Hansen Test Eviews

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Nabila99
Posts: 1
Joined: Sun Jun 11, 2023 4:13 am

Hansen Test Eviews

Postby Nabila99 » Tue Jun 13, 2023 1:53 am

Good Afternoon.
It would be a great assistance for me if anyone can help me with my query.
How can I run Hansen test on eviews? (using GMM)
Any command to run the test or steps to follow?
note: I am using eviews 11 (student version)

GradyTurner
Posts: 1
Joined: Sat Jul 22, 2023 12:07 am

Re: Hansen Test Eviews

Postby GradyTurner » Sun Jul 23, 2023 3:32 am

To run the Hansen test in EViews 11
Step 1: Perform the GMM estimation
First, you need to estimate your GMM model. Make sure you have already set up your GMM specification and identified the instruments. For this example, I assume you have already run the GMM estimation and stored the results in a named equation object, let's call it "gmm_eq."

Step 2: Open the equation window
Go to the "Quick" menu, then select "Estimate Equation" or simply press "Ctrl + E."

Step 3: Load the GMM equation
In the equation window, click on the drop-down arrow next to "Equation" and select your GMM equation ("gmm_eq" in this case) from the list.

Step 4: Open the test options
Below the equation specification box, you will find a series of tabs. Click on the "Test" tab.

Step 5: Choose Hansen test
Under the "Test Equation" drop-down menu, select "Hansen (Overidentification) Test."

Step 6: Set options (if needed)
You can set additional options for the test, such as the confidence level and other test-specific options. The default values should be appropriate in most cases.

Step 7: Run the Hansen test
Click on the "OK" button to run the Hansen test. EViews will compute the test and display the results.

Step 8: Interpret the results
Once the test is complete, you will see the results displayed in a new output window. Look for the test statistic, degrees of freedom, and the p-value associated with the Hansen test. The null hypothesis of the Hansen test is that the overidentification restrictions are valid. A small p-value (typically below 0.05) would lead to rejecting the null hypothesis, suggesting that the overidentification restrictions are not valid, which might indicate a problem with the model.
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