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In response to the potential green swans event in the future, China is adopting market‐oriented means to encourage green development, specifically through carbon emission trading schemes. At the same time, under the outbreak of the current global pandemic, it is equally important to consider the impact of black swan events. Therefore, this study aims to analyse the fluctuations in carbon emission trading prices under green and black swan events by utilizing daily data from seven carbon emission exchanges in China from 2017 to 2020. The analysis includes the construction of multiple regression models, PVAR models, and panel threshold models. Additionally, the study addresses the endogeneity problem by using instrumental variables. The findings of the study indicate that: (1) Rising temperatures will drive up the carbon emissions trading price, and this impact will persist over time. On the other hand, increased humidity levels and sunshine hours will reduce the carbon emissions trading price. Furthermore, there is a positive correlation between the increase in the price of primary energy and the increase in the carbon emissions trading price. (2) The spread of COVID‐19 has a restraining effect on the increase in temperature and will have a long‐term negative impact on the carbon emissions trading price. (3) The threshold effect concerning the prevalence of pandemics is recognized, which implies that the impact of the epidemic is staged and nonlinear. Overall, the results of this article highlight the importance of a reasonable response to both black swan and green swan events in order to enhance the efficiency of the current emission trading scheme. [ABSTRACT FROM AUTHOR]

This study used the panel data from 15 emerging markets to examine the impact of restrictive macroprudential policies on income inequality from 2000–2019 using Bayesian panel vector autoregression and Bayesian panel dynamics generalised method of moments models. The chosen models are suitable for addressing multiple entity dynamics, accommodating a wide range of variables, handling dense parameterisation, and optimising formativeness and heterogeneous individual-specific factors. The empirical analysis utilised various macroprudential policy proxies and income inequality measures. The results show that when the central banks tighten systems using macroprudential policy instruments to sticker debt-to-income and financial instruments for lower-income borrowers (the bottom 40% of the income distribution), they promote income inequality in these countries while reducing income inequality for high-income borrowers (the high 1 percent of the income distribution). The impact of loan-to-value ratios was found to be insignificant in these countries. Fiscal policy through government expenditure and economic development reduces income inequality, while money supply and oil-price shocks exacerbate it. The study suggests implementing a progressive debt-to-income (DTI) ratio system in emerging markets to address income inequality among lower-income borrowers. This would adjust DTI thresholds based on income brackets, allowing lenient credit access for lower-income borrowers while maintaining stricter limits for higher-income borrowers. This would improve financial stability and reduce income disparities. Additionally, targeted financial literacy programs and a petroleum-linked basic income program could be implemented to distribute oil revenue to lower-income households. A monetary supply stabilisation fund could also be established to maintain financial stability and prevent excessive inflation. [ABSTRACT FROM AUTHOR]

The paper explores the relationship between the shadow economy, corruption, and taxes in 25 high-financial developed countries (HFDCs) and 30 low-financial developed countries (LFDCs) using the PVAR method. The results of the impulse-response function show that the corruption perception index (CPI) has a positive correlation with tax revenue and the shadow economy in HFDCs, while tax revenue and the shadow economy are negatively correlated. In contrast, in LFDCs, the shadow economy has a positive correlation with tax revenue and a negative correlation with the CPI. In addition, the study also suggests that there is no relationship between tax revenue and the CPI. From the above findings, we propose several related policies for each group of countries.

This study examines the relationship between renewable and non-renewable energy consumption, economic growth, and ecological footprint for the top 14 Russian-energy-importing countries in 2000–2018. Through PVAR analysis, this study calculates the long-term correlation between variables using a VEC model. The VAR approach addresses the endogeneity issue by including endogenous interactions between the variables in the model. Additionally, the impulse response functions and the influence of various variables on certain lags are evaluated. Cointegration between variables was assessed using DOLS and FMOLS panel analysis to investigate the long-term link further. Our findings demonstrate that there is a cointegration relationship between all series. According to the impulse response analysis results, an energy shock from Russia will negatively affect the countries' economic growth and decrease the ecological footprint. Increasing renewable and non-renewable energy consumption domestically increases ecological footprint, but the effect of renewable energy consumption on ecological footprint seems to be less. According to DOLS findings, a 10 percent increase in Russian fuel exports increases the elasticity of economic growth by 0.61%. In contrast, FMOLS findings indicate that a 10% increase in Russian fuel export increases the elasticity of economic growth by 1%. However, the direction of the relationship is positive when the ecological footprint is considered the dependent variable: While the non-renewable energy consumption elasticity coefficient was 0.030 in the DOLS model, it was found to be 0.023 in the FMOLS model. The elasticity value of the economic growth variable was found to be 0.69 in the FMOLS model. [ABSTRACT FROM AUTHOR]

Sustainable development is increasingly recognized for its reliance on grassroots, bottom-up practices embedded in local communities. The economic literature has tested various influencing factors on household behaviors, such as culture or social cohesion, often considering proxies of so-called "intangible capitals" separately. This article aims to jointly consider the pivotal role of three of these potential capitals that could have a trigger effect on pro-environmental behaviors, specifically, social capital (sc), human capital (hc), and institutional quality (iq). In particular, our study, by adopting a PVAR approach, analyzes if and to what extent sc, hc, and iq influence the priority goal of increasing waste-sorting practices in the 20 Italian regions. Additionally, rooted in a robust theoretical framework, we present an in-depth analysis, with the trend of impulses from statistically significant variables—having observed the important roles played by hc, sc, and particularly iq, as well as the control variables GDP per capita and population density—in increasing the percentage of waste sorting. This impulse analysis suggests for policy interventions that there would be immediate effects (1–2 years) due to the improvement of our intangible capitals, but also a short duration. This suggests the need for lasting and structural interventions. [ABSTRACT FROM AUTHOR]

