Search

Introduction: This study investigates the relationship between economic growth, clean fuel utilization, trade, and environmental pollution. By focusing on the potential of clean fuels and trade in reducing pollution, this research aims to understand their role in promoting environmental sustainability in China from 1990 to 2020. Methods: The study employs the Nonlinear Autoregressive Distributed Lags (NARDL) approach to analyze time series data. This method enables the decomposition of impacts from clean fuels and trade on pollution levels, facilitating an understanding of their distinct contributions to environmental outcomes. Results: Findings indicate that economic growth is associated with an increase in pollution levels, while clean fuel usage exhibits a modest but significant reduction effect. Nonetheless, the relatively small coefficients highlight the need for a greater share of clean fuels in China's energy mix. Additionally, trade shows a significant negative relationship with pollution emissions, with data reflecting a gradual decline in pollution over time. Discussion: These results underscore the benefits of clean fuel adoption and trade promotion as effective measures for mitigating pollution. However, they also highlight the necessity for stronger regulatory policies, public awareness initiatives, and investments in sustainable technologies to ensure China's long-term environmental sustainability. [ABSTRACT FROM AUTHOR]

The economic development of N-11 countries has been significantly influenced by the contributions of natural resources (NAT) and economic globalization (EG). These countries have been facing drastic environmental problems for several years. Hence, it is imperative to ascertain the environmental ramifications of natural resource extraction activities in the N-11 nations. In doing so, this study examines the impact of gross domestic product (GDP), EG, and NAT on ecological footprints (EF) within the time frame of 1971 to 2022 in the group of N-11 countries. After verifying the cross-sectional dependence, this work found the integration of all variables at first difference. To provide short and long run econometric results; this study utilizes cross sectional autoregressive distributed lag (CS-ARDL). The findings indicate that the presence of NAT rent has a detrimental impact (0.03%) on the ecological quality within the N-11 nations. Moreover, it can be argued that both EG and GDP exhibit environmentally sustainable characteristics over an extended period by (0.03% and − 3.12%) respectively. This study does not provide evidence for the presence of an N-shaped Environmental Kuznets Curve (EKC) in the N-11 nations. Based on the findings, a policy recommendation is proposed for the nations in question. These countries must immediately implement and enforce robust environmental laws while fostering a heightened sense of environmental consciousness. It is imperative for emerging economies to increase their investments to explore and adopt efficient technologies in various economic sectors, including mining. [ABSTRACT FROM AUTHOR]

The advent of Industry 4.0 is imminent, with the internet emerging as a pivotal catalyst for this impending revolution as general-purpose technology (GPT). This study examines the transformative impact of internet penetration on economic development and employment dynamics in Bangladesh. Leveraging time series data from 1996 to 2022, and employing Vector Error Correction Model (VECM) and Linear Projections (LP) methodologies, the research reveals significant insights into the relationship between internet penetration, ICT exports, GDP growth, and employment trends. Findings indicate that a 10% increase in internet penetration led to a notable 4.7% rise in ICT exports and a marginal 0.8% increase in GDP, albeit with a concerning 1.1% decline in formal sector employment. While highlighting the positive influence of internet connectivity on trade and economic activities, the study underscores the challenges of job displacement and the need for inclusive and equitable growth strategies in the face of technological big push. [ABSTRACT FROM AUTHOR]

Purpose: This study aims to analyze the development of the Global Knowledge Index (GKI) (published by the United Nations Development Program (UNDP) and Mohammed Bin Rashid Al Maktoum Foundation (MBRF)) for Arab countries according to their income levels and to assess the impact of the level of knowledge on economic growth and per capita GDP in Arab countries during the period (2017-2021). Methodology: The study covers a sample of the following Arab countries: (UAE, Qatar, Bahrain, Saudi Arabia, Kuwait, Oman, Jordan, Algeria, Lebanon, Tunisia, Egypt, and Morocco). Two econometric models were conducted using panel data based on the (GKI) reports: the first model estimates the impact of knowledge on GDP in Arab countries, while the second model estimates the impact of knowledge on GDP per capita for the same sample. Findings: Although the study results reveal a noticeable decline in the level of knowledge in the Arab countries at their various income levels during the study period, the best performance was positively associated with income level. It is also found that the level of knowledge is statistically significant and positively affects the gross domestic product; meanwhile, it does not have a statistically significant impact on per capita GDP. Conclusions and Recommendations: Several factors could explain why the knowledge index has a statistically significant impact on GDP growth, while no significant impact on per capita GDP in Arab countries; among them: high population growth, structural issues like unemployment and skill mismatches, heavy reliance on specific sectors such as oil and gas, income inequality, weak governance, and cultural barriers. The study recommends that Arab countries should direct their economies towards more reliance on knowledge which will be reflected positively in their economic growth. In addition to creating partnerships with the private sector to convert research and innovations into successful economic opportunities that increase the knowledge-added value. [ABSTRACT FROM AUTHOR]

Doughnut Economics is an economic model designed to overcome the negative impact that the crude use of Gross Domestic Product (GDP) can have on both society and the environment. As the model becomes more widely adopted it is important to explore the model from a theological perspective. Early Christian economic thought provides a way of exploring and challenging many of the fundamental ideas and conceptualisations of the DE model. DE has much to learn from early Christian thinkers. Firstly, a non-absolutist understanding of property can fuel calls for a more radical distribution of wealth than called for in DE, with an even greater emphasis on the process and benefits of individual almsgiving. Secondly, it shows how the limitations of the social foundation of DE has much to learn from the positive value of the ascetic lifestyle promoted by some early Christian thinkers. Finally, at a time when there are understandable concerns about the limits of the ecological ceiling, early Christian thought offers both hope and a call to action. [ABSTRACT FROM AUTHOR]

