Note that users are NOT required to do this in order to run my published code.
STATA LOCAL INSTALL
Likewise, if you install an add-on on your local computer, it will not be available to your collaborators.īelow I describe how I set up my working environment to address these challenges. You could manually change this pathname every time a different person or different computer runs the code, but this solution is cumbersome for large projects with many lines of code. A project’s location may be /Users/jreif/my-project on one computer and /Users/coauthor/my-project on another computer. Using multiple environments makes it hard to define the pathname (location) of a folder. I work on several projects at the same time, access them from multiple computers (laptop, home, work), and share them with multiple coauthors. If you encounter any difficulties let me know. Try it out and see how easy (or not!) it is to reproduce my example analysis. The guide includes an accompanying AEA-compliant sample replication package that you are free to use as a template.
STATA LOCAL HOW TO
This guide describes how to set up a robust coding environment and write a “push-button” analysis in Stata.
![stata local stata local](https://www1.udel.edu/it/help/math-stat-software/stata/Stata_figure2sm.jpg)
Unfortunately, most researchers (myself included) received little or no training in how to organize projects, write code, or document analyses. The American Economic Association’s (AEA) new data and code availability policy aims to improve this situation by imposing professional standards for coding and documentation.
![stata local stata local](https://quotestats.com/topic/806043-stata-local-double-quotes-1004580.jpg)
Research suggests that the results from many published papers cannot be reproduced from the code and data provided by the original authors. Peer review rarely evaluates code, even though code often represents the bulk of the work.
![stata local stata local](https://www.princeton.edu/~otorres/Stata/dofile_files/image044.jpg)
These recent developments introduce complexity and the potential for non-transparent errors. Cutting edge analyses may require thousands or millions of lines of code written in multiple languages. Analyses employing confidential data must be performed remotely, often on a non-networked computer at a research data center. Research teams frequently include multiple people working at different universities. Researchers commonly estimate regressions with millions of observations derived from multiple datasets. Empirical research in economics has grown in importance thanks to improvements in computing power and the increased availability of rich datasets.