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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]

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]

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]

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]

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]

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]

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]

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]

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]

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]

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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]

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]

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]

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]

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.

Several research efforts were dedicated to analysing the effects of foreign direct investment (FDI) inflows on gross domestic product (GDP) and employment in the host economies. The variations in the conclusions signal that other variables influence and moderate the effects of FDI on GDP and employment. Institutional elements receive limited research attention, despite their influence on the host economies. This paper investigates the moderating role of institutional elements in the FDI-host economies on FDI’s effects on GDP and employment with China and India as case studies. The approach utilises three principal methodologies. The first methodology presents an in-depth analysis of China and India, highlighting selected institutional elements with the potential to influence FDI’s effects. The second methodology confirms the presence of a positive correlation between FDI and GDP and a negative correlation between FDI and employment-to-population ratio (EPR) in both China and India. The FDI, GDP purchasing power parity per capita, and EPR datasets are extracted from the World Bank – DataBank World Development Indicators to ensure the consistency of the data. The results of the quantitative analysis validate the qualitative analysis. The qualitative analysis confirms the moderating role of the selected institutional elements with variations in direction and strength. Significant variations in FDI’s effects on GDP and employment are strongly related to variations in the institutions of governance. The institutions of governance include the functionality of the state organs, the efficiency of the legal system and enforcement of the rule of law, and the quality of implementation of FDI-supportive policies. The findings aim to increase the absorption of the positive effects of FDI on GDP and employment in the respective countries. The research is a cornerstone of in-depth future research into the following areas: the role of selective FDI and constructive conditional FDI policies, the functionality of judicial authority controls, and FDI favourable exchange rates and interest rates policies. The novelty and contribution of the paper lie in its comprehensive exploration of the moderating role of institutional elements on the effects of FDI on GDP and employment in host economies, with a specific focus on China and India. The paper contributes significantly to the academic literature on FDI and economic development by emphasising the importance of institutional factors and providing actionable insights for policymakers and researchers. [ABSTRACT FROM AUTHOR]

This paper analyzes the relationship between GDP and the stock market over the long term, intending to understand the implications for Index Fund investments. A quantitative research method, using US (United States) GDP as an independent variable, and the S&P 500 index as a dependent variable, is employed. A population of 29 years, from 1990 to 2019, of data on US GDP and the S&P 500 from official US sources was used. Linear regression analysis with SPSS calculating techniques is performed to determine whether there is a relationship between GDP growth and the stock market (S&P 500). The results show a significant positive relationship between GDP growth and S&P 500 performance. β coefficient of the regression analysis of 0.911 shows a strong correlation between the GDP and the S&P 500. Our findings are also scientifically validated by the sig (P value) coefficient of 0.0000000000012. In addition, an R Square of 0.830 shows that our model explains all the variability of the response data around the mean at a level of 83%. The positive results of GDP and the stock market relationship, indicate considerable implications for Index Funds investments. Therefore, adding academic value to the practical financial implication aspects.

The aim of the article is to analyse the impact of foreign direct investments on GDP growth and the link between the COVID-19 pandemic and the economic growth of Central and Eastern European countries. The study has shown us that there is a positive impact between foreign direct investment inflows and GDP growth, and that variables such as exports, labour productivity and unemployment rate also positively influence the development of the countries under analysis. We used a panel regression model with fixed effects, which showed us the correlation between FDI inflows and GDP growth, from which we can see that the decreases in FDI caused by the pandemic, led to a decrease in the GDP growth rate and thus in the economic development of the Central and Eastern European countries.

In the era of rapid technological progress, the influence of dizitalization on different aspects of international economic activity can’t be overstated. The aim of this article is to conduct a comprehensive comparative study of digitalization’s impact on global goods and services markets, with a specific focus on advanced and developing economies using multiple linear regression. The research methodology involved comprehensive data collection for 35-38 advanced economies and 52-66 developing economies depending on the availability of data. The analysis included depended variables (18 export and import goods sectors and 18 export and import services), independent variables (digitalization, consisting of ICT deployment, ICT export and import, ICT investment variables), control variables such as GDP growth, CPI, trade openness, exchange rate and political stability. The findings demonstrate the ICT infrastructure and ICT exports positive impact on export of technology-intensive goods, such as ores and metals, machinery and equipment, and tools and devices in advanced economies. Digitalization’s positive impact on trade in goods appeared weaker in developing economies, potentially due to lower levels of ICT adoption or differing export focuses. ICT export has positive impact on financial services imports, indicating a reliance on imported financial services while exporting ICT capabilities. The model shows a high success rate depending on variables. The study highlights digitalization’s varied impact on advanced and developing economies, emphasizing its importance for trade, competitiveness and policymakers in the global market.

