Estimation of semiparametric locally stationary diffusion models

This paper proposes a class of locally stationary diffusion processes. The model has a time varying but locally linear drift and a volatility coefficient that is allowed to vary over time and space. The model is semiparametric because we allow these functions to be unknown and the innovation process is parametrically specified, indeed completely known. We propose estimators of all the unknown quantities based on long span data. Our estimation method makes use of the property of local stationarity. We establish asymptotic theory for the proposed estimators as the time span increases, so we do not rely on infill asymptotics. We apply this method to interest rate data to illustrate the validity of our model. Finally, we present a simulation study to provide the finite-sample performance of the proposed estimators.     

The gatekeeper,pair-dependency and structural centrality

This is a note to introduce a new measure of a kind of structural centrality called pair-dependency. Pair-dependency explicates the centrality-related notion of the gatekeeper. Moreover, it turns out to be a fundamental structural property of communication networks that provides the basis for the derivation of two standard measures of structural centrality.     

A model of wine tourist behaviour: a festival approach

The study constructs a temporal model of wine tourist behaviour on the basis of the social psychologist' theory of consumer attitudes and related concepts with regard to past behaviour, satisfaction, perceived value and behavioural intentions. More importantly, this study added two dimensions to this model by proposing that satisfaction and perceived value had an impact on the attendees' intentions (i) to visit a local winery and (ii) to buy local wine products. Using a path analysis approach and data collected from the attendees at a regional wine festival, the study examined the above relationships. The results of this path analysis can be summarised as: (i) past behaviour influenced the intention to revisit and the level of perceived value, but had no effect on the level of satisfaction; (ii) perceived value strongly affected the level of satisfaction; (iii) satisfaction had a strong impact on future intentions to revisit and also an effect on intentions to visit local wineries and to buy local wine products; and (iv) perceived value affected the intentions to revisit the festival and to visit local wineries but did not influence the intentions to buy local wines. It is believed that the results of the present study will be useful to organisers of wine festivals and/or wine tourism developers. Copyright © 2008 John Wiley & Sons, Ltd.     

Public Sector Organizational Failure: A Study of Collective Denial in the UK National Health Service

Journal of Business Ethics - This paper argues that public sector organizational failure may be best understood from a perspective of collective denial. The rise of this phenomenon is examined...     

An improved bootstrap test of stochastic dominance

We propose a new method of testing stochastic dominance that improves on existing tests based on the standard bootstrap or subsampling. The method admits prospects involving infinite as well as finite dimensional unknown parameters, so that the variables are allowed to be residuals from nonparametric and semiparametric models. The proposed bootstrap tests have asymptotic sizes that are less than or equal to the nominal level uniformly over probabilities in the null hypothesis under regularity conditions. This paper also characterizes the set of probabilities so that the asymptotic size is exactly equal to the nominal level uniformly. As our simulation results show, these characteristics of our tests lead to an improved power property in general. The improvement stems from the design of the bootstrap test whose limiting behavior mimics the discontinuity of the original test’s limiting distribution.     

Consistent estimation of a general nonparametric regression function in time series

We propose an estimator of the conditional distribution of X_t|X_t−1,X_t−2,…, and the corresponding regression function , where the conditioning set is of infinite order. We establish consistency of our estimator under stationarity and ergodicity conditions plus a mild smoothness condition.     

Nonparametric estimation and inference about the overlap of two distributions

This paper develops methodology for nonparametric estimation of a measure of the overlap of two distributions based on kernel estimation techniques. This quantity has been proposed as a measure of economic polarization between two groups, Anderson (2004) and Anderson et al. (2010). In ecology it has been used to measure the overlap of species. We give the asymptotic distribution theory of our estimator, which in some cases of practical relevance is nonstandard due to a boundary value problem. We also propose a method for conducting inference based on estimation of unknown quantities in the limiting distribution and show that our method yields consistent inference in all cases we consider. We investigate the finite sample properties of our methods by simulation methods. We give an application to the study of polarization within China in recent years using household survey data from two provinces taken in 1987 and 2001. We find a big increase in polarization between 1987 and 2001 according to monetary outcomes but less change in terms of living space.