Your first step to becoming an IESE doctoral student is to complete a Master of Research in Management (MRM) or be in the possession of a postgraduate degree in research methodologies for business and management sciences.
The MRM provides you with the foundations to become a thoroughly trained researcher. You’ll gain the quantitative and qualitative methodological skills needed for quality empirical and theoretic research for publication in mainstream business journals.
After finishing your coursework, you will take an examination in your area of specialization and submit an empirical research paper showing potential, both of which are needed to progress on to the IESE doctoral program.
You’ll have the chance to work as a research assistant for IESE faculty members throughout your MRM. Participating in key research projects provides you with valuable inspiration for your dissertation topic, in addition to being an unparalleled learning experience.
First Year – Term 1
This Pre-course is designed to serve as an opener of what research is about. Its purpose is to help you not to lose track of what you’re here for: becoming an independent researcher.
This introductory doctoral course provides a broad overview of the key theoretical insights in management and organization theory, and how they have influenced research also in other management disciplines (operations, marketing, finance). By the end of the course the students will be able to frame a research question from a theoretical point of view, and develop original research ideas to advance scholarship in their field.
The goal of this course is to develop the basic microeconomic tools that are necessary to analyze
managerial decisions from an economic point of view. Mastering these tools is essential to be able to take courses in industrial organization, finance, marketing, accounting and strategy at later stages in your PhD.
This class will focus on learning the basics of Python programming. Python is a very readable, easy to use, yet powerful high-level programming language that is becoming one of the more popular programming languages for scientific research. The other big application for Python is the WWW; some of the biggest web sites (youtube.com, reddit.com…) are written in Python. One of the main advantages of Python is that it is designed to facilitate usability rather than minimizing computing time. Python thus is not the fastest computer language, but it allows moving from idea to actual implementation very easily.
This course emphasize on practical data analysis. It differs from other introductory courses in that multiple regression is covered and analysis of variance is restricted to one-way ANOVA. The Statistics course includes descriptive statistics, probability basics, and estimation and testing, covering the classical tests on group differences and regression coefficients.
This course seeks to explore, first, the relationship between the emergence of ‘modernity’ and the invention of ‘social science,’ paying attention especially to Weber, Marx and Durkheim. These thinkers created some of social sciences most memorable and influential narratives. We will, second, explore several 20th century traditions of sociological thought, both in Europe and in the United States, which have shaped how we see our world today.
First Year – Term 2
This is a propaedeutic course on the philosophical study of human nature and action, that complements other scientific approaches to management. At the heart of management ‐both as science and practice‐ lies the human person, that through his or her actions ‐ in cooperation with other people and using resources efficiently‐ tries to achieve some valuable aims. Empirical sciences might not be sufficient for a full understanding of this reality.
The goal of this course is to develop your knowledge of applied econometrics and to put this knowledge into practice through examples and replication work. The tools that you will learn in this course will be useful to prepare you for conducting independent research in management.
This course is an introduction to the field of industrial organization. Industrial organization deals with the structure and performance of (imperfectly competitive) markets and the interaction between different players intervening in these markets such as firms, consumers and regulators or competition policy authorities. Among the particular subjects we will study are the determinants of market structure, the pricing decisions of firms, the strategic interactions among firms, and the effects of structure and conduct on price and non-price dimensions of market performance.
This seminar presents, discusses and evaluates contemporary developments in the field of organizational theory. Perspectives inherent in demography, environmentalism, networks, resource dependency and neo-institutional approaches are examined in detail. The conceptual challenges posed to existing theories by the emerging plurality of organizational forms is given special consideration. The seminar emphasizes non-economic approaches to organizational phenomena.
This course aims to lay a foundation for your empirical research. The goal is to help you to design and develop your future research projects. To this end, we will focus on the importance of careful theoretical thinking and on the conceptual difficulties associated with establishing causality in empirical work.
Organizational Economics A is a non-technical introductory course to organizational economics. What a firm is, what characterizes a neoclassical firm in economics, what the new contributions of economics of organizations are with respect to the theory of the firm are the key questions developed in the course. The logic of markets, transaction cost economics, its effects on governance, bounded rationality, opportunism, incomplete contracts, vertical integration, rents and efficiency, property rights, employment and executive compensation, alternative approaches to decision making, are some of the topics discussed.
The approach will emphasize the theoretical foundations and econometric rigor of empirical work. The course series will cover the main research areas of empirical research in asset pricing, corporate finance, and financial reporting. This first part of the series will focus on corporate finance and banking.
First Year – Term 3
Econometrics II is a theoretical and applied course. In the theoretical part you will learn how to develop appropriate models and advanced methods for the measurement of economic relationships using non-experimental data.
You will be able to implement methods for estimating and identifying causal effects and have the skills necessary to design and implement empirical strategies for causal analysis. Non-linear models will also be introduced, such as limited dependent variables, quantile regressions and generalized method of moments.
Applications in the areas of microeconomics, social policy and finance will be considered using the R programming language.
The field of Strategy studies the drivers of persistent performance differentials among firms. The course falls into two parts. In the first part, we will establish the “fact” that these persistent performance differentials exist and cover the different theories that have attempted to explain this fact from a historical perspective. In the second part, we cover research that highlights different strategic decisions that affect these performance differentials and their persistence.
