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Given that e-commerce is an essential way to improve the efficiency of resource allocation and boost economic growth in the era of digital technology, China has launched the national e-commerce demonstration city (NEDC) pilot project to enhance the application and extension of e-commerce. This study aims to explore the effect of the NEDC pilot policy on economic growth. Based on data sources from 285 prefecture-level cities in China from 2005 to 2021, this study assesses the effect of the NEDC pilot policy on economic growth by applying the staggered difference-in-differences (DID) method with the two-way fixed effects (TWFE) model. In addition, this study investigates the issues of heterogeneity, mediating effects, and cost–benefit of the NEDC pilot policy. The major results of this study are as follows: (1) Compared to non-demonstration cities, the implementation of the NEDC pilot policy resulted in a 4.1% increase in GDP in demonstration cities. Moreover, this boosting effect is particularly significant in prefecture-level cities associated with a high level of digital technology application; however, this positive effect disappears in prefecture-level cities with a high degree of local government intervention. (2) Decreasing transaction costs, increasing business opportunities, and reducing labor misallocation are the main mediating channels for the impact of the NEDC pilot policy on economic growth, implying that the NEDC pilot policy has played an important role in reducing information asymmetry, transaction links, and resource misallocation. (3) The benefits of the NEDC pilot policy exceed its costs as revealed by the fact that the pilot policy has dramatically increased the ratio of GDP to network costs, electricity consumption costs, and labor costs. This study recommends that when strengthening the application of e-commerce, it is essential to reduce excessive government intervention and enhance e-commerce support measures to ensure the role of e-commerce in facilitating economic growth. [ABSTRACT FROM AUTHOR]

Stimulating sustainable FDI through the connection of financial development and its moderating relationships with environmental quality and regulatory quality emerges as a crucial agenda nowadays. This study investigates into this relationship using quarterly data from 1990Q1 to 2022Q4 for Canada; employing ARDL bound tests, Granger Causality, and FM-OLS econometric models. Foreign direct investment is the dependent variable of this study. The findings confirm significant long-run relationships among financial development, stock market development, and the moderating effects of environmental and regulatory quality on FDI inflows in the Canadian economy. Conversely, in the short run, financial development, stock market development, and economic growth exhibit bidirectional causal links with FDI, while environmental quality, regulatory quality, and trade openness demonstrate unidirectional causal links with FDI. The error correction mechanism indicates that all variables quickly return to equilibrium except trade openness. Robustness checks further confirm that all the variables have fully modified co-integrating relationship with FDI inflows including the moderating effects of environmental and regulatory quality which is the innovation in the FDI-Growth existing literature. Thus, policymakers are urged to prioritize environmental quality and regulatory quality, alongside other significant explanatory variables identified in this study to promote sustainable FDI inflows. [ABSTRACT FROM AUTHOR]

This article addresses a critical issue facing developing countries: overcoming the "middle-technology trap" to achieve sustainable economic growth. It posits that transitioning to an innovation-driven economic growth model is pivotal for surmounting this trap and is an essential prerequisite for high-quality development. This study introduces a strategic approach through a new development model, emphasizing the synergy among three core systems: basic scientific research, applied technology, and financial support. This "three-pronged" collaboration model is argued to foster sustainable innovation-driven growth, essential for leaping over the "middle-income trap" towards high-quality development. By analyzing the historical trajectories of the Soviet Union and the United States, the article delineates the critical role of the proposed model in fostering an innovation economy. The Soviet Union's failure and the United States' success are examined through the lens of their respective approaches to integrating basic scientific research, applied technology, and financial systems. The analysis underscores the necessity of a balanced and interactive relationship among these systems for technological innovation, industrial development, and sustainable economic growth. The article concludes that for China to overcome the "middle-technology trap" and achieve long-term prosperity, it should embrace this "three-pronged" new development model, ensuring continuous scientific exploration, technological innovation, and productivity enhancement. [ABSTRACT FROM AUTHOR]

This study examines the relationship between foreign direct investment and total factor productivity on economic growth in 90 middle-income countries. Because middle-income countries often face particular challenges in achieving sustainable economic development. Investigating how FDI and TFP contribute to or hinder economic growth in these countries can provide insight and help policymakers make policy decisions. We employ the dynamic system Generalized Method of Moments to analyze an unbalanced sample with 2714 annual observations from 1990 to 2020. The empirical results show that a percentage increase in foreign direct investment will increase economic growth in middle-income countries by 9.3%. In addition, Total Factor Productivity also has a positive relationship with economic growth due to improved labor quality and production innovations. Furthermore, the results indicate that Total Factor Productivity empowers the positive nexus between Foreign Direct Investment and economic growth. In addition, the main findings are also robust even though we employ alternative economic growth proxies. These findings support economic growth and industrialization theories but do not support labor market dynamics theories. Finally, this study contributes practical suggestions for sustainable economic development in middle-income countries. [ABSTRACT FROM AUTHOR]

This paper aims to empirically examine the relationship between GDP and unemployment in Somalia from 2000 to 2021. The study also estimates Okun's coefficient. To evaluate the association between the unemployment rate and economic growth, we employ the Hodrick–Prescott (HP) filter detrending technique, the Augmented Dickey–Fuller (ADF) test, ordinary least squares (OLS), and fully modified OLS. The findings of this study demonstrate that the series is stationary at the level. However, the results confirm a statistically insignificant negative relationship between unemployment and economic growth. Consequently, our findings suggest that Okun's law does not apply in Somalia. For robustness, we employ fully modified ordinary least squares (FMOLS), canonical cointegrating regression (CCR), and dynamic ordinary least squares (DOLS). Nevertheless, the relationship between the GDP gap and unemployment is not strong enough to be considered statistically significant, and other factors may also influence unemployment. Therefore, policies aimed at reducing unemployment should take into account various factors, including education and training, labor market regulations, and social protection measures. [ABSTRACT FROM AUTHOR]

This article revisits the relationship between economic growth and exchange rate misalignments. We aim to test whether undervaluation's impact on growth depends on institutional quality, as suggested in the previous literature. In our analysis, we focus on recent decades characterized by globalization. We use the framework of cross-country growth regressions estimated using the recently developed two-stage instrumental variable method, which allows accounting for cross sectional dependence. In addition, we use external instruments to address the potential endogeneity between economic growth and undervaluation. Our results confirm the positive relationship between undervaluation and growth across all income groups from low-income to high-income countries. The role of institutions in the transmission of undervaluation on growth appears consistently only among lower-middle-income countries. Therefore, while our results point to the positive effects of undervaluation, the support for the hope that countries can successfully compensate for poor institutional quality via the undervaluation of currencies is weaker and limited to specific stages of economic development. [ABSTRACT FROM AUTHOR]

