We introduce an accurate, easily implementable, and fast algorithm to compute optimal decisions in discrete-time long-horizon welfaremaximizing problems. The algorithm is useful when interest is only in the decisions up to period T, where T is small. It relies on a flexible parametrization of...

Bayesian model averaging attempts to combine parameter estimation and model uncertainty in one coherent framework. The choice of prior is then critical. Within an explicit framework of ignorance we define a ‘suitable’ prior as one which leads to a continuous and suitable analog to the...

Data in econometrics are, as a rule, non-experimental and hence we have to use the same data set to select the model and also to estimate the parameters in the selected model.In standard applied econometrics practice, however, one reports zero bias and some variance of the (pretest) estimators...

This article is concerned with the estimation of linear regression models with uncertainty about the choice of the explanatory variables. We introduce the Stata commands bma and wals which implement, respectively, the exact Bayesian Model Averaging (BMA) estimator and the Weighted Average Least...

Two model averaging approaches are used and compared in estimating and forecasting dynamic factor models, the well-known BMA and the recently developed WALS. Both methods propose to combine frequentist estimators using Bayesian weights. We apply our framework to the Armenian economy using...

We propose a method to forecast the winner of a tennis match, not only at the beginning of the match, but also (and in particular) during the match.The method is based on a fast and exible computer program TENNISPROB, and on a statistical analysis of a large data set from Wimbledon, both at...

Economic motives are not the only reasons for committing a (small) crime. People consider social norms and perceptions of fairness before judging a situation and acting upon it. If someone takes a bundle of printing paper from the office for private use at home, then a colleague who sees this...

In econometrics, as a rule, the same data set is used to select the model and, conditional on the selected model, to forecast.However, one typically reports the properties of the (conditional) forecast, ignoring the fact that its properties are affected by the model selection (pretesting).This...