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Kenneth L. Judd
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DICE_N vs DICE_CJL
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CJL-flexible time period
CJL1
CJL10
CJL2
CJL4
CJL8
CJLhalf
CJLquarter
Terminal Value Function
DICE-N and Solvers
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output
Notes in Nordhaus original code
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Documentation for “Tyranny of the Top Five”
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General Discussion
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CJL – one half year
GAMS Code
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Doraszelski-Judd Paper and RAND’s rejection
Dynamic Programming
Judd Maliar Maliar
Quadrature
Structural Estimation
Penn State 2012
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University of Zurich 2020
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 07: Constrained optimization applications
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
The Fed and its Models
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Is extra computational power useful?
Is macro underfunded?
Pictures are important
Questions about FRB/US
We knew 2008 could happen
Working Papers
Kenneth L. Judd
Main Menu
About Us
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Blog
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books
Che-Lin Su Conference
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Program
Conferences
Menu Toggle
ICE 2005
ICE 2005 Participants
ICE 2005 Personnel
ICE 2005 Photos
ICE 2005 Poster Session Winners
ICE 2005 Program Description
ICE 2005 Schedule
ICE 2006
ICE 2006 Participants
ICE 2006 Personnel
ICE 2006 Program Description
ICE 2006 Schedule
ICE 2006 Supplemental Resources
ICE 2007
ICE 2007 Personnel
ICE 2007 Program Description
ICE 2007 Schedule
ICE 2007 Supplemental Resources
ICE 2008
ICE 2008 Personnel
ICE 2008 Program Description
ICE 2008 Schedule
ICE 2008 Student Presentations
ICE 2008 Supplemental Resources
ICE 2009
ICE 2009 Personnel
ICE 2009 Photos
ICE 2009 Program Description
ICE 2009 Schedule
ICE 2009 Student Presentations
ICE 2010
ICE 2010 Personnel
ICE 2010 Program Description
ICE 2010 Schedule
ICE 2010 Supplemental Materials
ICE 2011
ICE 2011 Personnel
ICE 2011 Program Description
ICE 2011 Schedule
ICE 2012
Benjamin Skrainka’s Reading List
ICE 2012 Personnel
ICE 2012 Program Description
ICE 2012 Schedule
nICE 2016
Contact
Contact Us
DICE_N vs DICE_CJL
Menu Toggle
CJL-flexible time period
CJL1
CJL10
CJL2
CJL4
CJL8
CJLhalf
CJLquarter
Terminal Value Function
DICE-N and Solvers
DICE with unconstrainted investment and Solvers
Nordhaus original code
output
Nordhaus unconstrained investment
output
Notes in Nordhaus original code
template
Documentation for “Tyranny of the Top Five”
Dynamic Stochastic Integration of Climate and Economy
Economics and Computation
Menu Toggle
American Economic Review
Econometrica
Economists vs Computation
Europe: Here’s an opportunity! Take it!
Games and Economic Behavior
Long Live Ludd!
Review of Economic Studies
Economics vs. Science
FlatTax+40
Homepage
Initiative for Computational Economics
judd home page
Judd Lecture Materials
Ken Judd Home Page
Ken Judd Home Page Old
Landing Page
Open Science Letter
Menu Toggle
General Discussion
Introduction
Results
CJL – one half year
GAMS Code
CJL – one quarter year
GAMS Code
CJL – One Year
GAMS Code
DICE2007 – Ten Year Time Step
GAMS Code
Papers
posts page
Privacy Policy
Program
Published Papers
Research Projects
Skrainka Lecture Materials
Teaching
Menu Toggle
Penn State Numerical Methods
Penn State 2014
DownWithLogLin
DSICE
FAQ
Iterative Methods
Penn State 2015
Lecture Notes
Michelangeli Papers
Papers
XSEDE
Penn State 2017
Penn State 2018
Penn State 2019
Penn State 2023
Penn State 2011
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
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 07: Constrained optimization applications
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
The Fed and its Models
Menu Toggle
Is extra computational power useful?
Is macro underfunded?
Pictures are important
Questions about FRB/US
We knew 2008 could happen
Working Papers
Dynamic Stochastic Integration of Climate and Economy
Coming soon.