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Item type:Publication, School education development index: A meta-frontier range directional measure benefit-of-the-doubt model(Elsevier Ltd, 2024-04-01)While the imperative of gauging school education development across regions is widely acknowledged, a scarcity of methodologically robust measures to quantify it persists. This paper introduces an innovative non-parametric framework for constructing an all-inclusive school education development index (SEDI) across regional entities. The proposed framework, termed “meta-RDM-BoD”, seamlessly integrates three distinct yet interconnected non-parametric efficiency modeling approaches: the range directional measure (RDM) proposed by Portela et al. (2004) [5], the meta-frontier analysis developed by O'Donnell et al. (2008) [6], and the benefit-of-the-doubt (BoD) technique put forth by Melyn and Moesen (1991) [7]. Notably, the proposed framework adeptly handles both desirable and undesirable indicators, accommodates indicators with negative and zero values without compromising the properties of translation and unit invariance, and effectively accounts for underlying heterogeneity across regional entities. To illustrate the efficacy of the SEDI, we provide a compelling example using data on 36 school education indicators for Indian states and union territories in 2021–2022. These indicators cover five crucial dimensions of school education: access to school, school infrastructure and facilities, teacher quality, school outcomes, and equity in education. The results reveal spatial gaps in school education development, offering valuable insights for benchmarking, ranking, and classifying regional entities. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Economic policy uncertainty and the inhibitory effect of firms' green technology innovation(Elsevier B.V., 2024-05-01)Given the potential unforeseen impacts of environmental regulation changes on the innovative activities of micro agents, it is crucial to examine the effects of economic policy uncertainty (EPU) on business development. Several studies have shown that uncertainty acts as a hindrance and can hinder business innovation. This study utilizes data from 807 listed companies spanning from 2007 to 2019 and employs a double fixed-effects model to investigate the influence of EPU on enterprises' green technology innovation activities. The results reveal that EPU decreased firms' green technology innovation. Moreover, EPU inhibits corporate green technology innovation by increasing corporate financing constraints. Thus, financing constraints mediate between EPU and enterprises' level of green technology innovation, with increased market competition reducing the inhibiting effect of EPU on innovation. Furthermore, EPU decreases green technology innovation more among nonstate-owned and low-tech businesses than state-owned and high-tech businesses. This paper reveals the intrinsic mechanism of EPU on firms' innovation, clarifies the technological innovation process, and provides insights into governmental environmental governance from the perspective of EPU. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Enhancing enterprise investment efficiency through artificial intelligence: The role of accounting information transparency(Elsevier Ltd, 2024-12-01)In the post-COVID-19 era, with global economic recovery as a critical goal, the rapid development of artificial intelligence (AI) has emerged as a key driver of economic growth and transformation. AI not only acts as a powerful catalyst for economic development but also significantly impacts enterprise investment efficiency (EIE). This paper explores the influence of AI on EIE, with a focus on the role of accounting information transparency. Using data from Shanghai and Shenzhen A-share listed enterprises between 2010 and 2021, the findings demonstrate that AI development significantly enhances EIE. These results are confirmed through robustness tests, including variable substitution, and addressing endogeneity and sample limitations. Mechanism analysis reveals that AI improves EIE by increasing the transparency of accounting information. Additionally, heterogeneity analysis shows that AI has a greater impact on the investment efficiency of high-tech and technology-intensive enterprises, non-state-owned enterprises, and those located in highly urbanised areas, such as ‘Broadband China’ pilot cities. This paper examines how AI development affects EIE through the lens of enterprise accounting information transparency, offering actionable insights for enhancing accounting disclosures and serving as a valuable resource for enterprises navigating the technological transformation of the modern era.