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The article investigates whether variety of democracy affects the probability to employ public subsidies for credit support by small- and medium-sized enterprises (SMEs) led by female entrepreneurs.

Building on the literature on democracy and on gender differences, it leverages a large firm- and country-level dataset (SAFE) of 31 democracies in Europe (EU and non-EU) over the 2009–2014 period by using probit models and instrumental variable approaches.

Results from the different econometric techniques and samples suggest that variety of democracy affects female-led SMEs in using public subsidies for credit support. The evidence is robust to endogeneity concerns.

The empirical evidence presents a time frame limitation. At the same time, SAFE is the only database that supplies information about the gender of firms and public subsidies for credit support, rendering it the only resource that allows the test of the hypothesis proposed. The article therefore offers insights for scholars to revisit our results in future studies that make use of datasets with a longer time span – when they will become available.

To the best of the authors' knowledge, the article is the first to study the effect of democracy on female entrepreneurial behavior in the use of public subsidies for credit support.

Our study aims to evaluate the impact of infrastructure and public investment on private investment in machinery and equipment in Brazil from 1947 to 2017. The contribution of our article to the existing literature lies in providing a more comprehensive understanding of the presence or absence of the crowding effect in the Brazilian economy by leveraging an extensive historical database. Our central argument posits that the recent decline in private capital accumulation over the last few decades can be attributed to shifts in economic policies – moving from a developmentalist orientation to nondevelopmental guidance since the early 1990s, which is reflected in the diminished levels of public investment and infrastructure since the 1980s.

We conducted a series of econometric regressions utilizing the autoregressive distributed lag (ARDL) model as our chosen econometric methodology.

Employing two different variables to measure public investment and infrastructure, our results – robust across various specifications – have substantiated the existence of a crowding-in effect in Brazil over the examined period. Thus, we have empirical evidence indicating that the state has influenced private capital accumulation in the Brazilian economy over the past decades.

Our article contributes to the existing literature by offering a more comprehensive understanding of the crowding effect in the Brazilian economy, utilizing an extensive historical database.

This study seeks to build a financial uncertainty index for Saudi Arabia. This index serves as a leading indicator of Saudi economic activity and helps to describe economic fluctuations and forecast economic trends.

This study adopts an extension of the Jurado et al. (2015) procedure by combining financial uncertainty factors with their net spillover effects on GDP and inflation to construct an aggregate financial uncertainty index. The authors consider 13 monthly financial variables for Saudi Arabia from January 2010 to June 2021.

The empirical results show that the constructed financial uncertainty estimates are good leading indicators of economic activity. The robustness analysis suggests that the authors’ proposed financial uncertainty estimators outperform the alternative estimates used by other existing approaches to estimate the financial conditions index.

To the best of the authors’ knowledge, this is the first attempt at constructing a financial uncertainty index for Saudi Arabia. This study extends the empirical literature, from which the authors propose a novel conceptual framework for building a financial uncertainty index by combining the approach of Jurado et al. (2015) and the time-varying connectedness network approach proposed by Antonakakis et al. (2020)

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.

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.

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.

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.

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.

The purpose of this study is to examine mediating role of public sector governance in the relationship between entrepreneurship and economic growth in the Palestinian context during the years 2005–2020.

The necessary data were collected from the World Bank website and the annual financial reports of the Palestinian Monetary Authority. To achieve the study’s objectives, the researcher used content analysis method and regression model.

There is an effect of some dimensions of entrepreneurship (starting a business, obtaining credit, women starting a business) and public sector governance with dimensions (voice and accountability, political stability and absence of violence, effectiveness of government performance, organizational quality, the rule of law and control of corruption) on economic growth. In addition, there is no mediating effect of public sector governance in the relationship between entrepreneurship and economic growth.

The study helps in enhancing the elements of entrepreneurship by evaluating public governance in Palestine. It also offers future researchers a comprehensive vision that encourages Palestinian economic growth.

The paper contributes to showing the reality of public governance indicators for the Palestinian context and the amount of support for entrepreneurial activities indicators that affect economic growth.

Trying to activate cooperation mechanisms between government institutions and entrepreneurial institutions to adopt creative projects and ideas, especially for women, needs to focus on activating the principles of public sector governance in addition to facilitating administrative and financial procedures to start commercial projects in a way that enhances economic growth with the need to achieve the highest level of public sector governance indicators.

This study investigates the relationship between credit booms and bank risk in Association of Southeast Asian Nations (ASEAN) countries, with credit information sharing acting as a moderator.

The authors use a two-step System Generalized Method of Moments (SGMM) estimator on a sample of 79 listed banks in 5 developing ASEAN countries: Indonesia, Philippines, Malaysia, Thailand and Vietnam in the period 2006–2019. In addition, the authors perform robustness tests with different proxies for credit booms and bank risk. The data are collected on an annual basis.

Bank risk is positively related to credit booms and is negatively associated with credit information sharing. Further, credit information sharing reduces the detrimental effect of credit booms on bank stability. The authors find that both public credit registries and private credit bureaus are effective in enhancing bank stability in ASEAN countries. These results are robust to regression models with alternative proxies for credit booms and bank risk.