The study set out to investigate whether transparency can mitigate the negative effects volatile capital flows have on growth using cross-section panel data from 21 sub-Saharan African countries from 2000 to 2019. Using the IVQR model, the study finds that at 75th quantile, poor growth performance in SSA is explained mostly by the volatility in debt net inflows compared to other categories of capital, while portfolio net inflow contributes most significantly to the low-level growth for low and medium income countries. Focusing on the interaction between transparency and capital net inflows, the study finds evidence that transparency reduces most of the negative effects of the volatility in debt net inflow compared to other categories of capital inflow. Thus, the study provides evidence that transparency can reduce the negative effects of volatile capital inflows on growth by a significant amount, which varies depending on the type of capital inflow. The implication is that the extent transparency dampens the negative impact of volatile capital flows depend on both the capital type and the level of income of the country concerned. Regarding FDI and FPI, transparency is most effective in reducing volatility of the flow for low income countries, while for debt flows transparency penalizes the volatility of flows for high income countries. On this basis, it recommends that central banks should adopt transparency as a policy tool, particularly in SSA economies with probably low initial transparency to help mitigate the harmful effects of large and volatile capital inflows. [ABSTRACT FROM AUTHOR]

This paper proposes a panel Granger causality approach for heterogeneous panels with cross-sectional dependence. We define a panel VAR model with unobserved common factors and apply the PANIC procedure to obtain the de-factored data. We then estimate the lag augmented (LA)-VAR model for each cross section and construct the panel statistics based on the meta-analytic approach that combines the p-values of the individual statistics. The Monte Carlo simulations indicate that the combination tests show good size and power properties and appear suitable for the panels where cross sections may have different unit root or co-integration properties. We finally re-investigate Granger causality between export and economic growth in OECD countries. The results shed light on the importance of accounting for cross-sectional dependence within a factor model framework in determining direction of Granger causality for country-specific analysis. The results further reveal that export and economic growth do not cause each other in the majority of the European Union countries. [ABSTRACT FROM AUTHOR]

The double-wheel drive of manufacturing industries and producer services industries is one of the key pathways to promote high-quality development relying on a modern industrial system. This paper explores the impacts of industrial co-agglomeration on regional economic growth in China with systematic consideration of static, dynamic, and spatio-temporal perspectives based on panel data for 285 prefecture-level cities from 2003 to 2020, employing the consolidated night-time light data. The empirical results show that industrial co-agglomeration significantly accelerates regional economic growth, especially high-tech intensity producer services industries, information industries, and finance industries. In addition, its spatial spillover effects are evidently established, which are characterized by cyclic accumulative, feedback features, and distance attenuation. Carrying out robustness tests, the preliminary regression results are verified. The heterogeneous influences are established across cities with different geographical locations, innovation capacities, and resource endowments. The further mechanism analysis indicates that industrial upgrading, technological progress, and efficiency enhancements account for the main channels for a sharp promotion in regional economic growth over the sample period. Furthermore, the government moderates this process more significantly than market forces do, especially when it comes to macroexogenous shocks that are regulated by the government. The findings of this study recommend policymakers to give full play to the positive externalities of industrial co-agglomeration and accelerate the industrial co-agglomeration process in a reasonable manner, so as to promote high-quality economic growth in China. [ABSTRACT FROM AUTHOR]

With intensified urbanization, cities are becoming increasingly important units for addressing air pollution issues. From the perspective of urban agglomeration (UA), in this paper, the influence of functional division on carbon dioxide (CO2) emissions is studied. To explore the spillover effect within UA, a spatial Durbin model is built. The mediating effects of economic growth, industrial structure, and technological progress are examined using the parallel multiple mediation model. An empirical study is carried out on the Yangtze River Delta in China. The results suggest that: at the UA level, functional division and CO2 emissions follows a positive "U-shaped" curve relationship. The level of functional division is located on the left side of this curve. This implies that when the functional division of the Yangtze River Delta improves, current CO2 emission levels will decrease. Within the UA, improving the level of functional division will minimize CO2 emissions of adjacent cities, exerting a significant spillover effect. Functional division imposes a significantly negative influence on CO2 emissions. Moreover, economic growth, industrial structure, and technological progress all exert a significant mediating effect on the influencing mechanism. Functional division within the UA can also significantly reduce CO2 by optimizing these three paths. [ABSTRACT FROM AUTHOR]

The study explores the dynamic and complex nexus between ICTs and economic performance by applying a meta-analysis with data from 65 typical studies at the country level. The overwhelmingly significant positive effects of ICTs on economic performance are confirmed through the vote count, funnel plot, precision-effect test, and meta-regression analysis. Additionally, differential influences of ICTs on developed and developing countries are investigated. Overall, developed countries gain more benefits from ICTs, while mobile technology tends to have more potential for economic growth. Moreover, the sample size and time period the data covered affect the ICTs—economic performance effect. In contrast, the type of data does not appear to significantly influence this effect. To better understand the impacts of ICTs, the continued skepticism and periodical revisit of this topic are required. The survey provides an updated and comprehensive examination of the state of the literature and also points out that although the generally favorable influences of ICTs are emphasized, the detrimental effects of ICTs on economic performance, especially for developing countries, cannot be ignored. With insights from this review, the study suggests directions for future research. [ABSTRACT FROM AUTHOR]

The digital economy, being a nascent technology, has exerted a substantial sway on how businesses are produced, how governments are run, how people live, etc. Considering this, additional investigation is required to gain a deeper comprehension of the connection between digital economic expansion and the impact of pollutant reduction, as well as the impact mechanism at play. Accordingly, using panel data from city-level data in China spanning the years 2011–2019 for analysis, this research explores the effects and mechanisms of digital economic growth on urban industrial pollution emission reduction. A two-way fixed effects model is applied. The outcomes demonstrate that a particular inflection point value determines how much the digital economy may reduce urban industrial pollutant emissions. Specifically, only when the digital economic development index surpasses 10 does it become viable to generate the emission reduction effect. The digital economic promotional influence on the decrease of urban industrial pollution emissions grows as industrial company service levels rise. Moreover, in regions with high market segmentation, in the eastern territories, and areas with strong policy support, the digital economy exhibits a lower inflection point for demonstrating its discharge lessening effects. [ABSTRACT FROM AUTHOR]

