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st: ARCH disturbances in truncated samples?

From   kokootchke <>
To   statalist <>
Subject   st: ARCH disturbances in truncated samples?
Date   Thu, 16 Jul 2009 17:27:49 -0400

I am running a model that has the spread of a bond as a dependent variable and a bunch of domestic and global variables on the right-hand side. The spread is an inverse measure of the price for which the bond is sold to potential bondholders and gives a sense of the bond issuer's creditworthiness (higher spread indicates lower creditworthiness). Examples of domestic variables are GDP growth, debt/GDP, reserves/imports for each individual country where the bond issuer resides, while examples of global variables are the US interest rate and various liquidity and volatility indices.

One problem is that I have quarterly macroeconomic data but I only observe the spread whenever countries actually issue a bond. Countries may decide not to issue a bond because the market will simply not buy the bond (for example, in the middle of a crisis) or simply because the country doesn't want to issue it (one quarter they may issue 3 bonds and the next quarter they may not need to issue at all).

Now I am not exactly sure of how to model this other than with a Heckman selection model (let me know if you have other suggestions). One problem is that I think my errors are not standard Normal, iid errors... but that I think they follow some sort of ARCH structure -- for a given country, for example, the error this period may be related to the error in the previous period. The problem is that "the previous period" may not be exactly t-1... but the previous period when there was a bond issue...

How do I account for this?

Thank you very much in advance...


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