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The purpose of this study is to extend the classical noncentral F-distribution under normal settings to noncentral closed skew F-distribution for dealing with independent samples from multivariate skew normal (SN) distributions.

Based on generalized Hotelling's T² statistics, confidence regions are constructed for the difference between location parameters in two independent multivariate SN distributions. Simulation studies show that the confidence regions based on the closed SN model outperform the classical multivariate normal model if the vectors of skewness parameters are not zero. A real data analysis is given for illustrating the effectiveness of our proposed methods.

This study’s approach is the first one in literature for the inferences in difference of location parameters under multivariate SN settings. Real data analysis shows the preference of this new approach than the classical method.

For the real data applications, the authors need to remove outliers first before applying this approach.

This study’s approach may apply many multivariate skewed data using SN fittings instead of classical normal fittings.

This paper is the research paper and the authors’ new approach has many applications for analyzing the multivariate skewed data.

Since equity markets have a dynamic nature, the purpose of this paper is to investigate the performance of a revision procedure for domestic and international portfolios, and provides an empirical selection strategy for optimal diversification from an American investor's point of view. This paper considers the impact of estimation errors on the optimization processes in financial portfolios.

This paper introduces the concept of portfolio resampling using Monte Carlo method. Statistical inferences methodology is applied to construct the sample acceptance regions and confidence regions for the resampled portfolios needing revision. Tracking error variance minimization (TEVM) problem is used to define the tracking error efficient frontiers (TEEF) referring to Roll (1992). This paper employs a computation method of the periodical after revision return performance level of the dynamic diversification strategies considering the transaction cost.

The main finding is that the global portfolio diversification benefits exist for the domestic investors, in both the mean-variance and tracking error analysis. Through TEEF, the dynamic analysis indicates that domestic dynamic diversification outperforms international major and emerging diversification strategies. Portfolio revision appears to be of no systematic benefit. Depending on the revision of the weights of the assets in the portfolio and the transaction costs, the revision policy can negatively affect the performance of an investment strategy. Considering the transaction costs of portfolios revision, the results of the return performance computation suggest the dominance of the global and the international emerging markets diversification over all other strategies. Finally, an assessment between the return and the cost of the portfolios revision strategy is necessary.

The innovation of this paper is to introduce a new concept of the dynamic portfolio management by considering the transaction costs. This paper investigates the performance of a revision procedure for domestic and international portfolios and provides an empirical selection strategy for optimal diversification. The originality of the idea consists on the application of a new statistical inferences methodology to define portfolios needing revision and the use of the TEVM algorithm to define the tracking error dynamic efficient frontiers.

In this chapter we demonstrate the construction of inverse test confidence intervals for the turning-points in estimated nonlinear relationships by the use of the marginal or first derivative function. First, we outline the inverse test confidence interval approach. Then we examine the relationship between the traditional confidence intervals based on the Wald test for the turning-points for a cubic, a quartic, and fractional polynomials estimated via regression analysis and the inverse test intervals. We show that the confidence interval plots of the marginal function can be used to estimate confidence intervals for the turning-points that are equivalent to the inverse test. We also provide a method for the interpretation of the confidence intervals for the second derivative function to draw inferences for the characteristics of the turning-point.

This method is applied to the examination of the turning-points found when estimating a quartic and a fractional polynomial from data used for the estimation of an Environmental Kuznets Curve. The Stata do files used to generate these examples are listed in Appendix A along with the data.

The purpose of this paper is to study the factors that caused The Association of Southeast Asian Nations (ASEAN) security regime to be ineffective in saving transnational drug smuggling, including the internalization of non-optimal values and norms of the ASEAN Drug-Free Declaration.

This study uses primary data and secondary data. Data analysis and observation are carried out simultaneously, where data are analyzed directly after it is obtained using descriptive analysis. Interactive data analysis is carried out at the initial step by collecting primary and secondary data. Data are analyzed inductively by drawing conclusions from data obtained from general views to specifics.

The development of ASEAN has led to the idea of “ASEAN Way,” namely, the ASEAN security forum to eliminate the use of force in maintaining relations between member countries through the dissemination of agreed values. Multilateral negotiations refer to the establishment of a negotiation regime at the ASEAN level that emphasizes the interests of ASEAN member countries in determining agreements relating to transnational drug crimes. There are several inhibiting factors in the negotiation process, namely, perception differences between ASEAN countries on the threat of drug smuggling in the Southeast Asia region and the differences of ASEAN leaders’ priorities and agenda.

The originality/authenticity of research is analyzing the factors that affect the ASEAN security system in transnational protection policies by using two models, namely, the international level negotiation model and one at the national level in the form of ratification of ASEAN international relations related to drug smuggling. At present, transnational crimes, especially drug smuggling, appear and pose a threat to national and international security. The object of this research is ASEAN international organizations in cases of transnational drug smuggling.

This paper aims to investigate the impact of exchange rate depreciation and money growth to the consumer price index (CPI) inflation in Indonesia.

Using threshold model applied to Phillips curve equation.

Using monthly data from 1980:1 to 2008:12, the econometric evidence shows that there are indeed threshold effects of money growth on inflation, but no threshold effect of exchange rate depreciation on inflation. Even though the threshold value for exchange rate depreciation is found at 8.4 percent, the F-test suggests that there is no significant difference between the coefficient below and that above the threshold value. While two threshold values are found for money growth, i.e. 7.1 and 9.8 percent, and they are statistically different. The impact on inflation is high when money grows by up to 7.1 percent, it is moderate when money grows by 7.1-9.8 percent, and it is low when money grows by above 9.8 percent.

