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A comparison of programming languages in macroeconomics

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  • Aruoba, S. Borağan
  • Fernández-Villaverde, Jesús

Abstract

We solve the stochastic neoclassical growth model, the workhorse of modern macroeconomics, using C++14, Fortran 2008, Java, Julia, Python, Matlab, Mathematica, and R. We implement the same algorithm, value function iteration, in each of the languages. We report the execution times of the codes in a Mac and in a Windows computer and briefly comment on the strengths and weaknesses of each language.

Suggested Citation

  • Aruoba, S. Borağan & Fernández-Villaverde, Jesús, 2015. "A comparison of programming languages in macroeconomics," Journal of Economic Dynamics and Control, Elsevier, vol. 58(C), pages 265-273.
    • Handle: RePEc:eee:dyncon:v:58:y:2015:i:c:p:265-273
    DOI: 10.1016/j.jedc.2015.05.009
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    References listed on IDEAS

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    1. Tauchen, George, 1986. "Finite state markov-chain approximations to univariate and vector autoregressions," Economics Letters, Elsevier, vol. 20(2), pages 177-181.
    2. Aruoba, S. Boragan & Fernandez-Villaverde, Jesus & Rubio-Ramirez, Juan F., 2006. "Comparing solution methods for dynamic equilibrium economies," Journal of Economic Dynamics and Control, Elsevier, vol. 30(12), pages 2477-2508, December.
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    Cited by:

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    2. Bognanni, Mark & Zito, John, 2020. "Sequential Bayesian inference for vector autoregressions with stochastic volatility," Journal of Economic Dynamics and Control, Elsevier, vol. 113(C).
    3. Stephen J. Terry, 2017. "Alternative Methods for Solving Heterogeneous Firm Models," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 49(6), pages 1081-1111, September.
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    5. Mingzhuo Deng & Pablo A. Guerron-Quintana & Lewis Tseng, 2023. "Parallel Computation of Sovereign Default Models," Computational Economics, Springer;Society for Computational Economics, vol. 62(3), pages 1047-1085, October.
    6. Yifei Wu & Jeffrey H Dorfman, 2018. "Reducing residential mortgage default: Should policy act before or after home purchases?," PLOS ONE, Public Library of Science, vol. 13(7), pages 1-23, July.
    7. Paul Carrillo‐Maldonado, 2023. "Partial identification for growth regimes: The case of Latin American countries," Metroeconomica, Wiley Blackwell, vol. 74(3), pages 557-583, July.
    8. Yifei Wu & Jeffrey H. Dorfman & Brady E. Brewer, 2021. "The susceptibility of farmland loans to default under falling farmland and commodity prices," Agricultural Economics, International Association of Agricultural Economists, vol. 52(4), pages 561-574, July.
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    10. Duarte, Victor & Duarte, Diogo & Fonseca, Julia & Montecinos, Alexis, 2020. "Benchmarking machine-learning software and hardware for quantitative economics," Journal of Economic Dynamics and Control, Elsevier, vol. 111(C).

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    More about this item

    Keywords

    Dynamic equilibrium economies; Computational methods; Programming languages;
    All these keywords.

    JEL classification:

    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • C68 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computable General Equilibrium Models
    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications

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