The China-Pakistan Economic Corridor (CPEC) is a cornerstone of China's Belt and Road Initiative (BRI). It aims to enhance regional trade and economic expansion in Pakistan. We adopted systematic review approach to investigate the agricultural trade narrative of the CPEC and identify future research avenues. Our study uses the Web of Sciences and Scopus database to extract the relevant literature. We executed the search query for 2013–2023. We followed the Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA) statement to identify the literature. The final analysis includes only 14 articles. We found that the literature mainly focuses on three topics, Gwadar port, road infrastructure, and agricultural complementarity and competitiveness. The review reveals the significant potential of CPEC on the agricultural trade of Pakistan. Based on the review, we point to avenues that could be considered in future research work to fully exploit the potential of CPEC in the agriculture sector of Pakistan. [ABSTRACT FROM AUTHOR]

Africa began implementing the Sustainable Development Goals (SDGs) in 2015 emphasizing on sustainable management and effective use of natural capital to spur economic growth (Goals 12, 14, and 15). This study using World Bank data sets from 46 African countries selected for the years 2000 to 2022, examined the nexus between natural resource endowments and economic growth in Africa. We used the system generalized method of moments (sys-GMM) and dynamic panel threshold regression (DPTR) to analyze the data. The findings of the two-step sys-GMM estimation using 'xtabond2' revealed that when the institutional quality variable is added and excluded from the model, natural resource dependence negatively impacts economic growth, but the impact is greater when the institution is excluded. In the estimation of the interaction variable of natural resource dependence and institutional variable included in the model, natural resource dependence positively impacts economic growth. The results of the DPTR using "xthenreg" showed that when the threshold value of natural resource dependence is ≤ 1.73% of gross domestic product, natural resource dependence has a positive impact on economic growth and a negative impact when the threshold value is above 1.73%. Similarly, when the institutional quality threshold is ≤ 0.277, natural resources dependence impacts economic growth negatively; above the threshold (0.277), the impact is positive. In conclusion, natural resource endowment is a curse with no or low-quality institutions and a blessing with high-quality institutions. Thus, building strong institutions and proper utilization of natural resources helps to minimize the adverse impact of resource endowments on economic growth. [ABSTRACT FROM AUTHOR]

The circular economy has been identified as a critical keyword for achieving the Sustainable Development Goals. Nevertheless, there is a lack of in-depth empirical literature on the impact mechanisms of the circular economy (CE) and economic growth (GDP) in mitigating e-waste generation (waste electrical and electronic equipment - WEEE). Given Europe's leading position in e-waste generation per capita, the study aims to scrutinize the interplay between CE, GDP, and WEEE for 2010–2020. The research applies advanced econometric methods, primarily centered around the system generalized method of moment and dynamic panel threshold. It was noteworthy that different CE indicators exhibited varying effects on WEEE through the econometric analysis. Therefore, the research uniquely utilized the entropy weight method to compute a holistic composite index for the circular economy (CEI) and gained some interesting findings. Firstly, CEI significantly reduced WEEE, while GDP drove its increase. However, an overly developed CEI of 0.7616 counteracted its beneficial effect. Secondly, the synergy of CEI*GDP engendered the circular economy rebound effect, diminishing environmental benefits. Thirdly, in the circular context, the environmental Kuznets curve was validated, showcasing an inverted U-shaped pattern. Finally, the study found CEI to have different threshold effects, with thresholds of 0.2161 to inhibit WEEE, 0.2114 to avert the circular economy rebound effect, and 0.2360 to leverage GDP in reducing WEEE. These outcomes give insights to policymakers in designing sound policies targeting circular economy development and decoupling e-waste generation from economic growth towards the United Nations' SDGs. [ABSTRACT FROM AUTHOR]

The present study attempts to examine the link between trade openness and sustainable human development (SHD) in 19 emerging economies. The study used the data for the period from 1996 to 2019. The study employed fixed-effect regression with Driscoll–Kraay standard error techniques robust to cross-section dependence. The study found the favorable impact of trade openness on sustainable development through sustainable human development. Trade openness affects sustainable human growth in many ways. It is a critical component that should not be ignored in sustainable development policies. Moreover, foreign direct investment, economic growth, and renewable energy consumption positively impact the sustainable human development. In contrast, innovations and institutional quality have an adverse impact on SHD. The study also provides policy suggestions for the emerging economies that will promote all the dimensions of sustainable development: economic, social, and environmental. [ABSTRACT FROM AUTHOR]

The relationship between economic growth and CO2 emissions has been analyzed testing the environmental Kuznets curve hypothesis, but traditional econometric methods may be flawed. An alternative method is proposed using segmented-sample regressions and implemented in 164 countries (98.34% of world population) over different periods from 1822 to 2018. Results suggest that while the association between GDP per capita and CO2 emissions per capita is weakening over time, it remains positive globally, with only some high-income countries showing a reversed association in recent years. While 49 countries have decoupled emissions from economic growth, 115 have not. Most African, American, and Asian countries have not decoupled, whereas most European and Oceanians have. These findings highlight the urgency for effective climate policies because decoupling remains unachieved on a global scale, and we are moving away from, rather than approaching, the Paris Agreement goal of limiting temperature increase to 1.5 °C above preindustrial levels. [ABSTRACT FROM AUTHOR]

Assessing the growth of social, environmental, and economic domains are too difficult task. Thus, an accurate prediction could not be made via the conventional prediction method. Hence, a novel Goat-based Artificial Neural System (GbANS), in order to provide improved growth visualization of socioeconomic and environmental behavior prediction. Moreover, the study region selected for this validation is Muzaffarpur City and its environs. Using the trained rainfall and flood data, the initial phase's flood and rainfall rates were estimated. The growth rate of environmental and socioeconomic behaviors was projected based on the condition. Here, the goat's best solution is used to analyze the growth in the socioeconomic and environmental domains. In the present research, the novelty lies in the integration of goat optimization with the artificial neural network for improved forecasting of rainfall and floods. Also, GbANS goes beyond simply predicting rainfall and floods. It incorporates modules to assess the potential socioeconomic and environmental impacts of the predicted flood. The model holds the most promising solution for accurate rainfall and flood prediction. GbANS has the potential to be a significant advancement in rainfall and flood forecasting due to its potential for improved accuracy and enhanced decision-making support. The performance characteristics of the developed GbANS were then assessed and compared in terms of accuracy, Mean Square Error (MSE), and Root Mean Square Error (RMSE) with other models that were already in use. The suggested method has achieved an enhanced best result with an accuracy of 98.1%. [ABSTRACT FROM AUTHOR]

