Asymptotic power of tests of normality under local alternatives

Seven tests of univariate normality are studied in view of their asymptotic power under local alternatives. The procedures under consideration are either based on the empirical skewness and/or kurtosis, including the popular Jarque-Bera statistic, as well as Cramér-von Mises, Anderson-Darling and Kolmogorov-Smirnov functionals of an empirical process with estimated parameters. The large-sample behavior of these test statistics under contiguous sequences is obtained; this allows for the computation of their associated local power curves and of their asymptotic relative efficiency in the light of a measure proposed by Berg and Quessy (2009). Comparisons are made under four classes of local alternatives, including those used by Thadewald and Büning (2007) in a recent Monte-Carlo power study. These theoretical results are related to empirical ones and many recommendations are formulated.     

Estimation for change point of discretely observed ergodic diffusion processes

We treat the change point problem in ergodic diffusion processes from discrete observations. Tonaki et al. (2021a) proposed adaptive tests for detecting changes in the diffusion and drift parameters in ergodic diffusion process models. When any change in the diffusion or drift parameter is detected by this or any other method, the next question to consider is where the change point is located. Therefore, we propose the method to estimate the change point of the parameter for two cases: the case where there is a change in the diffusion parameter, and the case where there is no change in the diffusion parameter but a change in the drift parameter. Furthermore, we present rates of convergence and distributional results of the change point estimators. Some examples and simulation results are also given.     

Estimation of Semiparametric Models when the Criterion Function Is Not Smooth

We provide easy to verify sufficient conditions for the consistency and asymptotic normality of a class of semiparametric optimization estimators where the criterion function does not obey standard smoothness conditions and simultaneously depends on some nonparametric estimators that can themselves depend on the parameters to be estimated. Our results extend existing theories such as those of Pakes and Pollard (1989), Andrews (1994a), and Newey (1994). We also show that bootstrap provides asymptotically correct confidence regions for the finite dimensional parameters. We apply our results to two examples: a ‘hit rate’ and a partially linear median regression with some endogenous regressors.     

Consistent Testing of Cointegrating Relationships

In this paper we investigate methods for testing the existence of a cointegration relationship among the components of a nonstationary fractionally integrated (NFI) vector time series. Our framework generalizes previous studies restricted to unit root integrated processes and permits simultaneous analysis of spurious and cointegrated NFI vectors. We propose a modified F‐statistic, based on a particular studentization, which converges weakly under both hypotheses, despite the fact that OLS estimates are only consistent under cointegration. This statistic leads to a Wald‐type test of cointegration when combined with a narrow band GLS‐type estimate. Our semiparametric methodology allows consistent testing of the spurious regression hypothesis against the alternative of fractional cointegration without prior knowledge on the memory of the original series, their short run properties, the cointegrating vector, or the degree of cointegration. This semiparametric aspect of the modelization does not lead to an asymptotic loss of power, permitting the Wald statistic to diverge faster under the alternative of cointegration than when testing for a hypothesized cointegration vector. In our simulations we show that the method has comparable power to customary procedures under the unit root cointegration setup, and maintains good properties in a general framework where other methods may fail. We illustrate our method testing the cointegration hypothesis of nominal GNP and simple‐sum (M1, M2, M3) monetary aggregates.     

Dialogue and creativity: The generative dialogical perspective in therapy

The generative perspective in therapy understands relations and dialogue as a generative social space where participants can promote innovative resources and possibilities for themselves, and their relations and circumstances, along with new social ecologies. It focuses on the creative dimensions of human relationality. This epistemological and clinical perspective has a heuristic value that allows us to discern and work with micro dialogues—micro processes of creative, generative dialogues—in the ongoing dialogue, mindful of the opportunities for creativity and innovation they provide. The generative perspective promotes creative processes and transformations to help clients build possible and viable futures when faced with problems, conflicts and challenges. It involves the dialogical and relational co-creation of resources and possibilities, and actions for implementation. The perspective is illustrated with a therapy process involving a 3-year follow-up. The paper includes a section where differences and similarities between dialogical perspectives are presented.     

Multivariate geometric anisotropic Cox processes

This paper introduces a new modeling and inference framework for multivariate and anisotropic point processes. Building on recent innovations in multivariate spatial statistics, we propose a new family of multivariate anisotropic random fields, and from them a family of anisotropic point processes. We give conditions that make the proposed models valid. We also propose a Palm likelihood-based inference method for this type of point process, circumventing issues of likelihood tractability. Finally we illustrate the utility of the proposed modeling framework by analyzing spatial ecological observations of plants and trees in the Barro Colorado Island data.     

The complementary effects of rationality and intuition on strategic decision quality

Rationality and intuition are important dimensions of the strategic decision process. Prior studies have viewed these as distinct dimensions, providing limited insights for our understanding of strategic decision processes. Drawing on the dual process theory and research on process capability, this study examines the interplay between rationality and intuition based on a sample of 103 strategic decisions made by service firms in Greece. The results suggest that combining rationality and intuition at the same time leads to successful strategic decisions. Also, the moderating role of environmental dynamism was investigated. We found that in dynamic settings, decision-making teams which combine rationality and intuition outperform teams which use rationality or intuition separately. The implications of these findings for theory and practice are important and are analysed in the paper.     

Individual differences and dyadic processes in conversations with peers in middle childhood

The goal of the current study was to investigate the contribution of both trait-like individual differences and dyadic processes to the content of children's conversations. Fifty-two groups typically consisting of four same-sex unfamiliar nine-year-old children (N = 202) interacted in all possible dyads, resulting in six dyads per group. Each dyad completed a 5-min frustration task and a 5-min planning task. Observers coded children's verbalizations into 10 categories and further summed these categories into prosocial (suggest, agree, solicit input, ask, encourage, state personal) and antisocial (command, disagree, discourage, aggress) verbalizations, resulting in 24 variables (12 per task). Across both tasks, Social Relations Model analyses provided evidence of the role of both individual differences [significant effects for actor variance (15 of 24 variables), actor-actor correlations, and intrapersonal correlations] and dyadic processes [significant effects for partner variance (4 of 24 variables), relationship variance (18 of 24 variables), dyadic reciprocity correlations (10 of 24 variables), and interpersonal correlations] in children's conversations with peers.     

中国股市投资者短期价格趋势推断行为的实验研究

提出基于启发式思维的中国股市投资者短期价格趋势推断行为假设,并通过实验研究对所提假设进行检验。研究发现,面对连涨或连跌短期股价序列信息,随着连涨或连跌时间的延长,中国股市投资者买入或卖出该股票的意愿均呈现先上升后下降的弱-强-弱的趋势变化,且上涨(下跌)过程中的买入(卖出)意愿大于卖出(买入)意愿,追涨杀跌特征明显。