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Within an effort of European Union (EU) policy to achieve carbon-neutral agriculture, the present study intends to explore the impact of carbon emissions generated by different sources related to agriculture namely energy used in farming, by enteric fermentation and by fertilizers on agricultural income in 25 countries from EU.

In order to evaluate the environmental – economic performance linkage for EU agriculture, we employ a couple of different widely used panel unit root tests explicitly Levin, Li and Chu, Im, Pesaran and Shin, ADF and PP Fisher Chi-square test cointegration test (Pedroni and Kao cointegration tests) and model estimation methodologies namely the FMOLS and DOLS and ARDL – PMG models.

All the cointegration techniques employed namely Pedroni, Kao test and Johansen Pesaran cointegration tests validate the existence of long run relationships. The most significant finding is the model estimation based on three different methodologies namely FMOLS, DOLS and ARDL/PMG models. No convergence in the results was found by different estimation models. For the short term coefficients and more specifically for the case of carbon emissions generated by energy the impact on agricultural income seems to be decreasing with a decreasing trend, a result that validates the little effort made by farmers to limit carbon emissions along with the limited efficacy of the implementing policy. The same findings are valid for the first two estimation models while for the case of the third model the reversed relationship is validated. For the carbon emissions generated by enteric fermentation, the inverted-U pattern is validated with DOLS and ARDL/PMG model while for the case of fertilizers only the third model confirms the validity of inverted-U- pattern.

Based on the obtained empirical results, a list of policy implications is unveiled with multiple impacts on the strategy and practices adopted by farmers in order for the objective of eco efficieny to be achieved.

The conducted research is focusing on the environmental – economic performance linkages for EU agriculture and examines the role of agri – environmental policy in the evolution of the particular relationship for different sources of environmental pollution in agricultural activity.

The study aims to explore the validity of the modern renewable energy-environmental Kuznets curve (REKC) while considering the relevance of financial development in the consumption of modern renewable energy in East Africa Community (EAC). Modern renewable energy in this study includes all other forms of renewable energy except traditional use of biomass. The authors controlled for the effects of urbanization, governance, foreign direct investment (FDI) and trade openness.

Panel data of the five EAC countries of Burundi, Kenya, Rwanda, Tanzania and Uganda for the period 1996–2019 were used. The analysis relied on the use of the autoregressive distributed lag–pooled mean group (ARDL-PMG) model, and the data were sourced from the World Development Indicators (WDI), World Governance Indicators (WGI) and International Energy Agency (IEA).

The REKC hypothesis is supported for modern renewable energy consumption in the EAC region. Financial development positively and significantly affects modern renewable energy consumption, whereas urbanization, FDI and trade openness reduce modern renewable energy consumption. Governance is insignificant.

The concept of the REKC, although explored in other contexts such as aggregate renewable energy and in other regions, has not been used to explain the consumption of modern renewable energy in the EAC.

The purpose of this paper is to look at the asymmetric effect of oil production on environmental degradation in OPEC member countries from 1970–2019.

The authors build a nonlinear panel ARDL–PMG model using the Shin et al. (2014) nonlinear autoregressive distributed lag (ARDL) approach in panel form to assess both the short- and long-run impact of positive and negative oil production movements on CO₂ emissions.

The result demonstrates that the variables are cointegrated. According to the linear long run coefficients, oil production, FDI inflows and economic growth both have a positive and significant relationship with CO₂ emissions, implying that they deteriorate environmental quality in OPEC countries, while renewable energy has a negative relationship with CO₂, implying that increasing renewable energy improves environmental quality. The asymmetric findings prove that positive and negative shocks of oil production exert a positive effect on carbon emissions in short run and long run.

To begin with, the empirical assessments do not include all OPEC member nations; researchers are advised to resolve this constraint by looking at the economies of other OPEC members. Albeit the lack of data for other energy sources may serve as another constraint of this research, future research is expected to broaden the current framework via other energy sources such as nuclear, electricity, biomass, solar as well as wind.

The research adds to the body of knowledge as many of the prevailing studies in the literature failed to look at the asymmetric effect of oil production on the quality of environment. This is another gap in the literature that the current study is set out to fill. This study adds oil production as an explanatory variable and helps to extend the existing literature for OPEC countries, which could propose a solution to deal with ensuing environmental issues.

Shadow banking has been evolving rapidly in China, with banks actively using wealth management products (WMPs) to evade regulatory restrictions. These products are the largest constituent of China's shadow banking sector. A large number of these products are off-balance-sheet and considered a substitute for bank deposits. China's banking sector, especially the small and medium-sized banks (SMBs), uses these products to avoid regulatory restrictions and sustainability risk in the deposit market.

