We concern a sender-receiver game of common interests having infinite types, e.g the set [0; 1]², but with finite signals. In our paper, we extend the game by introducing multiple priors over the type space and use incomplete preferences in Bewley's way. We characterize the equilibria under...

In statistics, samples are drawn from a population in a datagenerating process (DGP). Standard errors measure the uncertainty in sample estimates of population parameters. In science, evidence is generated to test hypotheses in an evidencegenerating process (EGP). We claim that EGP variation...

We study optimal tax design based on the idea that policy-makers face trade-offs between multiple margins of redistribution. Within a Mirrleesian economy with earnings, consumption and retirement savings, we derive a novel formula for optimal income and savings distortions based on...

This festschrift celebrates the extensive contribution John Wanna has made to the research and practice of politics, policy and public administration. It includes both personal acknowledgements of his work and substantial essays on the issues that he focused most closely upon during his academic...

The focus of this volume is on the European context of public budget policy and a variety of different approaches are used - theoretical modelling, econometrics and applied general equilibrium modelling. Empirical evidence and case studies of European countries are contained in all the papers....

[Background] The 1992 United Nations Conference on Environment and Development made the first call for the creation of sustainability indicators to measure the changes in the social, economic, political, and physical factors of sustainability. Different concepts of carbon (Rees, 1992) and water...

General equilibrium models are typically presented with mathematical methods, such as the Edgeworth Box, that do not easily generalize to more than two goods and more than two agents. This is fine as a conceptual introduction, but it may be insufficient in the "Big Data-Machine-Learning-Era",...