Implementation of recursive nonparametric kernel estimation and a monte carlo study on its finite sample properties

The recursive estimator for the conditional mean of a nonparametric regression model with independent observations was thoroughly explored by Ahmad and Lin (1976), and Singh and Ullah (1986). Their studies are mainly concerned with the estimator's asymptotic behaviour. However, they do not include much discussion on the strategy of computing the estimates. In this paper, we provide a convenient implementation of the recursive estimator and examine its finite sample properties through simulation studies. Our study has demonstrated that for relatively short length of recursive updating, the estimates are generally equivalent to their fixed window width counterparts However, we found that substantial recursive updating can seriously lower the estimator's efficiency even though it is a consistent estimator.     

Regression analysis with partially labelled regressors: carbon dating of the Shroud of Turin

The twelve results from the 1988 radio carbon dating of the Shroud of Turin show surprising heterogeneity. We try to explain this lack of homogeneity by regression on spatial coordinates. However, although the locations of the samples sent to the three laboratories involved are known, the locations of the 12 subsamples within these samples are not. We consider all 387,072 plausible spatial allocations and analyse the resulting distributions of statistics. Plots of robust regression residuals from the forward search indicate that some sets of allocations are implausible. We establish the existence of a trend in the results and suggest how better experimental design would have enabled stronger conclusions to have been drawn from this multi-centre experiment.     

Stability of Approximations of Average Run Length of Risk-Adjusted CUSUM Schemes Using the Markov Approach: Comparing Two Methods of Calculating Transition Probabilities

Risk-adjusted CUSUM schemes are designed to monitor the number of adverse outcomes following a medical procedure. An approximation of the average run length (ARL), which is the usual performance measure for a risk-adjusted CUSUM, may be found using its Markov property. We compare two methods of computing transition probability matrices where the risk model classifies patient populations into discrete, finite levels of risk. For the first method, a process of scaling and rounding off concentrates probability in the center of the Markov states, which are non overlapping sub-intervals of the CUSUM decision interval, and, for the second, a smoothing process spreads probability uniformly across the Markov states. Examples of risk-adjusted CUSUM schemes are used to show, if rounding is used to calculate transition probabilities, the values of ARLs estimated using the Markov property vary erratically as the number of Markov states vary and, on occasion, fail to converge for mesh sizes up to 3,000. On the other hand, if smoothing is used, the approximate ARL values remain stable as the number of Markov states vary. The smoothing technique gave good estimates of the ARL where there were less than 1,000 Markov states.     

The globalization of production,national labour regulations and income inequality in the global North and South, 1980–2013

A central concern over global value chains (GVCs) is whether the integration of national firms into GVCs exacerbates income inequality within countries. However, despite decades of research, the distributional consequences of GVCs remain unclear in the empirical literature. Drawing on panel data from 96 countries between 1980 and 2013, we examine the effects of GVC integration on market income inequality and whether national labour regulations moderate these effects. We find integration increases inequality in the global North and South. More importantly, we find labour regulations amplify the inequality effects of integration in Southern countries by expanding the size of the informal sector while suppressing these effects in Northern countries by promoting unionization. This suggests institutional power from national labour regulations may enhance the bargaining power of labour in the North through increasing collective resources while disempowering labour in the South through reinforcing labour market segmentation between formal and informal sectors.     

PORTFOLIO MODELING IN MULTIPLE-CRITERIA SITUATIONS UNDER UNCERTAINTY

There have been many models for portfolio selection, but most do not explicitly include uncertainty and multiple objectives. This paper presents an approach that includes these aspects using a form of stochastic integer programming with recourse. The method involves the use of a time-based decision tree structure called a “project tree.” Using this basic format, an illustrative six-project example is presented and analyzed. Various forms of objectives are discussed, ranging from the maximization of expected portfolio value to the maximization of the minimum weighted portfolio deviation from two goals. In each case, formulated numerical problems are given, and the solutions derived are presented. The approach is shown to be very flexible and capable of handling a variety of situations and objectives.     

On the Repeated Test-Retest Reliability of the End-User Computing Satisfaction Instrument: A Comment*

This comment extends the test-retest reliability of the end-user computing satisfaction (EUCS) instrument by Torkzadeh and Doll [10]. Whereas Torkzadeh and Doll [10] reportedstability for two hour and two week EUCS test-retest reliability, we investigate the test-retest reliability of the EUCS instrument at two points in time, separated by a two yearinterval. We assess the end user computing satisfaction of personal computer, as well as mainframe, administrative end users in a large public organization. The results of the repeated test-retest using differing application platforms add further support for the reliability of the EUCS measure and highlight some areas of concern for managers of information systems.