Hasil untuk "Public finance"

Oana Oprisan, Irena Munteanu

The purpose of this research is to evaluate the adequacy, structure, and effectiveness of education financing in Romania during the period 2020–2025, using a comparative European Union perspective. The main research objectives are to analyse the dynamics of public education expenditure in relation to GDP and EU benchmarks, to examine the allocation between current and capital expenditures, and to assess the implications of financing patterns for educational equity and system performance. The findings highlight persistent underinvestment compared to EU standards, the strong predominance of current spending, and significant territorial disparities in educational outcomes. Despite recent increases in funding and the extensive use of European Union financial instruments, including the Recovery and Resilience Facility, structural weaknesses in the financing framework remain largely unresolved. The study contributes to education economics and public finance literature by formulating evidence-based policy implications aimed at improving fiscal sustainability, allocative efficiency, and social equity in emerging European education systems.

Mislav Brkić

Following the shift in the European Central Bank's (ECB) monetary policy in mid2022, the interest income of euro area banks rose markedly, boosting their overall profitability. This paper shows that the positive impact of higher interest rates on bank profitability was amplified by the existence of abundant excess liquidity. In particular, since euro area banks held large stocks of excess liquidity, they were able to earn substantial risk-free interest income by simply putting their liquidity into the ECB’s deposit facility. In addition, due to the prolonged period of monetary expansion and zero interest rates on time deposits, the share of overnight deposits in total bank liabilities had increased significantly by the time the ECB tightened its policy. Since overnight deposits typically respond slowly to policy rate changes, such a structure of funding enabled euro area banks to enjoy comfortable net interest margins for some time.

Brynjólfur Stefánsson, Ásta Guðrún Helgadóttir, Martin Nizon-Deladoeuille et al.

Digital public services have revolutionised citizen and private sector interactions with governments. Certain communities are strongly dependent on such digital services for ensuring the availability of public services due to geographical isolation or the presence of adverse geophysical and weather phenomena. However, strong and effective security is key to maintaining the integrity of public records and services yet also for ensuring trust in them. Trust is essential for user uptake, particularly given a global increase in data-protection concerns and a turbulent geopolitical security environment. In this paper, we examine the case of public trust in various forms of authentication for electronic identification in Iceland, which has high availability requirements for digital public services due to its unique and dynamic geophysical characteristics. Additionally, Iceland has historically low levels of institutional trust which may conflict with the requirement for an increased need for digital public services. Through surveying the Icelandic general public, we find that there is a high-level of trust in digital identification services across all demographics. We conclude with a discussion and future research challenges towards improving the effectiveness of authentication considering the diverse groups within Icelandic society, such as the rapidly increasing population of migrants and the large and dynamic population of tourists.

Fanjun Bu, Kerstin Fischer, Wendy Ju

In this work, we analyze video data and interviews from a public deployment of two trash barrel robots in a large public space to better understand the sensemaking activities people perform when they encounter robots in public spaces. Based on an analysis of 274 human-robot interactions and interviews with N=65 individuals or groups, we discovered that people were responding not only to the robots or their behavior, but also to the general idea of deploying robots as trashcans, and the larger social implications of that idea. They wanted to understand details about the deployment because having that knowledge would change how they interact with the robot. Based on our data and analysis, we have provided implications for design that may be topics for future human-robot design researchers who are exploring robots for public space deployment. Furthermore, our work offers a practical example of analyzing field data to make sense of robots in public spaces.