Through quantitative modeling, the study established a dynamic supply and demand system from freight demand, renewable energy production, alternative new energy, renewable energy consumption and carbon dioxide emissions to assess the impact of demand-side and supply-side changes on energy decarbonization. The results indicate that adjusting the freight volumes of railway and aviation, renewable energy electricity supply, and the use of alternative new energy sources have varying degrees of impact on decarbonization in transportation. Through interventions on the demand side of freight volumes, CO2 emissions from transportation decrease to levels below those before the intervention-induced fluctuations, while consumption of renewable energy increases to levels above those before the adjustment. [ABSTRACT FROM AUTHOR]

Eco-efficiency is a vital tool for evaluating and advancing regional sustainable development. This study presents an urban eco-efficiency (UEE) framework that deserves widespread application. By using the Super Slacks-Based Measure model, the research calculates the UEE of 284 prefecture-level cities in China from 2005 to 2022. The study employs the Standard Deviational Ellipse to illustrate the spatiotemporal pattern of UEE in China and examines its effects using non-parametric kernel density estimation, the coefficient of variation, and both global and local Moran's I. The integration of UEE with urban development patterns, which is not immediately clear, is achieved through the entropy-based TOPSIS model. Additionally, the Malmquist index, the Two-way Fixed Effects (TWFE) model, and the Panel Vector Autoregression (PVAR) model reveal the dynamic changes and interactive driving mechanisms of UEE in China. The results indicate that: (1) UEE in China displays a consistent “core-periphery” pattern, exhibiting a notable hierarchical impact from regional, scale, and administrative perspectives. The complexity of UEE's spatiotemporal variations has increased due to the impact of COVID-19. (2) The UEE of Chinese cities shows a significant ‘club’ effect, with efficiency thresholds for high-high and low-low aggregations set at 0.8. (3) Only 25% of Chinese cities have achieved optimal UEE levels. Notably, cities in the west contribute most to national UEE growth, while midland cities contribute the least. The decreasing trend in UEE growth underscores the urgent need for a shift in China's urban development model. (4) UEE in China benefits from a resilient self-reinforcing mechanism, with urban development and economic growth significantly aiding UEE growth. Despite a non-significant negative impact from government intervention, the inhibitory effect of an intensive industrial structure on UEE turns into a promotional effect, especially following COVID-19.

In recent years, China's real estate prices have continued to rise, preventing the bursting of the house price bubble, and the various risks it triggers has become an important issue that governments at all levels have to face. In this paper, the backward sup ADF (BSADF) method was used to dynamically portray the evolution of real estate price bubbles in 31 large and medium-sized cities in China over a period of 11 years, from 2013 to 2021, and the dynamic relationship between the degree of financial support for real estate (hereinafter referred to as financial support) and house price bubbles in cities was investigated by employing a panel vector autoregressive (PVAR) model with panel data. The results showed that: Multiple cyclical bubbles significantly existed in the real estate markets of the cities during the study period, and in general, house price bubbles appeared earlier in the more economically developed regions than in the less economically developed regions and have spread to the less economically developed regions. Financial support contributed to house price bubbles, supporting the theory of excessive financial support. Furthermore, the results of the sub-sample showed that financial support contributed most strongly to house price bubbles in cities in the northern region.

We study the impacts of public investment, notably in construction and in R&D on economic growth and of crowding-out effects on private investment. For this purpose, we use Panel Vector Autoregression (PVAR) models and the Generalized Method of Moments (GMM) approach for 40 advanced and emerging countries from 1995 to 2019. Our findings are as follows: i) innovations in public investment have more positive effects on GDP growth and private investment in emerging economies; ii) the positive impulse of public investment on private sector is pronounced and significant in emerging economies; iii) government construction investment has a more positive effect on economic growth in emerging economies; iv) innovations in public construction crowd-out private investment spending in advanced countries; v) emerging economies benefit from public R&D investment; vi) the public investment multiplier of the full sample is 1.67, while it is 0.87 for advanced economies and 2.29 for emerging economies. [ABSTRACT FROM AUTHOR]

This study intends to analyze the influence of environmental taxes on pollution in EU-27 nations. Furthermore, energy from renewable sources consumption and urbanization are employed to clarify CO2 emissions in this study that tests the EKC hypothesis. According to the findings, an increase in environmental taxes reduces CO2 emissions by 0.14%. Also, the data supported the validity of the EKC concept. The findings of the causality test demonstrated that there is a bidirectional causal link between CO2 emissions and environmental taxes. These results reflect that environmental tax revenues contribute to sustainability as an effective policy tool in EU countries. Policies regarding environmental tax enforcement come to the fore in terms of both keeping the balance in economic activities and serving sustainability. [ABSTRACT FROM AUTHOR]

