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Using a two-step approach GMM, this study examines the short- and long-term effects of fiscal deficit on the economic growth of 42 Sub-Saharan African nations between 2011 and 2021. The World Development Index, the most reliable source, is where the panel data is taken from. Using the Levin-Lin-Chu and Hadri LM tests for unit root, it was determined that there is no risk of a random walk in the data. The study's findings indicate that while the fiscal deficit has short-term, positive, and significant benefits on the economic growth of SSA countries, it has long-term, negative repercussions. According to the system GMM's results, an increase in the fiscal deficit of SSA countries is linked to a short-term increase in economic growth of 0.036 percent, while an increase in the fiscal deficit of one percentage point is linked to a long-term decline in economic growth of SSA countries of 0.013 percent, holding all other factors constant. The study's findings also showed that the budget deficit has a larger positive short-run coefficient than a negative long-run coefficient. The study also revealed that while real effective exchange rates and inflation short-term hinder economic growth, gross fixed capital creation and real interest rates are the primary drivers of economic expansion. Long-term economic growth in the SSA countries is also found to be positively and significantly impacted by gross fixed capital formation. According to the study, SSA nations should manage their fiscal deficits and, in the long run, provide more funds for gross fixed capital development. [ABSTRACT FROM AUTHOR]

We model permanent and transitory changes of the predictive density of U.S. GDP growth. A substantial increase in downside risk to U.S. economic growth emerges over the last 30 years, associated with the long-run growth slowdown started in the early 2000s. Conditional skewness moves procyclically, implying negatively skewed predictive densities ahead and during recessions, often anticipated by deteriorating financial conditions. Conversely, positively skewed distributions characterize expansions. The modeling framework ensures robustness to tail events, allows for both dense or sparse predictor designs, and delivers competitive out-of-sample (point, density and tail) forecasts, improving upon standard benchmarks. [ABSTRACT FROM AUTHOR]

This study develops a new approach that shrinks the forecast combination weights towards equal weights by using weighted least squares and towards zero weight by using regularization constraints. We reveal the significant predictability of excess returns to the S&P500 index that can be achieved by using this double shrinkage combination (DSC). Furthermore, our DSC approach significantly outperforms the naïve equal‐weighted combination, solving the combination puzzle. The equal‐weight shrinkage has greater effect in economic recessions, whereas the zero‐weight shrinkage dominates in economic expansions. The DSC's superior performance over that of the naïve combination is observed in the application of forecasting macroeconomic indicators. [ABSTRACT FROM AUTHOR]

The rapid economic development leads to excessive consumption of fossil energy, resulting in a large number of carbon emissions, which makes the sustainable development of China's economy and society face great challenges. Under the background of global warming and environmental deterioration, developing low-carbon economy has become an inevitable choice for China to change its development model and improve its international competitiveness. Technological progress is the first driving force to promote economic growth. However, the influence degree and mechanism of technological progress on the development of low-carbon economy are still unclear. Based on this, the paper proposes the concept of low-carbon GDP, which is used to measure the low-carbon economic development of 30 Chinese provinces. Then, the panel fixed effect model is used to study the effect degree and mechanism of technological progress on low-carbon GDP and the moderating effect of other factors on the relationship between them. The results show that, first, economically developed provinces and regions have higher per capita low-carbon GDP and low-carbon GDP index, but the speed and quality of low-carbon economic development are not necessarily higher. Second, technological progress can promote the growth of low-carbon GDP and make greater contributions to resources-poor regions. Third, improving local education can make technological progress more effective in low-carbon economic development. China needs to upgrade technological development by developing new and high-tech technologies, promoting new urbanization and strengthening education in order to promote low-carbon economic development. [ABSTRACT FROM AUTHOR]

The aim of this paper is to examine the impact of a country's entry into the monetary union on its economic variables growth rate of real GDP as well as on GDP per capita growth for the period from 2010 to 2020. The clustering method and the ANFIS method were used in the data analysis. A total of two cluster analyses were performed. The first cluster includes countries that joined the EU in 2004 and became EZ members by 2010. The second cluster refers to those countries that joined the EU in 2004 but are not yet members of the EZ. For the first individual cluster analysis two models were analysed and for the second individual cluster three models were analysed using the ANFIS method. As expected, the results showed that GDP growth is connected with trade, inflation and gross investments in fixed capital in the observed countries, while GDP per capita is connected with unemployment, interest rates and public debt. With regard to GDP growth, the difference between countries that are in the eurozone and those that are not is not significant, which is in line with other studies. [ABSTRACT FROM AUTHOR]

This paper investigates the link between value chain importance and economic growth for the EU24 regions between 2008 and 2018. It finds that relying more on GVCs worsened regional growth during the financial crisis, but led to higher growth in the long run. The results contribute to the literature on regional resilience and the public debate on the impact of shocks and the desirability of GVCs. Furthermore, by separately analyzing the importance of global and regional value chains it contributes to the discussion on the effect of regionalization and provides insights on how the re-configuring of value chains may affect regional growth. [ABSTRACT FROM AUTHOR]

