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The impact of urban form on carbon emissions has become a crucial issue for sustainable socioeconomic development and the advancement of low-carbon cities. Transportation is a significant source of urban carbon emissions, highlighting the need for comprehensive research to aid China in achieving its carbon peak and neutrality goals. Currently, there is a lack of quantitative studies exploring the effects of urban form on transportation-related carbon emissions. This paper seeks to quantify the effect of urban form on the spatial and temporal patterns of transportation carbon emissions, utilizing panel data from 27 cities in the Yangtze River Delta (YRD) region of China, covering the years 2000 to 2020. First, CO2 emissions from transportation are estimated following IPCC guidelines, with Moran's I utilized to analyze spatial autocorrelation. Next, urban form indicators are quantified based on landscape ecology theory. Finally, econometric models are employed for regression analysis of the panel data. The findings reveal that urban complexity, compactness, and expansion influence transportation carbon emissions to varying degrees, with urban expansion and complexity associated with increased emissions, while compactness contributes to their reduction. This study offers theoretical support and a scientific basis for low-carbon urban spatial planning and development, underscoring the importance of urban form in emissions reduction strategies. [ABSTRACT FROM AUTHOR]

The accuracy of GDP per capita growth rate in countries with low statistical capacity has been questioned, which hinders understanding progress of Sustainable Development Goals (SDGs) accurately. This study aims to estimate GDP per capita growth rate in countries with poor statistical quality. To achieve this goal, the study builds an econometric model with processed Visible Infrared Imaging Radiometer (VIIRS) night-time light data and other economic variables and the study further assesses the accuracy of the model by comparing the estimated GDP growth to high-quality economic data from Organization for Economic Co-operation and Development (OECD) countries between 2014 and 2018. First, due to the abnormal fluctuations in the time series generated from yearly composite night-time light images, we propose a trend analysis method for the monthly night-time light data to synthesize a more stable yearly time series. Then, we construct artificially low-quality GDP simulations and combine VIIRS data and official statistics data to construct regression models to correct the simulated GDP. Finally, to assess the model accuracy, we compare its estimates of GDP per capita growth rates to official data from high-quality OECD countries, looking for any deviations. We have two major findings as follows: first, the VIIRS data, which comprise information on human activity, are a valuable resource for estimating GDP growth; second, the GDP estimation model can reduce the artificial bias of the simulated GDP per capita growth rate by using VIIRS night-time light data and the average accuracy of the model with simulated data can reach 89%. [ABSTRACT FROM AUTHOR]

This paper presents a methodology for modeling residential appliance uptake as a function of macroeconomic variables, and presents forecasts of appliance diffusion through 2030 for several scenarios of economic (GDP) growth. The approach followed allows the modeler to construct a bottom­-up analysis based at the end use and the household level. It captures the appliance uptake and the saturation effect which will affect the energy demand growth in the residen­tial sector. With this approach, the modeler can also account for stock changes in technology and efficiency as a function of time.

Copyright of Contaduría y Administración is the property of Facultad de Contaduria y Administracion-Universidad Nacional Autonoma de Mexico 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.)

One of the industries with the fastest development is the hospitality and tourism (HoReCa) sector. However, there is also a growing trend in this sector to evade some state taxes. Despite promises that digitalization will reduce tax evasion, this practice nevertheless is a serious threat to the economy and the state. This study aims to process a comprehensive model for screening and risk assessment of tax fraud in the HoReCa sector in Romania. In this sense, an empirical study was conducted using an econometric model to detect tax evasion in the HoReCa sector in Romania, based on a sample of 50 firms for each sub-sector (hotels, restaurants, cafes), analyzing the period 2018–2022. The dependent variable of the model was the tax evasion risk indicator, calculated as the difference between the average financial ratios of each firm and the average for the entire sector. The results show that the leverage ratio has the strongest positive impact on the tax evasion risk indicator. The fixed asset turnover ratio and the accounts receivable turnover ratio also have a significant impact, indicating false sales reports or collection irregularities. The solvency ratio and the immediate liquidity ratio show positive effects on the risk of tax fraud, while the net rate of return is the only one with a negative effect, suggesting that profitable entities are less prone to tax evasion. The proposed model provides a solid basis for identifying high-risk companies directing tax authorities to improve supervision in the HoReCa industry. The findings also highlight the importance of further automating tax reporting systems to reduce the risks of evasion.