This doctoral seminar aims to provide an in-depth look at some of the major topics of interest in contemporary organizational behavior (OB), with a primary focus on individual and collective processes – such as the study of individuals and groups within an organizational context, and the study of internal processes and practices as they affect individuals and groups.
This course offers an introduction to established and emerging themes, knowledge, theory and research in the field of organizational behavior. One particular feature of this seminar is its multicultural focus. As human values and behaviors are very often culture-bound, we will also investigate certain cultural variations so as to reflect on the universality/particularity of organizational behavior across different cultures.
This course provides an introduction to quantitative methods for management research. It provides an understanding of the strengths and weaknesses of different data and modeling traditions. It also covers prime challenges in model specification such as heterogeneity, multicollinearity, heteroskedasticity, endogeneity and aggregation. In our discussions, we will also devote attention to how to design research for academic and practice impact and to philosophy of science in general.
The course is an introduction to a few selected topics of finance at a PhD level. The objective is to equip students with tools to understand and do research in finance while discussing current policy developments as a result of the financial crisis. We shall revisit some of the classical concepts of financial economics, such as moral hazard and asymmetric information and how they impact corporate governance; introduce the role of information in financial markets; and conclude with a debate on banking and the financial crises. To achieve these objectives, we shall read and present recent papers in the area of finance, which use the following methods: mathematical modeling, empirical data and policy oriented tools. There will be also an emphasis on how finance is related to other areas of management such as corporate governance, control, strategic management and economics.
In this course, we cover the analysis of multivariate data on individuals or firms. The course provides useful tools for conducting research, like factor analysis and structural equation modeling.
Upon completion of this course, students will be able to…
i. Formulate the basic idea of factor analysis and structural equation modeling
ii. Decide whether factor analysis and/or structural equation modeling are appropriate analyses techniques for their research question(s)
iii. Run the basic forms of multivariate statistical analyses in Stata
iv. Conduct principal component analysis, execute the analysis in Stata and interpret its outcomes
v. Run exploratory and confirmatory factor analysis in Stata and interpret its outcomes
vi. Estimate, test, and evaluate structural equation models
vii. Perform multi-group analysis in Stata and interpret its outcomes
This course is intended for all doctoral students, regardless of substantive area or methodological orientation. The objective of the course is to develop your appreciation for qualitative research methods. The course takes a practical approach to this objective: the emphasis is on doing qualitative research — that is, reading it, evaluating it, learning the skills involved in conducting it, and applying these skills in the design, conduct, and write-up of a small-scale research study of your choice.
The overall aim of the class is to equip students with the knowledge and capacity to both conduct experimental research as well as interpret and critique others’ experimental research. To achieve this aim, this class is divided into two main phases. In the first phase, students are designing an experiment related to their own research. In the second phase, students can decide between: a) revise and improve their experimental design, b) conduct their proposed experiment and present their results, or c) critique and interpret experiments from their classmates and/or that are already published in top management journals.
Second Year – Term 1
Society, which gives business license to operate, increasingly demands ethical and responsible conduct from firms. Employees expect fair treatment and consumers demand respect for their rights. Similarly, stakeholders are pushing for transparency, accountability, and responsibility. Individuals, social groups and governments are calling for ethical behaviors and responsible conduct from business organizations.
To a great extent, leading companies around the world have already accepted this challenge, and ethics has become a feature in managing business. In practice, however, ethical dilemmas and practical difficulties can arise in decision-making as companies try to harmonize profits with social and ethical responsibilities, and these require solid bases and careful discussion.
Second Year – Term 2
They are specific courses seminars on different academic areas, which can vary every academic year.
Please see the list of the courses available for this academic year at the bottom of this page.
Second Year – Term 3
The student must successfully pass all the courses before he/she can take the Major Field Exam. The exam´s content includes topics relevant to the student´s field. However, the exam may include research design questions or questions related to the disciplines underlying his/her field of interest. The background knowledge required to answer these questions will probably be related with the core courses. Questions might include general evaluations of the field as well as questions about specific aspects of a particular paper.
The empirical paper will be developed during the second year, although it is advisable to start working on it from the end of the first year. The student will develop this paper under the guidance of a Faculty member by mutual agreement. The Faculty member’s name should be communicated to the Assistant Program Director by June. It will be assessed by the faculty member who has supervised the student’s work and the MRM liaison of the student’s area of specialization who will grade the paper. They may provide comments aimed at improving the paper, in which case a final version incorporating those comments should be submitted by September and the revisions should be approved by the involved faculty members no later than September. Failure to meet this requirement will preclude enrollment into the Ph.D. Program, if the student had been admitted to it.
The main objective of the course is to introduce students to sequential decision making under uncertainty through the framework of Dynamic Programming.
Along the way, it presents mathematical formulations and solution concepts for important problems in Management, such as inventory management, asset selling, and portfolio selection; and in Statistics, such as state estimation in HMMs and sequential hypothesis testing.
You will have the opportunity to attend electives and seminars organized by our faculty members. Enrolling in electives specific to your research, plus those that are complementary, will help give your studies a holistic and well-rounded perspective.
The following electives are scheduled for the present year:
- Advanced Strategy – David Wehrheim
- Advanced Organizational Behavior – Sebastian Hafenbrädl
- Behavioral Economics – Xavier Vives
- Behavioral Insights – Isabelle Engeler
- Frontiers of Entrepreneurship – Christoph Zott