Search results

This paper aims to study the formation and amplification mechanism of the financial crisis and business cycle and also discuss the related optimal rules for the central bank and government.

This study is developed basically on a simple financial business cycle model by embedding credit constrains into the DSGE model.

The model in this paper puts forward an explanation for the mechanism of cycles' formation. Using this it finds that: the financial lever in modern economy is the offender of the USA financial crisis, which created the cycles and amplified it into the crisis when the financial lever multiple was increased to much greater levels, and that the traditional policy rule is not good enough for a long running growth process.

The findings in this study suggest that to keep the financial lever multiple under a safe level and to reform the policy rule to be good enough for a long run growth process is necessary.

According to the model's principle, the paper claims that: the development of the financial and credit markets during recent years has increased the volatility of the economic cycle – excessive credit abuse has become the root cause of the instability of the economy system; the proportion of the mortgage loan and similar financial products in the economy should be controlled strictly; it is necessary to recheck the traditional standpoint of the monetary policy. Rule policy by the Keynesian model exists as a short‐term problem, thus it is not sufficient to study the questions related to technological shocks.

The model in this paper explains well the mechanism of cycles and crisis' formation. The findings under the modeling economy give a safe level for financial lever multiples for the first time. The financial business cycle model being used in studying the Chinese economy is a pioneering and exploratory experiment.

This study investigates the impact of AI finance on financing constraints of non-SOE firms in an emerging market.

Using a sample of non-SOE listed companies in China from 2011 to 2018, this research employs the cash–cash flow sensitivity model to examine the effect of AI finance on financing constraints of non-SOE firms.

We find that the development of AI finance can alleviate the financing constraints of non-SOE firms. Further, we document that such effect is more pronounced for smaller firms, more innovative firms and firms in developing areas.

This study suggests that emerging market countries can ease the financing constraints of non-SOE firms by promoting AI finance development.

This study, to the best of our knowledge, is the first one to explore the relationship between AI finance development and financing constraints of non-SOE firms in emerging markets.

This study aims to investigate the efficiency of Indian commercial banks from 2002 to 2018 using the stochastic frontier analysis.

This study uses the parametric approach of the stochastic frontier to examine the technical efficiency of banks acknowledging exogenous shocks, omitted variables and measurement errors, filling a gap in the existing financial literature. The scope of this study was constrained to 71 scheduled commercial banks to make it manageable and productive with 1,036 observations.

The results show that the mean technical efficiency of new private banks remained constant at 92.7% during the study period because of technology diffusion in banking systems. The technical efficiency of the nationalized, old private and foreign banks has enhanced over the period because of the efficient utilization of various innovative information technology services such as mobile banking, cheque truncation system, magnetic ink character recognition. However, the foreign banks are still laggards with a mean technical efficiency of 81.7%. The empirical findings suggest that new private sector banks depict higher efficiency than nationalized, old private and foreign banks.

This study’s sample represents all categories of banks (public, private and foreign) including the banks that merged or consolidated during the period of study. To achieve the desired results, the authors incorporate the consolidated and merged banks in their data set. Further, the authors excluded all scheduled small finance banks and scheduled payment banks from their analysis, as these entities commenced operations post-2015. Additionally, the authors also excluded regional rural banks because of their distinct mandate aimed at servicing the rural populace and agricultural sector.

This study contributes to the literature on the performance of conventional banks in general and emerging markets, in particular, using the most recent data and covering a relatively long period using the stochastic frontier approach.

The purpose of this study is to investigate the effect of internal and external variables on the profitability of conventional banks operating on developing and underdeveloped countries, the Organization of Islamic Cooperation (OIC) states.

In this paper, the author uses ordinary least squares fixed-effects model on an unbalanced panel data set of all conventional banks operating in OIC countries (52 countries included from 57) over the period 1989-2008, 686 banks.

The results suggest that equity, foreign ownership, off-balance sheet (OBS) activities, real gross domestic product growth, real interest rate and concentration foster banks’ profitability. In addition, the results showed that the banking sector development and loans will increase banks’ profitability in the long run in the countries of the studies. In contrast, the study reported that deposits lower profitability. The study also revealed that GDP per capita, market capitalization and banks size have no impact on profitability.

The findings of this study have considerable policy implications. First, policymakers need to regulate nontraditional activities to avoid any financial crisis because banks in OIC countries are heavily engaged in nontraditional activities to boost its profit. Second, policymakers are advised to improve the deposit insurance system to insure the stability of the financial system as well as improving banks’ profitability. Third, policymakers need to improve the efficiency of the stock market, maintain small banking system and encourage foreign investments in the banking system.

The paper adds to the literature on the commercial bank’s profitability determinants. In particular, such study has not been conducted on OIC countries, and the study included all mainstream banks and incorporated the effect of deposit insurance system so far. Also, pure sample of conventional banks used as many conventional banks in OIC countries have Islamic windows or offer Islamic products. In addition, this study investigated the effect of OBS activities on net interest margin (NIM) because the studies that explored this interrelationship are limited especially for developing and under developed countries. The results showed that OBS activities contributed significantly and positively to return on assets and NIM. Moreover, this paper used a pure sample of conventional banks to avoid any biasness; see data section. Moreover, this study gives an idea about the economic situation and financial conditions of OIC countries during the period of the study.

