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I am doing some research on Germany, France and Spain on their spread. I would like to try to 'forecast' or 'explain' the the spread on sovreign debt using OLS regression on unemployment and debt amount.

I would like to ask you some suggestions on the methodology:

1) To use OLS in time series all data shall be stationary but once I have stationarized them it works fine; right?

2) Would you regress the spread between germany and france on unemployment of France or on the $\Delta$ between unemployment in france and germany?

3) To forecast I would regress spread at time $t$ on variables at $t-1$, is it fine? To explain, on the other hand, both shall be at time $t$. Do you agree?

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  • $\begingroup$ Vandalizing questions isn’t allowed. $\endgroup$ – Bob Jansen Oct 31 '17 at 6:07
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These are good questions.

1: Yes. Similarly, consider absolute yield level as a regressand.

2: Regress on unemployment absolute AND difference. You can toss out any statistically insignificant (||<2).

3: Perhaps matching in time for observable and dependent variable is best; you can test lagged models, which is significant in the context of credit spread modelling where there is some degree of "looking ahead".

You may end up with multiple econometric models to test, no bad thing - here the art can be mathematicalised using AIC/BIC or similar model selection methods.

e.g.

france credit spread = debt + relative debt spread + unemployment rate + relative unemployment spread

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