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The paper aims to assess the macroeconomic impacts of government investment in Research and Development (R&D) and more generic fiscal policies by quantifying the Gross domestic product (GDP) and business R&D investment multipliers. Following the recent literature on fiscal policy, we combine the Local Projection approach with fiscal shocks estimated using Structural Vector Autoregressive modeling by focusing on a panel of 15 Organization for Economic Co-operation and Development (OECD) countries for the 1981–2017 period. Our findings support the idea that expansionary fiscal policies can positively and persistently affect the GDP level and crowd in business R&D investment. Additionally, our results show that public investment in R&D generates the largest multiplicative effect both on GDP and business R&D than the one associated with more generic public expenditures, even when fiscal expectations are considered. [ABSTRACT FROM AUTHOR]

Ecosystems generate a wide range of benefits for humans, including some market goods as well as other benefits that are not directly reflected in market activity1. Climate change will alter the distribution of ecosystems around the world and change the flow of these benefits2,3. However, the specific implications of ecosystem changes for human welfare remain unclear, as they depend on the nature of these changes, the value of the affected benefits and the extent to which communities rely on natural systems for their well-being4. Here we estimate country-level changes in economic production and the value of non-market ecosystem benefits resulting from climate-change-induced shifts in terrestrial vegetation cover, as projected by dynamic global vegetation models (DGVMs) driven by general circulation climate models. Our results show that the annual population-weighted mean global flow of non-market ecosystem benefits valued in the wealth accounts of the World Bank will be reduced by 9.2% in 2100 under the Shared Socioeconomic Pathway SSP2-6.0 with respect to the baseline no climate change scenario and that the global population-weighted average change in gross domestic product (GDP) by 2100 is -1.3% of the baseline GDP. Because lower-income countries are more reliant on natural capital, these GDP effects are regressive. Approximately 90% of these damages are borne by the poorest 50% of countries and regions, whereas the wealthiest 10% experience only 2% of these losses.

Disequilibrating macro shocks affect different firms' prospects differently, increasing idiosyncratic variation in forward-looking stock returns before affecting economic growth. Consistent with most such shocks from 1947 to 2020 enhancing productivity, increased idiosyncratic stock return variation forecasts next-quarter real GDP growth, industrial production growth, and consumption growth both in-sample and out-of-sample. These effects persist after controlling for other leading economic indicators. [ABSTRACT FROM AUTHOR]

Econometrics is a branch of economics that uses mathematical and statistical methods to study quantitative and qualitative relationships within economic phenomena. The purpose of this article is to study the impact of the capital market (financial instruments) on economic growth in Kazakhstan and the CIS countries through an understanding of the concept of “econometrics”. The task of the study is to determine the dependence of gross domestic product as a resultant factor over the past 20 years. Methods. The article determines the assessment of the impact of financial factors on economic growth in the short term. An econometric model was used for this purpose. The resulting factor was the gross domestic product over the past 20 years. Results. The results indicate that the capital market influences economic growth in Kazakhstan and the CIS countries. This paper presents a model of the GDP function for the economy of Kazakhstan. In the course of the study, coefficients and variables of the model were estimated to predict the level and future changes in the country’s GDP. Thus, the size of the capital market (Y1) depends on the following variables tested in the model: the number of securities issuance transactions; the volume of securities issuance transactions; the number of transactions of non-residents with shares at the secondary auction of KASE; the rate of change of shares of leading issuers on KASE

During the period of the pandemic and martial law, Ukraine has lost a significant part of its human capital: assessing these losses and developing proposals for their restoration is especially relevant in the context of the need to restore Ukraine’s economy in the post-war period. The purpose of the article was to study and systematize the causes of human capital losses and their structure, to determine the impact of learning losses on the formation of human capital, as well as to summarize proposals for compensation for learning losses and restoration of human capital. As a result of the analysis of the scientific works, a number of factors have been identified that affect the level of learning losses and learning gaps due to quarantine restrictions in various countries of the world, namely, Germany, Spain, Belgium, China. The systematization of information made it possible to group the factors that affect learning losses in Ukraine, with the allocation of groups of factors that are due to the restriction of opportunities to attend educational institutions, and groups of factors that have arisen as a result of hostilities in Ukraine. The paper substantiates the existence of regional differences in the occurrence of learning losses and their impact on the formation of human capital. The clustering of regions has been carried out on the basis of losses of entrants in educational institutions and the region’s contribution to the creation of the gross domestic product of Ukraine. The results of the clustering made it possible to determine the priority directions for the restoration of human capital. Based on the research results, measures to eliminate learning losses and learning gaps for educational institutions of various levels are proposed, which can be applied in practice in the post-war reconstruction of the country’s economy