This study offers a comprehensive examination of economic growth and convergence in the Indian States and Union Territories (U.T.) over the period from 1991 to 2020. It investigates absolute, sigma, and conditional convergence within this diverse set of states and utilizes the augmented Solow and extended Solow models to explore conditional convergence dynamics. The empirical findings reveal several significant insights. First, there is no substantial negative correlation between the initial per capita GDP ratio and the average annual growth rate, indicating the absence of absolute convergence across the Indian States and U.T. economies during the study period. These results align with those obtained from sigma convergence analysis, reinforcing the absence of widespread convergence. However, conditional convergence is observed, as evidenced by the rate of conditional convergence (coefficient of initial GDP per capita) estimated at 0.038 among the Indian States and U.T. The presence of conditional convergence implies that while initial conditions matter, other factors, including physical and human capital, population growth, and additional variables, significantly contribute to the growth and convergence of Indian regions. The study concludes that policies aimed at promoting economic growth in the Indian States should prioritize the expansion of the labor force, investments in physical and human capital, and prudent government consumption. Furthermore, fostering an environment that encourages access to new technologies and ideas, maintaining sound macroeconomic management, and increasing investments in human capital formation are essential for sustained growth. Effective resource allocation through prudent budgetary policies and heightened investments in the health sector are recommended. Incentives to reduce fertility rates and adept monetary policy management are also identified as crucial elements for ensuring stability and sustainable growth. In summary, this research underscores the importance of adopting a holistic approach to foster economic growth and convergence in the Indian States. The suggested policy measures create a conducive environment for sustained development and prosperity in this diverse and dynamic region. [ABSTRACT FROM AUTHOR]

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Contemporary development policy concentrates predominantly on reducing noticeable economic differences in a spatial system, and an important role in this respect is played by EU Cohesion Policy. Owing to the considerable scale of financial exposure of Cohesion Policy, the assessment of effectiveness of the implemented measures and their greater reliance on evidence are of major significance. Despite numerous attempts to empirically verify the effects of EU funds spending, the problem remains unresolved, and the results of recent studies lead frequently to ambiguous conclusions. The article aims to verify the β-convergence process in EU regions in the years 2007–2015 allowing for the impact of the received EU funds and the spatial effects determining economic growth. In the research, use was made of a convergence approach consisting in the regression modelling of per capita GDP growth. Spatial econometrics methods were applied, by adding variables determining spatial interactions that can influence the economic growth rate to the specification of the estimated models. The estimated econometric models show that in the years 2007–2015 EU funds positively affected economic growth. At the same time, the process of reducing economic disparities between EU regions was observed. Moreover, the existence of spatial effects for a dependent variable was confirmed. The results also show that the value of the EU funds received in the surrounding area generally did not translate into the dynamics of growth in a given location. The research presented is one of the few in which spatial interaction was verified by using weights matrices based on contiguity, distance, flows and affiliation. [ABSTRACT FROM AUTHOR]

The tax system serves as a crucial tool for achieving fiscal policy objectives efficiently, with minimal impact on the economy's functioning. Its primary role extends beyond merely funding government expenditures to include income redistribution and economic stabilization, fostering an environment conducive to sustained economic growth. The progress of nations on economic, social, political, and cultural fronts hinges significantly on governments' adeptness in revenue collection and maintaining fiscal system stability. This research delves into the intricate interplay between fiscal and social policies and their influence on the economies of emerging and developed nations within the Central and Eastern European Union member states during the period 2005-2020. Employing the autoregressive regression model (VAR), the study aims to unearth the impulse-response functions triggered by fiscal variables on the gross domestic product (GDP). By scrutinizing historical data, the research endeavors to offer forecasts concerning the economy's responses to shocks induced by both direct and indirect taxes, as well as social security contributions. The findings reveal nuanced insights. Indirect taxes exhibit minimal and statistically insignificant impact on the GDP. Conversely, direct taxes and mandatory social contributions demonstrate a substantial and adverse effect on the gross domestic product, signaling a noteworthy impact on the overall economy. This research contributes valuable perspectives on the intricate dynamics between fiscal policies and economic outcomes, shedding light on the need for strategic and calibrated approaches to taxation for sustained economic development and social welfare in the Central and Eastern European Union member states. [ABSTRACT FROM AUTHOR]

This article provides an overview of the economic relationship between Japan and India, with a focus on India's growing economy and its potential for further growth. India has experienced significant economic growth and is expected to become the world's third-largest economy in the near future. The article highlights India's efforts to boost its manufacturing sector through initiatives like "Make in India 2.0" and the Production Linked Incentive (PLI) scheme. It also discusses the rapid growth of India's electronics industry, particularly in mobile phone production, and its efforts to develop the semiconductor industry. The article acknowledges the geopolitical risks and challenges that India faces in its economic growth. It further explores the strengthening relationship between Japan and India, particularly in the areas of national security, economy, and infrastructure development. Specific initiatives include collaboration in building resilient semiconductor supply chains, investment by Japanese companies in India's manufacturing sector, and Japan's contribution to India's infrastructure development through official development assistance. The article emphasizes the potential for further expansion of the bilateral relationship and the importance of fostering mutual understanding through people-to-people exchanges. [Extracted from the article]

This paper investigates the impact of the main criterion employed by the European Commission for the allocation of the largest portion of Structural Funds, based on the threshold of the 75% of European Union (EU) average gross domestic product (GDP) per capita. We focus on the 2014–2020 programming period and on EU‐15 regions to analyze if this criterion has penalized some of them, as a consequence of the 2004 EU enlargement, which has represented an exogenous shock in the allocation process, due to the economic backwardness of new member states. Through the application of Synthetic Control Methods and Difference‐in‐Differences estimators at different geographical scales, we show that regions that did not obtain the less developed status in both the programming period 2007–2013 and 2014–2020, but that would have obtained it in the period 2014–2020 without the 2004 EU enlargement, experienced a significantly lower GDP per capita growth between −10.5% and −5.7%. Conversely, territories that in the period 2014–2020 lost the less developed status, previously obtained in the time frame 2007–2013, were not characterized by a significantly lower economic growth, providing some evidence of the effectiveness of the safety net. [ABSTRACT FROM AUTHOR]

