Teaching

Termine (Winter 2024-2025)

Vorlesung

• Lehrender: Prof. Dr. Uwe CantnerExternal link und Lukas Dreier
• Zeit: Montag, 10:15 - 11:45
• Ort:  HS 3

Übungen

• Gruppe 2
  • Lukas Dreier
  • Montag, 16:15 - 17:45, HS 4
• Gruppe 1
  • Tobias HädrichExternal link
  • Dienstag, 12:15 - 13:45,  HS 3

Tutorien

• Gruppe 1
  
  • Adrian Platz
  • Mo., 08 - 10 Uhr, Carl-Zeiss-Str. 3, SR 206
• Gruppe 2
  
  • Adrian Platz
  • Di., 16 - 18 Uhr, Carl-Zeiss-Str. 3, SR 314
• Gruppe 3
  
  • Anna Beer
  • Mi., 14 - 16 Uhr, Carl-Zeiss-Str. 3, SR 316
• Gruppe 4
  • Anna Beer
  • Fr., 08 - 10 Uhr, Carl-Zeiss-Str. 3, SR 207

Beschreibung

Die Veranstaltung Mikroökonomik befasst sich zunächst mit der Analyse der ökonomischen Entscheidungen von Unternehmen und Konsumenten. Hierzu zählen auf Seite der Unternehmen beispielsweise die Frage nach welchen Kriterien diese die Preise für ihre Güter festsetzen, welche Gütermenge sie produzieren und welche Produktionsfaktoren sie dafür einsetzen, mit welcher Marktmacht und mit welchen Strategien sie gegenüber ihren Konkurrenten und gegenüber Konsumenten auftreten. Auf der Seite der Konsumenten oder Haushalte interessiert, wie diese ihr Einkommen für konsumptive Zwecke einsetzen, wie sie ihre Arbeitskraft auf dem Arbeitsmarkt anbieten und ihre Ersparnisse auf dem Kapitalmarkt anlegen. Im Rahmen der Wohlfahrtstheorie erfolgt eine Bewertung der Markergebnisse und eine Analyse von Marktversagenstatbeständen. Neuere Entwicklungen aus der Netzwerk- und der Innovationsökonomik runden die Veranstaltung ab.

Gliederung der Vorlesung

1. Einführung
2. Produktionstheorie
3. Haushaltstheorie
4. Markt- und Preistheorie
5. Wohlfahrtstheorie
6. Neuere Entwicklungen

Literaturhinweise

• Varian H., Grundzüge der Mikroökonomik, 8. Auflage, Oldenbourg 2011.
• Bergstrom T.C., H. Varian, Übungsbuch zu Varian, Grundzüge der Mikroökonomik, 8. Auflage, Oldenbourg 2011.
• Hanusch H., T. Kuhn, U. Cantner, Volkswirtschaftslehre 1, 6. Auflage, Springer 2002 (Kapitel 1-4, in Teilen Kapitel 5).
• Dörsam P., Mathematik - anschaulich dargestellt - für Studierende der Wirtschaftswissenschaften, 15. Auflage, PD-Verlag 2010.
• Chiang A.C., K. Wainwright, H. Nitsch, Mathematik für Ökonomen - Grundlagen, Methoden und Anwendungen, Vahlen 2011.

Klausur

Klausur: Di., 18.02.2025, 08 - 10 Uhr, HS 1 + HS 2

Die regelmäßige Teilnahme an der Vorlesung sowie an den Übungen und vertiefenden Tutorien wird dringend empfohlen!