Renewable energy is essential for boosting economic expansion and lowering carbon dioxide emission (CO2) to achieve carbon neutrality. This study's objective is to investigate the relationship between the use of renewable energy, economic growth, and CO2 for South Caucasus Countries. For analysis purposes, time series methods were applied on the panel data. Second-generation unit root and cointegration tests were used to test the cross-sectional dependence. Afterward, panel causality and panel VAR techniques were performed to examine the relationship between the variables. Based on feedback hypothesis, results of our causality analysis revealed a bidirectional causality relationship between growth and renewable energy consumption. Moreover, we revealed unidirectional causality from CO2 to renewable energy and from growth to CO2 emission. We also found that the effect of a shock in renewable energy on growth is increasing, and on CO2, it is decreasing implying that renewable energy consumption will trigger growth and have a reducing effect on CO2 emissions. We portrayed significant workable implications for policymakers, regulation bodies, companies, stakeholders, and managers. Results from this study should be extrapolated with caution since their applicability is limited to the South Caucasus Countries. In addition, the research heavily depends on summaries, which may obscure regional differences. In the future, researchers may want to dig deeper into the data and examine the subtle effect of renewable energy policy nationally. Moreover, including socio-economic aspects and technical improvements in the research might give a more thorough picture of the dynamics at play. [ABSTRACT FROM AUTHOR]

Addressing the global warming challenge, the carbon emissions reduction potential of green building (GB) is garnering increasing attention. However, the extent to which GB can impact the eco-economic efficiency (EE) of the construction industry remains unclear. To fill this gap, based on panel data for 30 regions of China from 2003 to 2018, in this study, a comprehensive analysis of the EE and sustainable impact of GB is conducted using a super slacks-based measure (SBM-DEA), panel vector autoregression (PVAR) and threshold models. The findings reflect that only about 10% of provinces have achieved EE effectiveness, with pure technical effectiveness being a significant driving force behind this. The average comprehensive, pure technical, and scale EE show a 62.23%, 46.42%, and 31.91% improvement potential regarding the efficiency frontier. The EE in the Eastern Region is relatively high, while the Western Region surpassed the Central Region in regards to EE in the areas of scale and pure technical efficiency. EE is significantly reduced in the current period (year) when it is subject to the positive impact of a standard deviation from the existing economic level. This impact was the strongest in period 1, then gradually disappeared until period 6, aligning with the Kuznets curve's theoretical assumption. GB awareness negatively impacted the current period, but is expected to gradually show a positive effect after period 2. The urbanization, green building awareness, and green building coverage make a very small contribution to the EE, accounting for 8.6%, 1.6%, and 9%, respectively, with early EE and economic level identified as the primary variables affecting the current EE. The impact of GB on EE exhibits a threshold effect, with the ecological effect of GB significant only in cities with economic levels higher than 11.063. This research contributes to the existing knowledge of the eco-economic mechanism of GB and provides insights for government policies, promoting the sustainable development of the GB market. [ABSTRACT FROM AUTHOR]

The literature has mainly focused on analyzing the relationship of remittances with economic growth and social welfare, neglecting more complex aspects where remittances can have relevant implications. To contribute to the literature, the objective of this research is to examine the dynamic relationship between remittances, capital formation, structural transformation and economic growth in 15 Latin American countries during the period 1996–2019. To meet the objective, a panel vector autoregressive regression (PVAR) model was estimated, focusing on the analysis of the impulse-response function and variance decomposition. The results show a positive effect of remittances on economic growth and capital formation and a negative effect of remittances on structural transformation for initial periods and positive for later periods, framing a non-linear relationship. In addition, it was determined that structural transformation does not have a significant impact on economic growth. Finally, it was found that capital formation has a partial positive effect on economic growth. It is concluded that public policies should generate support mechanisms for the efficient channeling of these resources so that they become engines of growth. [ABSTRACT FROM AUTHOR]

The linkage between foreign direct investment (FDI) and economic development has been demonstrated in economic literature. In this study, we analyze the impact of FDI on economic development, considering the role of institutional quality in 63 provinces/cities in Vietnam in the period 2005–2022. Applying various regression methods, such as Pooled OLS, FEM, REM, GMM, and PVAR, the results confirm that foreign direct investment and institutional quality have a positive impact on economic development. Findings also provide evidence that institutional quality is an important factor in attracting FDI, determining both the quality and quantity of inflows from other countries into Vietnam. Some policy implications are given to promote the role of institutions and attract foreign direct investment, thereby promoting the economic development of provinces and cities in Vietnam. Doi: 10.28991/ESJ-2023-07-06-05 Full Text: PDF

For over a decade, developing nations have used foreign direct investment and trade to access advanced economies’ technology and knowledge. However, the role of emigrants in promoting the productive capacity of their home countries through the diffusion of knowledge and novel technologies has been relatively overlooked. The present study investigated the relationship between emigration stock and productive knowledge embedded in their origin economy, as measured by the Economic Complexity Index (ECI). The study applied a GMM Panel Vector Autoregressive (PVAR) technique to 86 non-high-income countries between 1995 and 2020. In principle, the PVAR model findings indicated that international emigrants promoted the level of technology and knowledge in their home countries. Further causality analyses revealed that within all countries, there was unidirectional causality from emigration to the ECI. However, a bidirectional relationship existed between the two variables in countries with low education levels. Developing countries should consider the opportunities emigrants offer when planning their development strategies. [ABSTRACT FROM AUTHOR]

