Search results
1 – 8 of 8Ayuba Napari, Rasim Ozcan and Asad Ul Islam Khan
For close to two decades, the West African Monetary Zone (WAMZ) has been preparing to launch a second monetary union within the ECOWAS region. This study aims to determine the…
Abstract
Purpose
For close to two decades, the West African Monetary Zone (WAMZ) has been preparing to launch a second monetary union within the ECOWAS region. This study aims to determine the impact such a unionised monetary regime will have on financial stability as represented by the nonperforming loan ratios of Ghana in a counterfactual framework.
Design/methodology/approach
This study models nonperforming loan ratios as dependent on the monetary policy rate and the business cycle. The study then used historical data to estimate the parameters of the nonperforming loan ratio response function using an Autoregressive Distributed Lag (ARDL) approach. The estimated parameters are further used to estimate the impact of several counterfactual unionised monetary policy rates on the nonperforming loan ratios and its volatility of Ghana. As robustness check, the Least Absolute Shrinkage Selection Operator (LASSO) regression is also used to estimate the nonperforming loan ratios response function and to predict nonperforming loans under the counterfactual unionised monetary policy rates.
Findings
The results of the counterfactual study reveals that the apparent cost of monetary unification is much less than supposed with a monetary union likely to dampen volatility in non-performing loans in Ghana. As such, the WAMZ members should increase the pace towards monetary unification.
Originality/value
The paper contributes to the existing literature by explicitly modelling nonperforming loan ratios as dependent on monetary policy and the business cycle. The study also settles the debate on the financial stability cost of a monetary union due to the nonalignment of business cycles and economic structures.
Details
Keywords
Mugabil Isayev and Omar Farooq
This paper aims to document the impact of shadow banking on non-performing loans (NPLs) of publicly listed banks in an international setting.
Abstract
Purpose
This paper aims to document the impact of shadow banking on non-performing loans (NPLs) of publicly listed banks in an international setting.
Design/methodology/approach
This paper uses the data from 27 countries and various estimation strategies to test the arguments presented in this paper. The sample covers the period between 2002 and 2020.
Findings
The empirical results suggest that banks headquartered in countries with high shadow banking activity have fewer NPLs than otherwise similar banks headquartered in countries with low shadow banking activity. The findings remain qualitatively the same in different sub-samples and after replacing the main variables with their alternate proxies. The paper also shows that this relationship is sensitive to bank-specific characteristics. Moreover, the paper also indicates that the stringency of banking regulations weakens the relationship between shadow banking and NPLs.
Research limitations/implications
The study’s data limitations prevent a detailed year-by-year analysis of NPLs and shadow banking, restricting insights into their evolving dynamics. In addition, the focus on country-level shadow banking data limits the exploration of how multinational banks’ activities in various jurisdictions impact individual banks’ NPLs.
Originality/value
The paper not only documents the effect of shadow banking on NPLs but also shows that the relationship between shadow banking and NPLs weakens as banking regulations become more stringent.
Details
Keywords
Annisa Adha Minaryanti, Tettet Fitrijanti, Citra Sukmadilaga and Muhammad Iman Sastra Mihajat
The purpose of this paper is to engage in a systematic examination of previous scholarship on the relationship between Sharia governance (SG), which is represented by the Sharia…
Abstract
Purpose
The purpose of this paper is to engage in a systematic examination of previous scholarship on the relationship between Sharia governance (SG), which is represented by the Sharia Supervisory Board (SSB), and the Internal Sharia Review (ISR), to determine whether the ISR can minimize financing risk in Islamic banking.
Design/methodology/approach
The literature search consisted of two steps: a randomized and systematic literature review. The methodology adopted in this article is a systematic literature review.
Findings
To reduce the risk of financing in Islamic banking, SG must be implemented optimally by making rules regarding the role of the SSB in supervising customer financing. In addition, it is a necessary to establish an entity that assists the SSB in the implementation of SG, namely, the ISR section, but there is still very little research on the role of the SSB and ISR in minimizing financing risk.
