Global Development Finance Research Articles

The time-varying co-movements between energy market and global financial market

Since the global financial crisis in 2008, international energy markets have become more closely linked to financial markets and energy prices have exhibited more financial characteristics. Therefore, it is of great theoretical and practical significance to study the time-varying synergy between the energy market and the global financial market. This paper sets up a model for realizing the time-varying co-movements between energy markets and global financial markets: It uses the Diebold &Yilmaz spillover index method and its dynamic expansion model to test the spillover mechanism of market volatility shocks, applies the deep long and short-term memory (DLSTM) model to predict market prices. The results of this study show that, first, energy markets and global financial markets are closely linked networks, and the spillover effects have obvious time-varying characteristics. Second, from a static spillover perspective, the Global Financial Price Index shows the largest net exporter in both yield and volatility spillovers, suggesting that the global financial development market has the strongest influence on other markets. However, in the volatility spillover, the net spillover index shows alternating periods of positive and negative periods most of the time.

The Effect of Digital Financial Inclusion on Bank Efficiency

The growing development of digital technology has profoundly alter the financial industry. This paper would like to investigate the effect of the digital financial inclusion on the bank efficiency. The digital financial inclusion will be measured by the digital payment, while the bank efficiency by the lending-deposit spread. Based on the country level data from Global Financial Development Index database issued by The World bank, this paper found the significant effect of digital financial inclusion on the bank efficiency. This result reflects the importance of financial inclusion in the digital form on the improvement of performance of banking sector.

Monetary Policy And Financial Development In Nigeria

The financial growth and developmental stride of Nigeria can only be achieved if there is consistency in the monetary policies and thriving of its elements including the interest rate. This study investigated the monetary policies and financial development in Nigeria between 2004 and 2023. The specific objectives include to examine the impact of interest rates on Nigeria’s financial depth; to assess the impact of interest rates on Nigeria’s financial stability; to evaluate the impact of interest rates on Nigeria’s access to finance; and to determine the impact of interest rates on Nigeria’s efficiency of the financial system. historical data of yearly from the World Development Indicator (WDI) for the data set of interest rates, that is, Broad Money (in terms of GDP) and Deposit Interest Rate, while, the data for financial stability, depth, access, and efficiency were obtained from the Global Financial Development, which are Bank Z-Score, Domestic credit to the private sector, Bank Branches per 100,000 adults, and Bank net interest margin respectively. Data analysis was done using descriptive statistics and inferential statistics of unit root tests, co- integration test, panel cointegration, estimation of panel cointegration regression while dynamic fixed effect model is applied to get the impact. The conclusion from this study shows that there is a significantly positive impact of BZS on the DIR indicating about 15% impact as reiterated by its 15.9% coefficient value while the DCPGDP, shows an insignificant positive impact on the DIR reinforced by its coefficient value of about 1.2%. For the BBA, it shows a positively low impact on DIR with coefficient of about 4% while the BNIM negatively impact the DIR shown by its coefficient of -24.5%. This study recommended that deepening financial sector growth is necessary to boost the monetary transmission mechanism meaning that it is important to acknowledge the lag in the effects of interest rate modifications on financial stability, hence, requiring a measured approach to assess the efficacy of policy alterations on the nation's overall financial stability.

Revisiting natural resources rents and sustainable financial development: Evaluating the role of mineral and forest for global data

This study analyzes the impact of total natural resources rents, economic growth, mineral rents, and forest rents on global financial development. Using the extended period from 1990 to 2020, this study utilizes the novel Quantile-on-Quantile regression approach. The estimated results asserted that economic growth is favorable for global financial development. However, total natural resources, mineral rents, and forest rents exhibit asymmetric influence on global financial development. The influence is positive with a lower frequency but negative in most quantiles for the latter (natural resources) variables. The negative impact of natural resource rents substantiates the natural resource curse in global financial development. The Breitung-Candelon Spectral Granger causality test asserted that total natural resources rents cause global financial development in the long run. It validates the importance of total natural resources in attaining global financial development. Based on the empirical results, this study suggests policies to help global financial development. Specifically, enhanced economic growth and government intervention in regulating natural resources via utilizing financial resources.