The study aims to investigate the relationships between the volume of net migration and the economic development of individual European countries, which will make it possible to forecast the level of GDP and strengthen their migration policy. Correlation-regression analysis was used based on statistical data from Eurostat and the State Statistics Service of Ukraine for the period 2014−2021 for selected European countries (the EU-27 member states, Switzerland, and Ukraine). The correlation-regression analysis showed a relationship between the volume of net migration and the level of GDP. The linear correlation equations forecasted the value of the GDP level depending on the influence of a single factor – the volume of net migration. The attention is focused on the importance of migration, which ensures economic growth for Poland. It is attractive due to a simpler mechanism for moving immigrants than in other EU-27 countries, ease of language learning and easier adaptation, territorial proximity, and a higher standard of living compared to neighboring countries that were part of the Soviet Union. Thus, an increase in net migration to Poland by 1% will lead to an increase in gross domestic product by 1.43 million euros. Due to Russia’s war against Ukraine, net migration from Ukraine to Poland has increased significantly, potentially increasing Poland’s GDP in 2023 by 0.08% or 529.54 million euros.

Water, energy, and food (WEF) are vital strategic resources for human survival and development, which are interacting positively or negatively. While WEF sustainability has received significant attention and extensive research has examined its interactions, there are a few studies exploring the trade-offs arising from advancing the sustainable development process. This paper aims to study the internal interrelation and external impact on WEF sustainability from the perspective of Sustainable Development Goals (SDGs). We first quantified the WEF sustainability at the provincial level in China from 2003 to 2020, then used panel vector autoregression (PVAR) to identify the interactions within the WEF system and examined how related SDGs actions (SDG 8, 12, 13) affected it. The findings revealed spatial disparities in sustainable processes across provinces. Internally, prioritizing water-sustainable actions fostered overall synergistic development, while trade-offs emerged between food and energy systems. Externally, SDG 8, 12, and 13 acceleration actions mainly contributed to WEF sustainability, but maintaining GDP growth and reducing CO2 emissions both presented challenges to sustainability. This study not only enriches the understanding of WEF sustainability from the SDGs perspective, but also provides valuable insights into how sustainable development actions can affect the WEF system. [ABSTRACT FROM AUTHOR]

Research on the relationship between fertility and gender ideology revealed inconsistent results. In the present study, we argue that inconsistencies may be due to the fact that such a relationship may be nonlinear. We hypothesize a U-shaped relationship between two dimensions of gender ideology (i.e., primacy of breadwinner role and acceptance of male privilege) and fertility rates. We conducted a cross-national analysis of 60 countries using data from the World Values Survey as well as the World Population Prospects 2019. Controlling for gross domestic product, we found support for a U-shaped relationship between gender ideology and fertility. Higher levels of fertility rates were found at lower and especially higher levels of traditional gender ideology, while a medium level of gender ideology was associated with the lowest fertility rate. This curvilinear relationship is in agreement with the phase of the gender revolution in which the country is located. [ABSTRACT FROM AUTHOR]

Pollution in the environment is today the biggest issue facing the globe and the main factor in the development of many fatal diseases. The main objective of the study to investigate green investments, economic growth and financial development on environmental pollution in the G-7 countries. This study used annual penal data from 1997 to 2021. The panel NARDL (Non-linear autoregressive distributed lag) results affirm that the positive change of green investment and negative shock in green investment have a significant and positive association with environment pollution in G-7 nations. Our findings provide more evidence for the long-term asymmetry between financial development and environmental performance. However, the findings confirm that a positive modification in financial development has a positive and significant effect on environment pollution. Whereas negative shock in financial development is negative and insignificant relationship with environment pollution. Moreover, the outcomes of the study reveal that both positive shock in gross domestic product growth and negative shock of economic growth have a significant and positive link with environment pollution in G-7 countries. According to the findings, by lowering carbon dioxide emissions, green investments reduced environmental pollution in the G-7 nations over the long and short term. Moreover, it is an innovative research effort that provides light on the connection between green investments, financial development, and the environment while making mention to the EKC in G-7 countries. After all these, our recommendation is to increases green investment expenditures to reduce environmental pollution in the G-7 nations based on our findings. Additionally, one important way for the nation to achieve its sustainable development goals is to improve advancements in the financial sector. [ABSTRACT FROM AUTHOR]

Law sets out the rules for society and the economy, particularly important for interactions between strangers. Legal code is a form of non-rival infrastructure, a public good important for investment and innovation. This paper investigates whether legal code complexity scales with population size in US localities. We analyse a corpus of municipal codes from 3259 cities and measure legal complexity using various metrics, including number of words, bytes, and compressed bytes. We find that legal complexity scales geometrically with jurisdiction population, with a scaling parameter of approximately 0.2 and an R2 of approximately 0.2. The estimated scaling parameter is similar to gross domestic product percapita, consistent with an interpretation of legal codes as regulating social interactions per capita in cities. This article is part of the theme issue 'A complexity science approach to law and governance'. [ABSTRACT FROM AUTHOR]

