting for 0.03 percent of total agricultural imports from China, the 

country with the highest reported proportions and volumes of smuggled 
v 

The Economics of Agricultural and Wildlife Smuggling / ERR-81

Economic Research Service/USDA

imports. Still, these figures, along with most widely reported estimates, are 

inexact due to the potential for bias in the data.

Smuggling is motivated by profits. Criminal penalties and fines represent 

a cost of smuggling, while the difference between the price of a smuggled 

good at its origin and at its (prohibited) destination represents its return. 

Governments may reduce the incentive to smuggle both by increasing the 

cost through higher penalties and tighter enforcement and by reducing its 

return. To reduce price disparities that encourage smuggling, governments 

may compensate producers affected by trade bans and eradication programs, 

ensure that close-substitute goods can gain legal trade access, and reduce the 

size of markets impacted by a trade ban through regionalization. A small but 

growing literature finds empirical support that smuggling responds to incentives related to enforcement, detection, and profitability. 

How Was the Study Conducted?

The analysis is supported by data on random and targeted inspections of agricultural cargo from USDA’s Animal and Plant Health Inspection Service, 

interdiction data from the U.S. Fish and Wildlife Service, and trade data from 

the U.S. Census Bureau. 
vi

The Economics of Agricultural and Wildlife Smuggling / ERR-81

Economic Research Service/USDA
1 

The Economics of Agricultural and Wildlife Smuggling / ERR-81

Economic Research Service/USDA

Introduction

Between 1998 and 2007, the real values of U.S. agricultural and wildlife 

imports increased 70 percent (Census Bureau) and 108 percent (FWS, 2008), 

respectively. Agricultural and wildlife imports, however, can introduce 

invasive species or disease-carrying pathogens and thus pose unique risks to 

the domestic environment and the agricultural economy. Furthermore, trade 

in certain wildlife goods places pressure on natural stocks abroad and can 

endanger the survival of animal and plant species, including elephants, exotic 

birds, and whales.

To mitigate these risks, regulators rely on trade restrictions allowed under 

the World Trade Organization’s (WTO) Agreement on the Application of 

Sanitary and Phytosanitary Measures (SPS Agreement) and the Convention 

for the Trade of Endangered Species (CITES). In many cases, specific 

commodities are restricted based on country of origin, destination within 

an importing country, and time of year (for seasonal pests). Enforcement 

of these restrictions is multifaceted. Infrastructure and logistical constraints 

make the complete physical inspection of all imported shipments impractical. 

Instead, inspection occurs at different rates (the percentage of shipments 

actually inspected) and intensities (the proportion of goods in a shipment 

actually physically observed). Even the most thorough enforcement process 

may fail to prevent all restricted goods from entering commercial trade. 

Smuggling, defined as the illegal import of contraband goods, is an ancient 

activity. However, only with the emergence of modern pathology and the 

progressive, environmental, and conservation movements since the late 

19th century have trade restrictions been widely adopted for goods harming 

public health, agricultural productivity, and the environment. These trade 

restrictions and regulations may disproportionately harm some consumers 

by constraining consumption choices or artificially benefit some domestic 

producers if used to mask protectionist measures. International treaties and 

agreements constrain the extent to which the United States may ban agricultural imports without repercussion from trade partners. They also require that 

the United States ban certain wildlife goods. Smuggling circumvents those 

bans and, despite significant resources devoted to enforcement, banned and 

contaminated goods still appear in U.S. markets. Integrated global markets, 

lower transportation costs, and rising incomes have not only increased the 

levels of both total trade and imports but also allowed for the more rapid 

movement of exotic pathogens and plant pests across borders and ecosystems 

and increased the size of potential markets for limited wildlife resources. 

The costs of agricultural and wildlife smuggling are difficult to quantify in 

specific terms. Interpol estimates that the value of the illegal global wildlife 

trade alone ranges between $7 billion and $20 billion annually and cites it as 

the second largest form of illegal trade (Interpol, 2006; 2008).1 

No comparable estimate of the size of agricultural smuggling is available, 

but its consequences are acknowledged to be significant due to the large 

potential risk posed by very small amounts of biological material that may 

enter a country with the smuggled goods. For example, an outbreak of Exotic 

Newcastle Disease among poultry in California in 2003 is thought to have 

1Exact sourcing of Interpol’s reported 

estimates on this figure is unclear. Malik et al. (1997), for example, state that 

the total value of all trade in wildlife, 

not just illegal products, is $8 billion to 

$20 billion. 
2

The Economics of Agricultural and Wildlife Smuggling / ERR-81

Economic Research Service/USDA

spread from smuggled game birds from Mexico. As a result, California 

poultry farmers incurred eradication costs of approximately $168 million. A 

2005 shipment of 450 citrus cuttings carrying citrus canker was intercepted 

by U.S. Customs and Border Protection (CBP); if the disease had become 

established in the United States, potential costs to the U.S. citrus industry 

have been estimated at between $173 million and $890 million. For invasive 

species, the Office of Technology Assessment estimates the annual costs at 

$4.9 billion (OTA, 1993). During the 1990s, spending on emergency eradication programs for invasive species in the United States increased from $10.4 

million to $232 million (Lynch and Lichtenberg, 2006). Moreover, the risks 

of wildlife and agricultural smuggling are interrelated as wild plants and 

animals are more likely to carry agriculturally significant pathogens than 

farm-raised animals or to become invasive themselves.2

Based on an analysis of data on shipment inspection and interdiction, this 

study examines the smuggling of agricultural and wildlife goods into the 

United States—including its specific characteristics and its responsiveness to 

economic factors. 

2Karesh et al. (2005) show that 

contact with animals in illegal markets 

substantially encourages transmission 

of wildlife-to-livestock, wildlife-tohuman, and wildlife-to-wildlife diseases, such as severe acute respiratory 

syndrome (SARS), avian influenza, 

(avian) paramyxovirus, monkeypox 

(in rodents), and chytriodiomycosis 

(in wild amphibians). Reed (2005) 

notes that illegally wild-caught boa 

constrictors are more likely to carry 

zoonotic diseases, such as Salmonella

on hitchhiking ticks, and that wild species are also likely to be more invasive 

if accidentally released in the wild, as 

has happened with boa constrictors in 

the Florida Everglades. Endangered 

live plants (such as orchids, cacti, and 

cycads) are periodically wild-harvested 

and transported in native soils, which 

might themselves contain a variety of 

invasive species.
3 

The Economics of Agricultural and Wildlife Smuggling / ERR-81

Economic Research Service/USDA

The Economics of Agricultural 

and Wildlife Smuggling

According to Naim (2005, p. 239), illicit trade is driven by high profits 

and not low morals. At its core, smuggling is a market phenomenon, and 

trade bans, by their very nature, encourage smuggling. Taxes, tariffs, and 

trade restrictions create gaps between the price that sellers receive and the 

price that buyers pay, the difference of which is the return to smuggling. 

Illicit trade is self-reinforcing because reductions in smuggling increase 

its profitability. The lost trade from this market disequilibrium represents 

that maximum amount of goods that might be smuggled in the absence of 

enforcement or legal penalty (Ferrier, 2008). 

A Model of Smuggling 

The market incentive for smuggling is the disparity between the price of 

a good at its origin and destination. Price disparities have been shown 

to encourage smuggling in the work of Fisman and Wei (2004) for tariff 

evasion generally; Thursby et al. (1991), Saba et al. (1995), and Goel 

(2004) for cigarettes; and Golub and Mbaye (2007) for sugar, wheat, and 

rice. A weak rule of law can lower the probability of penalty or apprehension and encourage smuggling as shown by Ivanova (2007) for ozonedepleting substances and Fisman and Wei (2004) for artwork. Von Hippel 

and Von Hippel (2002) show that the presence of substitutes, which may 

reduce demand and make it more elastic, also reduces smuggling in the 

case of wildlife goods. Yang (2008) shows that methods of smuggling to 

evade tariffs in the Philippines adjust when changes are made to inspection-targeting regimes. 

In Ferrier’s (2008) model of the illicit agricultural and wildlife trades, 

demand for smuggled goods is developed from trade theory while the supply 

of smuggled goods is developed from the economic model of crime first 

posed by Becker (1968). Several importers and exporters engage in competitive free trade (with several countries of origin exporting to one destination) 

and the price of traded goods differs only by transit costs. A trade ban for 

a single country of origin restricts that country’s exports so that its markets 

would transact under autarky if no smuggling occurred. Figure 1 depicts 

a market where two origin markets export to a single destination. Under 

free trade, prices net of transit costs across the three markets are equal and 

the sum of exports from origins one and two is equal to total imports to the 

destination. When a trade ban blocks imports from origin one to the destination market, prices rise in both the destination and the (unrestricted) origin 

two from 1

FT P and 3

FT P to 1

TB P and 3TB P , simultaneously raising origin two’s 

exports and lowering the destination’s total imports, until an equilibrium 

is reached where these two values are equal. Simultaneously, prices fall in 

origin one from 2

FT P to 2

TB P , where no exports occur. With the ban in place, 

a wedge emerges between the price at which a good is sold in origin one 

and the price at which a good is purchased in the destination market (net of 

transit costs). This price wedge represents the return to successful smuggling. The magnitude of the price wedge will influence its prevalence, and 

its size depends critically on several observable market factors, including 

market size, the magnitude of trade flow, the number of trade partners, and, 
4

The Economics of Agricultural and Wildlife Smuggling / ERR-81

Economic Research Service/USDA

most importantly, the relative elasticities of supply and demand. Generally, 

more inelastic supply and demand in the restricted origin leads to a larger 

price decrease, while more inelastic supply and demand in the remaining 

free trade areas leads to larger price increases. The price effects are not 

symmetric, however. A small number of trade partners in the free-trade area 

with elastic supply and demand can sufficiently adjust production to replace 

the lost supply of imports and mitigate price swings. In the restricted origin, 

the lack of alternative outlets for excess supply results in large extended 

price decreases. Goods likely to have inelastic demand include ethnic foods 

(certain spices, ethnic specialty goods), luxury food items (caviar), and 

medicinal items. As discussed later, the data show that these goods are all 

intercepted regularly. 

