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O R I G I N A L P A P E R
Impact of exchange-rate variability on commodity
trade between U.S. and Germany
Mohsen Bahmani-Oskooee Masoomeh Hajilee
Published online: 29 April 2012 Springer Science+Business Media New York 2012
Abstract Previous studies that looked at the impact of exchange rate volatility on
trade flows used aggregate trade data between one country and rest of the world or
between two countries. More recent studies, however, have expanded the literature
by using a highly disaggregated commodity level data between two countries. In
this paper we consider the sensitivity of 131 industries that trade between U.S. and
Germany. We find that exports and imports of a majority of the industries react to
the real dollareuro volatility in the short run. The short-run effects, however, lastinto the long run only in almost 50 % of the industries. Among these industries,
while almost all U.S. exporting industries are affected favorably by exchange rate
volatility, a majority of the U.S. importing industries are affected adversely.
Keywords Exchange rate volatility Industry data Germany United states Bounds testing
JEL Classification F31
1 Introduction
In an effort to avoid exchange rate uncertainty and risk associated with it, most
European countries have joined the euro zone so that they can trade using a single
M. Bahmani-Oskooee (&)
The Center for Research on International Economics and Department of Economics, The Universityof WisconsinMilwaukee, Milwaukee, WI 53201, USA
e-mail: [email protected]
M. Hajilee
School of Business Administration, University of HoustonVictoria, Victoria, TX, USA
e-mail: [email protected]
1 3
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DOI 10.1007/s10663-012-9193-8
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currency where there is no currency conversion, hence no uncertainty. Since trade is
not only among the euro zone members but also with non-members, still each
member faces some uncertainty when she trades with a non-member, especially if
the non-member is a major trading partner. This is the case for the trade between
Germany and the U.S. Clearly, the issue was an important one when DM wasGermanys currency and it is as important today when euro serves as domestic
currency.
Review of the literature by Bahmani-Oskooee and Hegerty (2007) reveals that as
far as response of German trade flows to exchange rate uncertainty is concerned,
studies could be classified into two groups. The first includes those that have
employed aggregate trade data between Germany and rest of the world. Examples
are: Akhtar and Hilton (1984), Kenen and Rodrik (1986), Peree and Stenherr (1989),
Asseery and Peel (1991), Chowdhury (1993), Kroner and Lastrapes (1993), and
Arize and Shwiff (1998). The findings have been mixed, some finding negativeimpact and some finding positive effects. Of course, both effects are in line with
theoretical developments in the literature as advanced by Dellas and Zilberfarb
(1993). While risk-averse traders may chose to trade less because of price
uncertainty due to exchange rate fluctuations, some traders may chose actually trade
more to maximize their current revenue so that they can avoid any loss of future
income.
Suspecting that the above mentioned studies suffer from aggregation bias, a
second group has emerged in which studies use trade data at bilateral level between
Germany and her major trading partners. The list includes: Hooper and Kohlhagen(1978), Chan and Wong (1985), Cushman (1983,1986,1988), De Grauwe (1988),
Thursby and Thursby (1987), Koray and Lastrapes (1989), Peree and Stenherr
(1989), Bini-Smaghi (1991), Bleaney (1992), McKenzie and Brooks (1997),
Aristotelous (2001), and De Vita and Abbott (2004). Again, the findings from these
studies have been mixed also, depending on which trading partner of Germany is
considered. For example, concentrating on her major trading partner, the U.S., while
Hooper and Kohlhagen (1978) found negative effects on the GermanU.S. trade
flows, McKenzie and Brooks (1997) found positive effects.
Our main argument in this paper is that studies in the second group also suffer
from aggregation bias, that is, different industries that trade between the two
countries like Germany and the U.S. could react differently to exchange rate
uncertainty. Significant negative effects in some industries could easily be offset
by significant positive effects in some other industries yielding an insignificant
result when aggregate bilateral trade data are used. To demonstrate this, we
disaggregate the trade data between Germany and the U.S. by industry and
consider experiences of 131 industries that trade between the two countries. This
approach will identify industries that react to exchange rate uncertainty negatively,
positively, or do not react at all. Additional analysis could shed light on whether
size of an industry or any other characteristic matters. To this end, in Sect. 2 we
introduce the models and methods. Empirical results are discussed in Sect.3 with a
summary appearing in Sect. 4. Finally, Data definition and sources are provided in
an Appendix.
