Doctoral Programme

Course Description

• Sets in n-dim. Real Space and Their Properties
• Calculus of Several Variables
• Functions of Several Variables
• Implicit Functions and Their Derivatives
• Quadratic Forms and Definite Matrices
• Unconstrained Optimization
• Constrained Optimization
• Concave and Quasiconcave Functions
• Economic Applications
• Eigenvalues and Eigenvectors
• Advanced Linear Algebra
• Advanced Analysis
• Probability Theory
• Basic Statistics

Prerequisites

Undergraduate Calculus

Course Structure

• Linear algebra
• Calculus
• Optimization
• Statistics

Course Description

The course covers the following topics:

• Review of statistics
• The Single-Equation Linear Model and OLS Estimation
• Instrumental Variables Estimation of Single-Equation Linear Models
• Estimating Systems of Equations by OLS and GLS
• System Estimation by Instrumental Variables
• Basic Linear Unobserved Effects Panel Data Models
• Discrete Response Models
• Censored Regression Models

Prerequisites

Basic knowledge of econometrics and statistics and algebra at the Ievel of an undergraduate course.

Course Structure

The course closely follows the main textbook of the course. While the course is self-contained, following the main textbook provides the participants with a well-structured source for further reading and deeper understanding of the topics. Topics are discussed from a theoretical point of view to provide the participants with a proper understanding of the econometric models. These discussions provide key knowledge on how different econometric models work and most importantly shed light on their limitations. The course also provides step by step application of new tools to different data sets in computer lab. The empirical assignments discussed in the class are generally replication of some of the empirical works that have been done by different researchers.

The participants must turn in assignments. These assignments are in general empirical in nature. The participants are encouraged to form groups to work on the assignments. The performance of the students on the assignments and on a final exam will ultimately determine the overall performance of the participants.

Course Description

• General Equilibrium Theory
• Dominant strategies and applications
• Nash Equilibrium and applications
• Subgame Perfect Equilibrium and applications
• Bayesian Equilibrium
• Perfect Bayesian Equilibrium and applications
• The Theory of Incomplete Contracts
• Cooperative Game Theory

Prerequisites

Microeconomics at graduate level.

Course Structure

In each section, the module starts with a presentation of the respective theoretical concepts and then moves on to examples. In these examples, special emphasis is put on applications from management, finance and industrial organization. The first section deals with consumer decision making and general equilibrium and is followed by 5 sections on no cooperative game theory. The final two sections deal with cooperative game theory and bi-forms, i.e. the combination of the two game theoretic solution concepts as applied by incomplete contract theory.

Course Description

Why do firms exist? Which value-adding activities should be performed inside the firm? Which ones should be outsourced? These are the critical questions of the research stream commonly referred to as “theories of the firm“. In this course, we will examine the conceptual building blocks of these theories, exploring the logic and methodologies of the extent of the market argument, of the opportunism-based theories of the firm, and of the resource-based theories of the firm.

Prerequisites

Basic Econometrics

Course Structure

• Overview
• The extent for the market argument
• Transaction cost economics and opportunism-based theories of the firm
• The resource-based view
• The resource-based view as a theory of the firm
• Empirical work in the extent of the market
• Empirical work in transaction-cost economics
• Empirical work in the resource-based view
• Analysis of working papers
• Research Proposal Presentations

Course Description

• Instrumental variables: linear and non-linear models
• Propensity Score Matching
• Difference-in-difference estimation
• Regression discontinuity design
• Dynamic panel data
• Non-linear panel data models
• Quantile regressions
• Robust regressions and outliers
• Model selection
• Multi-level regressions

Prerequisites

Econometrics I or equivalent course, providing solid background knowledge of econometrics.

Course Structure

The aim of the module is to discuss a selection of advanced modern econometric techniques, focusing on their applications in empirical research and paying special attention to the recent developments in applied econometric methodology. Specifically, the course combines theoretical introduction, practical exercises and discussion of key papers applying particular methods. The module covers econometrics of cross-sections and panel data.

Course Description

• Research ethics and research designs
• Reliability and validity
• Introduction to R and RStudio: How to use R? First steps in programming in R, data management, and descriptive statistics
• Correlation, regression, and path analysis with manifest variables: Examining associations between variables. Bivariate correlation, multiple regressions, direct and indirect effects with manifest variables. Computing and interpreting effect sizes.
• Confirmatory factor analysis (CFA): Working with latent variables. Independent clusters model of CFA and alternatives. Model identification, model evaluation, model interpretation.
• Structural equation modeling (SEM): Combining path analysis and confirmatory factor analysis. Testing substantive hypotheses with SEM. Model revision and comparison. Equality constraints
• Models for longitudinal data: Latent-State Models. Autoregressive Models and Latent Change Models: Quantifying and interpreting change over time. Comparing groups.
• Writing and Publishing: How to write an empirical paper

Prerequisites

Scientific training at or beyond master level in some discipline.

