Government Financial Policy Research Articles

The impact of financial resource allocation on industrial structure change

Financial resources play a vital role in resource allocation and industrial structure change. This paper aims to explore the impact of financial resource allocation on industrial structure change and put forward relevant theoretical and policy recommendations. This paper first reviews previous research results and explains the importance of financial resources in shaping industrial structure. Then, based on the theoretical framework, the impact mechanism of financial resources on the development and competitiveness of different industrial sectors is analyzed. The study found that the rational allocation of financial resources helps to promote the optimization and upgrading of industrial structure and improve overall economic benefits. The government's financial policies have also been proven to have an important impact on industrial structure change, and a healthy financial market can promote the sustainable development of industrial structure. Through case study analysis, the actual impact of financial resource allocation in different industries and regions is deeply explored to provide empirical support for the theoretical model. In summary, this study emphasizes the key role of financial resources in shaping the modern industrial structure and provides important inspiration for future research and policy making.

Impact of Non-Performing Assets on Financial Health of Banks

The banking sector is a crucial financial service industry that supports development plans by channelling funds for productive purposes, facilitating the flow of funds from surplus to deficit units, and aiding in the implementation of government financial and economic policies. Banks fulfil social objectives through priority sector lending, extensive branch networks, and employment generation. Maintaining asset quality and profitability is essential for the survival and growth of banks. However, a significant challenge faced by the banking sector is the prevalence of Non-Performing Assets (NPAs). The Reserve Bank of India defines an NPA as “an asset, including a leased asset, that ceases to generate income for the bank.” Major causes of NPAs include wilful default, misuse of borrowed funds, and inadequate pre-loan inquiries. As of June 30, 2018, the Gross NPA of Indian banks was ₹10.03 lakh crores, with Public Sector Banks accounting for 88.74% of this total. The top five Public Sector Banks—SBI, PNB, IDBI, BOI, and BOB—make up 46.67% of the Gross NPAs. Private Sector Banks hold 11.26% of the total Gross NPAs, with leading banks being ICICI, AXIS, and HDFC. The primary aim of this paper is to examine the causes and effects of NPAs in the banking sector.

The Impact of the Iraqi Government's Financial Policy on Reduction of Unemployment Rates During the COVID-19 Pandemic

This research paper aimed at analyzing the role of the financial policy taken up by the Iraqi government in confronting the outbreak of the COVID-19 pandemic and mitigating the repercussions of the pandemic on unemployment. It relied on quantitative and qualitative methods to analyze and evaluate the effects of financial policy on unemployment rates. Several international indicators were used, such as the Oxford University Government Response Tracker (OXCGRT) to know the strength of the stimulus package adopted by Iraq. The Principal Component Analysis (P) methodology was also used to analyze the composition of the stimulus financial policy taken. The results of the analysis generally came up with the fact that the the role of financial policy adopted by Iraq in promoting economic growth and accelerating recovery from the repercussions of the pandemic was significant on unemployment rates, depending on the size of that fiscal policy in Iraq.

Economic impact of a credit guarantee scheme: evidence from Spain

ABSTRACT Credit guarantee schemes have emerged as one of the preferred choices for policy makers concerned about financing small and medium-sized enterprises (SMEs). This article assesses the economic impact of a credit guarantee scheme by using data from a Spanish regional guarantee company for the years 2019 and 2020. We employ an input–output (IO) model, which is a robust methodology that has not been previously used in this type of study. Our findings confirm that a credit guarantee scheme has a positive impact on economic growth, as evidenced by increases in output, gross domestic product (GDP), and employment. We also evaluate the support measures implemented by the regional government to reduce the liquidity shortfalls experienced by SMEs during the COVID-19 pandemic, corroborating that during crises, government financial support policies to guarantee systems yield positive macroeconomic effects in the region in which they are implemented.