Termine (Sommer 2024)

Vorlesung

• Lehrender: Dr. Nils GrashofExternal link
• Zeit: Montag, 12:15 - 13:45
• Ort: SR 206

Übung

• Lehrender: Tobias HädrichExternal link
• Zeit: Donnerstag, 12:15 - 13:45
• Ort: HS 9

Beschreibung

Die Vorlesung führt in die Grundprobleme innovationsökonomischer Fragestellungen und Analysen ein. Zu diesem Zweck wird einerseits ein Überblick in das Schwerpunktfach Innovationsökonomik vermittelt, andererseits werden bereits erste Lösungsansätze und Analyseverfahren vorgestellt. Die Produktion von technologischem Wissen und dessen ökonomische Nutzung, die damit verbundenen unternehmerischen Entscheidungen und die Determinanten des Innovationserfolgs, die sich daraus ergebenden Effekte auf die Unternehmens- und Branchenentwicklung sowie auf die Entwicklung von Volkswirtschaften insgesamt werden sowohl theoretisch fundiert als auch anhand von empirischen Analysen und Fallstudien verständlich gemacht.

Gliederung der Vorlesung

Teil I: Einführung
1. Innovationsökonomik als ökonomische Disziplin
2. Wissenschaftsrevolution, industrielle Revolution(en) und technologische Entwicklung

Teil II: Grundbegriffe
3. Grundbegriffe: Das WAS, WIE, WER, FÜR WEN der Innovationsökonomik
4. Technologieindikatoren und deren Aussagekraft

Teil III: Theorie
5. Anreizbasierte (optimierende) Innovationstätigkeit
6. Know-how-basierte Innovationstätigkeit
7. Wachstum, technologischer Fortschritt und Spillovers

Teil IV: Politik
8. Grundbegriffe und Bedeutung der Technologiepolitik

Teil V: Innovationsökonomik als wissenschaftliche Disziplin
9. Theoretische Konzeptionen und Analytik in der Innovationsökonomik

Literaturhinweise

Vorlesungsbegleitende Literatur wird in der Veranstaltung bekannt gegeben.

Klausur

Mo., 08.07.2024, 14 - 16 Uhr, HS 3

Wiederholungsklausur

Di., 29.10.2024, 18:00 - 20 :00 Uhr, SR 114

Termine (Winter 2024/25)

Das Seminar BW20.3 - Mikroökonomik bzw.  das Seminar BW22.3 - Unternehmensentwicklung, Innovation und wirtschaftlicher Wandel werden auf Grund der Anmeldezahlen zusammengelegt (Lst. Cantner + Lst. Menter).

• Kick-off Veranstaltung am 17.10.2024 14-16 Uhr, Raum 4.157 (Besprechungszimmer des Lehrstuhls für Makroökonomik)
• Themenwünsche bis 25.10.2024
• Themenzuweisung bis 29.10.2024
• Informationsveranstaltung: Gestaltung Präsentation & Korreferat: Do. 12.12.2024 14-16 Uhr
• Abgaben:
  • Kurzbeschreibung, Gliederung und Literatur bis spätestens: Fr. 15.11.2024
    →  Besprechung mit Betreuer
  • Vollständige Entwurfsfassung (ohne Matrikelnummer): Mo. 16.12.2024
  • Überarbeitete finale Fassung: Fr. 31.01.2025
  • Umfang: ca. 4500 – 5000 Wörter ~ 15 Seiten (insgesamt)
• Präsentation – Blockseminar: Fr. 17.01.2025 8-16 Uhr

Beschreibung

Das Seminar wird jedes Wintersemester angeboten und richtet sich an Studierende im Bachelor. Es werden wechselnde Themen aus dem Bereich Mikroökonomik, Industrieökonomik und Innovationsökonomik angeboten. Hierbei werden aktuelle Forschungsfragen und -problemstellungen in den jeweiligen Gebieten bearbeitet und eine Einordnung in die Literatur vorgenommen. Vorkenntnisse aus dem Basismodul Mikroökonomik bzw. dem Vertiefungsmodul Innovationsökonomik sind empfehlenswert.

