Weibull inference using trimmed samples and prior information

Trimmed samples are commonly used in several branches of statistical methodology, especially when the presence of contaminated data is suspected. Assuming that certain proportions of the smallest and largest observations from a Weibull sample are unknown or have been eliminated, a Bayesian approach to point and interval estimation of the scale parameter, as well as hypothesis testing and prediction, is presented. In many cases, the use of substantial prior information can significantly increase the quality of the inferences and reduce the amount of testing required. Some Bayes estimators and predictors are derived in closed-forms. Highest posterior density estimators and credibility intervals can be computed using iterative methods. Bayes rules for testing one- and two-sided hypotheses are also provided. An illustrative numerical example is included.     

On unification of the asymptotic theory of nonlinear econometric models

After reading a few articles in the nonlinear econonetric literature one begins to notice that each discussion follows roughly the same lines as the classical treatment of maximum likelihood estimation. There are some technical problems having to do with simultaneously conditioning on the exogenous variables and subjecting the true parameter to a Pittman drift which prevent the use of the classical methods of proof but the basic impression of similarity is correct . An estimator – be it nonlinear least squares, three – stage nonlinear least squares, or whatever – is the solution of an optimization problem. And the objective function of the optimization problem can be treated as if it were the likelihood to derive the Wald test statistic, the likelihood ratio test statistic , and Rao's efficient score statistic. Their asymptotic null and non – null distributions can be found using arguments fairly similar to the classical maximum likelihood arguments. In this article we exploit these observations and unify much of the nonlinear econometric literature. That which escapes this unificationis that which has an objective function which is not twice continuously differentiable with respect to the parameters – minimum absolute deviations regression for example.

The model which generates the data need not bethe same as the model which was presumed to define the optimization problem. Thus, these results can be used to obtain the asymptotic behavior of inference procedures under specification error We think that this will prove to be the nost useful feature of the paper. For example, it i s not necessary toresortto Monte Carlo simulat ionto determine i f a Translog estimate of an elasticity of sub stitution obtained by nonlinear three-stage least squares is robust against a CES truestate of nature. The asymptotic approximations we give here w ill provide an analytic answer to the question, sufficiently accurate for most purposes.     

An echelon inventory-based single-stage cost function for a two-station tandem system

We propose an alternative cost-accounting function for inventory control problems on a make-to-stock setting. Our proposal is based on observing that the traditional holding and backlog parameters introduce some odd short term distortions on the inventory state space. Our single-stage cost function accounts for echelon inventories and possesses a pair of cost parameters for each echelon inventory variable, depending on whether it is positive or negative. With the modified cost-accounting function, we study a twostation tandem system producing a single product, and investigate how it compares with the performances obtained with the usual single-stage cost function. The results available so far show that the optimal policies approach a multi-echelon base stock structure for each machine. Also, the service levels achieved are better under the modified function without increasing the levels of finished goods inventory.     

Factors of regional poverty reduction in Colombia: Do institutional conditions matter?

Colombia has a unique history, which has been heavily conditioned by armed conflict lasting more than 50 years. This study examines the institutional conditions for success and failure in reducing poverty in Colombian departments by considering changes that took place between 2003 and 2014. Fuzzy‐set qualitative comparative analysis identifies the changes in regional conditions that reduce poverty over time. The pathways for poverty reduction are multidimensional, and many involve changes in institutional attributes such as government transparency, absence of violence, and electoral turnout. The framework developed in this paper can be used to monitor necessary and sufficient pathways in regional clusters.     

On the relationship between the reversed hazard rate and elasticity

Despite hazard and reversed hazard rates sharing a number of similar aspects, reversed hazard functions are far less frequently used. Understanding their meaning is not a simple task. The aim of this paper is to expand the usefulness of the reversed hazard function by relating it to other well-known concepts broadly used in economics: (linear or cumulative) rates of increase and elasticity. This will make it possible (i) to improve our understanding of the consequences of using a particular distribution and, in certain cases, (ii) to introduce our hypotheses and knowledge about the random process in a more meaningful and intuitive way, thus providing a means to achieving distributions that would otherwise be hardly imaginable or justifiable.     

Territoriality,map-mindedness,and the politics of place

Theory and Society - Political sociologists have paid closer attention of late to the territoriality of political communities, and have even begun theorizing the theme of territoriality’s...     

Explaining the Mexican‐American Health Paradox Using Selectivity Effects

While typically socioeconomically disadvantaged, Mexican migrants in the United States tend to have better health outcomes than non‐Hispanic whites. This phenomenon is known as the “Hispanic health paradox.” Using data from Mexico and the United States, we examine several health outcomes for non‐Hispanic whites and Mexicans in the United States and in Mexico and employ Blinder–Oaxaca decompositions to help explain the paradox. We find evidence that selectivity is playing a significant role in the relatively healthy status of Mexican migrants in the United States. More importantly, there is evidence that health selectivity is a complex process and its effects typically do not work the same way for different health conditions and across genders. We also find evidence that some of migrants' health advantages are lost as they spend more time in the United States.     

Navigating Americanized Identities: Bicultural Ethnicity,Race, and the Incorporation Experience

This paper reports on the complex ways in which immigrant young adults make sense of their Americanized ethnic and racial identities. The analysis draws on a large set of in-depth interviews (N?=?233) collected with immigrants between the ages of 18 and 29 across three regions in the US (California, New York, and Minnesota) in the early 2000s and is in dialogue with emerging new theories of immigrant incorporation which combine the insights of traditional assimilation and racialization frameworks. The identity narratives that emerge from these interviews demonstrate the overarching significance of racial and ethnic identification for young adults across various immigrant communities. The narratives also highlight some of the contextual factors involved in the construction of an ethnic identity in the US such as experiences with discrimination; or the presence of co-ethnic communities. The final substantive section explores how young American immigrants in the transition to adulthood attempt to cultivate hybrid, bicultural identities that balance their American-ness with the ongoing experience of living in a deeply racialized society. The paper concludes by discussing implications for the literature on identity formation and the transition to adulthood as well as on the immigrant incorporation experience.     

Forecasting interest rates: a comparative assessment of some second-generation nonlinear models

Modeling and forecasting of interest rates has traditionally proceeded in the framework of linear stationary methods such as ARMA and VAR, but only with moderate success. We examine here three methods, which account for several specific features of the real world asset prices such as nonstationarity and nonlinearity. Our three candidate methods are based, respectively, on a combined wavelet artificial neural network (WANN) analysis, a mixed spectrum (MS) analysis and nonlinear ARMA models with Fourier coefficients (FNLARMA). These models are applied to weekly data on interest rates in India and their forecasting performance is evaluated vis-à-vis three GARCH models [GARCH (1,1), GARCH-M (1,1) and EGARCH (1,1)] as well as the random walk model. Both the WANN and MS methods show marked improvement over other benchmark models, and may thus hold out several potentials for real world modeling and forecasting of financial data.     

Properties of systems with two exchangeable Pareto components

The life lengths of the units in a system can be modelled by a bivariate distribution. In this paper, we suppose that the joint distribution of the units is a symmetric bivariate Pareto (Lomax) distribution. For this model, we obtain basic reliability properties for series and parallel systems. J. M. Ruiz Partially Supported by Ministerio de Ciencia y Tecnologia under grant BFM2003-02947 and Fundacion Seneca under grant 00698/PI/04.