Course Structure

The module structure is tripartite (Philosophy of Science, Structural Equation Modeling, Academic Writing) reflecting a comprehensive approach to Research in the Social Sciences. It focuses on fundamental topics of empirical research and conveys practical skills relevant for a career in academia. The total grade will hinge on both class participation, writing a paper on issues of Philosophy of Science, an exam on SEM and presenting samples of personal writing in the concluding part on academic writing.

Course Description

The course is an in-depth introduction to the modern theory of asset pricing and portfolio choice. Its main focus is on the relationship between arbitrage and equilibrium, and how both conditions imply the existence of "state prices," positive discount factors such that the price of any security is simply its discounted expected payoff. The first part of the course examines static economies while the second extends into a multi-period framework. Both parts are restricted to discrete time and symmetric and complete information.

Prerequisites

The student is assumed to have a good working knowledge of probability, statistics, calculus and microeconomics.

Course Structure

• Arbitrage and pricing
• Equilibrium and pricing
• Optimal portfolio choice
• Mean-Variance analysis
• Asset pricing models

Course Description

This module introduces PhD candidates to the latest models that try to explain the role of banks in the economy. Based on those approaches this course presents latest theoretical contributions on modelling the origin of financial contagion and the role of regulation in mitigating systemic risk. Furthermore this course also presents the most recent models on competition in the banking sector and its implications for stability. The overarching aim of this course it to provide students not only with the thorough theoretical background required to pursue empirical studies. It should also enable students develop their own theoretical models in this area.

Prerequisites

Corporate Finance

Course Structure

The module is structured as follows:

• The role of financial intermediaries in the economy
• The inherent fragility of banks
• The origins of financial contagion
• Banking competition and financial stability
• Optimal capital structure and the need for banking regulation

Course Description

• Fixed effects regression
• Difference-in-differences estimators
• Regression discontinuity design
• Synthetic control estimator
• Instrumental variable regressions
• Governance of the research process

Prerequisites

Econometrics I and II

Course Structure

The course is structured in three parts (not necessarily chronological):

• Part 1: Empirical methodologies (focus on regression discontinuity, difference-in-difference estimators, synthetic control estimators)
• Part 2: Discussion of recent empirical papers with a focus on financial intermediation, corporate finance, and possibly with a link to accounting
• Part 3: Development of own research ideas

Course Description

The course makes students familiar with the main hidden information and hidden action models. It introduces a concise theoretical principle agent framework that allows analyzing the major topics in corporate finance including among others firms’ debt capacity and the optimal capital structure, corporate risk and liquidity management, and corporate control and governance.

Prerequisites

There are no prerequisites necessary.

Course Structure

This course is split in two parts. The first introduces the baseline models. The second part provides a more in depth application of the baseline model to a variety of different problems in corporate finance.

Course Description

The topic of the course is imperfect information in financial markets. It is an introduction to information choice and learning with applications to corporate finance and asset pricing.

Prerequisites

Microeconomics

Course Structure

• Adverse Selection, Screening, and Signaling
• Sequential Trade Models with Asymmetric Information
• Aggregation of Information by Prices
• Strategic Trade Models
• Information Sales in Financial Markets
• Herding
• Bubbles and Crashes
• Manipulation
• Reputation
• Feedback Effects

Course Description

This empirical PhD seminar in the Accounting concentration aims to provide a broad overview over the most important strands of literature, while the in-class discussion will also highlight test design choices. 

Aside from general class participation, students are expected to present select papers during class, the (take-home) deliverables at course conclusion are a research proposal and a referee report.  Students can opt to gain programming experience (SAS/Stata) through a (guided) replication of an existing study. 

The course is normally scheduled to meet weekly throughout the semester. If external students enroll, the format will be changed to three blocks of adjacent classes (4+4+3).

Prerequisites

Accounting, Econometrics (master level)

Course Structure

• Introduction to Empirical Accounting Research: The role of accounting research from informational and contracting perspectives
• Empirical accounting research classics: Accounting numbers and stock prices
• Accounting-based valuation
• Earnings responses and value relevance
• Conservatism: Motivation, measures, and consequences
• Returns and cost of capital
• Investor information processing and stock market anomalies
• Earnings management
• Earnings quality
• Standard Setting 1: Disclosure versus recognition
• Standard Setting 2: Comparative accounting research, IFRS adoption

Course Description

This module provides an introduction to academic empirical research on performance measurement and incentives. It covers topics such as financial and nonfinancial performance measures, subjective performance evaluation, target setting and target ratcheting, relative performance evaluation and management control systems.