Background: Insufficient physical activity (PA) was estimated to cause 4.8% of deaths and 2.6% of disability-adjusted life-years (DALYs) due to noncommunicable diseases in Saudi Arabia in 2019. While Saudi Arabia is already achieving great improvements, we predict the health and economic burden of insufficient PA up to 2040 to present a case for policy makers to invest more in the uptake of PA. Methods: Using a population health model to estimate avoidable health loss, we identified four causes of health loss related to low PA (cardiovascular diseases, diabetes, breast cancer, and colorectal cancer) and estimated the deaths and DALYs from these causes. We projected the expected disease burden until 2040 under alternative assumptions about future PA levels and trends by using three health scenarios: baseline (no change in 2019 PA levels), intervention (81% of the population achieving sufficient PA levels), and ideal (65% of population: moderate PA, 30%: high PA, and 5%: inactive). We applied an "intrinsic value" approach to estimate the economic impact of each scenario. Results: Overall, we estimate that between 2023 and 2040, about 80,000 to 110,000 deaths from all causes and 2.0 million to 2.9 million DALYs could be avoided by increasing PA levels in Saudi Arabia. The average annual economic loss from insufficient PA is valued at 0.49% to 0.68% of the current gross domestic product, with an average of US$5.4 billion to US$7.6 billion annually till 2040. The most avoidable disease burden and economic losses are expected among males and because of ischemic heart disease. Conclusions: This study highlights that low PA levels will have considerable health and economic impacts in Saudi Arabia if people remain inactive and do not start following interventions. There is an urgent need to develop innovative programs and policies to encourage PA among all age and sex groups. [ABSTRACT FROM AUTHOR]

This study aims to analyse the impact of the Movement towards Socialism (MAS) regime on GDP, income inequality and corruption levels. The empirical findings show that GDP has increased and corruption decreased with the MAS party in power. Income inequality, however, has tended to increase, even though average values for the Gini index during the MAS years have been lower. The difference between counterfactual and actual observations (i.e. treatment effects) was regressed against three key shocks experienced by the Bolivian economy and the findings demonstrate that all these shocks are correlated with the three outcome variables. [ABSTRACT FROM AUTHOR]

In the present work, India's primary energy use is analysed in terms of four socio-economic variables, including Gross Domestic Product, population, and the amounts of exports and imports. Historical data were obtained from the World Bank database for 44 years as annual values (1971–2014). Energy use is analysed as an optimisation problem, where a unique ensemble of two metaheuristic algorithms, Grammatical Evolution (GE), and Differential Evolution (DE), is applied. The energy optimisation problem has been investigated in two ways: estimation and a year-ahead prediction. Models are compared using RMSE (objective function) and further ranked using the Global Performance Index (GPI). For the estimation problem, RMSE values are found to be as low as 0.0078 and 0.0103 on training and test datasets, respectively. The average estimated energy use is found in good agreement with the data (RMSE = 6.3749 kgoe/capita), and the best model (E10) has an RMSE of 5.8183 kgoe/capita, with a GPI of 1.7249. For the prediction problem, RMSE is found to be 0.0096 and 0.0122 on training and test datasets, respectively. The average predicted energy use has RMSE of 7.8857 (kgoe/capita), while Model P20 has the best value of RMSE (7.9201 kgoe/capita) and a GPI of 1.8836. [ABSTRACT FROM AUTHOR]

Societies' use of material resources is increasingly recognized as a key factor behind sustainability problems. The mass of materials used per capita and year differs substantially between countries. However, a limited range of variables (mostly per‐capita gross domestic product [GDP]) were analyzed to explain this variation. Spatial patterns of cities influence their resource use, but the role of patterns of settlements and infrastructures as co‐determinants of national‐level material use is unknown, mainly due to lacking data to investigate their effects at that scale. Here we start closing this gap by systematically analyzing a broad set of potential determinants of national per‐capita material demand, including built structures. Material demand is represented by both production‐ and consumption‐based indicators. Among its potential determinants, we analyze eight novel indicators representing extent and spatial patterns of settlements and transport infrastructures in each country, along with GDP and other indicators considered so far. Analyzing 123 countries inhabited by 91% of the world population and accounting for 92% of world GDP, we show that built structures strongly co‐determine resource use. Indicators of extent and spatial patterns of built structures have substantial additional explanatory power beyond GDP and other conventional indicators for both production‐ and consumption‐based material flow indicators. The area of built‐up land per capita emerges as the strongest predictor, but several other indicators representing built structures are also highly relevant. Limiting built‐up land and designing spatial patterns of built structures hence deserve attention in attempts to reduce societies' resource throughput. [ABSTRACT FROM AUTHOR]

