The Hausman test in Panel Data Analysis by using STATA

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The Durbin-Wu-Hausman test (also called Hausman specification test) is a statistical hypothesis test in econometrics named after James Durbin, De-Min Wu, and Jerry A. Hausman. The test evaluates the consistency of an estimator when compared to an alternative, less efficient estimator which is already known to be consistent. It helps one evaluate if a statistical model corresponds to the data.
It is also applied in the context of linear regression to decide whether to choose a fixed effect model or a random effect model.
The null hypothesis for Hausman’s test, in this case, is that we use the random-effects model because it is more efficient. On the other hand, the alternative hypothesis tells us that we should use the fixed effects model since the random effect model is not consistent.
The hypotheses:
+ H0: Random-effects (RE) is preferred
+ H1: Fixed-effects (FE) is preferred
By applying the procedure for Hausman’s test given above we can decide which model (Fixed Effects vs Random Effects) is better. We can also apply Hausman’s test to check for the endogeneity of variables in a regression model.

[@rockfordcorpinc7044]

Thank you for a splended and simple explanation of the Hausman test. Teachers: THIS is how people learn in the best educational way

[@HKTStata]

Wow, thank you!

[@mageswarikanawathy-qi2ju]

I am much delighted by your simple yet detailed explication of the Hausman test... Thank you!

[@HKTStata]

Glad it was helpful!

[@nebagenta7048]

Probably the most comprehensive tutorial for Hausman test Ive found. I love how you walk through every little step. Thanks!

[@Amoralfitness0511]

Thanks ! I finally found it - the Hausman test in practice.

[@IvoPetrov13]

Great video, however there is one small inconsistency. Initially (around 1:35), you point out that having a p-value above 0,05 means that you accept the null-hypothesis and select RE. At the end of the video, with the data example, you get a p-value of 0, which means you reject the null hypothesis and go with the alternative - FE. However, you say that you "accept the null hypothesis" (5:44), which is incorrect.

[@HKTStata]

You are correct! Thanks very much for your comment, it must be "... reject the null hypothesis and go with the alternative - FE".

[@TheGaGaS1985]

This comment makes understanding it more complex. I thought it is "having a p-value BELOW 0.05 means that you accept the null-hypothesis" that random effects model is better.

[@rafly2142]

Thank you for explaining the Hausman test for me! You made it easy for me to wrap my head around the information.

[@chewbakka9943]

Thank you so much for great information about the Hausman test.

[@dodoexotic]

I now have a clear understanding. Thank you!

[@pika_3]

Wonderful! Simple and quite informative

[@vinciyeung2417]

Tt is a very helpful video to understand the Hausman test. You are a legend

[@ArtisticPrints-ow3vx]

Short and simple thank you very helpful

[@Cristinamorales]

Excellent. Thank you so much. Subscribed.

[@HKTStata]

Thanks and welcome

[@user-fj4ot2yb5o]

Very well explained the Hausman test. Thank you sir

[@fastabichannel3527]

I found your presentation very helpful and explained so clearly thank you :)

[@LongNguyen-pu9fh]

So well explained the Hausman test.

[@airjetfighter4325]

Thanks. It helped me in panel data analysis.

[@keyerteam7270]

Hi. Thank you for making it so easy. You explained in such a wonderful way.

[@LongNguyen-pu9fh]

Excellent Stata beginner tutorial.

[@nhilinh7170]

Great STATA Tutorial.

[@NicolasInfiel]

Very helpful information about the Hausman test

[@JoeMeels]

Really good Stata video guide

[@HKTStata]

Glad you liked it

[@dombatersesat8280]

Very good sum up

[@gitar2330]

Super helpful! Thank you!

[@gaminglegobuilder]

Thank you!! You explained everything well!!

[@carlosvallalive8935]

good job. Keep it up.

[@HKTStata]

Thank you, I will

[@Periodismo_Militar]

very helpful. thanx for sharing :)

[@WaterJo-ks8yv]

Fantastic video. Thanks a lot!

[@suzana2340]

thanks.

[@dka9756]

Hi, I have 4 dependent variables, when I run the hausman test for each one of them, 2 of them validate the random effect model, and the 2 others validate the fe model. Now which one to choose since I'm doing a multivariate regression? And on top of that, some of my dummy variables (useful ones) are omitted under fixed effect, but I really need to use them.

[@HKTStata]

Dummy variables are typically time-varying variables in panel data, and they are omitted in fixed-effects models. If you want to retain them, you must use between-effects model instead of FE. The selection process remains the same, only the between-effects model is not as commonly utilized. You can search and study about between-effects model. Good luck!

[@alljkkjj]

If the Hausman test favors the fe model over the re model, can I still proceed with using the re model? as re robust is only giving me good results.I am taking robust options after fe and re, general fe and re model is giving very bad result.
Also,robust fe and re model is not effective to test hausman.
So may i use general fe and re models hausman test in robust fe and re model selection?

[@HKTStata]

+ If the Hausman test favors the fe model over the re model, can I still proceed with using the re model?
No - because it means that re model is not appropriate to your data.
+ may i use general fe and re models hausman test in robust fe and re model selection?
No, the hausman test can not run with robust option
+ I recommend you to add or remove variables for the best results. Good luck!