Skip to main content

Advertisement

Log in

Economic Incentives for Managing Filterable Biological Pollution Risks from Trade

  • Published:
Environmental and Resource Economics Aims and scope Submit manuscript

Abstract

Infectious livestock disease problems are “biological pollution” problems. Prior work on biological pollution problems generally examines the efficient allocation of prevention and control efforts, but does not identify the specific externalities underpinning the design of efficiency-enhancing policy instruments. Prior analyses also focus on problems where those being damaged do not contribute to externalities. We examine a problem where the initial biological introduction harms the importer and then others are harmed by spread from this importer. Here, the externality is the spread of infection beyond the initial importer. This externality is influenced by the importer’s private risk management choices, which provide impure public goods that reduce disease spillovers to others—making disease spread a “filterable externality.” We derive efficient policy incentives to internalize filterable disease externalities given uncertainties about introduction and spread. We find efficiency requires incentivizing an importer’s trade choices along with self-protection and abatement efforts, in contrast to prior work that targets trade alone. Perhaps surprisingly, we find these incentives increase with importers’ private risk management incentives and with their ability to directly protect others. In cases where importers can spread infection to each other, we find filterable externalities may lead to multiple Nash equilibria.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3

Similar content being viewed by others

Notes

  1. One example is bovine viral diarrhea (BVD). BVD virus can spread from infected cattle to economically-valuable wildlife reservoirs (e.g., whitetail deer), but the risk from spillback infections—in which an infected deer transmits the disease to naïve cattle populations—is minimal (Passler et al. 2016). An alternative assumption that would also allow us to assume away any strategic behavior is that there is a single, representative importer within the region. We do not make this assumption because—as we show later—having multiple importers has important implications for policy design when externalities are filterable.

  2. Infected animals are assumed to be asymptomatic so that their individual health status is not known with certainty. For example, this may be the case with bovine tuberculosis, which has a long incubation period and is often only detected upon processing the animal in a slaughterhouse. It is through this detection, as well as random on-farm testing, that prevalence within a region is determined. We also assume vaccination is not a viable option. Even when available, vaccines may not be administered to livestock because vaccinated animals would test positive for disease (USDA-APHIS 2002). For instance, DEFRA (2014) estimates the EU would not allow trade of bTB-vaccinated cattle within ten years of the start of successful vaccination trials.

  3. Animal movements (e.g., via trade) are often prohibited during disease outbreaks, in which case the issue of purchasing animals from the risky source is moot. However, some policies allow for trade among sources within endemic areas. For example, “risk-based trading” enables livestock trade within endemic areas once importers have been made aware of the exporting herd’s health history (DEFRA 2014). Similarly, the EU’s Progressive Control Pathway (ECCFMD 2012) suggests various stages of control, including targeted movement controls that depend on risk differences between and within infected areas. In the current context, risk-based trading simply means importing from risky exporters is allowed given that importers are made aware of the risks relative to other areas (i.e., the risk-free exporters in our model).

  4. The uniform import risks facing each importer do not depend on our assumption of a single, uniformly risky export region. More generally, the risky sector will be heterogeneous. However, for imports originating from any particular exporter, each individual importer would still face the same infection probability associated with these imports.

  5. Inspection and quarantine efforts are undertaken by the individual importer rather than a government agency. Such efforts are commonly recommended anytime one’s animals are (re-)introduced to the herd (e.g., via trade or even after livestock shows; FAZD 2011). Additional, within-herd inspection efforts are not modeled, but these would be much more like inspection of imported animals in that they would provide impure public goods that protect the importer’s herd from possible spread of infection (and associated private losses) while simultaneously filtering the externalities.

