Silvana Tenreyro

English

Research Papers in Economics

This PDF is a selection from a published volume from the National Bureau of 
Economic Research
Volume Title: Europe and the Euro 
Volume Author/Editor: Alberto Alesina and Francesco Giavazzi, editors
Volume Publisher: The University of Chicago Press
Volume ISBN:  0-226-01283-2
Volume URL: http://www.nber.org/books/ales08-1
Conference Dates: October 17-18, 2008
Publication Date: February 2010
Chapter Title:  Comment on "The Estimated Trade Effects of the Euro: Why Are 
They Below Those from Historical Monetary Unions among Smaller Countries?"
Chapter Author:   Silvana Tenreyro   
Chapter URL: http://www.nber.org/chapters/c11659
Chapter pages in book: (212- 218)212    Jeffrey  Frankel
Tenreyro, S. 2001. On the causes and consequences of currency unions. Harvard 
University, Department of Economics. Manuscript, November.
Thom, R., and B. Walsh. 2002. The eﬀect of a common currency on trade: Ireland 
before and after the sterling link. European Economic Review 46 (6): 1111–  23.
Thursby, J. G., and M. C. Thursby. 1987. Bilateral trade ﬂ  ows, the Linder hypothesis, 
and exchange risk. Review of Economics and Statistics 69 (3): 488–  95.
Wang, Z. K., and L. A. Winters. 1991. The trading potential of Eastern Europe. 
CEPR Discussion Paper no. 610. London: Center for Economic Policy Research.
Wei, S.- J. 1996. Intra- national versus international trade: How stubborn are nations 
in global integration? NBER Working Paper no. 5531. Cambridge, MA: National 
Bureau of Economic Research, April.
Comment  Silvana Tenreyro
Background and Summary
In an inﬂ  uential and provocative paper, Andy Rose (2000) reported that 
sharing a common currency enhanced bilateral trade by more than 200 
percent.1 The paper divided the profession into two camps: believers and 
skeptics. The latter doubted the plausibility of such a large trade eﬀect and 
pointed out the futility of attempting to extrapolate the postwar experience 
of currency unions (made mostly of small and poor countries) to countries 
adopting the euro. Subsequent work by Micco, Stein, and Ordoñez (2003) 
using data on the early years of the euro found that the eﬀect of the euro 
on bilateral trade between euro zone countries ranged from 4 to 10 percent 
when compared to trade between all other pairs of countries and from 8 to 
16 percent when compared to trade among noneuro zone countries.
As the euro marks its tenth anniversary, Frankel’s chapter provides a 
timely opportunity to explain the gap between Rose’s and Micco, Stein, and 
Ordoñez’s estimates and to reappraise the eﬀect of the euro on trade.
The chapter argues that the gap between estimates is not caused by any of 
the usual suspects. In particular, the diﬀerence is not caused by (a) lags (or 
the view that it takes time for currency unions to aﬀect trade patterns); (b) 
omitted variables (including the Anderson and Van Wincoop multilateral 
resistance term);2 (c) reverse causality (trade may lead to the formation of 
currency unions); or (d) threshold eﬀects (or the view that currency unions 
can cause large trade increases in countries that are below a certain size or 
income threshold). Instead, the chapter concludes that the culprit for the 
diﬀerence in estimates is sample size. Indeed, Micco, Stein, and Ordoñez 
(2003) estimated the euro eﬀect using only post-  1992 data. When the whole 
sample (with all country pairs, going back to the mid-  1940s) is used, Fran-
Silvana Tenreyro is a reader in economics at the London School of Economics.
1. With some exceptions, work by other scholars found conﬁ  rmatory results using postwar 
data. See early review in Alesina, Barro, and Tenreyro (2002) and Baldwin (2006).
2. See Anderson and Van Wincoop (2002).The Estimated Trade Eﬀects of the Euro    2 1 3
kel’s chapter ﬁ  nds that sharing the euro is associated with an increase in 
trade among euro zone countries of between 150 and 170 percent, very close 
to the tripling eﬀect documented by Rose. The chapter then argues that the 
large estimates for the euro (150 to 170 percent trade eﬀect) resulting from 
the extended sample should be preferred.
Comments
Explaining the source of diﬀerence in estimates is certainly a welcome 
contribution. The case in support of the large estimates (from the extended 
sample), however, is unconvincing. To see why, let us start by looking at 
ﬁ  gure 5C.1, which shows the exports from euro zone countries to other euro 
zone countries relative to the aggregate gross domestic product (GDP) of 
the euro zone.3 The plot shows that in 1990, the average euro zone country 
was exporting 12 percent of its GDP to other euro zone countries. The cor-
responding ﬁ  gure was (just below) 16 percent by the end of the sample.
If the chapter’s preferred estimates are correct, the question is then: what 
would exports have looked like if the euro had not been introduced? This 
question can easily be addressed using the chapter’s estimates. The estimated 
equation is given by:
ln yijt   xijt     t EMUijt   εijt,
