Insurance loss data are usually in the form of left-truncation and right-censoring due to deductibles and policy limits, respectively. This paper investigates the model uncertainty and selection procedure when various parametric models are constructed to accommodate such left-truncated and...

This paper provides concise, nontechnical, step-by-step guidelines on how to conduct a modern meta-analysis, especially in social sciences. We treat publication bias, p-hacking, and heterogeneity as phenomena meta-analysts must always confront. To this end, we provide concrete methodological...

Standard economics models require that financial incentives improve performance, while leading theories in psychology allow for the opposite. Experimental results are mixed, and so far have not been corrected for publication bias and model uncertainty. We collect 1,568 economics estimates...

We propose a novel generalized recursive smooth ambiguity model which allows a three-way separation among risk aversion, ambiguity aversion, and intertemporal substitution. We apply this utility to a consumption-based asset pricing model in which consumption and dividends follow hidden Markov...

Simple financial ratios such as book-to-market are often used to identify value stocks. This paper examines the extent to which fundamental accounting information can be used to better identify truly undervalued value stocks to enhance profit in a simple value strategy. Gibbs sampling and model...

We study the effects of model uncertainty in a simple New-Keynesian model using robust control techniques. Due to the simple model structure, we are able to find closed-form solutions for the robust control problem, analysing both instrument rules and targeting rules under different timing...