Time heterogeneity, or the fact that subjects are measured at different times, occurs frequently in non-experimental situations. For time heterogeneous data having error components regression structure it is demonstrated that under customary normality assumptions there is no estimation method...

The difference between accommodated evidence (i.e. when evidence is known first and a hypothesis is proposed to explain and fit the observations) and predicted evidence (i.e., when evidence verifies the prediction of a hypothesis formulated before observing the evidence) is investigated....

This paper follows the theory of optimal taxation and the goal is to identify a tax/benefit design that maximizes social welfare. A two stage process is proposed where the individuals preferred choice of leisure and consumption is solved in the first stage, and the second stage identifies the...

Distance-based regression is a prediction method consisting of two steps: from distances between observations we obtain latent variables which, in turn, are the regressors in an ordinary least squares linear model. Distances are computed from actually observed predictors by means of a suitable...

Fifteen years of copy-editing experience – with theses (both in economics and in several medical fields), journal articles, book chapters and books, conference presentations, government reports, etc. – are distilled here. Papers are often sent to me for “language correction”, but what I...

Consider a model in which a consumer faces a lottery with j other people for a prize, so that the probability of winning the prize is 1/(j+1). Now let j be a random variable, determined by the binomial distribution. Specifically, let there be n potential competitors for the consumer in the...

Most multivariate variance models suffer from a common problem, the “curse of dimensionality”. For this reason, most are fitted under strong parametric restrictions that reduce the interpretation and flexibility of the models. Recently, the literature has focused on multivariate models with...

Most multivariate variance or volatility models suffer from a common problem, the “curse of dimensionality”. For this reason, most are fitted under strong parametric restrictions that reduce the interpretation and flexibility of the models. Recently, the literature has focused on...

The paper is concerned with analysing what makes a great journal great in economics, based on quantifiable measures. Alternative Research Assessment Measures (RAM) are discussed, with an emphasis on the Thomson Reuters ISI Web of Science database (hereafter ISI). The various ISI RAM that are...

The paper is concerned with analysing what makes a great journal great in the sciences, based on quantifiable Research Assessment Measures (RAM). Alternative RAM are discussed, with an emphasis on the Thomson Reuters ISI Web of Science database (hereafter ISI). Various ISI RAM that are...