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This study investigates the macroeconomic and financial repercussions of a real estate bubble burst in South Korea through the application of Bayesian estimation and impulse response function analysis. By utilizing this approach tailored to the specific economic conditions of South Korea, the research effectively captures the complex ripple effects across a range of financial and macroeconomic variables. The results demonstrate that a real estate bubble burst markedly increases financial market risks, leading to heightened liquidity demands within the banking sector and necessitating adjustments in both deposit rates and bond yields. The study also emphasizes the differentiated impacts on patient and impatient households, where wealth losses drive significant shifts in consumption and labor supply behaviors, further constrained by prevailing labor market conditions. Additionally, the broader economic implications are examined, revealing the adverse effects on corporate output and investment, as well as the dynamics of international capital flows that impact foreign exchange reserves and exchange rates. These findings highlight the urgent need for proactive monitoring and policy interventions to mitigate the detrimental effects of real estate bubbles, ensuring financial stability and fostering sustainable economic growth in South Korea. [ABSTRACT FROM AUTHOR]

Tajikistan holds the eighth position globally in terms of hydropower potential, estimated at 527 terawatt-hours (TWh), with a technically exploitable capacity of 317 TWh. Only 4–6 percent of this immense potential is currently utilized. In this paper, employing a combination of the Johansen cointegration test, vector autoregression, and the Granger-causality test on annual data from 1993 to 2021, we examine the causality relationship between electricity production and key macroeconomic variables, including gross domestic product (GDP), GDP per capita, exports, imports, final consumption, capital investment, and employment, in Tajikistan. The empirical findings reveal a positive unidirectional causality from electricity production to exports and imports. A positive bidirectional or feedback causality is found between electricity production and variables such as GDP, GDP per capita, final consumption, and employment. No causality relationship between electricity production and variables such as trade openness and capital investment is observed. The exploration of complex causal relationships between electricity production and key macroeconomic variables in Tajikistan, as revealed in this study, offers a modest yet meaningful addition to academic discourse. It presents insights that may inform policymakers and stakeholders, albeit with a recognition of the limitations inherent in the findings. These insights could potentially guide the formulation of sustainable development strategies and shed light on the underutilized potential of the country's hydropower resources. [ABSTRACT FROM AUTHOR]

This study examines the link between energy (using electricity generation as a proxy) and sustainable economic growth alongside the mediating role of salient socio-political factors, such as education, life expectancy, government effectiveness, and governance structure, among others, based on data about the Nigerian economy from 1980 to 2022. We employed a battery of econometric techniques, ranging from unit root tests to autoregressive distributed lag bound tests for cointegration and a modified version of the Granger causality test proposed by Dumitrescu and Hurlin. We also employed general-to-specific estimation techniques to examine the possibility of substituting renewable and non-renewable energy sources. Our results suggest a bi-directional Granger causality between electricity generation and sustainable economic growth. This supports the validity of the feedback hypothesis, suggesting that electricity and sustainable economic growth are interdependent. Our results further revealed that socio-political factors significantly impact electricity generation. The results of our general-to-specific estimation techniques suggest that no possibility of substitution exists between the two main energy sources in Nigeria. This has some key policy implications. [ABSTRACT FROM AUTHOR]

The aim of this research is to relate clean energies, CO 2 emissions, and economic variables. Relationships can be generated that characterize countries that manage to relate the use of clean energy with GDP, economic openness, and economic growth. We employ a quantitative methodology that utilizes clustering techniques to identify distinct groups of countries based on their susceptibility to climate change impacts. Subsequently, we employ a generalized linear model approach to estimate the investment behaviors of these country groups in alternative energy sources in relation to CO 2 emissions and macroeconomic variables. The clusters reveal that the countries grouped in each cluster exhibit significantly distinct behaviors among the clusters. This differentiation is grounded in the countries under analysis, showing the evolution of the countries in terms of the use of clean energy and the emission of CO 2 in relation to macroeconomic variables. According to the conducted research, there are different groups with differentiated behavior in terms of energy consumption and CO 2 emissions, which implies the implementation of policies consistent with the development characteristics of the countries and how they cope with climate risk. Moreover, as a result of this research, a recommendation for policy makers could be that sustainable and clean development countries are based in three different sustainability dimensions: environmental, economic, and social. [ABSTRACT FROM AUTHOR]