Hongjian Yu, Xiufan Zhang

Coordinating policies is an essential guarantee for carbon emission reduction and sustainable development. Based on the theoretical framework of the policy paradigm, we quantitatively analyze 266 policy documents on promoting carbon emission trading and green financial policies from 2011 to 2022 using the content analysis research method. Based on the matching network of "policy objectives-policy tools," we analyze the synergistic characteristics of carbon emission trading policies and green financial policies in promoting carbon emission reduction targets and reveal the matching mode of "objectives-tools" of green financial policies by using social network analysis. It is found that, first, from the perspective of policy objectives, the main policy objectives of carbon emissions trading are to promote green innovation of enterprises, and the main policy objectives of green finance are to promote green development, which reflects the consistency and endogenous motivation of policy objectives. Secondly, command-control and market incentive policy tools are the main policy tools in the structure of policy tools. The proportion of public participation policy tools is small, and there is a structural asymmetry. Third, carbon emissions trading tools focus on supervision, adjustment, and platform construction. The green financial policy tools have the characteristics of guidance, public welfare, and externality. The two constitute a complementary, embedded, and integrated ' double synergy ' carbon emission reduction policy. Based on this, this paper puts forward some suggestions to promote policy coordination and provides a reference for China to achieve the dual carbon goal.

Bo Zhou, Jintao Tan, Wenli Li et al.

BackgroundIn China, over 5 million people have been identified and registered by the public security institutions for using illicit drugs. The aim of this study is to compare the influence of different types of illicit drugs on the self-reported mental health of Chinese people. In particular, we want to assess the damage of Heroin, Methamphetamine and Ketamine to mental health in a social environment where drug use is strictly regulated.MethodsThe study is based on survey with 6,906 people who use drugs in Guangdong province, China. Risk of mental health issue is measured using the Brief Symptoms Inventory 18 (BSI-18) Scale, and a higher BSI-18 score indicates more severe mental health problems. The data was analyzed through multilevel regression analysis, propensity score matching analysis and mediation analysis.ResultsThe three major types of illicit drugs have both moderating and mediating effects on the length of drug-use history, that Heroin use leads to longer drug-use duration, while Ketamine use causes more damage on mental health per unit time of drug-use duration. Average duration of Methamphetamine use is 0.7 year shorter than average duration of Heroin use, and average duration of Ketamine use is 1.7 year shorter than average duration of Heroin use. For each year of increase of drug-use duration, Ketamine use leads to 1.2 times more of BSI score increase than Heroin use, and 2.3 times more of BSI score increase than Methamphetamine use.ConclusionThese three drugs are associated with severe mental health issue in a society with strict drug regulation. Attention should be paid to the mental health of people regardless of the type of drugs they use.

Mithinti Srikanth, G. Ramakrishna

Public transport administrators rely on efficient algorithms for various problems that arise in public transport networks. In particular, our study focused on designing linear-time algorithms for two fundamental path problems: the earliest arrival time (\textsc{eat}) and the fastest path duration (\textsc{fpd}) on public transportation data. We conduct a comparative analysis with state-of-the-art algorithms. The results are quite promising, indicating substantial efficiency improvements. Specifically, the fastest path problem shows a remarkable 34-fold speedup, while the earliest arrival time problem exhibits an even more impressive 183-fold speedup. These findings highlight the effectiveness of our algorithms to solve \textsc{eat} and \textsc{fpd} problems in public transport, and eventually help public administrators to enrich the urban transport experience.

Linn Arnell, Emma Engström, Gazi Salah Uddin et al.

Abstract This study uses the dynamic conditional correlation to investigate how technology subsector stocks interact with financial assets in the face of economic and financial uncertainty. Our results suggest that structural breaks have diverse effects on financial asset connectedness and that the level of bond linkage increases when the trend breaks. We see a growing co-movement between the technology sector and major financial assets when uncertainty is considered. Overall, our findings indicate that the connectedness response varies depending on the type of uncertainty shock.

