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Dynamic Stochastic Integration of Climate and Economy
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2009 Lectures at Peking and Renmin Universities
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Numerical Methods Course by Judd
Lecture 05: Nonlinear Equations
Lecture 06: Constrained optimization theory and methods
Lecture 07: Constrained optimization applications
Lecture 08: Structural Estimation I
Lecture 09: Finite-difference ODEs
Lecture 13: Approximation I
Lecture 21: Perturbation methods
Lecture 01: Introduction
Lecture 02: Computer Arithmetic
Lecture 03: Linear algebra and equations
Lecture 04: Unconstrained optimization
Lecture 10: Version Control Using Git
Lecture 11: Automatic Differentiation
Lecture 12: Homotopy
Lecture 14: Numerical quadrature MC qMC
Lecture 15: Dynamic optimization equilibrium NLCEQ
Lecture 16: Dynamic programming-discrete state
Lecture 17: Structural estimation II
Lecture 18: Dynamic programming-continuous state
Lecture 19: Projection methods I
Lecture 20: Projection Methods II
Lecture 22: Modern Approximation
Lecture 23: Dynamic Games
Lecture 24: Multi Objective Optimization
Lecture 25: Structural estimation III
Bonus Lecture: Macroeconomics
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Lecture 27: Concluding remarks
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Penn State 2021, March 18: MPEC, NFXP, Algorithms and Software
Penn State 2021, March 23: Not your grandfather’s confidence intervals
Penn State 2021, March 25: Macro-based empirical micro
Penn State 2021, March 25: SimEcon: A possible path for economics
Penn State 2021: Comments related to student presentations
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Approximation
Doraszelski-Judd Paper and RAND’s rejection
Dynamic Programming
Judd Maliar Maliar
Quadrature
Structural Estimation
Penn State 2012
Penn State 2013
University of Zurich 2020
Bonus Lecture: Macroeconomics
Lecture 01: Introduction
Lecture 02: Computer Arithmetic
Lecture 03: Linear algebra and equations
Lecture 04: Unconstrained optimization
Lecture 05: Nonlinear Equations
Lecture 06: Constrained optimization theory and methods
Lecture 08: Structural Estimation I
Lecture 09: Finite-difference ODEs
Lecture 10: Version Control Using Git
Lecture 11: Automatic Differentiation
Lecture 12: Homotopy
Lecture 13: Approximation I
Lecture 14: Numerical quadrature MC qMC
Lecture 15: Dynamic optimization equilibrium NLCEQ
Lecture 16: Dynamic programming-discrete state
Lecture 17: Structural estimation II
Lecture 18: Dynamic programming-continuous state
Lecture 19: Projection methods I
Lecture 20: Projection Methods II
Lecture 21: Perturbation methods
Lecture 22: Modern Approximation
Lecture 23: Dynamic Games
Lecture 24: Multi Objective Optimization
Lecture 25: Structural estimation III
Lecture 26: DSICE
Lecture 27: Concluding remarks
Lecture 07: Constrained optimization applications
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