Prerequisites

Econometrics I

Course Structure

• Intro: Paradigms in Management Accounting Research: Theory & Methods
• Explicit & Implicit Incentive Design Frameworks
• Performance Measures (I), especially Stock Prices & Accounting
• Measures & Nonfinancial Performance Measures
• Performance Measures (II) Organizational Design (Decentralization, Interdependencies), Subjectivity
• Management Accounting at the Top of the Firm: Corporate Governance
• Relative Performance Evaluation
• Target Setting
• Economic and Behavioral Aspects of Budgeting
• Cost Behavior and Management
• Management Control Systems & Informal Controls such as the Balanced Scorecard Framework
• Behavioral Aspects in Management Control

Course Description

This course is designed for Ph.D. students in accounting and may also be of interest to Ph.D. students with research interests in related fields, particularly corporate finance and management. The main goal is to enhance students’ understanding of empirical economics-based research in accounting. A secondary goal is to broaden the students’ view of what constitutes accounting research by showing how it is embedded in work in other disciplines such as economics, finance, and biology.

This course surveys leading academic research in economics, finance, and accounting and highlights in particular emerging topics and new research methods. Throughout the course, I intend to emphasize research design issues, identification strategies, and new (uses of) data. Students are allowed to take each module separately for credit, but are encouraged to attend the complete course.

Course Structure

Module I: Organizational design, performance measurement, and incentives

• Complementarities in organizational design and empirical consequences
• Delegation of authority
• Incentives and reward systems
• Performance measurement

Module II: Disclosure and contracting

• (Implicit) contracting theory, supply and loan contracts
• Conservatism and the confirmatory role of accounting information
• (Voluntary) disclosure choices and computational linguistics

Module III: Political economy of accounting and finance

• Corporate political activity and firm policies
• Media and other information intermediaries
• Enforcement and regulation in (international) capital markets

Module IV: Managerial characteristics, (firm) culture, and firm outcomes

• Do managers matter?
• Cultural heritage vs. innate characteristics of managers
• Plough vs. hoe or Rice vs. wheat: the origin of time preferences and why it is important

Course Description

• Attention, Perception, Memory
• Moods and Emotion, Non-conscious processes and priming
• Goals Choice under risk and uncertainty
• Judgment biases
• Decisions in a social context.

Prerequisites

Scientific training at or beyond master level in some discipline.

Structure

The module will be comprised of lectures and class discussions based on assigned readings.

Course Description

In part A, we will develop the model's primitives, and discuss the fundamental decision making trade-off that the model captures. We will then work towards the goal to derive an optimal solution, where "optimal" is relative to some specified objective (such as maximizing expected profit). Towards this goal, we will use different optimization and simulation techniques.

In part B, we will work towards a descriptive test of the model's predictions. We will derive and discuss hypotheses that flow directly from the normative treatment of the model, as well as hypotheses that can be motivated based on existing behavioral theory. We will develop, and implement, laboratory experiments specifically designed to test these hypotheses. Finally, we will analyze the data from published papers.

In part C, we will empirically test newsvendor theory in the field. Again, we will analyze the data from published papers.

Prerequisites

There are no prerequisites necessary.

Structure

This module has three parts: Part A (Theory), Part B (Experiment), Part C (Field)

Course Description

TBA

Prerequisites

Scientific training at or beyond master level in some discipline.

Structure

11 sessions @ 4 academic hours each

Frankfurt School’s Finance Research Seminars provide a forum for researchers of all disciplines to present and discuss their research. They usually take place on Wednesdays from 11:30 a.m. to 1:00 p.m. during the semester. Before or after the talk there is the opportunity to meet and exchange with members of the faculty in individual discussions.

Dissertation

Defence

Consumer Information Processing (Marketing)

Selin Atalay studies consumer information processing by using the methodology of eye tracking to trace consumer decision making processes in retail environments. Understanding the decision making process contributes to designing better retail environments. Furthermore, understanding how consumers focus their attention as they visually search for information also has implications for packaging.