Although scholars often portray Mexico as caught in the "middle-income trap," this description obscures important subnational variation in patterns of economic development. We leverage this variation by examining the case of Querétaro, a state with high levels of structural transformation and economic growth since the 1980s. We reconstruct the historical trajectory of its two leading industries, automotive and aerospace. We observe that while both have cumulatively delivered real developmental gains, each also exhibits a complex mix of strengths and weaknesses. We further find that these industries' advancements and hindrances over time appear closely related to the kinds of "partial" coalitions — groups of actors from the state, private firms, and civil society organizations such as labor unions — which participate in industry-level decision-making. Both industries saw periods of "upgrading" when the partial coalitions supporting them were expanding their cognitive diversity while avoiding gross imbalances in the distribution of power among their members. They likewise experienced periods of stagnation when either of those coalition conditions underwent major change. These findings suggest that debates on escaping the middle-income trap should consider how changes in partial political coalitions affect policy models and options. [ABSTRACT FROM AUTHOR]

This study investigates the effect of flash floods on local economic activity in Central America and the Caribbean. I measure these rarely analyzed floods by constructing a high-resolution, physically based index of flash flood occurrence from satellite data and connect these to changes in local night light emissions. After accounting for tropical cyclone activity, flash floods have a delayed, short-term negative effect on economic activity. In countries with a low to medium human development index (HDI), the average negative effect can be up to 5.6 % in the following months. Countries with higher HDI appear more resilient and are only marginally affected. Also, flash floods exhibit a minor positive spatial spillover in low to medium HDI countries, besides their more substantial local negative effect. Due to their high frequency, flash floods have a detrimental effect on local economic growth in developing countries that will likely be exacerbated by climate change. (JEL) [ABSTRACT FROM AUTHOR]

Public spending influences a country's economic activities due to its effect on aggregate demand. Although existing research has focused on government expenditures to understand the multiplier impacts of public spending, there is scant literature focusing on the spending of state-owned enterprises (SOEs), especially in strategic sectors such as the oil sector. This study analyzes the spending behaviour of an important Brazilian SOE, Petrobras, to understand its consequences to the Brazilian economic activity. The results suggest that multiplier impacts during recessions are bigger than those during economic expansions. The accumulated multiplier of Petrobras's investment expenditures is higher compared to current spending, especially in periods of recession. Moreover, the forecast error variance decomposition showed the impact that changes in government spending in Petrobras had on the Brazilian GDP growth in periods of expansion and contraction. [ABSTRACT FROM AUTHOR]

This study examines the empirical link between remittance inflows and India's economic growth, particularly emphasizing the association's asymmetries as the prior studies were neglected. Therefore, it formulated a growth function that assesses the non-linear influence of the remittance inflows on economic growth by endogenizing the gross fixed capital formation, official exchange rate, and export growth. Relying on the annual time series data for India, the work uses the Non-Linear Auto-Regressive Distribution Lag (NARDL) model to expose the non-linear influence of the remittance inflows on economic growth by controlling the gross fixed capital formation, official exchange rate, and export growth for the period ranges from 1975 to 2021. The outcomes show the presence of the long-run relationship among the variables vector. Further, the results indicate an asymmetric impact of remittance inflows on economic growth both in the long run and short run. Moreover, the findings reveal a rise in the remittance inflows leads to an increase in economic growth, whereas a fall in the remittance inflows ends up in a reduction of economic growth. Additionally, the outcomes show a negative and significant impact of gross fixed capital formation and official exchange rate on economic growth in the long run. It also observed an insignificant negative influence of export growth on the specified growth model. [ABSTRACT FROM AUTHOR]

Recent literature revisits cross-country convergence patterns over the last six decades. Whilst the debate has been about unconditional or conditional convergence, we question whether convergence rates differ across countries. Using the same dataset as in the recent studies of Kremer et al. (NBER Macroecon Annu 36:337–412, 2022) and Acemoglu and Molina (NBER Macroecon Annu 36:425–442, 2022) (GDP per capita for 108 countries over 58 years, 1960–2017), we systematically search models where the degree of heterogeneity varies from the mean group, pooled mean group, fixed effects and pooled estimators of convergence. The Bayesian Information Criterion selects the heterogeneous model whether we use the U.S., a common factor or country-specific trends as the steady state. We estimate a multi-country technological catch-up statistical model using the U.S. as the technological frontier. We show empirically that a failure to allow for heterogeneous rates of convergence creates a bias in the convergence coefficient towards zero. The long-run elasticity to the U.S.—another convergence parameter of interest—associates positively (0.79) with the country's average growth. Countries that learn from the technological frontier also grow faster. [ABSTRACT FROM AUTHOR]

Does China pull up its 31 mainland provinces as it converges to the incomes of advanced economies? The conventional method of modelling convergence in the Chinese provinces has been the Barro approach. This paper models convergence through a common factor, interpreted as the rising tides that lift the boats—the growth of China lifts its provinces. We question the conventional (Barro in Q J Econ 106:407–443 1991) definition of convergence. Imposing a common convergence rate across provinces would bias the convergence rate towards zero. We focus on the heterogeneous model where the convergence rate and long-run elasticity to the common factor differ across provinces. The rising tides of growth disproportionately benefit the poorer provinces and lifts the poor provinces more than the wealthier ones. This reveals the effects of transfer from the coastal provinces that developed first to the inner provinces that developed later. [ABSTRACT FROM AUTHOR]

The literature on convergence in per-capita income across countries has not converged on a common concept of convergence. It may be within a country towards its own steady state or between countries. Between country convergence may be absolute convergence to the same steady state; conditional convergence to country specific steady states, functions of observed variables; or club convergence to different steady states. It may be measured by beta convergence; sigma convergence; or the presence of a common trend. This paper surveys the econometric issues involved in estimating the rate of convergence; testing for convergence; and specifying the unobserved steady state. The survey suggests that rather than there being different ways to measure a single concept, convergence, the different measures are measuring different things. [ABSTRACT FROM AUTHOR]