The literature on public social expenditure envisages a role for the composition of public social expenditure in the design of policies to reduce inequality and promote economic growth. However, there is a lack of empirical evidence on which to ground social policy decisions. This study contributes to filling this gap by investigating the dynamic interdependencies between nine different categories of social spending, inequality and growth in 36 OECD countries over the period 1995–2017. According to the results of our work, based on a PVAR model, achieving a decrease in inequality without decreasing output growth is possible, requiring a change in the composition of social policy that gives more weight to spending on old age and survivors' pensions, incapacity and family benefits, and active labour market policies, the latter having also a positive impact on growth. On the contrary, social expenditure on housing, as it has been conducted, appears to harm growth and enhance inequality. [ABSTRACT FROM AUTHOR]

The study examines the relationship between green finance development, carbon emission intensity, and economic development in China's 30 provinces. The entropy approach is used to calculate the green finance development index, and a panel vector autoregressive model is established using this index along with economic development and carbon emission intensity. The study finds that green finance can promote economic growth and help achieve emission reduction objectives, while increasing carbon emissions can also promote economic growth. The study also highlights regional differences, with the economic growth of the eastern and central regions negatively correlated with carbon emissions after surpassing the inflection point of the environmental Kuznets curve. Additionally, the study suggests that there is still room for growth in green finance in the western region. The findings have important policy implications for China in developing targeted development strategies. [ABSTRACT FROM AUTHOR]

Under the leadership of China's ''dual-carbon'' goal, clarifying the interaction between the digital economy, artificial intelligence, and the sports industry is an important guarantee to promote the structural upgrading of China's sports industry and achieve low-carbon development. Therefore, a panel vector autoregression (PVAR) model is constructed based on the panel data of 15 provinces in China from 2014 to 2020 to investigate the interaction between the three. It is found that (1) every 1-unit increase in the level of digital economy in the lagged period can cause a 0.008-unit increase in the level of AI application in the current period at the 10% significance level, i.e., the digital economy has a short-term and weakly facilitating effect on AI. (2) Every 1 unit of digital economy level in the lagging period can cause 9.539 units of value added to the sports industry at a 1% significance level. That is, the digital economy has a short-term but strong enhancing effect on the development of the sports industry. (3) Their internal driving force mainly drives the development of digital economy and artificial intelligence, and the self-contribution rate is 72.7% and 91.5% respectively. In contrast, the self-driving force of the sports industry is weaker, and the self-contribution rate is only 68.2%. (4) The contribution rate of the digital economy and artificial intelligence to the development of the sports industry is 12.3% and 19.6% respectively, i.e., the sports industry is more affected by the degree of application of artificial intelligence than the level of development of digital economy.

In the cross-cultural context, interpersonal trust and cooperative behaviors become more complex due to mutual adaptation, communication and interaction between different cultures and races. This study explores the self-perception and materialism of Chinese and Russian youth in humanistic exchanges and the impact on interpersonal trust and cooperation behavior. This paper constructs a humanistic exchange and cooperation evaluation model based on VAR. We apply the panel data clustering method based on structural relationships to model and analyze heterogeneous and cross-sectionally independent PVAR. The variable coefficient PVAR is divided into K classes according to the structural relationship aggregation to reduce the number of parameters estimated by the model. The model estimation method of PVAR based on relational clustering in the case of cross-section independence is proposed. Among the various scores of humanistic exchanges between Chinese and Russian youths, the academic self dimension score of self-perception is positively proportional to the materialistic desire dimension score of materialism, with a correlation coefficient of 0.376. From the test of the differences in interpersonal trust and cooperative behavior between Chinese and Russian youths, Chinese youths’ interpersonal trust (M=5.36) and collective behavior (M=36.18) are higher than those of Russian youths’ interpersonal trust (M=4.27) and cooperative behavior (M=33.94). The combined results show that there is still a need to improve the cross-cultural adaptation of Russian youth coming to China and to enhance cooperative behavior with others.

The goal of this research is to ascertain how much foreign debt, foreign investment, and HCI have contributed to the growth of the economies of the four ASEAN nations. This research uses the Panel Vector AutoRegression Model (PVAR). The PVAR method is a method used to analyze the relationship between several variables that change over time. This method combines two approaches, namely Vector Autoregression (VAR) and panel data. The type of data used in this research is secondary data, an annual time series with a time range from 2000 to 2020 for all cross-section variables taken from four countries in ASEAN, namely Indonesia, Thailand, Vietnam and the Philippines. The World Bank provided the data for this study. The variables examined in this study are GDP, total foreign debt, foreign debt, FDI, and HCI which are represented by education and health variables. From this study, we find that the relationship between variables varies, such as gross domestic product which has a significant negative relationship with FDI but has a significant positive relationship with debt service. In addition, there is a significant and negative relationship between GDP and total foreign debt, GDP is also negatively and significantly related to education and health variables, which means that GDP is also negatively and significantly related to HCI. It can be concluded that in the four countries we studied, an increase in debt service will increase people's consumption capacity which will lead to an increase in economic growth, but in this study total foreign debt and debt service have a negative relationship with gross domestic product. This research shows that foreign direct investment (FDI) has a significant positive relationship with the gross domestic product (GDP) of ASEAN member countries, especially Indonesia, Thailand, Vietnam and the Philippines. Therefore, it is recommended that the governments of ASEAN member countries jointly determine foreign investment policies and manage their foreign debt to increase economic growth in the Southeast Asia region. In addition, it is recommended that the governments of ASEAN member countries pay more attention to their fiscal policies, because increasing debt service costs can reduce economic growth. This can be seen when there is a surge in foreign debt which is disproportionate to the ability to pay ASEAN member countries.