  6. Inspections at slaughterhouses often detect disease and are able to trace these back to a particular producer’s herd, at which time all animals from that herd may be closely inspected. The value of the producer’s sales is then summarily reduced, and the producer may bear testing and other costs. In cases where infection is determined on the farm, losses may involve the entire herd. Entire herds are routinely culled upon detection of an infected animal during fast-moving outbreaks (including the 2001 and 2007 UK foot-and-mouth outbreaks; NADIS 2016). Recent studies have also suggested whole-herd culling is one of few highly effective strategies to control bovine tuberculosis in Britain (Brooks-Pollock et al. 2014). Note that these inspection measures are assumed to be made at fixed rates, perhaps external to individual producers. We could expand the model to incorporate on-farm inspection by the importer. Such a private choice, while a control measure, could be modeled much like the prevention choice of inspection of imported animals, with similar implications: protection of one’s herd from within-herd spread, while also providing the impure public good of reduced risk of disease spread off the farm. We make no attempt to model every possible risk-management choice. Rather, we focus on a few key, relevant choices that are commonly modeled in prior literature and that provide varying degrees of private and public benefits, thereby facilitating our goal of understanding the role of filterable externalities for policy design.

  7. We could generalize our model to allow for risk aversion by specifying importers’ utility over profits as \(u\left( \pi \right) \), with \({u}^{\prime }>0\) and \({u}^{\prime \prime }<0~ \forall \pi \). It is not clear how private risk aversion would impact the optimal choice of risk mitigation relative to the risk-neutral case we present here. However, in a model of optimal prevention and control of invasive species, Finnoff et al. (2007) show that regulators optimally choose less prevention (analogous to \(x_i \) and \(z_i \) in our model) and greater control (analogous to \(a_i )\) as the degree of public risk aversion increases. This is because control of an existing invasion is more certain than prevention activities.

  8. Unilateral externalities are highly relevant for broader invasive species problems. An example is salt cedar (Tamarix spp.), an invasive shrub that was introduced via the nursery trade and has become widely established in the Southwestern U.S. (Whitcraft et al. 2007).

  9. Horan and Lupi (2005a) model damages to depend on a random variable that jointly affects the likelihood of spread, \(P_i^S \left( {a_i } \right) \). Incorporating this added complexity does not affect the primary qualitative results.

  10. More generally, whether a particular control action is a private good, pure public good, or impure public good depends on whether the region is an importing or exporting region. For example, a livestock producer’s abatement \(a_{i}\) would be an impure public good if (i) the final good is exported outside the region and (ii) the value of the output (B) decreased with infection risks within the region, e.g., due to reputational effects on the price of exported goods (c.f. Liu and Sims 2016).

  11. Some types of risk mitigation activities may be classified as either a prevention- or control-related choice, depending on how they are implemented. For example, inspection can be classified as (i) a prevention choice (captured by \(z_i\)) if the point is to identify infected animals prior to introducing them to the region and (ii) a control choice (included in \(a_i\)) if the point is to identify infected animals once they are introduced. We stress that whether any specific activity is considered prevention or control depends only on whether the activity is meant to reduce the probability of introducing an infected animal to the region or the probability of the disease spreading within the region, once the disease is introduced.

  12. Simulation models of disease transmission are commonly used to coordinate control activity during acute outbreaks (e.g., the 2001 UK FMD outbreak; Ferguson et al. 2001). Similar models could be used to estimate biological pollution emissions if risk-based incentives were implemented in practice. This approach is analogous to the use of predictive models (e.g., SWAT, SPARROW) for estimating nonpoint source emissions from farms. Assuming risk neutrality and perfect traceability, an equivalent approach is to charge importers a fine if an outbreak occurs and the infection can be traced back to their trade decisions. The optimal fine will be larger if traceability is imperfect (i.e., if outbreaks can be traced back to the original importer with probability less than one).

  13. Because the efficient outcome is determined by the joint solution to all FOCs in (5), all decisions will generally depend on the degree to which each producer’s externalities are filterable. However, at the margin when N is large, the degree to which producer i’s externalities are filterable will have little direct effect on the values of \(e_j^*\), which are the terms directly impacting \(t_i^*\).

