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This paper aims to explore factors influencing apartment price volatility in the two biggest cities in Vietnam, Hanoi and Ho Chi Minh City.

The study uses the supply and demand approach and provides a literature review of previous studies to develop four main hypotheses using four determinants of apartment price volatility in Vietnam: gross domestic product (GDP), inflation rate, lending interest rate and construction cost. Subsequently, the Vector Error Correction Model (VECM) is used to analyze a monthly data sample of 117.

The research highlights the important role of construction costs in apartment price volatility in the two largest cities. Moreover, there are significant differences in how all four determinants affect apartment price volatility in the two cities. In addition, there is a long-run relationship between the determinants and apartment price volatility in both Hanoi and Ho Chi Minh City.

Limitations related to data transparency of the real estate industry in Vietnam lead to three main limitations of this paper, including: this paper only collects a sample of 117 valid monthly observations; apartment price volatility is calculated by changes in the apartment price index instead of apartment price standard deviation; and this paper is limited by only four determinants, those being GDP, inflation rate, lending interest rate and construction cost.

The study provides evidence of differences in how the above determinants affect apartment price volatility in Hanoi and Ho Chi Minh City, which helps investors and policymakers to make informed decisions relating to the real estate market in the two biggest cities in Vietnam.

This paper makes several recommendations to policymakers and investors in Vietnam to ensure a stable real estate market, contributing to the stability of the national economy.

This paper provides a new approach using VECM to analyze both long-run and short-run relationships between macroeconomic and sectoral independent variables and apartment price volatility in the two biggest cities in Vietnam.

The purpose of this paper is to determine the effect of the industrial sector, renewable energy consumption and nonrenewable energy consumption in Indonesia on the ecological footprint from 1990 to 2020 in the short and long term.

This paper uses vector error correction model (VECM) analysis to examine the relationship in the short and long term. In addition, the impulse response function is used to enable future forecasts up to 2060 of the ecological footprint as a measure of environmental degradation caused by changes or shocks in industrial value-added, renewable energy consumption and nonrenewable energy consumption. Furthermore, forecast error decomposition of variance (FEVD) analysis is carried out to predict the percentage contribution of each variable’s variance to changes in a specific variable. Granger causality testing is used to enhance the analysis outcomes within the framework of VECM.

Using VECM analysis, the speed of adjustment for environmental damage is quite high in the short term, at 246%. This finding suggests that when there is a short-term imbalance in industrial value-added, renewable energy consumption and nonrenewable energy consumption, the ecological footprint experiences a very rapid adjustment, at 246%, to move towards long-term balance. Then, in the long term, the ecological footprint in Indonesia is most influenced by nonrenewable energy consumption. This is also confirmed by the Granger causality test and the results of FEVD, which show that the contribution of nonrenewable energy consumption will be 10.207% in 2060 and will be the main contributor to the ecological footprint in the coming years to achieve net-zero emissions in 2060. In the long run, renewable energy consumption has a negative effect on the ecological footprint, whereas industrial value-added and nonrenewable energy consumption have a positive effect.

For the first time, value added from the industrial sector is being used alongside renewable and nonrenewable energy consumption to measure Indonesia’s ecological footprint. The primary cause of Indonesia’s alarming environmental degradation is the industrial sector, which acts as the driving force behind this issue. Consequently, this contribution is expected to inform the policy implications required to achieve zero carbon emissions by 2060, aligned with the G20 countries’ Bali agreement of 2022.

This study investigates the impact of the COVID-19 pandemic on financial stability in Vietnam, a developing country characterized by a bank-based financial system.

Using a sample of daily data from January 23, 2020 to June 30, 2022, the VECM and NARDL models are employed to study Vietnam’s financial stability in face of the COVID-19 disaster. Following the literature on COVID-19, the authors measure the impact of the pandemic by the number of daily infected cases and the national lockdown. Given the reliance of the Vietnamese government on the banking system to regulate the economy, the authors evaluate financial stability from the interbank market and stock market perspectives.

The authors find that the pandemic imposes a destructive effect on financial stability during the early time of the pandemic; however, the analysis with an extended period indicates that this effect gradually fades in the long term. In addition, from the NARDL results, the authors reveal an asymmetric relationship between the financial market and the COVID-19 pandemic in both short term and long term.

An implication drawn from this study is that unprecedented health disasters should be resolved by unprecedented stringent countermeasures when conventional methods are ineffective. Although rigorous remedies may increase short-term liabilities, their implementation quickly ceases disease diffusion and helps an economy enter the recovery stage in a timelier manner.

The study is the first to examine the impact of the COVID-19 pandemic on financial stability, via the interbank market lens, in a developing country that relies on the bank-based financial system.