The supply of smuggled goods depends on the willingness of risk-averse 

agents faced with an uncertain payoff to supply criminal trading services. 

Given the level of fines and the probability of apprehension, some level 

of fine makes traders indifferent in choosing to earn the lower price at the 

restricted origin or the higher price at the destination with the probability 

of incurring a fine and forfeiture of goods. In general, as the price wedge 

between the restricted origin and the destination increases, traders will 

smuggle goods in larger quantities. As more goods are smuggled, the price 

disparity falls. An equilibrium occurs when the increased amount of smuggling lowers the price disparity to make traders indifferent to smuggling 

additional goods abroad or selling in the legal, but lower priced, domestic 

market. Compensation to producers affected by trade bans and eradication 

programs, encouragement of the development of acceptable close substitute 

goods, and reductions in the size of markets impacted by trade bans through 

regionalization can reduce the price disparity that encourages smuggling.

D1

S1

D2

S2

D3

S3

Destination market Origin market 1 

(trade banned)

Origin market 2 

FT P1 FT P2

 FT

TB P3 P2

 Exp2 

Exp1

Exp1+Exp2 

 QS QD Q1 QD QS

 Q2 QD QS

 Q3

Transit 

costs 

TB P1

 TB P3

Transit

costs 

Figure 1

Source: USDA, Economic Research Service.

The free trade and trade ban equilibrium
5 

The Economics of Agricultural and Wildlife Smuggling / ERR-81

Economic Research Service/USDA

Economic Literature on Smuggling 

More generally, economists have typically considered several interrelated 

questions with regard to smuggling. First, what are the costs of smuggling 

and is smuggling ever beneficial to society? Given the historical orientation 

of countries toward protectionist trade restrictions, economists (Bhagwati and 

Hensen, 1973; Kemp, 1976; Norton, 1988; and Martin and Panagariya, 1984) 

have typically approached smuggling without consideration for externalities, 

—situations in which a market transaction imparts a cost or benefit to another 

individual in a way not reflected in market prices. On this score, smuggling is 

typically found to improve aggregate societal welfare as it moves the market 

closer to its efficient equilibrium occurring under free trade. 

However, when restricted goods impart risks to security, public health, or the 

environment, smuggled goods create externalities. For example, smuggled 

goods can potentially introduce foreign plant diseases or pests that reduce 

agricultural productivity or require expensive eradication measures. These 

costs may be difficult to quantify, depending on the risk of the contraband 

goods entering the country, the amount entering, and the uncertain costs 

that will result if a pest becomes established. For wildlife goods, smuggling 

can endanger the survival of a species, entailing a loss of biodiversity and 

aesthetic beauty that is not easily quantified.3 Because agricultural and wildlife smuggling involves external costs, it differs substantially from ordinary 

tariff-avoiding smuggling, in which the harm is measured as the lost revenue 

from the proportion of goods smuggled. The harm of agricultural and wildlife 

smuggling, alternatively, may increase exponentially with the proportion of 

goods smuggled if foreign pests are more likely to become established with 

larger exposure or if threatened species are more likely to become extinct as 

a result of increased poaching. Moreover, an increased volume of imports 

would require a falling proportion of goods smuggled simply to maintain the 

status quo level of exposure to smuggling’s associated risks. Concern and 

regulation surrounding agricultural and wildlife smuggling may arise from 

human health effects, where the presence of smuggled goods lowers demand 

for legal goods (if, for example, smuggled goods present a health risk),4 and 

stigma effects, where the underlying demand for an illegally traded good may 

fall due to social pressure.5

Other questions considered by economists include the following: how much 

smuggling occurs and how much does smuggling respond to market forces? 

Undoubtedly, trade restrictions foster smuggling. Little is known about the 

illicit agricultural and wildlife trade specifically, relative to other types of 

illicit trade. Significant differences in the patterns of illegal trade may emerge 

for two reasons. First, most agricultural and some wildlife goods are likely to 

be sold in ordinary commercial outlets operating otherwise legally rather than 

in concealed clandestine outlets (illegal markets).6 Second, most agricultural 

and some wildlife goods have both legal and illegal sources. Identifying the 

relative proportion of legal and illegal trade is challenging due to the possible 

endogenous nature of enforcement. If contraband is sold in small quantities 

in legal markets, personnel in interdiction and inspection may be unaware of 

its occurrence. Alternatively, if contraband is sold openly and is commonly 

available, inspection and enforcement efforts may be limited in their effectiveness because complete enforcement is difficult. 

5Fischer (2004; 2003), Von Kooten 

(2006), and Heltberg (2001) all address 

stigma effects in their discussion of the 

illegal wildlife trade. 

6Henry (2004) finds that approximately 50 percent of selected stores 

surveyed offered traditional Chinese 

medicines, products for medical use 

labeled as containing animal parts controlled under CITES or the Endangered 

Species Act. 

4Health effects are likely to occur with meats, such as beef from 

countries with bovine spongiform 

encephalopathy (BSE) and poultry 

from countries with avian influenza. 

For plant products, most pests are not a 

threat to human health. Contamination 

and adulteration risk, primarily under 

the domain of the U.S. Food and Drug 

Administration, is still likely here, but 

these goods are more likely to be sold 

fraudulently rather than be smuggled 

(in an informed two-party transaction). 

3CITES and most sources on the 

illegal trade assume that smuggling is 

harmful prima facie. Hutton (2000), 

Martin (2000), Kremer and Morcom 

(2000), and Malik et al. (1997) argue 

that freer, sanctioned trade will create 

better incentives for developing countries to preserve sustainable harvests of 

wildlife in specific cases. This argument 

does not support illegal trade but argues 

for reduction in trade prohibitions.
6

The Economics of Agricultural and Wildlife Smuggling / ERR-81

Economic Research Service/USDA

Regulation 

With regard to the risks posed by imports of agricultural and wildlife goods, 

the government performs three basic functions—regulation, to establish 

the conditions for legitimate imports, including treatments and product 

requirements; inspection, to ensure that those imports satisfy regulations; 

and interdiction, to recover illegally imported material and enforce subsequent penalties. Over time, separate Federal Government agencies emerged 

to address the regulation, inspection, and interdiction of U.S. imports for 

different types of risk (see box, “The Evolving Regulatory Structure”). After 

2003, agricultural inspection operations (for invasive species) were moved 

to the newly formed U.S. Department of Homeland Security, while regulatory and interdiction authority of agricultural goods remained with USDA’s 

Animal and Plant Health Inspection Service (APHIS). All three functions—

regulation, inspection, and interdiction—of wildlife goods remained with the 

U.S. Fish and Wildlife Service (FWS). 

Domestically, the Plant Protection Act of 2000 and the Animal Health 

Protection Act of 2002 delegate to APHIS the authority to promulgate 

SPS-based trade restrictions. The laws also designate APHIS as the scientific 

authority in cases where the restrictions are challenged by U.S. trade partners. 

For example, disputes may arise over the degree to which an invasive species 

is already established in a country. If a country already has an established 

pest that is actively controlled, the importing country may not ban trade based 

on that pest threat. Similarly, APHIS provides evidence to trade partners to 

defend U.S. exporters against unfounded claims that U.S. goods may carry a 

disease or pathogen. Internationally, the 1995 Agreement on the Application 

of Sanitary and Phytosanitary Measures governs disputes over claims that SPS 

restrictions violate free trade commitments under the General Agreement of 

Trade and Tariffs.7 This agreement requires that trade restrictions designed 

to mitigate SPS risks follow two broad principles—that they not be used to 

disguise protectionism, and that the restrictions not be arbitrary or discriminatory. Evidence of harm and scientific risk assessment must be provided by an 

importing country to justify a restriction if challenged. If fumigation or cold 

treatment by an exporting country mitigates a pest risk or if certain exporting 

regions within a country can be determined to be pest free, then programs are 

to be put in place that address the remaining risk without halting all trade.

The harm from the importation of banned wildlife goods (that is, species 

loss or endangerment) is more diffuse, but certainly falls more squarely 

on the exporting country as species loss can result in less revenue from 

ongoing trade and tourism and the loss of a country’s ecological distinctiveness. International treaties, therefore, are oriented toward enforcing 

restrictions on imports determined collectively by member countries. The 

primary U.S. law regulating wildlife imports is the Endangered Species 

Act (ESA), which is also the enabling legislation for U.S. participation in 

CITES.8 CITES, however, also explicitly allows member states the discretion to enact “stricter domestic measures.” As a result, imports of certain 

species restricted by ESA are not restricted by CITES.9 Countries enacting 

discretionary restrictions of wildlife goods have occasionally been accused 

of being protectionist (Hutton, 2000).

7Members of the North American 

Free Trade Agreement (NAFTA) can 

appeal cases to NAFTA’s independent 

dispute resolution mechanism before 

going to the World Trade Organization.

9The General Agreement on Tariffs 

and Trade contains similar language allowing member countries to enact trade 

restrictions necessary for “conservation 

of exhaustible natural resources” while 

also requiring that they be nondiscriminatory. See Howse (2002) for a 

discussion of whether restrictions may 

be applied to production methods.