Two-Stage Data Envelopment Analysis Models with Negative System Outputs for the Efficiency Evaluation of Government Financial Policies

The main purpose of this study is to provide a comparative analysis of several possible approaches to applying data envelopment analysis (DEA) in the case where some decision making units (DMUs) in the original sample have negative system outputs. In comparison to the traditional model of Charnes, Cooper, and Rhodes (CCR) and the CCR model with a scale shift to measure second-stage outputs, the range directional measure (RDM) model produces the most appropriate results. In this paper, an approach is proposed for estimating returns to scale. The study applies a two-stage DEA model with negative second-stage outputs to assess the public support for research, development, and demonstration projects in the energy sector in 23 countries over the period from 2010 to 2018. The assessment of government performance depends on its contribution to the growth of energy efficiency in the national economy and the reduction of its carbon intensity. Intermediate outputs (patents in the energy sector) are included in the analysis as both outputs of the first stage and inputs of the second stage. Taking the similarity between the calculations obtained without stage separation and the system efficiency calculations from the two-stage model as a measure of model adequacy, the RDM model shows the highest similarity scores.

Eliminating the effects of external environmental factors to improve the analysis of local government financial condition: a study in Indonesia

ABSTRACT This article proposes an approach to the assessment of the financial condition of local governments by eliminating uncontrollable external environmental factors using cluster analysis. The author found seven clusters of provincial government, 13 clusters of regency government, and seven clusters of city government in Indonesia. The article provides evidence that clustering local government increases the effectiveness of analysis of financial conditions. The academic contribution of this article is generating cluster variables that are more comprehensive and relevant than those presented in previous studies. In addition, findings of this study can be used by authorities to develop local government financial management policies that are fairer.

Opportunities and Scope of Electric Vehicle in India

The vehicle industry has advanced due to the introduction of new technology. Alternatives to internal combustion engines include electric automobiles. Demand for electric vehicles is rising globally due to their lower CO2 emissions. The Indian government also intends to boost the production of electric vehicles in the automotive sector. This essay discusses the commercial prospects and difficulties for electric automobiles in India. This study discusses the economic, social, technological, and environmental variables influencing the electric car industry in India. The development of the infrastructure and batteries is influenced by the aforementioned economic and technological considerations. Over the past ten years, the global market for electric vehicles has grown at an unparalleled rate. In this essay, we first go over the potential and reach of electric vehicles in India. We also talk about the many frameworks and policies that the Indian government has put in place. Then, we research different adoption case studies for electric vehicles from throughout the globe. Finally, we discuss how India could put these tactics into practise and profit from them both locally and nationally. The India Electric Vehicle Market has a market size of USD 5 billion in 2020 and is projected to grow at an astounding CAGR of over 44% to reach USD 47 billion by 2026. (2021 – 2026). The market for electric cars (EVs) is expanding quickly on a global scale. The EV market has now experienced tremendous growth in India as well. As the Ministry of Heavy Industries and Public Enterprises implemented the FAME (Faster Adoption and Manufacturing of Hybrid and Electric Vehicles) initiative in 2015, the market is expanding further. Sales of all electric vehicles reached 365,920 units in 2018 and are projected to increase by 36% CAGR through 2026. In India, the market for EV batteries is anticipated to reach US$ 520 million in 2018 and increase at a CAGR of 30% through 2026.Electric cars provide ways to be self-sufficient and independent of foreign energy sources. One of the biggest producers of crude oil in the world is India. India might undergo a significant transformation towards self-sustainability thanks to electric automobiles. Alternatives to reduce carbon dioxide gas include electric vehicles (EV). Air pollution is a serious issue in large cities like Delhi and Mumbai. One of the sources of air pollution is the carbon dioxide produced by cars. Electric cars operate smoothly, emit little pollutants, and are highly efficient. According to research on the energy use and greenhouse gas emissions of plug-in hybrid electric vehicles in China, they consume 37.5% less energy and emit 35% fewer greenhouse gases than gasoline vehicles . Government financial policies to promote EV adoption have already been established, but for them to be effectively implemented, decision-makers must have a long-term perspective. India's history of EV has been disappointing so far. Lack of loading infrastructure, inconsistent government support and early product failures have all led to the stagnant growth in recent years.

