Landmark estimation of transition probabilities in non-Markov multi-state models with covariates

Lifetime Data Analysis - In non-Markov multi-state models, the traditional Aalen–Johansen (AJ) estimator for state transition probabilities is generally not valid. An alternative, suggested...     

Estimates of the likelihood of extreme returns in international stock markets

This study applies extreme-value theory to daily international stock-market returns to determine (1) whether or not returns follow a heavy-tailed stable distribution, (2) the likelihood of an extreme return, such as a 20% drop in a single day, and (3) whether or not the likelihood of an extreme event has changed since October 1987. Empirical results reject a heavy-tailed stable distribution for returns. Instead, a Student-t distribution or an autoregressive conditional heteroscedastic process is better able to capture the salient features of returns. We find that the likelihood of a large single-day return diff ers widely across markets and, for the G-7 countries, the 1987 stock-market drop appears to be largely an isolated event. A drop of this magnitude, however, is not rare in the case of Hong Kong. Finally, there is only limited evidence that the chance of a large single-day decline is more likely since the October 1987 market drop; however, exceptions include stock markets in Germany, The Netherlands and the UK.     

Characterizing optimality among three-decision procedures for directional conclusions

Jones and Tukey (2000) proposed three-decision procedures for directional conclusions in statistical inference, considered as an alternative to the conventional usage of one- and two-tailed significance testing. Moreover, implicit in their suggestions was to consider a procedure to be optimal in case indefinite results were minimized among all procedures with a given control of error. First, we argue by example that this characterization of optimality is not very fruitful when formalized into the strong sense of uniform minimization. Next, imposing a further regularity condition on the comparative class of procedures, we relate the suggested characterization to optimality criteria from test theory (UMP unbiasedness). Similarly, we also consider characterizing optimality in terms of maximizing correct decision rates and minimizing incorrect decision rates. Finally, we demonstrate the applicability of the three considered characterizations with respect to exponential families of distributions.     

Ecological inference in the social sciences

Ecological inference is a problem of partial identification, and therefore precise conclusions are rarely possible without the collection of individual level (identifying) data. Without such data, sensitivity analyses provide the only recourse. In this paper we review and critique recent approaches to ecological inference in the social sciences, and describe in detail hierarchical models, which allow both sensitivity analysis and the incorporation of individual level data into an ecological analysis. A crucial element of a sensitivity analysis in such models is prior specification, and we detail how this may be carried out. Furthermore, we demonstrate how the inclusion of a small amount of individual level data from a small number of ecological areas can dramatically improve the properties of such estimates.     

Alleviating linear ecological bias and optimal design with subsample data

Summary.  We illustrate that combining ecological data with subsample data in situations in which a linear model is appropriate provides two main benefits. First, by including the individual level subsample data, the biases that are associated with linear ecological inference can be eliminated. Second, available ecological data can be used to design optimal subsampling schemes that maximize information about parameters. We present an application of this methodology to the classic problem of estimating the effect of a college degree on wages, showing that small, optimally chosen subsamples can be combined with ecological data to generate precise estimates relative to a simple random subsample.     

Implementing human resource development best practices: Replication or re-creation?

Abstract

Firms increasingly introduce HRD ‘best practices’ developed somewhere else, but results often fall short of expectations. Much of existing theory fails to guide the implementation of HRD best practices because it does not recognize how introduced practices interact with existing practices in the firm. In this paper, we contrast the dominant perspective ‘Implementation as Replication’ with a perspective of ‘Implementation as Re-creation’. Through four stages of the implementation process, we identify and discuss how these contrasting perspectives yield different implications for how firms go about introducing HRD best practices. First, when firms take up a practice, is this a process of adoption or translation? Second, is it assumed that new knowledge can be implanted directly and lead to new behaviour, or is active experimentation a necessary precondition to gain new knowledge? Third, are deviations from the intended plan considered errors to be corrected or sources for learning? Fourth, are introduced best practices treated in isolation or as integral parts of the firm's management system? We argue that implementation efforts guided by the re-creation perspective increase the prospects of HRD best practices succeeding as a useful tool in the receiving firm.     

Subjective Measures of Employment Opportunities and Interregional Migration

Abstract. Empirical studies of interregional mobility routinely use regional unemployment differentials to characterize economic incentives to move between regions. In this paper, we present a new regional labour market indicator computed from survey data in which respondents are asked to evaluate local employment opportunities in their resident municipality and surroundings. The subjective measures of satisfaction with local employment opportunities have positive and significant impact on interregional migration flows, also when controlling for traditional measures of regional labour market conditions, including the regional unemployment rate. Contrary to most European studies, we find that regional labour market conditions have a strong effect on interregional migration flows.     

Impact of Number of Interactions,Different Interaction Patterns,and Human Inconsistencies on Some Hybrid Evolutionary Multiobjective Optimization Algorithms*

We investigate the impact of the number of human–computer interactions, different interaction patterns, and human inconsistencies in decision maker responses on the convergence of an interactive, evolutionary multiobjective algorithm recently developed by the authors. In our context “an interaction” means choosing the best and worst solutions among a sample of six solutions. By interaction patterns we refer to whether preference questioning is more front‐, center‐, rear‐, or edge‐loaded. As test problems we use two‐ to four‐objective knapsack problems, multicriteria scheduling problems, and multiobjective facility location problems. In the tests, two different preference functions are used to represent actual decision maker preferences, linear and Chebyshev. The results indicate that it is possible to obtain solutions that are very good or even nearly optimal with a reasonable number of interactions. The results also indicate that the algorithm is robust to minor inconsistencies in decision maker responses. There is also surprising robustness toward different patterns of interaction with the decision maker. The results are of interest to the evolutionary multiobjective (EMO) community actively developing hybrid interactive EMO approaches.