While there is little doubt that innovations drive economic growth, their effects on well-being are less clear. One reason for this are ambivalent effects of innovations on well-being that result from pecuniary and technological externalities of innovations, argued to be inevitably. Another...

Although decision makers are often reported to have difficulties in making comparisons between multidimensional decision outcomes, economic theory assumes a unidimensional utility measure. This paper reviews evidence from behavioral and brain sciences to assess whether, and for what reasons,...

Can sustainability economics profit from the fusion with Amartya Sen's capability approach, thereby gaining solid normative foundations and wider applicability? We argue that this fusion is mistaken to the extent that the capability approach is essentially a static normative framework while...

Although decision makers are often reported to have difficulties in making comparisons between multi-dimensional decision outcomes, economic theory assumes a uni-dimensional utility measure. This paper reviews evidence from behavioral and brain sciences to assess whether, and for what reasons,...

In this paper, we analyze a general multivariate linear rational expectations model.

This paper examines the extent to which social interactions affect optimal consumption decisions in peer groups. To this purpose, a standard life-cycle model with quadratic utility is augmented to allow for three different forks of social interaction, namely, conformism, altruism, and jealousy....

This paper analyzes the consequences of introducing stochastic technological progress and stochastic labor input into a Solow-Swan exogenous growth model and an 'AK' endogenous growth model with general savings and production functions.

This paper establishes a link between the problem of solving multivariate linear rational expectations models and the problem of solving large sparse linear systems with a block-tridiagonal matrix coefficient structure. Such large linear systems arise in a wide variety of scientific problems,...

This paper considers estimation and inference in panel vector autoregressions (PVARs) with fixed effects when the time dimension of the panel is finite, and the cross-sectional dimension is large. A Maximum Likelihood (ML) estimator based on a transformed likelihood function is proposed and...