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This study examines the importance of exchange rate and credit growth fluctuations when designing monetary policy in Thailand. To this end, the authors construct a small open economy New Keynesian dynamic stochastic general equilibrium (DSGE) model. The model encompasses several essential characteristics, including incomplete financial markets, incomplete exchange rate pass-through, deviations from the law of one price and a banking sector. The authors consider generalized Taylor rules, in which policymakers adjust policy rates in response to output, inflation, credit growth and exchange rate fluctuations. The marginal likelihoods are then employed to investigate whether the central bank responds to fluctuations in the exchange rate and credit growth.

This study constructs a small open economy DSGE model and then estimates the model using Bayesian methods.

The authors demonstrate that the monetary authority does target exchange rates, whereas there is no evidence in favor of incorporating credit growth into the policy rules. These findings survive various robustness checks. Furthermore, the authors demonstrate that domestic shocks contribute significantly to domestic business cycles. Although the terms of trade shock plays a minor role in business cycles, it explains the most significant proportion of exchange rate fluctuations, followed by the country risk premium shock.

This study is the first attempt at exploring the relevance of exchange rate and credit growth fluctuations when designing monetary policy in Thailand.

Marketplace lending has substantially changed since the first peer-to-peer lending platforms emerged in 2006. The industry is now an alternative to bank lending, predicted to total $70 billion for consumer and business loans worldwide by 2030. Marketplace lending is often deemed less safe than bank loans, mainly due to these portfolios' high degree of hidden information. These include needing more information on borrowers and potential correlations between them, which might lead to higher risk than is apparent at first glance. Deterministic processes cannot capture tail risk appropriately, so platforms and lenders should employ stochastic processes. This chapter introduces a Monte Carlo simulation and machine learning (ML) process to evaluate and monitor portfolios. For marketplace lending to become a viable and sustainable alternative to bank lending platforms, they must better evaluate, monitor, and manage tail risk in marketplace loans and develop tools to monitor and manage financial risk losses.

Traditionally vision-focused, tourism effectively ignores the other senses. With tourists travelling to “see” places, an understanding of how people with vision impairment or blindness (PwVIB) experience tourism is currently lacking. Borrowing from psychology, this viewpoint proposes innovative research approaches to address this knowledge gap, clarifying how PwVIB psychologically experience tourism, enabling tourism professionals to design meaningful and appropriate tourism products and services for this market.

Reviewing extant literature on the tourist experience of PwVIB, this study highlights the existing knowledge gaps regarding understanding how PwVIB experience tourism, proposing alternative theoretical approaches and methodologies for use in future studies.

Alternative research approaches, borrowed from psychology, are proposed to address this knowledge gap and clarify our understanding of how PwVIB experience tourism, serving as a call to action for researchers to attack this issue in innovative ways. An example study, using a mental imagery approach is discussed by way of illustration of how such techniques could be applied.

Highlighting a gap in the understanding of tourist experiences of PwVIB, this viewpoint proposes the adoption of innovative research methods from psychology as a means of delving into the cognitive and conceptual processes involved, offering a new perspective on how to address this important and topical issue and contribute to the design of inclusive and meaningful tourism experiences for this demographic.

This study examines why low-wealth women entrepreneurs forgo mobile enabled money services and government supported micro finance for informal, community-based revolving loans in rural Nigeria.

Thematic analysis of 25 interviews with women in rural, south-west Nigeria. Entrepreneurial ecosystem theory, in the gendered context of micro finance and community-based lending, is employed.

This study explains the paradox of forgoing seemingly accessible mobile enabled credit, and formal credit schemes (e.g. micro-finance programs) for informal, one-on-one borrowing. Convenience and trust-based relationships with respected community members ease the burden of time scarcity and vulnerability associated with formal capital. Flexible terms, autonomy, self-reliance and knowing who one is dealing with make Esusu a preferred source of finance. Findings are discussed in the context of gendered entrepreneurial ecosystems in which participants conduct business.

The sample is not representative of women entrepreneurs in rural Nigeria. Survivorship bias is acknowledged. Further research is needed on the psychological risks of informal capital and the benefits of community-based lending.

Measures to scale mobile enabled credit, without commensurate interventions to address time management and other structural issues that confront women traders, limit their utility and impacts. Power differentials between women traders and lenders must also be considered in the design of lending products. Training of women traders and formal lenders should incorporate curricula about gender gaps in capital markets and systematic gender challenges to support entrepreneurs who seek to grow beyond subsistence enterprises.

This study documents decision criteria that motivate informal rural women traders to employ community-based revolving credit or Esusu. Findings inform measures to increase women entrepreneurs' access to capital in a rural sub-Saharan Africa contexts.

As many businesses faced economic disruption due to the Covid-19 pandemic and sought financial relief, existing bank relationships became critical to getting a loan. This study examines factors associated with the development of personal relationships of rural small businesses with community bank representatives.

We applied a mixed-method approach. We employed descriptive statistics, principal factor analysis and logistic regression for data analysis. We distributed an online survey to rural small businesses in five states in the United States. Key informant interviews with community bank representatives supplemented the survey results.

A business owner’s trust in a banker was positively associated with the establishment of a business–bank relationship. However, an analysis of individual trust’s components revealed that the nature of trust is complex, and a failure of one or more components may lead to decreased trustworthiness in a banker. Small businesses that preferred personal communication with a bank were more inclined to relationship banking.