Will Alibaba’s additional financial service contribute to sellers’ satisfaction and loyalty during the pandemic? Evidence from Taobao sellers

ABSTRACT Electronic commerce (e-commerce) has shown dramatic growth in recent decades, and sellers on e-commerce platforms have also been affected by the global COVID-19 pandemic. By collecting data from 313 Taobao sellers, we investigated the relationships among e-commerce platform additional financial service quality, sellers’ satisfaction, and loyalty to the platform, as well as the moderating roles of sellers’ financial pressure during the pandemic and perceived COVID-19 government financial support in the satisfaction-loyalty relationship. Our results show that better financial service quality enhances sellers’ satisfaction with the platform, which in turn translates into platform loyalty. We also evidence the moderating effects of COVID-related financial pressure and sellers’ perception of COVID-related government financial relief policy on the satisfaction-loyalty relationship. Our research makes potential contributions to the e-commerce field and provides timely guidance for e-commerce practice in the pandemic period.

Spatial and sentiment analysis of public opinion toward COVID-19 pandemic using twitter data: At the early stage of vaccination

During the crisis of Coronavirus pandemic, social media, like Twitter, have been the platforms on which people have been able to share their opinions and obtain information. The present study provides a detailed spatial-temporal analysis of the Twitter online discourse (approximately 280 thousand tweets) in Ohio and Michigan at the early stage of vaccination rollout (January 2021, till March 2021). This work aims to explore how people were feeling about the pandemic, the most frequent topics people were talking about, and how the topics spatially were distributed. Moreover, state government responses and important news were gathered to analyze their impacts on public opinion based on the temporal analysis of the tweets. In this project, Natural Language Processing using the LDA method was employed to identify 11 topics and 8 sub-topics in the Twitter data. The temporal analysis of topics shows the sensitivity of the online discourse to the significant state news and the local government's reactions to the pandemic. Moreover, the spatial distribution of Coronavirus-related tweets and sentiments demonstrates concentrations in the more populated urban areas with a high rate of COVID-19 cases in Ohio and Michigan. The government's economic and financial policies taken during this time, the vaccination timeline phases specified by each state, and the pandemic-related information can contribute to public opinion and sentiment trends. The findings of this study can help explore public demands, and reactions, follow the impacts of the local authorities' policies at the county level and manage their future responses to such a pandemic.

TVAR-MODELS OF FINANCIAL SECURITY INDICATORS FOR MACROECONOMIC SYSTEMS: IMPACT ASSESSMENT OF ENERGY “SHOCK”

The break of connections in economic systems results in imbalance and a theoretical possibility of a threat for their development. This raises the issue of finding an effective mechanism for economic security in general and financial security in particular, which are important elements of how macroeconomic components work. The purpose of the study is to develop models that allow assessing the impact of an energy “shock” on financial security indicators, to identify the threshold values of exogenous variables at which the “shock” has a destructive influence on the level of financial security and can lead to the financial system destabilization. The work uses a branched structure of scientific methods which consist of theoretical and empirical research of the financial security for macroeconomic systems. The main results of this work are devoted to the consideration of the problem of how to design effective mechanisms for ensuring financial security under the conditions of exogenous “shocks” of the global economy. It considers the concept of “shock” and gives the examples of the impact of “shocks” on macroeconomic indicators. The work highlights the energy “shock” as dominant for the analysis and formation of an effective macroeconomic stability policy. The information area of research features is substantiated, including BRENT oil price data and indicators of monetary and currency security, such as the rate of inflation and the exchange rate. Emphasis on subsystems of monetary credit and currency security is made due to the importance of these channels of crisis infection in order to ensure financial security. The value of the lag in the model is substantiated with the help of information criteria; evaluation and testing of the quality of the model have been carried out; system stability has been assessed based on the impulse response function, the TVAR model has been developed. The areas of change of the exogenous variable reflecting the statistically significant impact of the energy “shock” on the rate of inflation are analyzed. Thus, the obtained results made it possible to identify the regimes of energy security, which become a channel of infection of the financial sphere and a significant increase in the level of inflation. Practical significance includes the versatility and applicability of the evaluation approach for research due to the ability to use the entire algorithm as a complete ensemble of models. The results of this material can be used in the formation of government financial security policies and reactions to destabilizing external influences.

