BEA511 Topics in Dynamic Modeling and Optimal Controls

• Topics

  Theoretical Topics

  The objective is to provide students with a capability to formulate and analyze problems in different fields of economics and management science using the tools of optimal control theory. Deterministic and stochastic theory will be presented. Continuous time problems are emphasized. Applied examples (applications) constitute the main part. Classical Hamiltonian formulation with focus on the Maximum Principal (MP) including different constraining relations and their transversality conditions are addressed. Modern formulation applying the value function concept through Dynamic Programming (DP) and its associated Hamilton-Jacobi-Bellman equation (HJB) are introduced to facilitate and bridge the gap to the course BEA514- Topics in numerical optimization.

  Stochastic optimal control problems are incorporated in this part.

  The relations between MP and DP formulations are discussed. The main focus is put on producing feedback solutions from a classical Hamiltonian formulation. Interpretations of theoretical concepts are emphasized, e.g. that the Hamiltonian is the shadow price on time.

  Differential games are introduced.

  The ideas of Equivalent Representation and The Principal of Extension are introduced.

  Finite and infinite time horizons are treated. Relaxation of the optimality concept is introduced through the notion of "Catching-Up optimality", which may apply if the classical value becomes infinite.

  Applied Topics

  Among others, we study applications such as Ramsey's growth model, production and storage planning, advertising, management of (non-) renewable resources, Pigouvian taxation and pollution control, road planning, maintenance and sale and allocation of private wealth on consumption, secure and risky investments. Real options are presented in a generic setting.

  Topics will be lectured in the following sequence:

  • Short summary of difference- and differential equations and stability analysis.
  • Basic concepts and ideas. Global optimality. Shadow prices and theoretical and practical interpretations of basic notions e.g. transversality conditions.
  • Introductions to applied control problems. Necessary and sufficient conditions.
  • Discounting and present value formulations. Extensions of optimality in infinite horizon problems.
  • Constrained problems: State and mixed restrictions. Bang-bang and singular controls.
  • Dynamic programming (DP) and the Hamilton-Jacobi-Bellman (HJB) equation.
  • Summary of stochastic processes. Stochastic feedback control. Merton´s example.
  • Differential games - open and closed loop policies.

• Learning outcome

  After completing the course, the candidates can:

  Knowledge

  • evaluate dynamic and stochastic effects on economic quantities and resources depending on policy choices
  • identify practical limitations of present-day numerical solution approaches

  Skills

  • review, assess and utilize relevant scientific papers addressing dynamic optimization
  • formulate and model operational management tasks evolving in time
  • identify potential intrinsic deterministic chaos in the formulated model

  General competence

  • take part in and manage interdisciplinary research involving dynamic modelling and decision tasks in an operational setting
  • analyze models concerning dynamic as well as structural stability
  • identify potential or implicit conserved quantities (conservation laws)
  • formulate and analyze problems in different fields of economics and management science applying the tools of classical and modern theories of optimal control and the calculus of variation.

• Teaching

  Topics/papers will be partly lectured by the course responsible and partly presented for discussion in the class by students.

  The course is compressed into four parts. Each part has two days of lecturing for 4 hours.

• Restricted access

  • PhD candidates at NHH.
  • PhD candidates at Norwegian institutions.
  • PhD candidates at other institutions.
  • PhD candidates from the ENGAGE.EU alliance.
  • Motivated master student’s may be admitted after application but are subject to the approval from the course responsible on a case by case basis.

• Required prerequisites

  Knowledge of medium advanced calculus and some familiarity with differential and difference equations and introductory probability theory.

• Compulsory Activity

  • Active participation in class
  • Exercises/assignments during the course

  Compulsory activities (work requirements) are valid for one semester after the semester they were obtained.

• Assessment

  Written individual assignment (100%). The assignments are made available two weeks before the final hand in through WiseFlow.

  Re-take is offered the semester after the course was provided for students with valid compulsory activities (work requirements).

• Grading Scale

  Pass/Fail

• Computer tools

  The use of high-level programming in Maple and MatLab is an integrated part of the course.

• Literature

  Main topics and applications are presented in part two of the textbook "Dynamic Optimization: The Theory of Variations and Optimal Control in Economics and Management" by Morton I. Kamien and Nancy L. Schwartz in the series "A series of Volumes in dynamic economics: Theory and applications" volume 4.

  Additional topics are given in lecture notes and selected journal articles.