Statistical Default Models and Incentives

Location Reparameterization and Default Priors for Statistical Analysis

This paper develops default priors for Bayesian analysis that reproduce familiar frequentist and Bayesian analyses for models that are exponential or location. For the vector parameter case there is an information adjustment that avoids the Bayesian marginalization paradoxes and properly targets the prior on the parameter of interest thus adjusting for any complicating nonlinearity the details ...

Default options , incentives and food choices

Objective: Examine whether requiring children to place fruits and vegetables on their lunch trays increases consumption of these items. Design: Observational study that exploits naturally occurring variation between two school districts and a pre-post observational study at schools that changed their lunch policy mid-year. Setting: 15 elementary schools from two school districts, one requiring ...

Costly monitoring, dynamic incentives, and default

We study optimal dynamic financial contracts between a lender and a borrower in the presence of costly state verification. The efficient contract is such that (1) interim monitoring can prevent future inefficient liquidation of investment projects that are due to informational asymmetries and (2) two levels of bankruptcy can be distinguished, one that leads to monitoring and the other that lead...

Causal Models and Default

Incentives and Information as Driving Forces of Default Effects†

The behavioral relevance of non-binding defaults is well established. While most research has focused on decision makers’ responses to a given default, we argue that this individual decision making perspective is incomplete. Instead, a comprehensive understanding of default effects requires to take account of the strategic interaction between default setters and decision makers. We analyze theo...