During the period 2010-2022, the European Union has successively gone through multiple economic, social and health crises that have affected the economic security of the European Union. We aim to critically analyse the sustainable development of the European economy and to design a new model of sustainable development and economic performance in the current geopolitical context. The methods used consist in the analysis of descriptive statistics on GDP per capita (as dependent variable), long-term unemployment rates, labour productivity, severe housing deprivation, internet use, municipal waste generation, net greenhouse gas emissions, and the share of renewable energy in gross final energy consumption. In addition, with the help of STATA version 18 we will develop a new sustainable development and economic performance model (SDEPM) that will identify the possibilities of sustainable economic development in the context of adequate security based on panel regression fixed effects data. The results of the study will allow the formulation of public policy proposals that will support European sustainable development in a security context and that will be useful for supranational decision-makers to adjust current economic development strategies.

In the current challenging context, dominated by multiple crises, social policy is a strategic element on which the EU has focused in regulatory, institutional and financial terms, with the objectives of ensuring social well-being for all European citizens, creating an institutional and economic climate of social security, ensuring equal opportunities and social inclusion. In this context, we aim to develop a study of the dynamics of social policy components at the European level and to develop the impact model on the effect of social welfare on sustainable economic development based on the evolution of the main economic and social indicators at the European level. The econometric methodology used is based on the application of linear regressions on panels of fixed effects data in order to highlight the vulnerability aspects in economic development and poverty reduction from the perspective of social policies at the European level. The analysis will make it possible to highlight the main social policy guidelines at European level and to situate these approaches in the current uncertain context.

Hydrologic, climatic, regulatory and economic factors interact in complex ways to influence groundwater conditions. These relationships can be difficult to measure and model but are important for water management and for considering viable futures for regional economies. This paper proposes a strategy for an improved understanding of how groundwater levels reflect signals of regulatory, economic and climate factors. Most existing econometric studies of groundwater use focus on large-scale irrigated agriculture and urbanized areas in first world nations, where groundwater extraction data is available. In much of the world, groundwater extraction data are not available for individual farms and other water users. The goal of this study is to explore the responsiveness of groundwater levels (a more widely available measure of groundwater conditions) to regulatory, economic and climate signals in rural areas, using a growing body of remotely sensed land cover data. Pooled Ordinary Least Squares econometric models examine the effects of regulatory, climatic and economic factors on groundwater levels in rural Arizona. Groundwater regulations, recharge projects, housing units and irrigated acreage have statistically significant relationships to groundwater levels in the study areas. This approach can be valuable for understanding factors that influence groundwater conditions and which may be useful in managing groundwater use in widespread areas where groundwater extraction data is unavailable. [ABSTRACT FROM AUTHOR]

The article is devoted to highlighting the results of research aimed at improving existing approaches to conducting a comprehensive analysis of the nature of the relationships between the parameters of the state's monetary and debt policy. Among other things, such indicators as the size of the domestic public debt, the size of international reserves, the level of inflation, the exchange rate and the discount rate are taken into account. The proposed approach to the analysis of the influence of managed monetary indicators on the size of the internal state debt proved that the use of the ARDL model gives slightly better results than the VECM in terms of the adequacy of the description and forecasting of the studied process. At the same time, both models proved their ability to describe the change in the size of the internal state debt, and have high values of coefficients of determination and low values of the indicator of the average absolute percentage error. In the future, it is recommended to use it for the analysis of the causality of the influence, discriminant analysis and the expediency of changing monetary instruments independently of other instruments. On the basis of the developed models, the results were obtained, which allow us to draw conclusions that the system continues to remain stable after fluctuations of key factors capable of destabilizing it and will be able to return to its previous state after a shock for some time. This is confirmed by the fact that, on the basis of statistical tests, the existence of a long-term relationship between the investigated indicators and the impulse response function together with the decomposition of the variance of the VAR model was proved. [ABSTRACT FROM AUTHOR]

Professional football clubs invest vast amounts of money in the recruitment of players. This article presents the latest advances in statistical modeling of the factors that market actors take into consideration to determine the transfer prices of professional football players. It extends to a global scale the econometric approach previously developed by the authors to evaluate the transfer prices of players under contract with clubs from the five major European leagues. The statistical technique used to build the model is multiple linear regression (MLR), with fees paid by clubs as an independent variable. The sample comprises over 8000 transactions of players transferred for money from clubs worldwide during the period stretching from July 2014 to March 2024. This paper shows that a statistical model can explain up to 85% of the differences in the transfer fees paid for players. Despite the specific cases and other possible distortions mentioned in the discussion, the use of a statistical model to determine player transfer prices is thus highly relevant on a global scale. [ABSTRACT FROM AUTHOR]

