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If you'd like, I can help you from your output or walk you through setting up your panel data correctly for this test. xtserial package - Stata
: You can view the Full PDF Article on the Stata Journal website. Key Usage Tips
However, xtserial is not part of official Stata; it is a user-written add-on that must be installed from the Boston College Statistical Software Components (SSC) archive. This paper details the installation process, verification, and common pitfalls. xtserial stata install
Serial correlation in the idiosyncratic errors of panel data models can bias standard errors and lead to invalid inference. The user-written command xtserial (Drukker, 2003) implements a robust test for first-order serial correlation in linear panel-data models with random or fixed effects. This paper provides a comprehensive guide to installing xtserial in Stata, covering both official and alternative methods, addressing common errors, and illustrating the command’s use with an empirical example.
set proxy_addr "proxy.youruniversity.edu" set proxy_port 8080 If you'd like, I can help you from
In a research pipeline, ensure your do-file installs the package automatically:
Because xtserial is not a built-in Stata command, you must install it from the Stata Journal archives. While many users try ssc install , this specific package is typically hosted through the net command suite. Follow these steps in your Stata command window: This paper provides a comprehensive guide to installing
You may already have the file, but it might be corrupted or saved in a location Stata isn't looking at.
If you run xtserial and get an error like version 8.0 not supported , you may need to update your Stata executable or the xtserial package to the latest version via ssc install xtserial, replace .
Panel data combine time-series and cross-sectional dimensions, making them rich for analysis but also prone to serial correlation. While Stata’s built-in xtreg post-estimation commands (e.g., xtserial, xthrtest ) offer some diagnostics, the xtserial command—written by David M. Drukker (StataCorp)—provides a direct implementation of the Wooldridge (2002) test for serial correlation. This test is attractive because it works under general conditions and is robust to heteroskedasticity.