  14. The availability of a subsidy for importers’ inspection effort assumes that \(z_i \) is observable. Alternatively (and equivalently), we could assume that \(z_i \) is unobservable but that a benevolent regulatory authority can also provide inspection effort—say, z—in addition to the importer’s own \(z_i \). If we assume that \(z_i \) and z are perfect substitutes, then the aggregate level of inspection effort \(z_i +z\) chosen by the importer and regulator (perhaps according to a Stackelberg game where the importer chooses his optimal \(z_i \) given the regulator’s z) will be the same as that chosen using an optimally-derived subsidy.

  15. We assume the actions that protect one’s own herd (\(b_i\)) are distinct from those that protect neighboring herds (\(a_i\)). These may include activities that use the same technology. For example, \(b_i\) may involve sanitizing shared equipment before allowing it to enter one’s farm, whereas \(a_i\) may involve sanitizing the same equipment before it leaves one’s farm. We stress that the distinction between the activities depends only on whether the activity is meant to reduce the probability of infection to one’s own herd or the herds of others. This framework is easily extended to allow spillovers among some abatement and biosecurity efforts. This could be modeled as an additional choice that reduces both \(P^{E}\) and \(P^{S}\). This additional choice would introduce another source of filterability into the model, as individual importers would invest some effort in this choice to promote self-protection, whereas the social incentives for investment would be greater.

  16. A numerical example in which \(\partial \Omega _i \left( {e_i } \right) /\partial e_i <0\) is available from the authors upon request.

  17. Existence of at least one Nash equilibrium follows from a straightforward application of Brouwer’s Fixed Point Theorem (Mas-Colell et al. 1995).

  18. It is also possible that an importer’s marginal incentives for self-protection decrease with his neighbors’ self-protection, in which case producers’ self-protection choices are strategic substitutes (Hennessy 2007; Barrett 2004). This case would arise in our model if \(\partial \Omega _i \left( {e_i } \right) /\partial e_i >0.\) Symmetric Nash equilibria are unique under strategic substitution, and so the optimal risk-based tax would be the same as in (18).

  19. In practice, these regulations may be achieved through restrictions on the inputs to \(e_i \). Specifically, suppose that the regulator can set and enforce regulations designating a minimum share of animals, \(\underline{x}_{i} \), that can be purchased from the risk-free region. Suppose also the regulator can provide supplemental surveillance, \(\underline{z}_i \), of all animals from the risky region whenever \(x_i \ne 1\). If we let \(\bar{e}_i =e_i (\underline{x}_{i},\underline{z}_{i},a_{i})\), then these input-based regulations have the same effect as placing a maximum bound on \(e_i \).

References

  • Anderson S, Francois P (1997) Environmental cleanliness as a public good: welfare and policy implications of nonconvex preferences. J Environ Econ Manag 34:256–274

    Article  Google Scholar 

  • Barrett S (2004) Eradication versus control: the economics of global infectious disease policies. B World Health Organ 82:683–688

  • Berry K, Finnoff D, Horan RD, Shogren JF (2015) Managing the endogenous risk of disease outbreaks with non-constant background risk. J Econ Dyn Control 51:166–179

    Article  Google Scholar 

  • Brooks-Pollock E, Roberts GO, Keeling MJ (2014) A dynamic model of bovine tuberculosis spread and control in Great Britain. Nature 511(7508):228–231

    Article  Google Scholar 

  • Dasgupta P, Mäler K-G (2003) The economics of non-convex ecosystems: introduction. Environ Resour Econ 26:499–525

    Article  Google Scholar 

  • Daszak P, Cunningham AA, Hyatt AD (2000) Emerging infectious diseases of wildlife—threats to biodiversity and human health. Science 287:443–449

    Article  Google Scholar 

  • Department for Environment Food & Rural Affairs (DEFRA) (2014) The strategy for achieving officially bovine tuberculosis free status for England. https://www.gov.uk/government/uploads/system/uploads/attachment_data/file/300447/pb14088-bovine-tb-strategy-140328.pdf. Cited 3 Feb 2017

  • Elbakidze L (2007) Economic benefits of animal tracing in the cattle production sector. J Agric Resour Econ 32:169–180

