Exchange rate fluctuations and quality composition of
exports: Evidence from Swiss product-level data
Dario Fauceglia
⇤
Conference Draft
⇤University of St. Gallen and Zurich University of Applied Sciences (Switzerland). Email:[email protected]
Abstract
This paper studies the relationship between exchange rate movements and theaverage export quality using Swiss disaggregated product-level data between 2004and 2013. We find evidence that the average export quality increases in response toa currency appreciation. The results also reveal that this improvement in quality isdriven by a shift in the export composition towards higher quality goods. From apolicy perspective, this points to the importance of allowing for a structural change inthe export composition to cushion the adverse effects of an exchange rate appreciation.Moreover, the findings imply that price estimations with more aggregated data tend tooverstate the degree of exchange rate pass-through because the change in the qualitycomposition of exports is usually not considered.
1 Introduction
A large part of the exchange rate related literature has emphasized the direct effect ofcurrency movements on aggregate prices and quantities (Burstein and Gopinath, 2013).Scholars have paid particular attention to the phenomenon of incomplete pass-through;the stylized fact that exchange-rate shocks are in the majority of cases only partiallytransmitted to foreign consumers. Apart from imported inputs and (distribution) costs inlocal currency, heterogeneity in terms of firm productivity and quality can help us under-stand pricing-to-market behavior and incomplete pass-through to local prices in variablemark-up frameworks (Berman et al., 2012; Chen and Juvenal, 2014). Relatedly, this paperstudies the effect of a currency appreciation on the average quality of exports that arisesdue to shifts in the product composition within narrowly defined sectors. There is, besidesAuer and Chaney (2009) using a different framework and data, to our knowledge no othercontribution that deals with a quality composition effect driven by exchange rate changes.As a result, this paper shows that exchange rate shocks do not only affect export prices andquantities but also generate a change in the product composition that leads to a higheraverage export quality. This export composition effect is also important from a policypoint of view, as it indicates that a structural change in the set of exported goods is vitalto cushion the negative effects of an exchange rate appreciation and to maintain a compet-itive economy. This is particularly relevant for high-wage countries such as Switzerland.Our study thus establishes quality as an additional margin of adjustment in response to acurrency appreciation.
We use the simplest possible CES-framework augmented with quality, similarly to Johnson(2012) and Baldwin and Harrigan (2011), to derive a prediction about the average qualityof exports. At the firm-level, this framework predicts full pass-through and no adjustmentin quality because of a constant a priori distribution of capabilities and mark-ups. Putdifferently, firm-level quality does not depend on exchange rate changes but is a functionof exogenous capability only. At the product-level, however, an exchange rate appreciationraises the capability threshold of the marginal firm that supplies a specific variety of aproduct. This results in a composition effect that increases average export quality wheneverfirm capability and export quality is positively correlated, which is empirically supported(Hummels and Klenow, 2005; Johnson, 2012; Kugler and Verhoogen, 2012).
To empirically test the relationship between quality and movements and the Swiss Franc(CHF), we use annual customs data between 2004 and 2013 that keep records of revenues
2
and quantities of the full universe of Swiss manufacturing exports at the disaggregatedhs8-digit level. The empirical results are consistent with the idea that exchange rate ap-preciations trigger a within product variety churning and shift production to higher qualitygoods. This increases the average product quality of exports. This is a novel result thatdiffers from the previous literature. For instance, our result seems to be in contradic-tion with Verhoogen (2008)that indicates the opposite relationship between exchange ratemovements and quality. Verhoogen (2008) shows that an exchange rate depreciation in-duces Mexican firms with higher abilities to upgrade their quality and to pay higher realwages. However, our results suggest that the product composition effect must be taken intoaccount if one wants to assess the overall effect of an exchange rate shock on the qualityof exports. This export composition effect has also implications for the estimation of ex-change rate pass-through. Since the average quality of exports rises after an appreciation,estimations of exchange rate pass-through with aggregate product-level data are likely tobe upward biased.
2 Theoretical Motivation
This section develops a two-country quality-augmented Melitz (2003)-model that borrowsimportant features from Crozet et al. (2012), Johnson (2012) and Baldwin and Harrigan(2011). Consumers in the destination market j exhibit Dixit & Stiglitz preferences U overthe differentiated varieties ! within a hs8-digit level product, with a constant elasticity ofsubstitution � > 1 , between any two varieties !. Moreover, the perceived quality q(!)
of a variety ! acts as demand shifter. Therefore, preferences U and demand x
j
(!) for avariety ! within a hs8-digit level product are of the form
U =
ˆN
!2⌦j
x
j
(!)qj
(!)d!
