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This chapter explores the relationship between bureaucracy and the ­democratization of the Republic of Korea by analyzing the roles and responsibilities of the Board of Audit and Inspection of Korea (BAI) and how Korea’s unique type of supreme audit institution (SAI) have been involved throughout the democratization process of Korea over the last two decades. Unlike western supreme audit institutions which mainly functioned for financial and performance auditing, Korea’s SAI, BAI bureaucracy, has functioned to reduce corruption, in cooperation with citizen’s participation which gives unique cases for the context of developing countries. The most important finding of this study is that bureaucracy can be an effective vehicle in a country’s political trajectory towards democratization given that the public institutions and agencies have specific traits such as having clear and comprehensive mandates, retaining high ­sensitivity to external needs, and maintaining well-qualified staff with active utilization of Information Technology. The main targets of the analysis are the conditions under which BAI bureaucracy could effectively exert its mandates and successfully fulfill its duties; also the question of how the BAI bureaucracy has facilitated democratization as being the locus of participatory democracy will be addressed.

In the context of Dynamic Factor Models, we compare point and interval estimates of the underlying unobserved factors extracted using small- and big-data procedures. Our paper differs from previous works in the related literature in several ways. First, we focus on factor extraction rather than on prediction of a given variable in the system. Second, the comparisons are carried out by implementing the procedures considered to the same data. Third, we are interested not only on point estimates but also on confidence intervals for the factors. Based on a simulated system and the macroeconomic data set popularized by Stock and Watson (2012), we show that, for a given procedure, factor estimates based on different cross-sectional dimensions are highly correlated. On the other hand, given the cross-sectional dimension, the maximum likelihood Kalman filter and smoother factor estimates are highly correlated with those obtained using hybrid procedures. The PC estimates are somehow less correlated. Finally, the PC intervals based on asymptotic approximations are unrealistically tiny.

This chapter provides a case study on a Sharīʿah-compliant home facility contract based on the Bai Bithaman Ājil (BBA) contract, generally used by Islamic banks in Malaysia. The study emphasises on the need to comply with the existing legal framework and execute relevant contracts in line with the Sharīʿah resolutions of the Sharīʿah Advisory Council of Bank Negara Malaysia without causing harm (ḍarar) to the customers or introducing uncertain elements or procedures (gharar) in the execution of the agreements. This chapter is based on doctrinal analysis of the relevant issues as well as a qualitative legal research through content analysis of relevant BBA agreements, case law as well as statutory provisions. The case study used in this chapter is completely anonymised. The study finds that the execution of BBA agreements in Malaysia leaves much to be desired. Even though the regulatory framework for Sharīʿah-compliant home financing in Malaysia is robust, there are some legal and Sharīʿah considerations which the stakeholders need to look into in order to project Malaysia as the main global hub of Islamic finance. This study demonstrates the need for proper Sharīʿah auditing of the practical execution of BBA agreements to avoid an incorporated element of gharar at the time of execution of the agreements, which might ultimately lead to unforeseen reputation risks for the bank. Though there are several studies on the Sharīʿah, financing and accounting aspects of the BBA home facility agreement, this study focusses on both Sharīʿah and legal issues, using the case study approach. The recommendations are expected to provide a good policy framework for the stakeholders in the Islamic financial services industry in Malaysia.

The Factor-augmented Error-Correction Model (FECM) generalizes the factor-augmented VAR (FAVAR) and the Error-Correction Model (ECM), combining error-correction, cointegration and dynamic factor models. It uses a larger set of variables compared to the ECM and incorporates the long-run information lacking from the FAVAR because of the latter’s specification in differences. In this paper, we review the specification and estimation of the FECM, and illustrate its use for forecasting and structural analysis by means of empirical applications based on Euro Area and US data.

Consistent exposure to sunshine with high ultraviolet values has significant negative effects on human skin. Key risks include melanoma and the rapid onset of signs of ageing. For Chinese, these are viewed as undesirable, because their genetic legacy predisposes them to greater numbers of skin blemishes and because darker shades are culturally and socially viewed as less attractive. Properties in sunshine locations may need to modify aspects of their infrastructure and service delivery to meet the needs of the globally influential Chinese market. Shaded spaces, new activities, scheduling of experiences in the early morning, evening and at night, are all a part of the required innovations in experience design.

Islamic banking contributes significantly to the total assets of Malaysian banking sector. Yet, many argue that Islamic banking in Malaysia does not receive satisfactory support and participation from the public mainly due to poor awareness of its products and services and misconception about the Islamic banking system. It is timely to study consumers’ awareness of Islamic banking in the hopes of providing useful strategies for and assistance with marketing plans. This study is to explore consumer awareness towards Islamic banking products and services across a diverse set of demographic variables.

A quantitative approach was used in this study. A total of 1,000 questionnaires were distributed via convenience and snowballing sampling method to bank customers in a public university in Malaysia, and 817 responses from the survey were used for the analysis. Descriptive and non-parametric statistics were employed to answer objectives of this study.

The findings of this study are anticipated to provide a holistic and comprehensive marketing insight to improve and strengthen Islamic banking in Malaysia.

This study examines the role of demographics such age, gender, race/religion, education level, occupation and income level in trying to understand the issues of Islamic banks’ product awareness. It is well accepted that the consumer’s attitude or behaviour should be studied among others through understanding customers’ demographics.

Forecasts from dynamic factor models potentially benefit from refining the data set by eliminating uninformative series. This paper proposes to use prediction weights as provided by the factor model itself for this purpose. Monte Carlo simulations and an empirical application to short-term forecasts of euro area, German, and French GDP growth from unbalanced monthly data suggest that both prediction weights and least angle regressions result in improved nowcasts. Overall, prediction weights provide yet more robust results.

Hausman (1978) represented a tectonic shift in inference related to the specification of econometric models. The seminal insight that one could compare two models which were both consistent under the null spawned a test which was both simple and powerful. The so-called ‘Hausman test’ has been applied and extended theoretically in a variety of econometric domains. This paper discusses the basic Hausman test and its development within econometric panel data settings since its publication. We focus on the construction of the Hausman test in a variety of panel data settings, and in particular, the recent adaptation of the Hausman test to semiparametric and nonparametric panel data models. We present simulation experiments which show the value of the Hausman test in a nonparametric setting, focusing primarily on the consequences of parametric model misspecification for the Hausman test procedure. A formal application of the Hausman test is also given focusing on testing between fixed and random effects within a panel data model of gasoline demand.

This chapter details the instructional experiences of a group of graduate students, who are emerging Human Systems Intervention practitioners – men and women who self-identify as white and work in organizational, community, and educational leadership settings. I outline a series of learning experiences that supported a group of MA students to uncover white supremacist thinking in their work – their approaches to intervention and their mental models regarding effective organizational or community functioning. Using contemplative practices to dig out oppressive, invisible dimensions of white identity, we examined how our whiteness shaped and warped how we enacted our work in community and organization development. We did this by reflective reading, meditation, contemplative arts, deep listening and storytelling, singing and music, and ceremony. This chapter illustrates how higher education can address a fundamental mental model and world view that influences how social responsibility is envisioned and how issues of social justice can be advanced within graduate professional education through socially responsible teaching and learning strategies and activities.