Block Exogeneity Test

[sguerra]

Dear Users,

I just want to request a little help about the Block Exogeneity test sugested on page 342 of the RATS Readers Manuals.

This test has a null hypothesis that the lags of one set of variables do not enter the equations for the remaining variables.

In the example sugested above, the rats manual shows how 3 real variables are as a block exogenuos. (GDPQ UNEMPRATE, GPDI)

Example VARCAUSE.PRG

(Please take your time to see the example)

The test just exclude nominal variables (GDPDEFL{1 to 4} and M2{1 to 4}) that you may incorporate as deterministics, and then you test using the RATIO instruction if those laged variables help to explain the whole system.

My question then is, WHY the manual tell us that the test is trying to see the Exogeneity of REAL variables?

Thanks for your help

Sergio Guerra

[ateeb]

I also have the same question. Also how can I model the following:

A standard VAR with all variables of interest say e.g. x1,x2,x3,x4,x5 and then compare with one which has x1,x2,x3,x4,x5 but only lags of x5 enters the equation for x5 and none other?

Regards,

[TomDoan]

That's treating x1,x2,x3,x4 as an exogenous block. So set up a system with x1 to x4 as the variables and run it with and without the lags of x5 included in the "deterministic" list.

[ateeb]

How to interpret the results of the RATIO test?

For example:

Exogeneity of Real Variables
Log Determinants are -38.037118 -37.640427
Chi-Squared(75)= 62.677151 with Significance Level 0.84422665

So the log determinants of the two models compared is not equal, so would it be interpreted that the models compared are statistically different? suppose I have tested lag restriction of a model with 6 lags against 3 lags ... how to interpret?

Thanks

[TomDoan]

How to interpret the results of the RATIO test?

For example:

Exogeneity of Real Variables
Log Determinants are -38.037118 -37.640427
Chi-Squared(75)= 62.677151 with Significance Level 0.84422665

So the log determinants of the two models compared is not equal, so would it be interpreted that the models compared are statistically different? suppose I have tested lag restriction of a model with 6 lags against 3 lags ... how to interpret?

Thanks

Of course they're not equal---the restricted model will always be higher. The chi-squared statistic measures whether that's statistically significant. It isn't (really isn't). So you don't reject the null of exogeneity. If you get a similar result is testing 3 vs 6, you would conclude that the 3 lag model is adequate.