! �
��1
, (1)
where N corresponds to the number of existing varieties within a hs8-digit product. whereThese preferences in (1) lead to the following demand function x
j
(!) for the variety !
within a hs8-digit level product:
x
j
(!) = q
��1j
p
��
j
eP
��1j
E
j
, (2)
3
p
j
denotes the price of a variety !, eP =h´
N
0 ep(!)d!
i1
1�� represents the (ideal) price indexdual to (1) and E denotes aggregate spending for the differentiated goods in both countries.As is standard in this framework, a firm applies mark-up pricing and sets an export pricep
j
that is a constant mark-up over marginal cost c.
p
j
(c) =
✓�
� � 1
◆"
j
⌧
j
c, epj
(c) =p
j
q
j
=
✓�
� � 1
◆"
j
⌧
j
c
q
j
, (3)
Denote that p
j
in (3) corresponds to the local-currency price in the foreign market. p
j
of afirm selling in destination market j therefore also reflects iceberg trade costs ⌧
j
, meaningthat ⌧
j
> 1 must be shipped in order for one unit of the good to arrive in j. Furthermore,"
j
is the exchange rate in terms of foreign currency per unit of domestic currency. Dixit-Stiglitz CES preferences imply full-pass through of exchange rate changes and thus thefollowing relationship p
j
= ✏
j
⌧
j
p
fob
j
between p
j
and the domestic-currency free on boardprice p
fob
j
. epj
(c) is the quality-adjusted price and is obtained by dividing p
j
by q
j
. Wecan define firm capability a
j
as the ratio between quality and marginal cost: a
j
⌘ q
j
c
.Intuitively, a capable firm is a high-productivity firm (low c) that sells high-quality products(high q) demanded by customers. We can thus express the quality-adjusted price and therevenues as a function of firm capability as follows:
epj
(a) =
✓�
� � 1
◆"
j
⌧
j
a
(4)
r
j
(a) = x
j
p
j
= epj
(a)1�� eP
��1j
E
j
(5)
As as result, more capable firms with a higher a charge lower prices (see equation 4) andgenerate higher revenues (see equation 5). In order to export to destination j a firm mustcover a fixed cost of market entry f
j
. This leads to the following zero-profit condition:
1
�
r
j
(a⇤j
) = f
j
(6)
The left-hand side of equation (6) corresponds to operating profits that must be equal orhigher than market entry costs f
j
for a firm to serve market j. For the marginal firm withzero profits equation (6) holds with equality. This determines the minimum capabilitythreshold a
⇤j
required to export a variety ! within a hs8-digit product to destination j.
4
Defining attractiveness of export market as A
j
= ⌧
1�� eP
��1j
E
j
and collecting terms in⌘ = �
��
��1
���1 , we obtain the minimum capability a
⇤j
of the marginal firm:
a
⇤j
= "
✓⌘f
j
A
j
◆ 1��1
(7)
For a given market entry cost f
j
, a more attractive export market j (high Aj
) due to largersize (higher E
j
), less competition (higher ePj
) or better accessibility (low ⌧
j
) also allows lesscapable firms to profitably enter and reduces a
⇤j
. Equation (7) also makes clear that theminimum level of capability is increasing in the exchange rate. In other words, an exchangerate appreciation raises the capability of the marginal firm. The observed product-levelquality depends on the relationship between firm capability and the provided quality. Weassume that this relationship can be described as a power function; q
j
=a
✓. Similarly toMelitz (2003), we compute special averages of the quality q
j
observed at the hs8-digitproduct-level:
q
j
(a(a⇤j
)) = a
✓(a⇤j
) =
1
1�G(a⇤j
)
ˆ 1
a
j
a
��1dG(a)
! ✓
��1
(8)
Equation (8) shows that the quality level q
j
rises whenever capability and product qualityare positively correlated or, equivalently, when ✓ > 1 holds . Equation (7) and (8) showhow the exchange rate and the observed quality at the product-level are tied together.An exchange rate appreciation increases the capability of the marginal firm (see equation7) and shifts the composition towards more capable firms that produce higher-qualityproducts (see equation 8). This results in rising shares of higher quality varieties and anincrease in the average export quality. The next hypothesis summarizes this result:
Hypothesis : An exchange rate appreciation increases the observed quality of a prod-uct through a composition effect that favors more capable firms producing higher qualityvarieties.