This work studies the impact of Foreign Direct Investment and portfolio flows on house prices of emerging market economies using a static factors panel VARX model. The results show that an increase in both Foreign Direct Investment and portfolio flows leads to higher house prices but that portfolio flows have a more persistent effect. This work also finds that mortgage credit, as a proxy for residential investment, is an essential variable in house price dynamics because it has a higher positive impact than any of the other endogenous variables. The results are robust to different model specifications, such as adding additional lags or changing the order in which the endogenous variables enter the model. [ABSTRACT FROM AUTHOR]

The literature has mainly focused on analyzing the relationship of remittances with economic growth and social welfare, neglecting more complex aspects where remittances can have relevant implications. To contribute to the literature, the objective of this research is to examine the dynamic relationship between remittances, capital formation, structural transformation and economic growth in 15 Latin American countries during the period 1996–2019. To meet the objective, a panel vector autoregressive regression (PVAR) model was estimated, focusing on the analysis of the impulse-response function and variance decomposition. The results show a positive effect of remittances on economic growth and capital formation and a negative effect of remittances on structural transformation for initial periods and positive for later periods, framing a non-linear relationship. In addition, it was determined that structural transformation does not have a significant impact on economic growth. Finally, it was found that capital formation has a partial positive effect on economic growth. It is concluded that public policies should generate support mechanisms for the efficient channeling of these resources so that they become engines of growth.

Addressing the global warming challenge, the carbon emissions reduction potential of green building (GB) is garnering increasing attention. However, the extent to which GB can impact the eco-economic efficiency (EE) of the construction industry remains unclear. To fill this gap, based on panel data for 30 regions of China from 2003 to 2018, in this study, a comprehensive analysis of the EE and sustainable impact of GB is conducted using a super slacks-based measure (SBM-DEA), panel vector autoregression (PVAR) and threshold models. The findings reflect that only about 10% of provinces have achieved EE effectiveness, with pure technical effectiveness being a significant driving force behind this. The average comprehensive, pure technical, and scale EE show a 62.23%, 46.42%, and 31.91% improvement potential regarding the efficiency frontier. The EE in the Eastern Region is relatively high, while the Western Region surpassed the Central Region in regards to EE in the areas of scale and pure technical efficiency. EE is significantly reduced in the current period (year) when it is subject to the positive impact of a standard deviation from the existing economic level. This impact was the strongest in period 1, then gradually disappeared until period 6, aligning with the Kuznets curve’s theoretical assumption. GB awareness negatively impacted the current period, but is expected to gradually show a positive effect after period 2. The urbanization, green building awareness, and green building coverage make a very small contribution to the EE, accounting for 8.6%, 1.6%, and 9%, respectively, with early EE and economic level identified as the primary variables affecting the current EE. The impact of GB on EE exhibits a threshold effect, with the ecological effect of GB significant only in cities with economic levels higher than 11.063. This research contributes to the existing knowledge of the eco-economic mechanism of GB and provides insights for government policies, promoting the sustainable development of the GB market.

This paper is to examine the dynamic causal relationship between economic growth, renewable energy consumption, and CO2 with a broad perspective. The study is analyzed by dividing into two main parts. Growth and energy consumption in the first part, and the relationship between renewable energy and CO2 in the second part, within the framework of the basic hypotheses in the literature. On the other hand, as an observation group, the G7 economies were examined in the 1997–2019 period. According to PVAR regression estimates, if GDPPC increases by 1%, REN decreases by 0.81%, while CO2 increases by 0.71%. However, CO2 and REN do not appear to have any influence on growth. According to the causality estimates, a unidirectional causal relation from GDPPC to CO2 and REN was determined. In this case, the conservation hypothesis is valid. Considering the relation between CO2 and REN, no significant relation was found between the two variables in both regression and causality estimations. In this case, the neutrality hypothesis is valid between the two variables. It is seen that the diversity of energy sources or the investments made in them are inefficient. Our study offers a different perspective on energy resources and air pollution for the G7 economies. [ABSTRACT FROM AUTHOR]

In this article, we provide evidence of the dynamic effects of financial development on a group of key macroeconomic variables, namely, output, consumption, investment, inflation, money, the interest rate and the exchange rate. As the measure of financial development we use a new broad measure of financial development instead of the narrow measures usually employed in the related literature. Another novelty is that we estimate the dynamic effects of financial development on economic activity in the context of a panel vector autoregressive model, comprising 36 countries observed in the period 1983–2019. Our results suggest that financial development has a positive impact on output, investment, and consumption. The results reported in this article also support the proposition that the benefits from financial development are larger in economies where the financial system is market-based. These results survive a battery of robustness checks. [ABSTRACT FROM AUTHOR]