The current context of economic development requires paying close attention to the energy industry. Since 2022, European countries has been facing specific problems due to energy crises against the background of the geopolitical conflict and the measures provided by European forums in order to reduce dependence on energy imports from Russia. In this context, we aim to define a new model of energy consumption and the function of energy sustainability at the European level, aspects that will lead to highlighting the position of the 27 European member states in the period 2005--2022 in terms of their energy sustainability. The methodology used is based on the study of literature, the consolidation of databases, econometric modelling, and procedures for testing the validity of modelling results. The results of the study are useful to European energy policy decision-makers in view of the necessary adjustments to achieve the objectives of the 2030 and 2050 Agenda. [ABSTRACT FROM AUTHOR]

Objective: to analyze the factors that influence the academic performance of students in Colombia, considering both individual characteristics and factors related to the educational institution. Methodology: a hierarchical econometric model was used to nest the data at different levels, and the individual results of the Saber 11° tests of the Colombian Institute for the Evaluation of Education were used for both semesters of 2021. Results: indicate that the nature of the school (public or private) is a key factor in student performance, explaining almost 11% of the differences between schools, despite the fact that students attending public schools have lower socioeconomic, cultural and social conditions than those attending private schools, there is still a significant gap in academic performance that cannot be fully explained. Conclusion: private schools were found to have more variability in their effect on student performance, indicating that the unique characteristics of private schools, such as admission fees and incentives granted to teachers, may influence student academic performance more randomly. [ABSTRACT FROM AUTHOR]

In the current challenging context, dominated by multiple crises, social policy is a strategic element on which the EU has focused in regulatory, institutional and financial terms, with the objectives of ensuring social well-being for all European citizens, creating an institutional and economic climate of social security, ensuring equal opportunities and social inclusion. In this context, we aim to develop a study of the dynamics of social policy components at the European level and to develop the impact model on the effect of social welfare on sustainable economic development based on the evolution of the main economic and social indicators at the European level. The econometric methodology used is based on the application of linear regressions on panels of fixed effects data in order to highlight the vulnerability aspects in economic development and poverty reduction from the perspective of social policies at the European level. The analysis will make it possible to highlight the main social policy guidelines at European level and to situate these approaches in the current uncertain context. [ABSTRACT FROM AUTHOR]

Due to the scarcity of economic resources, it is vital to optimize everything so that the supply and demand lines intersect in an optimized quantity, with no shortage or surplus of a provided item or service. Energy supply contains both surplus and shortage, thus estimating the amount of projected energy demand is a key work that must be completed. The objective of this paper is generating a mathematical model based on the actual data for thirty years forecasting. To create a mathematical model using actual data from the last fifteen years, a model that can represent the past trend and be used for future forecasting. This study provides a general overview of Ethiopia's current energy requirement with different energy type as well as sector-specific energy demand and estimates for different economic growth scenarios up to 2052. This model was created using a linear regression polynomial fit through Origin graphic and analysis software, and an econometric model was also applied. GDP was utilized as an independent variable in the economic model to determine the trend of energy consumption. Another input-output model is also used for multilinear regression to evaluate the change of four variables, GDP, population growth, urbanization growth rate, and general inflation rate, which was quantitatively linked with total energy requirement using Weka software. The mathematical model developed through linear and multilinear regression has been validated by using a different assumption on GDP growth based on past growth rate as low, medium and high growth rate and using the mathematical formula to generate an energy demand trend that can be compared with the actual trend; as a result, all the mathematical model that are generated has been found to be valid for the purpose of the intended work. Based on the generated mathematical model and different GDP growth rate scenario as low, medium, business as usual (BAU) and high a future energy demand was forecasted up to 2052 for thirty years. The model's results can help energy planners ensure that the country's supply capacity keeps up with predicted energy demand growth.

The article is devoted to highlighting the results of research aimed at improving existing approaches to conducting a comprehensive analysis of the nature of the relationships between the parameters of the state's monetary and debt policy. Among other things, such indicators as the size of the domestic public debt, the size of international reserves, the level of inflation, the exchange rate and the discount rate are taken into account. The proposed approach to the analysis of the influence of managed monetary indicators on the size of the internal state debt proved that the use of the ARDL model gives slightly better results than the VECM in terms of the adequacy of the description and forecasting of the studied process. At the same time, both models proved their ability to describe the change in the size of the internal state debt, and have high values of coefficients of determination and low values of the indicator of the average absolute percentage error. In the future, it is recommended to use it for the analysis of the causality of the influence, discriminant analysis and the expediency of changing monetary instruments independently of other instruments. On the basis of the developed models, the results were obtained, which allow us to draw conclusions that the system continues to remain stable after fluctuations of key factors capable of destabilizing it and will be able to return to its previous state after a shock for some time. This is confirmed by the fact that, on the basis of statistical tests, the existence of a long-term relationship between the investigated indicators and the impulse response function together with the decomposition of the variance of the VAR model was proved.