Abdulkadir Soygüder

Türkiye’nin dış ticaretinde önemli bir alanı kaplayan orman ürünleri; kâğıt, mobilya, lif levha (MDF), yonga levha, OSB, kontrtabla, kontrplak, tomruk, kereste, ambalaj gibi katma değeri yüksek eşyaları kapsamaktadır. Bu çalışmada 441112, 441113 ve 441114 GTIP nolu lif levha eşyasının son zamanlardaki döviz kuru artışı karşısındaki dış ticaret verileri irdelenecektir. Trademap üzerinden; 2018-2023 yılları arasındaki lif levha eşyasına ait dış ticaret verileri çeyrek veriler şeklinde çekilmiş ve düzenlenmiştir. Lif levha dış ticaretinde söz sahibi olan ülkelerin verileri Trademap, Türkiye’de MDF üretimi de FAOSTAT sitesinden elde edilmiştir. Türkiye’de 2018-2023 yıllarına ait döviz kuru değişimi EVDS’den çeyrek veriler şeklinde elde edilmiş ve lif levha eşyasının döviz kuruna göre dış ticareti korelasyon ile regresyon analizleri ışığında yorumlanmıştır. Analizler neticesinde döviz kurundaki yükselmelerin %95 güvenirlikte Türkiye’nin lif levha ihracatı ile anlamlı (%93), lif levha ithalatı ile anlamsız (%49) bir ilişkisi olduğu sonucuna varılmıştır. Türkiye’nin lif levha dış ticaretinin orman ürünleri dış ticareti içindeki hatırı sayılır katkısı da düşünüldüğünde ilerleyici potansiyelini aşikâr etme açısından bu çalışma literatüre katkı sağlayacağı düşünülmektedir.

Paolo Vanini, Sebastiano Rossi, Ermin Zvizdic et al.

Abstract Online banking fraud occurs whenever a criminal can seize accounts and transfer funds from an individual’s online bank account. Successfully preventing this requires the detection of as many fraudsters as possible, without producing too many false alarms. This is a challenge for machine learning owing to the extremely imbalanced data and complexity of fraud. In addition, classical machine learning methods must be extended, minimizing expected financial losses. Finally, fraud can only be combated systematically and economically if the risks and costs in payment channels are known. We define three models that overcome these challenges: machine learning-based fraud detection, economic optimization of machine learning results, and a risk model to predict the risk of fraud while considering countermeasures. The models were tested utilizing real data. Our machine learning model alone reduces the expected and unexpected losses in the three aggregated payment channels by 15% compared to a benchmark consisting of static if-then rules. Optimizing the machine-learning model further reduces the expected losses by 52%. These results hold with a low false positive rate of 0.4%. Thus, the risk framework of the three models is viable from a business and risk perspective.

Yunxu Wang, Chi-Wei Su, Yuchen Zhang et al.

As an important indicator that can reflect a country’s macroeconomic situation and future trend, experts and scholars have long focused on analyses and predictions of gross domestic product (GDP). Combining principal component analysis (PCA), the mixed-frequency data sampling (MIDAS) model and the error correction model (ECM), this investigation constructs the principal-component-based ECM-MIDAS and co-integration MIDAS (CoMIDAS) models, respectively. After that, this investigation uses the monthly consumption, investment and trade data to build a mixed-frequency model to predict quarterly GDP. The empirical results can be summarized as follows: First, the predictive effectiveness of the mixed-frequency model is better than that of the same-frequency model. Second, the three variables have a strong correlation, and applying the principal component idea when modelling the same and mixed frequencies can lead to more favourable predictive effectiveness. Third, adding an error correction term to the principal-component-based mixed-frequency model has a significant coefficient and a higher predictive accuracy. Based on the above, it can be concluded that combining the MIDAS model with error correction and a principal component is effective; thus, this combination may be applied to support real-time and accurate macroeconomic prediction.

Tumiso D. Mokhomole*

This article examines the mandate of Forensic Investigations Unit in the fight against fraud, corruption, financial misconduct, irregularities, and maladministration in the public sector of South Africa. Fraud, corruption, financial misconduct, irregularities and maladministration in public service have dire consequences to the lives of ordinary South Africans as these offences derail government efforts of improving the delivery of services such as construction of roads, access to clean water, electricity and housing. Thus, section 85(b) of the Public Finance Management Act, 1 of 1999 (PFMA) requires the Minister of Finance to craft regulations stipulating matter relating to the investigations of allegations of financial misconduct. The study employed a qualitative research approach including thoroughly revised several legislations such as Acts, regulations, policies and frameworks. Eight (8) participants from Forensic Investigations Units ranging from state departments/ institutions were interviewed using open-ended interview questions. The study followed purposive sampling as participant were selected purposively. The study found that it is the responsibility of Minister of Finance to craft regulations stipulating matter relating to the investigations of allegations of financial misconduct in the public sector. The study recommends the amended of Public Service Act of 1994 (PSA) interchangeable with Part three of Public Service Regulations of 2016 (PSR), PFMA and Treasury Regulations of 2001 to provide a Forensic Investigations Unit with clear mandate as these Acts and regulations remain silent on investigations performed by internal Forensic Investigations Units of the government departments/ institutions including State-Owned Entities (SOEs).