Due to the relatively small sample size and cross-sectional data, our results may not be conclusive but should be viewed as preliminary and as suggestions for future research. Bankers should be aware of the importance of trust for small business owners and of the actions that lead to increased trustworthiness.

The study extends the existing knowledge on the business–bank relationship by focusing mainly on social (instead of economic) factors associated with the establishment of the business–bank relationship in times of crisis and high uncertainty.

This chapter first examines how the confluence of the three forces discussed in the previous chapter is affecting demand and supply dynamics and giving rise to new business models that could form the core of the emerging digital financial landscape. This chapter then examines the challenges that arise from these new business models as well as from digitalization of financial services in general. The next chapter will review how these challenges might affect monetary and financial stability and the strategy that central banks might use to address them.

Hedonic shopping is a growing phenomenon designed to enhance gamers’ virtual content shopping experience with increasing economic significance, yet limited attention has been dedicated to this area. Our study explores key hedonic motivations of virtual content shopping and how hedonic shopping value builds trust (trust in virtual content and trust in virtual retailers) that enhances the intention to pay for premium.

This research adopts a mixed-methods approach. Study 1 is qualitative; 19 semi-structured interviews were conducted with virtual game retail platform users. Study 2, based on the literature review and qualitative inquiry findings (obtained from Study 1), proposes a research model empirically validated by analyzing survey data administered to 437 online gamers from gaming zones, cybercafés and e-sports centers.

The results show that in-game shopping-related adventure-, gratification-, role- and idea-seeking motivations significantly influence gamers' perceived hedonic shopping value. In turn, perceived shopping value has a significant indirect effect through trust on gamers’ intention to pay for premium.

This research contributes to gaming literature by offering a comprehensive model that elucidates the role of hedonic shopping in increasing gamers’ trust, which explains purchase behavior in the virtual game retail context. The findings deepen the understanding of the game retailing landscape and offer strategies to build gamers’ trust, increase premium usage and retain existing spenders.

This paper examines the impact of Central Bank Digital Currencies (CBDCs), regulated stablecoins and tokenized traditional assets on the cryptocurrency market, following the guidelines set by the Basel Committee. This study aims to analyze the implications for secure storage, cross-border transfers and necessary investments.

The paper uses a policy analysis approach to assess the potential effects of the Basel Committee’s regulations on CBDCs, regulated stablecoins and tokenized traditional assets. It explores their impact on the cryptoasset market, strategies of central and commercial banks, payment systems and risk management.

The adoption of CBDCs, regulated stablecoins and tokenized traditional assets is expected to grow rapidly in the coming years. It raises concerns about secure storage, cross-border transfers and required investments. Central banks are likely to introduce CBDCs and authorize stablecoin issuance, aiming for efficient monetary policies and risk management. Basel III regulations may lead to asset tokenization by banks, reducing asset size and increasing fee-based income.

This paper provides insights into the potential impact of the Basel Committee's regulations on CBDCs, regulated stablecoins and tokenized traditional assets. It contributes to the understanding of the evolving cryptoasset market and the strategies of central and commercial banks in adopting these technologies. The findings offer valuable information for policymakers, regulators and market participants in navigating the changing landscape of digital assets.

This paper seeks to explore the sensitivity of these parameters and their impact on fiscal policy outcomes. We use the existing literature to establish possible ranges for each parameter, and we examine how changes within these ranges can alter the outcomes of fiscal policy. In this way, we aim to highlight the importance of these parameters in the formulation and evaluation of fiscal policy.

The role of fiscal policy, its effects and multipliers continues to be a subject of intense debate in macroeconomics. Despite adopting a New Keynesian approach within a macroeconomic model, the reactions of macroeconomic variables to fiscal shocks can vary across different contexts and theoretical frameworks. This paper aims to investigate these diverse reactions by conducting a sensitivity analysis of parameters. Specifically, the study examines how key variables respond to fiscal shocks under different parameter settings. By analyzing the behavioral dynamics of these variables, this research contributes to the ongoing discussion on fiscal policy. The findings offer valuable insights to enrich the understanding of the complex relationship between fiscal shocks and macroeconomic outcomes, thus facilitating informed policy debates.

This paper aims to investigate key elements of New Keynesian Dynamic Stochastic General Equilibrium (DSGE) models. The focus is on the calibration of parameters and their impact on macroeconomic variables, such as output and inflation. The study also examines how different parameter settings affect the response of monetary policy to fiscal measures. In conclusion, this study has relied on theoretical exploration and a comprehensive review of existing literature. The parameters and their relationships have been analyzed within a robust theoretical framework, offering valuable insights for further research on how these factors influence model forecasts and inform policy recommendations derived from New Keynesian DSGE models. Moving forward, it is recommended that future work includes empirical analyses to test the reliability and effectiveness of parameter calibrations in real-world conditions. This will contribute to enhancing the accuracy and relevance of DSGE models for economic policy decision-making.

This study is motivated by the aim to provide a deeper understanding of the roles macroeconomic model parameters play concerning responses to expansionary fiscal policies and the subsequent reactions of monetary authorities. Comprehensive reviews that encompass this breadth of relationships within a single text are rare in the literature, making this work a valuable contribution to stimulating discussions on macroeconomic policies.