In 2010, the European Union has proposed to eradicate poverty at the level of the community space. For this purpose, legislative and economic steps have been taken and the Strategy for social inclusion and equal opportunities has been developed. Faced with multiple economic crises, Europe has experienced significant disparities in the risk of poverty at the level of the Member States. We aim to conduct a study on the influence of uncertainties on the risk of poverty in the European Union. The main objective is to develop an econometric model to study the effect of contagion of uncertainties on the risk of poverty. The methods used are to apply econometric modelling processes on social indicators for the period 2010-2021 at European level. The results of the study will highlight the impact of uncertainty on the risk of poverty and will allow the formulation of public policies to help supranational decision makers to limit this phenomenon at the level of the Eruopen Union.

Non-performing loans (NPLs) are a financial item that affects bank profitability by reducing banks' income from lending and increasing non-performing loans at the industry level. This phenomenon is associated with a decrease in lenders' financial capacity due to inflation and exchange rate instability. We aim to analyze the impact of non-performing loans on the Romanian economy based on an econometric model for the period 2010-2021 using financial indicators on bank non-performing loans in correlation with macroeconomic indicators such as unemployment, inflation, GDP deflator and general government final consumption expenditure. The methods used consist of literature review on non-performing loans, consolidation of a database, application of econometric modelling techniques using linear regression. The results of the study support the possibilities of reducing the negative impact of non-performing loans through macroeconomic recovery and smart financial allocation.

The multiple global crisis has made the economies of the world's countries, including EU's economy, vulnerable through the downgrading of the pandemic and the subsequent outbreak of geo-political conflict. These two events had the effect of decelerating the European economy and increasing the poverty level of the population, even that these developments are weaker than in rest of the world. The main objective of the present scientific approach is to identify a risk function based on Markov probability chains and to assess the possibilities of economic recovery through a package of policies structured over different time horizons. The used methods consist of meta-analysis, statistical analysis and geo-spatial and temporal modelling. The results of the study capture the integrated developments of risk-generating macroeconomic elements such as inflation, unemployment, public debt growth in a regionally segregated manner. These elements are useful for supranational decision-makers to increase the economic survival rate after multiple shocks through our proposed policy package. [ABSTRACT FROM AUTHOR]

During the period 2010-2022, the European Union has successively gone through multiple economic, social and health crises that have affected the economic security of the European Union. We aim to critically analyse the sustainable development of the European economy and to design a new model of sustainable development and economic performance in the current geopolitical context. The methods used consist in the analysis of descriptive statistics on GDP per capita (as dependent variable), long-term unemployment rates, labour productivity, severe housing deprivation, internet use, municipal waste generation, net greenhouse gas emissions, and the share of renewable energy in gross final energy consumption. In addition, with the help of STATA version 18 we will develop a new sustainable development and economic performance model (SDEPM) that will identify the possibilities of sustainable economic development in the context of adequate security based on panel regression fixed effects data. The results of the study will allow the formulation of public policy proposals that will support European sustainable development in a security context and that will be useful for supranational decision-makers to adjust current economic development strategies. [ABSTRACT FROM AUTHOR]

The paper analysed the input costs on the sunflower production at Mkalama district in Singida region using variables prices of fertilizer, plough, pesticide, land hired per acre, labour hired, hoe, improved seed (50kg) and Local seed (50kg). For this aim, descriptive statistics and an econometric analysis was conducted in 120 randomly selected sunflower farmers in Mkalama district. Descriptive statistics and OLS regression model were used to analyze the extent of input costs on the sunflower production by respondents. The results revealed that fertilizer, plough, labour hired and Local seed (50kg) inputs had the highest average total cost of inputs. The results of econometric model showed that fertilizers, ploughs, pesticides, land hired per acre, hoes and improved seed (50kg) were the most important inputs, significantly contributed to total production of sunflower seeds; While, the use of labour hired and Local seed (50kg) has negative relationship with output of sunflower. The paper found out that price per bag of fertilizer, price per plough, price per pesticide and price per acre of land hired are positive and statistically significant influence on the sunflower production (Beta= 0.535, 0.302, 0.502, 0.197, P>0.001). The paper concluded that major problems confronting sunflower production were found to be inputs cost which always affects the yield of sunflower. This paper recommended that the Government of Tanzania should enhance the productivity of the agricultural sector through the subsidies provision of the required inputs, which would minimize the total cost of production and speed up the productivity process of sunflower in Tanzania. [ABSTRACT FROM AUTHOR]

