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.

Evaluating dominance ranking of PSID incomes by various household attributes

We examine the dynamic evolution of incomes, both disposable and gross, for several groups in the PSID panel data at several points from 1968 to 1997. We employ the extended Kolmogorov-Smirnov tests of First and Second Order Stochastic Dominance (SD) as implemented by Maasoumi and Heshmati (2000). They do not impose the Least Favorable Case (LFC) of the composite null hypotheses of SD orders. This is in contrast to simulation and bootstrap-based techniques that do so, resulting in tests that are not asymptotically similar or unbiased. Our approach is also different from the subsampling technique of Linton et al (2005) who obtain critical values for these tests under very general sampling schemes. We offer partial control for many individual/family specific attributes, such as age, gender, education, number of children, work and marital status, by comparing group cells. This avoids having to specify and estimate models of dependence of incomes on these attributes, but lacks the multiple controls that is the promise of such techniques. We find a surprising number of strong rankings, both between groups and over time, in gross income and, to a lesser extent, in 'disposable' incomes

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

Consistent Testing for Stochastic Dominance: A Subsampling Approach

We study a very general setting, and propose a procedure for estimating the critical values of the extended Kolmogorov-Smirnov tests of First and Second Order Stochastic Dominance due to McFadden (1989) in the general k-prospect case. We allow for the observations to be generally serially dependent and, for the first time, we can accommodate general dependence amongst the prospects which are to be ranked. Also, the prospects may be the residuals from certain conditional models, opening the way for conditional ranking. We also propose a test of Prospect Stochastic Dominance. Our method is based on subsampling and we show that the resulting data tests are consistent.Prospect theory, stochastic dominance, stochastic equicontinuity, subsampling.

Consistent testing for stochastic dominance: a subsampling approach

We propose a procedure for estimating the critical values of the extended Kolmogorov- Smirnov tests of First and Second Order Stochastic Dominance in the general K-prospect case. We allow for the observations to be serially dependent and, for the …rst time, we can accommodate general dependence amongst the prospects which are to be ranked. Also, the prospects may be the residuals from certain conditional models, opening the way for conditional ranking. We also propose a test of Prospect Stochastic Dominance. Our method is based on subsampling and we show that the resulting tests are consistent and powerful against some N¡1=2 local alternatives. We also propose some heuristic methods for selecting subsample size and demonstrate in simulations that they perform reasonably.

Parametric and Nonparametric Tests of Limited Domain and Ordered Hypotheses

Abstract. Technical and conceptual advances in testing multivariate linear and non-linear inequality hypotheses in econometrics are summarized. This is done in the context of substantive empirical settings in economics in which either the null, or the alternative, or both hypotheses define more limited domains than the two-sided alternatives typically tested in the classical testing procedures. The desired goal is increased power which is laudable given the endemic power problems of most of the classical asymptotic tests. The impediments are a lack of familiarity with implementation procedures, and characterization problems of distributions under some composite hypotheses. several empirically important cases are identified in which practical "one-sided" tests can be conducted by either the e 2 ? distribution, or the union intersection mechanisms based on the Gaussian variate, or the increasingly feasible and popular resampling/simulation techniques. Point optimal testing and its derivatives find a natural medium here whenever unique characterization of the null distributions for the "least favorable" cases is not possible. Most of the recent econometric literature in this area is parametric deriving from the multivariate extensions of the classical Gaussian means test with ordered alternatives. Tests for variance components, random coefficients, over dispersion, heteroskedasticity, regime change, ARCH effects, curvature regularity conditions on flexible supply, demand, and other economic functions, are examples But nonparametric tests for ordered relations between distributions, or their quantiles, or curvature regularity conditions on nonparametric economic relations, have witnessed rapid development and applications in economics and finance. We detail tests for Stochastic Dominance which indicate a major departure in the practice of empirical decision making in, so far, the areas of welfare and optimal financial strategy

Searching for rehabilitation in nonparametric regression models with exogenous treatment assignment

This paper offers some new directions in the analysis of nonparamertric models with exogenous treatment assignment. The nonparametric approach opens the door to the examination of potentially different distributed outcomes. When combined with cross-validation, it also identifies potentially irrelevant variables and linear versus nonlinear effects. Examination of the distribution of effects requires distribution metrics, such as stochastic dominance tests for ranking based on a wide range of criterion functions, including dollar valuations. We can identify subgroups with different treatment outcomes. We offer an empirical demonstration based on the GAIN data. In the case of one covariate (English as the primary language), there is support for a statistical inference of uniform first order dominant treatment effects. We also find several others that indicate second and higher order dominance rankings to a statistical degree of confidence

A retrospective on J.D. Sargan and his contribution to Econometrics

This retrospective provides a biographical history of Denis Sargan's career and reviews his contributions to econometrics, emphasizing the breadth of his work in both theoretical and applied econometrics. We include a complete bibliography for Denis and a list of PhD theses that he supervised - students were a substantive facet of his profesional life. Finally, two of Denis' previously unpublished manuscripts on model building now appear in print. Keywords; dynamic specification, econometrics, error correction model, finite sample distributions, identification, instrumental variables, model building, numerical computation, prices, production function, specification searches, wages