Suchergebnisse

Cover; Contents; Acknowledgements; 1 Introduction and Overview; 1.1 What is Experimetrics?; 1.2 Experimental Design; 1.3 The Experimetrics of Theory Testing; 1.4 Dependence in Experimental Data; 1.5 Parametric versus Non-parametric Approaches; 1.6 Structural Experimetrics; 1.7 Modelling Subject Heterogeneity; 1.8 Experimetrics of Other-regarding Preferences; 1.9 Experimetrics of Bounded Rationality; 1.10 Experimetrics of Learning; 1.11 What is in this Book?; 2 Statistical Aspects of Experimental Design in Experimental Economics; 2.1 Introduction; 2.2 The Average Treatment Effect.

AbstractThe hedonic pricing method is used to investigate the way in which the prices of prostitutes' services are determined. The data used in the analysis are extracted from an internet site, each observation being based on a report submitted by a client. The factors affecting price are identified in a regression framework, and combined with other information to provide estimates of the earnings, both aggregate and individual, for a sub‐sector of this underground service industry in the United Kingdom. Comparison of these earnings' estimates with data on earnings from alternative employment then allows us to estimate the compensating wage differential, and also to verify the theoretical prediction that prostitutes' earnings are positively related to earnings from alternative employment.

We analyse the demand for goods which the consumer has an aversion to consuming in mixtures. Examples are presented. It is suggested that the axiom of non‐satiation should be relaxed in order for the model to be internally consistent. The indifference map with mixture aversion and satiation is constructed and is shown to have very unusual properties. It is then demonstrated that constrained maximization of the underlying utility function can result in both goods being consumed. It is also demonstrated that the type of goods analysed here can exhibit the rare characteristic of Giffenity.

"This paper is concerned with estimating preference functionals for choice under risk from the choice behaviour of individuals. We note that there is heterogeneity in behaviour between individuals and within individuals. By 'heterogeneity between individuals' we mean that people are different, in terms of both their preference functionals and their parameters for these functionals. By 'heterogeneity within individuals' we mean that behaviour may be different even by the same individual for the same choice problem. We propose methods of taking into account all forms of heterogeneity, concentrating particularly on using a Mixture Model to capture the heterogeneity of preference functionals." [author's abstract]