Panel Data Toolbox for MATLAB
Panel Data Toolbox v2.0 is a new package for MATLAB that includes functions to estimate the main econometric methods of panel data analysis. The package covers the standard fixed, between and random effects methods, that are extended to allow for instrumental variables, as well as spatial panel data specifications.
Journal paper describing the functionality of the toolbox can be found here:
https://ideas.repec.org/a/jss/jstsof/v076i06.html
Copyright 2013-2019 Inmaculada C. Álvarez, Javier Barbero, José L. Zofío
Cite As
Álvarez, Inmaculada C.; Barbero, Javier and Zofío, José L, (2017) A Panel Data Toolbox for MATLAB. Journal of Statistical Software. Volume 76, Issue 6, pp 1-27. http://dx.doi.org/10.18637/jss.v076.i06
Comments and Ratings (3)
MATLAB Release Compatibility
Platform Compatibility
Windows macOS LinuxCategories
Tags
Community Treasure Hunt
Find the treasures in MATLAB Central and discover how the community can help you!
Start Hunting!Discover Live Editor
Create scripts with code, output, and formatted text in a single executable document.
examples
examplesjss
numericalchecks
paneldata/estimation
paneldata/stafun
paneldata/tests
paneldata/util
unittests
Select a Web Site
Choose a web site to get translated content where available and see local events and offers. Based on your location, we recommend that you select: .
Select web siteYou can also select a web site from the following list:
Americas
- América Latina (Español)
- Canada (English)
- United States (English)
Europe
- Belgium (English)
- Denmark (English)
- Deutschland (Deutsch)
- España (Español)
- Finland (English)
- France (Français)
- Ireland (English)
- Italia (Italiano)
- Luxembourg (English)
- Netherlands (English)
- Norway (English)
- Österreich (Deutsch)
- Portugal (English)
- Sweden (English)
- Switzerland
- United Kingdom (English)
Thanks for a great toolbox. One little issue is the Walt test för joint significance when used to robust standard errors. It seems to use the wrong number of degrees of freedom so that it can e.g. produce a negative F-statistic in this case. To take a concrete example I have a balanced panel with N =17 and T=24, this code panel(Paneldata.Bank_number, Paneldata.Time, y1_consumer, [X1_consumer], 'fe','vartype', 'cluster','clusterid',Paneldata.Time) gives Wald F(96,23) and without the clustered standard errors it gives F(96,295).