Common sense is a dynamic concept and it is natural that our (statistical) common sense lags behind the development of statistical science. What is not so easy to understand is why common sense lags behind as much as it does. We conduct a survey among Japanese students and try to understand why...

Gauss' 1809 discussion of least squares, which can be viewed as the beginning of mathematical statistics, is reviewed. The general consensus seems to be that Gauss' arguments are at fault, but we show that his reasoning is in fact correct, given his self-imposed restrictions, and persuasive...

An expected utility based cost-benefit analysis is in general fragile to its distributional assumptions. We derive necessary and sufficient conditions on the utility function of the expected utility model to avoid this. The conditions ensure that expected (marginal) utility remains finite also...

This papers offers a theoretical explanation for the stylized fact that forecast combinations with estimated optimal weights often perform poorly in applications. The properties of the forecast combination are typically derived under the assumption that the weights are fixed, while in practice...

This paper develops a dynamic model consisting of two regions (North and South), in which the accumulation of human capital is negatively influenced by the global stock of pollution. By characterizing the equilibrium strategy of each region, we show that the regions' best responses can be...

This paper studies what happens when we move from a short regression to a long regression (or vice versa), when the long regression is shorter than the data-generation process. In the special case where the long regression equals the data-generation process, the least-squares estimators have...

We analyze the impact of short-run and long-run earthquake risk on Japanese property prices. We exploit a rich panel data set of property characteristics, ward attractiveness information, macroeconomic variables, seismic hazard data, and historical earthquake occurrences, supplemented with...

Overconfidence seems to be an essential aspect of human nature, and one way to study overconfidence is to consider students' forecasts of their exam grades. Part of a student's grade expectation is based on the student's previous academic achievements; what remains can be interpreted as...

The weighted-average least squares (WALS) approach, introduced by Magnus et al. (2010) in the context of Gaussian linear models, has been shown to enjoy important advantages over other strictly Bayesian and strictly frequentist model averaging estimators when accounting for problems of...