Die Gesamtnote setzt sich folgendermaßen zusammen:

• Bewertung der schriftlichen Seminararbeit (40%)
• Bewertung der mündlichen Präsentation (30%)
• Korreferat zu einer Arbeit der anderen Teilnehmer (20%)
• Mündliche Beteiligung an der Diskussion während des Seminars (10%)

Bitte befolgen Sie unsere allgemeinen Hinweise zum wissenschaftlichen Arbeitenpdf, 154 kb · de.

Voraussetzungen

• Mindestens eine Vorlesung des Lehrstuhls

Anmeldung

• Zentrale Anmeldung, siehe http://www.wiwiss.uni-jena.de/Studium/Seminaranmeldung.htmlExternal link
• Die Seminarplatzvergabe erfolgt am Ende des Sommersemesters.
• Im Anschluss an die Platzvergabe findet ein Kick-off Treffen mit Hinweisen zur Bearbeitung statt. Die Bearbeitung erfolgt selbständig in Absprache mit der Betreuerin oder dem Betreuer während der vorlesungsfreien Zeit. Die Arbeiten werden im Rahmen eines Blockseminars vorgetragen und diskutiert.

Seminararbeit

• Die Arbeit wird per email im PDF Format ohne Adresse oder Matrikelnummer an das Lehrstuhlsekretariat geschickt bzw. bei Moodle eingereicht.

Dates (Winter 2024-25)

• Lecture
  • apl. Prof. Dr. Holger GrafExternal link
  • Tue, 14:15 - 15:45 , Carl-Zeiss-Str. 3, HS 5
• Exercise
  • apl. Prof. Dr. Holger Graf
  • Thu, , 10:15 - 11:45, Carl-Zeiss-Str. 3, HS 7, starts at 24th October 2024
• Exam:
  • Midterm: tba
  • Final: Tue, March 4, 2025, time and room tba
  • Retake: tba

Description

The course Advanced Microeconomics extends the basic ideas and concepts from the course Microeconomics (BW 20.1). It introduces the students to the strategic interaction in oligopoly markets by imparting the relevant theoretical considerations and models. In the context of the information economics, the students will become familiar with the problems of asymmetric information for agents in the market and how these are analyzed.

Outline

Part 1: Strategic interaction and theory of oligopoly

1. Introduction
2. Oligopoly competition with homogenous goods
3. Oligopoly competition with heterogeneous goods
4. Cartels
5. Research & development

Part 2: Decisions under uncertainty and asymmetric information

6. Decisions under uncertainty
7. Principal-Agent Theory

Literature

• Part I:
  Church, J., Ware, R., Industrial Organization, Boston: McGraw-Hill, 2000.
  Shy, O., Industrial Organization, Cambridge (Mass.): MIT Press, 1995.
  Tirole, J., The Theory of Industrial Organization, Cambridge (Mass.): MIT Press, 1988.

• Part II:
  Varian H., Microeconomic Analysis, 3rd edition, Norton & Company, 1992.
  Macho-Stadler, I., D. Pérez-Castrillo, An Introduction to the Economics of Information, Oxford: Oxford University Press, 2001.

Exam

The examination consists of two written tests. There will be a

• 45-minute midterm exam in December and a
• 60-minute final exam

The midterm exam accounts for 30% of the final grade and has to be passed. In case of failure, there will be a retake opportunity for the midterm exam in January.

Dates (Summer 2024)

• Lecture,Exercise
  • Prof. Dr. Uwe CantnerExternal link
  • Wednesday, 8:15 - 9:45,
• Exercise
  • Lukas DreierExternal link
  • Thursday, 14:15 - 15:45, SR 128
• Exam: Mon., 8th July 2024, 14 - 16 pm, HS 3

Description

The course deals with the methodological foundations and the application of various methods of productivity and efficiency measurement. Based on theoretical and pragmatical considerations concerning the evaluation of production, index numbers, stochastic frontier analysis and data envelopment analysis are introduced and explained as to perform the evaluation. Differences in productivity are decomposed into the various components of efficiency such as pure technical efficiency, scale efficiency, and allocative efficiency. Therefore, decomposition formulae and the Malmquist index are introduced to identify the source of those various causes. All provided methods are applied to real-world data sets and problems by using freely available software packages.