Uncertainty caused by various economic and non-economic factors has a negative impact on the macroeconomic performance. Macroeconomic instability reduces the predictability of the macroeconomic situation and leads to improper allocation of resources, reduction of investment and economic growth. One of the most important factors affecting economic stability is political violence. Political violence is the deliberate use of power to achieve political goals. The purpose of this research is to investigate the economic impact of political violence in 20 selected countries of the Middle East and North Africa during the period from 2010 to 2020 using the panel vector autoregression method. The variable of political violence is the sum of inter-state violence, inter-state war, internal violence, civil war, ethnic violence and ethnic war. Macroeconomic instability index is calculated using inflation rate, unemployment rate, real exchange rate and exchange rate. The findings show that political violence has a positive and significant effect on macroeconomic instability in selected countries of the Middle East and North Africa. Political violence directs expenses towards non-developmental use, which leads to a decrease in productivity and job opportunities. Also, in order to cover the expenses of the war, internal resources should be used, including the printing of new banknotes, increasing taxes and internal borrowing, and external sources, including borrowing from international sources. Therefore, political violence causes an increase in inflation, unemployment and debt, which indicates an unfavorable macroeconomic environment. In addition, government spending, financial development, money supply and institutional quality have a positive and significant effect, and globalization and democracy have a negative and significant effect on macroeconomic instability.

The aim of this paper is to verify the theory of the balance sheet channel among Polish listed companies, especially during the COVID-19 pandemic period. This objective was achieved by examining the relationship between cash flow and investment, based on an Emerging Markets Information Services (EMIS) database covering companies listed on the Warsaw Stock Exchange, including the bourse’s alternative NewConnect market, and using panel econometric models (pooled OLS, Fixed Effect Model, Random Effect Model and Panel VAR). It has been established that there are no grounds to reject the hypotheses that investment is positively associated with the cash flow of Polish listed companies and that the relationship between investment and cash flow is particularly strong for financially constrained companies. This means that there is evidence in support of the balance sheet channel theories. The hypothesis that the relationship between cash flow and investment is especially strong for financially constrained companies during the COVID-19‑induced recession has been rejected. The main novelty of the paper is that the balance sheet channel theory was verified for Polish listed companies, with a particular emphasis on the COVID-19 pandemic period.

: This article investigates the interaction effects among government subsidies, research and development (R&D) input and innovation performance of the Chinese energy industry. This article establishes a panel vector autoregressive (PVAR) model and uses the impulse response function (IRF) tool and variance decomposition of all variables to reveal the evolution process of variables' relationship in different time periods based on the data of 95 listed energy companies in China from 2010 to 2018. : The results show that R&D input and innovation performance promote government subsidies; government subsidies and innovation performance promote R&D input; R&D input substantially promote innovation performance; and the dynamic interaction of the three variables differs for state-owned and non-state-owned companies. : This article focuses on the Chinese energy industry and considers the ownership of companies. The PVAR model is used to establish a dynamic interactive system of variables, which considers the dynamic interaction relationship among government subsidies, R&D input and innovation performance in this specific industry. [ABSTRACT FROM AUTHOR]

Copyright of Investigación Económica is the property of Universidad Nacional Autonoma de Mexico, Facultad de Economia and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Social Inequalities & Economic Growth / Nierownosci Spoleczne a Wzrost Gospodarczy is the property of University of Rzeszow and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Sustainable development (SD) strives to protect the environment and promote an inclusive prosperity. However, achieving this partly rests on the effectiveness of financial development (FD) among other factors. On the one hand, FD fosters eco-friendly investment, financial inclusion and economic growth and thus leads to SD. On the other hand, FD may result in financial instability, social inequality and environmental degradation by fueling unsustainable economic activity and deter the achievement of SD. Given the quandary, this study attempts to investigate the causal effect of FD on SD for 143 countries during period 1990–2020, where SD is represented by adjusted net savings (ANS), and a new index, using the principal component analysis, is constructed to measure FD. Results of the panel vector autoregression method reveal that FD has a causal relationship with SD, which is unidirectional in general; however, the causality between financial market index and ANS is bidirectional. In general, the results also suggest that FD is essential for SD; nevertheless, policymakers must monitor the possible downside of FD that may undermine its contribution to sustainability. The study bears important policy implications, and as far as the knowledge goes, this is the first paper that explains the comprehensive FD–SD causality. [ABSTRACT FROM AUTHOR]

In a culture like Bangladesh where social trust is low and corporate philanthropy is rare, corporate social responsibility (CSR) engagements of the banking sector have been in a conspicuously upward trend. It begs the question of whether the galvanization of CSR expenditure is validated by financial motivations or a genuine thirst for corporate philanthropy. The literature on the relationship between CSR and corporate financial performance (CFP) is without any overarching consensus. From an emotional viewpoint, we revere corporate philanthropy without necessarily analyzing its financial merits. This study extends the contemporary CSR literature horizon by examining 30 listed banks in Bangladesh from the years 2006 through 2018, with particular emphasis on methodology that attempts to validate the CSRCFP relationship. In addition to examining the bidirectional causality between CSR and financial returns using Panel Vector Autoregression, the study examines the factor determinants of CSR. The study finds that better CFP leads to more CSR expenditure, but CSR expenditure does not necessarily influence CFP. Moreover, net income, total deposits, return on asset, and previous year's CSR have a significant positive relationship with CSR whereas firm age has a significant negative relationship. [ABSTRACT FROM AUTHOR]

