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A little bit of Stata programming goes a long way..


  • Christopher F. Baum

    () (Boston College
    DIW Berlin)


This tutorial will discuss a number of elementary Stata programming constructs and discuss how they may be used to automate and robustify common data manipulation, estimation and graphics tasks. Those used to the syntax of other statistical packages or programming languages must adopt a different mindset when working with Stata to take full advantage of its capabilities. Some of Stata's most useful commands for handling repetitive tasks: -forvalues-, -foreach-, -egen-, -local- and -matrix- are commonly underutilized by users unacquainted with their power and ease of use. While relatively few users may develop ado-files for circulation to the user community, nearly all will benefit from learning the rudiments of use of the -program-, -syntax- and -return- statements when they are faced with the need to perform repetitive analyses. Worked examples making use of these commands will be presented and discussed in the tutorial.

Suggested Citation

  • Christopher F. Baum, 2005. "A little bit of Stata programming goes a long way..," Boston College Working Papers in Economics 612, Boston College Department of Economics.
  • Handle: RePEc:boc:bocoec:612

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    References listed on IDEAS

    1. Watson, Ian, 2005. "Further processing of estimation results: Basic programming with matrices," Stata Journal, StataCorp LP, vol. 5(1), pages 1-9.
    2. Nicholas J. Cox, 2001. "Speaking Stata: How to repeat yourself without going mad," Stata Journal, StataCorp LP, vol. 1(1), pages 86-97, November.
    3. Ian Watson, 2005. "Further processing of estimation results: Basic programming with matrices," Stata Journal, StataCorp LP, vol. 5(1), pages 83-91, March.
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    More about this item


    Stata; macros; foreach; forvalues; egen; matrix; program; syntax; return;

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C87 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Econometric Software


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