Model averaging has become a popular method of estimation, following increasing evidence that model selection and estimation should be treated as one joint procedure. Weighted-average least squares (WALS) is a recent model-average approach, which takes an intermediate position between frequentist and Bayesian methods, allows a credible treatment of ignorance, and is extremely fast to compute. We review the theory of WALS and discuss extensions and applications.
|Numero di pagine||32|
|Rivista||Journal of Economic Surveys|
|Stato di pubblicazione||Published - 2016|
All Science Journal Classification (ASJC) codes