Credit-risk models that are designed for general application across sectors may not be suitable for the construction industry, which has unique characteristics and financial risks that require specialised modelling approaches. Moreover, advanced bankruptcy-prediction models are often used to achieve the highest accuracy in large modern datasets. Therefore, the aim of this research is the creation of enterprise-bankruptcy prediction (EBP) models for Lithuanian micro and small enterprises (MiSEs) in the construction sector. This issue is analysed based on classification models and the specific types of variable used. Firstly, four types of variable are proposed. In EBP models, financial variables substantially explain an enterprise's financial statements and performance from different perspectives. Including enterprises' non-financial, construction-sector and macroeconomic variables improves the characteristics of EBP models. The inclusion of macroeconomic variables in the model has a particularly significant impact. These findings can be of great significance to investors, creditors, policymakers and practitioners in assessing financial risks and making informed decisions. The second question is related to the classification models used. To develop the EBP models, logistic regression (LR), artificial neural networks (ANNs) and multivariate adaptive regression splines (MARS) were used. In addition, this study developed two-stage hybrid models, i.e., the LR is combined with ANNs. The findings show that two-stage hybrid models do not improve bankruptcy prediction. It cannot be argued that ANN models are more accurate in predicting bankruptcy. The MARS model demonstrates the best bankruptcy prediction, i.e., this model could be a valuable tool for stakeholders to evaluate enterprises' financial risk. [ABSTRACT FROM AUTHOR]

The main objective of this study is to examine the dynamic impact of import tariff reduction on major macroeconomic variables and its long-run implications for the fiscal sustainability of Ethiopia. In addition, it estimates the increase in the average consumption tax required to compensate for the possible tax revenue loss and fiscal sustainability. A Recursive Dynamic Computable General Equilibrium Model (RDCGEM) is used to assess the dynamic impact on macroeconomic variables of import tariff reduction and examine the increased consumption tax required. The study is novel as there are no studies in general, and for Ethiopia in particular in this regard. We use the available 2013/2014 base year macroeconomic data from national income accounts, fiscal accounts, and balance of payments accounts of Ethiopia. The RDCGEM is calibrated to the base year data, checked for correctness, and tested for robustness using sensitivity analysis. The model then is simulated for the import tariff reduction under the base case and under various tariff reduction scenarios based on which the macroeconomic impacts of tariff reduction are analyzed. Based on the RDCGM outputs, the fiscal sustainability impact of import tariff reduction is verified, and using a cointegration method, we examine the sustainability of fiscal policy. The results suggest a 95 percent import tariff reduction that negatively impacts the major macroeconomic variables. It also leads to long-term fiscal unsustainability. The joint reform of the country has relatively better impacts on major macroeconomic variables but slightly negative effects on household income and consumption. [ABSTRACT FROM AUTHOR]

Purpose: This study examines the impact of macroeconomic factors on GCC banks' stability. As GCC countries still rely on oil export revenues to cover government expenses and perform an undiversified economy, hence, increased awareness of the financial diversifications in the GCC financial sectors is needed to contribute alongside oil sector revenues and then improve the non-oil sectors' investments in order to eliminate the oil and macro-financial linkage that causes any changes in the oil price to impact the whole macroeconomic and financial system of the country. In this context, this research selected the most important macroeconomic factors such as GDP growth, inflation rate, exchange rate, global financial crisis period (2008/2009), oil price fluctuation, and political instability within the period from 2005 to 2020, which covers many economic and political events. Design/methodology/approach: We used panel cointegration analysis, starting with a panel unit root test and including PFMOLS and PDOLS estimations. Additionally, FGLS estimation was used due to the existence of heteroskedasticity and auto-correlation in the sample. Findings: The findings suggest that there is an adverse relationship between the inflation rate, global financial crisis (2008/2009) and oil price changes, and the financial stability of GCC Islamic and conventional banks. However, the Islamic bank is less adversely affected by a financial crisis, oil price changes, inflation rate and political instability. Originality/value: This proposed model provided better knowledge for regulators and policymakers about the external impacts on GCC banks' stability, to commit an appropriate economic policy to help in reforming the economic and financial imbalances. [ABSTRACT FROM AUTHOR]

