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China’s growing economy contributes significantly to worldwide consumption. Economic rebalancing promises opportunities for manufacturing exporters, and that can weaken commodity demand in the long term. China exerts increasing influence on emerging countries through trade, investment, and ideas. China faces several important economic issues that can hinder future development, including distortive economic policies that have evolved into an overreliance on fixed investment and exports for economic growth, government assistance for state-owned businesses, and a weak banking system. Building an information infrastructure and enhancing the technical level and application capability of big data (BD) remain under the purview of the Chinese Government. Artificial intelligence (AI)-based hybrid artificial neural network (HANN) might boost total factor productivity by a large margin, influencing many sectors in China in ways that official statistics would miss, including changes to the labor market, investment patterns, and overall productivity. Hence, BD-HANN has a coefficient of variation, quantity graph analysis, standard deviation, and entropy index, some of the most conventional quantitative research tools used to examine disparities in regional economic growth. According to the neoclassical growth model, regions with lower starting values of the capital-labor ratio anticipate higher per capita income growth rates. Thus, poor areas will grow faster than rich ones, assuming that the only difference between regional economies is the level of their initial stock of capital.

A key component for economic growth is the foreign direct investment (FDI), which drew the attention of researchers worldwide. This study aims to examine the relationship between foreign direct investment (FDI), state-owned investment (SOI), private investment (PI), import (M), export (X) and Vietnam’s economic growth (GDP) since the Renovation (1986) to now (2019). The Vector Autoregression Model (VAR) and Vector Error Correction Model (VECM) were utilized to realize the above-mentioned goals. The Johansen co-integration test confirmed that there exists a long-run relationship among the above variables. The Granger causal relationship test found one-way causal relationship from GDP to FDI and PI in the short-run. Besides, the similar causal relationship between export and GDP is confirmed. Also, the two-way causal relationship between PI and export in the short-run is also found in this study. In addition, the impact of a shock of SOI on GDP is more significant than that of an FDI or PI shocks on GDP. By contrast, the response of GDP to shocks of import and export seems are small. Finally, it is certain that FDI plays an essential role in Vietnam’s economy.

This paper investigates the threshold effects of population aging on economic growth using country-level panel data covering 98 countries from 1970 to 2015. The overall estimation results indicate significant nonlinear effects on economic growth of the share of the elderly in the total population, with the estimated threshold between 10.1% and 10.9%. Beyond the threshold, deeper population aging begins to have negative effects on economic growth. Second, most of the threshold effects comes from the group of non-OECD countries, i.e., low-income countries, while the insignificant and delayed threshold effects are found in OECD countries, i.e., high- and middle-income countries. Third, as net capital inflows grow, particularly by the debt type, they can increase long-run economic growth in OECD countries, while they overall cause to deteriorate it in non-OECD countries. And finally, for the OECD countries, the positive impacts of capital inflows on growth are partially cancelled out as heightening in degree of population aging. These findings are overall robust to alternative measure of population aging, old-age dependency ratio and alternative country groups such as using US$7,000 in GDP per capita 1990 as reference income level. These results suggest that sufficient human capital investment, adoption of high technologies, and development of economic institutions including financial and foreign exchange markets are recommended in response to upcoming negative effects of population aging on economic growth especially for low-income country.

The objective of this study is to measure the energy efficiency and energy security by using Data Envelopment Analysis (DEA) and an econometric estimation such as ordinary least square method (OLS) to measure the relationship between energy efficiency, energy security and economic development with macro-economic indicators such as energy consumption, economic growth, and environmental degradation factors by using the data from 1976 to 2016 while the energy efficiency has been measured during the period of 2010 to 2018. Results show that Brazil and Russia are countries with less energy for these consecutive years. This work contributes to the existing literature on eco-friendly and sustainable policy design in BRICS countries based on multiple indicators. The analysis also indicates that the quality of a country’s laws and regulations are essential for expanding research on renewable energy because the right policy tools serve as the basis for the transition. It is also found that Brazil, Russia, and South Africa have the best score in terms of energy and economic development while China and India are among the lowest performing countries in clean energy. Energy efficiency results show that china has the highest score of 1 while India and South Africa energy score is about 0.623 and 0.64 respectively. This serves as a panacea to study the country’s energy insecurity and bridge the gap in the literature. As the renewable energy industry is considered a high-risk area, it is necessary to develop essential aversion tools for financial policy risks to attract private capital.

