Carnegie Mellon University

Ph.D. Courses

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47710 Seminars in Accounting

In this course, we will learn how to be better scientists, both in our theoretical and our empirical investigations. We will explore the role empirical content, or informative content plays in scientific examination of behavior in finance and accounting research. We will…
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47715 Topics in Financial Accounting Research

Structural methods for finance and accounting. Empirical accounting research and critical assessment of empirical work. Learn about the research process and develop ideas for your own research.

47719 Applied Contract Theory in Accounting & Finance

This course covers the main applications of contract theory and information economics, focusing on the business fields of accounting and finance. We start with two essential information-based economic problems moral hazard and adverse selection respectively and focus on…
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47720 Empirical Methods for Finance & Accounting

This is an applied econometrics course that covers the estimation techniques and econometric theory used in contemporary empirical work. With the goal of making causal inference, we will focus on the application of the tools in corporate finance and accounting. The methods…
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47722 Seminar in Finance II (Asset Pricing)

This course focuses on theoretical and empirical research in corporate finance. Topics covered include capital structure decisions, payout policy, mergers and acquisitions, initial public offerings, and financial distress and bankruptcy.

47723 Seminar in Finance III (Financial Institutions & Markets)

This course will focus on trading and market structure issues, and also attention to credit rating agencies, arbitrage and taxes.

47724 Seminar in Finance IV (Corporate Finance)

This is a PhD course intended for doctoral students in finance, economics, and accounting. We will study dynamic quantitative models of corporate investment, financing, and related decisions. While the topics will be primarily in the area of corporate finance, broadly…
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47726 Dynamic Models of Corporate Finance

This is a PhD course intended for doctoral students in finance, economics, and related fields. We will study dynamic quantitative models of corporate investment, financing, and related decisions. The topics will be primarily in the area of corporate finance, broadly…
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47747 Bayesian Statistics

Bayesian methods are widely recognized for the unified approach that they offer to statistical analysis. Additionally, these methods are readily amenable to decision problems which are frequently found in Marketing problems. The growth of Bayesian methods in the last ten…
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47757 Structural Models & Quantitative Methods

This course focuses on empirical structural models and their applications in Marketing, Economics, and Information Systems. The goal is to help students build up necessary toolkits and provide hands-on experience of applying structural models to empirical researches by…
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47762 Healthcare Operations

The course covers models and methods of analysis for macro-, meso- and micro-level topics, spanning market design, access to (and quality of) care, competing interests, personalized medicine, global health, organ transplantation, healthcare supply chains, ambulatory care,…
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47770 Strategic Queueing Models

This course is designed to introduce students to contemporary research topics in Operations Management built on a queueing framework. Queueing theory, the intrinsically dynamic and stochastic study of flow systems, will be used to model how waiting times depend on demand…
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47779 Quantum Integer Programming & Quantum Machine Learning I

This course is primarily designed for graduate students (and advanced undergraduates) interested in integer programming (with non-linear objective functions) and the potential of near-term quantum and quantum-inspired computing for solving combinatorial optimization problems.

47785 Quantum Integer Programming & Quantum Machine Learning II

This course is primarily designed for graduate students (and advanced undergraduates) interested in integer programming (with non-linear objective functions) and the potential of near-term quantum and quantum-inspired computing for solving combinatorial optimization problems.

47800 Microeconomics I

This course is the first course in the core micro sequence of the economics PhD program. It is an introduction to microeconomic theory and concerns the behavior of individual consumers and firms in competitive settings. The specific topics to be covered are preference and…
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47801 Microeconomics II

This course is the second course in the core micro sequence of the economics PhD program. It is an introductory course in game theory and concerns economic situations in which rational decision-makers interact. The course is intended to teach students the tools necessary…
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47802 Microeconomics III

This course is the last course in the core micro sequence of the economics PhD program. The topics studied are advanced topics in economic theory. They often include but are not limited to contract theory and economics of information, repeated games and advanced models of…
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47803 Macroeconomics I

This course is the first course in the core macro sequence of the economics PhD program. This is an introductory course to modern macroeconomics. The course covers topics from basic growth theory to labor markets, asset pricing and government policy. It makes the students…
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47804 Macroeconomics II

This course is the second course in the core macro sequence of the economics PhD program. The course expands on the topics discussed in macroeconomics 1. Mainly the course focuses on macroeconomic models that involve heterogeneity. The topics covered in the class are…
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47805 Macroeconomics III

This course is the last course in the core macro sequence of the economics PhD program. It covers advanced topics in macroeconomics. These include monetary economics, models of firm dynamics, technology adoption, innovation and growth.  