Banks in ASEAN countries tend to have strong lending growth to support the economy, but this could be detrimental to stability of the sector. Credit information sharing schemes should be encouraged because these schemes might enable growth of credit without compromising bank stability. Therefore, policymakers could promote private credit bureaus (PCB) and public credit registries (PCR) to realize their benefits. The authors' research focuses on developing ASEAN countries, but future research could provide more evidence by expanding this study to other emerging economies. In-depth interviews and surveys with bankers and regulatory bodies about these concerns could provide additional insights in the future.

The study is the first to examine the role of PCB and PCR in alleviating the negative impact of credit booms on bank risk. Furthermore, the authors use both accounting-based and market-based risk measures to provide a fuller view of the impact. Finally, there is little evidence on the link between credit booms, credit information sharing and bank risk in ASEAN, so the authors aim to fill this gap.

This study aims to investigate the intricate relationship between corruption and the credit costs faced by small and medium-sized enterprises (SMEs) in OECD countries, a critical yet underexplored area in financial crime research. The primary aim is to dissect and understand how corruption impacts SMEs’ access to credit, highlighting a significant yet overlooked aspect of financial crime. This research seeks to fill a gap in the literature by providing empirical insights into the economic consequences of corruption, specifically on SMEs financing.

This study used secondary panel data from the World Bank and OECD databases. The data covered the period 2007–2020 for 25 OECD countries. This study used interest rate for SMEs loans as a dependent variable and GDP per capita, inflation and corruption index as independent variables. This study used the panel autoregressive distributed lag (ARDL) model to examine the relationship between variables.

The empirical findings derived from Panel ARDL postulate an intriguing dichotomy in the effects of GDP per capita, inflation rate and corruption on interest rates in both the short and long run. It was discerned that an increase in GDP per capita and inflation rate correlates with a decrement in interest rates in the long run, suggesting a potential compromise by central banks between controlling inflation and fostering economic growth.

This paper makes a novel contribution to the field of financial crime by illuminating the often-overlooked economic dimensions of corruption in the context of SMEs financing. It provides a unique perspective on the ripple effects of corrupt practices in credit markets, enriching the academic discourse and informing practical approaches to combating financial crime.

This study aims to examine the effectiveness of the debt modification system (DMS) in Korea. We find that DMS does have a positive effect in increasing the credit scores and annual income of DMS users. We also find that a debt management plan (DMP) is more effective in raising credit scores than personal rehabilitation (PR). However, the credit scores of DMS users in the first half of 2019 (551.1–626.1 points) are at a very low level, making it difficult to access low-interest unsecured loans from banks. Therefore, DMS in Kores is still insufficient to support the return of debt-ridden consumers to normal financial life and provide opportunities for a fresh start.

The purpose of this study is to examine whether the required disclosure and the high frequency of key audit matters (KAMs) are likely to moderate the effect of higher credit risk on earnings quality.

This study uses 15,106 Taiwanese firm-year observations to explore the relationship between earnings quality and credit risk during the 2011 to 2020 period. We use the two-stage least squares method to test whether the presence of KAM disclosures moderated the association between earnings quality and credit risk and also to examine whether higher KAM frequency moderates the association between earnings quality and credit risk.

Our results provide evidence that the presence of a KAM disclosure requirement moderates the impact of firms with higher credit risk on earnings quality. In addition, there is significant evidence that the higher the frequency of KAM disclosures the greater the moderation impact that is found.

This research investigates whether the disclosure and high frequency of KAMs moderates the effect of credit riskiness on earnings quality. This study improves our understanding of whether more KAMs disclosures would improve earnings quality of firms with higher credit risk. In addition, we also use Beneish M-SCORE, as an alternative earnings quality proxy, to reinforce our empirical results. This markedly differentiates this paper from other studies.

Business research and development (R&D) is of critical importance for innovation and economic growth. The purpose of this study is to present an application of the analytic hierarchy process (AHP) to select the most appropriate policy measure to support the business expenditure on R&D (BERD).

AHP method adopts a multi-criteria approach that can be used to analyse and prioritize the policy measures based on pairwise comparisons between several attributes that affect the selection of a policy tool. The model formulated in this study is applied to a real case of supporting decision-makers in some high-tech sectors in Iran.

The results highlight the four main financial policy measures implemented in Iran to enhance the BERD; those are, public procurement for R&D, direct subsidies for R&D, grants for R&D and income tax credit for firms have the priority values of 0.280, 0.260, 0.249 and 0.211, respectively.

The findings of this study are based on subjective evaluation of policy measures by experts of designing policy measures. Objective assessment of policy measures is important too because the preferences of policy interventions change during the time. Another significant point is that the priorities of specific policy measures depend on the effectiveness of their implementing arrangement and the previously successful experience of firms in receiving them.

This paper presents an application of the AHP to select the most appropriate policy measure to support the BERD. This method could be used to prioritize the policies and interventions that governments implement to solve different problems, especially at the innovation system level.