Government Policy Interventions Research Articles

Does government procurement affect corporate carbon emissions? Evidence from China

ABSTRACT Supply-driven government intervention policies aid firm sustainability, but do demand-driven government intervention policies impact corporate carbon emissions? This study examines the impact of demand-driven government intervention, specifically government procurement, on corporate carbon emissions using the data of listed firms from 2015 to 2021. The results uncover that government procurement decreases carbon emissions by stimulating demand-driven effects and enhancing green innovation. The enhanced effect is evident with sustainable procurement practices and a favorable institutional environment, particularly in Eastern and Central China. This study contributes to comprehending demand-side environmental governance policies and informs strategies for optimizing carbon emission control policies.

Effectiveness of government policy interventions towards enhancing access to pre-primary and primary education by street children in North Rift Kenya

An estimated 150 million children live on the streets globally, with many not enrolled in school. This growing issue requires urgent attention. UN Sustainable Development Goal 4, Target 5, aims to eliminate educational disparities for marginalized groups like street children, emphasizing the need to address prejudice in education access.The Kenyan government has developed measures to improve all children's access to education, particularly at the pre-primary and primary levels, in light of its signature on the United Nations convention. Government funding for the creation and execution of policy initiatives targeted at improving the access to education for these socially marginalised populations has been consistently large. Many street children still do not go to school though. In this regard a study was conducted to assess the effectiveness of government policy interventions towards enhancing access to pre-primary and primary education by street children. The study used mixed method research and pragmatic paradigm. By using both purposeful and random sampling, a sample size of 322 was selected. The respondents comprised of Street children, county directors of education, quality assurance officers, officers in the Department of Children Welfare, urban primary school teachers, non-governmental organisations, and community-based organisations that assist street children. Data was collected using observation guides, in-depth interviews, and questionnaires. Descriptive and inferential statistics as well as theme analysis were used to analyse the data, respectively. The results showed a statistically significant relationship between government policy interventions and street children's access to pre-primary and primary education in North Rift Kenya; specifically, the national pre-primary education policy had a Pearson correlation coefficient of 0.711, while the inclusive education policy had a coefficient of 1.0. The research additionally demonstrated the necessity of reinforcing the involvement of other relevant parties in improving street children's access to pre-primary and primary education.

Parental concerns about the risks associated with harmful industries for their children

Abstract Background Harmful industries including tobacco, vaping, alcohol, and gambling are causing significant harms to communities, including children and young people. These industries try to resist reform by deflecting blame and shifting responsibility, often by suggesting that parents need to educate and protect their children. This study aimed to explore parents’ current concerns and risks relating to these industries and their children, and their attitudes about responses to prevent harm. Methods Australian parents (n = 455) who had at least one child aged between 11-17 years were invited through a panel company to complete an online qualitative survey. Participants were asked about their concerns and risks relating to each product, if and what they discuss about these products with their children, and who was responsible for protecting children from these industries. Thematic analysis was used to analyse the data. Results Parents were concerned about the short- and long-term consequences of their children engaging in these products. Many parents tried to talk to their children about the risks, however also believed that their child was influenced by their peers, and messages they see on social media. Although parents recognised their own role in protecting their children from harmful industries, they thought that a collective approach was needed, which included greater regulations and more effective education. Conclusions Parents are trying their best to protect their children from the harms associated with tobacco, vaping, alcohol, and gambling. However, they feel as though they are unable to counter the range of ways that their children are exposed to and influenced by these industries. Governments need to listen to parents and implement comprehensive regulations restricting marketing practices and increase evidence-based education that focuses on the tactics and harmful practices of these industries. Key messages • Harmful industries try to shift blame and put responsibility for protecting children onto parents. However, parents feel they are unable to counter the positive messages that their children see. • Parents are concerned about the range of risks these products could have for their children and want to see a collective response to address this issue, including government policy intervention.