China’s global development finance poses heterogeneous risks to coastal and marine socio-ecological systems

<h2>Summary</h2> Rapid coastal development continues to jeopardize the integrity of marine socio-ecological systems. China is now the largest bilateral creditor of overseas development finance, and there are growing concerns over the impacts of this boom in Chinese development finance on marine systems. Here, we quantify the risks of coastal development projects financed by China to marine biodiversity and coastal Indigenous communities. Ports present the greatest impact risks to marine systems, with power plants, roads, and other facilities presenting relatively high localized risks. Risks are most prominent in Africa and the Caribbean, with coastal Indigenous communities in Western Africa at greatest risk from development. All projects present some risk to threatened marine species and potential critical habitats, but few present high risks to nearby protected areas. Mitigating these risks will require more social and environmental safeguards, higher standards for host country impact assessments, and greater integration of land-sea risk mitigation and management approaches.

Regional Import and Export Influencing Factors in Jiangsu Province, China Based on RBF Neural Network Analysis

With economic globalization, import and export trade has become a key factor affecting economic growth, and the sample data of Jiangsu province, as an important part of China's import and export trade, is a typical representative. This paper selects the annual data of Jiangsu Province from 2000 to 2021, determines the main influencing factors by rooting in past research theories, adopts the structure, characteristics and training algorithm of RBF (radial basis function) neural network, and applies the neural network to establish a multi-factor nonlinear time series forecasting model based on the mapping relationship between Jiangsu Province's import and export and its influencing factors. The conclusions are as follows: This paper builds a neural network around the data related to the import and export of foreign trade affecting Jiangsu Province from 2000 to 2021, and establishes an indicator system for the trend of foreign trade and the influencing factors of Jiangsu Province. The analysis finds that the highest accuracy is achieved when the neuron is 9. The degree of trade barriers, regional social financing scale, global economic growth rate and financial development efficiency are the main factors influencing the total amount of foreign trade import and export of Jiangsu province. Under the background of global trade being hindered by the epidemic and stagnant, the current situation of foreign trade development in Jiangsu Province should focus on breaking through from the above factors, considering domestic and international economic development, accelerating its financing scale and financial industry development, and promoting the steady development of foreign trade.

Determinants of Non-performing Loans: A Panel Data Approach

This paper considers a panel of 80 countries across all continents, over the period 1999–2019, and uses panel generalized method of moments system estimations with data from the World Bank Global Financial Development database, to explain the evolution of the bank non-performing-loans-to-total-loans ratio. The results obtained provide clear evidence that banks with high profitability, benefiting from market stability and located in countries with increasing economic growth are not expected to have high values of the non-performing-loans-to-total-loans ratio. On the other hand, high values of this ratio are robustly associated with an increase of the bank-cost-to-income ratio, market concentration, and bank regulation. The paper also contributes to the literature by assessing the relevance of the level of each country’s income and economic integration. Overall, the results obtained reveal few differences between high-income and non-high-income countries and between Organization for Economic Cooperation and Development (OECD) countries and non-OECD countries. However, considering only the years after the onset of the global financial crisis (2009–2019), there is robust evidence that bank regulation contributed to a decrease in the non-performing-loans-to-total-loans ratio, but only in non-high-income countries and non-OECD countries. Finally, the results for all considered panels, clearly show that the promotion of economic growth is always the best way to assure a decrease in the non-performing-loans-to-total-loans ratio, reducing the likelihood of banking losses as well as potential financial crisis.

INFORMALITY AND TOTAL FACTOR PRODUCTIVITY IN KENYA

Purpose: The Kenyan economy is largely informal. The objective of the study was to establish the effect of size of the informal sector on total factor productivity in the country.&#x0D; Methodology: The study was based on the dualist theory of the economy. Data covering the period 1974 to 2016 was sourced from government publications (Economic Surveys and Statistical Abstracts), the Global Financial Development Database and the World Development Indicators. A growth accounting exercise was conducted using the Cobb-Douglas production function based on the Solow growth model. This enabled the decomposition of output growth to the contributions of labour and capital with a residual, commonly referred to as the total factor productivity which was the dependent variable in the study. The study was non-experimental and utilized a longitudinal research design using macro-level data thus limiting the possibility of data manipulation. Various theoretically and empirically recognized determinants on TFP were included as control variables. The analysis was conducted using ordinary least squares.&#x0D; Findings: The findings show that the size of the informal sector has a negative and statistically significant effect on total factor productivity in Kenya. Given the large informal sector, the study concluded that there is need to increase productivity of the sector in the country for improved economic performance.&#x0D; Unique contribution to theory, practice and policy: From the study findings, the informal sector has a negative and statistically significant effect on total factor productivity in Kenya. The study recommends the development and implementation of policies to enhance productivity in the sector. These include market and technological development, improved infrastructure and access to credit facilities.

Sustainable Financial Development: Does It Matter for Greenhouse Gas Emissions?