Copyright of International Journal of Professional Business Review (JPBReview) is the property of Open Access Publications LLC and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Given the need of the Agricultural Development Fund to measure its contribution in a quantitative manner to agricultural and economic development, this research was aimed to estimate the relative importance of the contribution of Agricultural Development Fund on agricultural output, gross domestic product and economic growth rate of Saudi Arabia during the period 1990–2019, using econometric analysis and binomial probability distribution. The study showed the instability of both agricultural loans and economic growth rate during the study period, where the coefficient of variation reached 120.5% and 133.3% for each, respectively. The Agricultural Development Fund plays a significant role in the Saudi economy, as its contribution to agricultural output ranged between a minimum of 1.8% and a maximum of 27.0% at a 95% confidence level. The upper limit of the Agricultural Development Fund's contribution on GDP was 2.81% at a confidence level of 95%. The upper limit of the Agricultural Development Fund's contribution on economic growth rate was 0.115% at a confidence level of 95% during the study period. As for the contribution of the agricultural sector on the economic growth rate, it reached a maximum of 0.381% at a confidence level of 95% during the period 1990–2019. Finally, this study recommends the need for the Agricultural Development Fund to reconsider the lending policy so that it does not depend only on collection rates, in addition to preparing a study on local agricultural investment, so that it can take advantage of the relative characteristics of the productive areas and choose projects characterized by a high internal rate of return and its ability to raise Standard of living for the largest number of people. Increasing the lending rates to expand the number of productive projects to be established or expanding existing projects to increase the value added in the Saudi economy and then increase the contribution of the Agricultural Development Fund to the gross domestic product. [ABSTRACT FROM AUTHOR]

The significance of the transportation sector, notably in terms of the carbon emission factor, is an undeniable fact. Along with this fact, individuals' transportation preferences depend on their income levels. In this context, when the issue is considered, the income level in the USA pushes people toward cheap air travel. The main reason for this is that it is cheap, accessible, and transports one to their destinations quickly. Thus, from the perspective of road transportation, bus transportation is popular among the public. The reason why both air and road transportation modes are empirically evaluated together through income distribution is due to the preference of the US people. In this context, the effectiveness of active transportation on both air and highways in the USA from 1975 to 2023 is investigated by taking into consideration the income distribution. Empirical findings obtained through the FMOLS, DOLS, CCR, and NARDL models demonstrate that all independent variables, including GDP, energy use, air transportation, and the Gini coefficient, affect carbon dioxide emissions. In addition, wavelet analysis is performed to comprehend the form of and fluctuations in the series, which are vital to monitoring the periodical changes. [ABSTRACT FROM AUTHOR]

This study aims to explore and test the relationship between GDP and renewable electricity output, renewable energy consumption, and total natural resource rent in Indonesia. It uses Vector Error Correction Model (VECM) analysis on World Bank data from 1995 to 2019, with a primary focus on Indonesia, to investigate the complex relationship between GDP and key sustainability metrics. This analysis highlights how Indonesia's economic growth is influenced by changes in the consumption of renewable energy, utilization of natural resources, and its impact on the environment over a span of 25 years. Ultimately, this research provides important insights for policy makers and researchers on Indonesia's evolving sustainability landscape, thereby facilitating the development of strategies that balance economic growth and prosperity, and environmental conservation. [ABSTRACT FROM AUTHOR]

The trade-off policy framing has been a central feature of green growth since the 1980s, employed to frame the countervailing spheres of social, environmental, and economic policies purported to ensure the sustainable development of the global economy. This article argues that so central has this framing become that IPE scholars have tended to focus on different types of 'greenable' growth observable within capitalism, rather than question the prospect of greening growth itself. Far from value-free, the trade-off framing is ultimately determined by the structural imperative for economic growth, veiling the disciplines anthropocentric ontology in a normative or objective guise. To account for the tacit prioritization, the trade-in policy framing – the compromising of environmental objectives to accommodate the growth imperative – is advanced as an alternative framing. The trading-in of environmental policies is legitimized through political-industrial narratives, of which three, the (i) consequential, (ii) allay, and (iii) finance are outlined in this analysis. [ABSTRACT FROM AUTHOR]

While traditional economic forecasting models have significantly improved, a few significant obstacles must be overcome. Conventional methods include time series and econometric models, which may rely hugely on historical data and are underlain by linear assumptions. These models fail to handle sudden shifts in the market or unseen economic events, like the financial crisis of 2008 or the COVID-19 pandemic 2020. Traditional models also need help bottling the vast amounts of unstructured data available today: articles, social posts, and other real-time information streams that influence economic sentiment. The chief objective of this research project is to explore the efficacy of AI-driven predictive modeling in forecasting US economic trends. This research project involved a time series analysis of three key financial indicators: Most notably, the Consumer Price Index (CPIAUCSL), the Gross Domestic Product (GDP), and the Unemployment Rate (UNRATE). Datasets entailed the Consumer Price Index for All Urban Consumers (CPI) from 1950 to the present, GDP: U.S. Gross Domestic Product (GDP) quarterly, and UNRATE: US Unemployment Rate (UNRATE) from 1950 to the present. These datasets provided valuable insights into the US economy, and this analysis aims to explore trends, seasonality, and relationships between these variables over time. One of the most immediate benefits for policymakers and the U.S. government is the significant improvement in the accuracy and timeliness of economic forecasts enabled by AI-driven models such as the ARIMA and SARIMAX. Another vital implication of AI-driven economic forecasting is improving policy formulation based on more sophisticated scenario analysis and simulations. AI-driven forecasting facilitates more targeted and proactive policy intervention, which is helpful in such sector-specific issues or regional disparities in economic performance. [ABSTRACT FROM AUTHOR]