8The Lacey Act prohibiting “the 

import, export, transportation, sale, 

receipt, acquisition, or purchase of fish, 

wildlife, or plants taken, possessed, 

transported, or sold in violation of any 

Federal, State, tribal, or foreign law” 

is also typically invoked when illegal 

trade is actually uncovered.
7 

The Economics of Agricultural and Wildlife Smuggling / ERR-81

Economic Research Service/USDA

CITES has three appendices that proscribe wildlife trade to different extents. 

Species listed in CITES appendix I are banned from trade entirely. Countries 

can transfer these species across borders only if the destination is a verified 

scientific institution or if the species was raised in captivity. Species listed 

in CITES appendix II can be traded only if the exporting country issues a 

certificate of origin and obtains a permit certifying that the product’s harvest 

was not detrimental to the country’s wild stock. Species listed in CITES 

appendix III can be traded only if all participating CITES members issue a 

certificate of origin to document that their exports are not from the country 

where the wildlife is threatened. The listing country must issue a permit certifying nondetrimental harvest. An exporting country may unilaterally add a 

species to CITES appendix III. Among all countries, CITES requirements are 

typically more important but also more burdensome for poor countries that 

have larger undeveloped regions and greater stocks of highly valuable but 

endangered wildlife. Relative to developed countries, these poorer countries 

have more limited infrastructure to enforce harvest regulation, higher returns 

to illicit exports, and fewer alternative industries for employment. 

The Evolving Regulatory Structure 

Prior to 2003, USDA’s Animal and Plant Health Inspection Service (APHIS) 

performed regulatory, inspection, and interdiction functions for U.S. agricultural 

imports. After 2003, the agency’s inspection responsibilities were consolidated 

into the newly formed U.S. Department of Homeland Security (DHS). APHIS 

retained its regulatory responsibilities for assessing pest risk, setting import 

protocols, and prohibiting certain goods from entering the country. 

Following the 2001 terrorist attacks in the United States, information sharing 

across inspections functions was seen as essential for a comprehensive approach 

to addressing immediate risk. Customs and Border Protection, under DHS, would 

inspect imports posing immediate threats, while other existing agencies would 

inspect goods posing other, but not necessarily immediate, risks. For this reason, 

the Fish and Wildlife Service of the U.S. Department of the Interior retained 

both its regulatory and inspection responsibilities for most wildlife, except for 

some live plants and fish. Similarly, the Food and Drug Administration of the 

U.S. Department of Health and Human Services both regulates and inspects 

agricultural products for pathogens and adulterants by testing and approving 

pharmaceutical drugs, pesticides, and food production methods for their safety 

and effectiveness and by sampling cargo containers for proscribed material 

and contaminants. However, the Customs Service (previously under the U.S. 

Department of Treasury), which inspects imports for tariff assessment, property 

rights violations, illegal weapons and narcotics, and other restricted trade, was 

also moved to Customs and Border Protection under DHS. 
8

The Economics of Agricultural and Wildlife Smuggling / ERR-81

Economic Research Service/USDA

Methods of Smuggling

Small amounts of smuggled goods occasionally move over pedestrian and 

personal vehicle pathways, but commercial volumes of smuggled goods are 

likely to be transported through international shipping channels. To this end, 

cargo manifests can be falsified so that the product or country of origin is 

misrepresented or goods can be trans-shipped through countries that do not 

prohibit imports of the goods (APHIS, 2006). For example, Mexico allows 

grape imports from Chile as long as the grapes are free of fruit flies, but the 

United States requires imports of the same Chilean grapes to be fumigated 

with methyl bromide. However, U.S. imports of Mexican grapes can enter 

without treatment (Meissner et al., 2003, pg. 122). Trans-shipping of grapes 

would involve moving Chilean grapes through Mexico into the United States 

to misrepresent them as being of Mexican origin and avoid additional fumigation expenses. Similarly, nursery stock from China must remain in Canada 

for a year before it can be exported to the United States as a Canadian 

product. Trans-shipping would involve moving the foreign nursery stock into 

the United States via another country as a way to sidestep the waiting period. 

Hansen (2000, pp. 175-80) documents how collectors and researchers of rare 

orchids use trans-shipping to bypass CITES-based import restrictions. 

More commonly, though, importers smuggle goods by incorrectly identifying contraband on cargo manifests. Prohibited agricultural goods may be 

relabeled as permitted goods, or endangered wildlife goods may be labeled 

as a nonthreatened species. For example, in 2004, APHIS found a prohibited shipment of frozen chicken feet from China that was labeled as frozen 

fish. CITES appendix I lists the entire orchid family and the parrot family, 

with the exception of three varieties, to help prevent the endangered family 

members from being “mismanifested” as similar looking but nonthreatened 

species (Roe et al., 2002, p. 27; Hansen 2000). Mismanifesting exploits 

the difficulties of physically inspecting cargo containers that are large and 

require space to unpack, especially if the cargo is refrigerated and labeled in 

a foreign language.

Whether goods are smuggled into the United States for commercial or 

personal purposes is directly relevant to the enforcement of trade regulations. 

Travelers smuggling goods for personal purposes may not readily recognize the extent of the trade prohibitions or the potential fines. Commercial 

importers, on the other hand, must submit manifests detailing the contents of 

shipping containers, interact more regularly with trade channels, and generally have obvious incentives to become knowledgeable with regulations. 

Criminal violations under the Endangered Species Act, the Plant Protection 

Act, and the Animal Health Protection Act may be punishable by fines 

ranging from $1,000 to $50,000 per occurrence, a year in prison, and the loss 

of the cargo. 
9 

The Economics of Agricultural and Wildlife Smuggling / ERR-81

Economic Research Service/USDA

Estimating the Size of Smuggling With Inspections Data

Smugglers seek to avoid discovery, which severely complicates any estimation of the size of smuggling and its responsiveness to regulatory policy. In 

theory, smuggling is revealed by inspection if three conditions are met. First, 

all cargo must enter the country through known, legal channels; second, all 

cargo must be inspected; and third, inspections must reveal perfectly whether 

imports are illegal. Because smuggled agricultural goods earn only modest 

markups and are difficult to transport, only a small portion are likely to arrive 

in noncargo conveyances that circumvent inspection points. This may not 

be the case for some wildlife goods (e.g., exotic parrots), which earn large 

returns. Agricultural smuggling is likely to go undetected owing to weaknesses in inspections involving the second and third conditions. Regulatory 

agencies can inspect all cargo entering the United States comprehensively, 

but it is prohibitively costly to do so. Comprehensive inspection may require 

several hours to unpack cargo containers (which may be refrigerated) and 

overwhelm the capacity of inspectors to process cargo (CBP, 2007b). Thus, 

some unregulated cargo is not inspected.10 Moreover, even inspected cargo 

may contain unrevealed smuggled goods. The intent to smuggle goods may 

be unclear when goods are imported as when the documentation of a wildlife 

good’s origin or an agricultural good’s phytosanitary certificate is missing. 

More significantly, inspections occur with different levels of intensity. Less 

rigorous inspections may not always detect smuggling, especially when 

oriented toward detecting pest infestations rather than smuggling, and may 

involve only sampling or a visual inspection. 

Despite these shortcomings in the inspection process and the potential for 

biases, this study’s estimation of the size of smuggling is based in large 

part on data gathered in the inspection process depicted in figure 2 (see box, 

“Alternative Methods for Estimating the Size of Smuggling”). As shown in 

the figure, producers ship goods to a foreign port of disembarkation. Entry 

of these goods into the United States may require certification of a particular 

production process. For example, meats shipped from countries that have 

experienced outbreaks of BSE require a certificate of origin and a health or 

inspection certificate; wildlife sales may require similar certificates of origin 

and nondetrimental harvest. On average, international agricultural shipments 

require 46 separate documents (AMS, 2004, p. 16).

For U.S. imports, regulated cargo must be inspected for pest risk in the 

United States or abroad before being released. Goods found with pests are 

treated, destroyed, or re-exported to another country. When inspectors find a 

prohibited good or a good containing a pest, they issue an Emergency Action 

Notice (EAN) to legally document the pest and mitigating actions as well as 

inform other ports of the potential risk. Goods released for sale in the United 

States are then entered into customs data, and importers pay applicable 

duties. Having cleared CBP, the first line of U.S. inspections, the goods may 

undergo further inspection by FWS (in the case of wildlife goods), the U.S. 

Food and Drug Administration, or other regulatory agencies. 

10Generally, regulated agricultural 

cargo must be inspected for pest risk 

to enter the United States, whereas 

unregulated cargo and cargo entering 

under the National Agricultural Release 

Program does not. Obviously, cargo 

that would be prohibited can be mismanifested as unregulated cargo.
10

The Economics of Agricultural and Wildlife Smuggling / ERR-81

Economic Research Service/USDA

Import Inspections Data Collection

Targeted

Inspections

(IT Goods Are

not Re-inspected)

No Pest Risk,

Present for

Entry to

Customs

Goods 

Appear as

Customs

Data

Random

Inspections

Record Random

Inspections in

AQIM

Foreign Port

(Offering Preclearance)

If

Pre-inspected Foreign Farm Production

Transit & Export

Goods

Transit & Export

Goods

Foreign Port

Foreign Port

(Vancouver, CAN)

Import

Requirements

CBP

Risk

Analysis

U.S. Port Targeting

(LAX, CA)

Commodity Is

Re-inspected in

the U.S.?

