The National Bank of Australasia was a bank based in Melbourne. It was established in 1858, and in 1982 merged with the Commercial Banking Company of Sydney to form National Australia Bank..
We provide empirical evidence to support the calibration of a limit on household indebtedness levels, in the form of a cap on the debt-service-to-income (DSTI) ratio, in order to reduce the probability of borrower defaults in Romania. The analysis establishes two findings that are new to the literature. First, we show that the relationship between DSTI and probability of default is non-linear, with probability of default responding to increases in DSTI only after a certain threshold. Second, we establish that consumer loan defaults occur at lower levels of DSTI compared to mortgages. Our results support the recent regulation adopted by the National Bank of Romania, limiting the household DSTI at origination to 40 percent for new mortgages and consumer loans. Our counterfactual analysis indicates that had the limit been in place for all the loans in our sample, the probability of default (PD) would have been lower by 23 percent.
To keep up with the continuously growing coverage demands and attain true global coverage, the deployment of multi-layered low Earth orbit satellite constellations is necessary. Next-generation mega satellite constellations are expected to rely on inter-satellite links to relay information, which will enable fast and reliable communications between the different satellite nodes in free-space and facilitate the utilization of coverage diversity modes that can further enhance the quality-of-service provided in the network. However, materializing these high performing systems is challenging due to the complexity of the network architecture which may require long and complex simulation processes during design. In this article, we develop theoretical modeling for the probability of coverage for various diversity modes in mega satellite constellations by leveraging tools from stochastic geometry. We first develop analytical models for conventional single-shell networks and then extend these models to incorporate multi-shell networks. The analysis is validated using Monte-Carlo simulations which show a close fit to the analytical models derived. Moreover, the analytical models provide a performance baseline that is comparable to practical networks that rely on regular network architectures such as SpaceX’s Starlink. This allows network operators to devise expansion strategies to cater for expanding demands and gain insights into the performance of the network as more shells are introduced into the network.
This study investigates how institutional quality (IQ) affects corporate cash holdings (CHs) in Vietnam – an emerging market where institutional frameworks are evolving and increasingly gaining policy attention. It further examines economic uncertainty as a mediating channel in this relationship. This study utilizes a panel dataset comprising 15,461 firm-year observations from 1,558 publicly listed firms in Vietnam over the period 2008–2022. We employ the fixed effects (FE) regression models to estimate the impact of IQ on corporate CHs. The analysis is further extended to explore the role of economic uncertainty in this relationship. The results indicate that higher IQ significantly reduces corporate CHs, primarily by lowering firms’ precautionary demand for cash. In addition, the study finds an inverse relationship between IQ and economic uncertainty, alongside a positive relationship between economic uncertainty and corporate CHs. These findings suggest that part of the effect of IQ on CHs operates through its ability to reduce economic uncertainty, thereby diminishing the need for precautionary cash reserves. This study highlights the influence of IQ on one of the most critical corporate decisions – CH – in the context of an emerging economy undergoing active institutional reform. By doing so, it underscores the pivotal role of IQ not only in shaping firms’ financial behavior but also in promoting economic stability, enhancing resource allocation efficiency and supporting the development of a more robust financial system.
Purpose: The objective of this study is to examine the key determinants influencing the adoption of mobile apps among SMEs in Bangladesh, with a particular focus on the role of digital financial literacy. Methods: The research gathered data using a structured questionnaire and probability-stratified random sampling methods. A total of 302 data were collected and analyzed with PLS-SEM. Two urban cities, Chattogram and Cumilla, along with their semi-urban areas, have been selected as the study areas. Results: The study found that relative advantages, competitive pressure, and organizational readiness are significantly correlated with behavioral intentions to adopt mobile payment systems. Nonetheless, compatibility and perceived security do not substantially influence the adoption of mobile apps in SMEs. Simultaneously, digital financial literacy moderates the interaction among competitive pressure, compatibility, and the adoption of mobile apps by SMEs in Bangladesh. Originality: This study contributes to the field by extending the TOE framework with digital financial literacy as a moderating factor, providing new theoretical and practical insights into how TOE dimensions influence the adoption of mobile payment systems by SMEs in Bangladesh.
The United Nations’ Sustainable Development Goals (SDGs) are one of the most widely accepted frameworks worldwide to design policy interventions and implement them in an endeavour to create a sustainable future. A decade from 2015 has ensured a maturity of understanding in terms of localizing the globally agreed indicators to the grassroots level. However, achieving a given sustainability target is highly context-specific, and member states need to design custom structures and policies to achieve specific targets in their regions. This is called the problem of SDG localization . The dearth of relevant frameworks for representing and reasoning about sustainability and policy interventions has resulted in SDG localization efforts being pursued in silos and in an ad hoc manner. In this work, we address the problem of designing a representation framework for policy interventions towards achieving sustainability targets. We call this activity “ Intervention Science ” and develop three essential structures: Differential Impact Modeling that studies predicted change in SDG indicator, Collateral Impact Modeling to understand the side-effects of policy interventions, and Stability Profile Modeling to assess the sustainability of the interventions. We take up specific examples from SDG 2-Zero Hunger to showcase how policy instruments can be designed for specific SDG indicators.
