Trend,Growth Rate,and Change Point Analysis—A Data Driven Approach

A data-driven technique is proposed to estimate the trend and relative growth rate of time series data. The method is based on the local linear regression smoother and the only assumption about the form of the trend and growth rate function is that they are smooth functions of time. We also extended the method for handling sudden shifts or changes in the trend or growth rate functions by adding dummy variables for the jumps. Simulation studies are carried out to see the performance of the proposed procedure. The method is applied to study the trend and growth rate of wheat production in India from 1951–2005.     

On Confidence Intervals for Process Capability Indices in a One-Way Random Model

In this article, we investigated the bootstrap calibrated generalized confidence limits for process capability indices C _pk for the one-way random effect model. Also, we derived Bissell's approximation formula for the lower confidence limit using Satterthwaite's method and calculated its coverage probabilities and expected values. Then we compared it with standard bootstrap (SB) method and generalized confidence interval method. The simulation results indicate that the confidence limit obtained offers satisfactory coverage probabilities. The proposed method is illustrated with the help of simulation studies and data sets.     

Bayesian bivariate survival analysis using the power variance function copula

Copula models have become increasingly popular for modelling the dependence structure in multivariate survival data. The two-parameter Archimedean family of Power Variance Function (PVF) copulas includes the Clayton, Positive Stable (Gumbel) and Inverse Gaussian copulas as special or limiting cases, thus offers a unified approach to fitting these important copulas. Two-stage frequentist procedures for estimating the marginal distributions and the PVF copula have been suggested by Andersen (Lifetime Data Anal 11:333–350, 2005), Massonnet et al. (J Stat Plann Inference 139(11):3865–3877, 2009) and Prenen et al. (J R Stat Soc Ser B 79(2):483–505, 2017) which first estimate the marginal distributions and conditional on these in a second step to estimate the PVF copula parameters. Here we explore an one-stage Bayesian approach that simultaneously estimates the marginal and the PVF copula parameters. For the marginal distributions, we consider both parametric as well as semiparametric models. We propose a new method to simulate uniform pairs with PVF dependence structure based on conditional sampling for copulas and on numerical approximation to solve a target equation. In a simulation study, small sample properties of the Bayesian estimators are explored. We illustrate the usefulness of the methodology using data on times to appendectomy for adult twins in the Australian NH&MRC Twin registry. Parameters of the marginal distributions and the PVF copula are simultaneously estimated in a parametric as well as a semiparametric approach where the marginal distributions are modelled using Weibull and piecewise exponential distributions, respectively.     

The effect of teaching strategies on student achievement: An analysis using TALIS-PISA-link

The present study investigates the effects of different teaching strategies on student achievement using data from the so-called TALIS-PISA link created by the OECD. This is a recently developed instrument that allows for connecting data about teacher characteristics and practices collected in the TALIS (Teaching and Learning International Survey) survey with students’ academic performance measured in PISA (Programme for International Student Assessment). Our empirical strategy is based on an instrumental variable (IV) approach. Our results suggest that traditional teaching methods have a positive influence on students’ proficiency in mathematics, while the implementation of more innovative active learning strategies seem to have a negative impact on student achievement.     

Rethinking social work ethics: what is the real question? Responding to Stephen Webb's ‘Against difference and diversity in social work’

Jose J. Rethinking social work ethics: what is the real question? Responding to Stephen Webb's ‘Against difference and diversity in social work’ Int J Soc Welfare 2010: 19: 246–252 © 2009 The Author(s), Journal compilation © 2009 Blackwell Publishing Ltd and the International Journal of Social Welfare. In his recent article, Stephen Webb argued that the real question for social work ethics concerns ‘recognising the Same and of restoring the principles of equality and social justice’. This argument also included raising questions about what should be considered an appropriate philosophical basis for progressive social work ethics. In his view, social work's emancipatory potential has been blunted by overstated and philosophically ill‐informed human rights claims about difference and diversity. He suggested that French philosopher Alain Badiou offers social workers a ‘set of conceptual devices for rethinking social work ethics’. I argue that pressing his points into Badiou's philosophical mould is unlikely to lead to a progressive social work practice, let alone solve the issues identified by Webb. Badiou's philosophical pronouncements about ethics are of questionable value and offer little or no assistance to social workers seeking to establish an ethical grounding for their professional practice.     

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.     

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 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.     

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.