This study empirically examined how banks in China, specifically SMBs, utilize these products on a short and long-run basis to manage and control their deposit levels. This study utilized a quarterly panel dataset from 2010 to 2019 for the top 30 Chinese banks, by first implementing a Panel ARDL-PMG model. For cross-sectional dependence, this study further executed a cross-sectional augmented autoregressive distributive lag model (CS-ARDL).

Under regulations avoidance theory, the findings revealed that WMPs and deposits have a stable long-run substitute relationship. Furthermore, the WMP–Deposit substitute relationship was only significant and consistent for SMBs, but not for large four banks. The findings further revealed that the WMP–Deposit substitute relationship existed, even after the removal of the deposit rate limit imposed by the People's Bank of China (PBOC) to control the deposit rates.

The individual bank-issued WMPs' amount data is not available in any database. Therefore, this study utilized the number of WMPs as a proxy for China's banking sector's exposure to the wealth management business.

This research helps policymakers to understand the Deposit–WMP relationship from the off-balance-sheet perspective. During the various stages of interest rate liberalization, banks were given more control to establish their deposit and loan interest rates. However, the deposit rates are still way below the WMP returns, making WMPs more competitive. This research suggests that policymakers should formulate a more balanced strategy regarding deposit rates and WMPs returns.

This study contributes to the existing literature on China's shadow banking by concentrating on the WMPs. This research represents one of the few studies that analyze regulatory arbitrage in terms of the WMP–Deposit relationship. Moreover, the implementation of CS-ARDL panel data models and multiple data sources makes this study's findings more reliable and significant.

This study aims to explore the impact of monetary policy on bank lending rate with the moderating effects of financial sector development for eight Asian developing economics.

This study uses panel autoregressive distributed lag/pooled mean group estimation over the period ranging from 1980 to 2020.

The empirical results exhibit an inverse link between monetary policy measured by broad money supply on the bank lending rate, indicating that the increase in the money supply by the central bank lowers the demand for loans and thereby lowers the cost of loan. Moreover, financial sector development decreases the lending rate and thus lowers cost of loan. It is also noted that the interactive term of monetary policy by lending broad money supply and financial sector development showed a positive impact on the lending rate in selected Asian developing countries during the period under the study.

The outcomes have many relevant policy implications that stronger financial development sector contributes to the efficiency of monetary policy. Regulators and policymakers are therefore recommended to pursue greater financial sector development to lower the cost for fund searchers and to lower the cost of loans, money supply increase is suggested.

This study contributes to the extant literature on the factors affecting lending rate with the prime aims of monetary policy effectiveness. This study also included financial sector development with some other variables and an interactive term of monetary policy with financial development to have new insight impact of both on the lending rate in developing Asian economies.

The search for more effective policies, choice of optimal implementation strategies for achieving defined policy targets (e.g., cost-containment, improved access, and quality healthcare outcomes), and selection among the metrics relevant for assessing health system policy change performance simultaneously pose continuing healthcare sector challenges for many countries of the world. Meanwhile, research on the core drivers of healthcare costs across the health systems of the many countries continues to gain increased momentum as these countries learn among themselves. Consequently, cross-country comparison studies largely focus their interests on the relationship among health expenditures (HCE), GDP, aging demographics, and technology. Using more recent 1980–2014 annual data panel on 34 OECD countries and the panel ARDL (Autoregressive Distributed Lag) framework, this study investigates the long- and short-run relationships among aggregate healthcare expenditure, income (GDP per capita or per capita GDP^_HCE), age dependency ratio, and “international co-operation patents” (for capturing the technology effects). Results from the panel ARDL approach and Granger causality tests suggest a long-run relationship among healthcare expenditure and the three major determinants. Findings from the Westerlund test with bootstrapping further corroborate the existence of a long-run relationship among healthcare expenditure and the three core determinants. Interestingly, GDP less health expenditure (GDP^_HCE) is the only short-run driver of HCE. The income elasticity estimates, falling in the 1.16–1.46 range, suggest that the behavior of aggregate healthcare in the 34 OECD countries tends toward those for luxury goods. Finally, through cross-country technology spillover effects, these OECD countries benefit significantly from international investments through technology cooperations resulting in jointly owned patents.

This research paper aims to handle the effects of economic growth, corruption, energy consumption as well as trade openness on CO2 emissions for a sample of West African countries during the period 1980 and 2018.