This paper explores the characteristics and inter-relationships of tax systems in the OECD countries over the period 2014–2020, i.e., from a relatively consolidated economic period until the end of the first year of the COVID-19 pandemic. A predictable tax system is essential for the proper functioning of the economy. One of our two main research objectives was to develop a composite indicator for taxation, consisting of tax rates and tax administration time. This composite indicator was then tested using multivariate statistical methods. Our second research objective was to explore the correlation between tax rates, tax burden indicators and macroeconomic indicators over the period 2014–2020, focusing on three years, 2014, 2019 and 2020. An important criterion for the choice of the study years was that 2014 was considered the first overall year of recovery from the crisis, 2019 the last year before the COVID-19 pandemic, and 2020 the first year affected by the pandemic. We investigated the significant differences between the composite indicator categories and the tax burden macroeconomic indicators, and examined and tested correlations between the variables under study (tax rates, tax burden and macroeconomic variables). We found that the amount of working time spent on tax administration is decreasing, presumably due to the increasingly digitalised environment, but this trend has been slightly interrupted by the pandemic. Furthermore, we found that countries with more complex tax systems with a high tax burden perform worse on certain macroeconomic indicators, mainly in southern Europe from a geographical perspective; however, these potentially more burdensome, higher-rate tax systems of more developed countries do not put these countries at a competitive disadvantage. This reflects on the fact that these countries rely on the monetarist school rather than the Keynesian school, a fact which was also compared and considered in our paper. [ABSTRACT FROM AUTHOR]

The current crisis caused by the COVID-19 pandemic has hit the global economy hard, causing significant damage to every aspect of the global banking system, and Bangladesh is no exception. For that reason, its performance and profitability have been affected. In this study, we investigate the impact of COVID-19 on the financial performance and profitability of the listed private commercial banks in Bangladesh. We initially compute each bank's financial performance index (FPI) to determine the position according to their financial performance individually before and the current period of COVID-19 by the standardized CAMELS rating system. After assessing the position, the fixed-effect regression model is used to explore the impact of the bank's specific variables and macroeconomic variables along with the banks' variables on the banks' profitability. The banks that performed better during the pre-pandemic period of COVID-19 also performed better during the pandemic period of COVID-19. The performance of AIBL, EBL, and BBL was almost autonomously higher during both periods. In the case of bank profitability, our paper discovered that during the pandemic period of COVID-19, high non-performing loan rates, holding more liquid assets, a high amount of hedging capital, and inappropriate bank size lessened the banks' profitability. In contrast, a low leverage position and inflation rate enhanced the bank's profitability during this period. The outcome of this study will help bank authorities detect the loopholes and take preventive measures that can improve their profitability during a crisis period like COVID-19. The investors and depositors who invest money in banks can precisely decide their portfolios. [ABSTRACT FROM AUTHOR]

Investor sentiment is an important aspect of behavioural finance, which provides explanation of anomalies to the asset's intrinsic values. Sentiments can easily affect individual investors. Historically, Australia is regarded as rich in resources but poor in capital, and this motivates the paper to further study and compare the effects of investor sentiment on performance returns. Aggregate and cross-sectional effects, as well as predictive regression analysis to forecast the relationships, while controlling for the macroeconomic variables, are used by employing Consumer Confidence Index (CCI) and trade volume as sentiment proxies. Contrary to some studies with aggregate stock markets, it is discovered that in the short term, investor sentiment poses a positive impact with strong predictive power on the forecast of portfolio returns but not so much in the long run, which supports the classical theories of rational investors. In both Australian and New Zealand markets, the sentiment proxies also cannot predict the returns portfolios with dividends in the long/short portfolio and book-to-market ratio long/short portfolio. [ABSTRACT FROM AUTHOR]

A trade war between the United States and China resulted in an increase in trade tariffs on imported goods entering each of these countries. Southeast Asian countries that have trade relations with the two countries, especially in terms of non-oil and gas exports of 25% to 35%, will be affected by export demand. Furthermore, the effects of the trade war will reduce gross domestic product (GDP) in Southeast Asian countries or the ASEAN and increase the current account deficit. On the other hand, the effects of the trade war that led to the decision of foreign investors to move their manufacturing base out of China will produce a flow of foreign investment that is ready to be captured by every ASEAN country. [ABSTRACT FROM AUTHOR]

