1. Jeffrey Frankel – The estimated effects of the Euro on trade

2.  Enormous political, administrative, legal, intellectual efforts of CNB, Croatian government, etc. to negotiate with EU and reach EMU entry criteria  There clearly is a pot of gold at the end of the rainbow.

3.  And says the pot of gold is a lot smaller than they think in Zagreb.  Or is it?  This paper is an econometric detective story to find out?

4. Use a large panel data set with a standard gravity specification to look at trade between country pairs.  Put in a dummy variable for currency unions and they have an enormous impact.  But, initial studies of the € indicate that it is different. The trade effect is there but much smaller than other currency unions.

5.  Initial studies used 5 years of experience, we now have a few more.  Perhaps, we need to be patient  Or it really is different ◦ Is it possible that the most ambitious and successful currency union is less trade inducing  If it is different, WHY?

6.  Maybe standard results is an overestimate rather than € effect an underestimate. ◦ A few years ago I went to Curacao after a visit to nearby Caracas and ran out of toothpaste. Why is Curacaoan Colgate Dutch?  Maybe the long run up to the € meant that all the trade effects occurred in anticipation – long leads instead of lags.

7.  Hard to distinguish EMU effects from EU effects. Are we seeing EMU effects are lagged EU effects now?  Maybe Euroland trade was relatively integrated before the EMU so there was not much way to go.  Maybe there is some hokey econometrics going on.

8.  Lags not the answer - € has been around long enough  All those mini country currency unions may really be ‘out of sample’ but size does not effect results  Endogeneity – currency unions follow trade rather than vice versa. Perhaps, but ‘natural experiments’ do not support this.

9.  Table 5A OLS 92-06 full sample (n=100,747) ◦ Non-EMU union 0.752**  2.1x effect ◦ EMU -0.017  Table 6A OLS full sample 48-06 (n=166,609) ◦ Non-EMU union 0.309**  1.4x effect ◦ EMU 1.005**  2.73x effect

10.  EMU effect (Table 6A 48-06) ◦ Disappears in OLS if we move from full sample to developed countries. ◦ Reappears if we move to EU sample but an one- fourth size ◦ Persists with fixed effects but at one-tenth size

11.  Tendency to look at all the results and rationalize the sample that produces ‘nice’ or ‘right’ results  But, perhaps we should conclude that we just don’t know  Unless, we have good reason to choose among approaches.

12.  We need to call in a statistician who does not know an export from an import.  To see how to choose a model and an estimator  And how to interpret coefficients

13. 1. There is a universe of 160,000+ country pairs but the € impact is drawn from a few years in a narrow corner of the world. ◦ How do I know if the sample is homogeneous? ◦ What is the correct data universe for looking at the € experiment?

14. 2. When should I include fixed effects and for what? ◦ How do time and/or country fixed effects change the way I interpret coefficients in the equation? ◦ We see that the choice effects estimates. Is one specification correct? Or does interpretation vary with the specification?

15.  There is no end to what you can do with 160,000 observations.  But, doing econometrics is the easy part.  Knowing what to do and how to read the results is easier… ◦ What advice do we give to Zagreb? ◦ Take these results back to the econometricians before you give the acquis back to Brussels.