This study examines the correlation between oil price fluctuation and absolute business development in Pakistan. Our study focusses on three economic sectors, agriculture and livestock, manufacturing and electricity production and transportation from 1980 to 2018 using the autoregressive distributed lag, with linear regression to evaluate the (time series or panel) data (please elaborate the frequency of data as well either it is daily, weekly, monthly, quarterly or yearly data). Our findings reveal negative impact of oil price on the economic development overall, and manufacturing, electricity production and livestock sectors individually; while, there is positive relationship observed with communication and transport sectors. There is need for policymaker’s attention on highly oil-dependent sectors to run their operations. Empirical findings suggest a 30% shortage of oil supply responsible for the highest fluctuated structure of oil pricing, which suddenly increases the projected welfare loss through a 40% reduction in gross domestic product. This study suggests that the country should maintain a minimum 100-day strategic petroleum reserves to hedge any adverse effect of oil price fluctuation on economic and social welfare losses.

This study examines the relationship between electricity consumption, trade openness and economic growth in 25 African countries during 1980–2016. It disaggregates electricity into renewable and non-renewable and disaggregates trade into exports and imports. It employs cointegration and Granger causality techniques that enable us to determine both joint and individual causality, as well as account for individual heterogeneity and cross-sectional dependence. It also uses the variance decompositions (VDs) and impulse response functions (IRFs). This study shows a short-run and long-run joint causality from electricity and trade to growth, as well as a short-run and long-run joint causality from trade and growth to electricity. Besides, the Dumitrescu–Hurlin Granger non-causality technique shows a bidirectional causality between electricity and growth and between trade and growth but a unidirectional causality from electricity to trade. It also reveals the causal relationships from exports, imports, renewable and non-renewable electricity to growth. This study implies that electricity consumption and trade openness stimulate growth, while the latter also determines electricity consumption and trade openness. Based on the findings, we recommend some policy options.

This paper uses systematic panel data methods to scrutinize the impact of China’s foreign direct investment (FDI) on economic growth in eight Association of Southeast Asian Nations (ASEAN) countries from 2004 to 2018. The findings indicate a statistically significant causal association between these countries’ economic growth and Chinese investment, which shows that China’s FDI is not a cause but rather a result of the economic expansion. Specifically, the results show that there was a causal chain running from fixed capital to Chinese FDI, through trade openness, in the relatively wealthier ASEAN countries; also, there was a causal chain running from economic growth to Chinese FDI, through trade openness, in relatively poorer ASEAN countries.

This study aims to examine the interaction among tourism revenue (TOV), the real exchange rate (REX), and economic development in Vietnam throughout 1995–2019. Using the bivariate and multivariate wavelet frameworks, we examine the lead–lag connectedness, co-movement and dynamic associations between these indicators across various time and frequency domains. By doing so, we employ wavelet transform coherence (WTC), cross-wavelet transform (XWT), partial wavelet coherence (PWC) and multiple wavelet coherence (MWC) frameworks. The findings indicate low covariance but a positive and robust nexus between tourism demand (TOV), economic growth (gross domestic product (GDP)), and the REX in the time–frequency space. In the long run, interdependence between variables is primarily negative and weak. The outcomes of PWC and MWC reveal that REX and GDP determinants affect the TOV–GDP and TOV–REX relationships under different frequencies, respectively. These results are of interest and significance to the Vietnamese government and policymakers as the outcomes have important implications for informing their decision-making.

The study examines the asymmetric influence of exports on economic growth in the Kingdom of Saudi Arabia using an augmented neoclassical production function incorporating export earnings and oil rent. It uses time-series yearly data from 1985 to 2019 published by the World Bank, employs the nonlinear autoregressive distributed lag (NARDL) approach and Toda–Yamamoto (T–Y) Granger causality test. The outcomes reveal a long-run cointegration among economic growth, exports, oil rents and other variables. Both the exports and oil rents have unveiled asymmetric impacts on economic growth. The overall impact of exports on economic growth remains robust; its positive shock maintains neutrality, while negative shock yields affirmative influence on economic growth in the long run. Similarly, the positive components of oil rents remain neutral, while the negative shocks negatively affect economic growth, with an overall adverse impact. The T–Y causality unleashes that economic growth causes exports negative shocks, and negative shocks cause positive shocks of exports and a feedback relationship between economic growth and positive shock of exports, and thus, validates the NARDL outcomes and verifies their robustness. The outcomes imply that the Kingdom should expand its exports and enhance its nonoil output through product and market diversification measures.

This paper aims to uncover the oil curse by presenting the distinctive characteristics of petrostates. Furthermore, it also clusters the countries to determine the mechanisms of oil resources by the importance of each transmission channel. Fixed and random effect models are performed, coupled with quantile regression. The results are threefold. First, oil abundance is favorable for economic growth. Second, oil dependence indirectly hinders growth by transmission mechanisms: in petrostates, the effect of indirect channel is the greatest by inhibiting human capital, the Dutch disease effect, which cripples the economic growth and by the increase in government intervention; and the institution effect turns to be positive. However, in non-petrostates, the greatest impact is experienced by different indirect channels. This study has further deepened our perception of the “oil curse” hypothesis and its transmission channels. Transmission channels determine whether natural resources are a curse or a blessing.