Purpose: This study aims to investigate the implications of natural gas rents and institutions as co-drivers of economic growth, focusing on the Gas Exporting Countries Forum (GECF) with panel data between 2001 and 2021. Design/methodology/approach: This research paper uses a specialised two stage estimator, the panel instrumental variable technique (panel IV), which takes care of the potential endogeneity issues in the model. Findings: The findings show that natural gas rent significantly impacts the economic growth of the GECF. On average, natural gas rent increases the sample's growth rate by about 2.634% percentage points in the short run. The result indicates that the qualities of institutions (political and economic) have a significant positive long-term effect on the economies of the GECF. In addition, the study's energy price volatility positively correlates with the countries' growth. Research limitations/implications: There might be a need to investigate the effects of natural gas rents and institutions as co-growth drivers in each country within the GECF. The likelihood exists that the impact of natural gas rents and institutions on economic growth at the country's level may differ from the outcome of such an experiment on the group level. Because of space and time limitations, this study could not carry out the specific country's investigation of natural gas rents and institutions as a co-growth driver. That limitation may constitute further study to advance this study to a new height. Practical implications: With good institutions, natural gas rent is likely to be an alternative growth driver for some economies that rely on fossil fuels like oil as a growth driver. By extension, the GECF has the potential to rival Organisation of Petroleum Exporting Countries (OPEC) in the global energy market, particularly in achieving Sustainable Development Goal number seven. In essence, evidence in this study suggests that natural gas rent has long-term positive effects on the growth of the GECF, conditioned on good institutions. Moreover, the drive of global energy consumption towards sustainable energy usage is an economic blessing for the GECF. By extension, the demand for natural gas would continue to rise, creating opportunities to improve natural gas rents. By implication, the GECF would continue to benefit from the pursuit of sustainability as the world shifts towards energy consumption with less CO2. Originality/value: Firstly, this study models the qualities of institutions for the GECF. Secondly, to the best of the author's knowledge, this study is the first attempt to examine natural gas rents and the qualities of institutions as co-determinants of economic growth among the GECF (a potential cartel). [ABSTRACT FROM AUTHOR]

In 2010, the European Union has proposed to eradicate poverty at the level of the community space. For this purpose, legislative and economic steps have been taken and the Strategy for social inclusion and equal opportunities has been developed. Faced with multiple economic crises, Europe has experienced significant disparities in the risk of poverty at the level of the Member States. We aim to conduct a study on the influence of uncertainties on the risk of poverty in the European Union. The main objective is to develop an econometric model to study the effect of contagion of uncertainties on the risk of poverty. The methods used are to apply econometric modelling processes on social indicators for the period 2010-2021 at European level. The results of the study will highlight the impact of uncertainty on the risk of poverty and will allow the formulation of public policies to help supranational decision makers to limit this phenomenon at the level of the Eruopen Union. [ABSTRACT FROM AUTHOR]

The current context of economic development requires paying close attention to the energy industry. Since 2022, European countries has been facing specific problems due to energy crises against the background of the geopolitical conflict and the measures provided by European forums in order to reduce dependence on energy imports from Russia. In this context, we aim to define a new model of energy consumption and the function of energy sustainability at the European level, aspects that will lead to highlighting the position of the 27 European member states in the period 2005–2022 in terms of their energy sustainability. The methodology used is based on the study of literature, the consolidation of databases, econometric modelling, and procedures for testing the validity of modelling results. The results of the study are useful to European energy policy decision-makers in view of the necessary adjustments to achieve the objectives of the 2030 and 2050 Agenda.

