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Microsimulation und Model Development

June 2009 (completed) Contract Research

Project Description

Content of this project is the ongoing development of the Liechtenstein micro-simulation models. There are two basic models: microLIE: PIT is the model of the personal income tax system and microLIE: CIT a model for the business tax. The micro-simulation models are continuously adapted to the current legal status and methodically expanded. For the business tax model was a data-based measure of the corporate marginal tax rate developed. In the model of the personal income taxation was a new welfare measurement implemented. The next steps in the methodological development of the business tax model concern the simulation of changes in capital structure, the model of natural persons will be extended by a life-cycle model.

Relevance to Liechtenstein

Die Mikrosimulationsmodelle bilden das liechtensteinische Steuersystem mit seinen Spezifika ab. Durch ihre Weiterentwicklung (ua der Modigliani-Miller Theoreme zur Bestimmung der gewichteten Kapitalkosten unter Einbezug des liechtensteinischen Steuersystems) können unter Berücksichtigung des Einflusses des liechtensteinischen Steuersystems Investitionen und Unternehmen bewertet werden.

Scientific, Economic and Societal Impact

The project allows the ongoing development of the Liechtenstein micro-simulation models. The implementation of new scientific methods extends the range of techniques available for policy analysis on behalf of the Liechtenstein government.

Keywords

Taxes Dynamic Microsimulation Redistributive and Welfare Effects Fiscal Policies and Behavior of Economic Agents

Participating Institutions

Chair for Tax Management and the Laws of Liechtenstein and International Taxation / Project Lead Regierung des Fürstentums Liechtenstein / Partner

Project Participants

Employee
Prof. Dr. Martin Wenz
- Principal Investigator
Professor - Business Management Taxation and Tax Law Academic Director - Liechtenstein Executive School
Principal Investigator
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Employee
Dr. Tanja Kirn
- Project Manager
Head - Center for Economics Assistant Professor - Liechtenstein Business School
Project Manager
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Publications

MIGAPE

October 2018 until September 2020 (completed) EU H2020-Funding Project

Project Description

On average, women receive a lower pension than men. This is known as the Gender Pension Gap. MIGAPE (2019-2021) is an international research project aiming at improving the understanding of the Gender Pension Gap. It adopts a multi-disciplinary approach using standard simulation of typical cases, dynamic microsimulation and social psychological research.
Research questions addressed:
- How do childcare and caring for older adults affect pension outcomes?
o Is the impact of childcare different than that of older adults' care?
o Which lessons can be learnt from other countries?
- How will the gender pension gap develop over the next 30 years?
o How will narrowing gender differences in employment rates and in wages during the last decades affect the future pension incomes?
- How to communicate effectively on issues related to pension income?
o How are women and men's expected pension benefits related to their expectations about their life circumstances after retirement and the relation with their labour market decisions?
o How can the framing of communication about the impact of labour market decisions on future pension outcomes affect a person's evaluations of these decisions?

Research design:
- Dynamic and static microsimulation to assess the impact of different life events on pension income
- Survey data to gain social psychological insights

Funding:
MIGAPE is co-funded by the Rights, Equality and Citizenship Programme of the European Union (2014-2020) via Grant Agreement no. 820798.
Further information: www.migape.eu

Project Results:

Relevance to Liechtenstein

As part of the "MIGAPE" research project, a detailed simulation model was created for the Liechtenstein pension system (first and second pillar pension). This model was used to analyze for the first time the impact of career breaks, the care of children and dependents, unemployment and divorce on the pension income of Liechtenstein citizens.
The research process was designed to be open and numerous Liechtenstein stakeholders (government and official agencies, NGOs, foundations, political parties and associations) were involved in the research process and Liechtenstein-specific questions were developed and answered.

Scientific, Economic and Societal Impact

Within the framework of this European research project, detailed microsimulation models for different pension systems were developed and analyzed. In addition, the project investigated how effective communication about aspects of individual pension planning should be designed.
The findings from the project are relevant for economy because they show how different pension systems and components of pension systems work. In addition, the social psychological research approach provides insights into how effective and targeted communication of pension-related aspects can be successfully designed.
Stakeholder involvement was built into the project design from the outset. By actively involving a broad stakeholder group, Liechtenstein-specific research questions were developed and answered. Thus, this project has contributed to the transfer of knowledge between science and society.
The stakeholder group at EU level, consisting of the OECD, European Commission, DG EMPL, European Commission, DG JUST, AGE Platform and the European Institute for Gender Equality (EIGE) fostered the societal impact at the international level.
Academic validation of research content will take place via conference presentations and academic publications.

