Exploring Accounting Research Topic Evolution: An Unsupervised Machine Learning Approach
June Cao, Zhanzhong Gu, Iftekhar Hasan
Journal of International Accounting Research,
No. 3,
2023
Abstract
This study explores the evolution of accounting research by utilizing an unsupervised machine learning approach. We aim to identify the latent topics of accounting from the 1980s up to 2018, the dynamics and emerging topics of accounting research, and the economic reasons behind those changes. First, based on 23,220 articles from 46 accounting journals, we identify 55 topics using the latent Dirichlet allocation model. To illustrate the connection between topics, we use HistCite to generate a citation map along a timeline. The citation clusters demonstrate the “tribalism” phenomenon in accounting research. We then implement the dynamic topic model to reveal the dynamics of topics to show changes in accounting research. The emerging research trends are identified from the topic analytics. We further explore the economic reasons and in-depth insights into the topic evolution, indicating the economic development embeddedness nature of accounting research.
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EVA-KULT
EVA-KULT Establishing Evidence-based Evaluation Methods for Subsidy Programmes in Germany The project aims at expanding the Centre for Evidence-based Policy Advice at the Halle…
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Transformation tables for administrative borders in Germany
Transformation tables for administrative borders in Germany The state has the ability to change the original spatial structure of its administrative regions. The stated goal of…
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Anniversary 2017
Anniversary 2017 25 years IWH. Highlights and turning points. A quarter of a century ago, our employees started to work for IWH. What has happened from then until now? Content 25…
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Privacy
Data Protection Policy We take the protection of your personal data very seriously and treat your personal data with confidentiality and in compliance with the provisions of law…
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Predicting Free-riding in a Public Goods Game – Analysis of Content and Dynamic Facial Expressions in Face-to-Face Communication
Dmitri Bershadskyy, Ehsan Othman, Frerk Saxen
IWH Discussion Papers,
No. 9,
2019
Abstract
This paper illustrates how audio-visual data from pre-play face-to-face communication can be used to identify groups which contain free-riders in a public goods experiment. It focuses on two channels over which face-to-face communication influences contributions to a public good. Firstly, the contents of the face-to-face communication are investigated by categorising specific strategic information and using simple meta-data. Secondly, a machine-learning approach to analyse facial expressions of the subjects during their communications is implemented. These approaches constitute the first of their kind, analysing content and facial expressions in face-to-face communication aiming to predict the behaviour of the subjects in a public goods game. The analysis shows that verbally mentioning to fully contribute to the public good until the very end and communicating through facial clues reduce the commonly observed end-game behaviour. The length of the face-to-face communication quantified in number of words is further a good measure to predict cooperation behaviour towards the end of the game. The obtained findings provide first insights how a priori available information can be utilised to predict free-riding behaviour in public goods games.
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An Empirical Analysis of Legal Insider Trading in The Netherlands
Frank de Jong, Jérémie Lefebvre, Hans Degryse
De Economist,
No. 1,
2014
Abstract
In this paper, we employ a registry of legal insider trading for Dutch listed firms to investigate the information content of trades by corporate insiders. Using a standard event-study methodology, we examine short-term stock price behavior around trades. We find that purchases are followed by economically large abnormal returns. This result is strongest for purchases by top executives and for small market capitalization firms, which is consistent with the hypothesis that legal insider trading is an important channel through which information flows to the market. We analyze also the impact of the implementation of the Market Abuse Directive (European Union Directive 2003/6/EC), which strengthens the existing regulation in the Netherlands. We show that the new regulation reduced the information content of sales by top executives.
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Skill Content of Intra-european Trade Flows
Götz Zeddies
European Journal of Comparative Economics,
No. 1,
2013
Abstract
In recent decades, the international division of labor has expanded rapidly in the wake of European integration. In this context, especially Western European high-wage countries should have specialized on (human-)capital intensively manufactured goods and should have increasingly sourced labor-intensively manufactured goods, especially parts and components, from Eastern European low wage countries. Since this should be beneficial for the high-skilled and harmful to the lower-qualified workforce in high-wage countries, the opening up of Eastern Europe is often considered as a vital reason for increasing unemployment of the lower-qualified in Western Europe. This paper addresses this issue by analyzing the skill content of Western European countries’ bilateral trade using input-output techniques in order to evaluate possible effects of international trade on labor demand. Thereby, differences in factor inputs and production technologies have been considered, allowing for vertical product differentiation. In this case, skill content of bilateral exports and imports partially differs substantially, especially in bilateral trade between Western and Eastern European countries. According to the results, East-West trade should be harmful particularly to the medium-skilled in Western European countries.
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What Drives FDI in Central-eastern Europe? Evidence from the IWH-FDI-Micro Database
Andrea Gauselmann, Mark Knell, Johannes Stephan
Post-Communist Economies,
No. 3,
2011
Abstract
The focus of this paper is on the match between strategic motives of foreign investments into Central-Eastern Europe and locational advantages offered by these countries. Our analysis makes use of the IWH-FDI-Micro Database, a unique dataset that contains information from 2009 about the determinants of locational factors, technological activity of the subsidiaries, and the potentials for knowledge spillovers in the Czech Republic, Hungary, Poland, Romania, and Slovakia. The analysis suggests that investors in these countries are mainly interested in low (unit) labour costs coupled with a well-trained and educated workforce and an expanding market with the high growth rates in the purchasing power of potential buyers. It also suggests that the financial crisis reduced the attractiveness of the region as a source for localised knowledge and technology. There appears to be a match between investors’ expectations and the quantitative supply of unqualified labour, not however for the supply of medium qualified workers. But the analysis suggests that it is not technology-seeking investments that are particularly content with the capabilities of their host economies in terms of technological cooperation. Finally, technological cooperation within the local host economy is assessed more favourably with domestic firms than with local scientific institutions – an important message for domestic economic policy.
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