Scott de Marchi

Untangling Neural Nets

Beck, King, and Zeng (2000) offer both a sweeping critique of the quantitative security studies field and a bold new direction for future research. Despite important strengths in their work, we take issue with three aspects of their research: (1) the substance of the logit model they compare to their neural network, (2) the standards they use for assessing forecasts, and (3) the theoretical and model-building implications of the nonparametric approach represented by neural networks. We replicate and extend their analysis by estimating a more complete logit model and comparing it both to a neural network and to a linear discriminant analysis. Our work reveals that neural networks do not perform substantially better than either the logit or the linear discriminant estimators. Given this result, we argue that more traditional approaches should be relied upon due to their enhanced ability to test hypotheses.

Cabinet Formation and Portfolio Distribution in European Multiparty Systems

Government formation in multiparty systems is of self-evident substantive importance, and the subject of an enormous theoretical literature. Empirical evaluations of models of government formation tend to separate government formation per se from the distribution of key government pay-offs, such as cabinet portfolios, between members of the resulting government. Models of government formation are necessarily specified ex ante, absent any knowledge of the government that forms. Models of the distribution of cabinet portfolios are typically, though not necessarily, specified ex post, taking into account knowledge of the identity of some government ‘formateur’ or even of the composition of the eventual cabinet. This disjunction lies at the heart of a notorious contradiction between predictions of the distribution of cabinet portfolios made by canonical models of legislative bargaining and the robust empirical regularity of proportional portfolio allocations – Gamson’s Law. This article resolves this contradiction by specifying and estimating a joint model of cabinet formation and portfolio distribution that, for example, predicts ex ante which parties will receive zero portfolios rather than taking this as given ex post. It concludes that canonical models of legislative bargaining do increase the ability to predict government membership, but that portfolio distribution between government members conforms robustly to a proportionality norm because portfolio distribution follows the much more difficult process of policy bargaining in the typical government formation process.

Congressional Bargaining in Presidential Time: Give and Take, Anticipation, and the Constitutional Rationalization of Dead Ducks

This article introduces a simple theory of bargaining between presidents and members of Congress. Although it employs the analytics common to the typical “sequenced” theories, its approach places more emphasis on give and take, on less reliable information about intentions, and on more complex strategic considerations. The formal results highlight a presidential tenure effect, which in turn suggests four empirical expectations. The article then uses a unique empirical opportunity and data to assess and eventually validate expectations suggesting, in turn, that declining presidential tenure has a substantial effect on confidential bargaining, making coalition formation more erratic and costly. The article concludes with a theoretically informed discussion of how growing congressional seniority led to imposing the 20th and 22nd constitutional amendments.