Product Is

Released by CBP

and Pays

Customs Duties

Good Is

Inspected by FWS,

FDA, and USDA

as Appropriate

Product Enters

U.S. Market

Contraband Is

Found in

U.S. Markets

Record FWS

Inspections in

LEMIS

Record All

Inspection

Outcomes as

PPQ 280 Data

Contraband

Confiscations Are

Recorded by

SITC

Yes

Yes

U.S. Border

Treat

U.S. Port

(LAX, CA)

U.S. Port

(Laredo, TX)

U.S. Port

(Laredo, TX)

Phyto Certificate,

Certificate of Origin

Issue EAN

Immediate

Export

Goods

Goods 

Are

Re-exported

Is There a Pest

Risk?

Is There a

Treatment?

Product

Destroyed

Inspection

Preclearance at Foreign

Port by U.S. Inspectors

Figure 2

Source: USDA, Economic Research Service.

In Transit

Goods

In Transit

Goods
11 

The Economics of Agricultural and Wildlife Smuggling / ERR-81

Economic Research Service/USDA

In addition to undergoing targeted inspections, goods are inspected randomly 

under the Agricultural Quarantine Inspection Monitoring Program (AQIM). 

Inspections data, covering both random and targeted inspections, represent 

the most comprehensive source of information on illegally imported goods. 

Other sources of data include the Pest ID data system, which records how 

pests found in shipments were identified, and the EAN database, which documents the alerts issued for the detection of prohibited goods or goods with 

pests. In all, four separate databases—PPQ 280 (USDA’s record of agricultural cargo inspections outcomes), AQIM, Pest ID, and EAN—along with the 

Work Activities Data System (WADS) make up the Agricultural Quarantine 

Activities System (AQAS). This system is the primary tool for analysis of the 

risk posed by agricultural imports. USDA and CBP collect and share the data 

in real time. 

Alternative Methods for Estimating 

the Size of Smuggling

Alternative methods for estimating the size of smuggling or its responsiveness to 

economic factors include those leveraging traceback data, those examining trade 

flow (or consumption ) disparities, and those isolating the effect of anti-smuggling 

measures on stock prices. Traceback data are essentially an extremely rigorous 

inspection tool that helps determine the true origin or protected status of a good. 

For example, elephant tusks can be traced back to where they were harvested 

to determine whether they were poached. Random samples of ivory for sale 

can be traced to help estimate the percentage of ivory that is illegally harvested. 

This method has primarily been used with endangered species, including whales 

(Dalebout et al., 2002), seals (Malik et al., 1997), elephants (Wasser et al., 2004), 

and agricultural goods, such as peanuts, coffee, and garlic (Ryan, 1998). 

Trade flows are often documented by both the country importing a good and the 

country exporting a good. Trade flow disparities arise when imports and exports 

do not match. Ordinarily, random discrepancies may result from innocuous data 

collection errors, but systematic disparity may suggest that one country may be 

concealing the actual volume of trade. Using data on trade flow disparities, Fisman 

and Wei (2004) found evidence that smuggling is used to evade tariffs on goods 

entering China from Hong Kong and that smuggling is larger for higher value 

goods and for goods in categories with similar-looking substitutes with lower 

tariffs that might be mismanifested. Similar methods of detecting smuggling have 

been employed by Golub and Mbaye (2007) for sugar, wheat, and rice; and by 

Thursby et al. (1991), Saba et al. (1995), and Goel (2004) for cigarettes. In each 

application, substantial amounts of goods are smuggled from specific geographic 

areas and traded between a relatively limited number of partners. 

Law-abiding companies will see their stock prices fall when embargoes are placed 

on their goods or when anti-smuggling measures are strengthened. Alternatively, 

under these conditions, companies that smuggle will see their stock prices rise as 

the restrictions widen or extend the time period of the price wedge. DellaVigna 

and LaFerrara (2007) show mixed findings on the sensitivity of stock prices of 

weapons-producing companies that differ in their likeliness to smuggle in the face 

of U.N. embargoes on weapons sales to areas of civil conflict. 
12

The Economics of Agricultural and Wildlife Smuggling / ERR-81

Economic Research Service/USDA

Analysis of Agricultural and 

Wildlife Smuggling

Most analyses of illegal trade suffer from incomplete data, and, therefore, estimates of the size of illegal agricultural trade are subject to a great deal of error. 

For example, a TRAFFIC11 source in Roe et al. (2002, pp. 10-12) writes: 

Any effort to describe the international wildlife trade must unfortunately begin with the recognition that this cannot be done with 

any accuracy. 

and

The true size of the illegal (wildlife) trade is anyone’s guess. 

Similarly, FWS (2005, p. 2) writes that:

. . . 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 that could influence how interdiction efforts could be 

improved locally.

USDA has no official estimate of the total scope of agricultural smuggling. 

Severe methodological challenges complicate the estimation of illegal agricultural and wildlife trade with current data sources and limit the extent to 

which it can be characterized in an unbiased manner. 

Analysis of USDA Random Inspections Data 

USDA uses the AQIM program to improve the targeting of agricultural 

inspections and to assess the effectiveness of specific port operations. Under 

program protocol, ports are designated to randomly inspect certain goods 

received in large numbers and record the cargo’s content, port of entry, 

origins, shipment contents, inspection method, pests found, and any indications of smuggling. AQIM inspections vary in levels of intensity. For 

example, an inspector might observe only the tailgate of a shipping container 

or truck, a proportion of the boxes drawn in a random sample, the entire 

contents of a part of the container, or the entire container’s contents. These 

alternative methods of inspection may not reveal smuggling when it occurs. 

AQIM data have other limitations. First, many AQIM inspections involve 

goods that are not specifically agricultural, including floor tiles, machine 

parts, and wood packing material. Trade restrictions on these goods make 

them unlikely candidates for smuggling or for providing cover for other 

illicitly traded agricultural goods.12 Second, AQIM inspections may not 

reveal smuggling even when performed correctly at the most rigorous level, 

especially in the case of goods having moved in trans-shipment. Also, actual 

inspection may be targeted toward the generally regular inspection goal of 

uncovering pests rather than smuggled goods. Third, AQIM inspections do 

not cover all agricultural goods, including, for example, meats. Fourth, a 

recent Government report indicates that some AQIM inspections in this time 

period may not have been conducted and recorded correctly (see OIG, 2007).

11TRAFFIC is a joint program of 

the World Wildlife Fund and the World 

Conservation Union.

12Because machine parts and floor tile 

have carried hitchhiker pests in the past, 

they are randomly inspected for compliance with packaging protocols. The 

cargo containers carrying these goods 

are not refrigerated and are therefore 

unlikely to be suitable for the transportation of most agricultural goods.
13 

The Economics of Agricultural and Wildlife Smuggling / ERR-81

Economic Research Service/USDA

Based on AQIM data (obtained through an interagency agreement with 

APHIS), inspections rarely revealed smuggling between March 2003 and 

January 2007. Smuggling was detected only once in 4,605 inspections of 

southern U.S. border cargo, twice in 4,894 inspections of manufactured goods, 

and zero times in the 2,473 inspections of air cargo and 2,858 inspections of 

northern U.S. border cargo. Given the infrequent detection of smuggling, little 

inference can be made surrounding the scope of agricultural smuggling from 

these data, although random sampling methods have been used successfully 

elsewhere.13

Analysis of USDA Interdiction Data 

Interdiction refers to the detection of illicitly traded goods in markets after 

they have entered the United States. While large resources are expended 

on the interdiction of narcotics and guns, far less is devoted exclusively to 

interdiction of illegally traded agricultural and wildlife goods. The APHIS 

Smuggling Interdiction and Trade Compliance (SITC) group comprises 

approximately 110 employees nationally who serve to recover goods that 

represent an SPS risk and have entered the U.S. supply chain. SITC prosecutes violators either through administrative or criminal punishments. In 

some cases, SITC focuses its efforts on recovering risky material, such as 

Spanish floor tile in wood packing material that was found to contain harmful 

wood-boring beetles in 2004. In these cases, no criminal intent is presumed. 

Data on criminal interdiction are published in SITC’s internal quarterly 

reports for the period 2002-06 and were obtained through interagency agreement with APHIS. These reports record each seizure by type, quantity, category, relevant Code of Federal Regulations violation for which the smuggler 

was penalized, and estimated value. Four types of goods are classified in the 

data: Animal and Meat Products,14 Other Plant Products, Fruit Products, and 

Federal Noxious Weeds. Over the data-collection period, SITC expanded in 

size and budget and, subsequently, the number of interdictions also increased. 

Based on the data alone, it is difficult to determine whether interdicted goods 

are being sold in a commercial setting or used for personal consumption. 

For this reason, shipments valued at less than $50 were excluded from the 

following analysis.

Interdiction data are not random. Agents may target higher risk goods or 

exploit criminal networks, and they face administrative pressures to monitor 

certain goods more closely. As a result, data are likely to be biased toward 

easily observed, restricted goods that are obviously banned rather than goods 

that are regionally prohibited or easily misrepresented. Interdiction data are 

collected as part of ongoing interdiction efforts, and agents collect as much 

prohibited material as possible. 

Tables 1-4 present interdiction data for the top five countries in each of 

these categories based on the number of interdictions between fiscal years 

2002 and 2006. For the Fruit Products category and the Other Plant Products 

category, the three most commonly interdicted products for each country are 

identified. For Animal and Meat Products and Federal Noxious Weed categories, there is little difference across countries with regard to the types of identified goods. 

13Specifically, Jacob and Levitt 

(2003) used the method for re-testing 

and Feinstein (1999) used the method 

for auditing.

