Econometric Model Research Articles

Sustainable energy consumption – empirical evidence of a household in Poland Sustainable energy consumption, electricity demand , econometric model, household energy transition, energy policy impact

Sustainable energy consumption – empirical evidence of a household in Poland Sustainable energy consumption, electricity demand , econometric model, household energy transition, energy policy impact

Logistic Model Usage Factors Apps to University Students

In the age digitalized information and technology its show a phenomenon that the applications new technologies with young generate dependence to dispositive, in special the mobile application and smartphones it is are grate tools to process management academic in the higher education institutions. Is intends develop the logit econometric model to determine the probability of using the necessary information tools in an academic App for university students. The study determines five (4) information factors required by students to consider them of quality. The results show that the factors identified are associated with information from academic administrative processes, academic information, interactive connectivity and other general ones. It concludes that observed factors that the

Innovation as a driver of business tourism competitiveness

Purpose The purpose of this study involves analysing the factors of and barriers to innovation and their respective impacts (directly and indirectly) on the competitiveness of both destination and their host companies. Design/methodology/approach Based on primary data collected by questionnaire from a sample of 119 companies operating in the tourism sector in the autonomous region of Madeira (Portugal), the authors applied a quantitative methodology with recourse to econometric models and multiple linear regression. Findings Comprehensive results based on a conceptual model are obtained through the analysis of competitiveness tourism-based and innovation factors. The study identifies and empirically tests the existing and underlying relationships between innovation (factors and barriers) as the means of leveraging the competitiveness of destinations and their companies. Originality/value The results hold important theoretical and practical implications contributing towards innovation for competitiveness and filling a shortcoming identified in the literature.

Do Water Transfer Projects Promote Water Use Efficiency? Case Study of South-to-North Water Transfer Project in Yellow River Basin of China

With a huge capital and labor input influx, inter-basin water transfer (IBWT) projects have been shown to effectively mitigate water stress and ensure the water demand for social and economic development in the receiving area. Whether they have promoted the improvement of regional water use efficiency (WUE) is crucial for sustainable management of regional water resources. Targeting the South-to-North Water Transfer Project (SNWTP), the largest and most ambitious inter-basin water transfer project in China, this study establishes quantitatively econometric models to analyze the impact of different water diversion projects, specifically the eastern route of the SNWTP (ER-SNWTP), middle route of the SNWTP (MR-SNWTP), and diversion from the main stream of the Yellow River (DYR), on the regional water consumption per unit of GDP; regional water stress, water use structure, economic structure, and urbanization level are used as control variables in different types of cities in the Yellow River Basin, and some intriguing results are found. While the overall water transfer project demonstrates a positive impact on water use efficiency, the effects of the three water transfer measures vary significantly. The ER-SNWTP does not exhibit a notable positive effect on regional water use efficiency, whereas the MR-SNWTP demonstrates a significant positive impact. Interestingly, the DYR has a notable negative influence on water use efficiency in developed cities. The water use structure, shaped by the pricing, scale, and policies of different projects, emerges as a pivotal factor in explaining these differences. Finally, this paper suggests that the impact of water transfer projects on the improvement of regional water use efficiency be viewed from a more comprehensive and developmental perspective.

Credit Growth and Risk Management in Indian Banks: Analysis Through Sectoral Deployment

This research paper explores the dynamics of sectoral credit deployment and its impact on risk management within the Indian banking sector over three fiscal years (2021-2023). Utilizing data from the Reserve Bank of India's annual reports, the study delves into the growth patterns of credit allocation to agriculture, industry, services, and personal loans, and assesses corresponding risk metrics such as the Gross Non-Performing Assets (NPA) ratio, Provision Coverage Ratio (PCR), and Capital Adequacy Ratio (CRAR). Descriptive statistics, correlation analysis, and regression modelling were employed to identify relationships and impacts. The findings reveal substantial credit growth in the services and personal loan sectors, accompanied by significant improvements in risk management indicators, including a marked reduction in the Gross NPA ratio and enhanced Provision Coverage Ratios. These trends highlight the sector’s increasing resilience and risk preparedness, reflecting broader shifts towards a consumer-driven financial landscape. The paper discusses the implications of these findings for banking stability and economic policy, emphasizing the need for nuanced regulatory frameworks to manage sector-specific risks. Future research could extend this analysis to predict long-term impacts of credit expansion on financial stability using advanced econometric models.