Participating Institutions

Center for Economics / Partner

Project Participants

Employee
Kara Theresa Thierbach MSc
- Project Collaborator
Project Collaborator
Employee
Kara Theresa Thierbach MSc
- Contributor
Contributor
Employee
Dr. Tanja Kirn
- Project Manager
Head - Center for Economics Assistant Professor - Liechtenstein Business School
Project Manager
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Employee
Kara Theresa Thierbach MSc
- Project Collaborator
Project Collaborator
Employee
Kara Theresa Thierbach MSc
- Project Collaborator
Project Collaborator
Employee
Kara Theresa Thierbach MSc
- Contributor
Contributor
Employee
Kara Theresa Thierbach MSc
- Project Collaborator
Project Collaborator
Employee
Nicolas Baumann BSc
- Project Collaborator
Project Collaborator

Publications

MIGAPE

June 2021 until August 2021 (completed) FFF-Funding Project

Project Description

On average, women receive a lower pension than men. This is known as the Gender Pension Gap. MIGAPE (2019-2021) is an international research project aiming at improving the understanding of the Gender Pension Gap. It adopts a multi-disciplinary approach using standard simulation of typical cases, dynamic microsimulation and social psychological research.
Research questions addressed:
- How do childcare and caring for older adults affect pension outcomes?
o Is the impact of childcare different than that of older adults' care?
o Which lessons can be learnt from other countries?
- How will the gender pension gap develop over the next 30 years?
o How will narrowing gender differences in employment rates and in wages during the last decades affect the future pension incomes?
- How to communicate effectively on issues related to pension income?
o How are women and men's expected pension benefits related to their expectations about their life circumstances after retirement and the relation with their labour market decisions?
o How can the framing of communication about the impact of labour market decisions on future pension outcomes affect a person's evaluations of these decisions?

Research design:
- Dynamic and static microsimulation to assess the impact of different life events on pension income
- Survey data to gain social psychological insights

Funding:
MIGAPE is co-funded by the Rights, Equality and Citizenship Programme of the European Union (2014-2020) via Grant Agreement no. 820798.
Further information: www.migape.eu

Project Results:

Relevance to Liechtenstein

As part of the "MIGAPE" research project, a detailed simulation model was created for the Liechtenstein pension system (first and second pillar pension). This model was used to analyze for the first time the impact of career breaks, the care of children and dependents, unemployment and divorce on the pension income of Liechtenstein citizens.
The research process was designed to be open and numerous Liechtenstein stakeholders (government and official agencies, NGOs, foundations, political parties and associations) were involved in the research process and Liechtenstein-specific questions were developed and answered.

Scientific, Economic and Societal Impact

Within the framework of this European research project, detailed microsimulation models for different pension systems were developed and analyzed. In addition, the project investigated how effective communication about aspects of individual pension planning should be designed.
The findings from the project are relevant for economy because they show how different pension systems and components of pension systems work. In addition, the social psychological research approach provides insights into how effective and targeted communication of pension-related aspects can be successfully designed.
Stakeholder involvement was built into the project design from the outset. By actively involving a broad stakeholder group, Liechtenstein-specific research questions were developed and answered. Thus, this project has contributed to the transfer of knowledge between science and society.
The stakeholder group at EU level, consisting of the OECD, European Commission, DG EMPL, European Commission, DG JUST, AGE Platform and the European Institute for Gender Equality (EIGE) fostered the societal impact at the international level.
Academic validation of research content will take place via conference presentations and academic publications.

Project Participants

Employee
Dr. Tanja Kirn
- Project Manager
Head - Center for Economics Assistant Professor - Liechtenstein Business School
Project Manager
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Employee
Nicolas Baumann BSc
- Project Collaborator
Project Collaborator

Publications

Managemet Methods for the Measurement and Enhancement of Experts' Productivity

May 2008 until October 2009 (completed) Internal Project

Project Description

A growing number of employees in the OECD countries are no longer involved in generating defined results by means of defined operations, but they have to solve more or less complex area-specific problems. Different inquiries in the fields of their job profiles, their necessary qualifications, and their competence levels are suggestive of this ongoing change. We call employees doing such jobs requiring area-specific knowledge "experts".

