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on Accounting and Auditing |
| By: | Guy Stephane Waffo Dzuyo (Forvis Mazars, LORIA - Laboratoire Lorrain de Recherche en Informatique et ses Applications - Inria - Institut National de Recherche en Informatique et en Automatique - UL - Université de Lorraine - CNRS - Centre National de la Recherche Scientifique, SYNALP - Natural Language Processing : representations, inference and semantics - LORIA - NLPKD - Department of Natural Language Processing & Knowledge Discovery - LORIA - Laboratoire Lorrain de Recherche en Informatique et ses Applications - Inria - Institut National de Recherche en Informatique et en Automatique - UL - Université de Lorraine - CNRS - Centre National de la Recherche Scientifique); Gaël Guibon (LORIA - Laboratoire Lorrain de Recherche en Informatique et ses Applications - Inria - Institut National de Recherche en Informatique et en Automatique - UL - Université de Lorraine - CNRS - Centre National de la Recherche Scientifique, LIPN - Laboratoire d'Informatique de Paris-Nord - CNRS - Centre National de la Recherche Scientifique - Université Sorbonne Paris Nord, SYNALP - Natural Language Processing : representations, inference and semantics - LORIA - NLPKD - Department of Natural Language Processing & Knowledge Discovery - LORIA - Laboratoire Lorrain de Recherche en Informatique et ses Applications - Inria - Institut National de Recherche en Informatique et en Automatique - UL - Université de Lorraine - CNRS - Centre National de la Recherche Scientifique); Christophe Cerisara (SYNALP - Natural Language Processing : representations, inference and semantics - LORIA - NLPKD - Department of Natural Language Processing & Knowledge Discovery - LORIA - Laboratoire Lorrain de Recherche en Informatique et ses Applications - Inria - Institut National de Recherche en Informatique et en Automatique - UL - Université de Lorraine - CNRS - Centre National de la Recherche Scientifique); Luis Belmar-Letelier (Forvis Mazars) |
| Abstract: | The identification of the financial characteristics of industry sectors has a large importance in accounting audit, allowing auditors to prioritize the most important area during audit. Existing company classification standards such as the Standard Industry Classification (SIC) code allow to map a company to a category based on its activity and products. In this paper, we explore the potential of machine learning algorithms and language models to analyze the relationship between those categories and companies' financial statements. We propose a supervised company classification methodology and analyze several types of representations for financial statements. Existing works address this task using solely numerical information in financial records. Our findings show that beyond numbers, textual information occurring in financial records can be leveraged by language models to match the performance of dedicated decision tree-based classifiers, while providing better explainability and more generic accounting representations. We think this work can serve as a preliminary work towards semi-automatic auditing. Models, code, and a preprocessed dataset are publicly available for further research at https://github.com/WaguyMz/hybrid company classification |
| Keywords: | Machine Learning, Industry Sectors, Large Language Models, LLM Applications, Audit, Financial Statement |
| Date: | 2025–02–25 |
| URL: | https://d.repec.org/n?u=RePEc:hal:journl:hal-05031499 |
| By: | Paloma Péligry (CEPS - Centre d'Economie de l'ENS Paris-Saclay - Université Paris-Saclay - ENS Paris Saclay - Ecole Normale Supérieure Paris-Saclay); Xavier Ragot (Sciences Po - Sciences Po) |
| Abstract: | We analyze the convergence or divergence of the diversity of fiscal systems after the financial crisis of 2007. Studying 29 countries, we first document the evolution of the taxation of households, firms, labour, consumption and capital. We identify three types of fiscal systems: liberal, intermediate and high-redistribution, which can be ranked in ascending order of tax rates, confirming known typologies in the diversity of capitalism literature. Only the tax rate on corporate profits shows signs of downward convergence over the period. The other tax rates show rather signs of divergence. Second, a divergence is observed among the liberal and high-redistribution group over the period. The European countries are converging towards the high-redistribution model, with the exception of Great Britain, which is moving towards the liberal model. Thus, the financial crisis seems to contribute not to the convergence, but to the divergence of fiscal systems. |
| Keywords: | tax systems, globalization, capital taxation |
| Date: | 2024–04 |
| URL: | https://d.repec.org/n?u=RePEc:hal:journl:hal-05033579 |
| By: | Jules Ducept; Sarah Godar |
| Abstract: | This paper documents the rise of corporate tax-base narrowing measures in the EU using a novel dataset covering both tax rate and tax base reforms implemented between 2014 and 2022. Our findings indicate a shift away from the ’cut rate – broaden base’ approach, as governments increasingly align corporate taxation with industrial policy objectives. We show that EU tax competition exerts downward pressure on high-tax countries, while the likelihood of tax cuts also varies with the political orientation of governments. Using financial accounts from more than 40, 000 affiliates, we find that the average effective tax rate of multinational enterprises in the EU has declined more rapidly than the statutory rate and estimate that tax base reforms account for 24% of this decline. The estimated revenue cost of all reforms combined amounts to 3.5% of total corporate tax revenue collected from the sample firms. These revenue losses should be carefully weighed against the anticipated benefits of tax reforms. |
