In this paper I show that an equilibrium exists to the sequential voting game in which a bandwagon begins with probability 1. These bandwagons are driven by a combination of beliefs and the desire of voters to vote for the winning candidate. Significantly, in this equilibrium the pivot probability for each voter is non-zero, even in an infinite population. Consequently, the bandwagons do not always start after one (or at most two) favourable decisions (as do economic cascades) and varying levels of informative voting are observed, consistent with observations from sequential voting in U.S. presidential primaries. Further, voters are exposed to counterintuitive incentives, referred to as “buyers' remorse”, that have been attributed to real primary voters. I also derive equilibrium behaviour in this environment when voting is simultaneous and compare the quality of information aggregation within each mechanism. I relate the conclusions to U.S. presidential primaries and find they are consistent with a common conclusion about the front-loading of the primary process: that in tight elections (with no front-runner) simultaneous voting is preferred, whereas in lopsided elections sequential voting is preferred. The superior performance of sequential voting in lopsided races is precisely because bandwagons occur.

I study a dynamic model of trial-and-error search in which agents do not have complete knowledge of how choices are mapped into outcomes. Agents learn about the mapping by observing the choices of earlier agents and the outcomes that are realized. The key novelty is that the mapping is represented as the realized path of a Brownian motion. I characterize for this environment the optimal behavior each period as well as the trajectory of experimentation and learning through time. Applied to new product development, the model shares features of the data with the well-known Product Life Cycle. (JEL D81, D83, D92, L26)

This paper considers a model of elections in which parties compete simultaneously for multiple districts. I show that if districts are heterogeneous, then a unique two‐party equilibrium exists under plurality rule in which further entry is deterred. The equilibrium requires that parties choose noncentrist policy platforms and not converge to the ideal policy of the median voter. These characteristics are consistent with empirical observation, in contrast to those of single‐district models. Necessary and sufficient conditions for the existence of the equilibrium are then characterized and related to Duverger’s law. The existence of multiple‐party equilibria in this environment is also considered.

Abstract We develop a model of policy experimentation in federal systems in which heterogeneous districts choose both whether to experiment and the policies to experiment with. The prospect of informational spillovers implies that in the first best the districts converge in their policy choice. Strikingly, when authority is decentralized, the equilibrium predicts the opposite. The districts use their policy choice to discourage other districts from free-riding on them, thereby inefficiently minimizing informational spillovers. To address this failure, we introduce a dynamic form of federalism in which the central government harmonizes policy choices only after the districts have experimented. This progressive concentration of power induces a policy tournament that can increase the incentive to experiment and encourage policy convergence. We compare outcomes under the different systems and derive the optimal levels of district heterogeneity.

We develop a model of experimentation and learning in policymaking when control of power is temporary. We demonstrate how an early office holder who would otherwise not experiment is nonetheless induced to experiment when his hold on power is temporary. This preemptive policy experiment is profitable for the early office holder as it reveals information about the policy mapping to his successor, information that shapes future policy choices. Thus policy choices today can cast a long shadow over future choices purely through information transmission and absent any formal institutional constraints or real state variables. The model we develop utilizes a recent innovation that represents the policy mapping as the realized path of a Brownian motion. We provide a precise characterization of when preemptive experimentation emerges in equilibrium and the form it takes. We apply the model to several well known episodes of policymaking, reinterpreting the policy choices as preemptive experiments.

The operation of markets and of politics are in practice deeply intertwined. Political decisions set the rules of the game for market competition and, conversely, market competitors participate in and influence political decisions. We develop an integrated model to capture the circularity between the two domains. We show that a positive feedback loop emerges such that market power begets political power, and political power begets market power, but that this feedback loop is bounded. With too much market power, the balance between politics and markets itself becomes lopsided and this drives a wedge between the interests of a policymaker and the dominant firm. Although such a wedge would seem pro‐competitive, we show how it can exacerbate the static and dynamic inefficiency of market outcomes. More generally, our model demonstrates that intuitions about market competition can be upended when competition is intermediated by a strategic policymaker.

Polarization is both a description of the current state of politics and a dynamic path that has rippled across the political domain over decades. We provide a simple model that explains why polarization appears incrementally and why it was elites who polarized first and more dramatically, whereas mass polarization came later and has been less pronounced. We incorporate an ostensibly unrelated finding about how voters form preferences into a dynamic model of elections. This change, when combined with the response of strategic candidates, creates a feedback loop that can replicate many features of the data. We explore the model’s implications for other aspects of politics and trace what it predicts for the future of polarization.

Expert advice often extends beyond a simple recommendation, including information about alternative options. To explore the role of this referential advice, we enrich the expert’s informational advantage in a canonical model of communication with hard information. We show that when constructed just right, referential advice dissuades the decision maker from choosing options other than the recommendation, thereby making the recommendation itself more persuasive. We identify an equilibrium in which, with probability 1, the expert is strictly better off providing referential advice than she is in any equilibrium in which she provides a recommendation alone.