Controlling exotic species introductions: trade-related policies and exposure (Summary of research) Christopher Costello* Carol McAusland* ERS: August *University of California, Santa Barbara

Introduction Most unintentional introductions occur via trade –Large literature on the problem, small literature on what to do about it Policy instruments to control them: –Some argue to block (or slow) trade altogether –Others suggest more thorough inspections –Both are costly Empirically, which trade partners are most infectious? Basis for differential treatment?

2 Projects 1. Tariffs vs. Inspections Under what conditions would we favor tariffs vs. port inspections? How does optimal policy respond to characteristics of trade partner or magnitude of damage? 2. Accumulation Curves Can we estimate species introductions as a function of trade volume? Disentangle discoveries from introductions. Estimate marginal contribution from each trade partner.

Tariffs vs. Inspections Model of trade in “contaminated” goods. Foreign exports the good (and species) to Home, where inspections can take place. Key Questions: –Optimal tariff, inspections at Home? –Cease trade altogether? –If Foreign can clean up? –Multiple trade partners? –Dynamics of species populations post-introduction?

Model sketch 2 countries (Home and Foreign) Proportion q of goods is contaminated. Inspections effort (I), cost is kI, proportion intercepted r(I). Tariff (t) on all trade. Some evade inspection, damage linear in number that get through. Trade model of production in Foreign and Demand in Home (for traded product)

Home’s objective Components of Home’s Welfare: –Consumer Surplus –Tax Revenue from Tariff, inspection cost –Damage from undetected species 2 Decision Variables –Tariff and Inspections Intensity Objective: –Maximize Home Welfare

Some results Optimal tariff always positive –Set at Pigouvian level (expected damages plus cost of inspections) –Increases in infectedness of Foreign. Inspections should balance: –Cost of inspections, rejection of some traded product, damage from undetected infections. –May be zero –Are highest at intermediate infectedness of Foreign.

Conclusions Strong theoretical evidence for partner- specific policies May offer guidance for trade policy (tariffs & inspections) that that are contingent on characteristics of trade partner. McAusland and Costello Avoiding invasives: trade- related policies for controlling unintentional exotic species introductions. Journal of Environmental Economics and Management. In Press.

Empirical accumulation curves Previous paper is entirely theoretical Would like to establish empirical basis for differential treatment of trade partners Basic Question: Which partners are most infectious? More specifically: With 1 more unit of trade, how many new species should we expect from each partner?

Introduction Don’t ask: –Which partner has introduced more species Instead ask: –What is marginal effect of one more unit of trade from each partner? Data: –Trade volume over time –Species discoveries over time An important challenge is to disentangle discoveries from introductions [see Costello & Solow (2003) and Solow and Costello (2004)]

Approach Have discoveries as function of trade volume. Want introductions as function of trade volume. Develop empirically estimable model of: –New species introductions with each shipment –Effort over time to discover Perform calculations for multiple trade partners –Estimate marginal contribution of additional trade from each partner. Illustrate with 2 data sets: 1 terrestrial, 1 marine

Graphically… Trade Volume Cumulative Species V 2004 Accumulation curve is empirically estimated Slope gives marginal Contribution of more trade

An example with multiple partners Species Volume Both A and B have same cumulative volume of trade and same number of introductions to Home. A B But B has much higher marginal contribution of species from trade

Empirical applications Marine –San Francisco, about 140 species introduced via ballast water, discovery dates –Known origins (12 regions) –Trade volume by year by country ( ) Terrestrial –Still looking for empirical applications –Suggestions?