Government Financial Policy, its Connection with Monetary Policy

Government Financial Policy, its Connection with Monetary Policy

Crypto Currency Price Prediction with Machine Learning Using Python

We use and study a wide range of machine learning methods to predict and trade in the daily crypto currency market. We teach the algorithms to make daily market predictions based on how the 100 cryptocurrencies with the most market value change in price. Based on our research, all of the used models are able to make estimates that are statistically sound, with the average accuracy of all crypto currencies falling between 52.9% and 54.1%. When these accurate numbers are based on the 10% most confident expectations for each class and day, they go up to somewhere between 57.5% and 59.5%. A well-known case study in the field of data science looks at how people try to figure out how much different digital currencies are worth. Stock prices and the prices of cryptocurrencies are based on more than just the amount of buy and sell orders. At the moment, the government's financial policies about digital currencies affect how the prices of these things change. People's views about a crypto currency or a star who directly or indirectly backs a crypto currency can also cause a big rise in buying and selling of that currency. This study looks at the trustworthiness of the three most famous coins on the market today: bitcoin, how well buying strategies for ethereum and litecoin that are based on machine learning work. The models are checked and tested with both good and bad market situations. This lets us figure out how accurate the forecasts are in light of any changes in how the market feels between the proof and test times.

Pedagogic device of innovation and entrepreneurship education in Polytechnics of Zhejiang Province

The study was aimed at describing the phenomenon and issues of IEE in polytechnics of Zhejiang province, drawing on Basil Bernstein's pedagogic device theory, and analyzing the pedagogic device of IEE from four aspects in Zhejiang. The empirical evidence was mainly gathered from the official IEE curriculum documents, government, and existing studies in the field. The purposive sampling was utilized and an SMS was sent to 14 teachers, 25 students, and 9 graduates selected for their geographical location and the ranking of polytechnics in Zhejiang province. A semi-structured interview examined how IEE cultivated their competencies. The results find out that in instructor training, Zhejiang Department of Education invests lots of resources to train many entrepreneurial mentors. In student training, polytechnics students must complete two credits of IEE courses and can apply for Start Your Business (SYB) curriculum free of charge. After seven years of development, the popularity of innovation and entrepreneurship competition has increased, and polytechnics' participation has doubled. After a decade of exploration and development, mass innovation space has evolved from the early 1.0 hardware version, which only provided sites and equipment, to the 2.0 and 3.0 software versions with capital docking and government financial policies support.

A systematic literature review of Chinese music education studies during 2007 to 2019

Based on findings from a large meta-data-based literature survey, this article is intended to provide a comprehensive synthesis of key features of China’s music education system as seen through the lens of n = 116 major research studies, drawn from a total of N = 3,257 high-impact Chinese journal articles published during 2007 to 2019. The synthesis suggests that (1) education reform, aesthetic education, Chinese traditional music and cultural identity were found to be the most prominent topics across all levels of formal music education; and (2) in most studies, government financial support, policy priorities, curriculum enforcement and paedagogical innovation are proposed as general cures to address perceptions of an unsatisfactory situation within music education. However, (3) by relating these findings to national statistics, a clear gap is identified between several research studies and actual social contexts, suggesting a possible deviation of academic communities from realistic educational and social challenges. Thus, external validity issues related to these studies are also discussed critically, along with their potential influence on views of what counts as Chinese music education in domestic and international research communities.

A system dynamics model of green innovation and policy simulation with an application in Chinese manufacturing industry

Green innovation is fundamental for the achievement of a "win-win" state between economic growth and environmental protection. Pivotal to maintaining the vitality of green innovation is the effectiveness of government policies. First, this paper develops a theoretical model to capture the structure of a green innovation system, incorporating five subsystems: government, environment, technology, economy, and energy subsystems. It further explores the transmission effects of the five subsystems of green innovation systems between government policy-related actions and green innovation. Second, a causal loop diagram of green innovation is constructed to analyse how government fiscal, tax, financial, technical, and environmental policies influence green innovation through these subsystems and other relevant variables. Third, taking the Chinese manufacturing industry as an example, this work builds a stock and flow model that can more clearly reflect the relationships among all variables in a green innovation system. Then, it calculates the quantitative relationship between different variables in the model. Model effectiveness is verified by historical data and sensitivity analysis. Finally, based on the above work, this study simulates the evolution of the green innovation system in the Chinese manufacturing industry by changing the variables of fiscal, tax, financial, technical, and environmental policies. The results show that different types of policies and differentiated implementation strengths have varied impacts on the green innovation performance of the manufacturing industry. There is a synergistic relationship between different types of policies, implying a higher-level effectiveness of policy orchestration compared to the use of separate policies. This paper generates valuable implications for the government for formulating and optimizing green innovation policies.