The current work uses the pooled mean group (PMG)-autoregressive distributed lag (ARDL) panel model to estimate the dynamics among the different variables used in the short and long terms.

The findings demonstrate that all variables have long-term effects. These results suggest that gross domestic product (GDP) per capita exhibits a positive and prominent effect on CO2 emissions. Corruption displays a negative and outstanding effect on long-term CO2 emissions. In contrast, energy consumption in West African countries and trade openness create environmental degradation. Contrarily to long-term results, short-term results demonstrate that economic growth, corruption and trade openness do not influence the environmental quality.

Empirical findings provide useful information to explore deeper and better the link between the used variables. They stand for a theoretical basis as well as an enlightening guideline for policymakers to set strategies founded on the analyzed links.

Mauritius’s residential real estate sector has undergone an increase in foreign investment over the past decades. This study aims to establish if the increasing level of foreign real estate investments (FREI) has increased land demand and land prices. The study also aims to depict whether the relation between FREI and land prices prevails at an aggregate and/ or a regional level.

Data from 26 regions, classified as urban, rural and coastal is collected on an annual basis over the period 2000 to 2019, and a dynamic panel regression framework, namely, an autoregressive distributed lag model, is used to take into account the dynamic nature of land price modeling.

The findings show that, at the aggregate level, in the long-term, FREI does not have a significant influence on land prices, while in the short term, a positive significant relationship is noted between the two variables. A regional breakdown of the data into urban, rural and coastal was done. In the long term, only in coastal regions, a positive significant link was observed, whereas in urban and rural regions FREI did not influence land prices. In the short term, the positive link subsists in the coastal regions, and in rural regions also land prices are positively affected by FREI.

Unlike other studies which have used quite general measures of FREI, the present research has focused on FREI mainly undertaken in the residential real estate market and how these have affected residential land prices. This study also contributes to research on the determinants of land prices which is relatively scarce compared to research on housing prices.

This paper aims to examine the effects of corruption control on domestic investment in the BRICS and CIVETS of emerging economies. This paper’s primary goal is to investigate how corruption has impacted domestic private investment in BRICS and CIVETS, empirically evaluate that impact and offer appropriate policy recommendations.

This paper uses secondary panel data from the World Bank spanning the period 2000–2020. The data covered the BRICS and CIVETS countries between 2000 and 2020. This study used gross domestic product (GDP) per capita growth, broad money as a percentage of GDP, real interest rate and corruption index as independent variables and domestic investment as a percentage of GDP as a dependent variable.

The significant results are presented using the panel, autoregressive distributed lag pooled mean group estimator. Growth in the per-capita GDP, money supply and the suppression of corruption all have long-term, positive and significant benefits on domestic investment. Comparatively, the real interest rate has a significant negative influence on investment, indicating that it may be necessary and beneficial to adopt anti-corruption measures to promote domestic investment. However, the country-specific analysis reveals that the long-term effects of corruption on investment tend to vary across countries, indicating that each country needs to research the issue of corruption independently. Finally, ensuring optimal levels of money supply and interest rates leaded by further control of corruption is necessary for strengthening the investment environment.

This study suggests several practical implications. For example, legislators and policymakers should pay more attention to anti-corruption policies. Central banks should put more effort into controlling the interest rate.

Higher economic growth accompanied by rising energy demand poses severe challenges to the long-term environmental sustainability of E7 economies, including Brazil, China, India, Indonesia, Mexico, Russia and Turkey. Thus, this paper explores the influence of foreign direct investment (FDI) inflows on energy diversification for E7 economies.

The dataset is panel data for emerging seven (E7) economies, covering the period 1992–2017. The empirical investigation relies on econometric techniques: panel cointegration test and panel autoregressive distributed lag model.

The findings reveal that energy diversification and FDI inflows are cointegrated. In the long run, higher FDI inflows encourage energy diversification, but energy efficiency improvements discourage energy diversification. In the short run, the effects of FDI inflows on energy diversification vary across E7 economies, highlighting the role of country-specific factors in determining the short-run influence of FDI inflows on energy diversification.

The findings suggested that FDI policies should encourage the adoption of nonconventional energy resources to stimulate energy diversification in E7 economies. Besides, better coordination between energy diversification and energy efficiency policies is required in the long run for a successful transition towards low-carbon economy goals.

This study is a unique empirical exercise that uncovers a cointegrating relationship between energy diversification and FDI inflows for E7 economies. Moreover, the analysis provides homogenous long-run and heterogeneous (country-specific) short-run coefficient estimates for the effect of FDI inflows on energy diversification.