    Google Scholar 

  • European Commission for the Control of Foot-and-Mouth Disease (ECCFMD) (2012) The progressive control pathway for FMD control (PCP-FMD): principles, stage descriptions and standards. http://www.fao.org/ag/againfo/commissions/docs/pcp/pcp-26012011.pdf. Cited 3 Feb 2017

  • Fenichel EP, Horan RD, Bence J (2010) Indirect management of invasive species through bio-controls: a bioeconomic model of salmon and alewife in Lake Michigan. Resour Energy Econ 32:500–518

    Article  Google Scholar 

  • Ferguson NM, Donnelly CA, Anderson RM (2001) The foot-and-mouth epidemic in Great Britain: pattern of spread and impact of interventions. Science 292:1155–1160

    Article  Google Scholar 

  • Finnoff D, Shogren JF, Leung B, Lodge D (2007) Take a risk: preferring prevention over control of biological invaders. Ecol Econ 62:216–222

    Article  Google Scholar 

  • Griffin RC, Bromley DW (1982) Agricultural runoff as a nonpoint externality: a theoretical development. Am J Agric Econ 64:547–552

    Article  Google Scholar 

  • Hennessy DA (2007) Biosecurity and spread of an infectious animal disease. Am J Agr Econ 89:1226–1231

  • Hennessy DA (2008) Biosecurity incentives, network effects, and entry of a rapidly spreading pest. Ecol Econ 68:230–239

    Article  Google Scholar 

  • Hirshleifer J (1983) From weakest-link to best-shot: the voluntary provision of public goods. Public Choice 41:371–386

    Article  Google Scholar 

  • Horan RD, Lupi F (2005a) Economic incentives for controlling trade-related biological invasions in the Great Lakes. Agric Resour Econ Rev 34:75–89

    Article  Google Scholar 

  • Horan RD, Lupi F (2005b) Tradeable risk permits to prevent future introductions of invasive alien species into the Great Lakes. Ecol Econ 52:289–304

    Article  Google Scholar 

  • Horan R, Perrings C, Lupi F et al (2002) Biological pollution prevention strategies under ignorance: the case of invasive species. Am J Agric Econ 84:1303–1310

    Article  Google Scholar 

  • Horan RD, Fenichel EP, Drury KLS, Lodge DM (2011) Managing ecological thresholds in coupled environmental-human systems. Proc Natl Acad Sci USA 108:7333–7338

    Article  Google Scholar 

  • Kim CS, Lubowski RN, Lewandrowski J, Eiswerth ME (2006) Prevention or control: optimal government policies for invasive species management. Agric Resour Econ Rev 35:29–40

    Article  Google Scholar 

  • Knowler D, Barbier E (2005) Importing exotic plants and the risk of invasion: are market-based instruments adequate? Ecol Econ 52:341–354

    Article  Google Scholar 

  • Leung B, Lodge DM, Finnoff D, Shogren JF, Lewis MA, Lamberti G (2002) An ounce of prevention or a pound of cure: bioeconomic risk analysis of invasive species. Proc R Soc Lond B 269:2407–2413

    Article  Google Scholar 

  • Liu Y, Sims C (2016) Spatial-dynamic externalities and coordination in invasive species control. Resour Energy Econ 44:23–38

    Article  Google Scholar 

  • Mas-Colell A, Whinston M, Green JR (1995) Microeconomic theory. Oxford University Press, New York

    Google Scholar 

  • McAusland C, Costello C (2004) Avoiding invasives: trade-related policies for controlling unintentional exotic species introductions. J Environ Econ Manag 48:954–977

    Article  Google Scholar 

  • Mehta SV, Haight RG, Homans FR, Polasky S, Venette RC (2007) Optimal detection and control strategies for invasive species management. Ecol Econ 61:237–245

    Article  Google Scholar 

  • Mérel PR, Carter CA (2008) A second look at managing import risk from invasive species. J Environ Econ Manag 56:286–290

    Article  Google Scholar 

  • Milgrom P, Roberts J (1990) Rationalizability, learning, and equilibrium in games with strategic complementarities. Econometrica 58:1255–1277

