Author(s):
Jannis Bischof, Dirk Simons, Johannes Voget, Davud Rostam-Afschar
Cooperation Partners:
DFG, German Research Foundation, Paderborn University, HU Berlin, LMU Munich, Frankfurt School of Finance and Management, WHU – Otto Beisheim School of Management, European School of Management and Technology Berlin, Goethe University Frankfurt (...)
Bundesverband der Deutschen Industrie, Institut für Mittelstand, Zentralverband des Deutschen Handwerks (...)
Description:
The German Business Panel (GBP) is a representative panel of managers bearing responsibilities for accounting and tax matters in German firms. These representatives are surveyed on a semi-annual basis on topics in the area of financial accounting, managerial accounting and taxation.
Let us know what you want to know about firm behavior! Both firms and researchers may submit survey questions for possible inclusion in the survey. From all submissions, firms can vote for inclusion in a list of top research questions. A scientific committee will select the most suitable questions for possible inclusion in the survey. On a regular basis, we provide indicators for tax sentiments and other relevant issues.
Link to website: https://gbpanel.org/
Author(s):
Christopher Ludwig, Christoph Spengel, Rainer Bräutigam
Cooperation Partners:
Chair of Business Administration and Taxation II
Description:
This project is based on publicly accessible Airbnb data regarding the type of lodging offered on the platform, the price per night, the facilities and equipment, the location of the accommodation as well as booking trends in 20 German cities. On the basis of this data we carry out projections to estimate the annual turnover of hosts as well as the potential tax revenue arising from this turnover. The annual turnover of all accommodations in the 20 considered cities is approximately 683 million euros. Based on the annual turnover projections, the analysis shows that the estimated tax revenue from income and value-added tax liability, is enormous for lodgings offered on the exemplarily analyzed sharing platform.
Given the size of tax revenues at stake, we develop recommendations on how to adjust existing tax systems in order to adapt them to the digital economy and to ensure compliance among taxpayers.
Author(s):
Christoph Spengel, Alexander Maedche, Sven Scheu, Sarah Winter
Cooperation Partners:
Institute of Information Systems and Marketing (IISM) at KIT, EnBW AG
Description:
Tax departments are facing new regulatory requirements to provide an increasing amount of information to tax authorities. Thus, being able to process structured and unstructured tax data in a timely manner and improve decision making processes is essential.
We collaborate with a major German energy supplier to develop new concepts for the digital transformation of the tax function. The project focuses on optimizing processes in the tax department through digital means and enhancing existing tax information systems and intragroup information processing. The project also aims at developing data-driven intelligent assistant functions to support decision-making processes using Process Mining, Business Intelligence, and more generally spoken Data Science.
Author(s):
Verena Dutt, Katharina Nicolay, Heiko Vay, Johannes Voget, Christoph Spengel
Cooperation Partners:
Chair of Business Administration & Taxation II, Taxation & Finance
Description:
The insights of this project are especially relevant in the context of the ongoing political discussions whether to introduce a public country-by-country (CbC) reporting for all large multinational firms in the EU.
The project uses hand-collected data – facilitated with an automated process – from mandatory CbC-reports of European banks. The data offer a precise look into the amount of profits and turnover and the number of employees in the jurisdictions where multinational banks operate and allow to estimate the profitability of different locations. The goal of this project is to identify if public CbC-reporting provides incremental information on the profit shifting behavior of multinational banks compared to commercial databases like Orbis.