Time-variation in disagreement about inflation expectations is a stylized fact in surveys, but little is known on how disagreement interacts with the efficacy of monetary policy. This paper fills this gap in providing theoretical predictions of monetary policy shocks for different levels of...

The green paradox conveys the idea that climate policies may have unintended side effects when taking into account the reaction of fossil fuel suppliers. In particular, carbon taxes that will be implemented in the future induce resource owners to extract more rapidly which increases present...

The pace of the global decarbonization process is widely believed to hinge on the rate of cost improvements for clean energy technologies, in particular renewable power and energy storage. This paper adopts the classical learning-by-doing framework of Wright (1936), which predicts that cost will...

This paper examines the implications of habit formation in private and public consumption for the Pareto-efficient provision of public goods, based on a two-period model with nonlinear taxation. If the public good supply is time-invariant, the presence of habit formation generally alters the...

We follow Fuhrer (2000) in estimating via Maximum Likelihood a log-linear consumption function on UK data. In doing so we consider various habit formation assumptions. We show that a model of purely external habits as in Fuhrer (2000) fits the UK data remarkably well, and possibly in a superior...

In a field experiment with 341 participants, we study whether social comparisons, either in isolation or in combination with a climate-related moral appeal, can change the use of public and car-related transportation. We do so in the context of a mobility budget offered to employees of a large...

The early warning system literature on banking crises has often relied on linear classifiers such as the logit model, which are usually estimated with large datasets of multiple regions of countries. We construct an EWS based on an artificial neural network model with monthly data from the...

Regression discontinuity designs (RDD) are widely used in the social sciences to estimate causal effects from observational data. Scholars can choose from a range of methods that implement different RDD estimators, but there is a paucity of research on the performance of these different...