This chapter examines the impact of banking competition, bank regulation, and the global financial crisis (GFC) of 2008–2009 on banks’ productivity changes. For the empirical analysis, I apply a semi-parametric two-step approach of Malmquist index estimates and bootstrap regression to a cross-country panel data of 8,451 commercial banks from 82 countries over the period 2004–2012. Empirical results show that (1) banking competition and capital regulation significantly enhance bank productivity, (2) a tighter bank supervision have a positive impact on bank productivity, and (3) bank productivity decreases during the GFC, but starts to increase as the GFC recovers. I also present consistent evidence that commercial banks in countries with better national governance have higher productivity growth before, during and after the GFC.

The purpose of this paper is to examine the effect of bank specific, financial structure and macroeconomic factors on the shareholder value of banks in GCC economies during 2000–2017.

To estimate the model and analyze the data collected from the BankScope and World Bank World Development Indicator database, the author uses static panel estimation techniques as well as two-step difference and system dynamic generalized method of moments estimator.

The results show that banks that are highly dependent on non-traditional activities have higher shareholder value. Higher opportunity cost, capitalization and demand deposits result in a better bank shareholder value. Furthermore, banks with higher loan exposure and growth have better shareholder value. Non-performing loans and market risk have insignificant effects on bank shareholder value. However, GCC banks suffer from diseconomies of scale and scope. The author also finds that banks located in countries with high inflation rates, high rates of interest or in financially developed economies offer better shareholder value. High credit to the private sector reduces the bank shareholder value. The paper also provides evidence that the impact of financial turmoil on the shareholder value of the GCC banking sector is negative and significant and has severely weakened the GCC banking system.

The results of this study necessitate formulation of various policy measures that can counter the effects of shareholder value of banks.

The present study is among the first to address the influence of financial turmoil on bank shareholder value. It also studies new variables, such as demand deposits, non-performing loans, loan growth, non-interest revenue and off-balance sheet activities, which have not been examined in relation to bank shareholder value. It also applies both static techniques and dynamic panel estimation techniques to analyze the data. The analysis is carried out at the aggregate level as well as at the national level and also provides several robustness analyses using various model specifications.

This paper examines the profitability and performance measurement of U.S. regional banks during the period 1994–2011, using the GMM estimator technique. Our study extends prior research by including several factors not previously considered using U.S. data.

We use bank-specific, industry-specific, and macroeconomic determinants of profitability contemporaneous with our performance indicators. We follow the accounting fundamental analysis path in explaining the bank performance.

Among the performance measures, the efficiency ratio and provisions for credit losses are negatively and equity scaled by assets is positively related to profitability. However, these relationships either reverse (efficiency ratio and provisions for credit losses) or become insignificant (equity scaled by assets) when the target becomes change in profitability. The level of nonperforming assets is negatively related to profitability across all measures of profitability used. Macroeconomic variables are largely unrelated to profitability during the year they are measured. However, they have a significant relationship with earnings change measures, suggesting they have a lagged effect on profitability. The slope of the yield curve is especially strong in this regard.

We use our determinants to model changes in bank profitability one year ahead, in addition to including several factors not previously considered, using the predictive focus of the fundamental analysis research.

Focusing on micro-level indicators, we investigate financial inclusion levels in rural China, examining its determinants and impact on household welfare. We construct a financial inclusion index of four essential financial services: savings, digital payments, credit and insurance. We identify factors influencing financial inclusion among Chinese rural households and assess the effects of financial inclusion on household welfare.

With the entropy method, we use data from the 2019 China Household Finance Survey to assess financial inclusion levels in rural China. Determinants and their impact on welfare are analyzed through probit and ordinary least squares models, respectively. Propensity scoring matching is applied to address potential endogeneity.

We reveal that rural households exhibit limited usage of formal financial services, with notable regional disparities. The eastern region enjoys the highest financial inclusion and the central region lags behind. Household characteristics such as family size, education level of the household head, income, employment status and financial literacy significantly influence financial inclusion. Financial inclusion positively impacts household welfare as indicated by household consumption expenditure. The use of different types of financial services is crucial with varying but significant effects on household welfare.

This study offers valuable insights into China’s rural financial inclusion progress, highlighting potential barriers and guiding government actions.

The purpose of this paper is to investigate the effect of external financing needs on both firm value and corporate governance mechanisms within the UK SME context. This framework is of importance because of the limited external financial resources SMEs might face.

The authors consider the endogeneity problem between corporate governance mechanisms and firm value, and hence, the three stages least squares and the instrumental variables based on two stages least squares estimation methods are employed.

The authors find a positive relationship between external financing needs and firm value. In addition, the authors detect that size and profitability are positively associated with firm value in the sample. Concerning the corporate governance index (CGI), the authors detect that big SMEs and those with low-debt levels have better corporate governance structures.

The authors employ a CGI for the sample which is constructed using ten corporate governance variables. The authors also examine different factors that affect SMEs 2019 governance by applying different models including logistic analysis.