Delegation of Authority and the Efficiency of Decision Making (Management)

Delegating decisions to employees is beneficial to utilise their knowledge, but they might pursue their own agenda. Psychology suggests that managers may keep control too often as they have a lure for authority. Eberhard Fees analyses the conditions which influence the frequency and efficiency of delegation both with economic theory and in the laboratory. (taught by Eberhard Feess)

IQ gets you hired but EQ gets you promoted (Management)

Emotional intelligence (EI) is a controversial construct. This project analyses to what extent EI predicts job-related outcome variables such as customer satisfaction, performance, and stress. (taught by Myriam Bechtholdt)

The Role of the Employee in Information Security (Information Systems)

Many organisations are aware of the fact that their employees are the weakest link in information security. This research project by Peter Rossbach identifies the factors influencing employee’s compliance with the information security policy (ISP) of an organisation and their relevance. The factors derive from literature research and are verified by quantitative methods based on a survey. (taught by Peter Rossbach)

Hierarchical Judgemental Forecasting (Operations)

Mirko Kremer empirically investigates the relative performance of bottom-up versus top-down forecasting processes popular in Sales & Operations Planning practice.

Meta-heuristics for Solving Highly Complex Business Problems (Operations)

Many business problems are characterised by a high degree of complexity (np-hard problems). One example is the so-called car sequencing problem where automotive manufacturers have to schedule the sequence of cars on their assembly line. Meta-heuristics such as Ant Colony Optimisation that incorporates the search behaviour of ants into the heuristic or Genetic Algorithms that uses the logic of human genes have the potential to identify optimal solutions and are most effective for solving complex problems not only in the automotive sector. (taught by Jörn-Henrik Thun)

Myopic Marketing Management – Whom to Blame? (Marketing)

We examine short-term oriented management with regard to cuts in marketing expenses. We find top marketing managers’ compensation incentives (but not those of the CEO) to be responsible. This result contradicts suggestions in marketing literature that the presence of a chief marketing officer can help to maintain a long-term orientation with regard to marketing spending (taught by Martin Artz)

The Impact of Financial Incentives on Customer Value (Marketing)

Firms often use financial incentives (promotions, referral rewards, loyalty programmes, etc.) to attract new or re-activate existing customers. The impact of such incentives on customer value is important, yet poorly understood. We investigate how their effect depends on incentive type, customer type, or the competitive environment to help firms spend their marketing budgets more effectively. (taught by Christian Schulze)

Strategic Decision-Making (Management)

Professor Ronald Klingebiel examines why and how firms with different decision-making patterns achieve different levels of success. He explores, for example, the conditions under which firms that keep their options open achieve higher performance than peers that might fully commit to uncertain innovation projects. His research often involves data from technology-intensive industries, particularly all things telecom.

Does Accreditation Count? (Management)

Accreditation is a typical external approach for patient safety and quality management in hospitals worldwide. But the evidence of the benefits of these systems is still lacking. The main objective of the research project is to discuss the potential advantages and disadvantages of accreditation and to analyse the relationship between accreditation and hospital quality. (taught by Rainer Sibbel)

Effective Outsourcing Strategies and Management (Information Systems)

We analyse organisational, social, and technical determinants that contribute to the effective governance of IT outsourcing relationships, e.g., by ensuring that service providers sufficiently invest in innovation and knowledge exchange or by supporting decisions about and management of relationships with multiple vendors. Research approaches include qualitative and quantitative field research, social network analyses, and the development of software artefacts. (taught by Daniel Beimborn)

Weight Jacket or Life Vest? Inventories in the Presence of Major Production Disruptions (Operations)

Severe production disruptions due to quality breakdowns have the potential to ruin performance over the complete life cycle of a highly profitable product. The project uses system dynamics modelling to investigate the interplay between different forms of customer adaptation to varying service levels, the availability of a substitute product, and the economic characteristics of the product. (taught by Jürgen Strohhecker)

• Curriculum Vitae and list of publications (if existent)

• Certified copy of your University Entrance Qualification (Abitur, A-levels or equivalent)

• Certified copy of your University Degree Certificate or equivalent and academic transcript of records (Candidates who have not yet completed their degrees should submit their most recent academic transcript instead)

• Official GMAT or GRE results

  GMAT institution code: FCB; Programme code: FCB-RP-82

  GRE institution code: 7573

• Proof of English Language Proficiency Test (TOEFL IBT min. score of 100/IELTS min. score of 7.0)

  TOEFL institution Code: 0239

  . Candidates with degrees from English-speaking study programmes do not need an English Language Proficiency. Please upload a certificate by the university confirming that the entire programme was conducted in English

• Two letters of recommendation from a former academic tutor or from another person in an academic environment.

• Statement of purpose and research interest (description of a possible research project, 2-5 pages, demonstrating how the candidate plans to apply his/her particular interests, skills and expertise to the pursuit of his/her academic objectives)