Dinamika Harga Beras di Kota Kendari: Analisis Fluktuasi 2015-2023

Food price stability is one of the essential issues in the direction of government policy. Price uncertainty at the farm level and the guarantee of food price stability at the consumer level are unresolved problems. This study aims to analyze rice price fluctuations in Kendari City from 2015 to 2024. The research was conducted in Kendari City in March - May 2024. The research used secondary data, namely time series data on rice prices in Kendari City from 2015 to 2023. The research data collection technique is a literature study, namely collecting time series data on rice prices in Kendari City sourced from the Central Bureau of Statistics and related agencies. The research variable is the price of rice in Kendari City from 2015 to 2023. Data analysis used to analyze rice price fluctuations in Kendari City is the Coefficient of Variation (CV). The results showed that rice price fluctuations in Kendari City from 2015 to 2023 were low, with a coefficient of variation (CV) of 3%. The highest rice price condition in Kendari City occurred in 2023, which amounted to IDR 13,321 per kilogram. At the same time, the lowest rice price condition occurred in 2015, which amounted to IDR 9,738 per kilogram. Therefore, government policy intervention is needed to stabilize food prices, especially rice in Kendari City.

The transformative potential of blockchain technology in developing green supply chain: An evolutionary perspective on complex networks

Distrust is the main obstacle to the green transformation of the supply chain. Blockchain can rebuild trust among multiple participants by employing distributed information technologies. Based on complex network evolutionary game models, this paper tries to reveal the transformative potential of blockchain in promoting the green transformation of the supply chain. Simulation experiments with real electric vehicle data show that if adopting blockchain technology: i) the greenness of the supply chain can increase by 200% even without government policy intervention; by 75% when jointly optimizing the intensity of rewards and penalties; by 40% when exclusively adjusting the reward or penalty intensity; ii) the profits of both suppliers and manufacturers can be improved when they adopt green investment strategies, creating a “win-win” scenario. Besides, optimal government rewards and penalties are provided to accomplish various high levels of greenness in a blockchain supply chain network. This study not only quantifies the significant impact of blockchain technology on enhancing the greenness of supply chains, but also reveals the decision-making mechanisms of enterprises and government under varying degrees of greenness, providing theoretical guidance for enterprises and government to manage green blockchain supply chains.

The Main Challenges Faced in the Implementation of Government Policy Interventions towards Access to Pre-primary and Primary Education by Street Children in North Rift, Kenya

Aims: Despite of the strong policy measures to have street children in school, many school-going-age are still not attending school. Therefore, the main purpose of this paper was to evaluate challenges faced in the implementation of Government policy interventions towards access to pre-primary and primary education by street children in North Rift, Kenya. Study Design: The study adopted a mixed method research design. Place and Duration of the Study: A survey was conducted in three towns of the North Rift Counties of Kenya (Kapsabet, Eldoret, and Kitale) which are the headquarters of the respective counties. Data collection done in the period between 1st December and 31st December 2022 Methodology: Purposive and simple random sampling was used to select 322 respondents (218 males and 23 females with a modal age of 10 -15 years; 18 female and 27 female teachers were aged between 30 – above 40 years). Data was collected using observation guides, in-depth interviews, and questionnaires. Descriptive and inferential statistics as well as theme analysis were used to analyze the data, respectively. The data was coded and analyzed using themes. Results: Main reasons street children had not enrolled in school were a lack of money for school materials (56.2%) and an unattractive school environment (30%). Other reasons included having to work to support their families (1.3%), distance to school (0.9%), being born and raised on the streets, being over-aged, and early parenting responsibilities. Conclusion: The study concluded that government policy interventions alone are insufficient for improving street children's access to education. Effective implementation requires collaborative efforts from all stakeholders, addressing barriers like poverty and parenting responsibilities, and restructuring education to include informal systems.

