Hasil untuk "Public finance"

A. C. Pigou

M. Tsechkovski

J. M. Buchanan

Nadezhda I. Yashina, Oksana I. Kashina, Mikhail V. Kazakov

Effective management of public finances is necessary to achieve such objectives as ensuring nationalsovereignty and improving the living standards of citizens. However, uneven territorial developmentleads to socio-economic disparities. This requires the development of individual trajectories and growth points for regions using adaptive budget policy. The study aims to develop a methodological tool and methods for determining the sustainability of territorial budgets, keeping in mind the financial support of program expenditures and the effective implementation of national strategic goals. The object of the study was the sustainability of Russian regions’ budgets. Statistical and economic-mathematical methods ensured the reliability of the study. It is based on the data of the Ministry of Finance and the Federal State Statistics Service of the Russian Federation, which allows to determine various aspects of budget sustainability and conduct an assessment to ensure the country’s strategic national priorities. An overview of current trends and factors ensuring the sustainability of territorial budgets is presented. A methodological tool for monitoring the sustainability of territorial budgets and clustering regions by levels of revenues and expenditures is proposed. It is tested on the data of budget reporting of Russian regions; the characteristics and classes of budget sustainability are defined. The sectoral, infrastructural and socio-economic regional peculiarities that determine the revenues and expenditures of regional budgets are identified. The scientific and practical significance of the study lies in the development of approaches to multidimensional assessment of budget sustainability and identification of individual national strategies of regional development and “anti-stress” scenarios of budget policy.

Fang Wang, Xinci Chen, Guochao Yang

Many public–private partnership (PPP) projects in China are facing increased fiscal expenditure responsibilities and weakened fiscal capacity, which may hinder investment in corporate innovation. Using data from Chinese prefecture-level cities and listed firms from 2014 to 2020, we find that PPP fiscal expenditure responsibilities negatively affect firms’ current and future innovation investment by reducing government subsidies and increasing corporate taxes. This negative effect is more pronounced when PPP fiscal expenditure responsibilities exceed a certain threshold. It is also stronger when local governments have higher levels of debt and lower central transfer payments. The effect is also stronger if the PPP project’s return mechanism increases the government’s future fiscal expenditure responsibilities, but weaker if the project’s operating model revitalizes government assets. The effect on private firms, small firms, high-debt firms, and firms facing strong financing constraints is more pronounced. From the perspective of fiscal capacity, this paper explains the underlying reasons why the effectiveness of government support policies for corporate innovation varies. Additionally, it examines the negative impacts of the financing-oriented PPP model on corporate innovation investment, providing empirical evidence to support options for optimal PPP strategies.

شيرين الحجار

ملخــصالاهداف : عندما يتم جذب وتطوير المواهب بشكل فعال تصبح المنظمة اكثر قدرة على الابتكار وتحقيق معدلات اداء مرتفعه ، وبالتالى سعت هذه الدراسة لقياس اثر تطبيق استراتيجيات ادارة المواهب فى تحقيق التألق التنظيمى لدى العاملين بشركة طنطا للكتان والزيوت.المنهجية : استخدمت الدراسة المنعج الوصفى التحليلى ، وطبقت على عينه قوامها 237 مفردة من العاملين بشركة طنطا للكتان والزيوت ، وتم جمع البيانات عن طرق استمارات الاستقصاء المعده لهذا الغرض ، وبلغ عدد الاستمارات الصحيحه القابله للاختبار الاحصائى( 168) استمارة بنسبة 71% .النتائج : اوضحت النتائج وجود علاقه ارتباط ذات دلالة احصائية بين استراتيجيات ادارة المواهب وبين تحقيق التالق التنظيمى لدى العاملين بمصنع طنطا للكتان والزيوت ، وأكثر هذه الاستراتيجيات إرتباطاً بتحقيق التألق التنظيمى هى استراتيجية الاحتفاظ بالمواهب، كما اثبتت الدراسة وجود تأثير معنوي إيجابي لاستراتيجيات ادارة المواهب ( جذب واختيار المواهب ، تنميه وتطوير المواهب ، إدارة أداء المواهب ، الاحتفاظ بالمواهب ) في تحقيق التألق التنظيمي للعاملين بالشركة محل الدراسة. الخلاصة : ضرورة ربط ادارة المواهب بأهداف ورؤية الشركة مع توضيح ذلك العاملين حتى يبذلوا أقصى قدراتهم لتحسين الأداء وتطوير سلوكيات الابداع والتميز وتحقيق التألق التنظيمى .الكلمات الداله : استراتيجيات ادارة المواهب ، التألق التنظيمى ، بشركة طنطا للكتان والزيوت