    Article  Google Scholar 

  • National Animal Disease Information Service (NADIS) (2016) Foot and mouth disease. http://www.nadis.org.uk/bulletins/foot-and-mouth-disease.aspx. Cited 3 Oct 2016

  • National Center for Foreign Animal and Zoonotic Disease Defense (FAZD) (2011) Biosecurity measures for meat goat and sheep managers. http://iiad.tamu.edu/wp-content/uploads/2012/06/Meat-Goat-and-Sheep-Part-1-English.pdf. Cited 5 Oct 2016

  • Olson LJ, Roy S (2005) On prevention and control of an uncertain biological invasion. Appl Econ Perspect Policy 27:491–497

    Google Scholar 

  • Paarlberg PL, Lee JG (1998) Import restrictions in the presence of a health risk: an illustration using FMD. Am J Agric Econ 80:175–183

    Article  Google Scholar 

  • Passler T, Ditchkoff SS, Walz PH (2016) Bovine viral diarrhea virus (BVDV) in white-tailed deer (Odocoa virginianus). Front Microbiol 7:1–11

    Article  Google Scholar 

  • Perrings C, Williamson M, Barbier EB, Delfino D, Dalmazzone S, Shogren J, Simmons P, Watkinson A (2002) Biological invasion risks and the public good: an economic perspective. Conserv Ecol 6:1

    Article  Google Scholar 

  • Perry BD, Grace D, Sones K (2011) Current drivers and future directions of global livestock disease dynamics. Proc Natl Acad Sci USA 110:20871–20877

    Article  Google Scholar 

  • Ranjan R, Marshall E, Shortle J (2008) Optimal renewable resource management in the presence of endogenous risk of invasion. J Environ Manag 89:273–283

    Article  Google Scholar 

  • Reeling CJ, Horan RD (2015) Self-protection, strategic interactions, and the relative endogeneity of disease risks. Am J Agric Econ 97:452–468

    Article  Google Scholar 

  • Shogren JF, Crocker TD (1991) Cooperative and noncooperative protection against transferable and filterable externalities. Environ Resour Econ 1:195–214

    Article  Google Scholar 

  • Shortle J, Abler D, Horan R (1998) Research issues in nonpoint pollution control. Environ Resour Econ 11:571–585

    Article  Google Scholar 

  • Thompson D, Muriel P, Russell D et al (2002) Economic costs of the foot and mouth disease outbreak in the United Kingdom in 2001. Rev Sci Tech OIE 21:675–687

    Article  Google Scholar 

  • Tietenberg TH (1985) Emissions trading, an exercise in reforming pollution policy. RFF Press, Washington

    Google Scholar 

  • Tweddle NE, Livingstone P (1994) Bovine tuberculosis control and eradication programs in Australia and New Zealand. Vet Microbiol 40:23–39

    Article  Google Scholar 

  • United States Department of Agriculture, Animal and Plant Health Inspection Service (USDA-APHIS) (2002) Foot-and-mouth disease vaccine factsheet. USDA-APHIS, Washington, DC

  • Vives X (2005) Complementarities and games: new developments. J Econ Lit 43:437–479

    Article  Google Scholar 

  • Wang T, Hennessy DA (2015) Strategic interactions among private and public efforts when preventing and stamping out a highly infectious animal disease. Am J Agric Econ 97:435–451

    Article  Google Scholar 

  • Whitcraft CR, Talley DM, Crooks JA et al (2007) Invasion of tamarisk (Tamarix spp.) in a Southern California salt marsh. Biol Invasions 9:875–879

    Article  Google Scholar 

  • Wilkins MJ, Bartlett PC, Frawley B et al (2003) Mycobacterium bovis (bovine TB) exposure as a recreational risk for hunters: results of a Michigan hunter survey, 2001. Int J Tuberc Lung Dis 7:1001–1009

    Google Scholar 

Download references

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.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Carson Reeling.

Appendix

Appendix

This appendix contains proofs of the major results stated in the main article text.

Proposition 1

The private optimum involves interior solutions when \(\Lambda _i >0\).