Structure

1. Introduction into the analysis of production decisions
2. Frontier function analysis with constant returns to scale - the productivity form
3. Frontier function analysis with constant returns to scale - the envelopment form
4. Frontier function analysis with variable returns to scale
5. Input versus output orientation
6. Extensions (slacks, allocative efficiency, super efficiency)

Literature

• Bogetoft, P., Otto, L. (2011), Benchmarking with DEA, SFA, and R, New York: Springer.
• Cantner U., H. Hanusch, Effizienzanalyse mit Hilfe der Data Envelopment Analysis, WiSt 27, 1998, S. 228-237.
• Cantner, U., Krüger, J., Hanusch, H. (2007), Produktivitäts- und Effizienzanalyse - Der nichtparametrische Ansatz, Berlin u.a.: Springer Verlag.
• Coelli T., D.S.P. Rao, G.E. Battese, An Introduction to Efficiency and Productivity Analysis, Boston: Kluwer, 1998.
• Cooper, W.W., Seiford, L.M., Tone, K. (2000), Data Envelopment Analysis: A Comprehensive Text with Models, Applications, References and DEA-Solver Software, Boston: Kluwer.
• Grosskopf, S. (1993), Efficiency and Productivity, in: H.O. Fried, C.A.K. Lovell, S.S. Schmidt (Hrsg.), The Measurement of Productive Efficiency, Oxford: Oxford University Press, S. 160-194.

Software

In the lecture and in the tutorials, the software EMS (Efficiency Measurement System)External link will be used to solve the problem of linear optimization.  The software is only available for Windows (please note that you need admin rights), but students can use WineExternal link to run the software on Linux and OS X.

Examination

There will be a 60-minute exam at the end of the course

Participation in the weekly exercise is highly recommended.

Dates (Winter 2024-25)

• Lecture
  • Prof. Dr. Uwe Cantner
  • Wed., 08:15 - 09:45, Carl-Zeiss-Str. 3, HS 7
• Exercise
  • Lukas Dreier
  • Mon, 12:15 - 13:45, Carl-Zeiss-Str. 3, HS 7, starts at 21st October 2024
• Exam:
  • Midterm exam: tba
  • Retake midterm exam:tba
  • Final: Wed., February 26, 2025, 10:00 - 12:00, HS 3
  • Retake: tba

Course Description

The course provides an introduction to the Economics of Innovation.

Part I will introduce the fundamental theoretical building blocks to be used in the following developments of the course.

Part II will discuss some prevailing models in the field of Industrial Organization dedicated to the analysis of the incentives and constraints to innovative activities (R&D expenditures) as well their relation with imitation, spillovers, firm size and market structure.

Part III will adopt a more dynamic and knowledge-based view, introducing models involving the direct generation of new knowledge, the catching-up/falling behind dynamics of competition and, briefly, the role played by market selection between innovative firms.

Part IV will be dedicated to technological competition (the dominance of one technological option when several alternatives exist) in the presence of network externalities.

Course Outline

Part I: Basics in the Economics of Innovation

Part II: Incentive based approach

1. Optimal design of research and development projects
2. Non-Tournament models
3. Tournament models (Patent races)
4. Neo-Schumpeter Hypotheses

Part III: Knowledge-based approach

1. Rationality, bounded rationality and the theory of the firm
2. Innovation and knowledge races
3. Selective Competition

Part IV: Competing technologies and network externalities

Literature

Readings are not compulsory, but they will improve your preparation and extend your knowledge of the topics.