Muhammad Ali Imran Caniago, Usman Shabur, Ibi Satibi

This study aims to explore the concept of Al-Mawardi's public loan. This type of research is qualitative with an exploratory approach. Data collection uses the library method. Primary data was obtained from the book Al-Ahkam As Sulthaniyah and secondary data was obtained from several scientific journals and books related to this research. The analysis used is a qualitative analysis involving descriptive and interpretive data exploration. The results of the study show that the book Al-Ahkam As Sulthaniyah discusses state income, state expenditure, and the Baitul Mal. State revenue comes from zakat, ghanimah, and fai'. The state is only allowed to spend the treasures of the baitul mal as long as these expenditures are used for the public good. Al-Mawardi divided the two objectives of allocating Baitul Mal funds: first, for maslahah (benefit) and arfaq (provision of public facilities). Second, for the mandatory function. If the government has an obligation that is a mandatory function, while the funds in the baitul mal are empty, the government may make public loans because it is feared it will cause state chaos. And this policy was never carried out by the Prophet. If the leader dies, the next leader is responsible for repaying the loan.

Wihan van der Heever, Ranjan Satapathy, Ji Min Park et al.

This study leverages explainable artificial intelligence (XAI) techniques to analyze public sentiment towards Environmental, Social, and Governance (ESG) factors, climate change, and green finance. It does so by developing a novel multi-task learning framework combining aspect-based sentiment analysis, co-reference resolution, and contrastive learning to extract nuanced insights from a large corpus of social media data. Our approach integrates state-of-the-art models, including the SenticNet API, for sentiment analysis and implements multiple XAI methods such as LIME, SHAP, and Permutation Importance to enhance interpretability. Results reveal predominantly positive sentiment towards environmental topics, with notable variations across ESG categories. The contrastive learning visualization demonstrates clear sentiment clustering while highlighting areas of uncertainty. This research contributes to the field by providing an interpretable, trustworthy AI system for ESG sentiment analysis, offering valuable insights for policymakers and business stakeholders navigating the complex landscape of sustainable finance and climate action. The methodology proposed in this paper advances the current state of AI in ESG and green finance in several ways. By combining aspect-based sentiment analysis, co-reference resolution, and contrastive learning, our approach provides a more comprehensive understanding of public sentiment towards ESG factors than traditional methods. The integration of multiple XAI techniques (LIME, SHAP, and Permutation Importance) offers a transparent view of the subtlety of the model’s decision-making process, which is crucial for building trust in AI-driven ESG assessments. Our approach enables a more accurate representation of public opinion, essential for informed decision-making in sustainable finance. This paper paves the way for more transparent and explainable AI applications in critical domains like ESG.

David Zámek, Liudmyla Zakharkina

In the context of rapid technological development, digitalization and transparency have a critical impact on national security, promoting transparency and combating corruption, while posing challenges to cybersecurity due to the increased availability of information. The purpose of this study is to identify, based on bibliometric analysis, trends and subject areas in research on the impact of digitalization and transparency on national security. To achieve this goal, a comprehensive bibliometric analysis of scientific works on the role of digitalization and transparency in national security published in the publications indexed by the Scopus database for 1991-2023 was conducted, which formed the statistical basis of the analysis. The bibliometric programs Vosviewer and SciVal were chosen as research tools, which allowed for an in-depth analytical review and identification of the main trends and interrelationships between different research areas, confirming the hypothesis of increasing interest in the study of digitalization and transparency in the context of national security. Based on the analysis of the common use of keywords, seven clusters were identified, covering a wide range of topics from digital transformation and adaptive governance for national security to global political and economic strategies, each of which reveals unique interrelationships between digitalization, transparency, innovation and their impact on national security, including cybersecurity challenges, ethics in governance, and the importance of transparency for democracy and human rights. The analysis of the evolutionary trends in research allowed us to identify four key periods of development of scientific interest in the impact of digitalization and transparency on national security: 1) the period from 2014 to 2016 is characterized by initial research on the role of digitalization in national security and mainly concerns e-government studies; 2) during 2017-2018, research focuses on the growing attention to transparency and its role in national security 3) in the period from 2019 to 2021, there is an increase in the number of studies related to cybersecurity and the impact of digital technologies on democracy; 4) from 2022 to the present, there is further in-depth research on topics related to artificial intelligence The spatial clustering of studies shows a high level of international integration in research on the impact of digitalization and transparency on national security. The findings can be used by state institutions to improve national security strategies, in particular by adapting the legislative framework to the challenges of digitalization and ensuring transparency at all levels of government and public life, including macro (national), meso (regional) and micro (local) levels, ensuring openness and accountability in all spheres of government and public control, which will ultimately contribute to ensuring stability and security at the national level.