47808 Dynamic Competitive Analysis

This course will focus on the overlapping generations (OLG) model. Together with the neoclassical growth model (aka the Ramsey-Cass-Koopmans model), the OLG is one of the workhorse models used in macroeconomic theory. Since the student will have been introduced to the RCK…
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47809 Computational Methods for Economics

This is a course in the basic tools of numerical analysis that can be used both to assess the quantitative implications of economic theory and to derive theoretical results of economic models without analytical solutions. While the most examples will come from…
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47811 Econometrics I

This course is the first course in the core econometrics sequence of the economics PhD program. It is an introduction to the basic questions, tools and techniques used in empirical social science research. Students will learn to calculate and perform correct inference on…
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47812 Econometrics II

This course is the second course in the core econometrics sequence of the economics PhD program. It is about estimating structural economic models. The basic question is how to use data to estimate the parameters of an economic model. We will want to establish: establish…
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47813 Econometrics III

This course is the third course in the core econometrics sequence of the economics PhD program. This course explores relationships between economic theory, identification, estimation and econometric practice. It develops structural approaches for analyzing large cross…
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47830 Integer Programming

Integer programming: scope and applicability. Formulations. Combinatorial optimization. Relaxations. Linear programs with integer solutions. Outline of solutions methods: enumeration and convexification. Complexity and problem reductions. Optimization and separation.…
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47831 Advanced Integer Programming

This graduate-level course is a sequel to 47-830 Integer Programming. The following advanced topics will be covered: The size of a smallest perfect formulation. Infinite relaxations. Equivalence between Optimization and Separation. Integer programming in fixed dimension.…
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47834 Linear Programming

Linear programming lies at the basis of modern optimization theory. This course focuses primarily on linear programming theory and algorithms, leaving beyond the scope of its practical applications. The main topics to be covered include modeling examples and expressive…
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47835 Network Optimization I

Network Optimization 1 & 2 (47-835 & 836) are a pair of doctoral level classes that cover basic topics in the intersection of graph algorithms and mathematical optimization. Topics covered include packing and covering problems in graphs such as flows, cuts, and…
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47836 Network Optimization II

Network Optimization 1 & 2 (47-835 & 836) are a pair of doctoral level classes that cover basic topics in the intersection of graph algorithms and mathematical optimization. Topics covered include packing and covering problems in graphs such as flows, cuts, and…
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47841 Applications of High-Dimensional Statistics

Modern data in settings such as e-commerce, healthcare, and operations management are almost always complex and in high dimension. Recent computational and algorithmic advances have led to exciting opportunities to leverage this data for analysis and decision making…
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47851 Modern Convex Optimization

This course will cover the main foundations of convex optimization. The goal is to develop solid command of the foundational blocks of this discipline at the highest possible level. The course topics will include a thorough treatment of duality, optimality conditions,…
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47884 Mechanism Design

This course is an advanced class on theory and applications of mechanism design. Theoretically, the course focuses on recent development in mechanism design: on topics such as robust mechanism design, mechanism design with multiple dimensions of heterogeneity, and…
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47887 Economic Regulation of Networked Industries

This course will examine principles of economic regulation of networked industries such as gas, electricity, water and telecommunications, including economic justifications for price regulation (e.g. natural monopoly); alternative approaches to price regulation (Rate of…
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47890 Seminar in Organizational Theory (Micro)

This seminar focuses on individual and group behavior in organizations. The purpose of this course is to examine and understand fundamental theories and empirical research in the field of organizational behavior, and to increase our understanding of people’s…
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47892 Seminar in Organizational Theory (macro)

This course introduces central concepts in Organizational Theory. The main objective of this course is to create a forum to discuss and develop an understanding of the different strategies organizational theorists use to explain organizational processes, develop theories,…
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47894 Research Methods in Behavioral Sciences

This course provides an introduction to research methodology applicable to organizational behavior and other related fields. The course will survey the major research methodologies used in organizational behavior and social/personality psychology, and will focus on both…
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47896 Seminar in Meso OB

As organizational environments have become more dynamic and unpredictable, many organizations have responded by flattening their structures and deploying teams as a means of increasing flexibility, responsiveness, information gathering and processing capabilities.…
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47902 Structural Models

This course focuses on empirical research in labor economics. It covers two main topics: labor supply and human capital accumulation. For each of these topics, first theoretical models are presented and then focus is shifted to empirical approaches to estimating these models.

47909 Writing/Persuasive Arguments for Behavioral Science

Through this course, students will discuss and learn about the various aspects of writing research papers for the behavioral sciences. Students often get considerable training on designing empirical strategies and producing and describing results. This course focuses on…
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47952 Estimating Dynamic and Structural Models

The seminar is intended to provide students with hand-on training in some cutting edge empirical frameworks and models. The topics we will cover would include (but are not limited to): latent class models, hidden Markov models, Bayesian learning models, single agent…
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47954 Human and Algorithmic Bias

The purpose of this course is to help students develop an economic perspective on algorithmic bias and related social and policy issues. To this end, we will read and discuss (1) classic economics, psychology and sociology papers on human bias and discrimination, (2)…
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