Investigating the State of Self-Harm and its Relationship with Suicidal Ideation in College Students: Evidence from a Cross-sectional Study in Southern Iran

Introduction Self-harm behaviors and suicidal ideation as two important psychological challenges can have irreparable consequences for students. Therefore, this study sought to investigate the state of self-harm and its relationship with suicidal ideation in students. Methods This cross-sectional study was conducted on 290 students of different fields at Jiroft University of Medical Sciences in the south of Iran between June and September 2023. Data were collected using two standard questionnaires of the Beck scale for suicidal Ideation (BSSI) and self-harm behaviors. Descriptive statistics methods were used for the scores of self-harm behaviors and suicidal ideation. Pearson's correlation coefficient was also used to check the correlation between these two main variables, and statistical tests such as t-test and one-way analysis of variance (ANOVA) were used to compare averages between groups. Statistical analyses were performed using SPSS version 23. Results Self-harm behaviors were at low, average, high, and very high levels in 24%, 67%, and 9% of students, respectively. Also, Suicidal ideation was in low, moderate, and high (readiness to commit suicide) levels in 5.6%, 3.4%, and 1.05% of students, respectively. Furthermore, 89.95% of students also had no suicidal thoughts. There was a statistically significant correlation between self-harm behaviors and suicidal ideation of students (p<0.001, r=0.667). Also, the mean score of self-harm behaviors, including dormitory residents (p=0.02), males (p=0.04), singles (p=0.001), undergraduates (p=0.003), and unemployed (p=0.01) was significantly higher than others. In addition, the average score of suicidal ideation was significantly higher in students living in the dormitories (p=0.03), including singles (p=0.005), undergraduates (p=0.02), and unemployed (p=0.04) than in others. Conclusion It is suggested that the officials of student, counseling, and cultural affairs of universities improve the living conditions of students in dormitories, pay attention to the needs of students, and try to solve their mental and psychological problems, as well as provide employment and marriage of students to reduce their self-harm behaviors and suicidal ideation. Additionally, government policy interventions, such as routine mental health care screening programs for students and timely interventions to solve mental health problems, are suggested.

Household migration decisions: Understanding Ethiopians irregular migration from Kembata‐Tembaro zone to the Republic of South Africa

AbstractThis research intends to shed light on the household migration decision‐making process of Ethiopian irregular migrants heading to the Republic of South Africa. Data were drawn from a cross‐sectional household survey (n = 659) and in‐depth interviews (n = 24) conducted in 2022. Descriptive statistics, binary logistic regressions and thematic analysis were employed to analyse the data. Our findings reveal that being a young male, having a large household size, the presence of family members and smugglers positively influence households' decisions for irregular migration. Possession of farmland, being employed and married have a negative influence on household decisions for migration. The study findings further show that prior information about the migration destination is important in the household's migration decision‐making process. We suggest that government actions and policy interventions should be based on such empirical evidence to promote safe and regular migrations while addressing potential migrants' aspirations and needs in their pursuit of a better life.

Smallholder palm oil and sustainable development goals (SDGs) achievement: An empirical analysis

This paper is aimed at examining and analyzing the contribution of palm oil smallholders to the achievement of the SDGs. Another objective is to determine the highest SDGs that contribute to the achievement of SDGs by examining 13 SDGs out of 17 SDGs analyzed using Principal Component Analysis (PCA) to estimate composite SDGs index. The survey was conducted in 7 provinces in Indonesia which are oil palm centers in Indonesia. Data was obtained from interviews with 3060 smallholder oil palm farmers divided into 3 strata based on the area of oil palm land owned. The results showed that the SDG composite index of smallholders reached 77.57 %, which informed that smallholder oil palm had reached 77.57 % of the 2030 SDGS target. This achievement is greater than the national achievement which reached 70.16 %. Of the 13 SDGs analyzed, SDG17 achieved the weakest followed by SDG5. While the highest achievement was obtained by SDG1 which was followed by SDG6 and SDG8. In the future, more comprehensive cross-sectoral research related to the achievement of SDGs, especially related to the impact of government policy interventions on the achievement of SDGs.