Deforestation poses a significant environmental challenge that demands global efforts to address, aiming to preserve forest ecosystems and promote sustainable development worldwide. This study investigates the global phenomenon of deforestation convergence from 1990 to 2020 across 149 countries, employing state transition probabilities assessed using Markov chains, dispersion indicators, and average deforestation rates. The analysis indicates a consistent decrease in dispersion indicators and average deforestation rates observed across the studied countries over three decades, coupled with high probabilities of maintaining current forest ecosystem states. These findings suggest the presence of sigma and beta convergence phenomena in the shift towards sustainable development, akin to patterns observed in economic growth. Furthermore, our research identifies the emergence of a Kuznets curve based on deforestation growth rates and dispersion indicators relative to GDP per capita since 2010. This also suggests a potential global convergence in sustainable forest-related activities. Hence, it is clear that coordinating environmental development policies among countries is crucial for achieving global ecological stability. This underscores the necessity for proactive measures to ensure worldwide forest conservation and sustainable management. [ABSTRACT FROM AUTHOR]

The quality of nighttime light (NTL) data is an important factor affecting the estimation of gross domestic product (GDP), but most studies do not use the latest NPP/VIIRS V2 annual composite product, and there is a lack of China's GDP estimation products in recent years. To address this problem, this paper studies the NPP/VIIRS remote sensing estimation method for the GDP in mainland China from 2013 to 2023. First, the remote sensing data are preprocessed, and the noise masking method is used to remove outliers. The total amount of NTL, average NTL value, and comprehensive NTL index data are extracted. Combined with the GDP data from the Statistical Yearbook, a fitting model of the GDP and NTL index is constructed. The differences between different GDP estimation models are compared and analyzed, and the optimal model is selected as the estimation model. In addition, through the optimal fitting model, GDP spatial estimation products from 2013 to 2023 are produced. Moreover, the spatiotemporal variation characteristics of the GDP in mainland China are analyzed, with a focus on the spatiotemporal variation of GDP decline regions and the changes in the GDP rankings of provinces and cities. The main conclusions include the following: (1) In the time regression analysis, the linear model MNL has a strong correlation with the GDP, with an R2 of 0.972. This model is selected as the optimal fitting model to calculate the spatial data of the GDP. (2) The spatial distribution of the GDP in mainland China is high in the east and low in the west, and it shows a characteristic of extending from the provincial capital to the surrounding cities. The connectivity between adjacent high-GDP areas continues to increase. (3) From 2013 to 2023, the GDP in most parts of China showed an upward trend, with 98.56% of pixels growing and only 0.99% of pixels declining. The declining pixels are mainly distributed in heavy industrial cities supported by fossil fuel resources, such as Ordos, Daqing, Aksu, etc. (4) Compared with statistical data, the overall difference of the GDP estimated by NTL data is not large, and the relative error is between 0.04% and 1.95%. From the perspective of the GDP ranking of each province, the ranking of most provinces is not much different, fluctuating between ±2. A small number of provinces have large ranking differences due to reasons such as dominant industries and power supply. By spatializing the GDP data of mainland China in the past 11 years, the spatiotemporal changes of the GDP within mainland China were analyzed. The research results can provide support for government economic decisions such as urban development. [ABSTRACT FROM AUTHOR]

This study investigates the correlation between the Gini index and gross domestic product (GDP) in two of the world's largest capitalist economies: the United States and the United Kingdom. Utilizing econometric methods, including stationarity tests and linear regression, this research work aims to elucidate the relationship between economic inequality and economic growth. The results for the United States reveal a significant positive correlation between GDP and the Gini index, suggesting that economic growth is associated with rising income inequality. In contrast, the United Kingdom shows a much weaker relationship, indicating that other factors, such as redistributive policies and social welfare programs, may mitigate the impact of economic growth on income inequality. These findings highlight the importance of national policies and institutional frameworks in shaping economic outcomes and can be used in policy making. This study contributes to the existing literature by providing a comparative analysis of the correlation between GDP and the Gini index in two major capitalist economies, offering fresh empirical insights. [ABSTRACT FROM AUTHOR]

ABSTRACT Gross domestic product (GDP) is frequently used as a proxy for well‐being. Such use of GDP is problematic for many reasons, for GDP excludes activities that contribute to well‐being and includes others that have a negative impact instead. As a result, a vast array of metrics has been developed to complement or replace it and put well‐being at the heart of policymaking. Nonetheless, previous research has shown that their use and impact on policymaking has been limited. This article examines the use and impact of well‐being metrics according to their own developers and intended users in the crucial cases of Scotland and Italy, focusing specifically on the two countries' official well‐being frameworks. Despite being at the forefront of the well‐being debate, both countries have never been studied in this regard before. This article fills this gap, collating views from more than 100 stakeholders, including statisticians, members of interest groups, policymakers and journalists. Findings show that the vast majority of informants could not cite any examples of cases in which either framework impacted on policymaking, or in which they themselves had used these. In some cases, this was due to them not being aware of what such frameworks were in the first place. Those who could identify some examples were those who were or used to be part of the government. Examples would, however, tend to be vague, in some instances remarkable yet merely anecdotal, and still in others the result of an ‘ex‐post rationalisation’. [ABSTRACT FROM AUTHOR]

Global challenges, such as the COVID‐19 impacts, climate crisis, and geopolitical tensions, have prompted economic transformations. These issues have led to macroeconomic data assuming non‐normal distributions, necessitating a nonlinear analytical approach. As a result, this study unveils the influence of energy intensity, renewable energy, economic growth, and financial development on carbon dioxide emissions in Iceland from 1995Q1 to 2020Q4 using the Quantile‐on‐Quantile Kernel‐Based Regularized Least Squares (QQKRLS) and Wavelets Quantile Correlation (WQC) methods. The QQKRLS results showed that energy intensity, renewable energy, and economic growth are negatively associated with carbon dioxide emissions across various quantiles, while financial development is positively linked with carbon dioxide emissions. Furthermore, the WQC outcomes confirm the results of the QQKRLS. In addition, in the short and medium term, financial development negatively affects carbon dioxide emissions across various quantiles, while in the long term, financial development positively influences carbon dioxide emissions. In light of the results gleaned from this study, Iceland should continue on its path of renewable energy investments, create policies that will completely decouple economic growth from carbon dioxide emissions, and ensure that the development of the financial system is funding clean energy activities. This provides a roadmap for sustainable economic and environmental development. [ABSTRACT FROM AUTHOR]