Against the backdrop of concerns for diminishing the vulnerabilities of the economies of the Member States, the EU has adopted measures to strengthen budgetary discipline and control of the public deficit. In this context, the responsibility of government institutions has increased, not only in ensuring the sustainability of public finances but also in direct or indirect cooperation for good economic governance. From this perspective, this study aims to assess the impact of macroeconomic variables and those associated with supreme audit institutions on the sustainability of public finances measured by the size and dynamics of government deficit and gross public debt. Additionally, the impact of the same variables on governmental effectiveness and control of corruption has also been assessed. The data collected from secondary sources and panel data models were used to conduct an empirical study of the EU Member States which covered the 2002–2019 period and the sub-periods, divided as follows: pre-crisis, crisis, and post-crisis. The results of the study show that supreme audit institutions, through their organizational structure, the nature of their activities, and professionalism, may contribute to the reduction of public deficit and gross public debt and, implicitly, to higher efficiency and control of corruption. The results of analyses for the sub-periods show that ISAs played a more important role in reducing government deficit during crisis and post-crisis periods. By confirming or rejecting the results of the few studies that have been conducted so far, this study provides additional evidence that fills the gaps in the literature. [ABSTRACT FROM AUTHOR]

The aim of this paper was to examine the relationship between changes in the US and China macroeconomic conditions and the excess returns of nine Asian-Pacific public real estate markets (Singapore, Indonesia, Malaysia, the Philippines, Thailand, Australia, Taiwan, Hong Kong, and Japan). We found that there are insignificant correlations between macroeconomic conditions in the US and China and the real estate markets' excess returns. Additionally, whilst the US macroeconomic factors show stronger causal relationships with the real estate markets in the long run, China's macroeconomic variables have experienced a stronger causal relationship in the short run. Finally, key macroeconomic variables, such as the industrial production output index, long-term interest rates, and economic policy uncertainty, produced fluctuating impulse responses to shocks from the US and China. Overall, we conclude that the US economy continues to have a dominant influence in the Asian-Pacific real estate markets. However, during economic crises and in the short run, the impact of China's economy grows significantly and outweighs that of the US In the context that a high degree of economic and financial integration has affected the interdependent level of international financial markets, the Asian-Pacific securitized real estate markets' performances are also impacted by global shocks. [ABSTRACT FROM AUTHOR]

The accelerated development of information and communication technology (ICT) over the past two decades has encouraged an increasing number of researchers to examine and measure the impact of this technology on economic growth. Our study aims to identify and evaluate the effect of using ICT infrastructure on economic growth in European Union (EU) countries for a period of 18 years (2000–2017). Using panel-data estimation techniques, we investigate empirically how various indicators of ICT infrastructure affect economic growth, proxied in our study by GDP per capita. Within the estimates, we have included some macroeconomic control variables. Our results indicate a positive and strongly effect of using ICT infrastructure on economic growth in the EU member states, but the magnitude of the effect differs depending on the type of technology examined. Regarding the impact of macroeconomic factors, our estimates indicate that inflation rate, unemployment rate, the degree of trade openness, government expenditures, and foreign direct investments would significantly affect GDP per capita at EU level. The findings are broadly similar to the theoretical predictions, but also to the findings of some relevant empirical studies. Our research reveals that ICT infrastructure, along with other macroeconomic factors, is an important driver of economic growth in EU countries. [ABSTRACT FROM AUTHOR]

Presently, the total supply of crude oil is sufficient, but short-term supply and demand imbalances and regional imbalances still exist. The effect of crude oil supply security and price impact cannot be ignored. As the world’s largest oil importer, China is highly dependent on foreign oil. Therefore, the fluctuation of international oil prices may impact the development of China’s various industries in a significant and differential way. However, because the available data have different frequencies, much of the recent research that addresses the effect of oil prices on industry development need to replace, split, or merge the original data, resulting in loss of the information from the original data. Using the mixed data sampling model (MIDAS(m,K,h)-AR(1)) with the first-order lag autoregressive terms of the interpreted variables, this study builds a mixed data model to investigate the effect of oil price volatility on the output of China's industries. This study expands the extant research by financial market fluctuations and macroeconomic analysis, and at the same time makes short-term predictions on the output of China’s seven main industries. The analysis results show that the mixed data regression model brings the original information contained in different frequency data into the model analysis, and utilizes the latest high frequency data of the explanatory variables to perform real-time short-term prediction of low-frequency interpreted variables. This method improves the timeliness of forecasting macroeconomic indicators and the accuracy of short-term forecasts. The empirical results show that the spot price of international crude oil has a significant and differential impact on the outputs of the seven industries in China. Among them, oil price fluctuation has the greatest impact on the output of China’s financial industry. [ABSTRACT FROM AUTHOR]