Several research studies globally focus on the volatility of gold and oil prices, neglecting an examination of silver price volatility in relation to other market commodities. The current Covid-19 pandemic has led to various uncertainties and fluctuations in financial and stock exchange markets, yet existing literature primarily concentrates on individual product rates rather than combined rate changes. Our study aims to bridge this research gap by analyzing the relationship between oil rates, silver rates, oil rate transitions, and silver rate transitions on the security exchange in China from 1990 to 2022, using the ARDL approach and Nonlinear ARDL for a comprehensive assessment. The findings reveal a significant impact of silver and oil rates on China's security exchange in the future, with the negative effects of oil rate changes and a positive effect of silver rate transitions. In the short term, oil and silver rates play a crucial role in influencing China's security exchange, highlighting the importance of monitoring these trends for investors. It is recommended that investors respond prudently to market transitions, particularly by considering silver as a secure option during times of uncertainty, while policymakers should implement appropriate measures to manage the rapid fluctuations from oil to the security market.

Farms are key to agricultural advancement and carbon emission reduction. Understanding the influence of farm size on emissions is vital for eco-friendly farming. Our study used an econometric model with instrumental variable adjustments to examine the effect of farm size on greenhouse gas emissions, revealing an inverted U-shaped relationship. The findings revealed that emissions increased with farm size until a peak and then decreased. We identified an optimal farm size range (0.45 km2 to 0.58 km2) for lower emissions, where the farm size maintaining the lowest greenhouse gas emissions per unit area was 0.58 km2, while the lowest greenhouse gas (GHG) emissions per capita occured at a farm size of 0.69 km2. Reducing emissions intensity per unit area is easier than reducing GHG emissions per person. Policymakers should prioritise promoting the expansion to moderately sized farms as a means of achieving emission reduction targets rather than solely increasing the number of farms. Overall, these insights offer policymakers novel approaches for ecological farm planning and the transition toward a low-carbon agriculture sector.

Due to constant tightening of the sanctions policy against Russia, the stable manufacturing industry is among fundamental factors of sustainability and active growth of the country’s economy. Since the beginning of 2022, sufficient efforts have been made to neutralise the negative consequences of foreign companies leaving the market and replace imported goods and technologies with domestic ones. An urgent issue is to assess importance of stable manufacturing industry for the economy of the country and its regions. For the industrially developed North-Western macroregion, which has been seriously affected by the disruption of relations with the European Union and the United States of America, the rapid restructuring and reorientation of commodity flows is an important task, alongside with the increase in production of high value-added goods based on the resources of the macroregion. The purpose of the study was to identify how much factors of development of the manufacturing industry influence gross regional product (hereinafter referred to as GRP) per capita in the North-Western Federal District (hereinafter referred to as NWFD). The constructed econometric model made it possible to assess the most serious factors, the increase of which will allow to influence the economy of the macroregion. It is proved that the average number of employees of small enterprises has the strongest positive impact on GRP per capita in the NWFD as its increase by 1 person leads to an increase in the resulting variable by 1,055.76 rubles, all other things being equal. Thus, currently, the activation of the manufacturing industry with more employees of small business will become a driver of recovery and sustainable development of the macroregion’s economy.

This paper delves into the relationship between inflation and economic growth, two pivotal elements in contemporary economic discussions. It aims to demystify and elucidate these concepts, particularly examining how they are interlinked through the development of a comprehensive econometric model. The study pays special attention to key economic indicators such as the Consumer Price Index (CPI), Producer Price Index (PPI) and the growth rate of Gross Domestic Product (GDP). In addition, the paper considers the role of monetary and fiscal policies in managing inflation and fostering economic growth. This exploration not only contributes to a deeper understanding of economic dynamics but also offers valuable insights for policymakers and economists in formulating effective economic strategies.

In the conditions of innovative economy development, the formation issues of the personnel and research potential of the region at the expense of local universities’ graduates are of particular importance. The article puts forward and confirms the hypothesis that a number of socio-economic development indicators of Kemerovo region significantly affect the number of graduates of regional universities, which can be predicted considering changes in these indicators. With the help of the created model, it is possible to study the impact of each of the arguments of the model on the number of university graduates, predict their dynamics, identify targets for the management decisions development in the field of regulating the number of young specialists with higher education (necessary for the regional economy), as well as formulate strategic planning tasks and assess university development the potential. The results of the study can be used by structural divisions of the Government of Kuzbass, the leadership of universities and organizations of the Kemerovo region.

