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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.

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.

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.

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.

Government spending plays a crucial role in fiscal policy in any country, both as a tool for implementing individual government policies and as a possible instrument for mitigating uneven economic developments and economic shocks. This chapter provides direct empirical evidence on the development and structure of general government expenditure and its relationship with real economic growth in Czechia and the European Union countries. Compared to theoretical recommendations, general government expenditure has not been used as a stabiliser in Czechia and EU countries and has been observed to be pro-cyclical in the period under review. Granger causality analysis identified the direction of causality between the macroeconomic variables analysed and found that in most cases economic growth came first, followed by government spending.

This paper aims to enhance the Global Projection Model (GPM) developed by the International Monetary Fund by constructing a GPM4 model that includes the United States of America, the Eurozone, Japan and China.

This article introduces the United States of America, the Eurozone, Japan and China into a comprehensive global forecasting model, analyzing the impact of liquidity management in G3 economies on nine key macroeconomic variables in China.

The findings reveal that the liquidity management strategies employed by major economies do exert a certain influence on China's major macroeconomic variables. Different types of liquidity shocks elicit varying effects. Monetary shocks exhibit the strongest instantaneous impact, while credit conditions and policy rate shocks contribute more significantly to China's long-term macroeconomic fluctuations. However, no single shock stands out as the dominant factor.

This paper attempts to expand the GPM model developed by the International Monetary Fund and build a GPM4 model including China, the United States of America, the Eurozone and Japan. For the first time, the GPM model was used to analyze the spillover effects of liquidity management in major economies on China's macroeconomy and revealed the impact of non-price factors such as credit conditions on China's macroeconomic variables.

This paper aims to deepen the understanding of the relationship between global economic uncertainty and price volatility, specifically focusing on commodity, industrial materials and energy price indices as proxies for global inflation, analyzing data from 1997 to 2020.

The dynamic conditional correlation generalized autoregressive conditional heteroscedasticity model is used to study the dynamic relationship between variables over a while.

The results demonstrated a positive relationship between commodity prices and the global economic policy uncertainty (GEPU). Except for 1999–2000 and 2006–2008, the results of the energy price index model were very similar to those of the commodity price index. A predominant positive relationship is observed focusing on the connection between GEPU and the industrial material price index. The results of the pairwise Granger causality reveal a unidirectional relationship between the GEPU – the Global Commodity Price Index – and the GEPU – the Global Industrial Material Price Index. However, there is bidirectional causality between the GEPU – the Global Energy Price Index. In sum, changes in price indices can be driven by GEPU as a political factor indicating unfavorable economic conditions.

This paper provides a deeper understanding of the role of global uncertainty in the global inflation process. It fills the gap in the literature by empirically investigating the dynamic movements of global uncertainty and the three most important groups of prices.

This paper aims to provide a comprehensive bibliometric study of housing prices according to the articles collected by the Web of Science (WOS).

This paper studies 4,125 research papers on housing prices in the core collection database of WOS. Using VOSviewer, this paper makes a bibliometric and visual analysis of the housing prices research from 1960 to 2020 and probes into the housing prices research from five aspects: time, international cooperation, institutions author cooperation and research focuses.

Keywords such as influencing factors of housing prices, analysis of supply and demand, policy and housing prices and regional cities appear frequently, which indicates the main direction of housing price research literature. Recent common keywords include regression analysis and house price forecast. Countries, like the USA started early in the study of housing prices, and the means and methods in the field of housing price research are mature, leading the forefront of housing price research. Compared with the USA and other Western developed countries, the housing price research in developing countries needs to use innovative research methods and put more effort on sustainability. Research shows that housing price is closely related to economy, and keyword cluster analysis shows that gross domestic product, interest rate, currency and other keywords related to economy are of high-frequency.

This paper only uses articles from one database (WOS), which does not represent all research papers published worldwide. Some studies have been published for a long time, and the reference value to the research focuses and future research might be limited. There are many kinds of journals included in the study with different publishing frequencies, time ranges and numbers of papers. These may have some influence on the research results.

The main theoretical contribution of this paper is to supplement the current academic research on housing prices. This paper reveals the key points of housing prices research and possible research problems that need attention. We can know from the future research direction and practice which can offer insights for future innovative direction.