The first official Marine Economy Satellite Account (MESA) of the United States was created to improve the credibility and reliability of comprehensive measurements of the nation's dependence on ocean and coastal resources. This methodology improves upon previous methods and yields results that (1) are consistent with national accounts statistics, such as gross domestic product, (2) capture additional categories of marine-related activities, and (3) bring measurement of the US marine economy into alignment with the most advanced international practices. These advances support recent sustainable growth initiatives of the US blue economy, allow policy makers to better evaluate industries perhaps most vulnerable and at risk from coastal hazards, and enable government and private businesses to promote and invest in this crucial driver of the US national economy. [ABSTRACT FROM AUTHOR]

Considering the differences in traffic delays and accident costs at different stages of the shipping cycle, this study develops a system dynamics model to determine the impacts of the shipping cycle on traffic delays and accident costs at port collector-distributor roads. Taking the collector-distributor roads of Yangshan Deepwater Port in Shanghai as a case study, parameter estimation and a model validity test are conducted. The changes in traffic delays and accident costs before and during maintenance activities at different stages of the shipping cycle are analyzed by increasing the growth rates of gross domestic product (GDP), and secondary and tertiary industries in GDP. The model results show that, as the economic growth rate increases, the growth magnitudes of traffic delays and accident costs during a peak period are significantly larger than those during a trough period. The results of this study provide policies and suggestions for improving traffic efficiency and safety on port collector-distributor roads. It is suggested to increase the maintenance frequency and maintenance funds during a peak period. Additionally, it is necessary to develop an intelligent road maintenance system for port collector-distributor roads that takes the shipping cycle into account in order to enhance the road safety level. [ABSTRACT FROM AUTHOR]

Aim: Spreading infectious diseases associated with introduced pathogens can have devastating effects on native biota and human livelihoods. We analyse the global distribution of 100 major alien fungal and oomycete pathogens with substantial socio‐economic and environmental impacts and examine their taxonomy, ecological characteristics, temporal accumulation trajectories, regional hot‐ and coldspots of taxon richness and taxon flows between continents. Location: Global. Taxon: Alien/cryptogenic fungi and fungus‐like oomycetes, pathogenic to plants or animals. Methods: To identify over/underrepresented classes and phyla, we performed Chi2 tests of independence. To describe spatial patterns, we calculated the region‐wise richness and identified hot‐ and coldspots, defined as residuals after correcting taxon richness for region area and sampling effort via a quasi‐Poisson regression. We examined the relationship with environmental and socio‐economic drivers with a multiple linear regression and evaluated a potential island effect. Regional first records were pooled over 20‐year periods, and for global flows the links between the native range to the alien regions were mapped. Results: Peronosporomycetes (Oomycota) were overrepresented among taxa and regional taxon richness was positively correlated with area and sampling effort. While no island effect was found, likely due to host limitations, hotspots were correlated with human modification of terrestrial land, per capita gross domestic product, temperate and tropical forest biomes, and orobiomes. Regional first records have increased steeply in recent decades. While Europe and Northern America were major recipients, about half of the taxa originate from Asia. Main Conclusions: We highlight the putative importance of anthropogenic drivers, such as land use providing a conducive environment, contact opportunities and susceptible hosts, as well as economic wealth likely increasing colonisation pressure. While most taxa were associated with socio‐economic impacts, possibly partly due to a bias in research focus, about a third show substantial impacts to both socio‐economy and the environment, underscoring the importance of maintaining a wholescale perspective across natural and managed systems. [ABSTRACT FROM AUTHOR]

Spatial dynamics of logistic allocation in large urban centers has gained relevance in urban economics, public policy formulation and transport engineering. A crucial aspect of these spatial, agglomerative, and dispersive phenomena are the causal links that such processes generate or by which they are generated. This study investigates the causal relationships linked to the allocation of logistics warehouses in the context of the sub-regions of the São Paulo Metropolitan Region (SPMR) based on the theory of agglomeration economies. Two variables related to the urban distribution of goods were selected: (a) Gross Domestic Product (GDP) and (b) Cargo Theft (CT) and contrasted with the number of logistics warehouses (NW). Five regions of the SPMR were considered both for spatial descriptive analysis and for the study of causality based on the Granger methodology, adapted by Hurlin, and on the cointegration methodology and Panel Vector Error Correction Model. For SPMR, the relationships obtained demonstrate, in the short term, unidirectional causalities between GDP/NW. In the short term, the causal relationship between CT/NW for the metropolitan region was unidirectional from the amount of cargo theft to the number of warehouses. The subregions showed strong heterogeneity in causal relationships, both in the short and long term, demonstrating the complexity of the logistical allocation phenomena in the SPMR. • Cargo theft is a crucial decision factor when installing a logistic warehouse. • The demand in high-GDP regions increases the need for nearby logistics services. • The number of warehouses affects long-term economic growth. [ABSTRACT FROM AUTHOR]