This paper investigates the relationship between domestic gold prices and inflation in Vietnam based on the monthly series of the gold price index and consumer price index over the period of December 2001–July 2020.

The co-integration between the domestic gold price and inflation is examined within the autoregressive distributed lag-error correction (ARDL bounds testing) framework. This paper also applies the vector error correction model (VECM) and impulse response function analysis to explore the causal relationship between these two variables. Moreover, since both gold and inflation series are likely to have structural changes over time, a unit root test controlling for significant breaks is employed in this paper.

Findings from the ARDL bounds testing model suggest the presence of a co-integration between the underlying variables. The VECM indicates that shocks in inflation lead to a negative response to gold prices in the long run. In the short term, only fluctuations in gold prices impact inflation, and this causality is unidirectional.

Gold is regarded as a critical financial asset to preserve wealth from inflation pressure in the case of Vietnam. These findings propose implications for both investors and policymakers.

Empirical results suggest that inflation has a long-term impact on gold prices in the Vietnamese market. In the existence of a permanent inflationary shock, domestic prices of gold respond negatively to this shock; hence, gold can act as a good hedge against inflation in Vietnam.

The Russian Federation is one of the world’s largest exporters of fossil-based energy sources such as oil, natural gas and coal. Approximately 90% of the energy production in the Russian Federation consists of oil, natural gas and coal. Renewable energy (RE) in the Russian Federation mainly comprises hydroelectric energy. The purpose of this paper is to identify the factors that influenced the growth of RE resources in the Russian Federation between 1990 and 2020.

The unit root tests augmented Dickey and Fuller and Phillips and Perron, as well as Johansen cointegration and Granger causality approaches, were used. This study was conducted using vector error correction models for the years 1990–2020.

The cointegration method's findings demonstrate that while a rise in non-RE sources has a negative impact on RE development, an increase in income, energy consumption, trade openness and CO₂ emissions has a favorable impact on RE expansion. The vector error correction model Granger causality test also shows a unidirectional relationship between RE and non-RE sources, gross domestic product, energy consumption and CO₂ emissions. Trade openness, on the other hand, has no causal association with RE.

The Russian Federation must consider the practical implications of RE sources. However, there is a greater need for the Russian Federation to frame sound energy policies for RE development.

This paper aims to fill a gap in the literature on Russian RE development. Furthermore, the results of the methodological analysis can be used to guide policymakers in the field of RE development. This paper is also more policy-relevant and is quite useful in the context of sustainable energy development.

The purpose of this study is to examine the effect of Islamic banks (IBs) and macroeconomic variables on economic growth in Saudi Arabia, the United Arab Emirates, Kuwait, Malaysia, Qatar, Bahrain and Bangladesh.

Based on these criteria, 672 observations from 24 IBs in Saudi Arabia, the United Arab Emirates, Kuwait, Malaysia, Qatar, Bahrain and Bangladesh were chosen for further investigation. Time series analysis is a well-known method for determining if model variables are stationary and how long-term relationships function through cointegration analysis. This study uses impulse response function (IRF) and variance decomposition (VD) methodologies to demonstrate how each macroeconomic variable shock influences the short-term dynamic path of all system variables.

Islamic banking promotes economic growth, especially in Saudi Arabia, the UAE, Kuwait, Malaysia, Qatar, Bahrain and Bangladesh. The findings of the Islamic banking VDC test have a direct and long-term effect on economic growth.

The literature on this topic can be improved in a number of ways, including by adopting a more robust method to analyze over a longer time frame. By researching specific financing in various areas of the economy, one can gain a deeper understanding of Islamic financing. This will enable the identification of sectors that contribute to economic expansion. Future research should examine combining nations with pure Islam and dual-banking systems to acquire sufficient data.

This paper has practice and research implications. It recommends adopting the nation’s successful experiment with the Islamic banking system as a model for attaining economic growth through Islamic financing. To replicate this successful experiment, government-based decision-makers and monetary policy experts must collaborate to make Islamic money flows simple and rapid through financial channels that enhance economic growth.

The study of the contribution of Islamic banking to economic growth in developing nations, particularly those with the highest total assets (TAs) and total deposits (TDs) in the world, remains of modest value. To the best of the authors’ knowledge, this is the first study to empirically assess the impact of IBs in developing nations, particularly those with the highest TAs and TDs in the world, on economic growth as measured by gross domestic product (GDP).

The purpose of this paper is to examine the impact of trade openness on the cost of financial intermediation and bank performance. Developed and developing countries are currently pursuing trade openness to achieve higher bank performance with less intermediation costs.

In attaining the study's objectives, several regression methodologies were employed (i.e. system generalized method of moments (GMM), fixed effect, pooled ordinary least squares (OLS) and vector error correction model (VECM)). The authors tested the hypothesis on data of 885 banks from BRICS countries, which span 18 years (2000–2017).