An investigation of the longitudinal trajectory patterns of health-related quality of life among Australians with disabilities: explaining disability types and properties

BackgroundResearch on health-related quality of life (HRQoL) trajectory patterns for people with disabilities (PwD) is scant. Understanding the HRQoL trajectory patterns for PwDs and investigating their relationship with disability types and socioeconomic factors can have important implications for Australia’s welfare policy.MethodsWe analysed data from waves 11 to 21 of the Household, Income and Labour Dynamics in Australia (HILDA) survey of respondents aged 15 + years of the PwDs. The analytic sample consists of 3724 self-reported disabled individuals and 34,539 observations in total. The SF-6D utility score is our HRQoL measure. Group-based trajectory modelling was utilised to identify trajectory groups, and multinomial logistic regression was employed to determine the baseline factors associated with trajectory group membership.ResultsThe study identified four distinct types of HRQoL trajectories (high, moderate improving, moderate deteriorating and low HRQoL trajectories). Psychosocial disability types followed by physical disability types had a high Relative Risk Ratio (RRR) in the low group compared with high trajectory group membership of PwDs (psychosocial: 6.090, physical: 3.524). Similar, results followed for the moderate improving group albeit with lower RRR (psychosocial: 2.868, Physical: 1.820). In the moderate deteriorating group, the disability types were not significant as this group has a similar profile to high group at the baseline. Compared with males, females had a higher RRR in low and moderate versus high improving HRQoL trajectories (low: 1.532, moderate improving: 1.237). Comparing the richest class to the poorest class, socioeconomic factors (income and education) predicted significantly lower exposure for the richer class to the low and medium HRQoL trajectories groups (RRR < 1).ConclusionDifferent forms of disability, demographic and socioeconomic factors have distinct effects on the HRQoL trajectories of disabled individuals. Healthcare and economic resource efficiency might be improved with targeted government policy interventions based on disability trajectories.

Determining geo-disaster chains probabilities and disaster mitigation mode: A meta-analytical perspective

In a harsh geological environment, different geo-disasters might co-occur or be in a chain sequence. Currently, existing research in related fields documents numerous instances of disaster chains and responses, which provided this study with important materials for determining disaster chains probability and summarized the disaster prevention and mitigation (DPM) mode. In this study, through the depth of the geo-disaster chains cases and the DPM cases, enabled a mitigation mode analysis summary. We take the case of geo-disaster chains as an example for this study, and represent 20 typical geo-disaster chains by data fusion and structuring of 139 geo-disaster chains cases.The probability assessment of geo-disaster chains is crucial for risk management and regional resilience. We introduced a Bayesian network (BN) model to describe the process of geo-disaster chains formation to map the structure and assess the joint probability of geo-disaster chains. The BN results showed that the longer the disaster chains length, the smaller the probability of the chains occurring. Among these, the probability of “Collapses-landslides-debris flows–barrier lakes–flash floods” is the lowest (0.069). Through sensitivity analysis, it is found that precipitation is the most sensitive factor in the development of geo-disaster. Interpretive structural modeling (ISM) is employed to examine the DPM index system across three key aspects: disaster emergency preparation, disaster response, and disaster recovery, and the conceptualized interaction among these components. ISM results showed that government policy intervention and scientific DPM measures can effectively reduce the losses caused by the development of geo-disaster chains. This research combined the occurrence process of the disaster chains with the disaster response process, and determined the entire chains of characterization from disaster understanding to disaster response, and helped reduce the vulnerabilities caused by disasters.