This paper aims to examine the relationship between tourism and economic growth in China’s eight central provinces through the annual data from 1995 to 2019 using quantile-on-quantile approaches. Results show a positive relationship between tourism and economic growth for China’s eight central provinces considered with substantial variations across provinces and quantiles within each province. The weakest relationship was noted for Shanxi, possibly because of the limited importance of the tourism sector relative to other major economic activities in this province. For Heilongjiang, Hubei, Hunan and Jilin, the most pronounced relationship between tourism activities and economic growth was observed only during the period of a deep economic upturn. The main reason for the economic downturn is that economic development during the periods of severe acute respiratory syndrome, avian influenza, Middle East respiratory syndrome coronavirus and coronavirus disease 2019 pandemics impacted tourist arrivals. Important provincial-specific policy implications may be drawn from these findings.

The main focus of this study is to determine suitable strategies for investing in natural capital to ensure steady economic growth. In this research, we categorize natural capital into three main areas: investment in energy and mineral resources development, investment in non-energy and mineral resources development and investment in the protection of natural resources. Subsequently, these three types of investment strategies are integrated into economic growth models, and we construct extended economic growth models that consider both exogenous and endogenous natural resources investment rates. Theoretical models indicate that in order to maintain stable economic growth, the growth rates of the three types of investments should be aligned. Furthermore, the optimal balanced growth rate of natural capital investment is influenced not only by the output elasticity of each input factor and the time discount rate, but also by the production efficiency of the research and development (R&D) sector, as well as the level of human capital invested in the R&D sector. These findings are in line with empirical evidence. Lastly, based on our research, we provide recommendations to maximize the overall potential of the local economy, society and environment. These recommendations aim to optimize the utilization of natural capital, leading to sustainable economic development.

In this paper, we investigate how bank branch supply affects rural income growth by analyzing a panel dataset of 1,542 counties in China between 2006 and 2019. We discover that enhancing bank branch supply fosters rural income growth through financial utilization and economic growth, and the process is also negatively moderated by rural financial utilization and economic levels. We then prove the inverted U-shaped relationship between bank branch supply and rural income growth, indicating that the marginal effect of bank branch supply increases at the earlier stage where rural bank branch supply lags behind the bank branch demand in boosting regional economic growth, and decreases at the later stage where the rural bank branch supply has exceeded the “optimal point” of bank branch supply. Further, bank branch expansion is more efficient than FinTech development in accelerating rural income growth, particularly in impoverished counties. The findings imply the necessity of enhancing bank branch supply in rural areas, especially in underdeveloped rural areas, to accelerate rural income growth.

Malaysia is approaching the aging society status, raising concern about whether population aging is a challenge or an opportunity for Malaysia to attain higher economic growth. Using state-level data from 2011 to 2021, the results show that population aging is negatively associated with economic growth. The economic impact of population aging is substantial and larger than the conventional determinant of economic growth. Further analysis reveals that the growth-deteriorating effect of population aging is transmitted through the labor force and productivity growth channels. The findings urge policymakers to recognize the scope of the new demographic reality and adjust policies to address the economic implications of population aging.

This paper studies the impact of the transfer payment policy for national key ecological functional areas (TPPNKEFA) on economic growth. As the most representative and extensive vertical ecological compensation policy in China, the TPPNKEFA plays an important role in protecting and restoring natural capital. Using the county-level TPPNKEFA data disclosed according to the application, we constructed a multi-stage DID model to identify the economic growth effect of TPPNKEFA. The results show that TPPNKEFA effectively improves the level of county economic development, which is more prominent in the counties located in the central and western regions, water conservation functional areas, low economic development level, large fiscal gap, and the counties where TPPNKEFA has been implemented for a long time. A mechanism analysis shows that industrial ecologization and ecological industrialization are important paths. The extension analysis shows that the original intention of TPPNKEFA to promote the restoration of natural capital and the improvement of people’s livelihoods has been well implemented. This study provides important evidence to support efforts to protect and restore natural capital, highlighting the need for governments to invest in natural capital and thus facilitate the transition to a low-carbon economy.