Introduction / Part I

• Mokyr, J. (2010). The contribution of economic history to the study of innovation and technical change: 1750-1914. Handbook of the Economics of Innovation, 1, 11-50.
• Arthur, W. B. (2007). The structure of invention. Research Policy, 36(2), 274-287.
• Fagerberg, J., Mowery, D. C., & Nelson, R. R. (2006). The Oxford handbook of innovation. [Just the contribution by Fagerberg]

Part II

• Dasgupta, P. & Stiglitz, J. E., Industrial Structure and the Nature of Innovative Activity, Economic Journal 90, 1980, 266-93;
• Arrow K. J. (1962), Economic Welfare and the Allocation of Resources to Invention, in R.R. Nelson (ed.), The Rate and Direction of Economic Activity, Princeton University Press, N.Y., 609-626
• (further reading for interested students) The Rate and Direction of Inventive Activity: Economic and Social Factors (NBER Book), 1962: downloadable at http://papers.nber.org/books/univ62-1External link
• Other relevant papers will be suggested during the course.

Part III

• Cohen W. M. & Levinthal, D. A., Innovation and Learning: The Two Faces of R&D, The Economic Journal 99 (397), 1989, 569-596; (see the downloads at the end of the page)
• For the Knowledge Race (Gap Model), see Chapter 5 of Verspagen (1993) here www.merit.unu.edu/training/theses/thesisBV.pdfExternal link
• Other relevant papers will be suggested during the course.

Exam

• Midterm exam (30% of the final mark)
• Final exam on the whole course program (70% of the final mark)

Dates (Summer 2024)

• Lecture
  
  • Manuel RomagnoliExternal link
  • Thursday, 08:15 - 09:45 am, SR 221
• Exercise
  
  • Manuel RomagnoliExternal link
  • Friday, 12:15 - 13:45 pm, SR 221
• Exam: Mon., 29th July 2024, 12 - 14 pm, SR 114

Course Description

Are there 'natural laws' behind how firms behave, compete, and change over time? What about the industries to which they belong? In this course, we uncover the foundations of what are called 'Industrial Dynamics': the dynamic patterns of behavior and performance of industrial sectors that are subject to and engage in innovative activities.

The course will guide you through the basic determinants of industry evolution. We will start by identifying some regularities (or stylized facts) derived from empirical evidence and learn how to capture the turbulent or stable nature of industries using some techniques fit for purpose. Other topics covered in the course are the theory and empirics of market selection, the patterns emerging from the evolution of industries in time, the formation of spinoffs, and the classification of industries according to some key characteristics.

At the end of the course, you will be able to understand the fundamental drivers of industrial change and differences, as well as their importance in informing policy design and firm strategy.  

Course Outline

1. A recap of basic concepts
2. Stylized facts: the regularities of industries' evolution
3. Measuring turbulence and stability in innovative and economic performance
4. Selection and competition in markets and value chains: theory and empirical tests
5. Putting some structure over firms' heterogeneity: sectoral systems of innovation, technological regimes, and the Pavitt Taxonomy
6. Industries changing in time: the theory of Industry Life Cycles (ILC)
7. Spinoffs dynamics

Literature

Each section of the course has

• an essential reading, whose study is required to pass the final exam
• one or more optional readings, useful to expand the knowledge on each topic covered

The reading list will be distributed at the start of the course.

Students seeking an introduction to the topic (especially to points 6 and 7 of the outline) can refer to the following books:

• Geroski, P. (2003). The evolution of new markets. Oxford University Press.
• Klepper, S. (2015). Experimental capitalism: the nanoeconomics of American high-tech industries. Princeton University Press.

Exam

100% written assessment (details will be provided at the beginning of the course)

 

 

Dates (Winter 2024-25)

• Lecture
  •  Dr. Nils GrashofExternal link
  • Tue, 10:15 - 11:45, Carl-Zeiss-Str. 3, SR 274
• Exercise
  • Dr. Nils GrashofExternal link
  • Thu, 08:15 - 09:45, Carl-Zeiss-Str. 3, SR 306
• Exam:
  • The course examination will consist of two parts: Students have to give a presentation on a recent paper for one of the three topics of the course.
  • The second part is the final exam on: Wed., February 19, 2025, 10:00 - 12:00, SR 113
  • Retake: TBA

Course Description

The course provides an introduction to three different topics: Regional Innovation Networks, Innovation and Sustainability and Digital Transformation and Employment. All three topics highlight the process of structural change occurring in the economic system and adopt as well focus on dynamics rather than on a static representation of economic phenomena.

