How does BREXIT affect production patterns of multinational enterprises?

This paper explores how the British exit from the European Union (EU) potentially affects the United Kingdom (UK) economy and the production patterns of multinational enterprises that choose the UK as either a destination market or a gateway to the EU market. Utilizing an extended version of the knowledge-capital model, which includes six types of firms and four countries grouped into market and non-market, simulation analysis reveals that efforts to enhance attractiveness of the UK as a destination market to increase horizontal-type inward foreign direct investment would be a solution to cover losses from reduction in the number of export-platforms.     

Does the twin deficit hypothesis hold in the OECD countries under different real interest rate regimes?

This paper explores the validity of the twin deficit hypothesis in selected 25 OECD countries with annual data for 2005–2016 by considering different real interest rate regimes. A non-dynamic panel threshold model, introduced by Hansen (1999), is employed. The novelty of the empirical findings from the present study is that there exists a non-linear relationship between the budget deficit and the trade balance, which is driven by a critical threshold level in the real interest rates. The findings suggest that twin deficit hypothesis holds only under the low real interest rate regime, that is, rises in budget deficits lead to deteriorations in the trade balance when the real interest rate is below the threshold level. When the high real interest rate (i.e. above-the-threshold) regime is concerned, increasing budget deficits give rise to improvements in the trade balance, a finding consistent with the twin divergence hypothesis. Thus, the effect on the trade balance of an expansionary fiscal policy that worsens the budget balance reverses substantially depending on the threshold level of the real interest rates. The major policy implication of this paper is that the policy makers in the selected OECD countries should pay a greater attention to fiscal discipline in order to prevent the trade balance from worsening, because the majority of the countries fall into the low real interest rate regime over the recent years of the sample period (i.e. between 2010 and 2016).     

Water cycle algorithm for solving the reliability-redundancy allocation problem with a choice of redundancy strategies

Abstract

This paper proposes a new mathematical model for the reliability-redundancy allocation problem (RRAP) with a choice of redundancy strategies. To maximize the reliability of a system, this model chooses the best redundancy strategy from among both active and standby ones for each subsystem. For those with a standby strategy, a continuous time Markov chain model is used to calculate the exact reliability values. In order to solve the proposed mixed-integer non-linear programing model, a powerful evolutionary algorithm, called water cycle algorithm (WCA), is developed and implemented on three famous benchmark problems. Finally, the results of different benchmark problems are compared with those previously reported to show the superiority of the proposed model and the efficiency of WCA.     

西方残障身份发展理论述评及本土化思考

积极的残障身份认同对残障者本身具有重要意义,残障身份发展是残障者实现身份认同的路径,理解残障身份发展的过程也可以让残疾人工作者更好地为残障者提供教育、康复等相关服务。本文通过梳理较为典型的西方残障身份发展理论,结合国内残障身份相关研究及本土社会文化背景展开讨论。文章认为,在西方残障身份发展理论框架下,残障者形成积极身份认同的关键在于认同并融入一套在残障社区内共享的残障文化,而在我国社会文化背景下,目前并没有一套成体系的残障文化,残障者也难以体会残障的文化身份感,国内残障者的身份认同缺少本土残障文化依靠。     

Asian children’s verbal development: A comparison of the United States and Australia

Using longitudinal cohort studies from Australia and the United States, we assess the pervasiveness of the Asian academic advantage by documenting White-Asian differences in verbal development from early to middle childhood. In the United States, Asian children begin school with higher verbal scores than Whites, but their advantage erodes over time. The initial verbal advantage of Asian American children is partly due to their parent’s socioeconomic advantage and would have been larger had it not been for their mother’s English deficiency. In Australia, Asian children have lower verbal scores than Whites at age 4, but their scores grow a faster rate and converge towards those of Whites by age 8. The initial verbal disadvantage of Asian Australian children is partly due to their mother’s English deficiency and would have been larger had it not been for their Asian parent’s educational advantage. Asian Australian children’s verbal scores grow at a faster pace, in part, because of their parent’s educational advantage.     

The effects of individually varying times of observations on growth parameter estimations in piecewise growth model

When using latent growth modeling (LGM), researchers often restrict the factor loadings, while the multilevel modeling (MLM) treats time as a metric variable. However, when individually varying times of observations are concerned in the longitudinal studies, the use of specified loadings would lead to inaccurate estimation. Based on piecewise growth modeling (PGM), this simulation study showed that (i) individually varying times of observations with larger boundaries got worse estimates and model fits when LGM was used; (ii) estimating the PGM across all the simulation situations was robust within MLM, whereas LGM got identically equal estimation with MLM only in the case of time boundaries of ±1 month or shorter; (iii) larger change of slope in piecewise modeling indicated better estimation.     

Assessing the Performance of a Classification‐Based Vulnerability Analysis Model

In this article, a classification model based on the majority rule sorting (MR‐Sort) method is employed to evaluate the vulnerability of safety‐critical systems with respect to malevolent intentional acts. The model is built on the basis of a (limited‐size) set of data representing (a priori known) vulnerability classification examples. The empirical construction of the classification model introduces a source of uncertainty into the vulnerability analysis process: a quantitative assessment of the performance of the classification model (in terms of accuracy and confidence in the assignments) is thus in order. Three different app oaches are here considered to this aim: (i) a model–retrieval‐based approach, (ii) the bootstrap method, and (iii) the leave‐one‐out cross‐validation technique. The analyses are presented with reference to an exemplificative case study involving the vulnerability assessment of nuclear power plants.     

Towards Uniformly Efficient Trend Estimation Under Weak/Strong Correlation and Non‐stationary Volatility

In this paper, we consider the deterministic trend model where the error process is allowed to be weakly or strongly correlated and subject to non‐stationary volatility. Extant estimators of the trend coefficient are analysed. We find that under heteroskedasticity, the Cochrane–Orcutt‐type estimator (with some initial condition) could be less efficient than Ordinary Least Squares (OLS) when the process is highly persistent, whereas it is asymptotically equivalent to OLS when the process is less persistent. An efficient non‐parametrically weighted Cochrane–Orcutt‐type estimator is then proposed. The efficiency is uniform over weak or strong serial correlation and non‐stationary volatility of unknown form. The feasible estimator relies on non‐parametric estimation of the volatility function, and the asymptotic theory is provided. We use the data‐dependent smoothing bandwidth that can automatically adjust for the strength of non‐stationarity in volatilities. The implementation does not require pretesting persistence of the process or specification of non‐stationary volatility. Finite‐sample evaluation via simulations and an empirical application demonstrates the good performance of proposed estimators.