What’s new in statistics (longitudinal data/panel data)
Here is a complete list of what’s new with Stata’s
xt command suite:
New command xtunitroot
performs the Levin–Lin–Chu, Harris–Tzavalis, Breitung,
Im–Pesaran–Shin, Fisher-type, and Hadri Lagrange multiplier tests for unit roots on panel data.
Concerning existing estimation command
xtmixed:
xtmixed now allows modeling of the residual-error structure of
the linear mixed models. Five structures are available: independent,
exchangeable, autoregressive (AR), moving average (MA), and
unstructured. Use new option residuals(). Within
residuals(), you may also specify suboption by(varname)
to obtain heteroskedastic versions of the above
structures. For example, specifying residuals(independent, by(sex))
will estimate distinct residual variances for both males and females.
xtmixed has new options matlog and matsqrt,
which specify the matrix square root and matrix logarithm
variance-component parameterizations, respectively. Previously,
xtmixed supported the matrix logarithm parameterization
only. Now xtmixed supports both parameterizations, and the
default has changed to matsqrt. Previous default behavior
is preserved under version control.
xtmixed now supports time-series operators.
predict
after xtmixed now allows new option reses for
obtaining standard errors of predicted random effects (best linear unbiased predictions).
Concerning existing estimation command
xtreg:
Specifying xtreg, re vce(robust) now means
the same as xtreg, re vce(clusterpanelvar).
The new interpretation is robust to a broader
class of deviations. The old interpretation is available under
version control.
Similarly, specifying xtreg, fe vce(robust)
now means the same as xtreg, fe vce(clusterpanelvar)
in light of the new results by Stock and Watson (2008).
xtreg now allows the inrange qualifier.
All xt estimation commands now allow Stata’s new factor-variable
varlist notation, with the exception of commands
xtabond,
xtdpd,
xtdpdsys, and
xthtaylor.
Also, estimation commands allow the standard set of
factor-variable–related reporting options.
Concerning existing estimation commands
xtmelogit and
xtmepoisson:
They have new option matsqrt, which allows you to explicitly
specify the default matrix square-root parameterization.
They now support time-series operators.
As of Stata 10.1, existing estimation commands
xtmixed, xtmelogit, and xtmepoisson
require that random-effects specifications contain an explicit level
variable (or _all) followed by a colon. Previously, if these
were omitted, a level specification of _all: was assumed,
leading to confusion when only the colon was omitted. To avoid this
confusion, omitting the colon now produces an error, with previous
behavior preserved under control.
Existing command xttab
now returns the matrix of results in r(results) and the number of panels in r(n).
Reference
Stock, J. H., and M. W. Watson. 2008.
Heteroskedasticity-robust standard errors for fixed effects panel data regression.
Econometrica 76: 155–174.
We use cookies to ensure that we give you the best experience on our website—to enhance site navigation, to analyze usage, and to assist in our marketing efforts. By continuing to use our site, you consent to the storing of cookies on your device and agree to delivery of content, including web fonts and JavaScript, from third party web services.
Cookie Settings
Privacy policy
Last updated: 16 November 2022
StataCorp LLC (StataCorp) strives to provide our users with exceptional products and services. To do so, we must collect personal information from you. This information is necessary to conduct business with our existing and potential customers. We collect and use this information only where we may legally do so. This policy explains what personal information we collect, how we use it, and what rights you have to that information.
These cookies are essential for our website to function and do not store any personally identifiable information. These cookies cannot be disabled.
Advertising and performance cookies
This website uses cookies to provide you with a better user experience. A cookie is a small piece of data our website stores on a site visitor's hard drive and accesses each time you visit so we can improve your access to our site, better understand how you use our site, and serve you content that may be of interest to you. For instance, we store a cookie when you log in to our shopping cart so that we can maintain your shopping cart should you not complete checkout. These cookies do not directly store your personal information, but they do support the ability to uniquely identify your internet browser and device.
Please note: Clearing your browser cookies at any time will undo preferences saved here. The option selected here will apply only to the device you are currently using.