Regional Innovation Networks will illustrate how innovative activities are usually undertaken in a collective/cooperative way, and it will analyze the conditions for knowledge flows (spillovers) between agents, as well as the role of network structure in affecting both innovative activities and economic performances.

Innovation and Sustainability focusses on how innovative activity for environmentally friendly technologies differs from 'standard' technologies and the respective disadvantages of such technologies. Special emphasis is given to the policy measures that can be implemented to overcome such disadvantages.  

Digital Transformation and Employment discusses how new, especially digital technologies influence skills and wages. We will discuss theoretically how polarization phenomena emerge and look at their empirical basis. Lastly, we turn to the future of employment and the role of AI. 

During the sessions, students will present and discuss state-of-the-art papers on the three topics.

Course Outline

1. Collective Innovation and Innovation Systems
   • Collective Innovation - geographical dimensions
   • Innovation Networks: Concept and pattern
   • Innovation Networks: Structures and Performance
   • Innovation Networks: Change and Dynamics
2. Innovation and Sustainability
   • Innovation and the environment
   • The multiple externalities problem 
   • Carbon lock-in
   • Technological transition
   • Policy instruments and mixes
3. Digital Transformation and Employment
   
   • Innovation, Digital Transformation and Economic Growth
   • Skill-Biased Technical Change
   • Task-Biased Technical Change
   • Empirical evidence
   • Future of employment

Literature

Additional relevant papers will be suggested during the course, see the moodle course.

Exam

The final grade is composed of an in-class presentation (50%) and a written research proposal (50%).

Dates (Summer 2024)

• Lecture, Exercise
  • PD Dr. Holger GrafExternal link
  • Tuesday, 10:15 - 11:45, SR 224
  • Thursday, 12:15 - 13:45, SR 114
• Exam: Wed., 31st July 2024, 10 - 12 o'clock, SR 113
  
  

Course Description

This course is about the normative aspects of technological and innovative change, i.e. we derive implications for policy from theoretical arguments or models concerned with technological change. We will discuss topics such as the characterization of knowledge, the process of generating innovations, innovation systems, R&D subsidies, R&D cooperations, policies concerning patenting and standardization, the diffusion of innovations, or the interplay between innovation and the environment.

Outline

1. Introduction and core concepts
2. Rationales for government intervention
3. Forms of innovation policies
4. The evolution of policy styles

The course is divided into two parts. The first half is devoted to the lecture, in the second half, there will be student presentations on assigned articles on innovation policies and their evaluation.

Exam

Presentation of assigned topic and overall participation (50%), two online exams (25% each).

Retake exam

Tue., October 22, 2024, time and room tba

Dates (Winter term 2024/25)

• Kick-off: Wed., 31.07.2024, 14 - 16 pm
• Paper submission: Fr., 1 November, 2024
• Presentations: end of November/early December 2024

Course Description

This seminar is provided every semester and is intended for master students. The topics of the seminar deal with the economics of innovation and microeconomic theory, so prior knowledge from other courses of the chair that introduce the basic concepts and literature that constitutes these research areas is recommended. In order to pass the seminar successfully, students must write a term paper (40% of overall performance), present this paper in the seminar (30%), discuss the term paper of a fellow student (20%) and participate in the discussion during the seminar (10%). We expect that students consider the chair's guidelines for the work on their term paper and participation during the seminar.

Requirements

• At least one course from the curriculum of the chair

Enrollment

• Centralized application process (link)

Term paper

• The term paper has to be submitted via e-mail as PDF without the student's address or enrollment number. For more details, see the guidelinespdf, 168 kb of the chair and the material that is distributed during and after the kick-off meeting.