Practical implications
Establishing an ISR to assist the SSB in carrying out its duties has direct practical implications for Islamic banking: minimizing financing risks and compliance with Islamic Sharia principles. In addition, new rules regarding the role of SSBs and the ISR in reducing credit risk include monitoring customers to ensure that they fulfill their financing commitments on time. This new form of regulation and review can be used as a reference by the Otoritas Jasa Keuangan or Finance Service Authority to create new policies or regulations regarding SG, especially in Indonesia.
Originality/value
Subsequent research may introduce other more relevant variables, such as empirically testing the competence, independence or integrity of SSB and the ISR team as it attempts to minimize the risk of financing in Islamic banks. In addition, further research is expected to examine whether the SSB or the ISR team has a positive or negative influence on the risk of financing Islamic banks with secondary data.
Details
Keywords
Emmanouil G. Chalampalakis, Ioannis Dokas and Eleftherios Spyromitros
This study focuses on the banking systems evaluation in Portugal, Italy, Ireland, Greece and Spain (known as the PIIGS) during the financial and post-financial crisis period from…
Abstract
Purpose
This study focuses on the banking systems evaluation in Portugal, Italy, Ireland, Greece and Spain (known as the PIIGS) during the financial and post-financial crisis period from 2009 to 2018.
Design/methodology/approach
A conditional robust nonparametric frontier analysis (order-m estimators) is used to measure banking efficiency combined with variables highlighting the effects of Non-Performing Loans. Next, a truncated regression is used to examine if institutional, macroeconomic, and financial variables affect bank performance differently. Unlike earlier studies, we use the Corruption Perception Index (CPI) as an institutional variable that affects banking sector efficiency.
Findings
This research shows that the PIIGS crisis affects each bank/country differently due to their various efficiency levels. Most of the study variables — CPI, government debt to GDP ratio, inflation, bank size — significantly affect banking efficiency measures.
Originality/value
The contribution of this article to the relevant banking literature is two-fold. First, it analyses the efficiency of the PIIGS banking system from 2009 to 2018, focusing on NPLs. Second, this is the first empirical study to use probabilistic frontier analysis (order-m estimators) to evaluate PIIGS banking systems.
Details
Keywords
Faisal Abbas, Shoaib Ali and Muhammad Tahir Suleman
This study examined how economic freedom and its related components, such as open markets, regulatory efficiency, rule of law and the size of government, affect bank risk…
Abstract
Purpose
This study examined how economic freedom and its related components, such as open markets, regulatory efficiency, rule of law and the size of government, affect bank risk behavior, focusing on the Japanese context.
Design/methodology/approach
The study employs a two-step GMM framework on the annual data of Japanese banks ranging from 2005 to 2020 to empirically test the hypotheses. Furthermore, we also use the ordinary least square method to ensure the robustness of our mainline findings.
Findings
The finding suggests that economic freedom increases the banks' risk-taking, thus making them fragile. The results also highlight that out of the four main subcomponents of economic freedom, regulatory efficiency and government size increase bank risk-taking, while the rule of law and open markets decrease banks' risk-taking. Additionally, we examine how the banks' specific characteristics affect the results by creating a subsample based on capitalization and liquidity ratios. Overall, the results are consistent with the baseline findings. Moreover, the results are robust to alternative proxy measures of risk.
Practical implications
The study's findings have several implications for regulators and policymakers. The results suggest that regulators and policymakers should reconsider their strategies for economic freedom to ensure that they promote stability in the banking system and reduce banks' risk-taking inclinations.
Originality/value
Although previous studies have examined the impact of economic freedom on bank stability and risk-taking, this study is the first to do so in the Japanese context, contributing to the literature by providing new insights and empirical evidence.
Details
Keywords
Kavita Kanyan and Shveta Singh
This study aims to examine the impact and contribution of priority and non-priority sectors, as well as their sub-sectors, on the gross non-performing assets of public, private…
Abstract
Purpose
This study aims to examine the impact and contribution of priority and non-priority sectors, as well as their sub-sectors, on the gross non-performing assets of public, private and foreign sector banks.