where yij is bilateral trade between two countries i and j at time t, xijt is a set 
of controls, and EMUijt is a dummy variable that takes on the value 1 if both 
countries are in the euro zone and 0 otherwise. Hence, predicted bilateral 
trade ﬂ  ows are given by:4
y ˆijt   exp(xijt  ˆ)
if at least one of the countries is not in the euro zone, and
y ˆijt   exp(xijt  ˆ     ˆt)   exp(xijt  ˆ) exp(  ˆt)
if both countries are in the euro zone. The factor exp(  ˆt) is the enhancement 
eﬀect coming from using the euro. Hence, we can compute the counterfac-
tual bilateral trade ﬂ  ows between euro members in the post-  1998 period 
under the assumption that the euro had not been introduced as:
yijt   
exp(  ˆt)
,
where yij is actual exports between two euro zone members, and the coeﬃ-
cients   ˆt {t   1998 . . . } are the chapter’s (preferred) estimates. Aggregating 
yijt over all euro members, we can then compute overall exports from euro 
3. By euro zone, here, I refer to the eleven countries that adopted the euro in 1999, plus 
Greece.
4. This ignores heteroskedasticity and other issues raised in Santos-  Silva and Tenreyro 
(2006).214    Jeffrey  Frankel
countries to other euro countries as a share of GDP, as in ﬁ  gure 5C.1. Figure 
5C.2 shows these counterfactual exports as a share of GDP, together with 
the actual shares (from ﬁ  gure 5C.1).
As the ﬁ  gure illustrates, the chapter’s preferred estimates imply that if 
the euro had not been introduced, trade shares would have collapsed in 
1998. This leaves the reader with two options: either believe that trade shares 
would have shrank dramatically without the euro or remain skeptical of the 
large estimates. I could not come up with any substantive reason for a trade 
fall of such dimensions. Moreover, for the reasons I will later explain, I think 
the estimation is misspeciﬁ  ed, and the biases generated by the misspeciﬁ  ca-
tion become more severe when the large sample is used.
There are at least two important concerns raised by the estimation ap-
proach that the chapter tries to address: endogeneity and sample size. I 
would like to discuss them in more depth.
Endogeneity: A Natural Experiment
In an almost self-  contained section, the chapter argues that endogeneity 
is not a serious problem in the estimation and therefore not the source of 
the large estimates. To make this point, the chapter studies bilateral trade 
patterns between countries in the euro zone and countries in the CFA franc 
zone.5 The latter, which were pegging their currency to the French franc 
Fig. 5C.1    Exports from euro zone to other euro zone members relative to GDP
Source: Tenreyro’s computation using Direction of Trade Statistics (DOTS; International 
Monetary Fund) and World Development Indicators (WDI; World Bank).
5. The CFA franc zone comprises two diﬀerent monetary unions: the West African Economic 
and Monetary Union, which uses the West African franc CFA (where CFA stands for Commu-The Estimated Trade Eﬀects of the Euro    2 1 5
before the introduction of the euro, continued to peg their currency to 
France’s—that is, to the euro—after 1999. These countries hence found their 
currency almost accidentally pegged to that of all other countries in the euro 
zone. This historical accident is an ideal quasi experiment to evaluate the 
eﬀect of a strong peg on trade. And it is obviously an important exercise in its 
own right and is of fundamental value for development macroeconomists. 
The author should be commended for the idea. As before, however, I would 
like to comment on the size of the trade enhancement eﬀect.
To gauge the trade impact of the strong peg between the CFA franc and 
the euro, the chapter introduces a dummy variable that takes on the value 1 if 
one of the countries is in the CFA franc zone and the other is in the European 
Monetary Union (EMU; currently or in the future) and 0 otherwise; so, for 
example, for the pair Italy-  Congo, this dummy is always 1. This dummy is 
then interacted with year dummies from 1980 to 2006 so as to estimate the 
extra trade between CFA and euro zone country pairs over time. That is:
 ln  yijt   xijt     1 · one country in CFA, the other in EMU   1980 
     2 · one country in CFA, the other in EMU   1981 
     3 · one country in CFA, the other in EMU   1982 
       . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .  
     28 · one country in CFA, the other in EMU   2006   εijt.
Fig. 5C.2    Actual and counterfactual exports from euro zone to other euro zone 
members relative to GDP
Source: Tenreyro’s computation using DOTS, WDI, and Frankel’s (2008) estimates.
nauté Financiére d’Afrique), and the Economic and Monetary Community of Central Africa, 
which uses the Central African CFA franc (where CFA stands for Coopération Financière en 
Afrique Centrale).216    Jeffrey  Frankel
As before, the estimated coeﬃcients   ˆ1 through   ˆ28 relate to the extra trade 
between a CFA member and a euro zone member (future or current). Fig-
