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I have collected bond yield data from 01/01/2008:31/12/2019 for several euro-zone countries. I would like to conduct an event study analysis of the main Non standard measures announced by central banks, but I am not sure which model is best from a theoretical point of view. I basically have dummy variables and control variables as regressors, that are the same for each countries, except for the first lags of the dependent variable. Would you estimate the model for each country seperately via OLS, or should I use a Panel estimation method? One of the main problem I face is that, bond yields were rising because of the sovereign debt crisis and many policies were announced on a period of turbolent markets so that I get for instance positive loadings on many non standard monetary policy announcements. How would you handle this issue?

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As part of your analysis, it is always a good idea to do something simple before pulling out the big guns. So, OLS by country with perhaps a handful of controls would be a good benchmark, if only to tell later if your complicated ideas don't amount to squashing a fly with a sledge hammer.

As for the panel idea, you have to think about how you'd be pooling your information. Country by country allows a maximal degree of freedom, but if you think some effects are shared or should be shared, you'd need a panel to capture this effect. The point here is that each estimator and regression equation tells a STORY. Think about it using words or pictures -- THEN, do the math.

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