Post occupancy evaluation of housing reconstruction after a disaster is imperative for every nation that pushes ahead the idea of disaster resilient housing, which is obligatory for the social, cultural, and economic growth of a society or a country. Cyclone SIDR is the most dreadful of all catastrophes that have struck Bangladesh and aftermath of this devastation, a number of donor organizations stepped forward to help disaster victims by providing housing solutions. The aim of this study is to effectiveness analysis of these housing reconstruction programs from planning and construction standpoints with a post occupancy framework. Based on three months of detailed field survey at the most devastated location of cyclone SIDR, Southkhali Union (small rural area) of Sarankhola Upazila (sub-district) of Bagerhat District, this research infers that the donor organizations didn't pay much attention in terms of choice, need and indigenous practices to provide reconstructed houses for the target beneficiaries. The study found that about 78% of the reconstructed houses hold dissatisfaction of the beneficiaries. As a result, people prompt to transform or modify 54% of the 'Donor Driven' houses soon after completion of the project. Another 16% donor driven house remained abandoned and rest 8% demolished. On the other hand, 'Owner Driven' houses were functionally perfect. They had freedom to build their houses with locally available natural materials with resilient planning and construction features which reduces disaster vulnerability and sustains for long time in comparison with donor driven houses. [ABSTRACT FROM AUTHOR]

Crowdfunding has emerged as a transformative alternative to traditional innovation financing. Limitations of conventional funding sources have led to increased interest in alternative financing mechanisms. Crowdfunding, leveraging online platforms, has democratized access to capital, enabling entrepreneurs to develop products and services that align with broader population needs. This paper surveys the literature, demonstrating how crowdfunding platforms have opened doors to capital for entrepreneurs who might otherwise have found it challenging to secure funding through established channels. While crowdfunding's impact on innovation is multifaceted and contingent on factors like innovation type, entrepreneur quality, and regulatory frameworks, its growth trajectory remains robust, solidifying its significance as a source of entrepreneurial finance. The study aims to (1) analyze the effectiveness of crowdfunding in bridging the funding gap for startups, (2) compare crowdfunding with other forms of entrepreneurial finance, (3) assess crowdfunding's role in fostering innovation, (4) differentiate between crowdfunding and crowdsourcing, and (5) identify the types of innovation facilitated by crowdfunding. Effective crowdfunding implementation hinges on these factors, necessitating concerted efforts from entrepreneurs, investors, and policymakers to surmount associated challenges and harness its potential for innovation and economic growth. The findings highlight the necessity for a supportive regulatory framework and the importance of transparency and trust in crowdfunding practices. This study underscores the role of policymakers in creating an environment that fosters innovation through alternative financing. However, this study is limited by the availability of comprehensive data across different crowdfunding platforms and regions. Further empirical research is needed to generalize the findings across various contexts, deepen our understanding of crowdfunding's impact on innovation, and develop strategies to leverage the potential of crowdfunding for innovation. [ABSTRACT FROM AUTHOR]

This research analyses the interplay between trade liberalisation, economic growth, and economic development in South Africa. The research focuses on two distinct periods, pre-BRICS (1991 to 2010) and post-BRICS (2011 to 2021) and aims to assess economic growth and development trajectories which are intertwined with liberalisation. A Vector Error Correction Model (VECM) is used to account for potential cointegration among the variables. The study reports a long-run equilibrium relationship among the variables. The study finds that trade openness substantially influences GDP growth in the post-BRICS period and highlights a unidirectional causal relationship between trade liberalisation and economic growth. The research also reveals a positive association between trade openness and economic development, implying that openness fosters growth and facilitates broader development outcomes in South Africa. The research underscores the importance of trade openness as a driving force for economic growth and economic development in emerging economies like South Africa. [ABSTRACT FROM AUTHOR]

Fiscal decentralization is perceived as a viable strategy for fostering economic growth in Pakistan. Concerns persist regarding its potential impact on environmental quality, particularly in relation to increased carbon emissions. Employing diverse analytical methods such as structural vector autoregressive (SVAR) modeling and autoregressive moving average model evaluations, this study comprehensively explores the dynamic relationships among fiscal decentralization, economic development, and environmental quality over the period 1979–2019. Intriguing trends emerge, revealing positive correlations between environmental efficiency and variables, including revenue collection, tax autonomy, and transfer payments. Conversely, a negative correlation is observed between government spending and economic growth. The interplay of these variables results in oscillations in the influence of fiscal decentralization on carbon emissions, presenting a complex challenge for policymakers. Notably, positive fiscal decentralization shocks lead to an increase in carbon emissions, while positive expenditure decentralization and economic development correlate with decreased carbon emissions. Despite economic growth's statistically significant negative impact on carbon emissions, the intricate nature of the relationships underscores the complexity of the link between fiscal decentralization, economic expansion, and environmental outcomes. From a policy perspective, the study emphasizes the need to adjust fiscal policies and coordinate intergovernmental fiscal ties across all government levels to enhance environmental efficiency. These findings provide policymakers with valuable insights to navigate the intricate landscape of fiscal decentralization and its environmental implications. [ABSTRACT FROM AUTHOR]

The impact of climate risk on economic and financial fields has attracted considerable interest from academics and practitioners. Recent literature documents that climate risk can affect oil volatility through the dual channel of economic activities and financial markets. Inspired by this, this paper uses climate policy uncertainty (CPU) to examine the predictability of crude oil price volatility. The empirical results indicate that changes in the CPU, rather than the original CPU, can forecast oil volatility. The revealed volatility predictability is both in-sample and out-of-sample. Asset allocation exercise shows that this finding is also economically significant. Furthermore, the predictive ability is mainly concentrated during economic expansions and the CPU contains climate risk that is not available for other predictors. Finally, CPU change indicators can explain the changes in crude oil consumption, which is the economic source of their predictive power. [ABSTRACT FROM AUTHOR]

The empirical literature on Kaldor's laws includes very few studies applied to the Middle East and North Africa. Those that examine the role of manufacturing in the growth process in the context of the region are almost nonexistent. This paper fills the gap and investigates the role of manufacturing growth in selected Middle Eastern and North African countries using panel data analysis from 2007 to 2019. The study tests Kaldor's three laws to identify the role of manufacturing in economic growth. The first law of Kaldor indicates that the growth rate of the manufacturing sector is strongly and positively related to the growth rate of the economy. The second law of Kaldor, also known as the Kaldor-Verdoorn law, shows the relationship between productivity in manufacturing and manufacturing output. The third law states that a rise in overall productivity in an economy has a positive effect on output in manufacturing. Using data from the World Development Indicators, an empirical analysis using the system generalized method of moments is performed in a sample of 13 Middle Eastern and North African countries. The results provide strong support for the three laws in the Middle East and North Africa, demonstrating that output growth in the manufacturing sector is critical for generating economic growth and increasing productivity. [ABSTRACT FROM AUTHOR]

