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A case study in efficient programming in Stata and Mata: Speeding up the ardl estimation command

Author

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  • Daniel C. Schneider

    (Max Planck Institute for Demographic Research)

  • Sebastian Kripfganz

    (University of Exeter)

Abstract

The user-written package ardl, first released in 2014, estimates autoregressive distributed lag (ARDL) time-series models and provides the popular Pesaran, Shin, and Smith (2001, Journal of Applied Econometrics) bounds testing procedure for a long-run relationship. In this presentation, the statistics and application side of the command take a back seat and give way to a discussion of the algorithms used under the hood of ardl. Efficient programming is critical for ardl for two reasons: optimal lag selection and for obtaining critical values via simulation. This presentation will use the "case study" of the ardl estimation command to discuss efficient programming in Stata and Mata. Various programming concepts (compilation, argument passing, data types, pointer variables, etc.) and their implementation in Stata/Mata will be explained, as well as various finer Mata-specific topics (fast matrix indexing, matrix inversion, etc.). The overall message is that coding based on common sense, knowledge of the workings of Stata/Mata, and knowledge of linear algebra goes a long way when trying to write high-performance code and in many cases is to be preferred to the tedium of moving to a lower-level programming language like C/C++.

Suggested Citation

  • Daniel C. Schneider & Sebastian Kripfganz, 2017. "A case study in efficient programming in Stata and Mata: Speeding up the ardl estimation command," German Stata Users' Group Meetings 2017 04, Stata Users Group.
    • Handle: RePEc:boc:dsug17:04
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    References listed on IDEAS

    as
    1. Sebastian Kripfganz & Daniel C. Schneider, 2023. "ardl: Estimating autoregressive distributed lag and equilibrium correction models," Stata Journal, StataCorp LP, vol. 23(4), pages 983-1019, December.
    2. Sebastian Kripfganz & Daniel C. Schneider, 2023. "ardl: Estimating autoregressive distributed lag and equilibrium correction models," Stata Journal, StataCorp LP, vol. 23(4), pages 983-1019, December.
    3. M. Hashem Pesaran & Yongcheol Shin & Richard J. Smith, 2001. "Bounds testing approaches to the analysis of level relationships," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 16(3), pages 289-326.
    4. Paresh Kumar Narayan, 2005. "The saving and investment nexus for China: evidence from cointegration tests," Applied Economics, Taylor & Francis Journals, vol. 37(17), pages 1979-1990.
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