Importantly, this result is entirely driven by an extensive margin adjustment of firm com-position to the exchange rate. The effect does not occur because firms adjust their qualityin response to the stronger exchange rate. The same composition effect is also presentin the initial Melitz (2003)-model that emphasizes firm productivity instead of capability.An exchange appreciation raises the export productivity threshold and forces the leastproductive exporters to exit. This leads to an increase in the aggregate productivity of
5
exporters and to lower average export prices, as also described Rodriguez-Lopez (2011).Our composition effect also bears similiarities with the competitive model proposed byAuer and Chaney (2009) in which low-quality producers also pull out of the export marketas a result of an exchange rate appreciation.
3 Measuring Quality of Exports
3.1 Estimated quality measure
First, we measure the quality of exports with an adaption of the method proposed byKhandelwal et al. (2013). Using "
j
⌧
j
p
fob
j
= p
j
we can describe demand in equation (2) inthe following log-linear forms:
log(xjt
) + �log(pfob
jt
) = (� � 1)log ePjt
� �log("jt
⌧
jt
) + log(Ejt
) + (� � 1)log(qjt
)| {z }=e
hs8jt
(9)
log(xhs8jt
) + �log(pfob
t
) = ↵
hs8 + ↵
jt
+ (� � 1)log(qjt
)| {z }=e
jt
(10)
The time fixed effects ↵
jt
in (10) control for changes in the income (Ejt
) and price indexof the destination country ( eP
jt
) as well as tariff and exchange rate changes (✏jt
, ⌧
jt
). The↵
hs8 fixed effect picks up fundamental differences across hs8-digit products. The basic ideaof this method is intuitive: Conditional on product price and income in the destinationcountry, increases in demand within a hs8-digit product are associated with a higher quality.Put differently, the quality of a product is identified from demand changes within a hs8-digit product for a given fob export price after controlling for price index, income , tariffand exchange rate changes. After estimating equation (10), the quality of exports is thencalculated from predicted residuals e
jt
:
log( ˆq
jt
) =e
jt
� � 1(11)
To obtain the predicted quality log(qjt
) in equation (11), we use the elasticities of substi-tution � from Imbs and Méjean (2015) available at the the 3-digit ISIC (Revision 2) that
6
also includes Switzerland in the country sample.1 This results in a time-varying estimateof the product quality at the highest level of disaggregation in our data (hs8-digit level),log( ˆ
q
jt
), as derived in equation (8). This variable is later employed to examine the effectof exchange rate fluctuations on product-level quality of exports.
3.2 Quality measure based on unit values
Empirical evidence suggests that the quality of a product increases disproportionately withfirm capability. This translates to ✓ > 1, which implies that product quality and observedfree on board export prices are positively correlated, as can be seen from equation (12):
p
fob
j
(q) =
✓�
� � 1
◆q
✓�1✓
, (12)
Equation (12) indicates that physical prices are valid quality approximations of the of theunderlying products within a relatively narrowly defined product group if ✓ > 1 holds. Asa consequence, we use a variant of the measure introduced by Auer and Chaney (2009)based on unit values as a second approximation for changes of the average product-levelexport quality:
4Quality
jt
=X
!2⌦t
\⌦t�1
(sj
� s
jt�1)⇥ ln(pfob
j,t�1), (13)
where s
jt
and s
jt�1 denote the export shares of destination-specific hs8-digit products intime t and t�1 within a hs4-digit product group ⌦. Export prices p
fob
j,t�1 in period t�1 aremeant to capture quality differences of hs8-digit products exported to a given destinationj within a hs4-digit product group. Only hs8-digit products that are exported in period t
and t � 1 are considered so that the export shares s
jt
and s
jt�1 sum to unity. A positivechange, 4Quality
jt
> 0 between t and t � 1 is caused by rising shares of more expensivehs8-digit products and is interpreted as an increase in the average export quality. Thequality measure of equation (13) is constructed mainly at the hs4-digit level. These arenarrowly defined sectors as there are about 1200 hs4-product groups in our sample. Forexample, the hs4-code 6106 corresponds to “Women’s or girls’ blouses & shirts, knit orcroch”, which contains the hs6-code 610610 “Women’s or Girls’ Blouses, Shirts, of Cotton,
1Imbs and Méjean (2015) employ the novel tetrad method proposed by Caliendo and Parro (2014) toestimate the trade elasticities.
