We investigate a process of decision-making in a multi-period winner-take-all contest, in which competing players simultaneously choose among actions with different levels of risk every period. Strategic risk-taking is analyzed in isolation from effort choices, and, according to expected utility theory, risk preferences are irrelevant. We derive a closed form solution of the dynamic game for any number of periods. In equilibrium, a leading player chooses the lowest level of risk, a trailing player chooses the highest level of risk, and all elements of the action space with intermediate levels of risk are irrelevant. We design a laboratory experiment to test various comparative statics of the model and explore behavioral deviations. Our findings are consistent with theoretical predictions – subjects tend to choose riskier lotteries when they are behind and safer lotteries when they are ahead, while the magnitude of the advantage does not seem to affect the risk-taking levels. We also observe some behavioral deviations such as a decline in risk-taking in the absence of the safe option, which only occurs while being behind. We find the quantal response equilibrium of our dynamic game and explain some of behavioral deviations; incorporating learning, subject types, and the probability weighting function into the behavioral model allows us to achieve a 40% improvement in fit and explain the rest of behavioral findings obtained from the data.

  • Dynamic Model of Endogenous Development: the Role of Pioneers [under review][Working paper (pdf)]

We investigate a dynamic development process which involves heterogeneous agents making location choices. In our spatial model agents differ from each other by the impact they have on the development dynamics. In equilibrium, a high impact agent, the pioneer, sacrifices some short-term benefits and chooses an underdeveloped location. The pioneer improves that location and creates incentives for other agents to choose it later in the game. We design a laboratory experiment to test various comparative statics of the model and analyze the role of pioneers as well as the effect that early investments in public goods have on long-term outcomes. Our findings are consistent with theoretical predictions – high impact subjects tend to choose pioneering more frequently than other agents. As predicted, improvements in initial conditions through early investments in public goods significantly affect the dynamics of the system and can lead to substantial welfare improvements. We also observe behavioral deviations such as when some low impact subjects consistently act as lesser pioneers and also choose an underdeveloped location. Learning and experimentation play a significant role in our experiments and help subjects’ behavior to match point predictions of the model.

  • Crowdfunding in Dynamics: Optimal Campaign Designs with Stretch Goals (with Arthur Nelson) [Available upon request]

Crowdfunding campaigns are widely used to successfully fund the production of innovative goods. Frequently the campaign designers rely on stretch goals – additional campaign goals, which stimulate consumers’ participation at a cost of providing free bonuses to buyers. We explore the role of such instruments within a novel dynamic model yielding a unique equilibrium for any length of the game. This allows us to demonstrate the flexibility of the setup with multiple goals and analyze optimal campaign designs. Our results show that the production costs dictate what goals should be chosen. In particular, production of digital goods is associated with a higher optimal target combined with a close-by stretch goal. Generally, crowdfunding campaigns allow producers to effectively compensate the increase in costs. Over time consumers expect a better campaign performance, which makes keeping the early momentum of the campaign critically important from the marketing standpoint.


  • Dynamics of Specialization Process: Experimental Evidence (with Luke Boosey and Sebastian Goerg) [Data collection in progress]

We study the way people adjust their specialization under ambiguity in future earnings, and there is a lot of evidence that workers in declining industries, such as coal miners, reject retraining, even with the state assistance. We design a laboratory experiment and focus on informational interactions between workers in a dynamic game, in which workers simultaneously choose occupations. We implement the learning-by-doing component as well as shocks to occupations. Thus, we introduce a trade-off between switching to a potentially more beneficial new occupation and sticking to an occupation which might be in crisis, while being more skillful in that occupation. Our results provide an insight on observed cyclical fluctuations of supply and demand of specialists in a given profession as well as technology-based changes such as industries dying off or new specializations appearing.

  • Endogenous Action Space: Experimental Results (with Dmitry Ryvkin)
  • Information Disclosure in Pure Risk-taking Dynamic Contests
  • Mobility Advantage in Dynamic Multi-battle Contests
  • Suspense and Surprise in Competitive Settings