In traditional working situations, it is generally accepted that working hard can result in better performance and higher income levels. However, research on whether this holds in the context of online content contribution is scant. This study examines the effect of working hard on the rate of earnings of content contributors on an online platform. The empirical results of a panel vector autoregression (PVAR) model show that longer hours of performance cannot induce more hourly monetary earnings, which suggests that working hard does not make online contributors rich. Furthermore, our investigations show that although working hard is not effective in increasing the earnings rate of individuals who have above-average earnings, it does have a positive effect on the earnings of those with below-average hourly revenue. [ABSTRACT FROM AUTHOR]

Este trabalho tem por objetivo analisar as relações entre a demanda por crédito rural, a área produzida, emprego e a rentabilidade da agricultura. Para isso, foram aplicadas duas metodologias, a primeira é o Panel Corrected Standard Errors (PCSE) e a segunda o modelo Panel Vector Autoregression (PVAR) para os municípios do Rio Grande do Sul, no período de 2013 a 2019. Os resultados apontam que o crédito rural tem baixo efeito sobre o aumento da produtividade agrícola, decorrente, em alguma medida, da subutilização dos recursos provenientes desses programas de crédito, bem como a utilização, em grande parte, para o custeio de safra; em contrapartida, verificou-se que a maior demanda por crédito resulta da expansão da área plantada. Ainda, a expansão da área cultivada reduz inicialmente a rentabilidade da agricultura, resultado que condiz com a expansão da produção ocorrer frequentemente para áreas menos produtivas.

Purpose – The purpose of the paper is to examine the differences in the impact of financial stress in advanced and emerging economies. Design/methodology/approach – The authors employ a panel vector autoregression model (PVAR) for a comparative analysis of the relationship between financial stress, economic growth and monetary stability in 14 advanced and emerging economies. A homogeneous measure of financial stress is constructed and measured as an index that provides signals of stress episodes in an economy. Findings – The impact of financial stress shocks is greater on the economic growth of advanced economies; likewise, financial stress shocks are significant only in advanced economies. The interbank interest rate is negatively affected by financial stress in emerging economies. In general, the results show a clear view of the importance of financial stability and the economic relevance of financial stress measures in the context of macro-prudential regulation. Originality/value – The results can be extended to monetary policy to implement measures that mitigate the impact of future financial crises.

This study analyses the dynamic impact of income inequality and unemployment on crime in a panel of 15 African countries during the period 1994–2019 using four models: the panel vector autoregression model, the generalized method of moments model, the fixed-effect model, and machine learning. These models were chosen due to their ability to address the dynamics of several entities. The variables employed for empirical investigation include income inequality, unemployment, and crime. Machine learning was adopted to find which socioeconomic issues contribute to crime between the two issues at hand. The results show that income inequality accounts for 64% of crime, making it the biggest contributor to crime. The findings further show that an unexpected shock in inequality and unemployment has a significant positive impact on crime in these countries. Even when pre-tax income held by the top 10% and male unemployment is adopted, the study yields similar results. Educational entertainment through secondary enrolment was found to increase crime, while it was found to decrease crime through tertiary enrolment at the tertiary level. Finally, economic development was found to decrease crime. From a policy perspective, the current study suggests to the government that some policies are more appropriate for addressing concerns about income inequality and unemployment (income policy or fiscal policy). Therefore, more policies targeting the distribution of income are crucial, as that might decrease income inequality while at the same time decreasing crime. In addition, policymakers should focus on addressing structural challenges through the implementation of sound structural reform policies that aim to attract investment consistent with job creation, human development, and growth in African economies. [ABSTRACT FROM AUTHOR]

Reducing exhaust emissions, promoting economic development, and realizing clean energy utilization have always been concerns in China. To measure the relationship between them, this study selects the data related to energy consumption, economic growth, and exhaust emissions from 2000 to 2019 in 30 Chinese provinces. By constructing a panel vector autoregressive (PVAR) model, the dynamic relationship between them in China is quantitatively analyzed. The results show that there is a long-term interaction between energy consumption, economic growth, and exhaust emissions. Among them, economic growth is highly dependent on energy consumption, but it can promote the reduction of exhaust emissions. However, energy consumption will produce a large amount of industrial waste, such as sulfur dioxide and carbon dioxide emissions. Specifically, the industrial structure and energy structure have the most obvious impact on reducing industrial sulfur dioxide emissions and carbon emissions, with the proportion between 0.071–0.090 and 0.031–0.032, respectively. Therefore, the adjustment of industrial structure and energy structure is the key to exhaust emission reduction. [ABSTRACT FROM AUTHOR]

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China is embarking on a new journey to build a comprehensive socialist modern state in the new era. Modernization of agriculture and forestry is the basis of agricultural modernization, but China's traditional agriculture and forestry industry are facing a more serious crisis of independent research and innovation. As the listed agroforestry companies are directly facing the demands of the market, it becomes essential to study the technological innovation of listed agroforestry companies. Therefore, this paper investigates the relationship between R&D innovation, corporate management, supply chain management, growth capacity, debt servicing capacity, and corporate performance of listed agroforestry companies. Based on the annual panel data of agroforestry listed companies in the CSMAR database from 2010–2021, the empirical study was conducted using panel PVAR models, OLS, 2SLS, LIML, and GMM estimation. The findings show that: (1) Granger causes affecting the supply chain management of listed companies in agroforestry are corporate management, debt servicing capacity, and growth capacity. Granger causes affecting the debt servicing capacity of listed companies in the agroforestry industry are R&D innovation, growth capacity, and corporate performance. Among them, there is a causal influence relationship between debt servicing capacity and corporate performance. (2) R&D innovation, corporate management, supply chain management, growth capacity, debt servicing capacity, and corporate performance contribute the most to its own impulse response, with an average contribution of 87.4%, 81.8%, 86.9%, 96.9%, 86.5%, and 94.7%, respectively. Compared to the other variables, the impulse response contribution of debt servicing capacity to corporate performance was the largest. (3) When supply chain management and growth capability play a fully mediating role, there is a significant positive effect of R&D innovation on corporate performance. Finally, we offer some policy recommendations and suggestions to the Chinese government, as well as some suggestions on how Chinese-listed companies in the agroforestry industry can improve their corporate performance. This paper provides a Chinese case study on the corporate performance of listed companies in the global agroforestry industry. [ABSTRACT FROM AUTHOR]