14The Animal Products and Meat 

Products categories were combined 

from the original data because their 

goods overlapped significantly.
14

The Economics of Agricultural and Wildlife Smuggling / ERR-81

Economic Research Service/USDA

In the Animal and Meat Products category, the data distinguish between 

pork, beef, poultry, or egg products with different levels of detail. Interdicted 

meat imports were particularly large from China, Japan, Korea, and India 

(table 1). Alternatively, the low monetary value of interdictions from Mexico 

suggests that shipments might have been oriented toward individual personal 

consumption (rather than distribution), which APHIS staff indicate is 

common prior to holidays when immigrants bring specialty meats across the 

southern U.S. border. For the Fruit Products category, interdictions were also 

high with imports from Mexico, China, and Thailand (table 2). 

For the Other Plant Products category, China has a disproportionately high 

number of interdictions, primarily involving shipments of szechuan pepper 

and citrus-based spice (table 3). Both of these goods may carry a variety of 

diseases that threaten citrus fruit, which has been an area of specialized focus 

following an outbreak of citrus canker in Florida in the late 1990s. 

SITC interdiction data reveal a high likelihood for interdicted goods to be 

nontraditional, ethnic goods (specifically, spices) and to have a high value 

relative to their size. This was evident in the Animal and Meat Products, 

Fruit Products, and Other Plant Products categories. Avocados represent an 

exception to this tendency, which is likely due to heightened political attention to avocado imports as trade of this product was liberalized over the 

period in question (APHIS, 2006). 

Table 2

Fruit product interdictions by SITC, 5-year totals (FY 2002-06)

Rank Country of origin Frequency Value Weight Top three items

Number Dollars Pounds

1 Mexico 60 94,426 69,840 Tejocotes, avocados, hog plums

2 China 32 75,044 39,437 Bael fruit, garlic,1 ya pears

3 Thailand 26 8,047 2,776 Bael fruit, wood apple, krasang

4 Bangladesh 9 7,677 2,110 Satakora, citrus 

5 Asia (unkown) 7 18,468 9,522 Citrus, longans, wood apple

Total 190 556,447 209,049 Bael fruit, tejocotes, avocados

1In response to concerns that China was dumping low-priced garlic, the United States imposed a 377-percent tariff on Chinese garlic. 

Subsequently, interdictions periodically uncover trans-shipments of Chinese garlic (Kane, 2004).

Source: USDA, Economic Research Service using USDA, Animal and Plant Health Inspection Service, Smuggling Interdiction and Trade 

Compliance (SITC) Quarterly Report (2002-06).

Table 1

Animal and meat product interdictions by SITC, 

5-year totals (FY 2002-06)

Rank Country of origin Frequency Value Weight 

Number Dollars Pounds

1 China 175 866,151 262,920

2 Japan 60 355,056 36,888

3 Korea 44 150,111 22,843

4 Mexico 44 17,473 4,867

5 India 42 165,031 70,286

Total 861 3,374,009 1,073,207

Source: USDA, Economic Research Service using USDA, Animal and Plant Health Inspection 

Service, Smuggling Interdiction and Trade Compliance (SITC) Quarterly Report (2002-06).
15

The Economics of Agricultural and Wildlife Smuggling / ERR-81

Economic Research Service/USDA

Only a limited number of goods are considered Federal Noxious Weeds, 

a designation that indicates that the good’s establishment and propagation 

make it an environmental threat by itself. For the countries in table 4, the 

top three goods for each were solanum torvum (turkey berry), imperata 

cylindrical (cogongrass, an ornamental grass), and ipomea aquatica (water 

spinach). Domestic transport accounts for a large share of Federal Noxious 

Weed interdictions, suggesting that internal trade is present. Given the infrequency of interdictions from Mexico and Vietnam, these observations are 

likely to be anomalous. 

In terms of absolute monetary value, China is the largest source of interdicted material for trade, a fi nding that bears out over several product categories (table 5). In terms of the value of interdicted goods to its legal trade, 

China also has the largest percentage15 of interdicted trade to legal trade 

(0.03 percent of total value), although the amount is not inordinately large 

relative to that for Japan, South Korea, and Taiwan. Although the percentages from each of the top 10 origin countries are small, it is important to 

15Ivanova (2007) similarly fi nds that 

China is the largest source of illicit 

traded ozone-depleting substances prohibited under international agreement.

Table 4

Federal noxious weed interdictions by SITC, 5-year totals (FY 2002-06)

Rank 

Country of 

origin Frequency Value Weight

Number Dollars Pounds

1 China 56 319,281 26,470

2 U.S. (domestic) 52 100,453 18,542

3 Thailand 29 46,505 9,743

4 Mexico 8 6,175 656

5 Vietnam 7 1,127 179

 Total 180 482,114 58,994

Source: USDA, Economic Research Service using APHIS-SITC Quarterly Report (2002-06).

Table 3

Other plant product interdictions by SITC, 5-year totals (FY 2002-06)

Rank 

Country of 

origin Frequency Value Weight Top three items

Number Dollars Pounds

1 China 338 1,169,561 801,332 Szechuan pepper, 

citrus-based spice, 

burdock 

2 India 140 116,842 51,895 Corn/millet, 

citrus-based spice, 

curcurbit

3 Mexico 125 192,462 33,098 Citrus-based spice, 

lemon grass, ruda

4 Thailand 64 69,263 71,932 Citrus-based spice, citrus, szechuan pepper

5 Korea 33 154,017 74,585 Corn/millet, lentil and 

citrus-based spice

 Total 897 2,193,803 1,170,664 Szechuan pepper, 

corn/millet, citrus 

Source: USDA, Economic Research Service using USDA, Animal and Plant Health Inspection 

Service, Smuggling Interdiction and Trade Compliance (SITC) Quarterly Report (2002-06).
16

The Economics of Agricultural and Wildlife Smuggling / ERR-81

Economic Research Service/USDA

recognize that this fi gure represents only a minimum level because the 

interdiction process almost certainly fails to uncover all smuggled goods. 

Moreover, certain factors may help explain why these countries have 

higher detected levels of smuggling. 

Asian countries, particularly China, have recently been recognized by the 

Federal Government as a source of potential invasive species because they 

have climates and habitats similar to those of the United States, they are 

home to a large variety of species that (unlike European species) have not 

been cultivated in the United States, and their volume of trade with the 

United States has increased signifi cantly (Mack et al., 2002, p. 37). Based on 

the types of goods interdicted, it appears that illegally traded foods are most 

commonly discovered in ethnic food markets. The expansion of U.S. immigration in the 1990s, as well as the rise in food imports from China over the 

last 20 years, may have encouraged the growth of Asian ethnic food markets 

that support this trade. 

The degree to which inspection and interdiction evidence is gathered is likely 

to depend on the ease with which smuggled goods are discovered. Inspectors 

and SITC offi cers may be more likely to identify contraband material if it 

is subject to a comprehensive ban based on the material’s country of origin 

rather than just based on a region within a country. Frequently interdicted 

goods, such as szechuan pepper from China, fall under this criterion. Also, 

China has hosted two particularly large threats to U.S. agriculture—avian 

infl uenza and citrus diseases—that may have caused inspectors to pay closer 

attention to imports from China than from other countries. 

Table 5

Total interdicted material and total agricultural 

imports, 5-year totals (FY 2002-06)

Rank 

Country of 

origin 

Interdicted 

material from 

2002 to 2006 

Agricultural 

imports from 

2002 to 2006

Interdicted to 

total value ratio

Dollars

Thousand 

dollars Percent

1 China 2,342,640 8,038,360 0.0291

2 Japan 374,562 2,063,320 0.0182

3 India 281,724 4,182,607 0.0068

4 South Korea 232,800 964,699 0.0241

5 Mexico 207,241 36,802,361 0.0006

6 Taiwan 184,844 904,963 0.0204

7 Thailand 136,705 5,171,291 0.0026

8 U.S. (domestic) 123,828 Not applicable Not applicable

9 Canada 58,817 57,791,976 0.0001

10 Vietnam 56,261 1,731,613 0.0033

Source: USDA, Economic Research Service using USDA, Animal and Plant Health Inspection 

Service, Smuggling Interdiction and Trade Compliance (SITC) Quarterly Report (2002-06).
17 

The Economics of Agricultural and Wildlife Smuggling / ERR-81

Economic Research Service/USDA

Analysis of USDA Targeted Inspections Data 

The outcomes of targeted agricultural inspections are collected in APHIS’s 

PPQ 280 database, which is publicly available under the Freedom of 

Information Act. PPQ 280 data reveal the types of good, origin, quantity, 

and disposition code for plant agricultural goods physically inspected in the 

course of their importation to the United States. The disposition code indicates 

whether the shipment was inspected and whether pests were detected, but 

it does not indicate whether cargo concealed smuggled goods. Even if such 

distinctions were available, however, estimated percentages of goods that are 

smuggled would be biased upward because targeted inspections are oriented 

toward finding the maximum amount of prohibited material. Targeting factors 

and intensity of inspection efforts are not available in the data.

Using data from 1996 and 2006, this study isolates five disposition codes16 that 

suggest that smuggling is being attempted,17 including three codes for products 

that are prohibited and destroyed, returned, or assigned another action; one 

code for products destroyed due to a discrepancy with the shipment’s phytosanitary certificate; and one code for products that are endangered species and 

sent to a rescue center.18 The sum of these shipments is herein called refused 

shipments. To avoid aggregation problems,19 the focus of this analysis is on 

refused shipments of fruits and vegetables only. Table 6 provides findings for 

the top five countries ranked in terms of cumulative refused shipments of fruits 

and vegetables. 