Energy transition is one of the main objectives of the European Union. Significant changes will mainly affect countries in which significant modifications will have to be made to their energy sources. The process will involve high investment in infrastructure and additional costs of the transformation, such as reduced production (which may affect the GDP value) in the economic sectors involved in the process. The aim of this article is to provide the energy transition community, namely the national economy in general and those involved in planning for structural change in particular, with the key lessons and challenges in researching the impact of production changes in the mining sector. This article also shows the relevance of the mining sector in the economy. Within this area, particular attention is given to the following issues: the impact of economic sectors on the country's GDP (gross domestic product); the identification of key sectors of the economy using the input–output method; the contribution of coal mining and the mining industry to Poland's GDP; an analysis of changes in the structure of Poland's economy using the input–output method; and the use of the input–output method in the context of changing/reducing the supply of economic sectors. [ABSTRACT FROM AUTHOR]

To construct a stochastic version of [R. J. Barro, J. Polit. Econ. 87, 940-971 (1979)] normative model of tax rates and debt/GDP dynamics, we add risks and markets for trading them along lines suggested by [K. J. Arrow, Rev. Econ. Stud. 31, 91-96 (1964)] and [R. J. Shiller, Creating Institutions for Managing Society's Largest Economic Risks (OUP, Oxford, 1994)]. These modifications preserve Barro's prescriptions that a government should keep its debt-gross domestic product (GDP) ratio and tax rate constant over time and also prescribe that the government insure its primary surplus risk by selling or buying the same number of shares of a Shiller macro security each period. [ABSTRACT FROM AUTHOR]

Background: Lithuania, a Baltic country in the European Union, can be characterized by high alcohol consumption and attributable burden. The aim of this contribution is to estimate the mortality burden due to alcohol use for the past two decades based on different relative risk functions, identify trends, and analyse the associations of alcohol-attributable burden with alcohol control policies and life expectancy. Methods: The standard methodology used by the World Health Organization for estimating alcohol-attributable mortality was employed to generate mortality rates for alcohol-attributable mortality, standardized for Lithuania's 2021 population distribution. Joinpoint analysis, T-tests, correlations, and regression analyses including meta-regressions were used to describe trends and associations. Results: Age-standardized alcohol-attributable mortality was high in Lithuania during the two decades between 2001 and 2021, irrespective of which relative risks were used for the estimates. Overall, there was a downward trend, mainly in males, which was associated with four years of intensive implementation of alcohol control policies in 2008, 2009, 2017, and 2018. For the remaining years, the rates of alcohol-attributable mortality were stagnant. Among males, the correlations between alcohol-attributable mortality and life expectancy were 0.90 and 0.76 for Russian and global relative risks respectively, and regression analyses indicated a significant association between changes in alcohol-attributable mortality and life expectancy, after controlling for gross domestic product. Conclusions: Male mortality and life expectancy in Lithuania were closely linked to alcohol-attributable mortality and markedly associated with strong alcohol control policies. Further implementation of such policies is predicted to lead to further improvements in life expectancy. [ABSTRACT FROM AUTHOR]

Recently, the economy in Guangdong province has ranked first in the country, maintaining a good growth momentum. The prediction of Gross Domestic Product (GDP) for Guangdong province is an important issue. Through predicting the GDP, it is possible to analyze whether the economy in Guangdong province can maintain high-quality growth. Hence, to accurately forecast the economy in Guangdong, this paper proposed an Elman neural network combining with wavelet function. The wavelet function not only stimulates the forecast ability of Elman neural network, but also improves the convergence speed of Elman neural network. Experimental results indicate that our model has good forecast ability of regional economy, and the forecast accuracy reach 0.971. In terms of forecast precision and errors, our model defeats the competitors. Moreover, our model gains advanced forecast results to both individual economic indicator and multiple economic indicators. This means that our model is independently of specific scenarios in regional economic forecast. We also find that the investment in education has a major positive impact on regional economic development in Guangdong province, and the both surges positive correlation. Experimental results also show that our model does not exhibit exponential training time with the augmenting of data volume. Consequently, we propose that our model is suitable for the prediction of large-scale datasets. Additionally, we demonstrate that using wavelet function gains more profits than using complex network architectures in forecast accuracy and training cost. Moreover, using wavelet function can simplify the designs of complexity network architectures, reducing the training parameter of neural networks. [ABSTRACT FROM AUTHOR]

This study examines the effect of remittance inflows on Nigeria economy as proxy with gross domestic product (GDP). The research specifically focuses on 41 years from 1981 to 2021, analyzing data from the Central Bank of Nigeria's statistical bulletin and the World Development Index. Through correlation analysis, unit root and co-integration tests, as well as error correction model estimation, the study investigates the relationship between remittance inflows and GDP growth. The results demonstrates that, in the short term, remittance inflows had an insignificant negative effect on Nigeria's GDP growth (-0.337970, p > 0.05). However, in the long run, remittance inflows shows a significant positive impact on the GDP growth rate (1.973835, p < 0.05). These findings highlight the importance of channeling remittances into productive activities within the home country. While short-term inflows may not contribute significantly to economic growth, sustained and increasing remittance inflows can play a crucial role in driving Nigeria's economic expansion. The study recommends the implementation of policies, programs, and systemic reforms to encourage the productive utilization of remittances. It emphasizes the need to ensure that remittances are utilized in ways that contribute to longterm economic growth and development. Furthermore, the study calls for the establishment of measures to prevent brain drain, protecting Nigeria's valuable human capital from being solely driven by financial incentives, which may not be evenly distributed for productive purposes in the short and medium term. These measures will help foster a balanced approach to leveraging remittance inflows for sustainable economic progress in Nigeria. [ABSTRACT FROM AUTHOR]

