Policy Tools for Managing Biological Pollution Risks from Trade

Carson J. Reeling* and Richard D. Horan†

* Corresponding author

Department of Economics and Environmental Science and Sustainability Program Western Michigan University carson.reeling@wmich.edu

† Department of Agricultural, Food, and Resource Economics Michigan State University

Selected Poster prepared for presentation at the 2015 Agricultural & Applied Economics Association and Western Agricultural Economics

Association Joint Annual Meeting, San Francisco, CA, July 26-28

Copyright 2015 by Carson J. Reeling and Richard D. Horan. All rights reserved. Readers may make verbatim copies of this document for non-commercial purposes by any means, provided that this copyright notice a appears on all such copies.

RESULTS

1. Social planner’s first-order conditions (FOCs) for input vi ∊ {xi, zi, ai} and bi:

• Private FOCs ignore the biological pollution externality, yielding vi = vi

0 in Fig. B.

• Externality arises from ei, which depends only partly on trade decisions (xi, zi).

• Size of externality is smaller when risks are filterable; distance between privately-optimal risk mitigation and social optimum is smaller when mitigation has private benefits (blue line in Fig. B) than when mitigation has no private benefits (red line in Fig. B).

2. Efficiency can be attained through

• Individual-specific tax on ei: a “risk-based tax” (analogous to a NPS performance proxy tax) or

• Individual-specific taxes on xi, zi, ai (analogous to NPS input taxes).

3. Strategic complementarities may arise due to presence of e–i in Ωi; may cause multiple Nash equilibria.

• Prices alone may not yield efficient outcome in such settings.

• Command-and-control instruments (e.g., minimum requirements on zi) may be required in addition to incentives.

• These will not be binding, but align importers’ expectations of others’ behavior around the efficient outcome

CONCLUSIONS

Our findings contrast with prior trade literature in three ways: (1) Incentives must target the externality directly or all choices contributing to the externality – targeting only trade choices is inefficient; (2) Efficient incentives are importer-specific, and the magnitude of efficient incentives is smaller for choices (like trade choices) for which importers have private incentives for risk mitigation; and (3) Bilateral spillovers imply the possibility of multiple Nash equilibria and the need for additional, command-and-control policy instruments for efficiency.

ACKNOWLEDGEMENTS

We gratefully acknowledge funding from the USDA National Institute of Food and Agriculture, Grant #2011-67023-30872, grant #1R01GM100471-01 from the National Institute of General Medical Sciences (NIGMS) at the National Institutes of Health, and NSF grant #1414374 as part of the joint NSF-NIH-USDA Ecology and Evolution of Infectious Diseases program. The contents of the paper are solely the responsibility of the authors and do not necessarily represent the official views of USDA or NIGMS.

A MODEL OF DISEASE RISKS

• Importers, indexed by i = 1, … , N, within a region purchase a share xi ∊ [0, 1] of animals from a risk-free region and the rest from a risky region.

• Importer i can invest in surveillance, zi ∊ [0, 1], and abatement effort, ai ∊ [0, 1]. Surveillance prevents diseased animals from being introduced into one’s own herd, and infected animals are culled if detected. Abatement prevents disease from leaving one’s herd to infect neighboring importers and non-importers.

• We consider two cases (see Fig. A):

1. Unilateral spillovers (no bilateral externalities in Fig. A) – importer i can spread disease to neighbors, but cannot be infected by other importers.

• The social expected net benefits from live animal trade are

where ei = ei(xi, zi, ai) is the probability disease spreads from i’s herd: the “biological pollution production function”.

2. Bilateral spillovers – importer i can spread disease to neighbors, and vice versa. We assume here importers can invest in biosecurity, bi ∊ [0, 1], to protect themselves from spread of infection by neighbors.

• The social expected net benefits from live animal movements are

where now individual importers suffer biological pollution spillovers from their neighbors’ choices, e-i. Importers can reduce the probability of damage by investing in biosecurity bi.

FIG. B. THE ABILITY TO FILTER RISKS SHRINKS EXTERNALITIES UNDER UNILATERAL SPILLOVERS

Magnitude of externality when

risks are not filterable

Magnitude of externality when risks are filterable

1 – x–i

1 – xi

xi

x–i

z–i

Risk-

free

region

Risky

region

Importer

i’ s farm

Externality is from spread, and therefore occurs at this point

Non-

importing

producers

zi

ai a

–i

Neighboring

importers’

(–i ) farms

Disease flow

Disease risk

abatement

FIG. A. BIOLOGICAL POLLUTION PROCESS

Bilateral Externalities

a–i

ai b

–i

bi

INTRODUCTION

The spread of infectious livestock diseases from live animal movement can be considered a form of “biological pollution.” Prior literature assumes trade-related biological pollution externalities are unilateral (i.e., importers can spread disease to neighbors, but cannot be infected by other importers) and arise solely from trade of infected goods. Their results suggest uniformly-applied trade-based policies can efficiently manage disease risks. However, trade is only part of the externality, and importers may be at risk from infection by other importers.

We find the problem is more analogous to nonpoint source pollution problems:

• Biological pollution is stochastic and largely unobservable at reasonable cost; • Myriad choices generate external risks – not just trade choices. Some choices:

• Produce only public risk-management benefits (not included in prior work); • Produce both public and private risk management benefits: trade-related

biological pollution is a “filterable externality” (private risk management incentives not included in prior trade models), and spillovers may be bilateral;

• Heterogeneous importers generate heterogeneous disease risks.

We reframe trade-related biological pollution as nonpoint source pollution and explore efficient policy design. The nonpoint literature suggests efficiency may be attained by directly targeting all choices that contribute to emissions (not just trade decisions) or by indirectly targeting these choices via a performance-based proxy, a pollution production function that depends on these choices.

Policy Tools for Managing Biological Pollution Risks from Trade Carson J. Reeling1 and Richard D. Horan2 | 2Department of Agricultural, Food, and Resource Economics, Michigan State University

1Department of Economics and Environmental and Sustainability Studies Program, Western Michigan University

Optimal taxes are smaller when risks are filterable (see Fig. B)