Microeconomics Core Requirement

One of the following courses:
Consumer theory; production theory; general equilibrium and welfare.
Consumer theory; production theory; general equilibrium and welfare.

Quantitative Methods Requirement

One of the following courses:

Basic concepts underlying the most important multivariate techniques, overview of actual applications in marketing, operations, finance, and accounting. Underlying mathematics and problems of applications. Sample Geometry and Random Sampling, The Multivariate Normal Distribution, Regression, Analysis of Variance, Multinomial Logit Choice Model, Principal Components Analysis and Factor Analysis, Structural Equations Models, Cluster Analysis.

Mathematical foundation that all students should have before starting the MA courses reviewed in a three-week long intensive Math Camp. Meets every other day (three times per week) during the first three weeks of the four-week period that preceeds the fall term. Two 75 min. classes per day. Three classes for evaluation (written exams).

Review of probability and statistics: random variables, univariate and joint probability distributions, expectations; bivariate normal; sampling distributions; introduction to asymptotic theory; estimation; inference. Linear regression: conditional expectation function; multiple regression; classical regression model, inference and applications.

Departures from the standard assumptions: specification tests; a first look at time series; generalized regression; nonlinear regression; simultaneous equations, identification, instrumental variables. Extensions and applications ML, GMM, VAR, GARCH, panel data.

Convex analysis, optimality conditions, linear programming model formulation, simplex method, duality, dual simplex method, sensitivity analysis; assignment, transportation, and transshipment problems.

Basic theory of the Poisson process, renewal processes, Markov chains in discrete and continuous time, as well as Brownian motion and random walks are developed. Applications of these stochastic processes are emphasized by examples, which are drawn from inventory and queuing theory, reliability and replacement theory, finance, population dynamics and other biological models.

Review of basics of psychological measurement; all steps of the process of assessment development; different methods of psychological assessment such as observational, self-administered, and interview techniques; and, ways of integrating information from multiple assessment methods. Greater cultural, ethical, and societal context of psychological measurement.

Fundamental quantitative methods used in business decision-making: mathematical programming, stochastic modeling, and simulation, with emphasis on formulation, analysis, and implementation.

Research Methodology Requirement

One of the following courses:

Multivariate data analysis techniques in management science such as MANOVA, MANCOVA, MLR, and MLOGR. Related analytical issues such as power analyses, effect sizes, data visualization, complex interactions, and mediation.

Introduction to the fundamental methodological issues that arise in experimental and quasi-experimental research. The development of research ideas; data collection and reliable measurement procedures; threats to validity; control procedures and experimental designs; and data analysis. Use of regression methods for non-experimental and quasi-experimental data and analysis of variance methods for experimental data.

Introduction to the fundamental research methods in social science, covering issues and methods shared by all of the social sciences and by many of the natural sciences. Emphasis on contemporary work in the fields of international relations and political science, on quantitative and qualitative methods and the steps in identifying a problem worthy of study and developing testable hypotheses, designing a research strategy, gathering data, analyzing data, and interpreting the results.

Doctoral Seminars

Area Seminars in Marketing, Quantitative Methods, Finance, Operations

This course introduces theoretical and empirical research on entrepreneurship. Students will get a broad overview of the literature on core topics, learn how to critically review research papers, and develop their own research projects. The course covers the following areas: mobility and careers perspective on entrepreneurship, individual and structural determinants of entry, venture growth, firm survival and mortality, and empirical methods in entrepreneurship research.

Depending on student interest, focus on one or several of the following topics: data mining, multiattribute utility theory and multi-criteria decision making, dynamic programming, decision theory, service management, behavioral operations.

This course provides an overview of econometric techniques for the quantitative analysis of cause and effect in social sciences. Methods covered include experiments, regression, panel methods, difference-in-differences, instrumental variables, regression discontinuity and matching. Each topic will be studied using applications from the recent marketing, economics, management and operations literatures.

Focus on consumer behavior. An overview of research in consumer behavior, particularly in the areas of consumer information processing, memory, attitudes, affect, and motivation. Introduce a body of literature and a strong foundation in critical thinking in the behavioral area for students to develop their own research interests.

Focus on consumer behavior and marketing strategy. Depending on student interests, focus on one or several of the following topics: marketing strategy, international marketing, and behavioral decision theory.