The interactive behaviors, such as competition and learning between local and neighboring cities, can lead to spatial spillover effects in policy implementation. Estimating the direct, indirect, and total effects of the carbon emission trading scheme (CETS) on green innovation is crucial to clarify its role and mechanisms. This paper applies the spatial difference-in-differences model to estimate these effects using data from 278 cities in China from 2009 to 2019. The results demonstrate that the CETS implementation catalyzes green innovation in pilot cities, which supports the Porter hypothesis. However, it has a negative impact on green innovation in neighboring cities of pilot cities, with this negative impact diminishing as distance increases. Notably, the total effect of the CETS is significantly negative, indicating that the CETS's average impact on green innovation in all cities is negative. Mechanism analysis reveals that the direct and indirect effects of the CETS on green innovation are strengthened in cities with higher levels of financial development, lower financial pressure, and easier economic growth targets. Notably, in cities with high-level industrial structures, the CETS not only enhances its contribution to green innovation but also mitigates its negative impact on neighboring cities. Furthermore, this paper explores the heterogeneous effects of the CETS from the perspective of its implementation measures. [ABSTRACT FROM AUTHOR]

Accurate real-time macroeconomic data are essential for policy-making and economic nowcasting. The rising interest in analyses at the sub-national level cannot be served as such data are currently not available. In this paper, I introduce a real-time database for German regional economic accounts. The database contains real-time information for nine macroeconomic aggregates and the 16 German states. I conduct both a revision analysis and a nowcasting experiment for real gross domestic product. By pooling the states together, the first official estimates show no systematic revision errors. The pooling, however, suppresses the revision characteristics of single states. For half of the 16 German states I find that the first estimates are no optimal predictions, thus, leaving room for improvements in the future. The real-time nowcasts for real gross domestic product growth based on a mixed-frequency vector autoregression are very accurate and beat several benchmark models. More regional data would help to better inform the model, thereby increasing its nowcast performance even further. [ABSTRACT FROM AUTHOR]

This study has a twofold objective. On the one hand, the comparative analysis of the efficiency of Spanish prisons structured based on three groups of conflict and size, by non-parametric radial and non-radial DEA methods, for 2015–2020. On the other hand, to determine to what extent exogenous factors such as Covid-19, the change of government or economic growth, have influenced the levels of efficiency, controlling for the prison size within each group. The comparative analyses carried out by the Radial and non-radial DEA estimations show important differences in the results. With the non-radial method, there is a clearly decreasing trend in efficiency over time and a greater dispersion of values in the inter-annual distribution. Therefore, the efficiency values of the Penitentiary Centers according to the group to which they belong in relation to their respective efficient frontiers show greater distances or possibilities for improvement in the case of this method compared to the Radial DEA. As for the results of the second stage, the influence of Covid on the management of the centers has had a negative impact on all groups. The implications derived from mandatory confinement have been reflected in greater organizational complexities, regardless of the type of center, in terms of size and criminal complexity. In this sense, there is a positive relationship between efficiency and the size of the centers. In the case of groups 1 (larger size and conflictive) and 2 (both average size and conflictive), a curvilinear shape (U-shape) is captured where a representative part of centers is in the increasing zone of the trend. In the case of group #3, the behavior is linear. Likewise, the influence of the political party in government has been captured. In the first case, differences in efficiency are found, depending on the legislative period, although the effects of the pandemic and its temporal coincidence, and the delay between political decisions and their subsequent implementation and return of results could have had an influence. Finally, the relationship between efficiency and economic growth is positive. [ABSTRACT FROM AUTHOR]

Sustainable development is a common goal across the world. As the core force to promote economic growth and enhance national competitiveness, the sustainable development of urban agglomeration is a key component of national strategy. This study explored the scale optimization in the Yangtze River Delta Urban Agglomeration (YRDUA) under the framework of sustainable development. Results showed that the sustainability of the overall urban agglomeration development is not optimal. With the increase in cities, the sustainability of the city combination formed with Shanghai as the seed point showed a trend of increasing at first and then decreasing. When the number of city group is 6, the sustainable development goal (SDG) index score is the highest. It indicated that the combination formed by some cities may be superior to urban agglomeration in sustainability. Therefore, the concept of pan-metropolitan area was proposed, and at current stage, the pan-metropolitan area should be developed first to achieve sustainable development within a smaller urban group, and then to build high-quality and coordinated development at the entire urban agglomeration. Finally, a road of urban agglomeration integration and international development from part to whole will be established. [ABSTRACT FROM AUTHOR]

This study examines the relationships among exports, economic growth, the World Uncertainty Index, and the Geopolitical Risk Index for Japan within both bivariate and multivariate frameworks. We analyze quarterly data spanning from 1994Q1 to 2022Q1. This investigation contributes to the existing literature on the export-led growth hypothesis through an innovative approach. Specifically, we employ the state-of-the-art Wavelet Local Multiple Correlation (WLMC) method introduced by Polanco-Martínez et al. (Sci. Rep. 10(1): 1-11 (2020). https://doi.org/10.1038/s41598-020-77767-8). Unlike conventional bivariate wavelet methods, the WLMC enables us to capture correlations between two/ three/four variables simultaneously. To the best of our knowledge, this study represents the first empirical analysis that evaluates the short, medium, and long-term dynamics of export-led growth in the context of uncertainty. Our research findings reveal that, in the multivariate framework, exports emerge as the dominant variable, providing support for the export-led growth hypothesis in the Japanese context. Furthermore, in the long run, we identify adverse effects of the World Uncertainty Index on economic growth. Based on our results, this paper puts forth essential policy recommendations for the Japanese government. These recommendations aim to guide the development of countercyclical policies that can stabilize both exports and economic growth amid a backdrop of uncertainty. [ABSTRACT FROM AUTHOR]

In the face of complex domestic and international situations, the influence of domestic trade on economic growth has been paid more and more attention by the academic community while we still know little about its internal mechanism. From the perspective of China's inter-provincial trade, based on the panel data of 29 provinces (municipalities and autonomous regions) in China from 2000 to 2021, this paper studies the impact of inter-provincial trade on economic growth by using a two-way fixed effects model. It is found that inter-provincial trade has a significant positive effect on economic growth, and each 1% increase in inter-provincial trade will increase per capita GDP by 0.19%. Furthermore, inter-provincial trade positively affects economic growth through the effect of technology improvement and industrial structure upgrading. However, the two mechanisms are heterogeneous in the eastern, central, and western regions. Among them, the technology improvement mechanism is only established in the central and western regions and the industrial structure upgrading mechanism is only established in the eastern and central regions. Finally, we suggest that governments should formulate targeted development goals and plans according to the actual situation of each region, to ensure that inter-provincial trade can play a full role in promoting economic growth. [ABSTRACT FROM AUTHOR]