How frugal innovation shape global sustainable supply chains during the pandemic crisis: lessons from the COVID-19

PurposeThe COVID-19 crisis has created enormous strain in global supply chains. The disruption has caused severe shortages of critical items, including personal protective equipment (e.g. face masks), ventilators and diagnostics. The failure of the industry to meet the sudden demand for these necessary items has caused a severe humanitarian crisis. These situations, resulting from the COVID-19, crisis have led to the informal growth of frugal innovation in sustainable global supply chains. This paper aims to provide a detailed overview of drivers of frugal-oriented sustainable global supply chains, following lessons acquired from emerging countries’ attempts to deal with the COVID-19 pandemic.Design/methodology/approachThe authors used a focused group approach to identify the drivers and this paper further validated them using existing literature published in international peer-reviewed journals and reports. The authors adopted total interpretive structural modeling (TISM) to analyze the complex relationships among identified drivers.FindingsThe authors present a theoretical framework to explain how the drivers are interlinked. This paper has developed the framework through a synthesis of the TISM modeling and Matrice d’impacts croisés multiplication appliquée á un classment analysis. This paper observed that government financial support, policies and regulations, under the mediating effect of leadership and the moderating effect of national culture and international rules and regulations, has a significant effect on the adoption of emerging technology, volunteering initiatives and values and ethics. Further, emerging technology, volunteering initiative and values and ethics have a significant effect on supply chain talent and frugal engineering. These results provide some useful theoretical insights that may help in further investigating the role of frugal innovations in other contexts.Originality/valueThe authors find that outcomes of the methodical contributions and the resulting managerial insights can be categorized into four levels. Industry and researchers alike can use the study to develop the decision-support systems guiding frugal-oriented sustainable global supply chains amid the COVID-19 pandemic and in recovering them thereafter. Suggestions for future research directions are offered and discussed.

Synergy and Communication of IoT Industry Development Strategies in the Perspective of Low Carbon Economy

In this paper, from the perspective of a low-carbon economy, the development mode and influencing factors of the IoT industry are studied, and development strategies are proposed in a targeted manner. Through the analysis of relevant literature, the connotation of the concept of cooperation and dissemination of IoT industry development strategy under low-carbon economy is enriched, emphasizing its systemic, multisubjectivity, and low-carbon effect, and its mechanistic effect is analyzed and different types of models are analyzed and established. The analysis of the model of IoT industry development strategy cooperation and dissemination in low-carbon economy finds that there is industrial variability in the overall trend of continuous increase of IoT industry development strategy cooperation and dissemination in the low-carbon economy, and the reasonable industrial categories and their characteristics are pointed out through cluster analysis. Based on the viewpoint of the IoT industry and regional differentiation, the analysis establishes the path analysis model of enterprise, industry, and region. From the perspective of enterprises using game analysis method research shows that the development process of IoT industry under low-carbon economy first adopts the important benchmarking significance of enterprise technology innovation behavior and its effect on potential enterprises and then pays attention to the government financial and tax policies and market cultivation on the coincidence between different types of IoT enterprises. The research shows that there are fault paths, distorted paths, and pathway types in the development of the IoT industry under a low-carbon economy. Finally, based on the policy analysis, we summarize our shortcomings and the above-mentioned development path views and make suggestions for better policy formulation of IoT industry development in a low-carbon economy from enterprise-level, industry level, and regional level. The above perspectives, conclusions, and policy recommendations on the synergy and dissemination of development strategies will have important positive theoretical and practical guidance for promoting the development of the low-carbon economy and IoT industry.