| Keywords: | Effective Tax Rates, Multinationals, Tax Competition, Corporate Income Tax, Tax Reform, Political Orientation, European Union |
| JEL: | F23 H25 H26 P11 |
| Date: | 2025 |
| URL: | https://d.repec.org/n?u=RePEc:diw:diwwpp:dp2117 |
| By: | Mara Faccio; Jin Xu |
| Abstract: | Using limitations to the deductibility of interest payments triggered by the introduction of interest ceiling rules globally, we show that affected private firms reduce leverage relative to unaffected firms. In support of a causal effect of taxes on corporate capital structure choices, we show that the results hold for firms near the thresholds triggering the limitations, in a propensity score matched sample, and in countries required to adopt the interest ceiling rules. In contrast, falsification tests show no reduction in leverage for affected firms around pseudo-reform years. Furthermore, within a country, firms with a higher fraction of nondeductible interest payments are less responsive to tax rate changes. More broadly, across 93 countries, we document that private firms tend to decrease leverage in response to tax rate cuts and increase leverage in response to corporate tax rate hikes. |
| JEL: | F30 G30 G32 G38 H2 H25 H26 |
| Date: | 2025–04 |
| URL: | https://d.repec.org/n?u=RePEc:nbr:nberwo:33685 |
| By: | Dounia El Hamel (Université Ibn Zohr = Ibn Zohr University [Agadir]); Mohamed Elkhabachy (Conseil régional d’Agadir des experts-comptables et des commissaires aux comptes) |
| Abstract: | The restructuring of the sports sector is a priority for the Moroccan legislator, who establishes the promotion of sports companies as a central pillar of this reform. These transformations aim to strengthen the structuring and regulation of the sports sector while promoting its expansion at all levels and reinforcing its fundamental educational and social values. Law 30-09 introduces significant advancements in this regard but also reveals certain limitations. For sports companies to fully benefit from these reforms, a thorough understanding of the accounting and tax treatment of their operations is essential, both at the time of their incorporation and throughout their development. A rigorous legal and financial analysis of the applicable legislation is necessary to identify its strengths and shortcomings and to consider the necessary adjustments to establish a more conducive framework for their sustainable growth. |
| Abstract: | La restructuration du secteur sportif constitue une priorité pour le législateur marocain, qui érige la promotion des sociétés sportives en pilier central de cette réforme. Ces transformations visent à renforcer la structuration et l'encadrement du domaine sportif, tout en favorisant son expansion à tous les niveaux et en consolidant ses valeurs éducatives et sociales fondamentales. La loi 30-09 introduit des avancées notables dans cette dynamique, mais elle révèle également certaines limites. Pour que les sociétés sportives tirent pleinement parti de ces réformes, une maîtrise approfondie du traitement comptable et fiscal de leurs opérations s'avère essentielle, tant lors de leur constitution que tout au long de leur développement. Une analyse rigoureuse, à la fois juridique et financière, de la législation en vigueur s'impose afin d'en dégager les atouts et les insuffisances et d'envisager les ajustements nécessaires pour instaurer un cadre plus favorable à leur essor durable. |
| Keywords: | Sports company, Anonymous company, Accounting and fiscal treatment, shortcomings of the accounting plan, Association, Société sportive, Société anonyme, Le traitement comptable et fiscal, Les insuffisances du plan comptable |
| Date: | 2025–03–07 |
| URL: | https://d.repec.org/n?u=RePEc:hal:journl:hal-05021740 |
| By: | Xavier Gabaix; Ralph S. J. Koijen; Robert J. Richmond; Motohiro Yogo |
| Abstract: | Firm characteristics, based on accounting and financial market data, are commonly used to represent firms in economics and finance. However, investors collectively use a much richer information set beyond firm characteristics, including sources of information that are not readily available to researchers. We show theoretically that portfolio holdings contain all relevant information for asset pricing, which can be recovered under empirically realistic conditions. Such guarantees do not exist for other data sources, such as accounting or text data. We build on recent advances in artificial intelligence (AI) and machine learning (ML) that represent unstructured data (e.g., text, audio, and images) by high-dimensional latent vectors called embeddings. Just as word embeddings leverage the document structure to represent words, asset embeddings leverage portfolio holdings to represent firms. Thus, this paper is a bridge from recent advances in AI and ML to economics and finance. We explore various methods to estimate asset embeddings, including recommender systems, shallow neural network models such as Word2Vec, and transformer models such as BERT. We evaluate the performance of these models on three benchmarks that can be evaluated using a single quarter of data: predicting relative valuations, explaining the comovement of stock returns, and predicting institutional portfolio decisions. We also estimate investor embeddings (i.e., representations of investors and their strategies), which are useful for investor classification, performance evaluation, and detecting crowded trades. We discuss other applications of asset embeddings, including generative portfolios, risk management, and stress testing. Finally, we develop a framework to give an economic narrative to a group of similar firms, by applying large language models to firm-level text data. |
| JEL: | C53 G12 G23 |
| Date: | 2025–04 |
| URL: | https://d.repec.org/n?u=RePEc:nbr:nberwo:33651 |