Every decision depends on a forecast of its consequences. We examine the calibration of the single longest and most complete forecasting project. The Survey of Professional Forecasters has, since 1968, collected predictions of key economic indicators such as unemployment, inflation, and economic growth. Here, we test the accuracy of those forecasts (n = 16,559) and measure the degree to which they fall victim to overconfidence, both overoptimism and overprecision. We find forecasts are overly precise; forecasters report 53% confidence in the accuracy of their forecasts, but are correct only 23% of the time. By contrast, forecasts show little evidence of optimistic bias. These results have important implications for how organizations ought to make use of forecasts. Moreover, we employ novel methodology in analyzing archival data: we split our dataset into exploration and validation halves. We submitted results from the exploration half to Collabra:Psychology. Following editorial input, we updated our analysis plan for the validation dataset, preregistering only analyses that were consistent across different economic indicators and analytic specifications. This manuscript presents results from the full dataset, prioritizing results that were consistent in both halves of the data. [ABSTRACT FROM AUTHOR]

The article focuses on various aspects of banking, financial markets, and regulatory practices. It covers topics such as the origins of financial crises, the evolution of banking systems, the role of stablecoin banking, the impact of negative interest rates, the importance of market-based information in regulation, and the value of soft supervisory information.

The study examines the link between fiscal expenditure and green economic development in heavily polluting Asian nations. The conventional wisdom that environmental sustainability and economic progress are incompatible is contested in this research. The study found a strong positive link between green fiscal policy and long-term economic development, offering empirical support for using fiscal policy to promote green growth. With an emphasis on high-pollution sectors like manufacturing and energy, the study used sophisticated econometric approaches, such as panel data regression and Granger causality tests, to evaluate the data from a few Asian nations. The findings supported the idea that increased government investment in environmental protection programs and eco-friendly technology positively impacted green economic development. The results also highlight how governmental actions influence economic trajectories and aid in the shift to a sustainable economy. The report emphasizes the need for cross-level and cross-sector policy coordination, arguing that achieving significant green economic development with comprehensive, well-integrated green fiscal policies would be more straightforward. The study also highlights the need for international collaboration and assistance while acknowledging possible restrictions on fiscal expenditure in emerging nations. Policymakers, environmental economists, and other stakeholders who want to transition to a green economy while pursuing economic growth and development should take these conclusions seriously. The linkages among fiscal investment and green economic development in heavily polluting Asian nations are substantially established in this work, but it also highlights the need for additional study. Future research could benefit from examining these patterns in a broader range of situations and over extended periods, given the intricate interaction of variables driving fiscal policy and green growth. [ABSTRACT FROM AUTHOR]

This article assesses specific components of the agricultural sector as it impacts the growth of a developing nation's economy. A mathematical model is developed with the aid of logistic growth model for the variables and the resulting model is solved numerically using a higher derivative block method to forecast the data for the agricultural components for years 2020-2025, thus utilizing data ranging from 1981-2025. Econometric analysis was carried out using ARDL bound test method and the findings indicate the existence of short and long run relationship between food production, livestock, and economic growth. In addition, the Pairwise Granger causality showed the causality movement and ascertain the positive link among the variables. Therefore, this research suggests the need to encourage food production and livestock as components of agriculture through precise economic policies and funding for progress in the country's economic outlook. [ABSTRACT FROM AUTHOR]

Foreign exchange rates as well as information and communication technology (ICT) are crucial in the global economy. Exchange rates affect trade balance, which influences gross domestic product (GDP) and economic growth. ICT also affects economic growth by reducing business transaction costs and increasing the income of investors and companies, stimulating national income and economic growth. This research examines the effect of exchange rate asymmetry and ICT on Indonesian economic growth, using annual time-series data on exchange rates, ICT usage (proxied by Internet, telephone, and mobile phone users), and economic growth (GDP from 1994 to 2018). The data were analyzed using a non-linear auto-regressive distributed lag model. The results show that the exchange rate exerts an asymmetric effect on long-term economic growth. ICT has short- and long-term positive effects on economic growth. According to the findings, the Indonesian government should stabilize the IDR/USD exchange rate through monetary policies to encourage economic growth. Monetary policy needs also to support IDR/USD exchange rate appreciation to enhance the trade balance, GDP, and economic growth. The economic growth of Indonesia, which is driven by ICT development, still needs to be sustained by the government initiating ICT development in cities and rural areas. [ABSTRACT FROM AUTHOR]

This article calculates the indices for high-quality economic development and water resource systems across 25 cities in the Yangtze River Delta from 2011 to 2021. Utilizing a multifaceted analytical framework comprising the CRITIC method, standard deviation ellipse, harmonious development coefficient, and coupling coordination coefficient, we investigate spatiotemporal evolutionary trends and overarching harmonious development states between the two systems. Results indicate: (1) Throughout the research period, mean values of high-quality economic development indices fluctuated within the range of 0.05 to 0.68, while water resource carrying capacity indices oscillated between 0.18 and 0.81. (2) The epicenter of high-quality economic development indices is situated in the periphery of Lake Tai, whereas the fulcrum of the water resource system indices is located in Huzhou City, both displaying a northwest-southeast orientation. (3) Coupling coordination development exhibits a propitious advancement trajectory, with certain locales attaining exemplary coordinated growth. [ABSTRACT FROM AUTHOR]

In order to improve the economic growth efficiency of industrial and commercial enterprises in coastal cities and realize the GDP growth of coastal cities, this paper studies the economic growth factors of industrial and commercial enterprises in coastal cities based on the unexpected super efficiency model. Based on the research and analysis of the previous economic growth theories, this paper finds out the main factors that affect the economic growth of industrial and commercial enterprises in coastal cities, and uses the advanced econometric method to establish the relevant test model to analyze the correlation between the time series of economic growth factors and the time series of coastal cities, so as to realize the economic growth factors of industrial and commercial enterprises in coastal cities Element study. The empirical results show that the main factors affecting the economic growth of industrial and commercial enterprises in coastal cities are capital and labor force, with labor force as the main body; Technical and institutional factors also contribute to the GDP of industrial and commercial enterprises in coastal cities, but the impact is not significant and needs further improvement. In general, these factors can promote the economic growth of industrial and commercial enterprises in coastal cities. The time series and time series of each factor variable are first-order non-stationary series with long-term cointegration relationship. [ABSTRACT FROM AUTHOR]