ure 5C.3 plots these coeﬃcients together with the one-   and two-  standard-
  error bands against time (as reported in the chapter), highlighting the year 
in which the euro was introduced. Interestingly, trade between these two 
groups of countries has been historically larger than trade between other 
country pairs (the coeﬃcients are always positive). The ﬁ  gure also shows 
a stark increase in trade in 1997. The timing is not perfect for the euro, as 
trade seems to jump before the actual introduction of the euro; the chapter 
acknowledges this point straight away but compellingly argues that the eﬀect 
may have been anticipated as expectations of the euro became more ﬁ  rmly 
established. However, there is some confusion regarding the magnitude of 
the eﬀect. The chapter estimates a CFA franc- euro eﬀect of about 70 percent 
in the post-  1997 period (with 70 percent   [exp(0.55) –   1] · 100 percent, 
where 0.55 is an average of the point estimates of the   ˆ coeﬃcients over 
the post-  1997 period). The enhancement eﬀect, however, should be com-
puted as the diﬀerence between the post-  and pre- 1997 (or the relevant year) 
periods, as trade between these two groups was already large in the 1980s. 
The average   ˆ coeﬃcient in the pre-  1997 period was about 0.35, implying 
that the enhancement eﬀect could not have been larger than 20 percent (20 
percent   [exp(0.55 –   0.35) –   1] · 100 percent). This number is much closer 
to Micco, Stein, and Ordoñez’s estimates than to Rose’s, suggesting that 
endogeneity may have played an important role in Rose’s estimates after all. 
But this should not distract us from the main ﬁ  nding: the euro has increased 
Fig. 5C.3    CFA-  euro zone coeﬃcients and standard error bandsThe Estimated Trade Eﬀects of the Euro    2 1 7
trade between CFA franc zone and euro zone countries; this is an unexpected, 
positive, and important by-  product of the euro.
Sample Size (and the Problems with Zeroes and Heteroskedasticity)
The chapter argues that the gap between 10 and 200 percent in estimates 
is almost fully explained by sample size. When the full sample (with all 
country pairs, going back to the mid- 1940s) is used, the estimated coeﬃcient 
on the euro becomes close to 200 percent. As argued earlier, it is impos-
sible to conceive an enhancement eﬀect of such magnitude without making 
heroic assumptions. Still, it is of academic interest to ask why and how the 
chapter can obtain such large estimates in the full sample. To understand 
why, notice that the large- sample speciﬁ  cation imposes the same coeﬃcients 
of the gravity equation to all country pairs over time. The chapter argues 
that this is a good strategy, as more information is available to pin down 
the coeﬃcients on other gravity variables. But it is not clear to me why one 
should do that: coeﬃcients may indeed have changed over time and across 
countries, and constraining the estimated parameters to be constant could 
lead to serious misspeciﬁ  cation. This adds problems to the already mis-
speciﬁ  ed estimation, which uses the logarithm of bilateral trade, a variable 
that (a) frequently (in more than 30 percent of the observations) takes the 
value 0 and (b) is highly hetoreskedastic. Both the presence of zeroes and 
heteroskedasticity lead to inconsistent estimates in logarithmic speciﬁ  ca-
tions, as shown in Santos-  Silva and Tenreyro (2006). The larger sample 
makes the problem of zeroes and heteroskedasticity much more severe, as 
there is a larger proportion of zeroes in the sample going back to the mid-
 1940s, and as it includes highly heterogeneous countries, increasing the rele-
vance of heteroskedasticity. In sum, there is every reason to try to avoid the 
large- sample estimates, unless an appropriate estimator is used. My sugges-
tion is to use the estimator proposed in Santos-  Silva and Tenreyro (2006), 
together with time- varying coeﬃcients on the gravity variables and the euro 
eﬀect.
Final Remarks
Frankel has written an enjoyable and stimulating article that will give new 
impetus to the debate over the pros and cons of currency unions.
References
Alesina, A., R. Barro, and S. Tenreyro. 2002. Optimal currency areas. In NBER 
Macroeconomics annual, ed. M. Gertler and K. Rogoﬀ, 301– 56. Cambridge, MA: 
MIT Press.
Anderson, J., and E. van Wincoop. 2003. Gravity with gravitas: A solution to the 
border puzzle. American Economic Review 93 (1): 170–  92.218    Jeffrey  Frankel
Baldwin, R. 2006. In or out: Does it matter? An evidence-  based analysis of the euro’s 
trade eﬀects. London: Center for Economic Policy Research.
Micco, A., E. Stein, and D. Ordoñez. 2003. The currency union eﬀect on trade: Early 
evidence from EMU. Economic Policy 18 (37): 315–  56.
Rose, A. 2000. One money, one market: Estimating the eﬀect of common currencies 
on trade. Economic Policy 15 (30): 7–  46.
Santos- Silva, J. M. C., and S. Tenreyro. 2006. The log of gravity. Review of Econom-
ics and Statistics 88 (4): 641–  58.

Europe and the Euro

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