Gaurav Meena, Krishna Kumar Mohbey, Sunil Kumar

Sentiment analysis has become a precious tool for businesses because it can be used in so many ways: to find out what customers think about products and services, to build customer relationships and loyalty, to improve customer service, and to use emotional marketing. Over the last several years, developing an end-to-end image sentiment analysis approach has significantly emphasized transfer learning methods. Deep learning algorithms have been proven to achieve remarkable outcomes across a broad spectrum of applications. Examining feelings conveyed by images is complex, but there is much space for development. A technique known as Inception-v3 that can readily focus on large portions of the body, such as a person's face, offers a significant advantage compared to the work that was done in the past. This study makes use of Inception-v3, which is a well-known deep convolutional neural network, in addition to extra deep characteristics, to increase the performance of image categorization. A CNN-based Inception-v3 architecture is employed for emotion detection and classification. The datasets CK+, FER2013, and JAFFE are used in this process. The findings are also compared with various well-known machine learning approaches, and the results obtained by the suggested model are superior. The research indicates that the proposed method can reach an accuracy level of 99.5%. The proposed approach can be used in many business applications such as Information Management, Sales, Marketing, User Interaction, Healthcare, Education, Finance, Public Monitoring, Digital PR, etc.

Nigar Ashurbayli, Ali Yusifov

In the realm of finance, cryptocurrency has emerged as a captivating alternative to traditional investment avenues, such as stocks, bonds, and real estate. Its decentralized nature, unfettered by government or financial institution control, presents a unique proposition in the world of wealth management. The allure of cryptocurrency lies in its potential for substantial returns. Its value has experienced remarkable growth in recent years, offering investors the prospect of significant financial gains. Additionally, cryptocurrency serves as a valuable tool for portfolio diversification, as its performance is often uncorrelated with traditional asset classes. Moreover, cryptocurrency boasts portability and accessibility, making it a convenient and inclusive investment option. Its digital nature allows for seamless storage and transferability, while its global reach enables anyone with an internet connection to participate in the cryptocurrency ecosystem. However, alongside these potential benefits, cryptocurrency also harbors inherent risks. Its volatility poses a challenge, as its value can fluctuate dramatically in a short period. Regulatory uncertainty looms, as governments worldwide grapple with the implications of cryptocurrency and may impose restrictive measures. Furthermore, security concerns persist, as cryptocurrency exchanges and wallets have fallen prey to cyberattacks, jeopardizing investors' assets. In light of these considerations, investing in cryptocurrency demands a thoughtful approach. Investors must carefully assess their risk tolerance and align their investment goals with the inherent risks associated with cryptocurrency. Thorough research and a well-diversified portfolio are crucial for navigating the complexities of this emerging asset class. The purpose of the article is to analyze the profitability and safety of investments in cryptocurrency and study the different methods associated with it.

Aja Fatou Senghore

The main objectives of this paper are three-fold. First, to identify the barriers to financial independence of female vegetable producers in the Gambia. Second, to assess the potential use of Islamic financing modes as enablers that can capacitate women in the Gambia’s horticultural sector. Finally, it proposes an inclusive financing mode to empower women in the country’s horticultural sector. To achieve these three objectives, different methodological approaches were used, drawing on various data collection techniques, including primary and secondary data collection methods. The results from the study indicate that lack of irrigation and storage facilities, access to markets and farming inputs (seeds, fertilisers) are the main challenges women encounter in their gardening activities. The study further found that the benefits of accessing and using microfinance services are impeded by these challenges, thereby preventing women vegetable producers from upscaling their horticultural activities. However, it is established in the paper that microfinance has great potential for promoting the financial independence of women in the Gambia, particularly women who engage in the horticultural sector. Based on these findings, the paper recommends using Parallel Salam Contract to tackle the problems of irrigation, storage facilities and market access. Murabahah/Musawamah contracts are also suggested to tackle the issue of the lack of farming inputs used by women in the horticultural sector. We further recommend that Islamic financial institutions educate the public about their business activities and for the regulators, including the Central Bank of the Gambia, to establish a Central Shari’ah Board to ensure the unification of fatwahs in the emerging Islamic finance sector in the Gambia, thereby ensuring transparency in the activities of the financial institutions participating in this sector and thus encourage more investors to partake in this burgeoning part of the Gambian economy.

