Innovation, the diesel engine and vehicle markets: Evidence from OECD engine patents

This paper uses a patent data set to identify factors fostering innovation of diesel engines between 1974 and 2010 in the OECD region. The propensity of engine producers to innovate grew by 1.9 standard deviations after the expansion of the car market, by 0.7 standard deviations following a shift in the EU fuel economy standard, and by 0.23 standard deviations. The propensity to develop emissions control techniques was positively influenced by pollution control laws introduced in Japan, in the US, and in the EU, but not with the expansion of the car market. Furthermore, a decline in loan rates stimulated the propensity to develop emissions control techniques, which were simultaneously crowded out by increases in publicly-funded transport research and development. Innovation activities in engine efficiency are explained by market size, loan rates and by (Organisation for Economic Cooperation and Development) diesel prices, inclusive of taxes. Price effects on innovation, outweigh that of the US corporate average fuel economy standards. Innovation is also positively influenced by past transport research and development. © 2014 Elsevier Ltd.

Paradoxical evidence integration in rapid decision processes

Decisions about noisy stimuli require evidence integration over time. Traditionally, evidence integration and decision making are described as a one-stage process: a decision is made when evidence for the presence of a stimulus crosses a threshold. Here, we show that one-stage models cannot explain psychophysical experiments on feature fusion, where two visual stimuli are presented in rapid succession. Paradoxically, the second stimulus biases decisions more strongly than the first one, contrary to predictions of one-stage models and intuition. We present a two-stage model where sensory information is integrated and buffered before it is fed into a drift diffusion process. The model is tested in a series of psychophysical experiments and explains both accuracy and reaction time distributions. © 2012 Rüter et al.