Dynamic effects of digital governance and government interventions on natural resources management: Fresh findings from Chinese provinces

This study investigates the dynamic effect of digital government on natural resource management in 30 Chinese provinces, considering the government intervention policies, GDP, foreign direct investment, trade openness, and energy prices. In this context, QLARDL, QR, and Dumitrescu Hurlin Panel Causality approach estimate the panel data collected from 2010 to 2020. Results suggested that the digital government positively impacts natural resources management at various quantile levels. On the contrary, government intervention has a limited effect, while Foreign direct investment boosts natural management, especially in the long run. At the same time, energy prices and openness trade significantly negatively impact natural resources management. Based on the empirical findings, several policy implications are suggested for the Chinese provinces.

중국의 토지 공급 정책이 부동산 시장에 미치는 영향

Purpose - This study aims to explore the relationship between housing and land prices, with a specific emphasis on the impact of government policies on these factors such as land supply quantity and the ratio of residential land to total land supplied. The goal is to identify the most effective government intervention strategies for controlling both housing and land prices. Design/methodology/approach - Data from 70 primary and medium-sized cities in China spanning from 2003 to 2017 are utilized in this research. The analysis employs a panel vector autoregressive (PVAR) model, with a primary focus on examining the relationships among housing prices, land prices, and government intervention policies. Findings - Housing and land prices are influenced by various factors. Through impulse response analysis and variance decomposition, it is observed that both housing and land prices are predominantly influenced by their internal dynamics, with comparatively weaker effects attributed to policy interventions. Research implications or Originality - By investigating the impact of government policies on housing and land prices, This study establishes a foundation for effective price control measures. Our study advocates for a comprehensive examination of China's land supply mechanism to enhance understanding of the pathways through which government policies influence the markets.

Review of Applications of Remote Sensing towards Sustainable Agriculture in the Northern Savannah Regions of Ghana

This paper assesses evidence-based applications of Remote Sensing for Sustainable and Precision Agriculture in the Northern Savanna Regions of Ghana for three decades (1990–2023). During this period, there have been several government policy intervention schemes and pragmatic support actions from development agencies towards improving agriculture in this area with differing level of success. Over the same period, there have been dramatic advances in remote sensing (RS) technologies with tailored applications to sustainable agriculture globally. However, the extent to which intervention schemes have harnessed the incipient potential of RS for achieving sustainable agriculture in the study area is unknown. To the best of our knowledge, no previous study has investigated the synergy between agriculture policy interventions and applications of RS towards optimizing results. Thus, this study used systematic literature review and desk analysis to identify previous and current projects and studies that have applied RS tools and techniques to all aspects of agriculture in the study area. Databases searched include Web of Science, Google Scholar, Scopus, AoJ, and PubMed. To consolidate the gaps identified in the literature, ground-truthing was carried out. From the 26 focused publications found on the subject, only 13 (54%) were found employing RS in various aspects of agriculture observations in the study area. Out of the 13, 5 studies focused on mapping the extents of irrigation areas; 2 mapped the size of crop and pasturelands; 1 focused on soil water and nutrient retention; 1 study focused on crop health monitoring; and another focused on weeds/pest infestations and yield estimation in the study area. On the type of data, only 1 (7%) study used MODIS, 2 (15%) used ASTER image, 1 used Sentinel-2 data, 1 used Planetscope, 1 used IKONOS, 5 used Landsat images, 1 used Unmanned Aerial Vehicles (UAVs) and another 1 used RADAR for mapping and monitoring agriculture activities in the study area. There is no evidence of the use of LiDAR data in the area. These results validate the hypothesis that failing agriculture in the study area is due to a paucity of high-quality spatial data and monitoring to support informed farm decision-making.