Differential Analysis of Carbon Emissions between Growing and Shrinking Cities: A Case of Three Northeastern Provinces in China

Carbon emission issues are becoming increasingly severe, and the carbon emissions in shrinking cities, primarily characterized by population loss, are often overlooked and insufficiently studied. This paper focuses on the carbon emissions from county-level administrative units in China’s three northeastern provinces from 2001 to 2017. The study scientifically identified shrinking cities and measured the differences in carbon emission characteristics between growing and shrinking cities using the Theil index. Ultimately, the paper constructs a panel spatial econometric model to analyze the factors influencing them and explore their spatial effects. (1) The total carbon emissions in the Three Northeastern Provinces exhibited an inverted U-shaped trend, increasing from 734.21 million tons in 2001 to 1731.73 million tons in 2017, with the Mann–Kendall trend test showing a significant increase; spatially, this manifests as a significant positive spatial autocorrelation. (2) The region has 138 shrinking cities, accounting for over 50%; regarding carbon emission characteristics, the Theil index has consistently remained above 0.18, indicating significant differences between the carbon emissions of growing and shrinking cities. (3) The panel spatial econometric model results show that the influencing factors of carbon emissions in shrinking cities have unique directions, intensities, and spatial effects. In shrinking cities, aside from localized GDP effects and per-capita GDP acting as a suppressant, the population size has a pronounced inhibitory effect on local and surrounding carbon emissions. The analysis reveals significant differences in the carbon emission patterns and mechanisms between growing and shrinking cities; based on these results, the paper proposes differentiated carbon control strategies.

Economic complexity and income inequality in Russian regions

Although economic growth leads to a reduction in poverty, the growing income inequality and its possible consequences are of some concern. The level of economic complexity has recently been increasingly viewed as an important predictor of income inequality. In this paper, using pool and models with time fixed effects, the impact of the economic complexity index on income inequality in Russian regions for 2013 and 2015 was estimated. The results of the evaluation of econometric models show that regions with more complex economies showed a higher level of income inequality compared to others. The explanations for the effect obtained include an increase in demand for highly qualified labor as a result of the development of high-tech industries and an increase in wage differentiation between high-skilled and low-skilled workers, as well as the migration of high-skilled workers to economically more complex regions. The main conclusion is that economic complexity is a significant factor of the variation in income inequality and should also be taken into account while conducting economic and social policy in Russian regions.

Social capital, government guidance and contract choice in agricultural land transfer.

This study explores the impact of farm households' social capital characteristics and local government policies on the selection of farmland transfer contracts in China's rural industrial revitalization context. Utilizing field research data from 1,979 households in ethnic areas of Hunan Province, this paper constructs an econometric model to assess how farm households' social capital and local governments' involvement in rural industrial revitalization influence farmland transfer contract selections. The findings indicate that, lacking government program support, farmers' social capital significantly affects contract type and duration, but not the rent. Specifically, farmers possessing extensive social capital prefer verbal and short-term contracts (coefficients of 0.525 and 0.643, significant at the 5% level), whereas their influence on rent (coefficient of 2.418, significant at the 5% level) manifests under government program support. These results challenge the conventional theory of farmland transfer contracts and offer substantial empirical support for the development of local government policies in rural industrial revitalization, underlining the critical role of government guidance and social capital in enhancing farmland transfer.

Identification of returns to new technologies under distinctive econometric approaches

ABSTRACT This article uses distinctive econometric models to investigate returns to new technologies and whether adoption decisions can be explained by comparative advantage. I consider three models: static and dynamic panel models of homogeneous returns to fertilizer, as well as the correlated random coefficient model of heterogeneous returns. I discuss both the benefits of using each of the models and their interpretations. I then use data from cocoa farming in Ghana to identify the returns to fertilizer by means of these three models. The estimated average returns in different models are positive, high and strongly significant statistically. I also find evidence of heterogeneous returns to new technology based on comparative advantage. My overall results suggest that adoption of new agricultural technologies may not necessarily benefit all farmers, and the adoption decision may be crop-specific, context-specific or technology-specific.