Ting Han, Lorenzo C. Lorenzo

In many countries, including China, traditional one-dimensional performance appraisal has led local governments to spend more on economic construction and less on human capital and public services. In 2013, China decided to abandon the traditional bias of performance appraisal. This study aims to analyze the effect of multidimensional performance appraisal on the local government expenditure structure in China. The study collected panel data from 31 provincial administrative regions in China during 2007–2018 for empirical analysis. By assigning different weights to economic-based performance appraisal pressure, livelihood-based performance appraisal pressure, and ecological-based performance appraisal pressure, the study observed the effects of performance appraisal criteria on local government expenditure structure. The results show that: local governments place more emphasis on tasks with higher relative incentive intensity and allocate more expenditures to them; the correlation between tasks affects the proportion of expenditures on related tasks; the basic principle of local government officials in balancing the expenditure structure is to maximize their own utility. They give priority to spending on tasks with high marginal revenue. In addition, this paper also discusses the causes and mechanisms of distortion in local government spending structure. Finally, the paper puts forward corresponding policy recommendations, which provide new ideas for multidimensional performance assessment of local governments.

Doratossadat Dastgheib, Hadi Farahani

In this paper, we propose a doxastic extension $BL^+$ of Lukasiewicz logic which is sound and complete relative to the introduced corresponding semantics. Also, we equip our doxastic Lukasiewicz logic $BL^+$ with public announcement and propose the logic $DL$. As an application, we model a fuzzy version of muddy children puzzle with public announcement using $DL$. Finally, we define a translation between $DL$ and $BL^+$, and prove the soundness and completeness theorems for D L

Daiki Miyagawa, Koki Miyabara, Genki Ichinose

Cooperation in human society is sustained by reputation. In general, the reputation of an individual is determined by others who observe his behavior, but this rarely happens in private situations. This may cause people to behave inconsistently, cooperating in public and not cooperating in private. A previous experiment showed that people gave a lower reputation to an individual who cooperated in public but defected in private rather than a consistently uncooperative individual regardless of public and private situations. However, the reason behind this is unclear. Here, we study how cooperation and the reputational mechanism co-evolve on the condition that two types of interaction (public and private) exist. The simulation results show that the evolved social norm is characterized by at least one of the following: preference for consistent or aversion of inconsistent behavior in both interactions when the risk that behaviors in private interactions are observed exceeds a certain threshold. We also find that such social norms promote cooperation in private situations as well as in public ones.

Anik Pramanik, Pan Xu, Yifan Xu

There are many news articles reporting the obstacles confronting poverty-stricken households in access to public transits. These barriers create a great deal of inconveniences for these impoverished families and more importantly, they contribute a lot of social inequalities. A typical approach addressing the issue is to build more transport infrastructure to offer more opportunities to access the public transits especially for those deprived communities. Examples include adding more bus lines connecting needy residents to railways systems and extending existing bus lines to areas with low socioeconomic status. Recently, a new strategy is proposed, which is to harness the ubiquitous ride-hailing services to connect disadvantaged households with the nearest public transportations. Compared with the former infrastructure-based solution, the ride-hailing-based strategy enjoys a few exclusive benefits such as higher effectiveness and more flexibility. In this paper, we propose an optimization model to study how to integrate the two approaches together for equity-promotion purposes. Specifically, we aim to design a strategy of allocating a given limited budget to different candidate programs such that the overall social equity is maximized, which is defined as the minimum covering ratio among all pre-specified protected groups of households (based on race, income, etc.). We have designed a linear-programming (LP) based rounding algorithm, which proves to achieve an optimal approximation ratio of 1-1/e. Additionally, we test our algorithm against a few baselines on real data assembled by outsourcing multiple public datasets collected in the city of Chicago. Experimental results confirm our theoretical predictions and demonstrate the effectiveness of our LP-based strategy in promoting social equity, especially when the budget is insufficient.