Global economies are facing geopolitical and ongoing economic impacts from the COVID-19 pandemic, which brings back the topic of growth determinants. This study focuses on the United States, the world's largest economy and a significant recipient of foreign direct investment (FDI). For this reason, we analysed whether there is a positive correlation between the volume of FDI inflows and the growth of gross domestic product (GDP). A multiple linear regression (MLR) model was used to examine the effects of various exogenous control variables on the quarterly GDP growth in the USA from 1999 to 2022. During these 96 quarters, FDI was found to have a positive effect on GDP growth at statistical significance of 5% (p < 0.05). Specifically, a one-million increase in FDI ceteris paribus caused an estimated GDP growth of approximately 743.43 dollars. The results ultimately propose positive implications for less developed countries that could utilize emphasising their FDI management policies to achieve higher economic growth. [ABSTRACT FROM AUTHOR]

Major international institutions like the World Bank, African Union, and International Monetary Fund have made the development of robust governance systems a “sacred utterance” since the 1990s. Our study aimed to refute this common thinking by examining how governance structures have affected the expansion of the financial market in 47 African countries from 2008 to 2019. Using the availability of venture capital as a proxy for financial market development, our article departed from existing literature which used stock exchange characteristics as benchmarks for growth in the financial market. The governance variables comprise the six global governance indices: control of corruption, government effectiveness, political stability, regulatory quality, the rule of law, and voice and accountability. The model’s control variables include GDP per capita, inflation, and trade openness. Our finding suggests that a great quality governance climate is significant in explaining the growth of the financial market in Africa using the generalized method of moments (GMM) methodological approach with corrected standard errors. Considering these findings, our research makes the case that solid institutional frameworks might encourage the degree of financial systems growth in Africa. Therefore, the financial development rate in the African region will be significantly influenced by improving the quality of governance through strengthening legal and institutional frameworks to facilitate financial inclusion. [ABSTRACT FROM AUTHOR]

This article explores strategies for promoting sustainable economic growth in Asia amidst global disruptions. It addresses challenges such as the Covid pandemic, rising fuel and food prices, and the struggles of the Chinese economy. The article focuses on three main topics: Japan's role in the disrupted world, the decline of Chinese economic growth, and building resilience in global supply chains. Distinguished Japanese economists provide insights on these issues, emphasizing the importance of education, addressing geopolitical risks, and upgrading international trade rules. The article also discusses the shift from free trade to protectionism in the 20th century and the need for a rules-based system to ensure stable growth. It highlights the potential for India's economic growth through pent-up demand, demographic factors, economic reforms, and digitalization. The article debates whether China will achieve global hegemony or if joint hegemony with the US and its allies will be established. It points out the risks faced by the Chinese economy, such as policy uncertainty, real estate depression, and geopolitical risks. The article also mentions the potential bubble in China's real estate market and the growth potential of India through digitalization and skilled human resources. It discusses the importance of ASEAN and India as venues for Japanese companies' foreign direct investment (FDI), with expectations about China decreasing. ASEAN and India are seen as attractive due to their market growth potential and efforts in digitalization. However, India's involvement in supply chains is limited due to protectionist policies. The article suggests that Japan should provide technological support and [Extracted from the article]

Temperature-economic growth relationships are computed to quantify the impact of climate change on the economy. However, model performance and differences of predictions among research complicate the use of climate econometric estimation. Machine learning methods provide an alternative that might improve the predictive effects. However, time series and extrapolation issues constrain methods such as random forests. We apply a simple thought experiment with national marginal GDP growth by aggregating subnational climate impact to alleviate the shortcomings in random forests. This paper uses random forests, multivariate cubic regression, and linear spline regression to examine the direct impacts of temperature on economic development and conducts a performance comparison of the methods. The model results indicate an optimal temperature of 15°C, 15°C or 21°C for each model. Furthermore, a thought experiment indicates that the marginal predictions of national GDP changes by approximately 1%, −3%, or −6% for models with 1°C warming. The performance comparison suggests that random forests have stable model performance and better prediction performance in bootstrapping. However, the extrapolation problem in random forests causes underestimation of climate impact in 5% of cells under 6°C warming. Overall, our results suggest that temperature should be considered in economic projections under climate change scenarios. We also suggest the use of more machine learning methods in climate impact assessment. [ABSTRACT FROM AUTHOR]

Corruption aggravates societal inequality and challenges organizations and governments. Although numerous studies confirm that economic growth inhibits corruption, corruption in China rises rather than falls with economic growth. No study found to date has focused on the psychological mechanisms underlying economic influence on corruption. Based on the stimuli-organism-response (SOR) framework and moral foundations theory (MTF), we collected social media big data from 30 provinces in mainland China (involving 1.16 million active users) from 2011 to 2016 to investigate the relationship between economic growth, moral foundations and the incidence of corruption. The results show that: (1) economic growth positively predicts corruption in China; (2) binding foundations rather than individualizing foundations can predict corruption; (3) Loyalty and Authority positively mediate the prediction of economic growth for corruption and (4) Sanctity negatively mediates the prediction of economic growth for corruption. The results confirm the mediating role of moral foundations between economic growth and corruption while providing insights to prevent corruption from a psychological perspective. [ABSTRACT FROM AUTHOR]