Labour market dynamics in the era of technological advancements: The system-wide impacts of labour augmenting technological change

The employment impact of future technological change is much debated. Some commentators predict devastating job losses, while others are more sanguine, claiming that technological change raises living standards without reducing total employment. Our analysis a use a combination of partial equilibrium and dynamic computable general equilibrium (CGE) analysis with neo-Keynesian characteristics. These models are employed to assess the implications of skill-biased labour-augmenting technological change. They are calibrated on recent German Social Accounting Matrix data and parameterised using the best available empirical results from developed economies. The numerical CGE multi-sectoral model simulates the system-wide impacts of pervasive technical change affecting all sectors of the economy. The model allows investigation of alternative scenarios based around a common economic structure and set of parameter values. The results suggest that labour-augmenting technological change typically stimulates GDP growth and long-run total employment. However, there are negative short- and medium-run employment and real wage implications which might require government policy intervention. The simulations indicate that for open developed economies, improving the efficiency of skilled workers, as opposed to unskilled workers, is the most beneficial. This improvement has positive long-run impacts that are spread across both skill classifications. On the other hand, increasing the efficiency of the unskilled produces negative impacts on skilled employment and real wages. Additionally, the openness of the economy to migration and trade are important in determining the scale of these system-wide effects.

Stakeholder interactions of government intervention in construction and demolition waste recycling market: A game theory approach

To acquire an in-depth understanding on how government intervention affects C&DW recycling market, this study develops four game models consisting of three main categories of stakeholders, e.g., the government, contractors, and C&DW receivers (recycling enterprises and landfills) to reveal stakeholder interactions of government intervention. Taking China's C&DW recycling market as an example, four different scenarios are established to examine and compare the effects of government intervention policies on C&DW recycling, illegal dumping, and stakeholder profits. Finally, numerical simulations are performed to gain further insights into the impact of government intervention on stakeholders' behaviors with a case study from Shenzhen, China. Results indicate: (1) government intervention policies can always lead to an increased amount of C&DW recycled and a reduced amount of C&DW illegally dumped compared to no any measure; (2) government subsidy can improve the market competitiveness of recycling enterprises and weaken the competitiveness of landfills. Both subsidy-only and subsidy-plus-penalty policies help reduce economic burden on contractors compared to no interventions, but penalty policy increases contractors' expenditures. Finally, penalty policy can significantly reduce the amount of illegally dumped C&DW, while subsidy policy can significantly increase the amount of recycled C&DW. This study provides valuable theoretical support and practical guidance for decision-making of governments in developing economies to develop C&DW recycling by formulating targeted intervention policies.

Investigating Public Support for the Carbon Generalized System of Preference through the Lens of Protection Motivation Theory and Information Deficit Model

The pressing challenges of climate change require government policy interventions. The carbon generalized system of preference (CGSP) is a novel incentive policy that has tremendous potential to reduce carbon emissions in response to climate change. However, there have been few studies focusing on public support for the CGSP, which is the precondition for its seamless implementation. Drawing on the protection motivation theory and information deficit model, this study presents and empirically validates a holistic theoretical framework in which information (information about climate change and information about the CGSP), threat appraisal (threat vulnerability and threat severity), and coping appraisal (response efficacy, self-efficacy, and response cost) are the factors influencing public support for the CGSP. Survey data of 372 respondents were empirically analyzed using the PLS-SEM method. The results show that threat vulnerability, threat severity, response efficacy, and self-efficacy positively affect public support for the CGSP, while response cost does not influence public support for the CGSP. Information about climate change indirectly influences public support for the CGSP through threat vulnerability and threat severity. Information about the CGSP not only directly affects public support for the CGSP but also indirectly affects public support for the CGSP through response efficacy and self-efficacy. The theoretical framework of this study can serve as a reference for future research on public support for environmental policies. The findings of this study also furnish insights for policymakers to develop feasible strategies for the seamless implementation of the CGSP.