Fiscal and monetary instruments of impact on economic development

The research subject includes the theoretical basis and mechanism of fiscal and monetary policy coordination. The study aims to justify the conceptual basis of fiscal- monetary policy interactions to ensure economic development. Methods. To achieve the appropriate tasks, we used a set of methods and approaches that helped ensure our investigation's conceptual unity. The systemic and structural approaches, analysis and synthesis methods, comparison, generalization, modeling, and scientific abstraction are applied. Results. In this paper, we improved the theoretical and methodological foundations of fiscal and monetary policy coordination. The author highlighted the necessity to use the institutional approach in that case. Also, we gave practical proposals to develop the system for assessing the effectiveness of the coordination of fiscal and monetary policy. Practical implications. Government economic policy and instruments of its implementation. Conclusions. Empirical experience has shown the advisability of fiscal and monetary policy coordination to ensure sustainable endogenous economic growth. Coordination of government financial policy measures in the context of the economic cycle stages should be based on an institutional approach. The interaction of fiscal and monetary policies should focus on increasing social welfare and the maintenance of long-term macroeconomic stability. The adaptive interaction of monetary and fiscal mechanisms and the improvement of the state's economic system's institutional architectonics contribute to the intensification of business entities' economic activity. Meanwhile, those factors positively influence on economy's competitiveness. The necessity of introducing a system for assessing the effectiveness of the coordination of fiscal and monetary policy determines effective measures of financial regulation at a certain stage of economic development.

TARGET GROUPS FOR INCREASING FINANCIAL POTENTIAL OF THE PPP SECTORS IN ORDER TO THE GOVERNMENT’S FINANCIAL POLICY

The relationship between the financial potential of PPP sectors and financial policy has been identified, which testifies to the dependence of the overall development of public-private partnership on strategic decisions at the state level. An analysis of causal relationships with the use of the canonical correlation method has been carried out to determine the relationship between the financial potential of PPP sectors and the power of interaction with public finance policy. This allows not only to assess the prospects of the development of events in the event of a change in one of the indicators in a specific public-private partnership sector, but also in the presence of relevant mathematical and statistical models to obtain an estimate of the magnitude of secondary changes. In turn, government financial policy measures should be tailored to the current state of financial potential of public-private partnership.
 It is revealed that the financial potential of PPP sectors has a high degree of interaction with financial policy, which is confirmed by the adequacy of the system of canonical correlation equations. Ranking the indicators of the financial potential of the PPP and determining their factor load allowed formulating targets. Target indicators of public-private partnership financial potential are selected based on the sectors that are the basis for adjusting the state's financial policy in order to increase the financial potential of the public-private partnership: in the public sector - indicators of budget expenditures and the degree of subsidized equalization of regions by the state; by the private sector - indicators of the volume of return of financial resources spent on fixed assets and profitability of business entities; in the financial and credit sector, is an indicator of lending to non-financial corporations.

The Early Impact of Government Financial Intervention Policies and Cultural Secrecy on Stock Market Returns During the COVID-19 Pandemic: Evidence From Developing Countries

This paper examines the role of government financial intervention policies and cultural secrecy on equity market returns during the start of the COVID-19 pandemic in developing countries’ stock markets. We employ global data including 939 observations across 32 developing countries (23 emerging and 9 frontier stock markets) from December 1 to April 28, 2020. Our results show that the above-mentioned policies that set out to curb the COVID-19 pandemic succeed in increasing equity returns. It reflects investors’ improved perceptions of governments’ commitment to stabilizing the economy during the pandemic in developing, emerging, and frontier equity markets. Results show that investors in all equity markets discount differences in cultural secrecy in processing market information when investing in stock markets. We find that equity market investors in developing and emerging countries truly react negatively to the rise in the number of confirmed COVID-19 cases reported. Yet, we find that COVID-19 wields no influence on equity market returns in frontier equity markets. This presents frontier equity markets as a safe-haven investment destination during a global health outbreak. Our work helps investors during such events to identify the best and worst investment destinations in developing, emerging, and frontier stock markets. At the same time, it is important to understand the critical roles of: firstly, the introduced government financial intervention policies; and secondly, the daily growth in reported COVID-19 cases on stock market returns.