Purpose -- This study investigates the relationship between commercial and social activities in Indonesian Islamic banks. Method -- This study employed a Panel Vector Error Correction Model (PVAR) model with Impulse Response Function (I.R.F), Variance Decomposition (V.D.C), and Granger Causality. Observations were conducted from 2010 to 2020 on eight Islamic banks in Indonesia, representing 72.72 percent of the total Islamic banking population in Indonesia. The collecting of data pertains to the yearly financial report. Social activities are based on the amount of zakat fund distribution (ZKT) and benevolence fund distribution (DKB). Commercial activities are based on Islamic banking financial ratios that are proxied by Return on Assets (ROA), Financing to Deposit Ratio (FDR), and Non-Performing Financing (NPF). Result -- The results showed that social activities in Indonesian Islamic banks are influenced by their commercial activities, but it does not apply vice versa. In other words, there is a one-way relationship between commercial and social activities in Indonesian Islamic banks. Contribution -- This study contributes by studying the relationship between commercial and social activities by using the PVAR model with the analysis of Impulse Response Function (I.R.F), Variance Decomposition (V.D.C), and Granger Causality which so far have not been explored. [ABSTRACT FROM AUTHOR]

This study explores the relationship between energy usage, per capita income, and ecological footprint as an assessment for ecological deterioration in the MINT (Mexico, Indonesia, Nigeria, Turkey) countries for the 1976–2016 period. This work estimates the long-term correlation between variables using a vector error correction model through panel vector autoregression analysis. By incorporating endogenous interactions between the variables in the system, the VAR approach addresses the endogeneity problem. Also, the impulse response functions and the effects of variables on certain lags are evaluated. Then, the cointegration between variables has been estimated with dynamic and fully modified ordinary least squares panel analysis to assess the long-term relationship further. After the examinations, a satisfactory Granger causality result of the short-term variables could not be achieved. However, the same cannot be said for long-run causality. In the impulse-response functions, the interactions of the variables on each other are evaluated. Only the increase in energy consumption, whose coefficient is statistically significant and coherent, increases the flexibility of the ecological footprint. [ABSTRACT FROM AUTHOR]

This study analyzes the relationships between domestic and foreign output gaps, current-account imbalances, and real effective exchange-rate (REER) misalignments. We first set up a theoretical framework based on the elasticities and absorption approaches of the balance of payments to derive and clarify these relationships. Next, we perform panel VAR estimates in a sample of 18 advanced economies between 1986 and 2017. We find an inverse relationship between domestic output gaps and current accounts with reciprocal influences between the two variables. Moreover, we observe that increases in current accounts generally boost both temporary and structural growth. Additionally, our results indicate that REER misalignment shocks cause reactions of the opposite sign on the current account and on cyclical economic growth. We also find evidence of higher growth resulting in a real exchange-rate appreciation, which supports the Balassa–Samuelson hypothesis.

We empirically study the impact of political uncertainty on macro-financial variables (stock prices, inflation, consumption) and behavioral dynamics (consumer confidence, anxiety) in the BRICS over the period 1990–2022. To this end, we applied a panel vector autoregressive (PVAR) model that tests further endogenous interactions between the variables in the model. Accordingly, we find that political uncertainty increases inflation while reducing consumer spending and stock prices. In addition, we find that consumer confidence and investor anxiety are negatively affected by political uncertainty. Our results have different implications, especially for policymakers who have to tackle political uncertainty in order to protect householders and investors more effectively. [ABSTRACT FROM AUTHOR]

Using the panel data vector autoregression (PVAR) model, this study examines the correlation between the stock market, gold price and USD exchange rate in the context of the COVID-19 pandemic in 55 Asian and 32 European countries from 11 March 2021 to 29 October 2021. The results of Granger causality test show that in Asian countries, there is a bidirectional causality between stock market and gold price. In addition, there is a unidirectional relationship between the stock market and the USD exchange rate, while the gold price and the USD exchange rate are completely independent of each other. Meanwhile, in European countries, stock market, gold price and USD exchange rate have a causal relationship at 1% significant level. The results of the impulse-response function analysis show that, in Asia, the stock market has a negative impact on the gold price and a positive effect on the USD exchange rate. In Europe, the stock market has a negative impact on the other two markets in the short term. The variance decomposition results suggest that, in Europe, the stock market return explains 2.5% for the gold price shock and 6.2% for the USD exchange rate shock from the tenth period. Meanwhile, these figures in the Asian countries are 1.6% and 3.2%, respectively.