The green transformation of industry and sustainable economic development both require considerable investment. In this regard, green finance that is compatible with economic development can help cope with the massive demand for capital. Taken China's Yangtze River Delta (YRD) as an example, this study is to measure the coordination degree between green finance and economic development. First, the concept, content and scope of green finance is defined based on the new financial regulation mechanism. Second, a green finance measurement index is built to calculate the green finance index for 30 Chinese provinces by the CFA test. Third, based on the economic structure index, an economic development index is built. Testing the rationality of green financial index and the economic development index, this paper finally measures the degree of coordination between green finance and economic development in the YRD. The results reveal that, first, green finance is a financial instrument that integrates financial industry development, environmental improvement, and economic growth. The measurement of the green financial development index includes the sum of regional green credit, green investment, green securities, and green insurance. Second, after years' development, the comprehensive score of YRD's coupling coordination degree exceeds 0.8 in 2020, which shows a high level of coordinated development between green finance and economic construction. However, there is a 2-year timing effect between the economic development and green finance index increase, which reveals that green finance development in the YRD requires further policy guidance and support. This study's findings can provide a theoretical reference and case support for the further development of green finance and related policies in China. [ABSTRACT FROM AUTHOR]

The issue of environmental degradation has become pertinent and the call for carbon neutrality has intensified in recent years. Achieving this target will require countries to meet the conditions of the sustainable development goals. To do this, the study applied spatiotemporal modelling and the generalized method of moments (GMM) to examine the nexus between economic growth (EG) and the load capacity factor (LCF) through environmental goods (ENG) and environmental tax (ENT) among European Union (EU) nations from 1995 to 2018. The findings demonstrate that spatial dependence leads to a change in EG and LCF that impacts the EG and LCF of the neighbouring countries. The study also found that there is a significant positive and bidirectional relationship between economic growth and load capacity factor. Moreover, the study revealed that a positive effect of ENG, ENT, REN and Human Capital Index (HCI) on EG, with a reducing effect from natural resource rents (NRR). Finally, HCI improves environmental quality, while ENG, ENT, REN and NRR degrade the environment. Our findings justify the need for EU countries and other developed nations to implement policies that will help achieve a green economic transformation. [ABSTRACT FROM AUTHOR]

Reducing the carbon intensity of human well-being (CIWB) is a potential form of climate action. We conduct a preliminary analysis of the effects of economic growth and income inequality on the CIWB of Canada's provinces, and find that both increase CIWB in this sub-national context. We also find that their effects are symmetrical, meaning that positive and negative changes in economic growth and income inequality result in the same proportional changes in CIWB. Therefore, and while incredibly difficult to do, it is possible that efforts to reduce income inequality and economic growth are potential pathways to reducing CIWB. [ABSTRACT FROM AUTHOR]

This research explores economic growth dynamics in five ASEAN countries (1980–2020), analyzing the short and long-term impact of financial development (FD), oil prices, investment (INV), and inflation on GDP growth. Panel ARDL analysis reveals a transient positive link between FD and long-term GDP growth, necessitating a holistic approach for short-term stability. Similarly, oil prices exhibit long-term volatility, urging diversification strategies. In contrast, consistent and significant relationships exist between INV and GDP growth in both time frames, underscoring investment's pivotal role. The study emphasizes managing inflation for sustained growth, offering vital insights for policymakers, economists, and analysts in fostering ASEAN's economic stability. [ABSTRACT FROM AUTHOR]

This paper explores the cause-and-effect relationship between the elderly population and global economic growth, focusing on different continents. A panel dataset spanning from 1961 to 2020 is utilized, with Gross Domestic Product (GDP) serving as the key measure for economic growth, represented as the percentage change in annual GDP. The study specifically centers on individuals aged 65 and above as a percentage of the total population. The analysis employs a Panel Granger causality test to assess the impact of the elderly population on economic growth. The results reveal a unidirectional Granger causality for Africa and Oceania, suggesting a one-way influence from the elderly population to economic growth. Conversely, instances of bidirectional Granger causality are identified for Asia, Europe, North America, and South America, indicating a mutual influence between the elderly population and economic growth during the study period. The study concludes that an endogenous relationship between economic growth and the elderly population emerges, but notably, this relationship becomes apparent only after an economy has completed its transition in economic development. This implies that the dynamics of the elderly population and economic growth are interlinked, with the nature of their interaction becoming more pronounced in the later stages of economic development. [ABSTRACT FROM AUTHOR]

University–Industry Collaborations (UIC) are increasingly recognized as crucial drivers of economic growth and development. While numerous studies have been conducted on this topic, this paper specifically focuses on UIC in the Arab World. The aim of this study is to explore the establishment of successful UIC by conducting a review of existing literature to identify and synthesize key factors that enable collaborative innovation between industry and universities. The findings are summarized into six main themes: the importance of UIC, barriers to UIC, gaps between universities and industry in the Arab World, partnerships and sustainable growth, current trends and perspectives, and future agenda for Arab countries. These themes are elaborated on and used to summarize results from the reviewed studies regarding facilitators of collaborative innovation. The contribution of this work lies in enhancing the existing body of literature and knowledge regarding collaboration between higher education and industry in the Arab World. This research presents specific measures that can be implemented to ensure successful UIC in the future. Its outcomes are significant for policymakers, academics, and industry experts in the Arab region, who aspire to form productive UIC partnerships that encourage economic development and innovation. [ABSTRACT FROM AUTHOR]

Using the Consumer Expectations Survey of the ECB, I estimate how individual expectations on core economic outcomes changed in France, Germany, Italy, and Spain right after the beginning of the Ukraine–Russia war. I find that individuals expected lower economic growth and higher inflation. The effect of the war was larger in the countries with a higher energy-imports dependency. Hence, the expectation formation process might have changed. [ABSTRACT FROM AUTHOR]

Despite the positive impact that renewable energy can offer its development is not necessarily and widely implemented by countries. It is against this backdrop this study investigates whether renewable energy contribute to economic growth in sub-Saharan Africa (SSA) between the periods 2005–2022. The study accounted for the role of information communication technology and globalization in stimulating economic growth. For empirical analysis, this study adopted Pooled Mean Group (PMG) Autoregressive Distributed Lag Model approach and other batteries of techniques for robustness testing. It was observed that both renewable energy and information communication technology (ICT) indicate a negative and significant impact on economic growth in the long run. The study further established a positive and significant impact of globalization and economic growth in the long run. This indicates the vital role of ICT and globalization in accelerating economic growth. In terms of policy suggestions, this study believes that infrastructural development, incentives among others could make renewable energy more affordable and attractive for private sector participation. There is also the need to provide research funding to develop home-produced technology to improve energy supply in the region, particularly in rural areas. [ABSTRACT FROM AUTHOR]