7
Knitted or Crocheted ” among others. Calculating 4Quality
jt
at the hs6-digit level wouldhave resulted in an excessive dropping of observations because in many cases there is onlyone hs8-product exported to a destination in each hs6-digit sector. However, the resultsare not sensitive to the use of 4Quality
jt
calculated at the hs6-digit level, as robustnesschecks will show. Even though differences in the fob unit values at the hs8-digit level mayreflect differing production costs and pricing strategies across varieties (Henn et al., 2013),most of the variation in unit values can be attributed to quality changes according toFeenstra and Romalis (2014) and Hallak (2006). Furthermore, using lagged export prices(pfob
jt�1) from the period t� 1 ensures that unit values are not affected by contemporaneousshocks or the introduction of new goods that change the variety composition within eachhs8-digit product category. This could have led to confound a composition effect with aquality change. The quality measure of equation (13) shows thus whether higher-pricedhs8-digit products containing a pre-established set of varieties increase their export shares,which is understood as a change in the average export quality of a more aggregated productcategory at the 4-digit or 6-digit level.
4 Empirical Methodology
4.1 Specifications and estimators
This section develops a empirical model to examine the effect of exchange rate movementson observed product-level quality of exports to destination j and time t.
4Quality
jt
= �4logER + �4logGDP
jt
+ �4logGDPPC
jt
+ �4logCost + ⌘
t
+ "
ict
(14)
We first run a specification in first differences similar to Campa and Goldberg (2005)and Auer and Chaney (2009). The first-difference model in (14) controls for unobservedheterogeneity at the hs8-destination level but is superior to a fixed effect estimator becauseof possible non-stationarity of the right-hand side variables such as exchange rates andprices (Wooldridge, 2002). An exchange rate appreciation (4logER ") is expected to havea positive effect on average export quality according to our theoretical motivation, implying� > 0 after taking into account the evolution of GDP and GDP per capita in exportmarkets and sector-level production cost changes (4logCost) in Switzerland. 4logCost
8
also includes a sectoral measure of imported input price developments that is constructedby weighting bilateral exchange rates with imported inputs from origin countries and inputshares taken from Swiss input-output tables (see the Appendix for more details on thismeasure). We employ time fixed effects ⌘
t
to capture trends that affect the quality of allexports similarly (e.g. the importance of after-sales services). Alternatively, time fixedeffects are replaced by an intercept. This intercept corresponds to a linear time trend inthe first-difference model.
In the next step, we test the robustness of the results in dynamic models. We employ theGMM estimator introduced by Arellano and Bond (1991) to add the lagged quality measureon the right-hand side of equation (14). This GMM framework also allows to consider thepossible endogeneity of exchange rate changes. Specifically, the lags of the exchange ratevariable can be used to instrument for contemporaneous exchange rate changes. As analternative, we employ the dynamic empirical model suggested by Blundell and Bond(2000) that allows the data to feature some persistency and error terms to follow a AR1process. As a consequence, this model is applied to a level-representation of equation(14). In this framework, it can also be tested whether the common factor restriction inthe estimation of the exchange rate effect of � is justified. Irrespective of this test, we alsoperform estimations of (14) at more disaggregated sectoral levels or the hs4-digit product-level as a robustness check.
