Multidimensional Poverty Measures from an Information Theory Perspective

This paper proposes to use an information theory approach to the design of multidimensional poverty indices. Traditional monetary approaches to poverty rely on the strong assumption that all relevant attributes of well-being are perfectly substitutable. Based on the idea of the essentiality of some attributes, scholars have recently suggested multidimensional poverty indices where the existence of a trade-off between attributes is relevant only for individuals who are below a poverty threshold in all of them (Bourguignon and Chakravarty 2003, Tsui 2002). The present paper proposes a method which encompasses both approaches and, moreover, it opens the door to an intermediate position which allows, to a certain extent, for substitution of attributes even in the case in which one or more (but not all) dimensions are above the set threshold. An application using individual well-being data from Indonesian households in 2000 is presented in order to compare the results under the different approaches.Multidimensional Poverty, Information Theory

Discounting The Equity Premium Puzzle

This paper applies recent tests of stochastic dominance of several orders proposed by Linton, Maasoumi and Whang (2003) to reexamine the equity premium puzzle. An advantage of this nonparametric framework is that it provides a means to assess whether the existence of a premium is due to an incorrect choice of either the utility function or the underlying returns distribution. The approach is applied to a range of data sets including the S&P500Equity premium puzzle, stochastic dominance, nonparametric, subsampling.

Consistent Testing for Stochastic Dominance: A Subsampling Approach

We propose a procedure for estimating the critical values of the Klecan, McFadden, and McFadden (1990) test for first and second order stochastic dominance in the general k-prospect case. Our method is based on subsampling bootstrap. We show that the resulting test is consistent. We allow for correlation amongst the prospects and for the observations to be autocorrelated over time. Importantly, the prospects may be the residuals from certain conditional models.Bootstrap, Prospect theory, Stochastic dominance