We have already shown that \(a_i^0 =0\) in the private optimum, and so we focus on the remaining choices. The marginal expected profits from \(z_{i}\) and \(x_{i}\), respectively, are:

$$\begin{aligned} \frac{\partial \pi _i }{\partial z_i }= & {} -w\left( {1-x_i } \right) h_z \left( {z_i } \right) +P^{I}\left( {x_i } \right) \frac{\partial P^{C}\left( {z_i } \right) }{\partial z_i }\left[ {\lambda -\delta \left( {1-x_i } \right) } \right] \end{aligned}$$
(19)
$$\begin{aligned} \frac{\partial \pi _i }{\partial x_i }= & {} \left( {wh\left( {z_i } \right) -v} \right) -\frac{\partial P^{I}\left( {x_i } \right) }{\partial x_i }\left[ {P^{C}\left( {z_i } \right) \left( {1-x_i } \right) \delta +\left( {1-P^{C}\left( {z_i } \right) } \right) \lambda } \right] \nonumber \\&+P^{I}\left( {x_i } \right) P^{C}\left( {z_i } \right) \delta . \end{aligned}$$
(20)

The relations in (19) and (20) involve both variables. Suppose \(x_i \rightarrow 1\). Then (19) implies \(\partial \pi _i /\partial z_i \rightarrow 0\,\forall z_i\), which means \(z_i \rightarrow 0\) as there is no economic reason to set \(z_i >0\). However, if \(z_i \rightarrow 0\), then (20) implies \(\partial \pi _i /\partial x_i <0\) as \(x_i \rightarrow 1\). These contradictory results imply that \(x_i^0 <1\). Moreover, our assumptions about \(P^{I}\left( {x_i } \right) \) ensure that \(x_i^0 >0\): hence \(x_i^0 \in \left( {0,1} \right) \).

Next, suppose \(z_i \ge \bar{z}\), where \(\bar{z}<1\) is defined such that \(wh\left( {\bar{z} } \right) =v\). Then (20) implies \(\partial \pi _i /\partial x_i >0\), so that \(x_i \rightarrow 1\). But we have already shown that \(x_i \rightarrow 1\) implies \(z_i \rightarrow 0\), resulting in a contradiction of our premise that \(z_i \ge \bar{z} \). Further, given \(x_i <1\), (19) implies that \(\partial \pi _i /\partial z_i >0\) when \(z_i \rightarrow 0\). These last two results imply an interior solution for \(z_i \): \(z_i^0 \in \left( {0,\bar{z} } \right) \). \(\square \)

Proposition 2

The efficient outcome involves interior solutions.

The marginal expected net social values of \(z_i \), \(x_i \), and \(a_i \), respectively, are:

$$\begin{aligned} \frac{\partial V}{\partial z_i }= & {} \frac{\partial \pi _i }{\partial z_i }+\Theta P^{I}\left( {x_i } \right) \frac{\partial P^{C}\left( {z_i } \right) }{\partial z_i }P_i^S \left( {a_i } \right) \end{aligned}$$
(21)
$$\begin{aligned} \frac{\partial V}{\partial x_i }= & {} \frac{\partial \pi _i }{\partial x_i }-\Theta \frac{\partial P^{D}}{\partial e_i }\frac{\partial P^{I}\left( {x_i } \right) }{\partial x_i }\left[ {1-P^{C}\left( {z_i } \right) } \right] P_i^S \left( {a_i } \right) \end{aligned}$$
(22)
$$\begin{aligned} \frac{\partial V}{\partial a_i }= & {} -f^{\prime }\left( {a_i } \right) -\Theta \frac{\partial P^{D}}{\partial e_i }P^{I}\left( {x_i } \right) \left[ {1-P^{C}\left( {z_i } \right) } \right] \frac{\partial P_i^S \left( {a_i } \right) }{\partial a_i } \end{aligned}$$
(23)

