The transition of a sector from a pollutant state to a clean one is studied. A green technology, subject to learning-by-doing, progressively replaces an old one. The notion of abatement cost in this dynamic context is fully characterized. The theoretical, dynamic optimization, perspective is...

We provide evidence for a beneficial welfare impact of a crime policy that is targeted at strengthening victim precaution. Regulation made application of the electronic engine immobilizer, a simple and low-cost anti-theft device, mandatory for all new cars sold within the European Union as of...

Using data from the U.S. automobile market, we empirically examine the link between competition and innovation. Consistent with a large literature, we use patent counts as a measure of innovation. The combination of the U.S. market's economic importance, market dynamics, and the significant...

Using three years of data from the 47 prefectures of Japan, we estimate behavior of households who simultaneously make discrete decisions about vehicle ownership and continuous decisions about driving distance. We use the estimated parameters to calculate elasticities and to simulate the effects...

We develop a behavioral macroeconomic model in which agents use simple but biased rules to forecast future output and inflation. This model generates endogenous waves of optimism and pessimism (“Animal Spirits”) that are generated by the correlation of biased beliefs. We contrast the...

We use a unique hand collected data set of 6 258 auctions from the online football manager game Hattrick to study micro-patterns of reserve price formation. We find that chosen reserve prices exhibit both, very sophisticated and “irrational” behavior by the sellers. Reserve prices pick up...

I distinguish two types of macroeconomic models. The first type are top-down models in which some or all agents are capable of understanding the whole picture and use this superior information to determine their optimal plans. The second type are bottom-up models in which all agents experience...