Advanced Industrial Economics, Spring 2023, KU Leuven

The course provides a graduate-level introduction (master and Ph.D.) to the topics and methods of Industrial Organization (IO). The course presents theoretical and empirical tools to analyze consumer behavior and strategic interaction between firms in various industries and to evaluate business strategies and public policies. The course is designed to provide a solid understanding of the structure of markets where policy issues related to antitrust and regulation and business implications of pricing, innovation, and competition are frequently publicly debated.

Advanced Industrial Organization (Graduate School), Spring 2021, University of Gothenburg

• Lecture: Demand estimation

• Lecture: Estimation oligopoly models (conduct lab)

• Lecture: Estimation of entry models

• Lecture: Estimation collusion models

• Lecture: Meager simulation

Advanced Micro Theory (Graduate School), Spring 2021, University of Gothenburg

• Lectures: Bounded rationality

• Lectures: Matching markets

• Lectures: Contract theory - Moral hazard

Dynamic Methods (PhD), Fall 2019, KU Leuven

The course presents the theory and applications of optimization techniques used to solve complex economic problems under uncertainty.

Empirics: Various numerical and empirical applications from IO, macro, management, marketing, environmental economics, finance are presented.

Software: Julia scientific programming language is used.

• Introduction: Static optimization and transition to dynamics

• Dynamic programming: Foundations of dynamic analysis in economics - part 1

• Dynamic programming: Foundations and examples -part 2

• Discrete dynamic programming: Nested fixed-point algorithm (NXFP) and empirical applications

• Discrete dynamic programming: Alternative approaches of identification and estimation (CCP and NPL)

• Dynamic programming: Simulation approach

• Approximate dynamic programming (ADP): Foundations

• Approximate Dynamic Programming: Empirical implementation and applications

• Dynamic programming: Euler equation and its role in estimating dynamic economic models

• Recent topics on dynamic methods

Industrial Organization (master), Spring 2018, 2019, 2020 Stockholm School of Economics

• Lecture: Productivity and markups

• Lecture: Auctions

• Lecture: Networks industries

Dynamic Methods, Fall 2017, KU Leuven

• Lectures: Approximate Dynamic Programming and Economic Applications

Industrial Organization, Spring 2017, Stockholm School of Economics

• Lecture: Product differentiation

• Lecture: Auctions

• Lecture: Networks

Advanced Industrial Organization, Spring 2008-2014, University of Gothenburg

• Lecture: Demand Estimation

  • Data: berry1994Example.csv (CSV)

• Lecture:Lab1:Testing static oligopoly models

  • Data(Stat): dutch_coffee_2014.dta

  • Data(CSV): dutch_coffee_2014.csv

Industrial Economics, Fall 2008-2014, University of Gothenburg

• Lecture: Networks

Financial Econometrics, Spring 2012, University of Gothenburg

• Lecture: Nonstationarity

  • R code: Simulation AR(1) model

  • STATA code: Cointegration Example

  • Data: U.S. Treasury Bill

  • Log file: Cointegration Example

  • Figures: Cointegration Example

Advanced Industrial Organization II, Fall 2010

• Reading List lectures 1 and 3

  • Empirical Studies on Theory of the Firm and Vertical Integration

  • Empirical Contract Theory. Part I

  • Lab1: Empirical M&A analysis Data: computer_industry.dta