Purpose: Financial market holds superior information that can give insights into the future trajectory of economic growth. Further, identifying sectors that hold the key to future economic growth is important for all economies, but particularly relevant to emerging markets. However, unlike existing studies, the paper provides new insights into the forward-oriented nexus between financial markets and economic growth. Design/methodology/approach: This paper takes a forward-looking approach of using financial market information to predict future economic growth. The authors use ARDL modeling approach to predict economic growth using the information from stock market sectoral returns. Findings: The authors find that sectoral stock returns significantly improve economic growth forecasts. However, the forecasting superiority is not uniform across sectors and horizons. Auto, consumers' spending, materials and realty sectors provide the most forecasting gains. In contrast, banking, capital goods and industrial sectors provide superior forecasts, but only at horizons beyond one year. The authors also find that the forecast superiority of sectors at longer horizons is inversely related to volatility. Research limitations/implications: Research highlights the need for sector-focused policy actions in driving economic growth. Further, the findings of the paper identify sectors that drive short-, medium- and long-term economic growth. Practical implications: There is a significant heterogeneity among different sectors and across horizons in predicting economic growth. Results suggest that targeted policy actions in sectors like materials, metals, oil and gas, and realty are key in driving economic growth. Further, policies geared toward the grassroots industries are at least as beneficial as the large-scale industries. Evidence also suggests the need for an active fiscal policy to address infrastructural bottlenecks in primary industries like basic materials and energy. Evidence nevertheless does not undermine the role of monetary policy actions. Originality/value: Unlike any paper till date, the innovation of the paper is that it takes an ARDL modeling approach to measure stock market sectoral returns' ability to forecast economic growth several months ahead in the future. Though the paper considers the Indian case, the innovation and contribution extents to the entire field of economic studies. [ABSTRACT FROM AUTHOR]

This paper uncovers that expected excess bond returns display a positive correlation with the slope of the yield curve (i.e. yield spread) in expansions but a negative correlation in recessions. We use a macro-finance term structure model with different market prices of risk in expansions and recessions to show that a very accommodating monetary policy in recessions is a key driver of this switch in return predictability. [ABSTRACT FROM AUTHOR]

New urbanization construction is important for promoting sustainable economic growth in resource-based cities and can help resource-based cities achieve a sustainable development model with efficient resource allocation and green and low-carbon industrial transformation. Based on the background of the comprehensive pilot policy of new urbanization, we examined whether new urbanization construction promoted the economic growth of resource-based cities using 2011-2017 data on prefecture-level cities and the difference-in-differences (DID) method. It was found that new urbanization construction significantly promoted the growth in GDP per capita of resource-based cities, with a coefficient estimate of 0.1330, and this result passed a robustness test. The mechanism test indicated that new urbanization construction promoted the economic growth of resource-based cities by improving the efficiency of resource allocation and promoting industrial structure upgrading, with interaction term coefficient estimates of 0.1465 and 0.2929, respectively. Heterogeneity analysis showed that the policy effect of new urbanization construction was stronger in resource-rich cities than in resource-poor cities, significant in energy-based resource-based cities but not in metal-based and other resource-based cities, and significant in resource-based cities in the eastern and western regions of China but not in the central region. This study provides government departments implementing new urbanization policies with the results of a policy performance assessment of new urbanization construction for resource-based cities and feasible policy recommendations for the sustainable transformation of resource-based cities. [ABSTRACT FROM AUTHOR]

The main aim of this article is to empirically examine the impact of economic growth and urbanisation on environmental degradation, as well as the existence of the environmental Kuznets curve (EKC) in three Baltic States (Lithuania, Latvia, and Estonia) from 2000 to 2020. The main Kaya identity and the extended urban Kaya identity models are applied within the analysis. The multiple regression analysis made it possible to assess the influence of urbanisation and other factors on greenhouse gas (GHG) emissions in the studied countries, as well as test the hypothesis of the inverted U-shaped EKC. The main finding reveals that GDP per capita growth has the largest and increasing effect on GHG emissions in all three countries. It was also found that changes in population in urban areas in Lithuania and Latvia reduced the amount of GHG until 2020, while in Estonia, the growing urban population greatly contributed to increasing GHG emissions. As a result, processes related to urbanisation have not yet had a significant impact on environmental quality in Lithuania and Latvia. Meanwhile, in Estonia, this is a significant factor that policymakers need to focus on when solving environmental pollution reduction problems. The hypothesis of the EKC was mostly supported when analysing GHG emissions in Lithuania and Estonia and using GDP per capita as an indicator for economic growth. On the other hand, it was found that the impact of the urbanisation rate on GHG emissions is not curved, yet there is some evidence that in Estonia, a growing urbanisation rate is related to diminishing GHG emissions, according to the multiple regression analysis. The results of the study showed that policymakers should consider economic growth and, especially in Estonia, urbanisation when solving problems related to environmental degradation. [ABSTRACT FROM AUTHOR]

China has proposed ambitious goals of carbon peak and carbon neutrality, and will pay more attention to the relationship between economic development and carbon emissions. It's significant to assess the current environmental decoupling and prospect the future conditions in China. This article studies the decoupling status and influencing factors in Chinese provinces from 1996 to 2018 through Tapio decoupling index and decomposition model. The results show that most provinces are currently in a weak decoupling state. The growth of per capita GDP and population will affect the process of strong decoupling, while the optimization of energy intensity, energy structure and industrial structure will promote the realization of strong decoupling. Moreover, this paper prospects the decoupling scenarios of Chinese provinces from 2019 to 2035 and finds that all provinces will achieve strong decoupling before 2040, 2035 and 2030 under different carbon emissions scenarios respectively. To achieve the strong decoupling of economic output and carbon emissions as soon as possible, the government must improve energy efficiency, use renewable energy in large quantities, and promote the industrial transformation and upgrading. [ABSTRACT FROM AUTHOR]