While Mexico has the largest amount of refused fruits and vegetables, it is also 

the largest source of fruit and vegetable imports to the United States. Mexico 

and China lead other nations in the number of shipments refused. While the 

rate of refusal for China is noticeably larger than that for Mexico, it is actually 

smaller than that for Argentina and Brazil. Inspection data do not allow for a 

specific estimation of the size of smuggling but do indicate the types of goods 

that are refused because of suspected smuggling. These include citrus goods, 

tropical fruits (including papaya and mango), and ethnic foods (including 

szechuan pepper and ya pears). These varieties also overlap with the types of 

goods interdicted in markets as discussed in the previous section. 

16These codes are DEPP, OTPP, and 

RXPP for the goods that were prohibited products; DEPD for the goods 

rejected for having phyto discrepancies; 

and ESRC for goods confiscated for 

being endangered species.

17Although APHIS staff indicate 

that attempting to import prohibited 

goods is suggestive of smuggling, 

import shipments may still receive 

these disposition codes when the goods 

are correctly manifested. Typically, 

APHIS does not consider goods as 

being smuggled unless there is intent to 

conceal the true contents.

18The relatively small number of endangered plant species include orchids, 

cacti, and cycads.

19Cut flower and propagative material imports are measured in stems and 

plant units rather than by weight and 

are difficult to interpret in terms of 

volume

Table 6

Total refusals of shipments of fruits, vegetables, and spices (FY 1996-2006) 

Country of 

origin

Shipments 

refused

Quantity refused, 

1996-2006

Quantity imported,

 2006

Top three goods refused, by number 

of shipments

Number Kilograms Kilograms

Mexico 1,418 8,346,009 3,952,110,724 Papaya (104), pepper (98), 

mango (97)

China 433 2,345,872 275,379,712 Citrus (130), szechuan pepper (104), 

ya pear (80)

Argentina 84 896,885 78,688,222 Citrus (24), mango (10), pear (5)

Brazil 74 1,129,368 103,591,410 Mango (42), papaya (12), citrus (9)

Spain 70 563,572 82,275,346 Pepper (31), citrus (21), cucumber (10)

Source: USDA, Economic Research Service using USDA, Animal and Plant Health Inspection Service PPQ 280 data (1996-2006) and U.S. 

Census Bureau data (2006).
18

The Economics of Agricultural and Wildlife Smuggling / ERR-81

Economic Research Service/USDA

Analysis of U.S. Fish and Wildlife 

Service Targeted Inspections Data 

FWS (2005) used goods refused at import to characterize illegally traded 

wildlife goods based on entries in FWS’s Law Enforcement Management 

Information System (LEMIS) declaration subsystem during 2000-04. The 

study explicitly acknowledged the known biases previously mentioned with 

APHIS inspections data. Refusals consist of goods that were given the disposition codes of seized, abandoned, or re-exported. While abandoned and 

re-exported goods suggest that trade might have been inadvertent, inspectors indicate that these goods are actually being traded illegally. The data 

collected through LEMIS are divided into the following taxonomic groups: 

reptiles, mammals, birds, mollusks, fish, coral, insects, amphibians, echinoderms, arachnids, crustaceans, and invertebrates. LEMIS data contain records 

on the number of goods imported each year as distinguished by country of 

origin, intended purpose (personal, commercial, hunting), estimated value 

(when possible), species, and size of shipment. Unlike goods under the PPQ 

280 system, where the pest risk may be unknown when the good is imported, 

goods refused under the LEMIS system are known to be prohibited from 

entry into the United States. 

Total refusals of wildlife goods in LEMIS data are disaggregated by purpose 

as follows: 61 percent for personal, 33 percent for commercial, 5 percent 

for hunting, and less than 2 percent for other reasons. Though the share of 

personal shipments refused each year (24 percent) is considerably higher than 

that of commercial shipments (1 percent) (FWS, 2005, p. 133), FWS does 

not distinguish between commercial and personal shipments in its detailed 

data reporting. The average refusal rate for all wildlife shipments was consistent at around 2.5 percent per year between 2000 and 2004, which includes 

both personal and cargo shipments. Note that about 24 percent of all wildlife 

shipments are inspected.20 From the LEMIS data, it is difficult to determine 

the SPS risks posed by illegally traded wildlife. Certain types of frequently 

traded wildlife goods, such as animal leather, bones, and shells, are likely to 

pose a relatively small threat. Conversely, nonthreatened wildlife entering 

the United States legally may pose an SPS risk without causing a resource 

risk because quarantine and disease inspection measures are inadequate (for 

example, deer transported by U.S. hunters returning from Canada21). 

Based on refusals in LEMIS data, the wildlife goods entering the United 

States with the highest percentage of refused entry are reptiles, coral, birds, 

and echinoderms (including starfish and sea cucumbers) (table 7). High 

refusal percentages for these goods are associated with a small volume of 

imports. This suggests that importers refrain from trading goods with a high 

probability of detection. 

Based on primary use of refused goods, the following is evident. First, 

refused goods tend to be goods that are high in value relative to their size and 

might be characterized as luxuries, such as boots and shoes produced with 

alligator or crocodile leather, jewelry, and traditional medicines. Caviar was 

recently added to the CITES list of restricted species after Caspian Sea stocks 

grew extremely depleted, and illegal trade in caviar has been particularly 

problematic. Second, for most animal categories (except birds), the meat and 

20Isolating commercial shipments 

to arrive only from air cargo, ocean 

cargo, mail, rail, or truck changes this 

figure from 24 to 25 percent (FWS, 

2005, pg. 137).

21USDA enacted several restrictions 

on Canadian wildlife imports after the 

2003 discovery of bovine spongiform 

encephalopathy in a Canadian dairy cow.
19 

The Economics of Agricultural and Wildlife Smuggling / ERR-81

Economic Research Service/USDA

live animal trade represents a relatively small portion of illegal trade, which 

is significant if these items have a greater SPS risk than other wildlife products, such as jewelry, leather, bone, and skin products.

Table 8 shows total refused wildlife imports as a proportion of total legal 

wildlife imports by country. The data do not distinguish between cargo and 

passenger shipments. Excluding the totals for Laos and Azerbaijan (whose 

wildlife trade is extremely small), Mexico is shown to have the highest rate 

of refusal of wildlife goods (and total number of refusals), but this finding is 

likely the result of the large amount of passenger travel between the United 

States and Mexico.22 After China, the percentage refused falls to 4.8 percent 

for Vietnam, the 11th-ranked country, whereas the median refusal rate for all 

countries is 4.0 percent. In terms of total refusals, Mexico, China, and Russia 

rank first, third, and sixth, respectively. For Mexico and Nicaragua, refused 

goods typically include live birds and snakes and leather products made 

22FWS (2005, p. 128) also notes that 

“the high number and rate of refusal 

(28.1 percent) for imports from Mexico 

is largely due to the strict prohibitions 

against export of most wildlife without 

permits, coupled with a vibrant trade in 

a variety of protected species products 

such as reptile skin boots.”

Table 7

Number of wildlife shipments refused in FWS LEMIS data, 5-year totals (2000-04)

Category

Total 

cleared Seized Abandoned 

Reexported Total 

refused Total 

Share 

refused

Primary uses of 

refused products

 --------------------------------------- Number --------------------------------------- Percent

Reptiles 85,379 3,255 1,267 641 5,163 90,542 5.7 Leather products, shoes 

Coral 19,021 611 407 105 1,123 20,144 5.6 Raw and live coral

Birds 48,141 1,213 467 402 2,082 50,223 4.1 Live birds, feathers, trophies

Echinoderms2,249 27 39 8 74 2,323 3.2 Bodies,* shells*

Mammals 218,353 3,146 1,322 528 4,996 223,349 2.2 Medicinals, skins, ivory

Fish 146,398 1,014 513 129 1,656 148,054 1.1 Caviar, live fish,* meat*

Mollusks 155,317 858 438 454 1,750 157,067 1.1 Shells for jewelry

All others 132,786 267 150 87 504 133,290 0.4

*Most of these products were regulated under domestic and foreign laws other than the Convention for the Trade of Endangered Species or the 

Endangered Species Act. 

Source: USDA, Economic Research Service using U.S. Fish and Wildlife Service (FWS), “U.S. Illegal Wildlife Trade” (2005, p. 6, table 7).

Table 8

Total refused shipments of wildlife by country of origin, 5-year totals (2000-04) 

Rank

Country of 

origin Cleared Abandoned Re-exported Seized Total 

Total 

refused

Share 

refused

 ------------------------------------------------ Number ----------------------------------------------- Percent

1 Laos 41 11 25 202 279 238 85.3

2 Azerbaijan 41 55 1 63 160 119 74.4

3 Mexico 9,641 1,743 229 1,800 13,413 3,772 28.1

4 Russia 2,149 252 13 297 2,711 562 20.7

5 Nigeria 1,415 151 7 165 1,738 323 18.6

6 Nicaragua 776 17 23 111 927 151 16.3

7 El Salvador 1,240 46 3 131 1,420 180 12.7

8 Unknown 904 61 49 14 1,028 124 12.1

9 Marshall 

Islands

844 2 2 98 946 102 10.8

10 China 15,555 264 178 696 16,693 1,138 6.8

Source: USDA, Economic Research Service using U.S. Fish and Wildlife Service, “U.S. Illegal Wildlife Trade” (2005, p. 129, table 35).
20

The Economics of Agricultural and Wildlife Smuggling / ERR-81

Economic Research Service/USDA

from reptile skin. In these cases, the movement of live animals is of special 

concern, especially among birds, due to the potential of these animals to 

introduce diseases and pathogens into the United States. For China, refused 

goods often include traditional medicinal products made from a variety of 

animals as noted in Henry (2004) and Von Hippel and Von Hippel (2002). 