The following challenges for the management of these experts arise - since it is evident that traditional management approaches, according to whom the results, operations, and resources are planed and controlled by "dispositive factors" and are carried out by the factor "operative work", no longer fits by implication to this new kind of employee.
1. Up to now it is largely unexplained where the actual management challenges are. Sociological findings refer to tensions between the professionals and bureaucratic organization, however, economic ones gear to the problem of identification, assessment, improvement and diffusion of knowledge. It's noticeable how sparsely the different academic disciplines take care of their reciprocal findings.
2. Which correcting means are after all available for managers of experts?
3. And finally, the efficacy of such correcting means has to be assessed

Keywords

Knowledge Management Controlling Knowledge management and organisational learning Leadership, motivation and incentive schemes Human Resources

Participating Institutions

Chair in International Management / Project Lead
Fachhochschule Vorarlberg / Partner
Geschäftsstelle der Internationalen Bodensee-Hochschule / Sponsor

Project Participants

Employee
PD Dr. habil. Stefan Güldenberg
- Principal Investigator
Principal Investigator

Publications

Messung von Erwerbs- und Arbeitslosigkeit im internationalen Vergleich: Liechtenstein und seine Nachbarländer

January 2005 until June 2005 (completed) Internal Project

Project Description

Die Begriffe Arbeitslosigkeit und Erwerbslosigkeit werden im deutschen Sprachraum nicht synonym verwendet. Die Arbeitslosenquote errechnet sich anhand der registrierten Arbeitslosen, die international teilweise erheblich unterschiedlich abgegrenzt sind. International vergleichbar sind nur die Erwerbslosenquoten auf der Basis der Richtlinien der Internationalen Arbeitsorganisation (ILO) und des Labour-Force-Konzepts (LFK). Eurostat wendet das LFK an und publiziert für alle Mitgliedsländer der Europäischen Union harmonisierte Erwerbslosenquoten. Auch die OECD benutzt dieses Konzept. Soweit vorhanden, übernimmt sie die Zahlen von Eurostat. Die vom Amt für Volkswirtschaft publizierte Arbeitslosenquote für Liechtenstein ist international weder mit den Erwerbslosen- noch mit den nationalen Arbeitslosenquoten vergleichbar. Dies liegt vor allem daran, dass in Liechtenstein die nationale Arbeitslosenquote nach dem Inlandsprinzip ermittelt wird. Sowohl im Rahmen des LFK als auch bei der Berechnung der nationalen Arbeitslosenquoten findet international jedoch das Inländerprinzip Anwendung. Der Beitrag enthält mehrere Vorschläge zur Modifikation der Berichterstattung zum Arbeitsmarkt in Liechtenstein.

Keywords

Economic research

Participating Institutions

Affiliate institute: KOFL Liechtenstein Economic Institute / Project Lead

Project Participants

Employee
Prof. Dr. Carsten-Henning Schlag
- Principal Investigator
Principal Investigator

Messen und Fördern der Informationskompetenz von Digital Natives in der Bodenseeregion

June 2016 until June 2018 (completed) IBH-Funding Project

Project Description

Die Bedeutung der Transformation von Gesellschaften zu digitalen Gesellschaften ist allgegenwärtig geworden. Für die Wettbewerbsfähigkeit von Städten, Regionen und Ländern ist es zukünftig entscheidend, inwiefern diese die Wandlung zu digitalen Gesellschaften effizient und wirksam vollziehen und sich im digitalen Binnenmarkt positionieren können. Eine wichtige Grundlage dazu ist die Entwicklung von Informationskompetenz (IK), d.h. der kompetente und effiziente Umgang mit digitaler Information, insbesondere bei den heranwachsenden Generationen der Digital Natives. Um IK schon im frühen Alter aufzubauen, wird deren Förderung verstärkt als Aufgabe und Ziel von Schulen gesehen. Die flächendeckende Einführung von IK in Schulen konnte bis jetzt jedoch nicht erreicht werden.

Der vorliegende Projektantrag greift diese Forschungslücke auf und hat zum Ziel, Informationskompetenz in der Sekundarstufe II der Bodenseeregion zu messen, durch den Einsatz eines MOOC zu fördern und zwischen den Ländern zu vergleichen.

Participating Institutions

Hilti Chair of Business Process Management / Partner

Project Participants

Employee
Dr. Sonia Lippe-Dada MScIS
- Project Manager
Project Manager
Employee
Dr. rer. oec. Charlotte Wehking
- Project Collaborator
Project Collaborator
Employee
Dr. Bernd Schenk
- Project Collaborator
Senior Lecturer - Liechtenstein Business School Academic Director BSc in Business Administration - Liechtenstein Business School
Project Collaborator
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Mergers and Acquisitions by Large Financial Investors in Germany, Austria and Switzerland

September 2007 until March 2008 (completed) KTT

Project Description

In this empirical project, we present empirical evidence on the gains and losses to target firm shareholders, focusing our analysis on the value effects from M&A transactions by financial investors. The main objective is whether M&A transactions by financial investors have a significant impact on the value of their target companies and if these value effects differ systematically from the value effects of target companies acquired by industrial companies. To conclude we can underline that from the perspective of the capital market - this is equivalent to shareholders of the target company - an M&A transaction of a financial investor is equivalently valued as an M&A transaction by an operating firm. This is an important result which should be taken into consideration by economic policy makers and regulators.