Make Lectures Match How We Learn: The Nonlinear Teaching Approach to Economics

This paper proposes a nonlinear teaching approach, based on learning theories in cognitive psychology, with a special focus on large-cohort economics modules. The fundamental rationale is to match the features of teaching with the nature of learning. This approach was implemented in an undergraduate economics module, which received qualitative feedback and quantitative evaluation. Formal econometric models with both binary and continuous treatment effects were developed and estimated to quantify the effects of the proposed approach. Evidence shows that the nonlinear teaching approach significantly improves the effectiveness and efficiency of the learning-teaching process but does not promote student attendance.

FDI impact: catalyzing digital capabilities in host nations

Purpose This study aims to investigate the impact of foreign direct investment (FDI) on national digital capability, specifically differentiating the impact between FDI greenfield and mergers and acquisitions (M&A). The research also investigates factors shaping digital capabilities, encompassing government transparency and absorptive capability, while exploring the mediating influence of absorptive capability in the FDI–digital capability relationship. Design/methodology/approach An econometric model has been developed to examine the interrelationship between national digital capability, FDI inflows, national absorptive capability and government transparency. The data set encompasses 55 countries over a period of nine years (2013–2021). National digital capability data is derived from the well-established index published by the World Competitive Centre (WCC). The sources of the explanatory variables align with standard practices, drawing from reputable institutions (UNCTAD and the World Bank, among others). Findings The findings reveal a significant positive impact of FDI, particularly in greenfield investments, on national digital capability. Government transparency and research and development (R&D) investment are crucial factors contributing to digital capabilities. Additionally, the absorptive capacity, reflected by R&D investment, also emerges as a potential moderating factor, influencing the impact of FDI inflows on digital capabilities. Practical implications The results recommend that policymakers and stakeholders should carefully consider the role of FDI, especially in greenfield investments, as a catalyst for enhancing national digital capability. The findings also underscore the significance of promoting government transparency and directing investments towards R&D to nurture digital capabilities. Moreover, understanding the mediating role of absorptive capability can inform strategies aimed at optimizing the impact of FDI on digital capabilities. Originality/value This study contributes uniquely to the existing literature by being the first to systematically explore the influence of FDI on national digital capability. Furthermore, it presents innovative empirical findings on the role of absorptive capability in enhancing the FDI impact on national digital capability, an area that remains relatively uncharted in current literature.

Diagnostics of the influence of medical and demographic indicators on regional socio-economic systems

The article presents approaches to monitoring and assessing social aspects of regional systems with identification of elements of the health system and demographic components that potentially affect the economic efficiency of functioning of territories. The relevance of the article is determined by objective features of the development of mesoterritories. The analysis of spatial features of the systems’ functioning was conducted on the materials of the Central Federal District. The purpose of the study is to assess the features of the regional genesis using regression analysis and the resulting indicator – gross regional product (hereinafter referred to as GRP), which allows us to give a more reliable characterisation of the mesoterritorial transformation. The subjects were grouped according to the quality of medical and demographic characteristics on the basis of the cluster analysis with further allocation of flagship, catching-up and lagging regions. To substantiate the reliability of the territories’ affiliation to a specific cluster group, a statistical analysis was performed on average values with consideration to identification of the level of medical and demographic development. The conclusion is made about the influence of some factor criteria on the regional space with the construction of a scatter plot. It displays the affiliation to the selected confidence interval and distribution of the elements of the set in the plane between the resulting and factor values, describing the dependence of the GRP on the medical and demographic indicator. These econometric and analytical models can be used by regional governments in the process of strategic planning.

Do Natural Disasters Reduce Loans to the More CO2-Emitting Sectors?