Chuan-Hsiang Han, Kun Wang

Abstract Tail risk is a classic topic in stressed portfolio optimization to treat unprecedented risks, while the traditional mean–variance approach may fail to perform well. This study proposes an innovative semiparametric method consisting of two modeling components: the nonparametric estimation and copula method for each marginal distribution of the portfolio and their joint distribution, respectively. We then focus on the optimal weights of the stressed portfolio and its optimal scale beyond the Gaussian restriction. Empirical studies include statistical estimation for the semiparametric method, risk measure minimization for optimal weights, and value measure maximization for the optimal scale to enlarge the investment. From the outputs of short-term and long-term data analysis, optimal stressed portfolios demonstrate the advantages of model flexibility to account for tail risk over the traditional mean–variance method.

Raysa Capote Pérez, Amalia Díaz Silva, Carlos Cesar Torres Paez et al.

The main objective of this article is to propose a microcredit program to stimulate Local Economic Development projects. This definition is based on the preponderant role of local development in Cuba, which has become a public policy of strategic importance as a complement to the National Economic and Social Development Plan until 2030, as well as a central and articulating axis of the public agendas of governments at the municipal and provincial levels. However, there is evidence of financial limitations to implement development project ideas in the state and non-state sector, as a consequence, among other factors, of the limited offers of financial mechanisms that stimulate entrepreneurs to put their business ideas into operation. The methods used in the research were: historical-logical, systemic and modeling to determine the trends in the management of microcredits in terms of local development and to support the proposed procedure for the allocation of microcredits to finance local economic development projects. The proposed microcredit program represents a support tool to solve the scientific problem stated in this research. The procedure has a set of suggestions that will facilitate its application, which are variable according to the criteria of the local actors.

شيماء أحمد حسن عبد الحميد

يتناول هذا البحث التعرف على أثر المرونةفى جدول العمل على سلوک المواطنة التنظيمية وذلک بالتطبيق على العاملين فى شرکات توزيع الأدوية ، وقد اقتصر مجتمع الدراسة على أکبر ستة شرکات لديها أعلى قيمة سوقية بجمهورية مصر العربية وذلک طبقآ للتقارير الرسمية الصادرة من مرکز التخطيط والسياسات الدوائية بوزارة الصحة المصرية ، يتمثل مجتمع البحث فى (302) مفردة ، ولتحقيق أهداف البحث تم صياغة ثلاث فروض رئيسة ، للتحقق من تلک الفروض قامت الباحثة باستخدام مجموعة من الأساليب الإحصائية تمثلت فى : الإحصاء الوصفى ، تحليل التباين ، معامل ألفا کرونباخ ، الانحدار المتعدد ، معامل اختبار مان ويتنى ، تحليل معامل الارتباط بيرسون . وأسفرت نتائج التحليل الإحصائى عن وجود إرتباط معنوى موجب بين المرونة فى جدول العمل وسلوک المواطنةالتنظيمية ، کما وضحت النتائج أيضآأنه توجد فروق معنوية بين متوسطى سلوک المواطنة التنظيمية لمن يتفاوض من اجل الحصول على مرونة فى جدول العمل فيما يتعلق بتوقيت التفاوض أو النية للتفاوض مستقبلآ ، أيضآ من يحقق رغبته مرونة جدول العمل ، کذلک نظرة الزملاء عند السعى لذلک .کمالا توجد فروق معنوية بين متوسطات سلوک المواطنة التنظيمية للمجموعات فيما يتعلق بالسن او النوع او عدد سنوات الخبرة ومستوى التعليم والحالة الوظيفية.

Charles J. Hadlock, C. James

Lianbiao Cui, Yuran Huang

J. Abor, N. Biekpe

Lu Xu, Yongsheng Hong, Yu Wei et al.

Visible and near-infrared reflectance (VIS-NIR) spectroscopy is widely applied to estimate soil organic carbon (SOC). Intense and diverse human activities increase the heterogeneity in the relationships between SOC and VIS-NIR spectra in anthropogenic soil. This fact results in poor performance of SOC estimation models. To improve model accuracy and parsimony, we investigated the performance of two variable selection algorithms, namely competitive adaptive reweighted sampling (CARS) and random frog (RF), coupled with five spectral pretreatments. A total of 108 samples were collected from Jianghan Plain, China, with the SOC content and VIS-NIR spectra measured in the laboratory. Results showed that both CARS and RF coupled with partial least squares regression (PLSR) outperformed PLSR alone in terms of higher model accuracy and less spectral variables. It revealed that spectral variable selection could identify important spectral variables that account for the relationships between SOC and VIS-NIR spectra, thereby improving the accuracy and parsimony of PLSR models in anthropogenic soil. Our findings are of significant practical value to the SOC estimation in anthropogenic soil by VIS-NIR spectroscopy.

Nezih Guner, Remzi Kaygusuz, Gustavo Ventura