Gross Domestic Product (GDP) is one of the macroeconomic indicators that reflects the level of welfare of a country's population. The APEC (Asia-Pacific Economic Cooperation) forum has the main goal of promoting economic growth and enhancing prosperity in the AsiaPacific region. This is done by encouraging and facilitating more open trade and investment in the region. APEC member countries have different export characteristics, namely agricultural exports and high-technology exports. This study analyzes the influence of agricultural exports, high-technology exports, Foreign Direct Investment, and regulatory quality on the Gross Domestic Product of APEC member countries. The research data used are secondary data from the World Bank from 2011 to 2020, analyzed using the Fixed Effect Model approach of panel data regression method using E-Views 12. The results show that simultaneously, agricultural exports, high-technology exports, Foreign Direct Investment, and regulatory quality have a significant influence on the economies of APEC member countries. Partially, high-technology exports and regulatory quality have a positive and significant impact, while agricultural exports and Foreign Direct Investment have a positive but not significant impact on GDP. APEC countries should focus on productivity by harnessing technology and achieving inclusive economies for societal welfare. [ABSTRACT FROM AUTHOR]

Introduction: This study used artificial intelligence and strategic management to predict sports industry development in Taiwan. Through public government information, we aimed to determine the dynamics of the sports industry and analyze the current situation of domestic sports industries and sports industry sectors. We also explored national sports policies and development issues to construct a Taiwan Sports Industry Gross Domestic Product Forecasting Model that aligns with the requirements of government agencies and the sports industry. Methods: This study explored time series data for 12 sports industries and 40 sports industry sectors from 2009 to 2018. We used artificial neural networks to predict future gross domestic product (GDP). We also used the moving average method to calculate the trend direction and used strategic management and brand positioning analysis to analyze industry positioning and trend development. Results: Only one sports industry, Sports Venue or Facility Construction, had an optimistic forecast for growth, while the GDP of the remaining 11 sports industries was predicted to decline. The average GDP forecasting accuracy for the sports industry was 94% in 2017 and 97.2% in 2018. Among the 40 sports industry sectors, eight had growth forecasts, while the GDP of the other 32 sectors was predicted to decline. The average GDP forecasting accuracy for sports industry sectors was 99.5% in 2017 and 99.4% in 2018. In the strategic matrix analysis, all 12 sports industries showed a growth trend. All sports industries showed a consistent upward trend in the GDP time series, indicating overall continuous growth in the sports industry. Similarly, among the 40 sports industry sectors, the Star and Cash Cow sectors showed growth trends and trend lines in the strategic positioning matrix and GDP time series. In contrast, the Question Marks and Dogs sectors showed declining trends and trend lines. Conclusion: This study makes six specific recommendations: (1) Seek solutions for the sports industry through prediction and estimation, (2) use strategic management to chart the course for developing the sports industry, (3) explore and propose future trends in the sports industry, (4) explore and propose future trends in the various sports industry sectors, (5) define the scope of the sports industry and address significant data management and its implications, and (6) foster research and development in technology management and its academic applications. These recommendations aim to provide valuable insights and guidance for the advancement and strategic planning of the sports industry, considering future trends and technological advances. [ABSTRACT FROM AUTHOR]

We study how foreign financial developments influence the conditional distribution of domestic GDP growth. We propose a method to account for foreign vulnerabilities using bilateral-exposure weights when assessing downside macroeconomic risks within quantile regressions. For an advanced-economy panel, we show that tighter foreign financial conditions and faster foreign credit-to-GDP growth are associated with a more severe left-tail of domestic GDP growth, even controlling for domestic indicators. Incorporating foreign variables improves estimates of domestic GDP-at-Risk, both in and out of sample. Decomposing GDP-at-Risk into domestic and foreign origins, we show that foreign shocks are a key driver of domestic macroeconomic tail risks. [ABSTRACT FROM AUTHOR]