MULTIDIMENSIONAL POVERTY AND EDUCATIONAL INEQUALITY: ASSESSMENT OF GOVERNMENT POLICY INTERVENTION IN NIGERIA

Aim of the study: Nigeria has a high incidence of multidimensional poverty and educational inequality. The government has implemented several policies to address these challenges, but the results have been mixed. Given this, the study assesses a comprehensive analysis of Nigeria's government's policy intervention regarding multidimensional poverty and educational inequality based on the country's current situation, policy initiatives, effectiveness, and the way forward. Design/Methodology: The study employed the interpretivism philosophy, and a qualitative approach was adopted in data collection and analysis. Secondary data were sourced from the current reports of the World Bank, UNDP, UNICEF, UNESCO, and NBS for a more detailed and accurate analysis. Findings: The findings of the study reveal that addressing multidimensional poverty and educational inequality is a complex and long-term process that requires sustainable efforts through investing in rural development, as 80% of all multidimensionally poor people live in rural areas. Practical Implications: The research was able to bring to light the need for governments to invest massively in formal and informal education, industrialisation, proper planning and policies, inter-ministerial collaboration, database unification, and timely population census. Originality/value: This empirical study will provide more in-depth knowledge of SDGs 1, 2, 3, 4, and 5 through practical implementation for Nigerian governments at all levels and other stakeholders. The study distinguished itself from prior similar investigations. To summarise, this empirical study will provide more knowledge through real-world application, primarily for addressing multidimensional poverty and educational inequality in Nigeria. Keywords: Government policy interventions, Multidimensional poverty, educational inequality, intersectionality Theory, Gender inequality Paper Type: Review Article

Carbon tax and low-carbon credit: Which policy is more beneficial to the capital-constrained manufacturer's remanufacturing activities?

Remanufacturing has attracted much attention for its enormous potential in resource recycling and low-carbon emission reduction. To investigate the effects of different government intervention policies on remanufacturing and carbon emissions, two profit maximization models of the capital-constrained manufacturer under carbon tax and low-carbon credit policies are constructed respectively. Then, through theoretical and numerical analyses, some significant findings are drawn: (1) Both carbon tax and low-carbon credit policies can encourage capital-constrained manufacturers to produce more remanufactured products, but which intervention policy is more advantageous also depends on the carbon emission cost of new products or financing cost of the remanufactured products. (2) Although carbon tax policy can effectively control carbon emissions, it is always at the expense of both capital-constrained manufacturers and consumers; while low-carbon credit policy can help capital-constrained manufacturers achieve the goal of win-win economic and environmental benefits when the remanufacturing carbon savings advantages are more apparent. (3) From the perspective of consumer benefits, carbon tax is more advantageous when the consumer willingness to pay for remanufactured products is higher; otherwise, low-carbon credit policy should be implemented. (4) The higher the environmental damage coefficient is, the more it can highlight the advantages of the two intervention policies in social welfare enhancement, especially the carbon tax policy; and when the environmental damage coefficient is given, the stronger the consumers’ willingness to pay for remanufactured products is, the more it is conducive to reducing the negative effects caused by the carbon tax or low-carbon credit policy in social welfare enhancement, or increasing the corresponding positive effects. Based on above findings, some managerial insights and policy implications are provided to capital-constrained manufacturers and policy-makers.

Consequences of COVID-19 for Currency Markets of US Dollar and RMB

The present research explores the influence of the COVID-19 epidemic on the currency markets of the US dollar and RMB, with the aim of comprehensively grasping the operational mechanisms of global financial markets. Through time series analysis, ARIMA and GARCH models are constructed to capture the short - and long-term effects of currency markets fluctuations. The findings showed that the market uncertainty surged in the early stage of the epidemic, leading investors to turn to the US dollar, making the US dollar/RMB currency markets fluctuate significantly in the short term. This paper emphasizes that exchange rate fluctuations are affected by multiple factors, including economic activity, investor sentiment and government policy intervention. Investors are advised to diversify their portfolios and consider the impact of currency markets fluctuations over immediate and extended periods. Policymakers should also prepare plans to deal with market uncertainty, including intervening in foreign exchange markets, stabilizing the financial system, and adopting targeted monetary policy. In conclusion, this paper provides an in-depth examine how the USD/RMB exchange rate has been influenced by the COVID-19 pandemic. and provides practical advice for investors and policymakers.