The results from this robust study showed that embedding higher trade openness reduces financial intermediation costs and improves banks' performance. The results remain robust following the use of different estimation methods and alternative variables as proxies. In addition, results were still valid upon considering bank level, industry level and country level as control variables. It was also observed that the relation pattern holds its rigidity during “good” and “bad” times (i.e. the global financial crisis).

The results provide better references for bank regulators, academics and policymakers to take advantage of the low financial intermediation costs resulting from trade openness.

This paper aims to understand the effect of a change in Economic Policy Uncertainty (EPU) of India and the USA on investors' sentiment in the Indian context, consisting of Sensex returns and volatility index (Vix).

The authors employ bounds testing approach to cointegration to capture the short-and long-run effects of EPU on investors' sentiment, along with impulse response functions and variance decompositions to check the effect of a shock on Sensex and Vix.

The study concludes the existence of a cointegrating relationship for both models, that is, Vix and Sensex. In the long-run, changes in EPU_India affect Vix and Sensex positively and negatively, respectively. On the other hand, EPU_USA affects Vix and Sensex positively. Furthermore, Gregory and Hansen (1996) cointegration with endogenous structural break reveals a long-run cointegrating relationship for both models.

The effect of EPUs on investors' sentiment reveals that when there is an uncertain event that adversely affects the stock prices, investors should not make haste to take a decision as the impact on stock prices perturbation might be temporary. Therefore, one should persevere for the dip in prices to hit the desired target.

Various studies look at the effect of cross-country EPU on the home country, However, there is no such study in the Indian context. The present study examines the impact of India's EPU on investors' sentiments after controlling the USA's EPU, one of India's largest trading partners and a key determinant of global economic policy.

Trade of environmentally sensitive goods (ESGs) is often exposed to countries with less stringent regulations suggesting that those countries have comparative advantage in the polluting sector. The Group of Twenty (G20) members are among the highest polluters, globally. Different stringency policies are enacted time to time in G20 to control environment pollution. However, the impact of policy stringency on export performance of ESGs is seldom examined. The paper aims to address some of the issues concerning this matter.

The present study aims to address the short run and long-run association between Revealed Comparative Advantage of ESGs and Environmental Policy Stringency Index for the period of 1990–2019 in G20. Periodic fluctuations and time adjustment mechanism are also studied. Second Generation Panel Cointegration, Vector Error Correction, Impulse Response Function and Variance Decomposition methods are employed to address the objectives.

Result is evident that more exposure to stringent environmental regulations reduces the comparative advantage of ESGs in the long run. But there is no evidence of the short-run relationship between the variables. The possible reason could be that new regulations enacted prove fruitful in the long run.

The novelty of the study is to focus on inter linkages between stringency and global export competitiveness in G20, almost nonexistent in the past studies. The study also provides a road map to policymakers to find out potential ways for sustainable development by balancing environmental stringency measures and international trade.

The peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-08-2022-0560

The growth of the Indian economy is accompanied by the rising trend of energy utilisation and its devastating effect on the environment. It is vital to understand the nexus between energy utilisation, climate and environment degradation and growth to devise a constructive policy framework for achieving the goal of sustainable growth. This study aims to analyse the long- and short-run association and direction of association between energy utilisation, carbon emission and growth of the Indian economy in the presence of structural break.

The study probes the association and direction of association between variables at both aggregate (total energy utilisation, total carbon emission and gross domestic product [GDP]) and disaggregates level (coal utilisation and coal emission, oil utilisation and oil emission, natural gas utilisation and natural gas emission along with GDP) over the time period of 50 years, i.e. 1971–2020. Autoregressive distributed lag model is used to examine the association between the variables and presence of structural break is confirmed with the help of Zivot–Andrews unit root test. To check the direction of association, vector error correction model Granger causality is performed.

Aggregate carbon emissions are affected positively by aggregate energy consumption and GDP in both short and long run. Bidirectional causality exists between total emissions and GDP, whereas a unidirectional causality runs from energy consumption towards carbon emission and GDP in the long run. At disaggregate level, consumption of coal energy impacts positively, whereas GDP influences coal emission negatively in the long run only. Furthermore, consumption of oil and GDP influences oil emissions positively in the long run. Lastly, natural gas is the energy source that has the fewest emissions in both short and long run.

There is a rapidly growing body of research on the connections and cause-and-effect relationships between energy use, economic growth and carbon emissions, but it has not conclusively proved how important the presence of structural breaks or changes within the economy is in shaping the outcomes of the aforementioned variables, especially when focusing on the Indian economy. By including the impact of structural break on the association between energy use, carbon emission and growth, where energy use and carbon emission are evaluated at both aggregate and disaggregate level, the current study aims to fill this gap in Indian literature.