Essentially the same arguments made above for expressions (19) and (20) can be applied to expressions (21) and (22) to show that \(x_i^*\in \left( {0,1} \right) \) and \(z_i^*\in \left( {0,\bar{z} } \right) \). We therefore focus here on expression (23). When \(a_i =0\), then \(\frac{\partial V}{\partial a_i }=-\Theta \frac{\partial P^{D}}{\partial e_i }P^{I}\left( {x_i } \right) \left[ {1-P^{C}\left( {z_i } \right) } \right] \frac{\partial P_i^S \left( {a_i } \right) }{\partial a_i }>0\), whereas \(\partial V/\partial a_i =-{f}^{\prime }(a_{i})<0\) when \(a_i =1\). Hence, \(a_i^*\in \left( {0,1} \right) \). \(\square \)

Proposition 3

The private externality, \(e_i^0 \), exceeds the first-best externality, \(e_i^*\),when the restricted profit function \(\pi _i \left( {e_i } \right) =B-c\left( {e_i } \right) -\Lambda \left( {e_i } \right) =\mathop {max}\nolimits _{x_i ,z_i ,a_i } \{B-c\left( {x_i ,z_i ,a_i } \right) -\Lambda \left( {x_i ,z_i } \right) |e_i \left( {x_i ,z_i ,a_i } \right) \le e_i \}\) is concave in \(e_i\).

Define the generalized restricted profit function

$$\begin{aligned} \pi _i \left( {e_i ,\phi _i } \right)= & {} B-c\left( {e_i ,\phi _i } \right) -\phi _i \Lambda \left( {e_i ,\phi _i } \right) \nonumber \\= & {} \mathop {\max }\limits _{x_i ,z_i ,z_i } \left\{ {B-c\left( {x_i ,z_i ,a_i } \right) -\phi _i \Lambda \left( {x_i ,z_i } \right) \hbox {|}e_i \left( {x_i ,z_i ,a_i } \right) \le e_i } \right\} , \end{aligned}$$
(24)

where \(\phi _i \in \left[ {0,1} \right] \) is a parameter representing the degree of filterability so that a larger \(\phi _i \) implies more filterability. (Note that \(\phi _i \) only plays a role in proving Proposition 4 below; we introduce it here to avoid re-deriving the restricted profit function.) The privately optimal level of \(e_i \), denoted \(e_i^0 \left( {\phi _i } \right) \), solves

$$\begin{aligned} \frac{\partial \pi _i }{\partial e_i }=0. \end{aligned}$$
(25)

Given (24), we can rewrite expected social net benefits as

$$\begin{aligned} V\left( {\mathbf{e},{\varvec{\upphi }} } \right) =\sum \nolimits _{i=1}^N \pi _i \left( {e_i ,\phi _i } \right) -D\left( {P^{D}\left( {\mathbf{e},{\varvec{\upphi }} } \right) } \right) , \end{aligned}$$
(26)

where \({\varvec{\upphi }}\) is a vector with ith element \(\phi _i \). The first-best externality, \(e_i^*\left( {\phi _{i}} \right) \), solves

$$\begin{aligned} \frac{\partial \pi _i }{\partial e_i }=\Theta \frac{\partial P^{D}}{\partial e_i }. \end{aligned}$$
(27)

Upon comparing (27) and (25), concavity of \(\pi _i \left( {e_i ,\phi _i } \right) \) in \(e_i \) implies that \(e_i^0 \left( {\phi _i } \right) >e_i^*\left( {\phi _i } \right) \). \(\square \)

Proposition 4

Other things equal, the filterability of producer i’s externality reduces (i) both the privately-produced externality and the efficient externality of producer i when \(\pi _i \left( {e_i } \right) \) is concave in \(e_i \) and \(\Lambda \left( {e_i } \right) \) is increasing \(e_i \), and (ii) the difference \(e_i^0 -e_i^*\) if, additionally, \(\pi _i \left( {e_i } \right) \) is reasonably approximated by a quadratic relation (so that \(\partial ^{2}\pi _i \left( {e_i } \right) /\left( {\partial e_i } \right) ^{2}\) is essentially constant) and \(\Lambda \left( {e_i } \right) \) is convex in \(e_i\).