Islamic banking is among rapidly-growing components in the world's financial system. Within its institutions, continuous criteria of efficiency facilitate the evaluation of the impact of the reforms and policies on the banks' performance. In this paper, we employ the Multivariate Adaptive Regression Splines (MARS) method for estimating the efficiency of Islamic banks in developed and developing countries. MARS is a well-known efficient method for the flexible modelling of high-dimensional data. Unlike previous work, using a nonparametric technique of such a robustness instead of parametric approaches contributes to the improvement of the various estimates, which provides investors with accurate and timely information they can immediately react upon for a better decision-making in turbulent times. On the one hand, the results of the experiments show that, in the emerging region, there is evidence of a strong linkage between Islamic banking efficiency and gross domestic product. On the other hand, in the developed region, the efficiency is rather based upon Sharia Supervisory Board and board committees. These outcomes confirm previous works showing that governance-related variables have a significant positive effect on Islamic banking efficiency. Furthermore, the overall MARS-based predictions reveal that Islamic banks operating in developed countries are relatively more efficient than their counterparts in emerging countries. [ABSTRACT FROM AUTHOR]

In this study, the nexus between Foreign Direct Investment (FDI) and financial deepening is critically examined. The study employed a robust dynamic panel cross‐sectionally augmented distributed lag method for 31 countries in sub‐Saharan Africa (SSA). The results reveal that: (1) a strong significantly positive long run impact of FDI on financial deepening exists; (2) real gross domestic product (GDP), trade openness and government effectiveness stimulate the positive FDI–financial deepening nexus; (3) the strength of the FDI–financial deepening nexus also depends on the percentile position in the income distribution of SSA countries (countries in the upper strata of the income distribution evidently had stronger FDI–financial deepening relations than those in the lower strata and (4) real GDP, trade openness and government effectiveness also enhance financial deepening in SSA. The study recommends that governments in SSA should foster fiscal, financial and regulatory incentives for attracting FDI for improved financial depth in SSA by: strengthening the regulatory frameworks and institutions of governance through the removal of unwarranted governmental interferences in the administration of justice and electoral processes; removing multiple tax regimes; and stabilizing prices and exchange rate volatility via stimulating local productivity and guaranteeing the rule of law, political stability and security of life and property in the region. [ABSTRACT FROM AUTHOR]

The thorny issue and contradictory conclusions on dividend payments and firm value are not ending any time soon. The existence of a divergence of findings in the literature suggests the need for further empirical studies on this subject matter. Therefore, this study focuses on how a firm's cash flow influences dividend payments in Ghana. Using data from 2015 to 2020, pooled ordinary least squares and random effects estimation, this study provides evidence of dividend payments in Ghana. The results show that dividend payments are influenced by a firm's net cash flow from operations, free cash flow to equity, firm size, and age. The relevant macroeconomic variables for dividend payments are inflation and gross domestic product growth. Another finding is that the more nonfinancial firms take on the characteristics of financial firms, the less dividends they pay. Managers of listed firms in Ghana should grow the size of their firms; however, this should be done in a manner not to expropriate value to managers as predicted in the Jensen agency problem associated with free cash flow. [ABSTRACT FROM AUTHOR]

The article explores the non‐linear relationship between oil prices, inflation, and GDP in eight African countries that import oil from other nations. The study uses various econometric techniques, including symmetric and asymmetric dynamic panel ARDL models, mean group, and pooled mean group approaches, to examine quarterly data from 1983 Q2 to 2020 Q4. The analysis looks at both short‐term and long‐term variations to measure the positive and negative effects of oil prices and inflation on GDP. The findings reveal that the variables are related, but there are significant non‐linearities in the long run. While both rising oil prices and inflation have a positive impact on GDP in most instances, lower oil prices and inflation might have a neutral or negative impact. [ABSTRACT FROM AUTHOR]

Invasive alien plants (IAPs) have serious environmental and economic impacts, especially in vulnerable areas of China. However, IAP richness distribution patterns, their driving factors, and the dynamic shifts in potential distribution areas remain elusive. We assessed IAP richness distribution patterns and drivers using 402 IAPs recorded in China at 88 926 occurrence points, and then predicted their potential distribution areas. The results show that IAP hotspots were mainly located in southeastern China, especially coastal areas of the South and East and large inland cities. Population density, gross domestic product (GDP), and four climate variables associated with precipitation and temperature jointly influenced the richness distribution pattern of all IAPs. Specifically, population density and GDP impacted the richness distribution pattern of narrow‐range IAPs, and population density, GDP, distance to the nearest national highway, and five climate variables affected the richness distribution pattern of widespread IAPs. Only GDP contributed significantly to the richness distribution pattern of the top 5% hotspot grid cells, whereas population density, GDP, and precipitation in the driest month (BIO14) significantly influenced the richness distribution patterns of hotspots for both the top 10% and top 20%. Prediction analysis demonstrated that southeastern China would have particularly high invasion risk under both current and future climate scenarios. Regions with increases in predicted species richness are more common (44.83–64.97%) than those with decreases, except under the Representative Concentration Pathway (RCP) 4.5 scenario. Climate change will contribute greatly to the expansion of potential IAP distribution areas under both optimistic (RCP 2.5) and pessimistic scenarios (RCP 8.5). The results of this study provide insights into the priority management of IAPs by developing promising strategies for the control and prevention of IAP invasion. [ABSTRACT FROM AUTHOR]

