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The economic development incentives game: an imperfect information, heterogeneous communities approach

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Abstract

The economic development incentives game developed in this paper extends the basic incentives game framework utilized in previous research by: (1) assuming heterogeneous communities with a priori unknown (to the communities or the firm) benefits and costs associated with the location, (2) providing a mechanism for communities to discover their true benefits and costs, and (3) allowing firms, as well as communities, to experience consequences associated with accepting a ‘bad deal’. Modeling an incentives competition game with these elements generates equilibrium behaviors and payoffs consistent with those observed in empirical and case studies.

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Notes

  1. Ellis and Rogers (2000) frame unilateral withdraw in the context of a negative business climate signal. Anderson and Wassmer (2000) discuss comparative disadvantage from unilateral withdrawal. Schragger (2009), Thomas (2007), Rodriguez-Pose and Arbiz (2001), and Buss (2001) provide a general discussion of why jurisdictions do not unilaterally withdraw from incentives competition.

  2. See Burstein and Rolnick (1995) and Buss (2001) for an overview of attempts to limit incentives competition between the States. Thomas (2007) discusses attempts to implement incentive controls at the international, national, and subnational level.

  3. The structure of the model developed herein is applicable to competition between governments at any level. The term community can thus be broadly interpreted. The model is concerned only with the competing jurisdictions, though. If any conclusion about global impacts were to be drawn, it would be with the implicit assumption that net positive benefits to the jurisdiction being analyzed are a necessary, but not sufficient, condition for wider-level benefits. If one assumes that the benefits of spillovers and externalities accrue within and outside jurisdictional boundaries, then the jurisdiction’s net benefit should reflect those within its borders.

  4. Kenyon et al. (2012) note the lack of ex ante and ex post evaluation of property tax incentive programs. One of the authors’ primary policy recommendations is broader implementation of benefit-cost analysis by jurisdictions. The Pew Charitable Trust also find that the majority of states do not use ex ante (or ex post) evaluation to inform economic development incentives policy (Pew Center for the States 2012).

  5. Based upon the process used by site selection consultants at Fantus Consulting, Ady (1997) describes the firm location decision as a three-stage process. Incentives, taxes, and public services are evaluated during the third stage when only a few potential sites remain in contention.

  6. The term “winner’s curse” is used differently in the empirical economic development incentives literature and the game theory literature. In the empirical incentives literature, the term “winner’s curse” refers to situations when the return on the public’s investment for an economic development project does not exceed the cost of the incentive. The “winner’s curse” in game theory refers to a phenomenon in common value auctions with incomplete information where the winning bid overestimates the value of the asset because the bidder fails “ to take account of estimating bias conditional on winning” (Wilson 1992).

  7. See Bucholz’s case study of the competition for FedEx in Schweke (2009) for an example of matched bidding.

  8. Wilson (1999) gives a very thorough survey of the tax competition literature from which I draw heavily.

  9. Although locations may still differ in terms of fundamentals, such as labor and market access, the assumption is that the final two locations are equally profit-maximizing when all these differences are included in the profit function. This assumption underlies the idea that incentives affect firm location on the margin and is in accordance with the firm location decision as a multi-stage process (see Sect. 2) rather than incentives as a compensating differential. Empirical evidence indicates incentives are not used as a compensating differential in practice (see Fisher and Peters 1998 or Anderson and Wassmer 2000 for a discussion). Some evidence suggests precisely the opposite – that incentives are “icing on the cake” for a location that is already more profitable.

  10. Given the current trend in economic development to contractually obligate firms to a certain number of jobs and/or capital investment in order to receive the incentives, uncertainty about \(X\) is not modeled.

  11. Note that communities face net new costs associated with workers and their families to the extent that location of the firm induces new residents or commuters that use the community’s services. The impact on current residents and firms results from a shortfall associated with firm and net new resident costs. If servicing the new firm or new residents requires new infrastructure, then costs will be much greater and are unlikely to be recouped through new taxes (Altshuler and Gomez-Ibanez 1993; Wassmer 2009).

  12. As noted in Kenyon et al. (2012), there is also an opportunity cost for the incentive, which is “... the net benefit that would have been generated if revenues used to pay for incentives were instead available to fund the next-best alternative.” Calculating this opportunity cost, however, is far from trivial.

  13. See Fisher (2007) for a confirming discussion on the availability of good direct benefit estimates. See Anderson and Wassmer (2000) for an example benefit-cost analysis.

  14. It is reasonable to assume that the communities and firm will know the communities’ types by reputation and observation. See Bucholz’s case study of Fed Ex in Schragger (2009) for an excellent discussion of the strategic reasons for firms to ensure communities are aware of competitor identities. See Ellis and Rogers (2000) for a discussion of reputation in the incentives game.

  15. It is also important to note that the community’s ‘information costs’ type does not provide a signal to the firm or the community about the true cost of service. For example, having invested in a sophisticated economic development organization does not provide information about the capacity and efficiency of water/sewer facilities.

  16. This means that communities know that a community revenue shortfall may result in a loss for the firm, but do not know the value of this loss. The parameter \(\psi \) is a scalar that transforms the community revenue shortfall into a loss and is unique to each firm. In order for full information about \(\psi \) to affect equilibrium bids, communities would also need to know the true benefit and cost parameters of the competing community. As currently modeled, this information is not revealed to the competing community (even when the discovery mechanism is exercised).

  17. Note that if communities are interpreted as local governments, then there is a policy recommendation for State or Federal intervention.

  18. This result might raise the concern that if all communities are type \(\underline{c}\) communities, then there may not be enough deal flow for each to recoup the investment of transitioning from a type \(\overline{c}\) to a type \(\underline{c}\) community. Whether or not this is truly an issue would be governed by the cost of transition. Assuming governments will spend on economic development anyway, then one could ease this concern by simply recommending that existing resources be redirected to the transition (e.g., do not start the new advertising campaign and use those funds for transition, have a staff member attend training on fiscal impact analysis rather than the next trade show, etc.)

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Acknowledgments

I would like to thank Mark Partridge, the editor, two anonymous referees, Benjamin Anderson, and James Peck for their comments and suggestions. I would also like to thank the participants at the 2010 North American Regional Science meetings, particularly my discussant Stefan Van Parys, the 2011 Western Regional Science Association meetings, and the 2011 Southern Regional Science Conference for their helpful comments.

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  1. Department of Economics Andrew Young School of Policy Studies, Georgia State University, P.O. Box 3992, Atlanta, GA, 30302-3992, USA

    Carlianne Patrick

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Correspondence to Carlianne Patrick.

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Patrick, C. The economic development incentives game: an imperfect information, heterogeneous communities approach. Ann Reg Sci 53, 137–156 (2014). https://doi.org/10.1007/s00168-014-0621-5

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