The economic impact of the tourism and hospitality sector as an economic system is partly general, similar to other sectors of the economy, and partly specific. At the same time, the sector is a major driving force for macro-economies, with positive effects on various sectors of the economy. Based on an analysis of current statistical data, the study formulates the characteristics of the sector: the share of hotels and restaurants in GDP, the revenue from accommodation fees of commercial accommodation establishments, the evolution of the turnover of guests in commercial accommodation establishments, the average gross monthly earnings of employed persons, etc. Analysing the data for the period under review, 2008-2021, we can see that Hungary started to see some growth in employment and average gross earnings after 2010, but still lagging behind the targets set in 2005. In line with international trends, tourism in Hungary has developed positively in several areas by 2019, reaching or exceeding pre-2008 crisis levels, with overall growth in the sector exceeding the national economy average. However, the sector’s performance was also significantly affected by the sharp decline caused by Covid-19 and the war situation in 2022. The aim of the analysis is to present the impact of the international financial crisis starting in 2008 and the Covid-19 epidemic in March 2020, to compare the effects of the two crises on GDP, labour market factors, with a special focus on the accommodation and food services sector.

Abstract The purpose of this “perspective” type paper is to revisit and recapitulate an existing alternative approach to measuring economic and sustainable GDP (using the ISEW as a proxy) at both national and regional levels. Motivated by the recognized inadequacies of Gross Domestic Product (GDP) in capturing true economic welfare, this study highlights the need for comprehensive indicators that reflect genuine prosperity. While GDP has long served as the primary macroeconomic measure of development, it fails to account for genuine progress, prompting the exploration of alternative measures. In recent decades, sustainable development has become a focal point for global, national, and regional economies, highlighted by the United Nations' 17 Sustainable Development Goals. The inability of GDP to capture sustainable welfare has led to the proposal of various alternative indicators in the literature. This study revisits and recapitulates the Index of Sustainable Economic Welfare, first introduced by Daly and Cobb (For the common good: redirecting the economy toward community, the environment, and a sustainable future, Beacon Press, Boston, 1989), which adjusts GDP to better reflect sustainable development. The current “perspective” reviews the application of ISEW across different countries revealing significant insights into the limitations of GDP and the benefits of more holistic measures. Additionally, the study emphasizes the importance of capturing sustainable economic prosperity at the local level and advocates for the inclusion of cultural aspects as the fourth pillar of sustainable development.

This study adjusts the net national product (NNP) and gross domestic product (GDP) of the Peruvian mining sector by incorporating natural capital depreciation, new discoveries, and environmental degradation during the period 1994–2018. The results suggest that NNP has been overestimated, on average, by 172 % to 210 %, which is attributed to the omission of natural depreciation. When GDP was corrected, the overestimation fluctuated between 64 % and 72 %. This underscores the importance of including natural capital depreciation, especially in countries whose economy is highly dependent on extractive industries, as is the case of Peru.

More the capital more the industries can be lead to more employability. Hence, current paper aims to analyze the trend and pattern of FDI and its impact on the Indian economy using uses stepwise regression to select the appropriate variables with time series data over thirty years from 1992-2021 and found that there is a positive trend of FDI inflow into the country over the study period and the intersection between FDI and GDP is very high and the foreign exchange reserve is also very high, Moreover, foreign exchange reserves and interest rates have a significant relationship with FDI.

The Micro, Small, and Medium Enterprise (MSME) sector stands as a pivotal pillar within the Indian economy, contributing to 48% of the nation's production output and providing employment to a staggering 110 million individuals. The pervasive impact of the pandemic has inevitably reverberated across the economic landscape, although its full extent remains shrouded in uncertainty. Particularly, the small-scale enterprises that play a crucial role in India's manufacturing and service domains have borne the brunt of this impact. The year 2020 witnessed an unprecedented deceleration in revenue, with the MSME sector grappling with severe challenges in maintaining operational continuity. In response to this crisis, the government took affirmative action aimed at rejuvenating the beleaguered sector, offering targeted support to MSMEs. This concerted intervention proved to be a significant impetus, infusing hope and vitality into these enterprises. Consequently, a comprehensive evaluation of the barriers encountered, a candid exposition of these hurdles, and the formulation of a robust strategy to surmount the pandemic-induced turmoil have become imperative. In light of this exigency, the researcher undertakes a rigorous analytical investigation into the government's policies crafted to ensure the sustainable growth of MSMEs in India. By distilling insights from diverse sources, a holistic understanding of the challenges faced by MSMEs and the efficacy of governmental interventions is pursued.