We studied the impact of major floods occurring in Turkey between 2005 and 2020 on lending and the allocation of loans between sectors that differ in their CO2 emissions. Our evidence shows that the floods are not significant determinants of lending or the allocation of loans between sectors, even though CO2 emissions contribute to the reallocation of loans from the more polluting to the less polluting sectors. Indeed, risks and returns of the sector remain the main determinants of lending and of the allocation of loans among sectors. The results are robust to alternative estimation methods and specifications of the econometric models. Since in the period of investigation no environmental regulations were implemented in Turkey, and the Paris Agreement was ratified only at end-2021, the evidence suggests that more stringent regulations and green policies are required to accelerate the green transition in Turkey.

Strategic Integration: Fostering Sustainability in Low-Income Country through Poverty Alleviation, Carbon Efficiency, Energy and Economic Resilience

This study emphasizes the critical importance of strategic integration for sustainable development goals (specifically Goals 1 and 2) in low-income countries (LICs). The research uses econometric models to focus on poverty reduction, economic resilience, energy use, and carbon emissions in Indonesia from 1996 to 2022. The study reveals a long-run co-integration among the estimated parameters, with a significant speed of adjustment at a 1.04% level. ECM models highlight a positive relationship between energy use, poverty, and carbon emissions while indicating a negative association between economic growth and carbon emissions. Robustness checks support these findings, including Fully Modified Ordinary Least Squares (FMOLS) and Canonical Co-Integrating Regression (CCR). Granger causality analysis reveals a unidirectional causality from energy use to carbon emissions and economic growth, along with one-way causation from carbon emissions to economic growth and poverty. Diagnostic tests affirm the model's reliability. The study's outcomes contribute valuable insights to the discourse on strategic integration, offering policymakers and stakeholders guidance in formulating sustainable development strategies tailored to the unique challenges encountered by low-income countries.

The role of thematic specialization in international scientific collaboration: the case of Chagas research

Abstract Scientists are increasingly specializing to manage the vast knowledge bases within their domains, making knowledge-sharing strategies essential for scientific progress. Among these strategies, international scientific collaboration has increased markedly. We analyse the role of thematic specialization as one of its drivers in the context of Chagas research, a neglected disease. Since there is a strong research tradition in Latin America on this topic, it is an interesting context to study centre-periphery research dynamics. Using a novel bibliometric database on Chagas research during 1990–2019, we exploit its panel structure in a gravity-type econometric model. The findings show that the degree of specialization and its proximity among partners boost joint publications. Both effects are particularly important for country dyads involving authors from the periphery linked to authors in the centre. This paper is the first empirical study to assess the role of specialization as a driver of international scientific collaboration.

Causal impact evaluation of occupational safety policies on firms’ default using machine learning uplift modelling

It is often undermined that occupational safety policies do not only displace a direct effect on work well-being, but also an indirect effect on firms’ economic performances. In such context, econometric models dominated the scenes of causality until recently while Machine Learning models were seen with skepticism. With the rise of complex datasets, an ever-increasing need for automated algorithms capable to handle complex non-linear relationships between variables has brought to uncover the power of Machine Learning for causality. In this paper, we carry out an evaluation of a public aid-scheme implemented in Italy and oriented to support investment of small and medium enterprises (SMEs) in occupational safety and health (OSH) for assessing the impact on the survival of corporations. A comparison of thirteen models is performed and the Individual Treatment Effect (ITE) estimated and validated based on the AUUC and Qini score for which best values of 0.064 and 0.407, respectively, are obtained based on the Light Gradient Boosting Machine (LightGBM). An additional in-depth statistical analysis also revealed that the best beneficiaries of the policy intervention are those firms that experience performance issues in the period just before the interventions and for which the increased liquidity brought by the policy may have prevented default.

