Resources on Computation (Old!)
Compiled by Gabriel Mihalache

This list of resources related to computation and programming for Economics has not been updated in quite a few years, and therefore it predates the proliferation of AI coding assistance and related technology. It remains here largely for historical purposes. It might eventually receive an update. Caveat emptor.

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Lecture Notes, General Resources

• Jesús Fernández-Villaverde lecture notes
• Pablo A. Guerron-Quintana lecture notes
• Wouter J. den Haan lecture notes
• Kenneth L. Judd lecture notes and git
• Foundations of Computational Economics online, video lecture notes by Fedor Iskhakov
• Eric Sims' notes on solving linear RE models (local methods)
• Pascal Michaillat's notes and video lectures on unemployment, search, frictional markets
• QuantEcon: theory, Python, Julia
• Open Source Macroeconomics Laboratory Bootcamp BFI, U Chicago
• RED (code) appendices, mostly Fortran and MATLAB
• Econ-ARK, structural modeling of economic choices of heterogeneous agents (Python)
• Applied Macroeconomics Forum

Fortran

Compilers and IDEs

• Intel oneAPI Toolkits are free and include Fortran and C++ compilers, plus libraries like MKL and MPI
• NVIDIA HPC SDK is freely available, with GPGPU support via CUDA, OpenMP, and OpenACC
• Windows Subsystem for Linux for Windows 10+ allows you to install gfortran, MPI, and other open source libraries
• Fortran language support for Visual Studio Code, now with Intel OneAPI support
• SimplyFortran is a commercial all-in-one option for gfortran on Windows
• Fortran-Lang's list of compilers

Language and Libraries

• Fortran-Lang's list of packages
• Modern Fortran: Building efficient parallel applications, free to read online/"live book"
• Grey Gordon lecture notes
• FortranWiki
• MPI Tutorial (Youtube), to get started with parallel computing across multiple computers
• Fortran for C Programmers from the LLVM project
• Code for Dynamic General Equilibrium Modelling by Burkhard Heer and Alfred Maußner
• b-splines for interpolation in 1-6D
• ogpf, Object Based Interface to GnuPlot from Fortran
• MINPACK and NLESolver-Fortran for solutions to systems of nonlinear equations
• NLopt for constrained maximization with local or global methods. For Fortran use these much higher quality bindings
• A note on my Fortran+MATLAB workflow, to easily save and load binary data with full precision

MATLAB

• My GPU code examples: the income fluctuation problem and a sovereign default model
• Dynare for local methods, deterministic/perfect foresight, filtering and more
• The Bayesian Estimation, Analysis and Regression toolbox (BEAR) is a comprehensive (Bayesian Panel) VAR toolbox for forecasting and policy analysis.
• Matlab and Dynare Codes by Eric Sims
• OccBin for local methods with occasionally binding constraints
• RISE Toolbox for solution and estimation of Markov Switching Rational Expectations
• A toolbox for VAR analysis, by Ambrogio Cesa-Bianchi
• Lilia Maliar publications and code appendices (incl applications of machine learning)
• Chebyshev and Smolyak approximation by Robert Kirkby
• Chebfun for Chebyshev interpolation and approximation

C++

• Intel oneAPI Toolkits are free and include Fortran and C++ compilers, plus libraries like MKL and MPI
• C++ Wiki and language reference
• Armadillo templating library for vectors, matrices and higher dimension arrays
• SG++, the sparse grid toolbox
• Tasmanian, a collection of robust libraries for high dimensional integration and interpolation, including adaptive grids
• Solvers and maximization: NLopt, dlib, Ceres Solver
• Akima splines for mitigating oscillations of interpolation
• Guide on mixing C++11 and Fortran 2008
• clang-format for consistent code formatting and style

Julia

• Quantitative Economics with Julia
• The Jupyter Notebook
• Optimization: JuMP, including NLopt.jl
• Root-finding, systems of equations: NLsolve.jl and Complementarity.jl
• Interpolations.jl for B-Splines
• Florian Oswald's projects, including adaptive sparse grids and MSM optimization
• Old-style distributed computing using MPI.jl
• Julia for Economists 2022, video lectures on YouTube, by Cameron Pfiffer

Machine Learning Methods in Macroeconomics

• Financial Frictions and the Wealth Distribution, Fernández-Villaverde et al.
• Flux.jl for neural networks in Julia; TensorFlow for Python
• A minimalist Flux tutorial for a simple classifier
• neural-fortran for neural networks in Fortran, parallelized on the CPU

LaTeX and Graphics

• Mathcha.io online mathematics + diagrams editor
• TikZ for programmatic vector graphics
• BibTeX Tidy will reformat and de-duplicate your bibliographies
• matlab2​tikz exports MATLAB figures to TikZ code
• TikZiT WYSIWYG editor for TikZ diagrams
• Ipe Diagram Editor, vector- and LaTeX-based
• Detexify, sketch symbol to find its name in LaTeX
• PDFtk for splitting, merging and cropping PDFs
• excel2latex addon for Excel for quick table design

Stata

• stata_kernel allows you to run Stata interactively in Jupyter notebook
• HAMILTONFILTER module for the Hamilton (2017) filter

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