Accurately predicting future carbon emissions is of great significance for the government to scientifically promote carbon emission reduction policies. Among the current technologies for forecasting carbon emissions, the most prominent ones are econometric models and deep learning, but few works have systematically compared and analyzed the forecasting performance of the methods. Therefore, the paper makes a comparison for deep learning model, machine learning model, and the econometric model to demonstrate whether deep learning is an efficient method for carbon emission prediction research. In model mechanism, neural network for deep learning refers to an information processing model established by simulating biological neural system, and the model can be further extended through bionic characteristics. So the paper further optimizes the model from the perspective of bionics and proposes an innovative deep learning model based on the memory behavior mechanism of group creatures. Comparison results show that the prediction accuracy of the heuristic neural network is higher than that of the econometric model. Through in-depth analysis, the heuristic neural network is more suitable for predicting future carbon emissions, while the econometric model is more suitable for clarifying the impact of influencing factors on carbon emissions. [ABSTRACT FROM AUTHOR]

To address climate change, the world needs deep decarbonization to achieve carbon neutrality (CN), which implies net-zero human-caused CO2 emissions in the atmosphere. This study used emission-side drivers, including socioeconomic and net primary productivity (NPP)-based factors, to determine the changes in CN based on vegetation carbon sequestration in the case of China during 2001-2015. Spatial exploratory analysis as well as the combined use of production-theoretical decomposition analysis (PDA) and an econometric model were also utilized. We showed that CN was significantly spatially correlated over the study period; Yunnan, Heilongjiang, and Jilin presented positive spatial autocorrelations, whereas Guizhou showed a negative spatial autocorrelation. More than half of CN declined over the period during which potential energy intensity (PEIE) and energy usage technological change were the largest negative and positive drivers for increasing CN. PEIE played a significantly negative role in increasing CN. We advise policymakers to focus more on emission-side drivers (e.g., energy intensity) in addition to strengthening NPP management to achieve CN. [ABSTRACT FROM AUTHOR]

In this article, the relationship between risk premium spending and important financial and macroeconomic variables in Iran in the years 2013-2014 has been investigated. In this regard, standard OLS regression and the Hodrick-Prescott filter were used. The results of the research showed that there is a positive and significant relationship between the change and evolution of the money supply process and the variable of risk premium. This is while the variables of the gap between private consumption and its trend, exchange rate and stock index of the 50 largest companies in the stock market have a negative and significant effect on the amount of risk premium i.e. ERP in Iran. [ABSTRACT FROM AUTHOR]

This paper analyzes and compares the key factors influencing food security in two populous countries (China and India), and categorizes them into three types; agricultural production, economic development and income level, and income distribution. Using the prevalence of undernourishment as an indicator of food security, the paper empirically tests the degree of impact of various factors on food security in both countries using Tobit regression and Newey regression methods. The study finds that improving the level of economic development can significantly enhance food security in both countries; reducing the Gini coefficient has a significant impact on India, but not on China; increasing the agricultural production per capita has a much greater effect on China than on India. Therefore, both countries should take measures that are both similar and different according to their national conditions to improve their food security level. [ABSTRACT FROM AUTHOR]

Fiscal policy stands as a crucial pillar of economic development through its economic financing function. The regulatory effects of fiscality have been shown to reduce the ripple effects of uncertainties on economic growth within the EU. Unlike the average European economy, the Romanian economy has exhibited particularities concerning economic growth (ranking highly in economic growth among European nations in absolute terms), partly due to a more assertive fiscal policy applied to a consumption-based economy affected by hyperinflation (especially in the last five calendar years). The research issue stems from the premise of the lack of predictability in Romanian fiscal policy and its implications for the business environment. Our aim is to develop an econometric model of the fiscal effects of VAT on the business performance of the construction sector in Romania for the period 2010–2021. The methods employed involve empirical analysis and the development of consolidated industry-level databases followed by econometric modeling using the multiple linear regression method. The results of the research demonstrate that financial independence and solvency promote excessive taxation in emerging markets and developing countries, such as Romania, being correlated with the macroeconomic evolution of the respective state. Additionally, the results indicate that tax pressure can constitute a barrier to the sustainable development of firms, with direct repercussions for consumers. Attractiveness to investors is also affected, remaining a priority for companies. The study's findings will enable the identification of the main impediments and opportunities brought about by VAT taxation on branch-level performance, proving useful for construction sector managers and fiscal policy makers in fostering sustainable industry development and establishing a sustainable fiscal regime to safeguard investors. [ABSTRACT FROM AUTHOR]

Copyright of Runas. Journal of Education & Culture is the property of CICSHAL - Centro de Investigaciones en Ciencias Sociales y Humanidades desde America Latina 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.)

Copyright of Studies in Law & Economics / Studia Prawno-Ekonomiczne is the property of Lodz Scientific Society / Lodzkie Towarzystwo Naukowe 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.)

