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Significant evidence in the literature points to money demand instability and therefore inaccurate forecasting. In view of this issue, this chapter seeks to use a method, innovative for money demand literature, that is, the machine learning model to predict money demand. Specifically, this chapter uses Random Forest Regression to predict money demand using monthly data in the Indian context over the period April-1996 to December-2018 using the variables usually used in literature. The chapter finds that in money demand prediction, the Random Forest Regression performs fairly well. The results are also compared to traditional models and it is found that the Random Forest Regression model has the potential to enhance the prediction of money demand over what traditional models predicts.

This chapter estimates causality properties between real money demand and a number of determinants, that is, real output, the lending rate and the real exchange rate, across 10 Asian economies through linear and nonlinear causality methodologies spanning the period 1990–2012. The results document both bidirectional and unidirectional causality between monetary aggregates (M1 and M2) and their determinants for different country groups. The empirical findings exemplify the role of the demand for money as a policy tool and can provide useful policy recommendations to the Asian monetary authorities in their vision of forming a future monetary union.

What role does government play in determining the medium of exchange? Economists weighing in on the issue have typically espoused one of two views. State theorists credit government with the emergence and continued acceptance of commonly accepted media of exchange. In contrast, spontaneous order theorists find little need for government, maintaining that money emerges and continues to circulate as a result of a decentralized market process. History suggests a more subtle theory is required. We provide a generalized theory of the emergence and perpetuation of money, informed by both approaches and consistent with recent theoretical and empirical advances in the literature.

Purpose: This chapter aims to present the arguments for and against central bank digital currency (CBDC) increasing financial inclusion. Financial inclusion is one of the many reasons for issuing a CBDC.

Need for the study: There is a need to offer a critical perspective on the proposed financial inclusion benefits of CBDC. This is the first paper to present arguments supporting and statement against CBDC for financial inclusion.

Method: This chapter uses discourse analysis methodology to identify the arguments about CBDC promoting financial inclusion

Findings: The arguments in support of CBDC increasing financial inclusion are that CBDCs can digitise value chains, CBDCs can improve access to digital financial services, CBDCs can help to enlarge the digital economy, CBDCs can enhance the efficiency of digital payments, CBDCs can be used offline when there is no internet coverage, and CBDCs have low transaction costs. Some criticisms are that CBDC may not prioritise financial inclusion, a high price to purchase digital devices for holding a CBDC, non-interest-bearing CBDCs, the strong preference for cash over digital currency, the burdensome identification and regulatory requirements, and the imposition of transaction costs.

Implications: Overall, the arguments presented in this chapter show that there is still disagreement over whether a central bank’s digital currency can increase financial inclusion. Nevertheless, in the light of recent events, many central banks are determined to issue a CBDC for many reasons. Even though CBDCs do not achieve the intended financial inclusion objective, at least the other goals for publishing a CBDC will be performed, such as a significant reduction in cash management costs and the effective conduct of monetary policy.

It is widely argued that money laundering (ML) is not a new phenomenon and the pervasiveness of ML is associated with some severe economic, social and political costs. Due to the lack of studies on the ML’s issue in the UAE, this study aims to examine the determinants of ML in the country between 1975 and 2020.

The autoregressive distributed lag bounds testing results demonstrate the presence of long-run relationship between ML and the selected macroeconomics variables. The analysis is validated by the dynamic ordinary least squares, the fully modified ordinary least squares and the canonical co-integration regression estimators.

The estimation result reveals that while the real estate market, outflow of money, arms procurement and size of the underground economy influences the size of ML positively, gold trade, the level of financial development and the size of economic activities are negatively associated with ML, both in the short- and long-run.

Up to date from a country-level analysis, no study has been devoted to the ML in UAE, except for Aljassmi et al. (2023). To the best of the authors’ knowledge, this study is the first to investigate the determinants of laundered money in the UAE economy. Based on these outcomes, strategies and measures which will deter the laundering of illicit funds through the real estate and gold market, remittance system, financial system and arms procurement contracts in the UAE are recommended.

Despite the vulnerability of rapidly developing and emerging market economies, researchers have paid less attention to the determination of the size of money laundering (ML) in these economies, including the United Arab Emirates (the UAE). Therefore, this paper aims to estimate the magnitude of ML in the UAE between 1975 and 2020 based on the currency demand approach (CDA).

The study uses the Gregory–Hansen cointegration technique alongside the autoregressive distributed lag bounds testing procedure to estimate the CDA model.

The results illustrate that an amount equivalent to about 19.034% of the GDP is laundered in the UAE between 1975 and 2020, on average, with the value lying between 15.129% and 23.121%. In addition, the results demonstrate the importance of the real estate market, gold trade, remittance channels and the size of the underground economy in facilitating the laundering of illicit funds in the country.