As the detrimental effect of greenhouse gas emissions becomes increasingly significant, it has been a worldwide concern. As a result, the purpose of this paper is to examine the effect of sustainable financial development on greenhouse gas emissions via heterogeneous technological progress, using 162 countries as a sample. Empirical assessment is conducted using panel data from 2000 to 2019 and the mediation effect model as well as the country and year fixed-effect model. The findings are shown as follows: (1) Greenhouse gas emissions are increased as a result of sustainable financial development. (2) Environmental technology progress and technology choice progress have a dilution effect. Together, they have the ability to lower the amount of greenhouse gas emissions caused by sustainable financial development. However, these two dilution effects do not completely cut down on the amount of greenhouse gas emissions that come from global sustainable financial development, even though they do help. (3) The direct and indirect effects of sustainable financial development on greenhouse gas emissions are heterogeneous among countries with different income levels. Through technological progress, sustainable financial development in middle-income countries significantly cuts greenhouse gas emissions. Sustainable financial development, on the other hand, increases greenhouse gas emissions in both high- and low-income countries, although there are distinctions between them. (4) Environmental technology progress in high-income countries has a dilution effect. Meanwhile, technological choice and progress in low-income countries have a mediating effect on greenhouse gas emissions. To conclude, the evidence provided in this paper may provide some potential solutions to the issue of greenhouse gas emissions, and also enrich the existing literature.

Analysis of the Economic Impact of the US Presidential Candidates on the United States and China

The year 2020 is the year of the US presidential election, with both candidates focusing on key development areas such as finance and trade, economic and financial governance. Different candidates will shape different global economic and financial development strategies that will have a greater impact on the U.S. economy and the global economy, including China’s. China-us relations have become the focus of the world's attention. We collected data for both China and the US (2002-2019) based on data regression and prediction. Besides, the model of random forest and support vector machine is established to analyze the relationship between various data to help us solve the problem and to think about the impact of different candidates' election on the Chinese and American economies. The clearer the data relationship is, the more accurate our conclusions will be. This paper looks up the relevant data and selects the features through stepwise regression, and uses the final retained features in SVM model to fit the relationship between various measures and economic development, and finally makes prediction. This paper establishes a BP neural network model to fit China's economic development data with the quantitative data of the relevant measures of the president of the United States, and finally realize the prediction of China's economic development. based on the results of the previous two questions, this paper compares Biden's and Trump's policies towards China, and gives relevant suggestions.

An improved weighted principal component analysis integrated with TOPSIS approach for global financial development ranking problem of Middle East countries

AbstractFinancial development means some improvements on providing the information about investment possibilities in a region or country. In this study, a new perspective of financial development is considered which is called the multi‐criteria global financial development‐ranking problem. In this problem, some countries from the Middle East are considered to be ranked according to the criteria of global financial development from the world bank database. Due to high number of criteria that may affect the quality of the obtained ranking negatively, a solution methodology in three stages is proposed. First, as a novelty, an improved version of the weighted principal component analysis (PCA) approach is proposed to select the most important criteria from the initial set of criteria and also determine their importance weights. This approach considers both linear and nonlinear relationships of the data instead of considering just linear relationships. Then using the reduced decision matrix and the obtained importance weight values, the technique for order of preference by similarity to ideal solution multi‐criteria decision approach is used to rank the countries of case study. The computational study is done based on the proposed improved weighted PCA approach and the obtained results are analyzed and compared by those of the classical approaches, for example, some versions of the classical weighted PCA approach.

Bank Concentration and Stability in Central Asia: The Effect of Capital Regulation and Financial Freedom

In this study, the interrelation between bank concentration and stability is examined, focusing on the joint impact of capital regulation and financial openness. Using the data from the Global Financial Development Database provided by the World Bank and the Index of Financial Freedom from The Heritage Foundation and The Wall Street Journal, a sample of five countries in Central Asia was obtained, specifically during 1993-2017. The results show that the relationship between bank concentration and stability supports the concentration-stability hypothesis. Moreover, higher concentration and well-capitalized banks increase financial stability. However, the effect of bank concentration and financial freedom on stability is negative and significant. Capital regulation and supervision from authority control in the financial sector need to be strengthened to solve financial instability.