This study aims to understand how quickly Japanese banks readjust their capital ratios (leverage, regulatory capital, tier-I capital and common equity) following an economic shock.

This study uses a two-step system GMM framework to test the study's hypotheses using the annual data of Japanese commercial and cooperative banks ranging from 2005 to 2020.

The findings show that banks adjust their leverage ratio faster than regulatory capital, tier-I capital and common equity ratios. In addition to that, the results reveal that the speed of capital adjustment is higher for commercial banks than for cooperative banks, suggesting higher economic costs and implications for commercial banks. Furthermore, it is worth noting that well-capitalised (under-capitalised) banks tend to prioritise the adjustments to common equity (leverage) before considering the adjustments to leverage (common equity). According to the results, high-liquid (low-liquid) banks alter their regulatory capital and tier-I capital ratios (leverage) more quickly (more slowly) than low-liquid (high-liquid) banks.

The findings suggest that when formulating and implementing new banking regulations, particularly in assessing and adjusting specific capital requirements under Pillar II of Basel III, management (including bankers, regulators and policymakers) should consider the heterogeneity observed in the rate of capital adjustment across various bank characteristics. Additionally, bank managers should also consider the speed of adjustment when determining optimal half-life and target capital structures.

To the author's knowledge, this study represents a pioneering investigation into the rate of adjustment of capital ratios (leverage, regulatory, tier-I and common equity) within Japan's banking sector. The study employs a comprehensive dataset encompassing both commercial and cooperative banks to facilitate this analysis. A notable contribution to the existing body of literature, this study offers a detailed analysis and emphasises the varying degrees of adjustment in capital ratios. The study also highlights the heterogeneous nature of the adjustment rate in these ratios by categorising the data into well-capitalised, under-capitalised, highly liquid and low-liquid banks.

To the best of our knowledge, no study has examined credit cycle synchronizations in the context of emerging economies. Studying the credit cycles synchronization across BRICS (Brazil, Russia, India, China and South Africa) countries is crucial given the magnitude of trade and financial integration among member counties. The enormity of the trade and financial linkages among BRICS countries and growth spillovers from emerging economies to advanced and low-income countries provide the rationale and motivation to study the synchronization of credit cycles across BRICS.

The study investigates the credit cycles coherence across BRICS economies from 1996Q2 to 2020Q4. The synchronization analysis is done using the noval wavelet approach. The analysis examines not only the coherence but also the extent of credit cycle synchronization that varies across frequencies and over time among different pairs of nations.

The authors find heterogeneity in the credit cycles' synchronization among the member nations. China and India are very much in sync with the other BRICS countries. China's high-frequency credit cycle mostly leads the other countries' credit cycles before the global financial crisis and shows a mix of lead/lag relationships post-financial crisis. Interestingly, most of the time, India's low-frequency credit cycles lead the member countries' credit cycles, and Brazil's low frequency credit cycle lag behind the other BRICS countries' credit cycles, except for Russia. The results are crucial from the macroprudential policymaker's perspective.

The empirical design is applicable to a similar set of countries and may not directly fit each emerging economy.

The findings will help understand the marked deepening of trade, technology, investment and financial interdependence across the world. BRICS acronym requires no introduction, but such analysis may help understand the interaction at the monetary policy level.

This is the first study that highlights the need to understand the credit variable interactions for BRICS nations.

This paper bridges the gap between the theory and practice by developing a life cycle sustainability tracker (LCST). The study is seeking to proffer solutions to an observed shortcoming of conventional life cycle sustainability assessment (LCSA) communication platforms. Notably, the static nature of the information provided on such platforms has made it difficult for them to be used for real-time decision-making and predictions. The main aim of this paper is to develop a LCST that facilitates a dynamic visualisation of life cycle sustainability results and allows for an integrated benchmark across the dimensions of sustainability.

The study leverages the model development capabilities of the design science research strategy in accomplishing a dynamic and novel communication platform. A life cycle thinking methodology and appropriate multicriteria decision approach (MCDA) is applied to accomplish a comprehensive, streamlined and replicable approach in mapping and tracking the progress of sustainable development goals (SDGs) in the National Infrastructure Pipeline (NIP) projects in India.