Refused goods from Russia often include caviar. 

The proportion of the monetary value of the illegal wildlife trade to that of 

all wildlife trade is approximately 0.4 percent based on refusal data after 

correcting for data anomalies (table 9).23 As with APHIS inspections data, if 

targeting occurs across the type of good imported, its origin, and its arrival 

conveyance, this estimate will be biased upward.

However, no further adjustment is made to correct for this potential bias for 

several reasons. Unlike agricultural inspections, wildlife goods inspections 

are more specifically directed at uncovering illicit trade, making the reported 

rates of interception much more reliable. Little correlation exists in refusal 

and inspection rates across transport methods, which indicate that alternative 

transports likely receive the same level of scrutiny. Based on the number of 

shipments, a larger percentage (around 1 percent) of inspected commercial 

import entries than personal entries is refused (FWS, 2005, p. 133). Finally, 

there is no obvious manner in which this bias might be corrected. 

23In table 9, “lines refused” refers to 

shipment entries refused. “Share with 

no value” refers to the percentage of 

imports that have no recorded import 

value because they cannot be legally 

sold (FWS, 2005, p. 122). 

Table 9

Value of legal and illegal trade in wildlife 

Year

Lines 

refused

Value 

refused

Share with 

no value

Lines 

cleared Value cleared

Share with 

no value All shipments value

Share of total 

refused

Number Dollars Percent Number Dollars Percent Dollars Percent

2000 4,510 5,371,5621 26.4 259,629 1,702,763,815 11.0 1,713,435,377 0.6

2001 4,352 6,607,5992 22.2 310,508 1,468,274,339 10.1 1,475,381,938 0.5

2002 4,467 4,467,893 21.8 340,300 1,356,102,306 8.8 1,360,570,199 0.3

2003 4,712 4,381,595 28.5 375,200 1,512,419,944 9.2 1,516,801,539 0.3

2004 4,824 4,056,743 27.1 378,524 1,766,764,3993 6.6 2,770,821,142 0.2

Total 30,685,392 8,806,324,803 8,837,010,196 0.4

1Excludes an outlier for ivory in 2000 valued at $5.3 million. 2Excludes an outlier for caviar in 2001 valued at $0.5 million. 3Excludes an outlier for a panda bear in 2004 value at $1 billion. 

Source: USDA, Economic Research Service using U.S. Fish and Wildlife Service, “U.S. Illegal Wildlife Trade” (2005, p. 121, table 31).

 Illegal trade Legal trade Total trade
21 

The Economics of Agricultural and Wildlife Smuggling / ERR-81

Economic Research Service/USDA

The Characteristics of Agricultural and Wildlife Goods 

This analysis supports three general conclusions. First, illegally traded 

agricultural goods are not those conventionally sold in supermarkets but 

tend to be specialty items with a high value relative to their size. Food 

items interdicted by APHIS are more likely to be ethnic foods and spices, 

such as szechuan pepper (a citrus-based spice), tejocotes (a Mexican crab 

apple), and ya pear (an Asian pear variety). Inspections data corroborate 

this finding somewhat, with szechuan pepper and ya pear being frequently 

found, along with citrus and high-value tropical fruits, including mango and 

papaya. Second, illegally traded wildlife goods are likely to be luxury items 

to be used for jewelry, reptile-leather shoes, and other products; caviar; and 

medicinal goods. Third, Mexico and China represent a large percentage of 

the detected illegal trade for wildlife and agricultural goods, respectively, 

though biological and geographical factors may help account for the different 

percentages across countries. 
22

The Economics of Agricultural and Wildlife Smuggling / ERR-81

Economic Research Service/USDA

Conclusions 

The recent passage of the Plant Protection Act and the Animal Health 

Protection Act reflects the ongoing concern in the United States over sanitary 

and phytosanitary concerns and resource risk in an era of increasing agricultural and wildlife imports and recent costly episodes of invasive species 

introductions. Inspections of imports play a crucial role in risk management, 

and U.S. inspection agencies have undergone significant consolidation since 

the creation of the U.S. Department of Homeland Security in 2003. 

Several findings emerge from the examination of import refusals and 

interdiction data from APHIS and FWS. Illegal agricultural imports are 

driven primarily by specialty markets for ethnic foods and may reflect the 

general idiosyncrasies of agricultural trade prohibitions and enforcement. 

Illegal wildlife imports are driven by the trade in luxury items and jewelry, 

including leather products; culturally specific traditional medicines; ivory; 

caviar; and shell jewelry. These types of imports are also likely to command 

high prices relative to their cost and size, which is not surprising given the 

profit motive of smuggling. 

Smuggling of wildlife into the United States is most prevalent with Mexico, 

and smuggling of agricultural products is most prevalent with China. Both 

countries are major trade partners with the United States, and U.S. imports 

from both increased dramatically over the last 25 years. Similarly, immigration may have increased the prevalence of ethnic food, traditional goods, and 

medicinal goods that seem to be especially associated with illegal trade. In 

terms of size, detected illegal trade seems to be a significant part of the total 

wildlife trade and a smaller but nontrivial part of the agricultural trade. Based 

on the fragmentary inspection evidence, the illegal wildlife trade is approximately 1 percent of commercial wildlife shipments and 0.4 percent of the 

total value of the wildlife trade. Based on fragmentary interdiction evidence, 

the illegal agricultural trade has a lower bound of approximately 0.03 percent 

of total agricultural trade for China, which had the highest reported proportions and volumes. Still, these figures, along with most widely reported 

public estimates, are inexact due to the potential for bias in the data. 

Concerns over smuggling extend beyond risks surrounding invasive species 

or endangered wildlife. Expertise across different fields, including international law, criminology, economics, agricultural sciences, pathology, and 

environmental science, is necessary to formulate an impartial and comprehensive regulatory and enforcement regime. Idiosyncratic factors influence 

the need for individual regulations, yet the nature of inspections and border 

security has necessitated that risks from imports—SPS, resource, or other 

national security interests—be addressed in a unified manner. A better understanding of the incentives to smuggle goods is emerging and will aid further 

research efforts as markets and supply chains become more integrated. 
23 

The Economics of Agricultural and Wildlife Smuggling / ERR-81

Economic Research Service/USDA

References

Becker, Gary S. “Crime and Punishment: An Economic Approach,” Journal 

of Political Economy, 76(1968)2:169-217.

Bhagwati, J., and B. Hensen. “A Theoretical Analysis of Smuggling,” 

Quarterly Journal of Economics, 87(1973)2:172-187. 

Bushway, S., and P. Reuter. “Economists’ Contribution to the Study of 

Crime and the Criminal Justice System,” in Michael Torny (ed.), Crime 

and Justice, Volume 37: A Review of Research, University of Chicago 

Press, 2008.

Caulkins, J.P., and P. Reuter. “Illicit Drug Markets and Economic 

Irregularities,” Socio-Economic Planning Sciences, 40(2006):1-14. 

Caulkins, J.P., and P. Reuter. “What Price Data Tells Us About Drug 

Markets,” Journal of Drug Issues, 28(1998)3:593-612.

Convention on International Trade in Endangered Species of Wild Fauna and 

Flora. Appendix I, II, and III, http://www.cites.org/eng/app/E-Jul01.

pdf, current as of July 2008.

Dalebout, M.L., G.M. Lento, F. Cipriano, N. Fubahashi, and C.S. Baker. 

“How Many Protected Minke Whales Are Sold in Japan and Korea? 

A Census by Microsatellite DNA Profiling?” Animal Conservation, 

5(2002)143-152

DellaVigna, S., and E. La Ferrara. “Detecting Illegal Arms Trade,” NBER 

Working Paper 13355, August 2007. 

The Economist. “Easy Money,” September 21, 2006. 

Feinstein, J. “Approaches for Estimating Noncompliance: Examples 

from Federal Taxation in the United States,” The Economic Journal, 

109(1999)456:360-369.

Ferrier, P. “Illicit Agricultural Trade,” Agricultural and Resource Economic 

Review, 37(2008):2. 

Fischer, C. “The Complex Interactions of Markets for Endangered Species 

Products,” Journal of Environmental Economics and Management, 

48(2004):926-953.

Fischer, C. “Trading in Endangered Species: Legal Sales Versus Total 

Bans,” Resources, 150(2003):12-14.

Fisman, R., and S. Wei. “Tax Rates and Tax Evasion: Evidence 

from ‘Missing Imports’ in China,” Journal of Political Economy, 

112(2004)2:471-496.
24

The Economics of Agricultural and Wildlife Smuggling / ERR-81

Economic Research Service/USDA

Fisman, R., and S. Wei. “The Smuggling of Art, and The Art of Smuggling: 

Uncovering the Illicit Trade in Cultural Properties and Antiques,” NBER 

Working Paper 13446, 2007. 

Goel, R.K. “Cigarette Demand in Canada and the U.S.: Canadian Cigarette 

Smuggling,” Applied Economic Letters, 11(2004):537-540.

Golub, S., and A. Mbaye. “Colonial History, Regional Integration and 

Smuggling in South Africa: The Case of The Gambia,” Swarthmore 

College Working Paper, June 2007. 

Hansen, Eric. Orchid Fever, Random House Books, 2000.