Dynamic Connectedness of Major Digital Currencies: A Time‐Varying Approach

The continuous increase in the market capitalization of digital currencies has determined them to be an essential force driving global financial development. Research on digital currency connectedness has implications for the pricing of related financial products and the development of risk hedging strategies. This study aims to analyse the changing relationship among four prominent digital currencies over time. Our research period covers normal periods, outbreaks, and the post‐epidemic phase. A refined TVP‐VAR method was adopted to conduct this study, which ensures time‐varying analysis and avoids errors caused by the rolling‐window size and the calculation of the observation loss. It is found that the total connectedness of major digital currencies is in an upward trend in the majority of the time, which, however, dropped dramatically in 2020 as the epidemic spreads internationally. It is also found that ETH is a consistent spillover transmitter and that although BTC is often shown as a transmitter, its spillover initially declines considerably and then remains weak until recently. BNB and XRP are typically spillover recipients, with BNB’s spillover varying more greatly.

The role of institutional quality in bank deposit growth In European transition economies

This study aims to investigate the influence of institutional quality on bank deposit growth besides bank-specific and macroeconomic variables in European transition economies. Generalized method of moments (GMM) is applied to analyze the panel data which is collected from the Global Financial Development and World Development Indicators of world Bank over the period 2000–2017. The results show that institutional quality strengthens the positive effect of deposit mobilization on bank deposit growth. Specifically, rule of law is found to have a positive correlation with bank deposit. In addition, macroeconomic factors including broad money supply (M2) and economic growth (rGDP) are also significant factors in bank deposit growth. However, bank-specific factors comprising bank efficiency and bank branch expansion do not influence bank deposit growth. Accordingly, the results of the study propose a core message that transition countries should recognize institutional quality indicators since these major indicators could promote and strengthen the resilience of bank funding.

Financial Intermediation and Economic Development in Nigeria from 1980-2019

The study investigates the relationships between financial intermediation and economic development in Nigeria for a period of 39years ranging from 1980-2019. The analysis utilized a secondary time series data from IMF Global financial development index and World Bank database, while the E-views 10.0 econometric analytical tools were used for analysis of data collected. The results of Augmented Dickey-Fuller (ADF) unit root test conducted uncovers that all the data were stationary at order 1(1). Again,JohanasenCo integration test for (PVR) and CUSUM test indicates 1 cointegrating equation with the maximum eigenvalue at 5% levels of significance, thus indicates the presence of short and long-run relationships among the variables used for the study, while the result of Granger Causality test further established a bidirectional causality relationship among the variables. Furthermore, the OLS test result reveals the fitness of the model in making informed decisions. The study utilized data from Global financial development index IMF database which includes financial development index (LFDI), financial institution access index (LFIAI), financial institution depth index (LFIDI), financial institution efficiency index (LFIEI), and financial institution index (LFII) to proxy financial intermediation as independent variables, while economic development is proxied with Poverty rate (PVR) as dependent variable.the study recommend that, the key players in the financial institutions frameworks should concentrate more with policies and progrmmes that will enhance more rapid actions to drive bank financial access and efficiency so as to propel rapid economic development, as one of the essential vehicles to reduce or even eliminate poverty rate in Nigeria.

The Effects of Financial Intermediation on Bank Performance in Nigeria from 1980-2019

The study empirically examines the effect of financial intermediation on bank performance in Nigeria from 1980-2018. A time series data from IMF Global financial development database and World Bank data base was used. A diagnostic analysis of test for stationarity was conducted to ensure that regression results were not spurious, using Augmented Dickey-Fuller (ADF) unit root test; the results indicate all the variables are stationary at 1(1) respectively. The ARDL result indicates that LROA has a negative and significant relationship with LROA; LFID has a positive but non-significant relationship with LROA; LFIE has a negative and significant relationship with LROA and LFII has positive and significant relationship with LROA respectively. The R 2 indicate the fitness of model and relationships with the explanatory variables. Furthermore, the result of Granger Causality test indicates that the relationship between financial intermediation and bank performance is Bidirectional. The study adopted IMF Global Financial Development index indicators on access, depth, efficiency and stability. The dependent and independent variables used for the study includes; bank performance proxy with return on asset (LROA) while, financial intermediation proxy with financial development index (LFDI), financial intuitions access index (LFIA), financial institution depth index (LFID), financial institution efficiency index (LFIE), and financial institution index (LFII). While E-views econometric statistical package 10.0 was used for the data analysis. The study recommends among others, that the key players in the financial sector should ensure those policies towards improving access to financial services and its efficiency as a major driving force and sustainable economic development propeller bearing a life wire for the survival of the banking industry; as such both the financial and regulatory authorities must provide adequate score cards on the number of bank branches and outlets either in quarterly basis or yearly for proper management as to avoid excessive use of these policies to prevent economic distortions.