(i) Assume \(\frac{\partial ^{2}\pi _i }{\left( {\partial e_i } \right) ^{2}}<0\) and \(\frac{\partial \Lambda _i }{\partial e_i }>0\). Substitute \(e_i^0 \left( {\phi _i } \right) \) into (25) to create an identity, and then differentiate this identity with respect to \(\upphi _i \) to obtain

$$\begin{aligned} \frac{de_i^0 }{d\phi _i }=-\frac{\partial ^{2}\pi _i^0 /\left( {\partial e_i \partial \phi _i } \right) }{\partial ^{2}\pi _i^0 /\left( {\partial e_i } \right) ^{2}}=\frac{\partial \Lambda _i^0 /\partial e_i }{\partial ^{2}\pi _i^0 /\left( {\partial e_i } \right) ^{2}}<0, \end{aligned}$$
(28)

where the second equality in (28) is due to the envelope theorem: \(\partial \pi \left( {e_i ,\phi _i } \right) /\partial \phi _i =-\Lambda \left( {e_i ,\phi _i } \right) \). Expression (28) indicates that greater filterability reduces the privately optimal externality.

Now consider the efficient level of the externality. Recall that the RHS of (27) is independent of \(e_i \), as \(P^{D}\) is linear in \(e_i \). Substitute \(e_i^*\left( {\phi _i } \right) \) into (27) to create an identity, and then differentiate this identity with respect to \(\phi _i \) to obtain

$$\begin{aligned} \frac{de_i^*}{d\phi _i }=-\frac{\partial ^{2}\pi _i^*/\left( {\partial e_i \partial \phi _i } \right) }{\partial ^{2}\pi _i^*/\left( {\partial e_i } \right) ^{2}}=\frac{\partial \Lambda _i^*/\partial e_i }{\partial ^{2}\pi _i^*/\left( {\partial e_i } \right) ^{2}}<0. \end{aligned}$$
(29)

Expression (29) indicates greater filterability reduces the efficient value of the externality.

(ii) We extend the assumptions for part (i) by taking \(\frac{\partial ^{2}\pi _i }{\left( {\partial e_i } \right) ^{2}}\) to be essentially constant and \(\frac{\partial ^{2}\Lambda _i }{\left( {\partial e_i } \right) ^{2}}>0\). We want to show that the difference \(e_i^0 \left( {\phi _i } \right) -e_i^*\left( {\phi _i } \right) \) is decreasing in \(\phi _i \). We therefore derive

$$\begin{aligned} \frac{\partial \left( {e_i^0 \left( {\phi _i } \right) -e_i^*\left( {\phi _i } \right) } \right) }{\partial \phi _i }=\frac{\partial \Lambda _i^0 /\partial e_i }{\partial ^{2}\pi _i /\left( {\partial e_i } \right) ^{2}}-\frac{\partial \Lambda _i^*/\partial e_i }{\partial ^{2}\pi _i /\left( {\partial e_i } \right) ^{2}}=\frac{\partial \Lambda _i^0 /\partial e_i -\partial \Lambda _i^*/\partial e_i }{\partial ^{2}\pi _i /\left( {\partial e_i } \right) ^{2}}, \end{aligned}$$
(30)

where the second equality stems from our assumption that \(\partial ^{2}\pi _i /\partial e_i^2 \) is constant (independent of \(e_i )\). Given our result in part (i) that \(e_i^0 \left( {\phi _i } \right) >e_i^*\left( {\phi _i } \right) \), combined with convexity of \(\Lambda _i \), implies the numerator of the RHS of (30) is positive. As the denominator of the RHS of (30) is negative due to concavity of \(\pi _i \), this means (30) is negative. \(\square \)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Reeling, C., Horan, R.D. Economic Incentives for Managing Filterable Biological Pollution Risks from Trade. Environ Resource Econ 70, 651–671 (2018). https://doi.org/10.1007/s10640-017-0160-5

Download citation

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10640-017-0160-5

Keywords

Navigation