4.2 Data overview
Product-level bilateral trade data is obtained from the Swiss Federal Customs Administra-tion (Eidgenössische Zollverwaltung) and include the free on board value of transactions inCHF and a quantity measured in kg at the hs8-digit level from 2004 to 2013. This allowsto generate fob unit values as a proxy for export prices that are necessary to estimate andconstruct the quality measures presented in equation (11) and (13). We reduce the datasetto the 37 most important trading parters for Switzerland, including all OECD countriesand the BRICS that account for more than 90 percent of Swiss exports. The monthlyrecorded transactions are collapsed to annual data. Data on exchange rates are sourcedfrom the Swiss National Bank (SNB). Real GDP and GDP per capita data are taken fromthe World Bank’s World Development Indicators. Swiss production price indices at theISIC 2-digit level and the consumer price index come from the Swiss Federal StatisticalOffice (Bundesamt für Statistik). All these data are summarized in Table 1. Both quality
9
Table 1: Summary Statistics of Estimation Variables
Variables Obs. Mean Std.Dev. Min Max4Quality (Khandelwal et al. 2013) 627736 -0.005 1.755 -62.2 60.3
4Quality (unit value based) 194778 -0.027 0.939 -12.1 10.34Exchange rate 627736 0.030 0.071 -0.195 0.414
4Real GDP (destination) 627736 0.020 0.035 -0.089 0.1334Real GDP per capita (destination) 627736 0.014 0.034 -0.094 0.128
4Production prices (CH) 627736 0.008 0.038 -0.339 0.1714Imported input cost (CH) 627736 0.030 0.047 -0.041 0.1224Consumer price index (CH) 627736 0.006 0.009 -0.007 0.024
measures in Table 1 reveal that the average quality declined sightly from 2004 to 2013. Wealso observe that the bilateral exchange rate indices exhibited both periods of deprecia-tions and appreciations. GDP and GDP per capita in destination countries rose on averageduring the sample periods. The same also holds for production and consumer prices inSwitzerland, while imported input costs fell in Switzerland between 2004 and 2013, onaverage.2
2To be precise, 4Imported input cost (CH) is an inverse measure of imported input costs. This meansthat increases correspond to cost decreases (see also Appendix: Imported input costs).
10
5 Results
Table 2 presents the results about the relationship between exchange rate changes andthe adjustment of product-level quality. The dependent variable corresponds to the qual-ity change estimated and derived in the equations (9) to (11) according to the methoddescribed in Khandelwal et al. (2013). Column 1 of Table 2 suggests that an exchangerate appreciation translates into a higher export quality after controlling for GDP, GDPper capita in destination countries and sectoral production, imported input and consumerprices in Switzerland. This result is robust to the inclusion of a linear time trend in col-umn 2 or year fixed effects in column 3. In column 4 we replace the nominal exchange ratechange by the log change of the real exchange rate. This does not affect the results. A10%-appreciation of the CHF increases the quality measured at the hs8-digit product-levelby 2.5% on average at the 1%-significance level in columns 1 to 4. This set of estimationstakes into account unobserved heterogeneity by considering fixed effects at the hs8-partnerlevel that were dropped due to first differencing. Next, we employ the Arellano-Bond es-timator that allows to include the lagged quality measure and to control for the possibleendogeneity of exchange rate changes by instrumental variables. After including the oneperiod lag of quality in the regression, the effect of the exchange rate reduces in termsof size and significance. However, the Sargan test on the error autocorrelation structuresuggests that the residuals exhibit second-order autocorrelation, which precludes the con-sistency of the GMM estimator in the Arellano and Bond (1991)-setup. We thereforeinclude another lag of the quality measure in order to ged rid of second-order autocorrela-tion in the residuals. Furthermore, we permit a gradual adjustment of quality to exchangerate changes by including a lagged exchange rate variable. The exchange rate is also con-sidered to be endogenous in this specification. Estimations in column 6 reveals that thecurrent quality growth rate depends negatively on its first- and second-order lag, implyinga mean-reverting behavior in our quality measure. Both current and lagged exchange ratechanges turn out to have a positive and significant effect on product quality. The cumula-tive effect of the exchange rate in in column 6 is economically large, as a 10%-appreciationis associated with a 4.2 % (0.42=0.158+0.262) rise in average export quality. Moreover,test statistics indicate that second-oder autocorrelation is not a concern after includingan additional quality lag and the validity of the used instruments are not rejected at the5%-significance level according to the Sargan test of instrument overidentification. Thissuggests that our model is correctly specified and the instruments for the lagged dependentand the exchange rate variables are not correlated with the error structure of the estima-
11
Tabl
e2:
Rel
atio
nshi
pbe
twee
nex
chan
gera
tech
ange
san
dqu
ality
aths
8-di
git
leve
l
Dep
ende
ntva
riab
le4
Qua
lity
(Kha
ndel
wal
etal
.20
13)
(1)
(2)
(3)
(4)
(5)
(6)
4Q
ualit
y(l
ag1)
-0.2
67**
*-0
.675
***
(0.0
11)
(0.1
45)
4Q
ualit
y(l
ag2)
-0.4
43**
*(0
.141
)4
Exc
hang
era
te0.
