Strategic Misspecification in Regression Models

Signorino, Curtis S.; Yilmaz, Kuzey

doi:10.2307/3186115

Cited by 52 publications

(74 citation statements)

References 6 publications

(13 reference statements)

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“…This selection model incorporates the strategic interaction hypothesized by our theory into the likelihood function to be estimated, which should improve the efficiency of our results and remove any bias due to strategic misspecification (Signorino, 1999;Signorino and Yilmaz, 2003). We argue that a candidate government faces uncertainty about the IMF's response when deciding to seek an agreement with the IMF.…”

Section: Sample Selection: Strategic Probit With Partial Observabilitymentioning

confidence: 94%

Adverse selection and growth under IMF programs

Bas

Stone

2013

Rev Int Organ

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The dominant approach to studying the effects of IMF programs has emphasized moral hazard, but we find that adverse selection has more impressive effects. We propose a novel strategic selection model to study the growth effects of IMF programs, which allows for the possibility of adverse selection. We find that adverse selection occurs: the countries that are most interested in participating in IMF programs are the least likely to have favorable growth outcomes. Controlling for this selection effect, we find that countries benefit from IMF programs on average in terms of higher growth rates, but that some countries benefit from participation, while others are harmed. Moral hazard predicts that long-term users of Fund resources benefit least from participating in programs, while adverse selection predicts the opposite. Contrary to previous findings, we find that IMF programs have more successful growth performance among long-term users than among short-term users.

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Section: Sample Selection: Strategic Probit With Partial Observabilitymentioning

confidence: 94%

Adverse selection and growth under IMF programs

Bas

Stone

2013

Rev Int Organ

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“…Therefore, these models do not capture the influence on a particular choice that results from interaction with other actors. The combination of choice models and game theory is a relatively new approach in the context of urban development, but it has been thoroughly adapted in other fields (Anderson et al, 2001;Bas et al, 2008;Arcidiacono et al, 2016;Chen et al, 1997;Choi and Desarbo, 1993;Clarke and Signorino, 2010;Hensher et al, 2007;Le Cadre et al, 2009;Luo et al, 2007;Signorino, 2003;Signorino and Yilmaz, 2003;Soetevent and Kooreman, 2007;Toivanen and Waterson, 2000).…”

Section: Phase 4: Strategic Choice Model (Scm)mentioning

confidence: 99%

A negotiation decision model for public–private partnerships in brownfield redevelopment

Glumac

Han

Schaefer

2016

Environment and Planning B: Urban Analytics and City Science

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Urban development cannot proceed without the commitment of multiple actors, because decisionmaking processes have become more and more interdependent. This article supports better decision-making in brownfield redevelopment projects in cases where the project realization depends on a public-private partnership between a municipality and a developer. In a broader sense, in this research, we investigate how the negotiation process in brownfield redevelopment projects can be improved by providing an understanding of the characteristics of a brownfield area and the interaction between the parties involved. In order to improve the process, a negotiation decision model is proposed. This is a hybrid model consisting of five phases. Its novelty lies in the combination of a latent class model and a strategic choice model that can be formulated as a prescriptive-interactive approach in decision theory. The hybrid negotiation model is applied to a reconstructed case study in order to present its possibilities. Accordingly, three applications of the model are introduced, and in each application the beneficiary is a municipality. Although using decision models for brownfield redevelopment projects has already been thoroughly studied, there is little evidence concerning the prescriptive-interactive component built into existing models.

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“…For example, the only functional forms to have been derived from formal theories of international conflict are massively violated by the restrictions of logit models, especially that logit probabilities are usually monotonic functions of the explanatory variables (Signorino 1999). Moreover, Signorino and Yilmaz (2003) prove that if even the simplest form of strategic interaction exists among the dyads, then the restrictions inherent in logit models make its estimates "biased and inconsistent." In contrast, neural network models can approximate and thus test models derived from strategic theory to any degree of precision.…”

Section: Model Flexibilitymentioning

confidence: 99%