The transportation industry (TRAI) is an important source of carbon emissions for China to achieve its peak carbon and carbon neutrality targets. This study analyzes the coupled integration of TRAI economic growth and carbon emissions in 30 Chinese provinces from 2005 to 2020 using a Tapio decoupling elasticity model and an environmental Kuznets curve (EKC) model. Then, a long-term energy alternative planning (LEAP) system model was constructed to predict and simulate the development of TRAI in China. The results of the study are as follows. (1) TRAI shows an inverted U-shaped decoupling in most provinces across the country, and most of the decoupling is usually more volatile in provinces with higher levels of economic development. In addition, COVID-19 positively contributes to the development of TRAI nationwide and in three regions. (2) The Tapio-EKC coupling curves of TRAI and eastern TRAI (ETRAI) nationwide have an inverted N-shape, and central TRAI (CTRAI) and western TRAI (WTRAI) have an inverted U-shape. Twenty-seven provinces crossed the decoupling elasticity inflection point nationwide, all provinces of ETRAI crossed the EKC inflection point, while all provinces of CTRAI and WTRAI did not cross the EKC inflection point; (3) The carbon reduction rates after scenario simulation ranged from 5.07 to 54.94%, with aircraft, ships, private vehicles, and their fuels (aviation kerosene, diesel, and gasoline) being the focus of energy saving and emission reduction. The coupled Tapio-EKC analysis model of this study is universal and can be extended to other provinces, cities, or industries. [ABSTRACT FROM AUTHOR]

In the modernized world, stimulating economic growth and employment without endangering environmental sustainability remains a fundamental challenge for developing and newly industrialized economies. This current study investigates the dynamic connections between income growth, unemployment, and environmental deterioration in Turkey within the environmental Phillips and Kuznets curve frameworks. The study employs a novel econometric technique, the augmented autoregressive distributed lag (A-ARDL) model, and examines annual time-series data from 1980 to 2018. To the best of the authors' knowledge, no study has tested the validity of the environmental Phillips curve (EPC) hypothesis (a novel approach linking unemployment with environmental pollution) for Turkey. Another concern with the existing research is that only a few papers simultaneously analyze the EPC and environmental Kuznets curve (EKC) hypotheses and consider the significance of the ecological footprint. Therefore, the study utilizes ecological footprint as an environmental degradation indicator and tests these two hypotheses by setting six models that control renewable energy consumption, natural resource rents, financial development, foreign direct investments, and urbanization to provide more reliable and consistent results. Empirical evidence from the multiple models justifies the validity of both hypotheses in the short and long run. The results also suggest that natural resource rents increase the ecological footprint, while urbanization contributes to environmental quality. Nonetheless, renewable energy, foreign direct investments, and financial development have no significant environmental impact. These outcomes suggest that a rise in employment not accompanied by green energy technologies, higher environmental awareness, a well-educated labor force, and expanded renewable energy utilization may impede the country from attaining its long-term development goals. [ABSTRACT FROM AUTHOR]

Unquestionably, all countries prioritize maintaining peace and fostering long-term sustainable economic growth. For this purpose, this study assessed the impact of military expenditure on economic growth using a multivariate regression model based on the enhanced production function in the presence of energy consumption. The study clustered 48 Islamic countries into their income levels over the period from 1990 to 2018, and using the dynamic common corrected effects in determining the elasticities of the explanatory variables. The empirical results revealed a negative effect of military expenditure on economic growth and the elasticity of military expenditure to economic growth was lowest in upper-middle-income countries than in the other three groups. In the main panel a 1% increase in military expenditure led to a 0.101% decrease in economic growth. The results of the paired Dumitrescu Hurlin panel causality test revealed a bidirectional causal affiliation between economic growth and military expenditure. In addition, the empirical findings revealed that the levels of military expenditure, as a component of total government expenditure, are too high in the employed economies and need to be transferred toward more productive non-military expenditure in order to improve the economic growth performance and other growth determinants. [ABSTRACT FROM AUTHOR]

Scholars have given enormous attention to the roles of energy use and trade in economic growth strategies; however, recent international trade literature suggests that not merely the volume of trade but the diversification of goods may have a potential effect on economic growth. Thus, this paper uses the diversification of export goods and diversification of import goods as explanatory variables along with energy consumption and assessed the role of these important variables in economic development. The empirical results from Westerlund's (J Appl Econom 23:193–233, 2008) and Westerlund's (Oxf Bull Econ Stat 69:709–748, 2007) tests disclosed the existence of cointegration. The long-run estimations obtained from the CUP-FM technique revealed that both import and export product diversifications positively influence economic growth. This presents a vital opportunity for emerging nations to expand growth by diversifying export and import products. Likewise, energy use, labor, and capital contribute to increasing economic growth. The estimates from the causality test illustrated bidirectional causality between export diversification and economic growth and unidirectional causality from energy to export diversification. Finally, policy suggestions to expand economic progress are discussed. [ABSTRACT FROM AUTHOR]

Raising economic growth is the primary concern of most of countries especially the developing and emerging economies in order to enhance the living standard of people. However, increase in economic activities increases energy demand which rise carbon dioxide emissions and leads to environmental degradation. Technological innovations might be the remedy to overcome the issue of increased carbon dioxide emission by reducing energy use, raise energy efficiency and also push economic growth activities efficiently. In this regard, this study explores the interrelationship of technological innovation, carbon dioxide emissions, and economic growth from 1985 to 2019 in 35 Belt and Road countries. The study uses ordinary least squares, two-step system generalized method of moments, two-step difference generalized method of moments, seemingly unrelated regression, and three-stage least square models for analysis. The results indicate that technological innovations increase economic growth and enhance environmental quality. Foreign direct investment also increases economic growth while degrading environmental quality. Economic growth increases technological innovation while exerting harmful effects on the quality of the environment. The impact of trade on economic growth is positive, while financial development reduces economic growth. School enrollment has a significant and positive effect and increases technological innovation, while foreign direct investment and research and development reduce it. The results also confirm that research and development expenditures significantly reduce carbon emissions and enhance environmental quality. The findings of this study have considerable policy implications for the sample countries with respect to economic growth, technological innovations, and environmental quality. [ABSTRACT FROM AUTHOR]