M‐RAS plays a crucial role in the RAF–MEK signaling pathway. When activated by GTP, M‐RAS forms a complex with SHOC2 and PP1C, initiating downstream RAF–MEK signal transduction. In this study, the crystal structure of the GDP‐bound human M‐RAS protein is presented with two forms of crystal packing. Both the full‐length and truncated human M‐RAS structures aligned well with the high‐confidence section of the AlphaFold2‐predicted structure with low r.m.s.d., except for the Switch regions. Despite high sequence similarity to the available mouse M‐RAS structure, the full‐length human M‐RAS structure exhibits unique crystal packing. This inactive human M‐RAS structure could offer novel insights for the design of selective compounds targeting M‐RAS. [ABSTRACT FROM AUTHOR]

The target of the manuscript is to quantify and examine the effects of public saving on agricultural and fishing investments for the government and private sectors and economic growth in Iraq for the period 2005-2021. Econometric tools were used to clarify the impact (autoregressive model with distributed lag periods). The findings show that there is cointegration relationship between public saving (S) independent variable, government investments in agriculture, and fishing (GI) dependent variable, private sector investments in agriculture, fishing (PI) dependent variable, and economic growth (GDP) dependent variable, Moreover the value of the error correction parameter significant Generally speaking at the degree of negative (1%) and (5%) for all variables. The results indicated that there was a significant and positive short-term relationship between (S) and (GI) at a significance level (5%), in addition to the absence of a lengthy effect between the two elements that during the study period. There is also no substantial impact of public saving on private investment in agriculture, forestry, and hunting during the research period, neither in the short term nor in the long term. The results also showed that there is a significant and positive short-term relationship between (S) and (GDP), and the presence of a long-term favorable impact at a substantial degree (5%), which means that increasing public saving by one unit results in a rise in GDP of (0.001577). Conversely, a decrease in public saving by one unit leads to a decrease in GDP by the same amount, assuming other factors remain constant. This report suggests that the Iraqi government be given more authority through its economic policies in driving savings and employing it towards investment in the agriculture industry to boost and diversify agricultural output. [ABSTRACT FROM AUTHOR]

Human capital is accepted as an indicator of individuals' education, experience, knowledge and skills. Having a high level of human capital is one of the factors that facilitates the process of adaptation for immigrants to their new country of residence. On the other hand, the level of human development attracts immigrants to these regions with factors such as better living conditions, human rights and employment opportunities. Therefore, countries with strong human capital and human development elements are attractive for people who want to migrate due to features such as strong labor markets, quality of life, educational opportunities and economic development. The aim of this study is to examine the impact of human capital on migration in European Union (EU) countries through the mediating roles of human development and Gross Domestic Product (GDP) per capita. In this context, a model proposal was presented and path analysis was carried out with SEM with the data of EU countries between 2000 and 2020. Analysis findings show that human capital has a significant and positive effect on migration. On the other hand, it was concluded that human development and GDP per capita mediate the relationship between human capital and migration. [ABSTRACT FROM AUTHOR]

In the scope of this study, we delved into a thorough exploration of the intricate relationship between PISA study outcomes and a spectrum of socio-economic variables across 33 diverse countries. Our analytical approach harnessed the power of multivariate linear regression models, executed using STATA, a reliable and robust statistical software. These models served as a precise tool to effectively gauge the influence of a multitude of factors on PISA scores, thereby offering a nuanced understanding of the dynamics at play. However, we didn't stop at mere regression analysis. We further enriched our investigation by embracing the K-means clustering method. This clustering approach allowed us to classify countries into distinct groups based on shared characteristics related to PISA scores and socio-economic factors. By doing so, we unlocked a deeper layer of insight into the unique patterns and commonalities within the dataset, shedding light on the complex interplay between education, socio-economic variables, and the broader landscape of economic development. The amalgamation of these two analytical methods presented a holistic perspective, enabling us to unravel the multifaceted interactions that underlie education outcomes and socio-economic conditions. These findings, ripe with implications, offer valuable guidance for policymakers, educators, and researchers alike, as they grapple with the challenges of enhancing educational quality and promoting sustainable economic development. [ABSTRACT FROM AUTHOR]

The human race has been confronting the issue of poverty which is threatening its continued existence for a long time. Poor access to finance can lead to poverty this breeds health issues, lack of access to social and recreational facilities, social delinquencies, reduced living standard, malnutrition and economic difficulties. The goal of defeating poverty in its various ramification remains a cardinal concern for policy formulators in the Nigerian state and international bodies such as the World Bank and United Nations. Following the thriving emergence of financial technology (fintech) in Nigeria, there exist a dearth in academic researches to examine how fintech can be a driver in the reduction of poverty. This study examined the impact of financial technology on poverty reduction in Nigeria. Data on poverty rate, financial technology, mortality rate, literacy rate and gross domestic products were obtained from the National Bureau of Statistics (NBS) in Nigeria and the Central Bank of Nigeria (CBN) statistical bulletin for the period of 1991 - 2021. This study employed the multiple linear regression estimation technique to analyse collected data as it examines a cross-section of major key independent variables across a time series data, on the premise of a common effect model. Data analysed indicates a negative and significant nexus between poverty rate and financial technology innovation. The result also suggest that literacy rate and poverty rate have a negative and insignificant relationship. The poverty rate was also found to be positively and insignificantly related to mortality rate and gross domestic products respectively. The study findings have several significant policy implications. Firstly, infrastructures that support internet and mobile telephony should be expanded by providing incentives for investment since technology is the backbone of the operations of fintech. Secondly, education on fintech, information communication technology and finance should be increased to fill the gap among citizens who are not technological inclined especially in the rural areas to increase the use of fintech. Lastly, there should be further regulatory interventions through reforms to remove the barriers to credit. [ABSTRACT FROM AUTHOR]