Financial sector transparency and bank interest margins: do quality of political and financial regulatory institutions matter?

Purpose This study aims to examine the effect of private (PRST) and public (PUST) sector-led financial sector transparencies on bank interest margins (BIM) termed as social cost of financial intermediation in different institutional quality setups. Design/methodology/approach This study uses a two-step dynamic generalized method of moments panel data and bootstrapped quantile models with 91 economies between 2004 and 2016. Data is sourced from World Development Indicator and Global Development Finance databases. Findings The results show that under strong and weak political and financial regulatory institutional setups, the reducing effect of PRST on BIM are observed and reported while the full sample reports no significant nexus between PRST and PUST on BIM. Furthermore, under political institutional quality sample, economies with strong corruption control and regulatory quality are able to reinforce the dampening effect of PRST on BIM while under the same political institutional quality sample, economies with weak rule of law are able to heighten the reducing effect of PRST on BIM. Moreover, under financial regulator institutional quality sample, economies with strong overall weighted and unweighted, chief executive officer and policy dependent central banks are able to intensify the diminishing effect of PRST on BIM while under the same financial regulator institutional quality sample, economies with weak limits on lending are able to amplify the reducing effect of PRST on BIM. However, PUST is reported to propel lower levels BIM in the bootstrap models, especially in strong institutional economies. Practical implications These findings imply that policymakers may rely on PRST to reduce BIM, especially under financial regulatory institutional quality. Additionally, economies must be careful on their reliance on PRST because the effectiveness of PRST to tame high BIM is dependent on the strength of political and financial regulatory institutions. Originality/value To the best of the authors’ knowledge, this study presents first time international evidence on the effect of private and public sector-led financial transparency on BIM in strong and weak political and financial regulatory institution economies.

Research on Trend Forecasting System Utilizing Big Data Network and Information Technology

In this paper, we take big data, the GDP of the United States from 1992 to 2020 as the research object. Through SPSS software analysis and descriptive statistics, we can compare the GDP of Biden and Trump during their tenure. Using big data’s analytical technology, the line chart we get visually shows that the election of different candidates will shape different strategic patterns of global economic and financial development. A new comprehensive factor W is obtained from the data that directly reflect the overall GDP of the United States. Finally, by establishing a forecasting model, we can find out the comprehensive event factors that will occur due to different political positions and policy plans between Biden and Trump in the future. In the end, we use the results of big data’s analysis to show that Biden’s economic plan may increase US GDP growth by 1.2 percentage points in 2021, push GDP growth to 4.9%, and help the US economy recover the economic losses caused by the epidemic in mid-2021.

Multiple Imputation for Missing Values with an Empirical Application

Abstract Missing data are the most common problem in many research areas. For cross-section and time-series data, imputation can be a challenging problem. The most widely used method for filling missing observations is the multiple imputation which increase the number of the available data and thereby reducing biases that may occur when observations with missing values are simply deleted. The main purpose of this paper is to employ a bootstrapping expectation–maximization (EM) algorithm in order to impute missing values mainly to economic data. In the application we use a dataset that is consisted by annual panel data for the 27 countries of the European Union covering the period 2000-2017. The data were obtained from the databases of World Bank and Eurostat namely the Global Financial Development Database, The Standardized World Income Inequality Database by Solt (2019) and the World Development Indicators. Different indicators were chosen representing the development of banking system and stock markets, economic growth, economic inequality, innovation, fiscal policy, physical and human capital, and trade openness. Finally, diagnostic tools are used inspecting the imputations that are created. Keywords: Multiple imputation, Amelia II, Economic data, Financial development, Inequality.

Digital currencies: The present and the future

Subject. The article considers digital currencies in the context of global and national financial system development. Objectives. The purpose is to identify and justify the role of digital currencies in the global finance development and the place of modern central bank policies in the development of digital currencies, to underpin the need for changing approaches to digital currencies on the part of central banks, and to predict possible scenarios for the development of digital currencies on the global scale. Methods. The study applies methods of logical and statistical analysis, the comparative approach, and systematization. Results. The paper describes major pros and cons of digital currencies by comparing them with cryptocurrencies; identifies the beneficiaries of the introduction of digital currencies in countries with the most developed strategies for the introduction of national digital currencies. It also unveils barriers to a large-scale introduction of digital currencies to the world market, and highlights the main areas of their use. I developed three scenarios of digital currencies introduction to the world market. Conclusions. A large-scale introduction of digital currencies as a means of international settlements is not possible at the present stage, however, their use as a tool for dealing with financial crises is the most realistic scenario.