Focus on empirical modeling. State of the art in empirical marketing models. Focus on models of consumer and models of market behavior. Utility theory, discrete choice models, stochastic models, multi-dimensional scaling, and hierarchical decision making. Models examined in the context of how consumers and the market react to marketing stimuli. Readings drawn from leading marketing journals. Introduce a body of literature and expose students to the state-of-the art empirical modeling techniques, for them to develop their empirical modeling skills and to help identify their potential research interest in this area.

Focus on mathematical modeling. State of the art in analytical marketing models. Focus on managerial models of advertising allocations, channel design, sales force allocations, sales promotion, pricing, product design, test markets, and competitive positioning. Readings drawn from leading marketing, operation management and economic journals. Key models and substantive issues in analytical modeling. Students to develop their own models and papers on a topic of interest.

This is a doctoral seminar course focusing on behavioral foundations of marketing strategy research. Since marketing strategy is inherently interdisciplinary, the course acquaints students with theories emanating from economics, sociology, psychology, strategy, the organizational sciences, as well as marketing. Students will be introduced to a variety of research designs and techniques for doing marketing strategy research. We will examine research involving experiments, quasi-experiments, surveys, qualitative data, and secondary data. Some of the topics covered include: marketing capabilities and resources, financial returns to marketing strategies, market knowledge and learning, marketing and innovation, marketing networks. The goal is that students finish the course with a deep understanding of the literature as well as how they might contribute to it. Students write a research paper on a topic of interest.

First part focuses on recent theoretical developments in corporate finance theory. Relevant concepts in game theory and contract theory and their applications to corporate finance. Techniques developed are used to understand agency conflicts between debt holders and equity holders, the role of managerial reputation and monitoring by financial intermediaries; conflicts of interest between managers and shareholders; capital structure and security design under asymmetric information; interactions between capital structure and product market competition; the market for corporate control, takeovers and acquisitions; bankruptcy and reorganization; IPOs and under-pricing. Second part studies the firm’s choice of its capital structure and dividend policy in settings characterized by moral hazard or asymmetric information, security issuance, investment decisions, corporate control, and corporate governance. Introduction to databases and empirical methods used most frequently in corporate finance research.

Focus on two core ideas: 1) time series properties of asset returns (predictability, volatility, correlations with other variables etc) and 2) cross-sectional properties of asset returns implied by equilibrium asset pricing models (including CAPM, consumption-based asset pricing, factor models etc). Topics include the arbitrage pricing theory, intertemporal capital asset pricing model, derivative pricing models, asymmetric information and rational expectations and an introduction to empirical testing.

The first part introduces a variety of econometric techniques, including maximum likelihood, generalized method of moments (GMM), panel data regressions, and various time-series models, including ARMA, GARCH, and regime-switching. Application of these econometric methodologies to asset pricing tests, dynamic asset allocation, financial risk management, and derivative pricing. The second part provides the foundations of continuous-time modeling. Continuous-time stochastic processes, Markov/Wiener processes, martingales, Ito’s lemma, stochastic differential equations and changes of measure. The applications of continuous time models include fixed-income pricing models, models of forwards, futures and other derivatives, and portfolio choice problems.

Focus on (1) anomalies in equity and debt markets; (2) ideas to come up with profitable portfolios with relatively low risk; (3) how to form long-short equity portfolios; (4) extreme losses of equity and fixed income portfolios; (5) arbitrage with equity, debt, and derivative securities; (6) model the term structure of interest rates, yield curves, and interest rate volatility; and (7) link macroeconomic variables and fundamentals with volatility in financial markets.


Graduate courses approved by the advisor

General Requirements (non-credit pass/fail)

The course, which consists of 4 modules, has been created to support the development of graduate students and to assist them during their research processes. Students participating in the course will be familiar with; overall library services, tips for literature review, reference and citation management, open science methods that you can benefit in your academic practice and research, scholarly publishing and academic ethics, researcher profiles and research impact measurement.


Hands-on teaching experience to graduate students in undergraduate courses. Reinforces understanding of basic concepts and allows to communicate and apply knowledge of the subject matter.

Academic Writing

Writing a scientific paper for publication requires skills that are different than writing a thesis or dissertation. This course focuses on issues including formulation of the research question, articulation of the theoretical foundation, explanation of the research methodology, description and critical discussion of the findings. The course will also present the key points in selecting the right outlet for publication, submitting the paper, and addressing the reviewers’ comment in the revision.

Research Methods and Ethics

Students are required to complete an online ethics course by their second semester.


Required to be completed in every semester until graduation.