This paper analyzes the persistence of the sovereign debt / GDP and sovereign debt / GDP per capita series for the five largest European economies and the US using fractional integration. We use historical data starting in 1800 for the US and the UK, in 1861 for Italy and in 1880 for Germany, France and Spain. The results indicate high degrees of persistence of debt-to-GDP and debt per capita ratios with clear evidence of no mean reversion in both debt indicators. We also find evidence of correlation with the primary deficit, supporting the idea that one of the causes of this debt persistence is precisely the primary deficit persistence. Empirical results support the need for a better coordination between fiscal and monetary policies to enhance debt control in the countries under examination. [ABSTRACT FROM AUTHOR]

Information technologies have become an integral part of the modern economic environment and social life in Ukraine and the EU. The development of the IT industry in various countries demonstrates significant potential to stimulate economic growth. The article is aimed at assessing the impact of IT exports on the macroeconomic indicators of Ukraine, Poland, Estonia and Germany in order to formulate recommendations for the development of the IT industry in Ukraine. The study examines the impact of the export of IT services on GDP, GDP per capita, foreign direct investment and unemployment rate on the example of these countries by calculating the Fechner correlation coefficient. Based on the analysis of data from 2012-2022, it has been discovered that IT exports have a considerable positive impact on GDP and GDP per capita. In EU countries, the export of IT services also positively influences FDI attraction and the employment level. Despite the growth in the export of IT services, Ukraine shows adverse tendencies in the FDI volumes and increasing unemployment. In Ukraine, there is an inverse weak relationship between the amount of FDI and the IT service exports (Fechner correlation coefficient -0.2727) and a direct moderate relationship with the unemployment rate (Fechner correlation coefficient 0.4545). Considering the complexity of the challenges to the functioning of the economy during the war, the IT sector alone is unable to negate the impact of all threats to the economy of Ukraine. However, the share of IT exports in the total volume of service exports in Ukraine amounted to more than 45% in 2022. That is, on the one hand, the IT sector is developing despite the war (somewhat slower in 2022 compared to previous years); while on the other hand, a strong imbalance remains in Ukraine regarding the predominant increase in the export of IT sector services. According to the results of a comparative analysis with EU countries, we can say that the export of IT services can become a driver of investment attractiveness and decrease unemployment in Ukraine in the future. [ABSTRACT FROM AUTHOR]

This study aims to measure the elasticity of pension revenues from the General Social Security Regime (RGPS) in relation to the Gross Domestic Product (GDP) in Brazil, considering monthly data from January 1997 to July 2023. Based on a rigorous analysis of stationarity, co-integration and temporal causality, considering the presence of structural breaks, the results obtained from the estimation of an autoregressive vector model with an error correction mechanism (VECM) indicate that social security revenues are elastic in relation to GDP in the long term. [ABSTRACT FROM AUTHOR]

Purpose: The importance of household expenses in creating demand for domestic products causes the factors affecting it to be considered in establishing financial incentives. The studies conducted so far have investigated the effect of financial stimulus on macroeconomic variables partly with closed input-output models. However, like Keynes' consumption theory, this model considers household consumption as a function of current income only. Since it overestimates the relationship between the household sector and the production sector, the results of this model are distorted due to the presence of exogenous consumption within the matrix of intermediate goods. Methodology: To solve this problem, the current research uses a semi-closed inputoutput model with semi-endogenous consumption, which was first introduced by Chen et al. (2016). This model adapts the output to other theories of consumption. Also, due to the removal of false effects caused by the transfer of exogenous consumption to the final demand class, more realistic results are obtained from the government's fiscal stimulus. For this purpose, the present study compares the effects of fiscal stimulus on Iran's gross domestic product in two closed models and a semiclosed model using the input-output table issued by the Central Bank of Iran in 2015. Findings and discussion: The results of this research show that, with a 10% increase in government spending as a financial stimulus, more value added has been created in the agriculture and horticulture sectors and the private residential unit sector. This is because these two sectors have a larger endogenous consumption coefficient than other sectors. It states that the larger or smaller endogenous consumption coefficient is of effect on the intensity of government investment or the increase in government spending affects the value added and the production level. Moreover, the value-added coefficients obtained from the semi-closed input-output model are smaller than those obtained from the closed input-output model, and they eliminate the distortion in the results of the closed model and increase the accuracy of the calculation results. Conclusions and policy implications: To consider the relationship between the household sector and the production sector, a closed input-output model is usually used, but, due to not considering all the factors affecting household consumption, this model cannot calculate the results of policy making. It is because the model overestimates the difference between the household sector and the production sector. To solve this problem, a semi-closed input-output model with semi-endogenous consumption was introduced by Chen’s team. Their model considers all the factors affecting household consumption, hence used for Iranian data in the present study. In this model, due to the calculation of the coefficient of endogenous consumption, the key sectors are specified, and then, due to the elimination of false effects caused by the transfer of exogenous consumption to the final demand class, more realistic results are obtained from predicting the effect of policy on production or other macroeconomic variables. [ABSTRACT FROM AUTHOR]

This study delves into the effect of environmental, social and governance (ESG) indicators on economic growth trajectory of an emerging economy. A sample of firms listed on the ESG index of the National Stock Exchange (NSE) was examined. The findings reveal a positive and statistically significant relationship between ESG performance indicators and economic growth represented as gross domestic product (GDP) per capita. The sample is further segregated into energy and non‐energy sectors, where the aggregate ESG scores exhibited a statistically significant influence on economic growth in both sectors. However, upon a closer examination of the individual ESG pillars, the governance pillar is observed to exert a negative influence on economic performance in non‐energy firms. In contrast, the environment and social pillars show no significant influence. The analysis then employs a unique approach by applying a Difference‐in‐differences estimator to assess the impact of Business Responsibility and Sustainability Reporting (BRSR) regulations, which confirms a positive impact on economic growth after regulations but exclusively within the non‐energy sector. This study underscores the substantial impact of ESG aggregate and individual scores on GDP per capita, which translates to economic growth. [ABSTRACT FROM AUTHOR]