Environmental taxes ensure sustainable development, but their fiscal and environmental effectiveness differs for countries with different socio-economic characteristics. This study aims to compare the impact of environmental tax revenues on economy’s decarbonization (measured through carbon productivity – the ratio of GDP to carbon dioxide emissions) in different countries, considering their green technologies development and carbon emissions. The paper analyzed OECD and World Bank statistical data for 38 OECD countries for 2002–2021 using linear panel regression models with fixed and random effects (using Hausman test and STATA 18). To identify explicit and latent patterns of this influence, which are common to certain countries, this analysis did not consider each country separately but targeted clusters, distinguished by Ward and Sturges methods based on the effective tax rate on carbon emissions, total environmental tax revenues, total carbon emissions, and carbon productivity. The positive influence of environmental tax revenues on the economy’s decarbonization level has been confirmed for 29 countries (four from six clusters). The effect is the largest for the USA (an increase in tax revenues by 1% leads to an increase in carbon productivity by 0.9% on average) and the smallest – for the cluster including Austria, Belgium, Canada, Costa Rica, Czechia, Estonia, France, Germany, Hungary, Iceland, Korea, Lithuania, New Zealand, Poland, Portugal, Slovakia, Spain, and the Great Britain (increase – 0.1%). The negative impact was confirmed for nine countries (two from six clusters): Denmark, Finland, Israel, Latvia, and Sweden (decrease – 0.3%) and Greece, Italy, the Netherlands, and Slovenia (decrease – 0.21%).

Gross Domestic Product (GDP) is one of the key macroeconomic aggregates that measures the added value produced in a country during a period. In the contemporary world, macroeconomic uncertainty, among others due to the COVID-19 pandemic and the conflict in Ukraine, and GDP prediction remain important goals in public policy making. This study aims to predict Benin's GDP through a unidimensional statistical approach and machine learning techniques. For this purpose, GDP data were collected from the Central Bank of the West African States (BCEAO) website from 1960 to 2021. The predictions are based on comparing classical statistical and machine learning methods. For the classical statistical methods, we investigated the Autoregressive Integrated Moving Average (ARIMA) and Error Trend Seasonality (ETS) forecasting models. As for the machine learning methods, the K-Nearest Neighbors (KNN) and Long Short-Term Memory (LSTM) forecasting models proved to be sound. The findings revealed that the statistical models (ARIMA and ETS) better predict Benin's GDP. However, machine learning models (KNN and LSTM) also provide a wide range of results that can be used to analyze Benin's economic growth.

The transition from coal to more sustainable energy sources represents a critical shift for economies reliant on coal production. To investigate the intricate processes involved in such a transition, the use of powerful analytical tools is essential. This study assesses the impact of the delignification process on GDP growth over a 20-year horizon (2015–2035) in the Region of Western Macedonia, Greece, using the Vensim PLE Plus 9.0.1 software, a robust tool for system dynamics modeling. By developing a dynamic model that captures the key variables and feedback loops associated with coal transition, this research examines economic, social, and investment variables, emphasizing their causal relationships. The study integrates societal, economic, and educational impacts on production transition, addressing issues such as unemployment, financial support, and investments in human resources and R&D. Additionally, it considers the influence of climate change on GDP. The model highlights population dynamics, economic development, and education as critical factors. Scenarios explore the impact of increased funding on education, research, and financial aid efficiency, providing insights into enhancing GDP in decarbonizing regions. The study reveals that increased investment in education and human capital leads to slight improvements in local GDP, though the effects are not immediate. Enhanced efficiency in government and European spending significantly boosts local GDP by creating strong value chains and local economies of scale. It is found that the increase in financial support to the regions in transition is of the utmost importance and has a multiplicative nature, something that should encourage the European Union to increase its financial support tools. The model's simulations align closely with historical GDP data, validating its accuracy. The contributions of the present work offer valuable insights to policymakers and stakeholders engaged in the transition processes. [ABSTRACT FROM AUTHOR]

This article examines the relationship between household food waste and Gross Domestic Product (GDP) in various European regions, aiming to determine how economic prosperity influences the levels of household food waste. Using comparative analysis of secondary and tertiary data, a synthetic indicator (IpFW) was developed to assess the interaction between GDP per capita and household food waste per capita. Linear correlation analysis was also applied for better interpretation of the data. Despite expectations, higher GDP is not consistently correlated with lower household food waste, challenging economic prosperity and environmental stewardship assumptions. This research highlights the complexity of the interaction between economic factors and household food waste management, revealing a lack of significant correlation even at the regional level. The findings indicate a need to re-evaluate current policies and highlight that improving food supply chains and influencing consumer behavior can promote more sustainable consumption patterns, which is in line with the Sustainable Development Goals. [ABSTRACT FROM AUTHOR]

This study investigates how carbon dioxide emissions, natural gas, energy consumption, energy investment, coal and crude oil, and per capita exports affected the economic growth of the United States from 1993 to 2023 using the Vector Error Correction (VEC) model. The findings highlight the importance of exports and energy investment in driving both short- and long-term economic growth, while also highlighting interactions between carbon emissions, coal use and crude oil. It was determined that changes in natural gas and exports affected energy investment in the short term, while coal and exports affected natural gas. These results provide valuable information about the dynamics of the American economy and contribute to our understanding of the complex interactions between various factors and their effects on economic growth, offering implications for further research and policy development to promote sustainable economic development. [ABSTRACT FROM AUTHOR]