Spatiotemporal variations and influencing factors of methane emissions from livestock in China: A spatial econometric analysis

In recent years, China has been implementing policies to improve the livestock industry in response to the global trend toward green and low-carbon development. These policies include the establishment of demonstration zones for high-standard agriculture, the relocation of farms to the north, etc. This study aims to investigate the impact of changes in the spatial structure of the livestock industry on methane emissions. It used panel data from 31 provinces in China from 2001 to 2021 and applied the IPCC methodology to quantify methane emissions at both the national and provincial levels. In addition, a spatial econometric model was used to analyze the impact of changes in the spatial structure of the livestock industry on methane emissions. The results show that methane from livestock in China decreased from 13.85 million tons in 2001 to 11.82 million tons in 2021. In addition, methane emissions from livestock in China show a significant spatial gradient and correlation. The Southwest has the highest methane emissions, accounting for 24 % of the total emissions. After controlling for spatial correlation and other factors in the model, it was found that the spatial structure of the livestock industry has a different influence on methane emissions both in the province and in neighboring provinces. To improve methane emission efficiency in the future, policies such as establishing functional zones for livestock farming, strengthening technological innovation and sharing for green development in agriculture, and promoting the optimization of agricultural and rural management structures should be implemented.

Unlocking Economic Resilience: A New Methodological Approach and Empirical Examination under Digital Transformation

Economic resilience is crucial for urban sustainability as it ensures stability and growth in the face of external shocks, promotes social cohesion and inclusivity, fosters environmental sustainability, and enhances cities’ adaptability to future challenges. This study expands the conventional perspective on economic resilience beyond the context of shocks, focusing on the inherent resilience of regional economic systems. A novel method for quantifying economic resilience is introduced, emphasizing system sensitivity and adaptability. Using Chinese prefecture-level city data and an econometric model, we empirically examine how Fintech, a major digital transition in current urban systems, affects economic resilience. The findings reveal that Fintech has a substantial positive effect on economic resilience, primarily through the upgrading of industrial structures and technological innovation. Furthermore, there is significant regional heterogeneity in the impact of Fintech on economic resilience, with more pronounced contributions in the east, central, and western regions of China, as opposed to the northeast. Additionally, the impact of Fintech on economic resilience is more substantial in large-scale cities. The promotion of economic resilience through digital transformation serves as a potent risk prevention measure. Understanding the role of economic resilience in urban systems holds valuable implications for countries worldwide.

Analysis of Synergistic Effect of Energy Efficiency Improvement and Vocational Competence Development

INTRODUCTION: Growing global energy demand and constant competition for energy resources have made energy efficiency a focus of international attention. At the same time, occupational competency development is crucial for sustained individual and overall economic growth.OBJECTIVES: This study explores the synergistic effects of energy efficiency improvement and occupational competence development to inform policy-making and business strategies.METHODS: A literature review summarises relevant theories and research progress on energy efficiency improvement and occupational capability development. Then, the relationship between energy efficiency improvement and vocational ability development was analyzed in depth using econometric models and a large amount of empirical data.RESULTS: There is a significant positive association between energy efficiency improvement and vocational ability development. Specifically, improving energy efficiency not only reduces the cost of energy consumption and enhances productivity but also helps promote technological innovation and industrial upgrading, which in turn enhances the level of occupational ability of workers. In turn, improving occupational ability further encourages technological innovation and productivity in enterprises, forming a virtuous circle and promoting the sustainable development of the economy.CONCLUSION: This study reveals the synergistic effect between energy efficiency improvement and vocational competence development, emphasizing the critical role of energy efficiency improvement and vocational competence development in promoting economic growth and achieving sustainable development. 

Behavioural determinants of the healthcare providers in Ukraine: Focus on competition context

The development of the healthcare system is an important task for every country, given that long-term economic and social development is absolutely impossible without a healthy nation. Therefore, improving public health and ensuring that the maximum number of people have access to quality healthcare services is one of the state's strategic priorities. In this regard, the authors of the paper set a goal to establish how the reform of the healthcare system in Ukraine has led to changes in the behavioural determinants of healthcare providers and recipients in the domestic healthcare market. The paper uses such research methods as comparison, visualization, graphical data visualization tools, and statistical methods of data analysis. The study revealed that Ukrainian citizens got a chance to freely choose their physicians by signing declarations with them, which led to increased competition among physicians and other doctors and healthcare facilities; at the same time, the number of declarations signed with private healthcare facilities increased significantly. Furthermore, the developed econometric model allows us to identify statistically significant relationships between the amount of state funding and lifestyle and environmental indicators, which will allow us to improve the mechanisms and amount of funding in the sector, improving the health of the nation in the new competitive environment.