This research is using methodology proposed by Hansen which the threshold is based on the minimum SSR. The value of SSR will differ from one model to one model. For example, model using quarterly data will give the different result from that using monthly or yearly data. Also, when the author uses the new data, the result could be different.

Even though inflation targeting framework has been adopted by Bank Indonesia (BI) since 2005, BI should not disregard the monetary aggregate variable, especially M1. This is because the growth of money is still matter to influence inflation in the short run. The impact on inflation is found to be larger than the impact of exchange rate depreciation when it is below a certain threshold value.

This is the first paper that evaluates the threshold effect of exchange rate and money growth in emerging country, especially in Indonesia.

This article contributes to a better theoretical and empiric understanding of mixed results in the literature investigating the relationship between institutional confidence and adherence to recommended measures during a pandemic.

The article relies on structural equation models (SEMs) based on data from ResPOnsE COVID-19, a rolling cross-section (RCS) survey carried out in Italy from April to June 2020.

The authors’ findings show the existence of multiple pathways of confidence at the national and local level. Confidence in the institutions is positively associated with support for the performance of the Prime Minister and that of the regional institutions in the North West, which in turn, raises the likelihood of following the restrictive measures. However, in the same regions, a good appraisal of the regional system's performance also had a direct positive effect on the perception of being safe from the virus, decreasing adherence to the restrictive measures. Finally, the direct effect of confidence in the institutions on compliance is negative.

The result enlightens the crucial role both of national and local institutions in promoting or inhibiting adherence to restrictive measures during a pandemic and suggests that “one size fits all” measures for increasing overall institutional confidence might not be sufficient to reach the desired goal of achieving compliance in pandemic times.

The authors theorize and test three cognitive mechanisms – (1) the “cascade of confidence”; (2) the “paradox of support” and (3) the “paradox of confidence” – to account for both the positive and negative links between measures of political support and public acceptability of COVID-19 containment measures.

The aim of this investigation is to examine the level of adoption of e‐government at the regional level in Europe in terms of eight different categories addressing both services provided, internal capacity in terms of training and policies, and perceived barriers to e‐government.

A survey approach was employed to achieve the overall aim of the study, based on existing survey instruments and informed by the requirements of policy makers. A survey of 1,021 municipalities across seven European regions was conducted in order to ascertain the development of e‐government.

The findings suggest that despite e‐government being heavily promoted throughout the Europe, there is relatively little commonality across regions evident to date. The study identifies a number of areas for improvement within the eight categories investigated.

The desired minimum confidence level and confidence interval was not realised across all regions. It would be appropriate to conduct further investigations which include larger (non‐UK) administrative bodies in order that progress made by comparable organizations may be evaluated. Although the study includes results from municipalities in seven regions, it would be desirable to expand the scope of the investigation.

The primary value of this paper lies in the size of the sample derived at regional rather than national level, the resulting data extending our understanding of the adoption of information and communication technologies within municipalities at regional level in Europe.

The purpose of this paper is to analyze the moderating role of self-confidence and risk acceptance on the relationship between perceived risk and intention to use internet banking.

A survey was conducted with 180 Brazilian banking customers. The Johnson-Neyman test was used to verify the moderation and significant regions along self-confidence and risk acceptance levels.

Self-confidence and risk acceptance moderate the relationship between risk perception and intention to use internet banking. For individuals with high self-confidence, the effect of perceived risk on intention to use internet banking is lower than it is for individuals with low self-confidence. In the same way, for individuals with high risk acceptance, the effect of perceived risk on intention to use internet banking is lower than it is for individuals with low risk acceptance.

This research contributes to the understanding of the conditions (two personal factors) under which risk perception does not influence intention to use a technological tool.

This paper provides insights for marketing managers to encourage customers to develop greater risk acceptance and self-confidence to minimize the negative effects of perceived risk of the adoption of internet banking.

Although risk perception can contribute to customers’ avoidance of internet banking, this is the first paper to verify how acceptance of risk and self-confidence can moderate the effects of perceived risk on intention to use internet banking.

This paper aims to propose a robust and efficient method for vanishing point detection in unstructured road scenes.

The proposed method includes two main stages: drivable region estimation and vanishing point detection. In drivable region estimation stage, the road image is segmented into a set of patches; then the drivable region is estimated by the patch-wise manifold ranking. In vanishing point detection stage, the LSD method is used to extract the straight lines; then a series of principles are proposed to remove the noise lines. Finally, the vanishing point is detected by a novel voting strategy.

The proposed method is validated on various unstructured road images collected from the real world. It is more robust and more efficient than the state-of-the-art method and the other three recent methods. Experimental results demonstrate that the detected vanishing point is practical for vision-sensor-based navigation in complex unstructured road scenes.

This paper proposes a patch-wise manifold ranking method to estimate the drivable region that contains most of the informative clues for vanishing point detection. Based on the removal of the noise lines through a series of principles, a novel voting strategy is proposed to detect the vanishing point.

This chapter discusses the empirical application of a class of strategic network formation models, using the approach to identification introduced by de Paula, Richards-Shubik, and Tamer (2018). The author emphasizes the interplay between model specification and computational complexity, and suggests tactics to make empirically realistic models become tractable. Two detailed examples, on friendship networks and coauthorship networks, are used to illustrate these issues and to demonstrate the performance of the approach with both simulation and empirical evidence. Also, the author presents extensions to the estimation method, which expand the potential range of applications, and which provide statistical inference with minimal computational burden.