• Manufacturing share in India's GDP has increased by about 16 percentage points between 2003 and 2018. • Dominant contribution to increased manufacturing GDP share is made by petroleum refining. • There has been a tremendous increase in the real value-added share of ICT equipment industry. • For assessing properly the performance of manufacturing, double-deflation of GDP is essential. Contrary to a widely held impression that the share of manufacturing in India's GDP has long stagnated, the paper claims that it has increased significantly. Measured at the prices of different goods and services prevailing in 2004-05, and deflation applied separately with input prices as well as output prices to account for differential input price trends, the GDP share of manufacturing has increased during the post-reform period from about 17 per cent in 1993-94 to about 32 per cent in 2018-19. The paper notes that the concept of real share in GDP relates to the volume effect and represents the change in the share of the volume of manufacturing activity out of the volume of all economic activities in the Indian economy. Some explanation is provided for the apparent stagnancy of the share of manufacturing in India's GDP at current prices. [ABSTRACT FROM AUTHOR]

Financial processes have changed how economic growth is carried out, yet little research has been done examining how financialization affects the well-established association between economic activity and emissions. We construct fixed effects regression analyses with robust standard errors for 172 nations between 1960 and 2014. In this article, we estimate financial processes' moderation of the association between GDP per capita and CO2 emissions per capita, as well as whether or not such processes reduce the environmental intensity of manufacturing activities. We find that financialization decouples total GDP per capita from emissions per capita but fails to do so for growth from manufacture. Noting the absolute rise in manufacturing activity, we argue that the economic reorganization that financialization represents may obfuscate the ongoing pressure that economic growth places on the environment. [ABSTRACT FROM AUTHOR]

This article uses multilevel analysis of 24 European countries to examine the effects of macroeconomic variables (GDP and unemployment) and welfare state interventions (active and passive labour market policies) on job insecurity and job quality in Europe from the mid‐1990s until the last 2021 COVID crisis. The paper makes a distinction between the crisis of the welfare state and the reaction of welfare states to crises and connects the job quality literature with that on the transformation of the welfare state. The article introduces several innovations to the literature by looking at the impact of welfare state interventions on multidimensional job quality, distinguishing between different types of active labour market policy spending and considering the generosity of benefits. The findings show that active labour market policies (ALMPs) and passive labour market policies (PLMPs) have a positive effect in reducing job insecurity across skill groups. ALMPs and PLMPs also improved several dimensions of job quality, but mostly among manual/low‐skilled workers, while they have a negative effect on work pressure which mostly affects medium‐ and high‐skilled workers. The article concludes by discussing how, due to the reach of ALMP and PLMP interventions, the positive effects of the welfare state on job quality are concentrated among lower‐skilled workers, thereby limiting the ambition of contemporary welfare states to generate positive spillover effects on the quality of work for all workers. [ABSTRACT FROM AUTHOR]

Cross-border cooperation is a major instrument of European policy to overcome the barriers posed by national borders and correcting regional imbalances. But the question of whether it is leading to the convergence of cross-border regions (CBRs) is still open for debate, given the significant heterogeneity of borders and the localized and spatially bound nature of many border effects. This article analyses the beta and sigma convergences in GDP per capita growth for the NUTS-3 at the Portuguese-Spanish border between 2000 and 2018, also considering their population growth. The main finding is that, even if their population growth is below the national averages, the CBR is converging in economic terms. This convergence is visible in the reduced dispersion of the GDP in the border regions and is also confirmed by spatial models, which showed that being a border region increases the probability of having above-average growth rates and that the NUTS-3 with initially low GDP in the cross-border region were also growing above average. This convergence was found to be robust, considering different model specifications and important factors for convergence, such as population growth and spatial dependence. A negative relationship between population and GDP per capita growth was found. [ABSTRACT FROM AUTHOR]

We document a walk-down in gross domestic product (GDP) growth projections that is akin to that in sell-side analysts' earnings forecasts. While the walk-down in earnings forecasts has been generally attributed to the strategic interplay between corporate managers and sell-side analysts, professional macro forecasters affiliated with the Federal Reserve are less susceptible to outside pressure. Our evidence shows that countercyclical variation in forecasting difficulty, due to asymmetry in the steepness of economic downturns relative to upturns, is relevant in explaining the walk-down in macro forecasts. Without rejecting the expectations game between managers and sell-side analysts, our article offers a more auspicious characterization of forecast walk-downs whereby such patterns can surface even without conditioning on strategic incentives for bias. An overarching implication is that research on the properties of sell-side analysts' forecasts should consider strategic incentives for bias interacted with information about the state of the economy and heterogeneity in the cyclical exposure of individual firms. [ABSTRACT FROM AUTHOR]