Dates (Winter 2024-25)

• Lecture
  
  • apl. Prof. Dr. Holger GrafExternal link
  • Mon., 14:15 - 15:45, Carl-Zeiss-Str. 3, SR 214, 216 (PC-Pool)
• Exercise
  • apl. Prof. Dr. Holger Graf  / Hikaru Ota
  • Fri., 10:15 - 11:45, Carl-Zeiss-Str. 3, SR 216, 214 (PC-Pool), starts at 25th October 2024
•   details on MoodleExternal link

Course Description

R is a software environment for data analysis, statistical computing, and graphics and which is widely used in education, research, and business. This course aims to provide a hands-on introduction to R with a special focus on data handling, transformations, and visualization as a prerequisite for empirical analyses.

The course consists of a lecture part, exercises, and a student research project (group work). Intermediate tasks will also be assigned throughout the course.

Examination:       

• 50%: intermediate tasks
• 50%: research project

This seminar is provided every summer semester and is intended for master students with a strong interest in empirical analysis and with some knowledge of R statistical software (e.g., by passing the course Introduction to R). The application process is the same as for all seminars (link) and students receive credit for (MW 20.7).

Dates (Summer 2024)

• Kick-off: 7 March, 2024, 16:00-17:30, SR 209
• PD Dr. Holger GrafExternal link
• Friday, 10:15 - 11:45, SR 128
• Submission deadline for the first series of tasks: TBA

Course Description

Patents are a valuable source of information for innovation scholars. They are used to measure technological spillovers, innovation productivity, innovation networks, etc. The goal of this research seminar is to provide students with the basic tools of patent analysis, including information about patent databases, queries for patent selection, and data description. A special focus will be on the analysis of patent data, including citation analysis and social network analysis.

Structure

This is a weekly seminar where, in the first weeks, the theoretical and methodological foundations will be laid. We will use R statistical software for data handling and analysis. During the subsequent weeks, teams of students will develop research proposals, which will be conducted under the guidance of the lecturers during class. A final version of the research paper is to be submitted by the end of the lecture period. In the final two weeks, the research groups will present and discuss their research results.

Deliverables

• Tasks
• Research proposal
• Presentation
• Research paper (group work)

 

Anmeldung

Falls Sie sich für eine Bachelorarbeit an unserem Lehrstuhl interessieren, suchen Sie sich ein Thema aus den Bereichen Mikroökonomik oder Innovationsökonomik (Themenlistepdf, 76 kb · de), füllen Sie das Anmeldeformular pdf, 63 kb · deaus und schicken Sie es ans Lehrstuhlsekretariat.

Registrierung

Nachdem Sie mit Ihrer Betreuerin oder Ihrem Betreuer auf ein Thema geeinigt haben, erfolgt die Registrierung beim Prüfungsamt.

Anfertigen der Arbeit

Bitte befolgen Sie unsere Hinweise zum wissenschaftlichen Arbeitenpdf, 154 kb · de und nutzen Sie unsere Vorlagen für oder LaTeX. Wir empfehlen auch die Nutzung einer Literaturverwaltungssoftware, wie beispielsweise ZoteroExternal link, MendeleyExternal link, oder JabrefExternal link.

Abgabe

Bachelorarbeiten müssen in elektronischer Form (pdf) beim Prüfungsamt (constanze.herrmann@uni-jena.de), dem Lehrstuhlsekretariat (olga.gaessner@uni-jena.de) und Ihrer/m BetreuerIn abgegeben werden. Bei empirischen Arbeiten müssen zusätzlich die genutzten Daten und der Code abgegeben werden.