241*
**0.
238*
**0.
244*
**0.
254*
**0.
110*
0.15
8**
(0.0
398)
(0.0
398)
(0.0
405)
(0.0
432)
(0.0
566)
(0.0
616)
4E
xcha
nge
rate
(lag
1)0.
262*
*(0
.105
4)4
Rea
lGD
P(d
esti
nati
on)
-0.2
55-0
.719
***
-0.6
03**
-0.4
230.
0426
0.06
79(0
.250
)(0
.276
)(0
.276
)(0
.277
)(1
.560
)(1
.528
)4
Rea
lGD
Ppe
rca
pita
(des
tina
tion
)0.
374
0.80
6***
0.57
6**
0.46
00.
235
-0.0
0545
(0.2
66)
(0.2
84)
(0.2
83)
(0.2
83)
(1.5
62)
(1.5
37)
4P
rodu
ctio
npr
ices
(CH
)0.
216*
**0.
209*
**0.
205*
**0.
205*
**0.
191*
**0.
142*
**(0
.047
6)(0
.047
6)(0
.049
2)(0
.049
2)(0
.056
8)(0
.050
0)4
Impo
rted
inpu
tco
st(C
H)
-0.1
69**
*-0
.210
***
-1.0
91**
*-1
.091
***
-1.1
23**
*-0
.372
(0.0
528)
(0.0
598)
(0.2
70)
(0.2
70)
(0.2
83)
(0.3
16)
4C
onsu
mer
pric
ein
dex
(CH
)-1
.695
***
-1.8
36**
*(0
.245
)(0
.272
)O
bser
vati
ons
627,
736
627,
736
627,
736
627,
736
388,
745
304,
785
Est
imat
ion
OLS
OLS
OLS
OLS
GM
MG
MM
Line
arti
me
tren
dN
oY
esN
oN
oN
oN
oY
ear
fixed
effec
tsN
oN
oY
esY
esY
esY
es**
*p<
0.01
,**
p<0.
05,*
p<0.
1,R
obus
tst
anda
rder
rors
inpa
rent
hese
s,er
ror
corr
ecti
onfo
rco
rrel
atio
nat
the
hs8-
part
ner
leve
lin
colu
mns
1-4.
Het
eros
keda
stic
-rob
ust
erro
rsin
colu
mns
4-6.
.A
llva
riab
les
are
deno
ted
inlo
gsan
dfir
stdi
ffere
nces
.
12
tion model. No consistent picture with regard to estimation of control variables emerges.There is some evidence that higher production, imported input prices and real GDP percapita in destination countries are associated with a higher average export quality in Table2. However, the effect of real GDP per capita on quality is not robust across specificationsand the effect of imported input costs disappears in the dynamic specification of column6.
Overall, the results of Table 1 show that there is a significant and robust increase in theobserved quality at the hs8-digit product-level triggered by a CHF appreciation. This isconsistent with our theoretical motivation that predicts a firm composition effect afteran appreciation, which favors the production of higher quality varieties by more capablefirms. However, the estimation results may also be partly driven by firm-level adjustmentsin quality. The observed average quality at the hs8-digit level is therefore the sum of aproduct composition effect and firm adjustments in quality. With our second measure ofquality, we are able to isolate the first effect. The quality measure explained in Section3.2 indicates whether the quality at the hs4-digit product-level group rises as a resultof an exchange rate appreciation. This can only occur because more expensive hs8-digitproducts of higher quality gain market shares. Since we hold unit values as a proxy forquality fixed by using their lagged values, quality changes due to simultaneous firm-levelquality adaptations as a reaction to a stronger CHF can be excluded.
