JSTOR is a not-for-profit service that helps scholars, researchers, and students discover, use, and build upon a wide range of content in a trusted digital archive. We use information technology and tools to increase productivity and facilitate new forms of scholarship. For more information about JSTOR, please contact support@jstor.org. AbstractDuring the late 1 980s and early 1 990s, taxation of wage income has undergone a change towards a proportional tax regime in many countries. Our analysis shows that gradual tax reforms in Norway may have removed some of the distortions on worker behavior. Moreover, we find that proportional taxes may reduce the inequality in the distribution of disposable household income. Yet, when the distributional consequences are related to changes in individual welfare, we find that rich households may benefit far more than households at the other tail of the income distribution, because they earn more without any significant increase in effort.

In this paper we discuss a general framework for analyzing labor supply behavior in the presence of complicated budget-and quantity constraints of which some are unobserved. The point of departure is that an individual's labor supply decision can be considered as a choice from a set of discrete alternatives (jobs). These jobs are characterized by attributes such as hours of work, sector specific wages and other sector specific aspects of the jobs. We focus in particular on theoretical justification of functional form assumptions and properties of the random components of the model. The paper includes an empirical application based on Norwegian data, in which the labor supply of married women is estimated.JEL classification: J22,C51.Key words: Labor supply, non-convex budget sets, non-pecuniary job-attributes, sector-specific wages. ___________________________________ * Statistics Norway, Oslo. E-mail: john.dagsvik@ssb.no ** Department of Economics, University of Oslo. E-mail: steinar.strom@econ.uio.no We are indebted to Tom Wennemo for skillful programming assistance and Rolf Aaberge for constructive critisism throughout the revision process. We thank two anonymous referees and the editor for useful comments and helpful suggestions.We also thank James J. Heckman for valuable comments on an earlier version of the paper and Anne Skoglund for proof reading and word processing. S.Strøm is grateful to ICER, Turin, for providing excellent working conditions. 2

The Generalized Extreme Value Model was developed by McFadden for the case with discrete choice sets. The present paper extends this model to cases with both discrete and continuous choice sets and choice sets that are unobservable relative to the analyst. We also propose behavioral assumptions that justify random utility functions (processes) that have a max stable structure i.e., utility processes where the finite dimensional distributions are of the multivariate extreme value type. Finally we derive non-parametrically testable implications for the choice probabilities in the continuous case.

This paper analyzes the potential demand for alternative fuel vehicles. The alternative fuel vehicles we consider are liquid propane gas and electric powered vehicles in addition to a dual-fuel vehicle. The data were obtained from a stated preference survey in which each respondent, in a randomly selected sample, was exposed to 15 experiments. In each experiment the respondents were asked to rank three hypothetical vehicles characterized by specific attributes, according to the respondents' preferences. Several versions of a random utility model are formulated and estimated. They include a model for rank ordered data, and models that allow for different types of correlation in preferences across experiments. Apart from one case the model specifications are estimated from the data on first choices. The most general model turns out to predict aggregate second and third choices rather well. The model is applied to assess the willingness to pay for alternative fuel vehicles.

Abstract:In this paper we discuss Hicksian demand and compensating variation in the context of discrete choice. We first derive Hicksian choice probabilities and the distribution of the (random) expenditure function in the general case when the utilities are nonlinear in income. We subsequently derive exact and simple formulae for the expenditure and choice probabilities under price (policy) changes conditional on the initial utility level. This is of particular interest for welfare measurement because it enables the researcher to compute the distribution of Compensating variation in a simple way. We also derive formulae for the joint distribution of expenditure, the choice before and after a policy change has been introduced.Keywords: Random expenditure function, Compensated choice probabilities, Compensating variation. Equivalent variation. JEL classification: C25, D61Acknowledgement: We wish to thank Mårten Palme, Thor O. Thoresen and Steinar Strøm for useful discussions and comments that have improved the paper. We are particularly grateful to a referee whose suggestions have improved the exposition of the paper substantially. Thanks to Anne Skoglund for excellent word processing and proof reading.

Abstract:This paper develops aggregate relations for a matching market of heterogeneous suppliers and demanders. The point of departure is the analysis of two-sided matching found in Roth and Sotomayor (1990). Under particular assumptions about the distribution of preferences, the present paper derives asymptotic aggregate relations for the number of realized matches of different types in the presence of flexible contracts (such as a price). Simulation experiments demonstrate that the model also provides excellent predictions in small populations.

Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. Models of labor supply derived from stochastic utility representations and discretized sets of feasible hours of work have gained popularity because they are more practical than the standard approaches based on marginal calculus. In this paper we argue that practicality is not the only feature that can be addressed by means of stochastic choice theory. This theory also offers a powerful framework for developing a more realistic model for labor supply choices, founded on individuals having preferences over jobs and facing restrictions on the choice of jobs and hours of work. We discuss and clarify how this modeling framework deviates from both the conventional discrete approach (Van Soest, 1995), as well as the standard textbook approach based on marginal calculus (Hausman, 1985). It is argued that a model based on job choice opens up for a more realistic representation of the choice environment, and consequently offers the possibility of conducting a richer set of simulations of alternative policies. Terms of use: Documents inJEL-Code: C510, J220, H240.

In this paper we develop a general random utility framework for analyzing data on individuals' rank orderings. Specifically, we show that in the case with 3 alternatives one can express the probability of a particular rank ordering as a simple function of first choice probabilities. This framework is applied to specify and estimate models of household demand for conventional gasoline cars and alternative fuel vehicles in Shanghai based on rank ordered data obtained from a stated preference survey. Subsequently, the framework is extended to allow for random effects in the utility specification to allow for intrapersonal correlation in tastes across stated preference questions. The preferred model is then used to calculate demand probabilities and elasticities and the distribution of willingness-to-pay for alternative fuel vehicles.