Article history: Received 18 September 2003 Received in revised form 20 September 2005 Accepted 3 November 2005 Available online 18 January 2006 The empirical environmental Kuznets curve (EKC) literature is vast but far from conclusive. Many authors have analysed the existence of an EKC for various pollutants. Others have used the EKC framework to identify country characteristics that help to e...

We consider the problem of obtaining D-optimal designs for factorial experiments with a binary response and k qualitative factors each at two levels. We obtain a characterization of locally D-optimal designs. We then develop efficient numerical techniques to search for locally D-optimal designs. Using prior distributions on the parameters, we investigate EW D-optimal designs that maximize the d...

Taste stimuli encountered in the natural environment are usually combinations of multiple tastants. Although a great deal is known about how neurons in the taste system respond to single taste stimuli in isolation, less is known about how the brain deals with such mixture stimuli. Here, we probe the responses of single neurons in primary gustatory cortex (GC) of awake rats to an array of taste ...

A Bayesian semi-parametric estimation of the binary response model using Markov Chain Monte Carlo algorithms is proposed. The performances of the parametric and semi-parametric models are presented. The mean squared errors, receiver operating characteristic curve, and the marginal effect are used as the model selection criteria. Simulated data and Monte Carlo experiments show that unless the bi...

A common problem in models for dichotomous dependent variables is “separation,” which occurs when one or more of a model’s covariates perfectly predicts some binary outcome. Separation raises a particularly difficult set of issues, often forcing researchers to choose between omitting clearly important covariates and undertaking post–hoc data or estimation corrections. In this paper I present a ...

In this paper, we develop a Bayesian analysis of a semi-parametric binary choice model. The prior speciication of the functional parameter , namely the distribution function of a latent variable, is of the Dirichlet process type and the prior speciication of the Euclidean parameter , namely the coeecients of a linear combination of exogenous variables, is left arbitrary. The model identiication...

Using statistical textons for texture classification has shown great success recently. The maximal response 8 (MR8) method, which extracts an 8-dimensional feature set from 38 filters, is one of state-of-the-art rotation invariant texture classification methods. However, this method has two limitations. First, it require a training stage to build a texton library, thus the accuracy depends on t...

We propose a multi-index binary response model for analyzing large databases (i.e., with many regressors). We combine many regressors into factors (or indexes) and then estimate the link function via parametric or nonparametric methods. Neither the estimation of factors nor the determination of the number of factors requires ex ante knowledge of the link between the response and regressors. Fur...

We consider the problem of obtaining locally D-optimal designs for factorial experiments with qualitative factors at two levels each with binary response. Our focus is primarily on the 2 experiment. In this paper, we derive analytic results for some special cases and indicate how to handle the general case. The performance of the uniform design in examined and we show that this design is highly...

We quantify the identifying power of special regressors in heteroskedastic binary regressions with median-independent or conditionally symmetric errors. We measure the identifying power using two criteria: the set of regressor values that help point identify coe¢ cients in latent payo¤s as in (Manski 1988); and the Fisher information of coe¢-cients as in (Chamberlain 1986). We …nd for median-in...