Participating Institutions

Chair in Business Administration, Banking and Financial Management / Project Lead

Project Participants

Employee
Prof. em. Dr. Marco J. Menichetti
- Principal Investigator
Professor Emeritus - Liechtenstein Business School
Principal Investigator
Dr. Marcel Vaschauner MBA
- Project Collaborator
Project Collaborator

Human and Artificial Intelligence Systems - Transfer of Knowledge

September 2018 until June 2022 (completed) PhD-Thesis

Project Description

The dissertation aims to investigate the knowledge transfer between humans and artificial intelligence systems. As machine learning becomes the primary driver of these systems, the need to comprehend and transfer knowledge acquired by machines increases. The main research interest is on approaches, strategies, and methods to render machine-made decisions comprehensible to humans, i.e. "What the machine has learned, such that it makes particular decisions?". Another area of interest that within the scope of this project is the machines' learning phase. This part is approached as the challenge of transferring knowledge into machines, i.e. "What did the machine see during its learning phase, such that it learned particular concepts?". This dissertation draws primarily on researches in three main areas: machine learning, information visualization, and knowledge transfer. They are intended to provide the author with the following know-hows on: getting information in and out from the artificial intelligence, conveying the extracted information to human users, and conceptualizing a sound framework of transferring knowledge, respectively.

Keywords

Knowledge Transfer Machine Learning Artificial Intelligence

Participating Institutions

Hilti Chair of Business Process Management / Doctoral instiution

Project Participants

Employee
Dr. rer. oec. Joshua Peter Handali M.Sc.
- PhD-Student
PhD-Student
Employee
Prof. Dr. Jan vom Brocke
- Supervisor
Visiting Professor - Information Systems and Process Science
Supervisor
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Prof. Dr. Michalis Vlachos
- Co-Supervisor
Co-Supervisor

Human and Artificial Intelligence Systems - Transfer of Knowledge

September 2018 (completed) Preproposal PhD-Thesis

Project Description

The dissertation aims to investigate the knowledge transfer between humans and artificial intelligence systems. As machine learning becomes the primary driver of these systems, the need to comprehend and transfer knowledge acquired by machines increases. The main research interest is on approaches, strategies, and methods to render machine-made decisions comprehensible to humans, i.e. "What the machine has learned, such that it makes particular decisions?". Another area of interest that within the scope of this project is the machines' learning phase. This part is approached as the challenge of transferring knowledge into machines, i.e. "What did the machine see during its learning phase, such that it learned particular concepts?". This dissertation draws primarily on researches in three main areas: machine learning, information visualization, and knowledge transfer. They are intended to provide the author with the following know-hows on: getting information in and out from the artificial intelligence, conveying the extracted information to human users, and conceptualizing a sound framework of transferring knowledge, respectively.

Keywords

Knowledge Transfer Machine Learning Artificial Intelligence

Project Participants

Employee
Dr. rer. oec. Joshua Peter Handali M.Sc.
- PhD-Student
PhD-Student
Employee
Prof. Dr. Jan vom Brocke
- Supervisor
Visiting Professor - Information Systems and Process Science
Supervisor
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Bringing more process-oriented thinking to a complex process landscape

since September 2023 Preproposal PhD-Thesis

Project Description

The proposed research study is done in close collaboration with Hilti AG and aims to address the unique challenge of bringing process-oriented thinking to a large, cross-functional department with a diverse process landscape by adopting a streamlined approach to process management.

Cross-functional departments contribute to the overarching strategic objectives of an organization's strategy, but all have different needs & contexts in which they function. This is based on the nature of their competencies & contributions to the overall strategy. Due to missing standardization in all the existing processes across functions, traditional business process management is difficult to implement as those principles are not applicable in all departments. Instead, it requires a context sensitive approach to manage & optimize processes & workflows.

This research project aims to improve efficiency by bringing process management into the teams to enable them to successfully & effectively manage their processes. The research objectives focus on developing a process-oriented framework, evaluating its effectiveness, & providing practical recommendations for implementation. The methodology follows a deeply grounded Design Science Research (DSR) approach which involves a combination of gathered qualitative & quantitative data followed by thorough analysis & the development of a tailored framework.

The research findings will offer valuable insights & actionable recommendations to better manage processes for the industry while also generating more empirical data and insights to advance academia.

Project Participants

Employee
Nina Bulling
- PhD-Student
PhD-Student
Employee
Prof. Dr. Jan vom Brocke
- Supervisor
Visiting Professor - Information Systems and Process Science
Supervisor
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