The economic downturn caused by the financial crisis of 2008–2009 and the intensifying global climate policy trends forced changes in the energy management of the European Union. The study examined how the most relevant energy economic variables affected the economic growth of the E.U. between 2010–2019. The study used the PSL-PM methodology to explore the relationship between G.D.P. (dependent variable) and energy consumption, greenhouse gas emissions, the average energy price, and renewable energy use (independent variables). The main findings are: G.D.P. growth is negatively correlated with CO2 emissions, showing that the E.U. economy is still highly dependent on fossil fuels; the increase in the proportion of renewable energy consumption contributed to the growth of the E.U.'s G.D.P.; CO2 emissions, energy consumption, and the average energy price are more critical in E.U. member states with a lower G.D.P.; renewable energy use and energy balance are essential in countries where more emphasis is placed on replacing traditional energy sources and reducing energy dependence; there is a strong positive correlation between G.D.P. and renewable energy use, indicating that this type of energy use effectively supports E.U. economic growth. The results of the multicollinearity test show that there is also a strong linear dependence between the independent energy economic variables. One of the significances of the study is that the presented and analyzed variables and the relationships between them can contribute to optimizing the E.U.'s currently critical energy management and economic growth. [ABSTRACT FROM AUTHOR]

In recent years, environmental issues have become controversial, and policymakers are discovering new predictors of carbon emissions. Some economists/researchers have advocated for fiscal decentralization to improve the quality of the environment by offering more financial authority to provincial/local and sub-national governments. Therefore, this work aims to inspect the effect of fiscal decentralization on economic growth and environmental quality in India by taking data from 1996 to 2021. This work applies both ARDL and NARDL econometric models for empirical examination. The findings of this study suggest that expenditure decentralization has asymmetric long-term and short-term consequences on economic growth, and carbon emission in India. The result of the asymmetric ARDL model also indicates that positive and negative shock in expenditure decentralization contrarily affects economic growth and carbon emission. Moreover, the positive and negative shock in revenue decentralization helps in reducing carbon emissions both in the long run and short run in India. These outcomes are useful for policy analysis from the Indian economic policy perspective. The study also laid out potential outcomes that may benefit India's local governments and central government in resolving the issues of economic growth and environmental degradation. [ABSTRACT FROM AUTHOR]

Monetary policy in Algeria aims to control money supply to stimulate economic growth. This study examines the role of monetary policy tools in achieving economic growth from 1990 to 2020, focusing on the impact of Law 90-10. The findings suggest that monetary policy has had limited success in boosting growth due to the economy's heavy dependence on oil revenue for financing development projects. Despite efforts in implementing reforms and developmental schemes, desired growth rates have not been achieved. [ABSTRACT FROM AUTHOR]

The objective of this study is to investigate the impact of unconventional monetary policy on inflation and economic growth in Algeria. To investigate this impact, we estimated a SVAR model, covering the period from 2006 to 2022 using quarterly data. The originality of this study is the use of the estimated dynamic effects of shocks (stylized facts) as a benchmark for assessing the effectiveness and pass-through of unconventional policies. Our results show that the shock induced by unconventional monetary policy is not transmitted to inflation, neither in the short run nor in the long run, even under theoretical restrictions. In addition, unconventional monetary shocks have no effect on real variables (economic growth). [ABSTRACT FROM AUTHOR]

The Kingdom of Saudi Arabia has recently declared its vision of turning carbon neutral by 2060. This declaration has motivated policymakers in this Arab nation to design policies that can green economic activities in Saudi Arabia so that environmentally sustainable growth can be ensured. Against this backdrop, this study models the independent and joint effects of financial development, globalization, and energy efficiency rates on green growth of the Saudi Arabian economy. In this regard, green growth in the Kingdom of Saudi Arabia is proxied by the difference between the nation's annual per capita growth rates of gross domestic product and carbon dioxide emission. Utilizing data from 1972 to 2018 and controlling for structural break-induced problems found in the data, the findings from the regression and causality analyses confirm the green growth–inhibiting impacts of financial development and trade globalization. In contrast, greater financial globalization is evidenced to drive green growth in the Kingdom of Saudi Arabia. Furthermore, more efficient uses of energy resources are found to not only directly boost green growth but also partially neutralize the long-run green growth–dampening impacts associated with the development of the financial sector. In addition, financial development and trade globalization are observed to jointly inhibit green growth attainment both in the short and long run. In line with these important findings, it is recommended that the government of Saudi Arabia conceptualizes new green growth policies so that the nation's annual per capita economic growth rate outpaces its annual per capita growth rate of carbon dioxide emissions. [ABSTRACT FROM AUTHOR]

This study uses a comparative approach for comparing the nexus of economic growth, renewable and nonrenewable energy consumption, urbanization, trade, and CO2 emissions for South and East Asian countries from 2000 to 2018. The short- and long-run connections between the variables are explored using the dynamic common correlated effects (DCCE) CS-ARDL approach, and the causal linkages are assessed using the Dumitrescu-Hurlin (DH) panel causality test. The data show that the factors have long-term relationships. The findings show that nonrenewable energy consumption and economic growth increase long-term CO2 emissions in South Asia, but trade and use of renewable energy consumption reduce CO2 emissions in the short term. Long-term causal relationships between CO2 emissions, renewable energy use, economic growth, and trade are also revealed by the South Asian causality test. In East Asia, economic growth, NREC, trade, and urbanization increased CO2 emissions in the short and long run, while REC appears to reduce CO2 emissions. According to the causality analysis, long-run bidirectional causation exists between CO2 emissions, renewable energy use, economic growth, and trade. Furthermore, policy suggestions may be made, such as using renewable energy sources to lessen CO2 emissions and improving education and corruption to forecast economic growth in the examined areas. [ABSTRACT FROM AUTHOR]

