Serguei Maliar

CURRENT RESEARCH:

  1. Kenneth L. Judd, Lilia Maliar and Serguei Maliar, (2016). “Lower Bounds on Approximation Errors to Numerical Solutions of Dynamic Economic Models”, Econometrica (forthcoming).

  2. Cristina Arellano, Lilia Maliar, Serguei Maliar and Viktor Tsyrennikov, (2016). “Envelope Condition Method with an Application to Default Risk Models”, Journal of Economic Dynamics and Control 69, 436-459.

  3. Lilia Maliar and Serguei Maliar, (2016). “Ruling Out Multiplicity of Smooth Equilibria in Dynamic Games: A Hyperbolic Discounting Example”, Dynamic Games and Applications 6(2), 243–261, in special issue "Dynamic Games in Macroeconomics" edited by Edward C. Prescott and Kevin L Reffett.

  4. Lilia Maliar, Serguei Maliar, John Taylor and Inna Tsener (2015). “A Tractable Framework for Analyzing a Class of Nonstationary Markov Models”, NBER 21155.

  5. Lilia Maliar and Serguei Maliar, (2015). “Merging Simulation and Projection Aproaches to Solve High-Dimensional Problems with an Application to a New Keynesian model”, Quantitative Economics 6, 1-47 (LEAD ARTICLE).

  6. Kenneth L. Judd, Lilia Maliar, Serguei Maliar and Rafael Valero, (2014). “Smolyak Method for Solving Dynamic Economic Models: Lagrange Interpolation, Anisotropic Grid and Adaptive Domain”, Journal of Economic Dynamic and Control 44(C), 92-123.

  7. Kenneth L. Judd, Lilia Maliar, Serguei Maliar and Inna Tsener, (2014). “How to solve dynamic stochastic models computing expectations just once”, NBER 17418.

  8. Lilia Maliar and Serguei Maliar, (2013). “Envelope Condition Method versus Endogenous Grid Method for Solving Dynamic Programming Problems”, Economic Letters 120, 262-266.

ASSOCIATE EDITOR:

    - Journal of Economic Dynamics & Control

ADVISER:

    - Canadian Central Bank, Model Development Division

    - Income Club Investment Company

CONTRIBUTOR:

    - Becker Friedman Institute at the University of Chicago, Macro Financial Modeling group

Active NSF grant, 08/15/2016- 07/31/2019:

    - Analyzing non-stationary and unbalanced growth economic models, SES-1559407.

HANDBOOK OF COMPUTATIONAL ECONOMICS:

    Lilia Maliar and Serguei Maliar, (2014). "Numerical Methods for Large Scale Dynamic Economic Models” in: Schmedders, K. and K. Judd (Eds.), Handbook of Computational Economics, Volume 3, Chapter 7, 325-477, Amsterdam: Elsevier Science.

    Summary. This chapter provides an introduction to perturbation, projection, value function iteration, Smolyak, endogeneous grid and envelope condition methods, parallel computation, supercomputers, GPUs and many other methods and shows how to use these methods to solve dynamic stochastic economic models with hundreds of state variables. Check our MATLAB codes.