Christian Bucio Pacheco, Luis Villanueva, Raúl de Jesús Gutiérrez

The objective of this work is to estimate the patterns of dependence between the yields of the stock prices of the main banks of the United States (US) and Mexico. We estimate the patterns of absolute dependence and tail dependence through copulas of the Archimedean family and the use of rolling windows of 245 days. The data employed come from the daily share prices at closing from January 2, 2015, to December 31, 2020, for seven banks. Our results show that: i) there are patterns of high dependence among the main banks in the US, ii) there are patterns of very low dependence among the main banks in the US and Mexico, and iii) there are patterns of low dependence among the main banks in Mexico. These results have several implications, among them that the high-dependency patterns obtained among major US banks limit the joint selection of these US bank equity assets in an investment portfolio. Although this paper focuses on a small sample of banks, they represent an important portion of the banking sector in both countries. Given the limited literature on this subject in Mexico, our paper contributes to expanding this literature with a novel approach.

Forum Dave

This paper theoretically underpins the idea of greater involvement of local governments in the overall development of India explained through the theory of Fiscal Federalism. The theory outlines the dynamics of decentralization of power and functions through a multi-layered governance system leading to a new structure and added functions, finance, and accountability to local government. The paper also provides an overview of the increasing role of urban local governments in India and investigates whether the Urban Local Bodies (ULBs) of Gujarat – a state in India, are efficient to perform the functions and responsibilities assigned to them by the 74th Constitutional Amendment Act (CAA). It scrutinizes the financial health of local governments in the urban regions of India. The results based on the application of MANOVA indicate that the 74th CAA empowered ULBs with a strong economic base that these ULBs are capable of mobilizing their own resources. This means that smaller municipalities must develop and convergence must be supported by a proportionate level of grants. This will ensure that with the development of social infrastructure, economic activities will increase, and, as a result, the conversion will occur.

Javad Doliskani

Our main result is a quantum public-key encryption scheme based on the Extrapolated Dihedral Coset problem (EDCP) which is equivalent, under quantum polynomial-time reductions, to the Learning With Errors (LWE) problem. For limited number of public keys (roughly linear in the security parameter), the proposed scheme is information-theoretically secure. For polynomial number of public keys, breaking the scheme is as hard as solving the LWE problem. The public keys in our scheme are quantum states of size $\tilde{O}(n)$ qubits. The key generation and decryption algorithms require $\tilde{O}(n)$ qubit operations while the encryption algorithm takes $O(1)$ qubit operations.

Bran Knowles, John T. Richards

Trusted AI literature to date has focused on the trust needs of users who knowingly interact with discrete AIs. Conspicuously absent from the literature is a rigorous treatment of public trust in AI. We argue that public distrust of AI originates from the under-development of a regulatory ecosystem that would guarantee the trustworthiness of the AIs that pervade society. Drawing from structuration theory and literature on institutional trust, we offer a model of public trust in AI that differs starkly from models driving Trusted AI efforts. This model provides a theoretical scaffolding for Trusted AI research which underscores the need to develop nothing less than a comprehensive and visibly functioning regulatory ecosystem. We elaborate the pivotal role of externally auditable AI documentation within this model and the work to be done to ensure it is effective, and outline a number of actions that would promote public trust in AI. We discuss how existing efforts to develop AI documentation within organizations -- both to inform potential adopters of AI components and support the deliberations of risk and ethics review boards -- is necessary but insufficient assurance of the trustworthiness of AI. We argue that being accountable to the public in ways that earn their trust, through elaborating rules for AI and developing resources for enforcing these rules, is what will ultimately make AI trustworthy enough to be woven into the fabric of our society.