Due to some social, economic, and environmental factors, the under-5 mortality rates in low-income countries (LICs) are usually high. The primary purpose of this study is to determine the impact of health expenditures, electricity consumption, economic growth, renewable energy, urbanization, and fertility rates on the under-5 mortality rates in low-income countries. For the theoretical framework, the Grossman health production theory is conducted. Due to the existence of the cross-sectional dependency problem and the unit-roots problem, the static and dynamic models are employed to evaluate the long-run estimation findings. The static and dynamic models of the fixed effect, random effect, system generalized method of moments, and dynamic generalized method of moments illustrated that health expenditure, electricity, GDP, and urbanization significantly alleviated the infants' mortality rates under-5 in the low-income countries, by contrast, renewable energy, and fertility rates contributed to the increase of the mortality rates under -5. The quantile regression evaluates the validity and robustness of the results. The robust outcomes narrated that health expenditure, electricity, GDP, and urbanization declined the mortality rates whenever the fertility rate increased the mortality rates. The research suggests important policy recommendations for low-income countries. [ABSTRACT FROM AUTHOR]

Addressing interpersonal violence and environmental pollution as a global health crisis has expanded dramatically after the UN's post-2015 Action Agenda for Sustainable Development. This study investigates the asymmetric effects of environmental pollution, economic development, population growth, and unemployment on interpersonal violence across 24 OECD countries over the period 2000–2017 after controlling for human capital, health expenditures, government quality, and alcohol consumption. After confirming that the data are not uniformly distributed, panel quantile regression is employed. The results show that the effect of target variables on interpersonal violence varies across different quantile points. Environmental pollution and population growth appeared to be up-pulling determinants of interpersonal violence while economic growth and unemployment decrease interpersonal violence, especially at the higher quantiles of the distribution. For robustness checks, we further disaggregated interpersonal violence into physical (by the sharp object and by the firearm) and sexual violence. The findings are similar for physical violence, but a negative effect of air pollution on sexual violence is observed. Based on the estimated results, appropriate policy implications are reported to address interpersonal violence issues. [ABSTRACT FROM AUTHOR]

The need for school belonging is crucial for adolescents and affects academic performance (Goodenow, 1993). School belonging refers to the extent to which students feel accepted, valued, and included in their school environment. It encompasses a sense of connectedness to peers, teachers, and the broader school community, contributing to students' emotional and social well-being (Allen et al., 2021). Using selected data from the International Institute of Islamic Thought (2019–2020) and Item Response Theory (IRT), we derived a measure for school sense of belonging across Muslim countries/regions. Three main discriminative items were identified: pride in school, respect from teachers, and community integration. Additionally, the scores of school belonging revealed that students in Tatarstan showed higher levels of belonging, while those in Bangladesh, India, Kenya, Sudan, and Tanzania reported lower levels. We conducted a regression analysis to gain insight into the relationship between school belonging and the country's GDP. The results showed a significant association between school belonging and GDP per capita, indicating that students in wealthier countries tend to have a stronger sense of belonging. These findings have practical implications for educators, researchers, policymakers, and stakeholders in the field of education and social well-being. They underscore the need for schools to focus on pride, teacher respect, and being part of a school community to foster belonging to make a positive impact on students' well-being and academic performance. [ABSTRACT FROM AUTHOR]

Prior to the oil boom, Agriculture accounted for over 60% of Nigeria's GDP. However, the oil boom of the 1970s brought about declining interest in agriculture by the Nigerian Government. This impact is particularly noticeable in the palm oil sub sector where Nigeria, which was the largest producer of palm oil in the world in the 1960s, accounting for 43%, today accounts for just 2% of global output and has become a major importer of palm oil. In recent years, the Nigerian government has sought to wean itself of its over reliance on oil by encouraging diversification of the economy. This article aims to draw the reader's attention to the great prospects available in the agricultural sector, particularly in palm oil production. This article explores the Isenberg model and opportunities for success, barriers of entrepreneurship in Nigeria, entrepreneurial characteristics, and local entrepreneurial role models. [ABSTRACT FROM AUTHOR]

Copyright of Revista Foco (Interdisciplinary Studies Journal) is the property of Revista Foco and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Introducing dental implants into a patient's oral health plan requires a collaborative effort between all members of the care team, including the "implant dentist" and referring general dental practitioner (GDP), should the treatment be carried out in a referral practice. This article aims to discuss the pivotal role referring general dental practitioners (GDPs) play in preparing patients for dental implant placement, whatever the setting for the planned treatment. An overview of the patient referral process is outlined, as is the role of GDPs in the ongoing maintenance of the dental implants and the patient's oral health. Furthermore, this article may be viewed as a road map for GDPs who refer patients to an "implant dentist" as part of their treatment plan. [ABSTRACT FROM AUTHOR]

Purpose: This study aims to examine the share of foreign direct investment (FDI) in creating the value added (VA) of innovative and other industries in Poland in 2004–2020. Design/methodology/approach: In terms of the empirical analysis of FDI stocks, their locations were divided into innovative and other industries. The differences in the creation of VA are presented by domestic and foreign enterprises. The impact of FDI stocks in individual industries on gross domestic product (GDP) changes was assessed using the vector error correction model (VECM). Findings: FDI from innovative industries generated approx. 7% VA of the Polish economy in the years 2004–2020. In 2009–2018, the share of VA of foreign enterprises in innovative industries in Poland showed a faster growth (by 5 pp) than in other industries. The results of decomposition confirm that the level of explanation of GDP by FDI in innovative industries is higher than in other industries. Research limitations/implications: Changes in the classification of activities reduce the time series period available. Practical implications: This study explains the participation of foreign and domestic enterprises in creating VA. The results are useful to pursuing the national investment policy. Social implications: The economic results of domestic and foreign enterprises in the host country affect the economic growth and development and ultimately the socio-economic conditions of life. Originality/value: This work provides some additional explanations for the inconclusive results of international research into the impact of FDI on GDP or the spillovers effects. Its usefulness concerns the detailed impact of FDI by industrial structures on GDP. [ABSTRACT FROM AUTHOR]