Heltberg, R. “Impact of the Ivory Trade Ban on Poaching Incentives: A 

Numerical Example,” Ecological Economics, 36(2001):189-195.

Henry, L. “A Tale of Two Cities: A Comparative Study of Traditional 

Chinese Medicine Markets in San Francisco and New York City,” 

TRAFFIC North America: World Wildlife Fund, 2004. 

Howse, R. “The Appellate Body Ruling in the Shrimp/Turtle Case: A New 

Legal Baseline in Trade and Environmental Debate,” 27 Columbia Review 

of Law (2002) 489.

Hutton, J. “Who Knows Best? Controversy of Unilateral Stricter Domestic 

Measures,” in Endangered Species, Threatened Convention: The Past, 

Present and Future, J. Hutton and B. Dickson (eds.), Earthscan Ltd., 

2000. 

Interpol. Personal communication, October 2006.

Interpol. Wildlife Crime, http://www.interpol.int, accessed April 10, 2008.

Ivanova, K. “Corruption, Illegal Trade, and Compliance with the Montreal 

Protocol,” Environmental Resource Economics, (2007) 38:475-496.

Jacob, B., and S. Levitt. “Rotten Apples: An Investigation of the Prevalence 

and Predictors of Teacher Cheating,” Quarterly Journal of Economics,

118(2003)3: 843-877.

Kane, L. “A Recipe for Scampi - How It Really Gets To Your Table,” 

Customs and Border Patrol Today, December 2004, http://www.cbp.gov/

xp/CustomsToday/2004/Dec/commoditytrail.xml.

Karesh, W.B., R.B. Cook, E.L. Bennet, and J. Newcomb. “Wildlife 

Trade and Global Disease Emergence,” Emerging Infectious Disease, 

11(2005)7:1000-1002. 

Kemp, M. “Smuggling and Optimal Commercial Policy,” Journal of Public 

Economics, 5(1976)3:381-384.

Kremer, M., and C. Morcom. “Elephants,” American Economic Review, 

90(2000)1:212-234
25 

The Economics of Agricultural and Wildlife Smuggling / ERR-81

Economic Research Service/USDA

Levitt, S.D. “Using Electoral Cycles in Police Hiring to Estimate the Effect 

of Police on Crime,” American Economic Review, 87(1997)3:270-290. 

Lynch, L., and E. Lichtenberg. “Foreword: Special Issue on Invasive 

Species,” Agricultural and Resource Economics Review, 35(2006)1:iii-v.

Mack, R.N., S.C.H. Barrett, P.L. deFur, W.L. MacDonald, L.V. Madden, 

D.S. Marshall, D.G. McCullough, P.B. McEvoy, J.P. Nyrop, 

S.E.H. Reichard, K.J. Rice, and S.A. Tolin. Predicting Invasions of 

Non-Indigenous Plants and Plant Pests, National Research Council, 

National Academy Press, 2002.

Malik, S., P.J. Wilson, R.J. Smith, D.M. Lavigne, and B.N. White. “Pinniped 

Penises in Trade: A Molecular-Genetic Investigation,” Conservation 

Biology, 11(1997)6:1365-1374. 

Martin, L., and Panagariya, A. “Smuggling, Trade and Price Disparity,” 

Journal of International Economics, 117(1984)3:4:201-217. 

Martin, R.B. “When CITES Works and When It Does Not,” in Endangered 

Species, Threatened Convention: The Past, Present and Future, John 

Hutton and Barnabas Dickson (eds.), Earthscan Ltd., 2000. 

Meissner, H., A. Lemay, T. Kalaris, J. Vila, R. Duncan, and R. Olive. 

Mexican Border Risk Analysis, Plant Epidemiology and Risk Analysis 

Laboratory, Center for Plant Health Science and Technology, 2003.

Min, H., M. Gopinath, S. Buccola, and P. McEvoy. “Rent-Seeking in 

Invasive Species Regulation: The Case of Noxious Weeds,” Land 

Economics, 84 (2): 306-326.

Naim, M. Illicit: How Smugglers, Traffickers and Copycats Are Hijacking 

the Global Economy, Doubleday, 2000.

Norton, D. “On the Economic Theory of Smuggling,” Economica, 

55(1988)217:107-118. 

Reed, Robert, N. “An Ecological Risk Assessment of Nonnative Boas 

and Pythons as Potentially Invasive Species in the United States,” Risk 

Analysis, 25(2005)3: 753-766

Roe, D., Mulliken, T., and Milledge S. (eds.). Making a Killing or Making a 

Living: Wildlife Trade, Trade Controls and Rural Livelihoods, IIED and 

UCN, London, UK, 2002.

Ryan, M.A. “Finding Food Imposters: It’s Not Just Peanuts,” Today’s 

Chemist at Work, 7(1998)6:63-66, http://pubs.acs.org/hotartcl/tcaw/98/

jun/fin.html.

Saba, R.P., R.T. Beard, and R.B. Ekelund. “The Demand For Cigarette 

Smuggling,” Economic Inquiry, 33(1995):189-202. 
26

The Economics of Agricultural and Wildlife Smuggling / ERR-81

Economic Research Service/USDA

Strumpf, K. Illegal Sports Bookmakers, University of North Carolina 

Working Paper, 2003.

Thursby, M., R. Jensen, and J. Thursby. “Smuggling, Camouflaging, and 

Market Structure,” Quarterly Journal of Economics, 106(1991)3:789-814. 

U.S. Department of Agriculture, Agricultural Marketing Service (AMS). 

Agricultural Export Transportation Handbook, Agriculture Handbook 

700, 2004.

U.S. Department of Agriculture, Animal and Plant Health Inspection Service 

(APHIS). Personal communication, USDA-APHIS-SITC Staff in Raleigh, 

NC, August 2006.

U.S. Department of Agriculture, Animal and Plant Health Inspection Service 

(APHIS). “APHIS Preclearance Programs,” Revised March 24, 2004, 

on file with author and available at: www.aphis.usda.gov/import_export/

plants/plant_imports/downloads/preclearance_chart.pdf.

U.S. Department of Commerce, Census Bureau (Census Bureau). U.S. 

Imports of Merchandise, various years.

U.S. Department of Homeland Security, Customs and Border Protection 

(CBP). “Customs and Border Patrol Press Kit: Agriculture,” www.cbp.

gov/xp/cgov/newsroom/fact_sheets/cbp_overview/press_kit/, accessed 

May 10, 2007a.

U.S. Department of Homeland Security, Customs and Border Protection 

(CBP). Personal communication, Port of Baltimore Agricultural 

Inspectors, September 21, 2007b.

U.S. Department of Homeland Security, Customs and Border Protection 

(CBP). “U.S. Customs and Border Patrol Interception of Illegal Citrus 

Cuttings Becomes First Felony Conviction in Violations of the Plant 

Protection Act of 2005,” Press release dated September 9, 2005. 

U.S. Department of the Interior, Fish and Wildlife Service, Office of Law 

Enforcement Intelligence Unit (FWS). U.S. Wildlife Trade: An Overview 

for 1997-2003, 2003, www.fws.gov/le/pdffiles/Wildlife Trade Overview 

Report.pdf.

U.S. Department of the Interior, Fish and Wildlife Service (FWS). “U.S. 

Illegal Wildlife Trade: LEMIS Data Analysis and Risk Assessment,” 

Internal FWS Report, November 2005. 

U.S. Department of the Interior, Fish and Wildlife Service (FWS). Personal 

correspondence regarding import/shipments recorded in LEMIS, 

December 2008.

U.S. Government Accountability Office (GAO). Homeland Security Office: 

Management and Coordination Problems Increase the Vulnerability of 

U.S. Agriculture to Foreign Pests and Disease, GAO-Report 06-664, 

2006, www.gao.gov/new.items/d06644.pdf
27 

The Economics of Agricultural and Wildlife Smuggling / ERR-81

Economic Research Service/USDA

U.S. Government Accountability Office (GAO). Persistent Weaknesses in the 

In-Bond Cargo System Impede Customs and Border Protection’s Ability 

to Address Revenue, Trade, and Security Concerns, GAO-Report 07-561, 

2007, www.gao.gov/new.items/d07561.pdf

U.S. Departments of Agriculture and Homeland Security, Offices of the 

Inspector Generals (OIG). “Review of Customs and Border Protection’s 

Agriculture Inspection Activities,” Report OIG-07-32, February 2007, 

www.dhs.gov/xoig/assets/mgmtrpts/OIG_07-32_Feb07.pdf.

U.S. Office of Technology Assessment (OTA). Harmful Non-indigenous 

Species in the United States, OTAF-F-565, 1993.

Von Hippel, F.A., and W. Von Hippel. “Sex Drugs and Animal Parts: 

Will Viagara Save Threatened Species?” Environmental Conservation, 

29(2002)3:277-281. 

Von Kooten, G.C. “A Dynamic Bioeconomic Model of Ivory Trade: Details 

and Extended Results,” Working Paper #2006-03, University of Victoria, 

Department of Economics, Victoria, BC, Canada, 2006. 

Wasser, S.K., A.M. Shedlock, K. Comstock, E.A. Ostrander, B. Mutayoba, 

M. Stephens. “Assigning African Elephant DNA to Geographic Region 

of Origin: Application to the Ivory Trade,” Proceedings of the National 

Academy of Sciences, 101(2004)14847-14852, http://www.pnas.org/cgi/

content/full/101/41/14847.

Yang, D. “Can Enforcement Backfire? Crime Displacement in the Context 

of Customs Reform in the Philippines,” The Review of Economics and 

Statistics, 90(2008)1:1-14.