Select a (broad) topic

The first step to conducting a scientific research is to identify a broad topic. The topic should interest you, in order to provide the right motivation, and it should also be a research topic that works on the frontiers of knowledge. Furthermore, the topic should fall under the research expertise of the Chair. We suggest checking the study material of the Chair to identify one or more areas of research to be explored and/or extended within the thesis. Additionally, you may check the chair team personal web pages to get to know our specific research interests and ongoing projects.

After a broad research topic has been chosen, you should develop one or a set of research questions - the general trajectories that orient your search in the knowledge space. Research questions can be oriented to conceptual/theoretical or empirical analysis. There is no a priori preference between theoretical and empirical work, and the precise design of the research method for a thesis should be agreed upon with your supervisor.

Application

Once the potential thesis topic is thoughtfully considered, you may apply for supervision. Supervisors are assigned based on the topic proposed and on the availability of our team.

Fill this form to apply for a MASTER THESIS at the Microeconomics ChairExternal link.

Registration

After you have been accepted for writing a thesis at the Microeconomics Chair and a topic is agreed with their prospective supervisor, you can formally register with the Exam Office (Prüfungsamt) to start the thesis completion process. Information on this step can be found on the Prüfungsamt page on the Faculty website.

Writing

You should follow our guidelinespdf, 168 kb in completing their theses. We recommend using our templates for MS Word or LaTeX and a reference management software, such as ZoteroExternal link, MendeleyExternal link, or JabrefExternal link.

Submission

Master's theses have to be submitted as an electronic version (pdf) to the exam office (constanze.herrmann@uni-jena.de), to the chair secretary (olga.gaessner@uni-jena.de) and your supervisor. You also need to submit one printed copy (book/hardcopy binding and heat-binding are allowed – ring-binding is not allowed) to the exam office. Color print is not necessary. In case of an empirical thesis, you must also make all data and code available to your supervisor.

Presentation

For all Master's theses registered after 1 August 2024, there will be a presentation (defence) and discussion in front of the examiner and supervisor approximately 2-3 weeks after submission of the thesis. The defence lasts 40 minutes, including a 20-25 minute presentation and a 15-20 minute discussion.
  

Bachelor

• Hinweisepdf, 154 kb · de zum wissenschaftlichen Arbeiten
• Alle Seminar- und Abschlussarbeiten müssen eine unterschriebene "Eigenständigkeitserklärung" enthalten, die in ihrer aktuellen Fassung auf der Website des Prüfungsamtes zu finden ist. Diese Erklärung bezieht sich auf unsere "Freigabeerklärungpdf, 131 kb · de", in der die erlaubten Forschungsmittel und Dokumentationspflichten aufgeführt sind.

Master

• Guidelines (en)pdf, 168 kb for academic writing
• All seminar papers and final theses must include a signed "Declaration of Academic Integrity," the current version of which can be found on the Examinations Office website. This declaration refers to our "Declaration of Permitted Resourcespdf, 136 kb," which specifies the permitted research tools and documentation requirements.
  
  

MS Word

• Bachelorarbeit/Masterarbeit (de)docx, 44 kb · de
• Bachelor thesis/master thesis (en)docx, 49 kb

LaTeX

• Bachelorarbeit or Master's thesis (zipzip, 172 kb · de) - use this template if you have a local LaTeX installation.
• Overleaf templateExternal link - Overleaf is a cloud based LaTeX system. No local LaTeX installation is required, but you need to register on overleaf.com.
• For presentations with LaTeX, see https://www.overleaf.com/learn/latex/BeamerExternal link

If you plan to do an empirical master thesis, we can help you to find appropriate data.

• For firm level data, please check out the Orbis databaseExternal link, available on campus.
• If you want to work with patents, we have access to a variety of databases. Please consult Holger Graf.
• EU funding data (FP7) can be found hereExternal link.
• OECD Science, Technology and Industry e-OutlookExternal link, for country profiles and policies
• Worldbank Enterprise SurveysExternal link are conducted in 139 countries
• Penn World TableExternal link
• You can find datasets for various topics in public data repositories, such as the Harvard DataverseExternal link