This paper proposes a novel and flexible framework to estimate autoregressive models with time-varying parameters. Our setup nests various adaptive algorithms that are commonly used in the macroeconometric literature, such as learning-expectations and forgetting-factor algorithms. These are...

This paper presents the multiple imputation model for the imputation of the missing values of the Austrian Household Survey on Housing Wealth 2008. It is based on Bayesian inference and on the fully conditional specification approach. Both theoretical framework and model specification are...

This paper proposes an operationally simple and easily generalizable methodology to incorporate climate change damage uncertainty into Integrated Assessment Models (IAMs). Uncertainty is transformed into a risk-premium, damage-correction, region-specific factor by extracting damage distribution...

We propose a novel framework for the economic assessment of climate-change policy. Our main point of departure from existing work is the adoption of a "satisficing", as opposed to optimizing, modeling approach. Along these lines, we place primary emphasis on the extent to which different...

We review some of the (theoretical) economic implications of David Schmeidler's models of decision under uncertainty (Choquet expected utility and maxmin expected utility) in competitive market settings. We start with the portfolio inertia result of Dow and Werlang (1992), show how it does or...