We develop a model of satisficing with evaluation errors that incorporates complexity at the level of individual alternatives. We test the model predictions in a novel data set with information on hundreds of millions of chess moves by experienced players. Consistent with the theory, complex...

Extremely rich data on farm households in Burkina Faso are used to test whether resource are allocated Pareto efficiently. The complexity of household structures, including multi-generation and polygynous households, is taken into account to developing tests from theoretical models of behavior....

Less developed countries tend to experience higher output volatility, a fact that is, in part, explained by their specialization in more volatile sectors. This paper proposes theoretical explanations for this pattern of specialization -- with the complexity of the goods playing a central role....

Disclosure policies have the potential to help consumers and make markets more efficient. Yet, the effectiveness of disclosure policies can be undermined if firms strategically make unfavorable information unnecessarily complicated to understand. To explore the incentives for using complexity in...

The extant literature predicts market returns with "simple" models that use only a few parameters. Contrary to conventional wisdom, we theoretically prove that simple models severely understate return predictability compared to "complex" models in which the number of parameters exceeds the...

This paper examines the econometric causal model for policy analysis developed by the seminal ideas of Ragnar Frisch and Trygve Haavelmo. We compare the econometric causal model with two popular causal frameworks: Neyman-Holland causal model and the do-calculus. The Neyman-Holland causal model...

This paper uses the concept of the triad census first introduced by Holland and Leinhardt, and describes several distributions on directed graphs. Methods are presented for calculating the mean and the covariance matrix of the triad census for the uniform distribution that conditions on the...

We define a general class of network formation models, Statistical Exponential Random Graph Models (SERGMs), that nest standard exponential random graph models (ERGMs) as a special case. We provide the first general results on when these models' (including ERGMs) parameters estimated from the...

Haavelmo's seminal 1943 paper is the first rigorous treatment of causality. In it, he distinguished the definition of causal parameters from their identification. He showed that causal parameters are defined using hypothetical models that assign variation to some of the inputs determining...

We propose that innovative originality (InnOrig) is a valuable organizational resource, and that owing to limited investor attention and skepticism of complexity, firms with greater InnOrig are undervalued. We find that firms' InnOrig strongly predicts higher, more persistent, and less volatile...