Although state-owned enterprises are associated with less efficiency and lead to resource misallocation, they may have stabilizing effect in face of a crisis. Exploiting the COVID-19 pandemic as a natural experiment, we study the role of firm ownership in trade credit provision and find robust evidence that SOEs increase their trade credit to downstream firms more than non-SOEs after the outbreak of the pandemic. Moreover, we explore the underlying mechanism and find that better financing ability and multitask of the SOEs contribute to greater trade credit during the pandemic, and the latter plays a more active role. Further analyses show that SOEs' advantage in trade credit extension is more pronounced in industries with higher external financial dependence and provinces with a higher level of government involvement, suggesting that SOEs might have greater comparative advantage in screening due to its involvements in local economy during crisis periods. Our paper provides new insights into the real effects of SOEs on the economy.
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http://dx.doi.org/10.1016/j.jimonfin.2023.102901 | DOI Listing |
Appl Health Econ Health Policy
January 2025
Menzies Centre for Health Policy and Economics, Sydney School of Public Health, University of Sydney, Sydney, NSW, Australia.
Background: Non-invasive prenatal testing has the potential to be a useful genetic screening tool in Australia. However, concerns have been raised about its cost, commercial provision, the psychological impacts of the screening process, and disparities in access experienced by rural and regional communities.
Aims: The aims of this study are (1) to estimate Australian preferences for features of prenatal screening; (2) to explore potential variations in preferences between metropolitan and rural/regional communities; (3) to estimate the extent to which respondents are willing to trade-off between attributes, using willingness to pay (WTP) and willingness to wait estimates.
J Environ Manage
January 2025
Ecoresolve, San Francisco, CA, USA; Earth Observation Centre, Institute of Climate Change (IPI), Universiti Kebangsaan Malaysia, Bangi, 43600, Malaysia; Department of Civil Engineering, College of Engineering, American University of Sharjah (AUS), P.O. Box 26666, Sharjah, United Arab Emirates; Department of Geography, University of California-Berkeley, Berkeley, CA, 94709, USA. Electronic address:
Mangrove-based carbon market projects (MbCMP) aim to conserve, protect and restore mangrove habitats in order to generate high quality blue carbon credits via a crediting program, as a contribution to climate change mitigation/adaptation, biodiversity conservation, ecosystem services provision and local socio-economic development. The blue carbon credits generated are transferable, verifiable and sold through carbon markets to earn additional income for governments and local communities. The main aim of the paper is to provide important considerations for pre-field planning, that is, how challenges associated with fieldwork, project implementation, and monitoring reporting and verification (MRV) can be addressed with proper pre-field planning.
View Article and Find Full Text PDFHeliyon
October 2024
LERMA Laboratory, College of Engineering, International University of Rabat, Sala Al Jadida, 11100, Morocco.
In the context of growing focus over climate changes and promoting sustainability across a various range of fields, microgrids can play a significant role in global decarbonization endeavors, contributing to carbon neutrality and ultimately attaining net-zero emissions in the energy sector. The objective of this paper is to address the integration of voluntary carbon trading within microgrid communities, in the perspective to mitigate greenhouse gas (GHG) emissions and boost the integration of renewable energy sources (RES). Introducing five modular algorithms managing key aspects of carbon trading, the study engineers a comprehensive framework aiming to optimally orchestrate the Voluntary Carbon Market (VCM) within microgrids.
View Article and Find Full Text PDFHeliyon
October 2024
School of Economics and Management, Tsinghua University, Beijing, 100084, China.
This paper aims to provide new avenues for innovation in credit governance in the digital economy to provide more reliable credit evaluation solutions for financial, commercial, and social interactions. This paper integrates the potential value of Internet of Things (IoT) technology in credit governance and proposes a credit governance method that utilizes IoT data and an improved Long Short-Term Memory model. The proposed model introduces an adaptive mechanism to monitor changes in data in real-time and automatically adjust network parameters to improve the model performance.
View Article and Find Full Text PDFMethodsX
December 2024
Infineon Technologies, Free Trade Zone, Batu Berendam, Melaka 75350, Malaysia.
Credit card usage has surged, heightening concerns about fraud. To address this, advanced credit card fraud detection (CCFD) technology employs machine learning algorithms to analyze transaction behavior. Credit card data's complexity and imbalance can cause overfitting in conventional models.
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