Table 3 displays the estimated coefficients explaining quality change at the hs4-digit prod-uct group. The effect of an exchange rate appreciation is estimated fairly precisely and hasa systematic positive impact on the average quality of hs4-digit export goods in columns1 to 4. The specification in column 4 considers the possible persistency and gradual ad-justment in average quality by including lagged quality and exchange rate variables. Forthe Arellano and Bond (1991)-model of column 4, test statistics suggest no autocorrelatederrors and the validity of instruments for the lagged quality and exchange rate variables,which are both required for consistency. Across columns 1 to 4, the exchange rate effectis estimated to be around 0.18. This indicates that a 10%-appreciation of the CHF raisesthe quality of the exported goods at the hs4-digit level by about 1.8%. This is similar insize to the corresponding exchange rate effect shown in Table 2. This reveals that upwardadjustments in quality, resulting from a currency appreciation, come about predominantlythrough a shift towards firms producing higher quality goods rather than through improve-ments in quality at the firm-level. This appears to hold at least in the short-run. Columns5 to 7 show that estimation with our first quality measured does not depend on the ag-
13
Tabl
e3:
Rel
atio
nshi
pbe
twee
nex
chan
gera
tech
ange
san
dex
port
qual
ityat
the
hs4-
leve
l
Dep
ende
ntva
riab
les
4Q
ualit
y(u
nit
valu
eba
sed)
(1-4
)4
Qua
lity
(Kha
ndel
wal
etal
.20
13)
(1)
(2)
(3)
(4)
(5)
(6)
(7)
4Q
ualit
y(l
ag1)
-0.3
46**
*0.
078
4Q
ualit
y(l
ag2)
-0.1
61**
(0.0
81)
4E
xcha
nge
rate
0.18
0***
0.18
6***
0.17
1***
0.17
4**
0.26
6***
0.26
3***
0.27
7***
(0.0
417)
(0.0
417)
(0.0
420)
(0.0
710)
(0.0
550)
(0.0
550)
(0.0
565)
4E
xcha
nge
rate
(lag
1)-0
.068
0.12
84
Rea
lGD
P(d
esti
nati
on)
-1.7
89**
*-0
.807
**-0
.876
***
-2.6
47-0
.582
-1.1
40**
*-1
.020
**(0
.276
)(0
.328
)(0
.328
)(1
.661
)(0
.371
)(0
.425
)(0
.425
)4
Rea
lGD
Ppe
rca
pita
(des
t.)
1.28
9***
0.37
70.
556*
2.49
80.
660*
1.17
8***
0.99
2**
(0.2
90)
(0.3
32)
(0.3
37)
(1.6
74)
(0.3
94)
(0.4
32)
(0.4
36)
4P
rodu
ctio
npr
ices
(CH
)-0
.028
6-0
.018
50.
0102
0.03
430.
234*
**0.
228*
**0.
225*
**(0
.060
0)(0
.060
1)(0
.061
6)(0
.071
8)(0
.064
4)(0
.064
4)(0
.068
0)4
Impo
rted
inpu
tco
st(C
H)
-0.1
31**
-0.0
428
0.24
10.
174
-0.1
68**
-0.2
18**
*-0
.693
(0.0
547)
(0.0
591)
(0.2
98)
(0.3
36)
(0.0
754)
(0.0
838)
(0.4
35)
4C
onsu
mer
pric
ein
dex
(CH
)-0
.616
**-0
.312
-1.6
85**
*-1
.858
***
(0.2
39)
(0.2
59)
(0.3
42)
(0.3
79)
Obs
erva
tion
s19
4,77
819
4,77
819
4,77
813
0,56
018
9,44
618
9,44
618
9,44
6E
stim
atio
nO
LSO
LSO
LSG
MM
OLS
OLS
OLS
Line
arti
me
tren
dN
oY
esN
oN
oN
oY
esN
oY
ear
fixed
effec
tsN
oN
oY
esY
esN
oN
oY
es**
*p<
0.01
,**
p<0.
05,*
p<0.
1,cl
uste
r-ro
bust
stan
dard
erro
rsin
pare
nthe
ses,
erro
rco
rrec
tion
for
corr
elat
ion
atth
ehs
4-pa
rtne
rle
vel.
All
vari
able
sar
ede
note
din
logs
and
first
diffe
renc
es.
Col
umns
1-3
use
the
qual
itym
easu
reba
sed
onK
hand
elw
alet
.al
(201
3),w
hile
colu
mns
3-6
use
the
unit
valu
eba
sed
qual
itym
easu
reby
Aue
ran
dC
hane
y(2
009)
.
14
Figure 1: Distribution of log change of exchange rate estimate on quality at the hs4-digitlevel (left panel: all estimates, right panel, only significant estimates at p<0.05)
gregation level, as the results obtained a the hs4-digit level do not significantly differ fromthe corresponding estimates of Table 2 at the hs8-digit level.