Design/methodology/approach
The Reserve Bank of India's database on the Indian economy is used to retrieve data over 13 years (2008–2021). Public sector (12), private sector (22) and foreign sector (44) banks are represented in the sample. Two-way ANOVA, multiple regression and panel regression statistical techniques are used in SPSS and EViews to examine the data. Further, the results are also validated by using robustness testing by applying the fully modified ordinary least square (FMOLS) and dynamic least square (DOLS) regression.
Findings
The results showed that, for private and foreign banks, the non-priority sector makes up the majority of the total gross non-performing assets, although both the priority and non-priority sectors are substantial for public sector banks. The largest contributors to the total gross non-performing assets in public, private and foreign banks are industries, agriculture and micro and small businesses. The FMOLS displays robustness results that are qualitatively similar to the baseline result.
Practical implications
Based on the study's findings about the patterns of non-performing assets originating from these specific industries, banks might improve the way in which these advanced loans are managed.
Originality/value
There has not been much research done on the subject of sub-sector-specific non-performing assets and how they affect total gross non-performing assets across the three sector banks. The study's primary focus will be on the issue of non-performing assets in the priority’s and non-priority’s sub-sectors, namely, agricultural, micro and small businesses, food credit, industries, services, retail loans and other priority and non-priority sectors.
Details
Keywords
Luís Jacques de Sousa, João Poças Martins, Luís Sanhudo and João Santos Baptista
This study aims to review recent advances towards the implementation of ANN and NLP applications during the budgeting phase of the construction process. During this phase…
Abstract
Purpose
This study aims to review recent advances towards the implementation of ANN and NLP applications during the budgeting phase of the construction process. During this phase, construction companies must assess the scope of each task and map the client’s expectations to an internal database of tasks, resources and costs. Quantity surveyors carry out this assessment manually with little to no computer aid, within very austere time constraints, even though these results determine the company’s bid quality and are contractually binding.
Design/methodology/approach
This paper seeks to compile applications of machine learning (ML) and natural language processing in the architectural engineering and construction sector to find which methodologies can assist this assessment. The paper carries out a systematic literature review, following the preferred reporting items for systematic reviews and meta-analyses guidelines, to survey the main scientific contributions within the topic of text classification (TC) for budgeting in construction.
Findings
This work concludes that it is necessary to develop data sets that represent the variety of tasks in construction, achieve higher accuracy algorithms, widen the scope of their application and reduce the need for expert validation of the results. Although full automation is not within reach in the short term, TC algorithms can provide helpful support tools.
Originality/value
Given the increasing interest in ML for construction and recent developments, the findings disclosed in this paper contribute to the body of knowledge, provide a more automated perspective on budgeting in construction and break ground for further implementation of text-based ML in budgeting for construction.
Details
Keywords
Łukasz Kurowski and Paweł Smaga
Financial stability has become a focal point for central banks since the global financial crisis. However, the optimal mix between monetary and financial stability policies…
Abstract
Purpose
Financial stability has become a focal point for central banks since the global financial crisis. However, the optimal mix between monetary and financial stability policies remains unclear. In this study, the “soft” approach to such policy mix was tested – how often monetary policy (in inflation reports) analyses financial stability issues. This paper aims to discuss the aforementioned objective.
Design/methodology/approach
A total of 648 inflation reports published by 11 central banks from post-communist countries in 1998-2019 were reviewed using a text-mining method.
Findings
Results show that financial stability topics (mainly cyclical aspects of systemic risk) on average account for only 2%of inflation reports’ content. Although this share has grown somewhat since the global financial crisis (in CZ, HU and PL), it still remains at a low level. Thus, not enough evidence was found on the use of a “soft” policy mix in post-communist countries.
Practical implications
Given the strong interactions between price and financial stability, this paper emphasizes the need to increase the attention of monetary policymakers to financial stability issues.
Originality/value
The study combines two research areas, i.e. monetary policy and modern text mining techniques on a sample of post-communist countries, something which to the best of the authors’ knowledge has not been sufficiently explored in the literature before.
Details