The discussion on the effect of natural resources on economic growth remains a contentious issue of scientific research. An emerging issue to this discussion is the role of political regime in determining the nature of the growth and natural resource nexus. Consequently, this study examines the effect of natural resources on the economic growth of Tunisia and how the country's political regime moderates this relationship using annual time series data over the 1970–2017 period. Regression analysis established that in the long‐run natural resources generally have positive effects on the country's economic growth, while political regime has mixed effects on economic growth. The interaction between political regime and resources indicates democracy enhances the positive gains from natural resources on economic growth although in the short run, the outcome is mixed. The effects of specific natural resource (oil, mineral, and forest rents) on sectoral growth are positive. Political regime interacts with oil, mineral, and forest rents to propel growth in the agricultural sector. The study concludes that democratic regime is crucial for the effective utilization of resources for long‐run economic growth in the country. Beyond natural resource abundance examined in this study, there is a further need to analyze the extent to which the economy relies on these natural resources and its effect on the economy in future studies. This would elucidate the "natural resource blessings" estimated in this study. The role of other measures of institutional quality on the subject matter can be explored in Tunisia and other countries in future studies. [ABSTRACT FROM AUTHOR]

Governments worldwide are increasingly focused on promoting innovation activity to generate much needed economic growth. Innovation precincts are seen as providing the strategic opportunity to leapfrog economies and deliver a future competitive advantage. However, there are limited insights into how innovation activity in precincts takes place. In particular, the factors that enable successful innovation precincts, how they are measured and how their locations influence improved economic outcomes. This paper presents an analysis of the important enablers of innovation precincts, with a focus on measuring the relative importance of these enablers and their contribution to innovation and economic outcomes. A novel mixed-methods approach involving the use of a 'double-blind doubledscoring' methodology and analytical hierarchy process (AHP) are applied to score and determine the relative importance of enablers of innovation precincts. [ABSTRACT FROM AUTHOR]

High economic and tourism growth demand extensive energy production that needs the energy creation industry's attention and demands the researchers' and policymakers' emphasis. Hence, the present study examines the impact of economic and tourism growth on renewable energy production (REP) in Vietnam. The present research has taken the gross domestic product (GDP), exports, human capital, and employment rate to measure the economic growth, while international tourism receipts and expenditures have been used to measure the tourism growth. The secondary data have been extracted from 1983 to 2020 using World Development Indicators (WDI) database. The Nonlinear Autoregressive Distributed Lagged (NARDL) model has been applied to investigate the linkage between the constructs. The findings indicated that GDP, exports, human capital, employment rate, international tourism receipts, and expenditures have a significant and positive relationship with REP in Vietnam. These results guide the regulators while making regulations related to the extensive energy production in return for high economic and tourism growth. [ABSTRACT FROM AUTHOR]

This article assesses the impact of the development of logistics systems (LS) on the efficiency of the economy. A multi-level methodology for assessing the impact of LS on the economy consisting of six stages (transport, investment, economic, information, material and technical, labor and infrastructure) is proposed using a dynamic structural model for a group of macroeconomic logistical factors for the period 2009-2020 for the republic and the regions of Kazakhstan. Their close relationship with economic growth has been established. Based on the results of factorial and index methods of analysis, mechanisms of differentiation in the management of the regional economy are proposed based on the level of development of logistics and their impact on the growth of the regional economy. Four groups of regions are identified according to the level of development of logistics and their impact on the economy, and directions for their further development are proposed. The forecast is based on the studied factors up to 2030. In particular, it has been established that for the long-term development of the economy of Kazakhstan, the development of agriculture and industry, investment in fixed assets, freight turnover, the availability of vehicles, wages, communication services, and the density of the railway network are important factors. [ABSTRACT FROM AUTHOR]

Recent decades have witnessed an unprecedented transformation in the global energy landscape, driven by environmental concerns and the quest for sustainable economic growth. As the world grapples with the urgent need for decarbonization, the utilization of renewable energy technologies with the instrumental role of rare earth elements (REEs) has come to the forefront. However, empirical investigations into their synergistic pathways for product and economic complexities concerning achieving a low-carbon future remain scarce. Therefore, we forecast synergistic pathways between the REE supply, renewable energy, economic and product complexities, and GDP growth using a panel dataset of 11 REE-producing countries from 1990 to 2023. We used Common Correlated Effects and Temporal Causal Models as primary methods to estimate panel long-run elasticities and subsequently forecast mutual causal synergies between the variables. The results indicated that REE supply led to renewable energy and economic growth that further elevated the countries' product and economic complexities rankings. GDP growth increased REE production, economic complexity, and renewable energy directly, and consequently, product complexity and REE production through them. This underscores the positive role of REE production coupled with renewable energy technologies in achieving a low-carbon future based on economic diversification, enhanced industrial capabilities, and technological sophistication. [Display omitted] • We forecast causal synergistic pathways to achieve green economic growth. • Rare earth elements supply promotes renewable energy use and economic complexity. • Renewable energy use contributes to elevating the product complexity index. • Economic growth contributes to raising the supply of rare earth elements. • Economic complexity extends rare earth elements supply and economic growth. [ABSTRACT FROM AUTHOR]

The economic growth in the new normal is no longer limited to the total amount and scale of economic growth in the traditional and neoclassical periods, but has changed to "quality" and "development" under the dual requirements of historical changes and tasks of the times. The quality of regional economic growth is an important part of the quality of China's economic development and an important part of the quality of China's economic development in the new era. Therefore, this paper proposes a BP neural network based on visual recognition in a regional economic prediction model and conducts application experiments. This regional economic forecasting model is relying on data technology for economic panel data mining, then graphical processing of panel data, followed by the selection of visual recognition technology for economic panel map analysis, to derive its various component coefficients, and finally then using the BP neural network to fit the prediction, at the same time, through long-term and short-term prediction, to predict the future development quality of each region's change trends and fluctuations, to predict the institution's role, so as to avoid major transitions and deteriorating alarms, and to provide support for the macroregulation of regional economic development quality. [ABSTRACT FROM AUTHOR]