To the best of the authors’ knowledge, the study is the pioneering attempt at estimating the amount of illicit funds laundered in the UAE. Besides, the adoption of a novel, yet robust, approach based on the modification of the CDA technique also sets the study apart as it ensures a correct, clear, unambiguous and indisputable estimate of the magnitude of ML is obtained. In addition, it is expected that the outcome of the study will expand the frontiers of knowledge among policy makers and relevant agencies and ensure the adoption of the most efficient and effective measures to curb the ML menace in the country.

This paper empirically investigates the effect of economic policy uncertainty (EPU) on the UK money demand stability during the inter-war period (1920–1938). Both a narrow definition (M0) and a broad definition (M3) of money are investigated.

The empirical investigation is conducted by employing the autoregressive distributed lag (ARDL) bounds testing approach to cointegration.

Results presented indicate a stable demand for both definitions of money only when EPU is included as one of the determinants of demand function. The EPU imposes a negative effect on the demand for both definitions of money. The causality test results further indicate long- and short-term causality from the determinants (including EPU) to both forms of money demand.

Significant presence of the economic uncertainty weakens the effects of the monetary policy on the economy.

This is a historical economics paper. Given the turmoil and uncertainty associated with the inter-war period, an empirical investigation of UK money demand is an interesting exercise. This is the first such paper.

The purpose of the study is to identify the perceived lack of certain core knowledge, skills and attributes in external quality auditors (EQAs) that contributes to an audit process that does not add value for client organizations. This paper describes the development of a competency requirement framework for quality management system (QMS) EQAs that would improve their capability and audit performance.

A review of relevant international literature on auditor competence and education, clients' expectations on external auditors, explicit and implicit expectations based on ISO 9001:2015 and ISO 19011:2018, and current auditor capability was conducted to obtain insights into the present situation and requirements of the environment. A survey questionnaire was then utilized in the collection of data from 19 heads of certification and technical reviewers of accredited certification bodies (CBs) in Malaysia. Univariate and bivariate analysis were used in analyzing the data from respondents.

The overall results show that the most important components of knowledge for EQAs to possess are quality management principles, system and standards; risk management; and business process and operations management. In terms of skills, the most important skills for auditors are auditing and report writing and critical/analytical thinking, followed by communication/interpersonal/people/ICT and team management. Attributes such as integrity, being ethical, professional and objective are found to be most important in EQAs to be effective and add value to the audits. Based on the results, the competency requirement framework of EQAs was developed.

This paper presents the knowledge, skills, attitudes and experience needed by EQAs identified by the CBs which is then developed into a competency requirements framework for future auditor training. The resulting framework from the study can be used by accreditation bodies, CBs and training organizations to evaluate and improve the auditors' competence and audit performance in the future.

This paper seeks to adopt FRBRoo as an ontological approach to integrate heterogeneous metadata, and transform human-understandable format into machine-understandable format for semantic query.

Two cases of use with museum artefacts and literary works were exploited to illustrate how FRBRoo can be used to re-contextualize the semantics of elements and the semantic relationships embedded in those elements. The shared ontology was then RDFized and examples were explored to examine the feasibility of the proposed approach.

FRBRoo can play a role as inter lingua aligning museum and library metadata to achieve heterogeneous metadata integration and semantic query without changing either of the original approaches to fit the other.

Exploration of more diverse use cases is required to further align the different approaches of museums and libraries using FRBRoo and make revisions.

Solid evidence is provided for the use of FRBRoo in heterogeneous metadata integration and semantic query.

This is the first study to elaborate how FRBRoo can play a role as a shared ontology to integrate the heterogeneous metadata generated by museums and libraries. This paper also shows how the proposed approach is distinct from the Dublin Core format crosswalk in re-contextualizing semantic meanings and their relationships, and further provides four new sub-types for mapping description language.

Money laundering is an activity where illegal proceeds are hidden. This often leads to a reduction in government revenue and loss of government control of public funds. This study aims to identify the important sources of growing demand for money laundering in developing countries. Further, it identifies the factors that reduce the impact of sources of demand for money laundering.

This study used the panel approach of feasible generalized least square to investigate the growing demand for money laundering in 62 developing countries and provides a moderation-based solution for managing the demand factors.

The empirical results of this study indicate that there are two sources that increase the demand for money laundering in developing countries. This includes a high tax rate on profit linked with private firms and businesses and diversion of public funds related to government officials and politicians. The results indicate that profit tax and diversion of funds increase the demand for money laundering. The profit tax-based money laundering can be moderated by the quality of the education system and the diversion of public funds and money laundering can be moderated using bureaucracy quality.

This is one of the first studies to empirically estimate the impact of two important sources (i.e. diversion of public funds by government officials and politicians and a high tax rate) that create demand for money laundering in developing countries. The findings help developing countries’ governments formulate policies and curb the growing demand for money laundering.