Abstract The economic development of N-11 countries has been significantly influenced by the contributions of natural resources (NAT) and economic globalization (EG). These countries have been facing drastic environmental problems for several years. Hence, it is imperative to ascertain the environmental ramifications of natural resource extraction activities in the N-11 nations. In doing so, this study examines the impact of gross domestic product (GDP), EG, and NAT on ecological footprints (EF) within the time frame of 1971 to 2022 in the group of N-11 countries. After verifying the cross-sectional dependence, this work found the integration of all variables at first difference. To provide short and long run econometric results; this study utilizes cross sectional autoregressive distributed lag (CS-ARDL). The findings indicate that the presence of NAT rent has a detrimental impact (0.03%) on the ecological quality within the N-11 nations. Moreover, it can be argued that both EG and GDP exhibit environmentally sustainable characteristics over an extended period by (0.03% and − 3.12%) respectively. This study does not provide evidence for the presence of an N-shaped Environmental Kuznets Curve (EKC) in the N-11 nations. Based on the findings, a policy recommendation is proposed for the nations in question. These countries must immediately implement and enforce robust environmental laws while fostering a heightened sense of environmental consciousness. It is imperative for emerging economies to increase their investments to explore and adopt efficient technologies in various economic sectors, including mining.

Agriculture is the engine of an economy. In Bangladesh, 50% of the entire laborer force is employed in farming, and around 87% of rural families depend on agriculture for any part of their wages. Considering the importance of the agriculture sector in Bangladesh, the study examines the nexus between agricultural output and economic growth. In the finding of this causality, the VECM test has been applied and found the long-run relationship between variables where the rate of restoring the disequilibrium into equilibrium is 66.4%. The research applies the impulse response function and variance decomposition where in both cases, the result implies that the agricultural output is much more significant on economic growth than industrial output, meaning that to be a sustainable economy, the agriculture sector cannot be ignored. The study also provides insights to the policymakers that the agriculture sector should be given much more priority in terms of budget, and the academician should do more research to develop sustainable agro-based products.

The various theories concerning migration are demonstrating that migration is a complex phenomenon, with equally complex and diverse implications. At the same time, society is in constant change, and major shifts at the international level could generate new migratory flows or different perspectives on this phenomenon. The effects of migration manifest in various fields, and the sciences concerned with migration address them specifically in their areas of influence. The most evident consequences appear from a socio-economic perspective. Labour emigration has had significant economic impacts, including reductions in GDP, wage shifts and a weakening of innovation potential and while remittances provide some financial relief, they are insufficient to offset the broader challenges created by labour shortages. The negative long-term effects on competitiveness and productivity underscore the need for comprehensive policy responses to mitigate the economic consequences of emigration. Romania has one of the largest diasporas in Europe, and the economic effects of this migration are vast. By choosing to analyze these two components – GDP and remittances, we can capture both the losses and benefits generated by migration for Romania’s economy. The study of GDP reflects the losses in terms of internal production, while the analysis of remittances shows how these external financial flows can contribute to the stabilization and regional economic development. By focusing on GDP and remittances, our paper will provide a well-founded perspective on the real impact of migration on Romania's economy, using specific data and relevant economic analyses to highlight both the challenges and opportunities.

The topic of the article is investigation of methods used to estimate the quality of life with due regard to regional specific features. The goal of the research is to study the process of altering the ‘quality of life’ definition and to analyze the current methods of appraising quality of life in regions of the Russian Federation in view of finding the dependence between level of social welfare and satisfaction with high standard of quality of life. The article analyzes origin of the notion ‘quality of life’, studies world and Russian practices of estimating the quality of life index in present day conditions and identifies principles of shaping the key indicators of appraisal. The author analyzed experience of the rating assessment of quality of life by Russian and overseas agencies and academic associations. The analysis showed that key elements of indicators take into account such trends as the level of region development, natural and climatic conditions, level of people income, social sphere and labour market. The use of numerous criteria can give an opportunity to obtain an accurate and truthful assessment on the regional level. Factors provided in the article show the necessity to develop uniform approaches on theoretical and methodological levels based on human-centric principles, which can become a key indicator of the general appraisal of social and economic development of regions and a tool of strategic planning.

The BRICS organization is making significant and consistent progress in its development. The 15th BRICS Summit was held in Johannesburg from 22 to 24 August 2023. This summit is a global event that sets the trends and guiding principles for future economic policies. Four of the five BRICS member countries are among the ten largest countries in the world in terms of GDP, territory and population. According to open sources, the total area of the BRICS countries is 39.7 million square kilometers (26.7% of the world’s land surface), and the population is estimated at3.2 billion people (41.5% of the world’s population). The economic potential of BRICS, as the leading economic organization in the world, is more than significant. These competitive advantages in the economy and financial sphere represent an enormous resource of industrial, human and technological potential that can serve as the locomotive of the global economy. Following the conclusion of the above summit, the leaders of the BRICS countries adopted the final “Johannesburg-2” declaration, which noted the advisability of using their countries’ respective national currencies in international trade and collectively resolving problems related to international debt. In addition, decisions were made to expand BRICS and admit new member states to the organization. BRICS has established itself as a prominent entity on the global stage, whose influence in world affairs is consistently strengthening. The strategic course of their unification is aimed at planning for the future and meets the interests of the leading nations of the international community, the so-called world majority. By acting cohesively on the principles of equality, partnership support and mutual consideration, the BRICS member countries are effectively addressing the most pressing issues on the global and regional agenda. The BRICS member states are strongly in favor of the establishment of a multipolar world order that is based on international law and is fair. At the same time, they are committed to adhering to the fundamental principles of the United Nations Charter. BRICS is the most important guarantor of the legal foundations of international relations and a fair world order in general. The recent expansion of the BRICS group is a significant event that enables the group to have an even greater influence in international affairs. The presented article analyzes the features of the recent expansion of BRICS and its impact on world geopolitics, taking into account the admission of new states to the organization. The distinctive features of the BRICS group activities and its role in relation to the G7 and G20 are revealed. The trends in the transition to a multipolar world are discussed. Furthermore, issues of political and economic cooperation between the different BRICS member countries are analyzed.