Theory and practice suggest that entrepreneurship is the engine of economic growth. The speed with which a nation moves from economic growth to economic development depends on the performance of entrepreneurial initiatives. Given the role played by entrepreneurship for the development of an economy, increasing its performance can help the development of national markets and the increase in national competitiveness. The main objective of our paper is to investigate the link between entrepreneurial performance and economic development of countries. The research was carried out on a sample of 27 European Union countries in a period of twelve years. We used panel data regression models. As dependent variables for expressing the economic development, we considered the global competitiveness index and the gross domestic product per capita growth. As independent variables, we used a set of indicators measuring entrepreneurial performance. Our findings highlight the significant role played by increased entrepreneurial performance for enhancing the economic development of EU countries. We also find that some indicators expressing entrepreneurial performance might have different effects on the economy depending on the stage of economic development of countries. Our research provides empirical evidence regarding the need for performant entrepreneurial activities for enhancing economic development. [ABSTRACT FROM AUTHOR]

Purpose: This paper investigates the relationship between human capital, economic freedom, governance performance, and economic growth and whether institutional factors such as governance performance and economic freedom mediate the association between human capital and economic growth. Design/methodology/approach: In this study, the authors apply the panel data regression method to verify five hypotheses and check the robustness of the empirical findings from four aspects (chow test, panel unit root test, granger test and generalized method of moments) based on the data covering China, India, Russia, Brazil and South Africa from 2000 to 2018. Findings: After multiple tests with mixed methods, the empirical results show that the relationship between human capital and economic growth is not linear but inverted U-shaped. Furthermore, human capital has a positive effect on economic growth only in a certain period of time, and governance performance positively moderates the effect of human capital on economic growth in BRICS. Originality/value: First, the impact of human capital on economic growth is not linear but an inverted U-shaped and governance performance moderates the effect of human capital on economic growth in BRICS. The study and research model enhances the authors' insights on the advantage and challenges of human capital in the future. Second, the proposed multi-methods in the study accurately forecast economic growth which partially solves endogenous problems because of reverse causality. [ABSTRACT FROM AUTHOR]

This paper uses the idea of fractional order accumulation instead of the form of grey index, and applies the fractional order accumulation prediction model to the economic growth prediction of the member states of the Group of Seven from 1973 to 2016. By comparing different evaluation indexes such as R 2 , MAD and BIC, it is found that the prediction performance of fractional order cumulative grey prediction model (GM(α ,1)) is significantly improved in the medium and long term compared with the traditional grey prediction model (GM(1,1)). [ABSTRACT FROM AUTHOR]

Nigeria is the biggest economy in Africa and a significant player in the geopolitics of the continent. The country's ability to command so much relevance is based partly on its status as an oil exporter. It is, therefore, imperative that the country's government protects its golden goose, oil. In this paper, we argue that the recent act of the Nigerian government to resist the promotion of electric vehicles (EV) in the country as a way to protect its economic goose is ill advised. We contend that global transportation and energy phenomena suggest that for Nigeria to remain relevant in the future of the world economy, it is pertinent that it pursues a shift from its current economic model. To buttress our claim, we show how embracing sustainable transportation systems like adopting EV promoting policies, can give Nigeria a rare opportunity to be a big player in the future world economy. [ABSTRACT FROM AUTHOR]

The propulsion of economic growth is a multifaceted construct, influenced by technology, capital, and resource management, with Small and Medium-sized Enterprises (SMEs) being a significant contributors to innovation and employment. This study examines the growth of Scottish SMEs across four sectors over a 14-year period (2008–2021) by employing a novel statistical approach to understand their development trajectories within the framework of open innovation. The paper engaged in a longitudinal analysis to assess trends and inform policy for sustainable growth by the utilization of open-access data. Theoretical metrics such as the Average Growth Rate, Compound Average Growth Rate (CAGR), and Year-Over-Year (YoY) Growth were applied to evaluate sectoral performance. The findings revealed varied growth patterns; the information technology sector exhibited a robust increase, while the telecommunications sector showed significant percentage growth. Conversely, the Information and Communication Technologies (ICT) sector experienced a decline that suggests a potential market gap. An affirmative trajectory in CAGR was observed in most sectors except ICT, which corroborates a shift in technological evolution and market needs. The study illuminates the dynamic economic landscape of Scottish SMEs, with telecoms emerging as the most prosperous sector in terms of growth rates, thus indicates a shifting economic focus. The study's limitations are briefly discussed, in addition to the need for updated databases and further research employing predictive modeling with machine learning to enhance forecasting capabilities and foster open innovation for sustainable economic development. [ABSTRACT FROM AUTHOR]

To reflect the trend of electricity consumption (EC) in China's Pearl River Delta (PRD) under a balanced environment and economy, this paper proposes an EC forecasting framework from the perspective of optimal economic growth. The historical GDP statistics of the PRD are calibrated with data from the new "NPP-VIIRS-like" nighttime light dataset from 2000 to 2020, and two simulation scenarios of optimal economic growth are constructed according to the carbon emission reduction rate. Finally, based on the electricity data from 2000 to 2017, an error correction model is constructed to predict and compare the trend of EC in the PRD under different carbon emission scenarios. The results demonstrate the following. (1) The economic growth path under low-carbon constraints is more closely aligned with the actual economic development of the PRD. (2) The electricity demand required to sustain optimal economic growth in the PRD under low-carbon constraints is projected to reach saturation around 2037, approximately a decade earlier than the scenario without carbon constraints. The results of the projections are expected to guide future work on power system planning and economic development assessment in the context of carbon reduction. • The balance between environmental resources and economic development is considered. • The optimal economic growth path under the low-carbon goal is measured. • Calibration of regional statistics with the nighttime light dataset "NPP-VIIRS-like". • The error correction model is built as a short-term regulation mechanism for power prediction. • Predicted electricity demand for optimal economic growth in the PRD under different scenarios. [ABSTRACT FROM AUTHOR]