It was found that: (1) The use of the LCST tracker provides a dynamic and holistic insight into the key LCSA indicators with clearly defined benchmarks to assess the impact on the SDG 11, (2) The NIP projects achieve an upward trend across all the regions, and the percentage of opportunities ranges from 11 to 24%, with the South experiencing the highest growth and the North having the minimal increase in percentage and (3) The assessment score (52–58%) provides performance metrics that align well with the LCST – which ranges between “Fair” and “Average” for all the regions in India.

The novelty of this research is that the LCST provides a transparent and harmonised approach to reporting on the LCSA results. The LCST utilises heat maps and radial mapping to achieve an intuitive display of large amounts of highly heterogeneous data, thus allowing the synthesis of large sets of information compactly and with coherence. Progress towards the SDGs change on a yearly basis; hence, a dynamic LCSA tool provides a timely and the valuable context to map and track performance across different regions and contexts.

Do women contribute to performance of companies on which they serve as board of directors? Many prior studies examine this issue, but no consensus is reached on the benefits of women taking on leadership positions. The present study considers this thorny issue from a slightly different perspective. Does the association between gender diversity and business performance vary across sectors and economic cycles?

The sample for this study was derived from the firms included in the S&P Australian Securities Exchange (ASX) 300 Index, and the study period of 2004–2016 allowed authors to consider the effects of different sectors as well as different economic cycles on the relationship between gender diversity of boards and business performance. The authors consider the Australian context, which is somewhat unique from the other Western countries, as quotas on boards of directors are not made mandatory and the corporate governance practices are principle-based rather than rule-based.

Employing panel data models, at the aggregate level, the authors find no evidence of board gender diversity impacting business performance. Consideration of sectoral differences and economic cycles in the empirical analyses yielded additional insights. In particular, gender diversity has a beneficial association with performance for businesses in the services and financial sectors after the changes to corporate governance guidelines relating to diversity in 2010. These economic benefits, however, are not evidenced in the resources sector.

These findings offer support for critical mass and resource dependence theories.

The findings of this study have implications for inclusion and diversity policies of businesses and the society. Specifically, the findings offer support for gender diversity of corporate boards of directors.

This study highlights that women bring their unique skills and experiences to create economic value in sectors where they traditionally have more experience and opportunities.

This article seeks to offer an answer. It explores the criteria on which commercial property market participants can develop strategies in hugely challenging circumstances. For this purpose, a survey-based approach was developed with work conducted with property-market professional in the United Kingdom (UK), France, Germany and Sweden to produce a criteria-based tool supporting adaption to changing market circumstances.

The data have been analyzed using statistical analysis. The data's statistical analysis included Cronbach's alpha's application to evaluate the respondents' replies' reliability. A entral tendency test was used to identify the means of relevance of the criteria. The Mann–Whitney U test was used to determine potential material differences between the UK and other countries with Bonferroni corrections applied to minimize type-I errors.

Thirty characteristics have been identified that impact the dynamics of the commercial property market. Their relevance to the commercial property market was determined using a survey. The literature analysis showed that the researchers paid more attention to quantitative criteria and their comparison. The survey showed that the relevance of criteria to the commercial property market dynamics is unequal. However, the survey results showed that it is most important to pay attention to emotional criteria to adapt to uncertainty changing conditions. The problem of the environment has been on the agenda for the last four decades. Therefore, the fact that the results of the study showed that the environmental criteria are the least significant is unexpected.

The study involved economically developed countries of Europe. Extending the study's geographical scope would be valuable in revealing whether the same differences exist in other geographical areas (such as Australia or the USA).

The practical implication of the analysis may be to facilitate the decision-making process of either selecting a country for commercial property investment or selecting the most sensitive and relevant criteria for the decision-making.

Criteria for commercial property market performance which promote successful property investment have been developed. Moreover, the criteria affecting the commercial property market have been weighted by their relevance to the market and their sequence of relevance has been established. And finally, the developed criteria have been placed into five groups that could serve as a foundation for a macro-level assessment of commercial property market dynamics.