Your first step to becoming an IESE doctoral student is to complete a Master in 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 our 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 participate in key research projects with IESE faculty, providing you with valuable inspiration for your dissertation topic, in addition to being an unparalleled learning experience.

MRM Coursework

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 theoretical research for publication in mainstream business journals.

 

  • Anthropology & Ethics

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.

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  • Computational Social Science

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 websites (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.

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  • Econometrics I

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.

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  • Management Classics

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.

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  • Research Design

The main objective of this course is to improve the design of your 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. Although this is not an econometrics course, econometric concepts, problems, and analyses will be considered, making explicit connections with what you have seen and will see in econometrics courses as well as in other methods courses.

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  • Research Methods

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, heteroscedasticity, 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.

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  • Statistics

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.

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  • Empirical Research Paper (TFM)

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.

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  • Special Field Exam

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.

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  • Advanced Research Methods: Stochastic Modeling and Optimization

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 fundamental problems such as inventory management, asset selling, portfolio selection, dynamic pricing, and trajectory tracking; an introduction to state estimation and dynamic learning problems; as well as a primer in infinite-horizon discounted problems.

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  • Contemporary topics in Entrepreneurship, Social change, and Governance

This course seeks to provide a deep understanding of the linkages between entrepreneurship, social change, and governance. It is built from the premise that governance is a central and foundational topic in assessing how entrepreneurial action can contribute to the public good. It also examines important interdisciplinary research at the intersection of entrepreneurship and social change, including sustainable and social entrepreneurship, gender issues, creativity, minority-based entrepreneurship, technology and innovation, impact investing, the treatment of time, uncertainty, institutional change, industry development and evolution, and field experiments, amongst others.

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  • Discipline in Management

Discipline in Management allows IESE MRM students to pursue a specific research project related to their area of interest under the supervision of an IESE faculty member. The student and a faculty mentor determine the nature and extent of this independent study project. The main objective of the Discipline in Management is to improve the student’s knowledge of their area of specialization and to enhance their ability to design and execute research projects effectively.

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  • Econometrics II

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.

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  • Economics

This course addresses the economic framework in which organizations operate, the traditional models underpinning the theory of the firm and their contemporary alternatives, as well as the role of property rights and incomplete contracting in shaping incentives and organizational structures. It also examines issues arising from asymmetric information—such as adverse selection and moral hazard—and reflects on the limits of economics as a discipline, recognizing the need to integrate interdisciplinary perspectives to achieve a more comprehensive understanding of management and organizational decision-making.

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  • Economic Sociology

This seminar focuses on the contributions of the “New Economic Sociology”. The past three decades have witnessed an almost radical transformation in the field of sociology’s approach to the economy. Building on work by original authors in this area, the seminar deals sequentially with some of the most significant contributions in the economic sociology field. It starts with basic concepts such as classical foundations, markets and fields, work, and occupations. The course, then, moves on to examine the key economic institutions: Markets, firms, and networks. Finally, the third part emphasizes different aspects of inequality as well as new themes emerging in the field from a sociological lens. The outcome of the seminar should be a short but innovative conceptual and/or empirical work closely based on the seminar’s concepts.

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  • Entrepreneurship

This course is designed to expose you to cutting-edge theoretical and empirical developments, and to appropriate methodological perspectives on entrepreneurship research. For a solid understanding of the phenomenon, the course will give you a brief introduction to the entrepreneurship field, its foundations and intellectual heritage. We will then focus on the main questions that define the field today and critically examine how researchers are approaching these questions.

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  • Experiments

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.

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  • Finance

This course has two main purposes:

1)To give students a solid basis in corporate finance, especially in empirical methods. The vast majority of our students work in empirical corporate finance (both reduced form and structural) but have limited training in these topics. This makes it hard for many of us in the department to supervise and work with them efficiently.
2)To expose students to what faculty members in the department are working on.

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  • Independent Area Project

Independent Area Project (IAP) allows IESE MRM students to pursue a specific research project related to their area and research interest that is under the supervision of an IESE faculty member. The student and a faculty mentor determine the nature and extent of this independent study project. The main objective of the IAP is to improve your knowledge of the area of specialization of your  interest and the design of your research projects.

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  • Industrial Organization

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.

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  • Microeconomics

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.

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  • Organizational Behavior

This doctoral seminar aims to provide an in-depth look at some 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.

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  • Organizational Theory

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.

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  • Qualitative Methods

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.

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  • Research Methods in Finance

This course intends to provide students with the knowledge of the quantitative tools used in current finance research. We will discuss numerical and econometrics methods, including Solution of dynamic; models of firm behavior; Non-linear estimation methods: Generalized Method of Moments, Maximum Likelihood, Monte Carlo Simulation Methods, Machine learning methods. We will then see how these methods are applied in current finance research to investigate topics such as: Capital structure (e.g., debt vs. equity, cash holdings); Corporate investment, Mergers and acquisitions; Corporate governance, Asset pricing.

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  • Strategic Management

The objective of this first-year PhD course in Strategic Management is to familiarize the students with the key theories and research questions that the Strategic Management field deals with. The course will build on and leverage the methods developed in the Research Methods course to address these questions. By the end of the course, the students should have a clear map of the field of Strategic Management, understand how to develop an interesting research question and be able to structure a research paper to address that question.

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