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Behavioral economics poses a challenge for the welfare evaluation of choices, particularly those that involve risk. It demands that we recognize that the descriptive account of behavior toward those choices might not be the ones we were all taught, and still teach, and that subjective risk perceptions might not accord with expert assessments of probabilities. In addition to these challenges, we are faced with the need to jettison naive notions of revealed preferences, according to which every choice by a subject expresses her objective function, as behavioral evidence forces us to confront pervasive inconsistencies and noise in a typical individual’s choice data. A principled account of errant choice must be built into models used for identification and estimation. These challenges demand close attention to the methodological claims often used to justify policy interventions. They also require, we argue, closer attention by economists to relevant contributions from cognitive science. We propose that a quantitative application of the “intentional stance” of Dennett provides a coherent, attractive and general approach to behavioral welfare economics.

Hungary is situated in east central Europe with an area of 93 thousand square kilometers and a population of 10.2 million. Its Gross Domestic Product (GDP) per capita was 5,669 Euro in 2001 (Statistical Yearbook, 2001). Ninety-seven percent of the country’s population is Hungarian. The ethnic minorities, comprising 3% of the population, are German, Slovak and Romanian. The minority with the highest population, and of a peculiar status, is the Gypsies. Their proportion of the population of Hungary is estimated at 5–6% (Hablicsek, 2000). Gypsies are linguistically divided, with 70% speaking Hungarian as their maternal language. Their recognition as a separate ethnic group is currently a matter of political debate.

The burgeoning interest over the last decade in technology transfer at universities in the United States has driven contentious debates over patent policy. In this context, biotech patenting has become the poster-child for claims that the proliferation of patenting by universities, and in the private sector, is undermining scientific norms and threatening innovation. Commentators have expressed particular fears about the negative effects of biotech patenting on the public information commons and concerns about emerging “patent anticommons.” This chapter argues that the standard (finite) commons model is being misapplied in the biotech arena because, owing to the complexity of biological processes and the power of existing biotech methods to produce genetic data, biomedical science is, in crucial respects, an unbounded, uncongested common resource. These findings imply that strategic biotech patenting of problem-specific research tools (i.e., single-nucleotide polymorphisms, drug targets) is not economically justified and therefore is irrational.