When we estimate the equation 14 separately for each hs4-digit sector using our firstmeasure of quality (see Section 3.1), it turns out that there is wide variation of estimatesof the log change of the exchange rate with a majority of hs4-level sectors exhibiting anonsignificant response of quality to a CHF appreciation. The distribution of estimatesat the hs4-digit sector is displayed in Figure 1. In the left panel, the distribution of allexchange rate coefficients is displayed, while the right panel only shows the distributionof significant estimates at the 5%-level obtained in regressions with more than 50 degreesof freedom (=observations-estimating variables). Even though the mean quality responseto a CHF appreciation is consistent with the previous pooled results and is about 0.61,the right panel also reveals that there is a wide range of hs4-digit sectors that feature areduction in quality as a reaction to a stronger CHF.
15
6 Conclusions
This paper shows that exchange rate fluctuations affect the average export quality. Specifi-cally, the average product-level quality of Swiss manufacturing exports increases in responseto a currency appreciation. Apart from changes in export prices, profit margins and quan-tities, the upward adjustment in quality is thus another channel through which an economyreacts to a loss of competitiveness resulting from a stronger currency. The estimations alsoconvey that a large part of the quality improvement occurs through a shift in productiontowards higher quality goods rather than quality upgrading at the firm-level. This is in-dicative of the importance of policies that promote product market flexibility and allow fora structural change in the product composition of exports. This quality reaction impliesthat price estimations with aggregate data are likely to overstate the extent of exchangerate pass-through since the quality composition effect is usually neglected. The resultsare robust across various specifications, including the first difference estimator that con-trols for unobserved heterogeneity and the possible nonstationarity of price and currencymovements and dynamic specifications with lagged quality measures that also considerthe potential endogeneity of exchange rate changes in the GMM framework suggested byArellano and Bond (1991). Interestingly, pooled estimations across the entire universe ofSwiss manufacturing sectors hide a substantial heterogeneity in the response of productquality to exchange rate changes, as separate estimations at the the hs4-digit level reveal.There is a large share of products whose quality is not significantly or negatively affectedby a currency appreciation. A promising avenue for future research (and drafts!) would beto study the structural reasons for the heterogenous response of quality to exchange ratechanges at the disaggregated sector and product-level.
16
References
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17
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18
Appendix : Imported input costs
To approximate for imported input costs at the sectoral level, time-varying sectoral im-ported input weighted exchange rates are calculated based on supplier-specific importedinput values similarly to Greenaway et al. (2010) and Fauceglia et al. (2012).3 These realexchange rate indices are then weighted according to the import share of each input sectorin the respective output/export industry. These import shares are calculated from the2001 I-O table for Switzerland taken from OECD (2012).4
More formally, these imported input prices costs are constructed as follows:
Importedinputcost
so,t
=X
si
8<
:
"X
j
✓�W
j
si
�t
·✓
e
j,t
· p
ch
e
j,o
· p
j
◆◆#
t,si
·�R
si
so
�9=
; , (15)
where t is the time period, j is the origin country of imported inputs, si is the input-output(I-O) imported input sector and so is the I-O output sector. e
jt
and e
jo
are the supplier-specific bilateral nominal exchange rates in time t and in the base period (1.2004) and p
ch
p
j
measures the inflation differential between and Switzerland and the import source country.Therefore, e
j,t
·pch
e
j,o
·pj
corresponds to a real exchange rate index. Increases in this exchange rateindex denote a real appreciation of the CHF. (W ,j
si
)t
is the value of imported inputs ( inCHF expenses) from origin country j relative to the total value of imported inputs in sectorsi in year t. This term is included to obtain an average import weighted exchange rate foreach input sector si. Finally, these exchange rates are multiplied by R
si
so
, corresponding tothe share of imported inputs from sector si to total imported inputs in each output/exportsector so. The weights R
si
so
do not vary over time so that our approximation of sectoralimported input prices is primarily driven by changes in the bilateral real exchange ratesand import patterns across countries over time through (W i
si
)t
. The resulting variable,Importedinputcost
so,t
is an inverse measure of imported input costs. This means that arise in this measure corresponds to declining costs. In the paper, we employ the log valueof this measure in first differences.
3The classification of inputs (or intermediates) used in this paper is available at:http://wits.worldbank.org/wits/data_details.html
4The sector classification used to calculate the indices corresponds to those used in Swiss I-O tables.Each I-O table sector consists of one up to five 2-digit ISIC product groups.
19