Energy subsidy reform is crucial for nations aiming to transition towards a circular economy. This study examines the relationship between energy subsidies and economic growth in Malaysia from 1978 to 2019, using Autoregressive Distributed Lag, Non-linear Autoregressive Distributed Lag and Multi Threshold Non-linear Autoregressive Distributed Lag models. The study addresses three key objectives: understanding the influence of energy subsidies on economic growth, assessing their asymmetric impact and investigating how they interact with oil prices and energy usage to affect economic growth. The findings reveal several significant relationships. First, energy subsidies exhibit a negative association with economic growth. Second, while energy consumption positively contributes to economic growth, this relationship weakens in the presence of energy subsidies. Third, oil prices have a greater positive impact on economic growth when interacting with energy subsidies. Fourth, reducing energy subsidies leads to a more substantial positive impact on economic growth compared to increasing them. Overall, the presence of energy subsidies in the economy impedes economic growth. We recommend implementing energy subsidy rationalization measures. Malaysia should also prioritize the development of a comprehensive renewable energy master plan to bolster domestic production and consumption, redirecting subsidy funds towards sustainable energy sources and fostering a circular economy.

Vocational education can be seen as an important tool in leveraging India’s demographic dividend. Given the labor surplus in terms of the young population, it is important to examine how vocational education and training can serve as a critical driver of economic growth. This study aims at examining the impact of vocational education and training on economic growth in India, using the framework of the augmented Solow growth model by decomposing human capital into vocational education, along with primary, secondary and higher education. Using an ARDL model based on the annual data from 1990 to 1991 and 2019 to 2020, the study analyzes the short-run and long-run impact of vocational education. The results indicate that in the case of India, the impact of vocational education on economic growth is both a short-run and long-run phenomenon exhibiting a stable positive relation. Other control variables used in this study, such as Investment, Population, Openness and Inflation are found with a significant impact on economic growth. The study suggests that it is necessary to upgrade vocational education programs to create high-quality workers with a view to improving productivity and macroeconomic outcomes in India.

Circular economy aims recycling in the production process instead of destroying the products. With the help of this situation, waste can be considered in the remanufacturing process so that the rate of consumption of natural resources can be decreased. It is necessary to focus on certain investment issues to achieve a circular economy, but all investments have some risks. Hence, the economies should make priority analysis to take efficient actions. Investment priorities are identified to have circular economy. A novel fuzzy decision-making model has been created for this purpose. In the first stage, balanced scorecard criteria are evaluated with the help of multi stepwise weight assessment ratio analysis (M-SWARA). Later, the multidimensional investment priorities of circular economy are ranked. In this context, elimination and choice translating reality (ELECTRE) approach is taken into consideration. The main contribution of the paper is that a new methodology is created by the name of M-SWARA. Owing to these new improvements, cause and effect relationship among the items can be analyzed. It is identified that financial issues play the most crucial role for investments to improve circular economy. On the other side, it is also concluded that remanufacturing is the most significant investment alternative to develop circular economy. For the sustainability of the investment to improve circular economy, necessary financial analysis should be performed. With the help of this situation, these substances can be reintroduced into the production process in the form of raw materials. With the increase of remanufacturing, it will be possible to reduce waste and save scarce material resources.

The rise of the digital economy has had widespread and profound impacts on the economy and society. Extensive literature exists on digital economy and carbon emissions. However, there is a lack of literature focusing on the impact of the digital economy on the relationship between economic development and carbon emissions. This paper examines whether the digital economy has changed the relationship between economic growth and carbon emissions using panel and spatial econometric modeling. Using a panel dataset of 278 prefecture-level cities in China for the period from 2011 to 2019, the results show that there is a significant inverted U-shaped relationship between economic growth and carbon emissions, which is consistent with the Environmental Kuznets Curve (EKC) model. Moreover, the digital economy brings the turning point forward. In terms of spatial decomposition effects, both direct and indirect effects of economic growth on carbon emissions are significant, suggesting that economic growth has a positive impact on carbon emissions both in local cities and in neighboring areas. Overall, these findings provide valuable policy insights for promoting the synergistic development of the digital economy and accelerating the transition to a low-carbon economy.

Investment is one of the major driving forces of economic growth. Developing countries often suffer from a deficiency of domestic investment (DI) and persuade foreign investment. India, at the time of gaining independence, was a capital-deficient poor country. Development activities of the country rely on the accumulation of foreign investment. In the post-reform period, several initiatives have been taken to attract foreign investment. After three decades of reform, a trend-diverging pattern of foreign direct investment (FDI), debt and DI is noticed. Against this backdrop, this paper explores whether investment fuels growth in India for an extended period, 1981–2019, and separately for the post-reform period, 1991–2019. It involves the autoregressive distributed lag approach to cointegration followed by its error correction representation. Results find that the FDI is detrimental to long-run growth. The external debt also retards long-run growth but has a trivial positive impact in the short run. On the other hand, a growth-augmenting impact of DI is noticed. Importantly, the impacts of foreign and DI have not changed much in the post-reform period. The results also indicate a growth-augmenting impact of human capital, with a detrimental impact of trade openness and exchange rate depreciation. In short, the study corroborates that foreign investment is not conducive to growth even in the post-reform era. Appropriate policy manifestation and an investment-friendly ambiance are critically important for growth gains from investment.