There is an expected increase in the demand for electricity from households in European countries. The outcome of the growing proportion of renewable energy sources in the energy supply mix should result in improved customer awareness regarding their electricity usage. Additionally, they must assume a more proactive role in overseeing their electricity usage. Innovation and pollution management have become crucial catalysts for promoting sustainable economic development and environmental protection. This is a response to the increasing threats posed by climate change. This study addresses this existing research gap in sustainable energy consumption. The research aims to examine the advantages of replacing traditional sources of heating with renewable ones. The empirical case study of households in Poland serves as an illustration of the theoretical foundation. The purpose of the study entails the construction of a multi-equation econometric model describing the mechanisms of electricity consumption in a specific household. The model hypothesis indicates that the model should take the form of a system of interdependent equations. The following will be described: the monthly volume of electricity consumption, the cost of this energy payment (in PLN), and the price per one MWh in a given month. Monthly time series from September 2015 to June 2023 were used. The resulting time series amounted to a count of 94 statistical observations. The results in the form of a multi-level empirical econometric model indicate that the economic, environmental, and social benefits of using renewable sources of heating can make a significant contribution to reducing fossil fuel consumption and CO2 emissions. In the context of growing environmental awareness and the need to reduce greenhouse gas emissions, heat pumps are becoming an increasingly important element in the discussion of the future of heating. Their role in transforming the energy sector in the direction of sustainability is crucial.

Digitization brings important changes to the accounting profession, changes related both to the implementation of digitized systems in the routine work of an accountant, and to education in this field, which prepares future accountants. The aim of this paper is to identify the perception and opinion of professional accountants regarding the impact of digitalization on the profession in terms of the challenges brought by digitalization in the accounting field, as well as in terms of the level of knowledge and use of digital systems in Romania. The results obtained through the econometric analysis carried out, help us establish the aspects that requires changes in order to maintain the prosperity of the accounting profession in the context of digitalization.

The current context for the development of smart cities is affected by the economic and social uncertainties generated by the multiple crises that are manifesting themselves in the European space both through the declining geopolitical conflict and the economic recession that the European Union is going through. We aim to conduct a study on smart city vulnerabilities in the current context of uncertainty in order to identify the contribution of smart governance components to increase social welfare. We will also develop a regression model of social welfare for smart cities using empirical and econometric methods (multiple linear regression). The results of the study will highlight the level of smart city development of 10 European regions (Bulgaria, Denmark, France, Germany, Hungary, the Netherlands, Poland, Romania, Sweden and the EU27 average) over the period 2012-2021. The results will be useful for national decision-makers to improve public policies related to smart city development in Europe.

This study aims to explore the relationship between economic growth and performance in Nepal, identifying key drivers for growth. Studying the nexus between economic growth and economic performance in Nepal is crucial for understanding how these factors interact within the nation’s specific context. Growth of gross domestic product (GDP) is represented as the primary indicator for evaluating economic performance, reflecting the overall well-being of a nation's economy. Economic performance encompasses a broader spectrum, including indicators such as employment rate, inflation, income distribution and overall economic stability. Using E-Views 10, a descriptive and analytical research approach has been applied to analyze time series secondary data from 1990–2021 using an econometric model. This study found that faster-growing economies typically experience increased jobs, higher investment, more exports, and often lower inflation. These relationships are part of a long-run equilibrium relationship. In the event of an economic shock disrupting this equilibrium, the economy tends to naturally return to the equilibrium over time. This study found that short-term causality running from lagged GDP, gross capital formation (GCF), exports, human development index (HDI), and employment ratio influence immediate GDP growth. These variables wield a short-term influence over GDP growth; for instance, a sudden surge in exports can prompt a temporary boost in economic growth. This indicates that there is a long-term sustained link between GDP growth and the independent variables rather than merely a short-term event.

Professional football clubs invest vast amounts of money in the recruitment of players. This article presents the latest advances in statistical modeling of the factors that market actors take into consideration to determine the transfer prices of professional football players. It extends to a global scale the econometric approach previously developed by the authors to evaluate the transfer prices of players under contract with clubs from the five major European leagues. The statistical technique used to build the model is multiple linear regression (MLR), with fees paid by clubs as an independent variable. The sample comprises over 8000 transactions of players transferred for money from clubs worldwide during the period stretching from July 2014 to March 2024. This paper shows that a statistical model can explain up to 85% of the differences in the transfer fees paid for players. Despite the specific cases and other possible distortions mentioned in the discussion, the use of a statistical model to determine player transfer prices is thus highly relevant on a global scale.