Military spending is a widely discussed topic, especially in the current geopolitical landscape. Expenditures on “equipment” play a pivotal role in total defense spending.. However, the nature of the equipment expenditures is cumulative. Thus, when trying to estimate the capability of a state we should consider a longer period, not just one year. The aim of this article is, therefore, to offer (i) an exploratory analysis of the cumulative equipment expenditures of NATO countries between 2014-2023 and (ii) to verify – by using OLS multivariate regression – the extent to which the GDP per capita primarily drives these expenditures (adjusted per soldier), the share of defense spending from the GDP, or by the fraction of defense spending that goes specifically to equipment. The results show that the GDP per capita is by far the most powerful predictor.

The impact of research and development (R&D) expenditure is crucial for understanding contemporary economic development strategies. This study investigates the relationship between R&D spending as a percentage of GDP and economic growth, focusing on the South Caucasus countries (Azerbaijan, Georgia, and Armenia) and Israel, which is notable for its substantial R&D expenditure (5.71% of GDP in 2020). The objective is to evaluate the impact of R&D expenditure on economic development through the application of rigorous empirical methods. By employing a quantitative approach, this study aims to offer a detailed analysis of the impact of R&D investment on economic growth across various countries. Ordinary least squares (OLS) regression analyzes the association between R&D expenditure and GDP levels. Granger causality tests are utilized to investigate the causal relationships. The results demonstrate a significant positive relationship between R&D expenditure and GDP across all studied countries. Furthermore, the analysis reveals that GDP growth stimulates increased R&D investments in Azerbaijan and Armenia, as evidenced by Granger causality tests. To sum up, this paper underscores the critical role of R&D spending in driving economic development and highlights the necessity for policy initiatives focused on strengthening R&D frameworks.

The purpose of the research is to present the realised forecasts of Ukraine's economic power in order to find reserves for the recovery of the national economy and opportunities for the formation of digital entrepreneurship on the basis of innovative functioning, which will lead to economic growth in the medium and long term. The object of scientific research is the expenditure on SRD and S&T development by types of work in Ukraine from 2010 to 2022 and the analysis of indicators of GDP the influence of time, employment and inflation factors; expansion of digital capabilities of entrepreneurship due to the conducted R&D, which will become a guarantee of the emergence of breakthrough innovations as one of the key reserves of innovative and digital development of the country during the war and post-war reconstruction of Ukraine. Methodology. A study was conducted utilising dialectical, systematic, mathematical and statistical methods to investigate the R&D expenses by types of work in Ukraine from 2010 to 2022 and the GDP from 2011 to 2023. This analysis determined the prospective existing reserve of economic strength with positive dynamics and highlighted the necessity for a strategic format of digital business work based on innovation. A CRA was conducted to determine the strength of the relationship between SRD expenditures and time (i.e., a set of factors that consistently influence SRD funding and drive its growth trend). Fisher's test was calculated, and an econometric analysis was performed based on GDP indicators over 56 quarters, establishing the dependence of the GDP volume on the time factor and the cyclicality of seasonal fluctuations. Resluts. The conditions for accelerating the digitisation of business processes at domestic enterprises are, in particular, the presence of highly qualified S&R personnel, innovators and researchers in the country, the development of new institutes of innovative and digital development, and the transformation and adaptation of old institutes of development to the existing conditions. The obtained data of CRA show that there is a close relationship between the GDP of Ukraine and the time factor, and the direction of the relationship is direct, i.e., linear, which in this case is a positive fact. It is determined that in pursuit of the goal of restoring the innovative potential of the national economy in the post-war period and further active development of digital entrepreneurship in Ukraine, it is necessary to continue financial support for scientific research and scientific and technical developments carried out in various sectors of the economy. Practical implications. The analysed statistical data had a positive impact on the professionalism of the forecast calculations and allowed to state that in 2027, with a probability of error of 6.29%, the volume of expenditures on research and development is projected to range from 20,202.74 to 29,201.18 million UAH. The results of the CRA show that the multiple correlation coefficient (R) is 0.94, which indicates a close overall relationship between the country's GDP and three independent variables (inflation rate, unemployment rate, time factor). The linear regression equation fits the sample data well and the model is qualitative. The results of the forecast are as follows: Ukraine has the potential for post-war recovery and can develop models for post-war economic reconstruction and changes in its structure. Government officials can develop institutional instruments to attract investment and provide effective mechanisms for the future transformation of the existing labour market and human capital institution. Value / Originality. Having conducted a thorough analysis of the statistical data on the dynamics of spending on S&T development and implementation of the SRD in Ukraine in 2010-2022, the authors managed to determine the relative error of approximation – a criterion for assessing the reliability of the forecast, which amounted to 8.74% and considered the approximation to be qualitative, and the forecast for 2027 is reliable. It is determined that the regression equation is most accurate when R2 approaches its maximum value, that is, 1, and in this case, it is 0.9096, which is a good result and means that the linear regression equation fits the sample data well and the model is of high quality. And for Ukraine's economy, which is under martial law, such positive expectations for GDP and the possibility of increasing R&D spending give hope that Ukraine's economic strength is real, as confirmed by the forecast calculations.