数字经济时代会计变革及对策

随着数字经济时代的来临，以人工智能技术为代表的现代信息技术越来越多地应用到会计工作中，会计工作将进入数字会计时代，向共享会计、管理会计、智能会计发展。为了适应数字经济带来的变化，会计机构要成为企业的“数据中心”，发挥管理和服务职能。会计人员要积极学习现代信息技术和管理知识，实现由核算型向管理型转型。     

Herding behaviour and the declining value relevance of accounting information: evidence from an emerging stock market

This article sheds light on the underlying mechanisms behind the changes in the value relevance of accounting information in the Karachi Stock Exchange (KSE) during the 1999–2010 period. We find that neither changes in earnings quality nor the earnings lack of timeliness hypothesis can explain the decline in the value relevance of accounting information in the KSE. Based on the stylized facts associated with the growth of the KSE and the broader economics literature, we argue that the reduction in the explanatory power of accounting information vis-à-vis stock returns was caused by herding behaviour. Empirical estimates from state-space model of herding behaviour confirm the existence of herding, and we find that the value relevance of accounting information is significantly lower in periods characterized by herding behaviour. This article is also amongst the first attempts to empirically demonstrate that an expansionary monetary policy and increases in foreign portfolio investment lead to increased levels of herding.     

Total factor productivity convergence in German states since reunification: Evidence and explanations

A quarter-century after reunification, labor productivity in the states of eastern Germany continues to lag systematically behind the West. Persistent gaps in total factor productivity (TFP) are the proximate cause; conventional and capital-free measurements confirm a sharp slowdown in TFP growth after 1995. Strikingly, eastern capital intensity, especially in industry, exceeds values in the West, casting doubt on the embodied technology hypothesis. TFP growth is negatively associated with rates of investment expenditures. The stubborn East-West TFP gap is best explained by low concentration of managers, low startup intensity and the distribution of firm size in the East rather than R&D activities.     

Seasonality and regional productivity in the Spanish accommodation sector

This study quantifies the impact of peak demand and seasonality on regional productivity in the Spanish accommodation sector. We then identify factors affecting seasonal fluctuations and their relative contributions to regional variations in seasonality. The results show that demand for accommodation in the peak season mainly determines productivity. Thus, improving a region's attractiveness as a tourist destination is most effective for tourism-based regional development. In addition, reducing seasonal variations has a non-negligible impact on productivity. A decomposition analysis reveals that providing climate-independent tourist attractions and attracting business travelers are effective in reducing seasonality.     

European firms’ corporate biodiversity disclosures and board gender diversity from 2002 to 2016

We examine how board gender diversity is associated with biodiversity disclosures of a firm, and whether the Global Reporting Initiative (GRI) and the EU biodiversity strategy reinforce this relationship. Using institutional theory and resource dependency theory, our sample comprises 4013 firm-year observations from European corporations covering data from 2002 to 2016. We use panel regressions with country, time and industry dummy variables to analyse the disclosure of biodiversity initiatives (DBI) and logit regressions to explain biodiversity impact assessment (BIA). We find that board gender diversity is positively associated with the DBI and BIA of a firm, and that the GRI framework and the EU biodiversity strategy positively moderate this relationship. Moreover, the GRI framework and the EU strategic plan show positive relationship with the DBI, rather than BIA. Altogether, our evidence suggests that corporate boards with a higher proportion of female directors are more sensitive to the concerns of institutional pressures and respond to those concerns by increasing corporate biodiversity disclosures. Overall, we find that firms tend to comply with the GRI framework and the EU 2020 strategy by undertaking symbolic biodiversity disclosures, rather than providing a comprehensive disclosure of their impacts on biodiversity.     

NOMINAL GDP TARGETING AND CENTRAL BANK CONSERVATIVENESS

In the literature on monetary economics, there is the ‘inflationary bias’ result which predicts that the rate of inflation will be biased towards a higher level under discretionary monetary policy than under a rule‐based policy regime. It is established that a credible nominal target can eliminate this ‘inflationary bias’. In this paper, we examine the case of nominal GDP targeting, which is a rule‐based monetary regime. Depending on the degree of conservativeness by the central bank, we show in a stylized model the choice of different combination of inflation and real GDP targets can still result in an ‘inflationary bias’, and there also exists the possibility of a ‘dis‐inflationary bias’.     

Schmoozers,not snoozers: Busting the Kevin and Angela stereotypes in public accounting

In contrast to the well-known stereotype of the boring, unsociable accountant, today’s public accounting professionals argue that they are boundary spanners. Working at the intersection of the firm/client interface, these professionals contend that sociability is a requisite skill for routinely navigating the many interactions they have with multiple personnel at client organizations. This research aims to address this disconnect and to confront whether the public perception is warranted. Using the Trait Emotional Intelligence Questionnaire (TEIQue), we assess the sociability of 176 public accounting professionals and discover that, contrary to the stereotype, male public accountants are more sociable than males in the general population. Our analysis also demonstrates that female public accountants are no more or less sociable than females in the general population. Additional analysis shows that while male public accountants are more sociable than female public accountants, this effect is attributable to differences at lower levels of the profession and that male-female differences disappear when comparing male managers and partners to female managers and partners. Given the importance of sociability in public accounting, this research offers recruiting strategies that will help to dispel the myth of the unsociable accountant and provides training tips for enhancing sociability within the ranks.     

Enhancing environmental information transparency through corporate social responsibility reporting regulation

This research aims to contribute to the scientific debate about the lack of interlinkages between mandatory non-financial reporting and sustainable business models. For our purposes, a counter-accounting analysis was conducted on the non-financial reports of a sample of 145 Italian firms interested by the Directive 2014/95/EU effects. Specifically, the study adopts an empirical approach to evaluate environmental information transparency, which represents one of the main critical issues concerning the non-financial declarations prepared by European Italian Public Interest Entities (PIEs) to comply with Directive 2014/95/EU. The results highlight that corporate governance and report characteristics affect environmental transparency. Furthermore, the results confirm the overall attitude to avoid the disclosure of unfavourable or unavailable environmental information through impression management strategies. Finally, the analysis underlines the opportunities for policymakers to rethink mandatory non-financial reporting to sustain the ecological transition of European PIEs.     

浅析会计信息系统实施与评价

计算机技术的蓬勃发展,使得企业办公更加智能化、效率化。由于传统手工记账具有容量小的弊端,无法处理大、中型企业庞大的金融数据。企业运用计算机处理繁杂财务工作的突出效果,间接吸引了大批科技企业加快对企业财务应用系统的研发速度。针对会计信息系统应用中的问题,急需对系统进行改造升级,保护财务数据安全;聚焦会计信息管理,提高专业人员素质;严于监管,战略转变,突破技术壁垒。     

Machine learning for financial transaction classification across companies using character-level word embeddings of text fields

An important initial step in accounting is mapping financial transfers to the corresponding accounts. We devised machine-learning-based systems that automate this process. They use word embeddings with character-level features to process transaction texts. When considering 473 companies independently, our approach achieved an average top-1 accuracy of 80.50%, outperforming baselines that exclude the transaction texts or rely on a lexical bag-of-words text representation. We extended the approach to generalizes across companies and even across different corporate sectors. After standardization of the account structures and careful feature engineering, a single classifier trained on 44 companies from 28 sectors achieved a test accuracy of more than 80%. When trained on 43 companies and tested on the remaining one, the system achieved an average performance of 64.62%. This rate increased to nearly 70% when considering only the largest sector.