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2 The trade flow models and estimation method
Previous studies that investigated the link between industry trade and a measure of
exchange rate volatility basically adopted the same models that were used at the
aggregate level. Thus, in formulating the export and import demand models weadopt these models from Bahmani-Oskooee and Hegerty (2009a,b) who carried out
similar analysis for U.S.Mexico and U.S.Japan commodity trade respectively.
Since data are reported by the U.S., we specify these models from U.S. perspective.
The long-run export and import demand models, therefore, take the following
forms:
Ln Xit b0 b1Ln YG;t b2Ln REt b3Ln VARt et 1
Ln Mit a0 a1Ln YUS;t a2Ln REt a3Ln VARt et 2
where Xi in (1) denotes U.S. export volume of commodity i to Germany which is
assumed to depend positively on German income (YG) and negatively on the real
dollareuro rate, RE. As the Appendix shows, REis defined in a manner that an
increase reflects appreciation of the euro or depreciation of the dollar. Therefore,
estimates ofb1and b2are expected to be positive. As for the estimate ofb3, it could
be negative or positive. Similarly, in (2)Miis import volume of commodity i by the
U.S. from Germany which is assumed to depend positively on U.S. income, YU.S.,
and negatively on the real exchange rate, RE.1 Thus, while an estimate of a1 is
expected to be positive that ofa2
is expected to be negative. Once again, an estimateofa3 could be negative or positive.
Coefficient estimates of export and import demand models outlined by Eqs.
(1) and (2) only yield long-run effects. Since short-run effects could be different
and may or may not last into the long run, we express (1) and (2) in error-
correction formats by including short-run dynamics into the adjustment mech-
anism. The specification here follows Pesaran et al.s (2001) bounds testing or
Autoregressive Distributed Lag (ARDL) approach which allows us to estimate
the short-run and long-run effects in one single step. As such, the specifications
are:
D lnXi;t a bEUROtXn1j1
cjD lnXtj Xn2j0
cjD ln YGtj
Xn3j0
djD lnREtj
Xn4j0
jjD ln VARtj h1lnXi;t1 h2ln YGt1 h3lnREt1
h4ln VARt1 et
3
and
1 The negative relation between imports and the real exchange rate is based on the notion that
depreciation of dollar raises import prices, leading to a decline in import volume of commodity i.
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D lnMi;t d eEUROtXn5j1
/jD lnMi;tj Xn6j0
ujD ln YUStj
Xn7j0
pjD lnREtj
X
n8
j0#jD ln VARtj h5lnMi;t1 h6ln Y
USt1 h7lnREt1
h8ln VARt1 lt 4
The two specifications outlined by (3) and (4) are standard distributed lag models
where the linear combination of lagged level variables are added as a substitute for
lagged error term from (1) and (2) respectively. To justify the inclusion of lagged
level variables, Pesaran et al. (2001) propose applying the familiar F test for their
joint significance. If significance is established, not only the lagged level variables
belong to the model, but also they are said to be cointegrated. Clearly, the test
results will be sensitive to whether variables are integrated of order zero, I(0), or
integrated of order one, I(1). To account for integrating properties of the variables,
Pesaran et al. (2001) provide new critical values for the F test. An upper bound
critical value is produced when all variables are I (1) and a lower bound critical
value is introduced when variables are I (0). They demonstrate that upper bound
critical values could also be used if some variables are I(0) and some I(1). Since
most time-series variables are either I(0) or I(1), there is no need for pre-unit root
testing under this approach. Once cointegration is established, long-run effects are
derived by the estimates ofh2h4normalized onh1in (3) and by the estimates ofh6
h8 normalized on h5 in (4).2 The short-run effects are reflected by the estimates ofcoefficients attached to first-differenced variables in each model. Note that a dummy
variable (EURO) is also included in both models to account for introduction of the
euro in 1999. It takes a value of zero before 1999 and one thereafter.
3 The results
We estimate export and import demand models outlined by Eqs. (3) and (4) using
SITC-3-digit level annual data over the 19712009 period from 131 industries thattrade between U.S. and Germany. Following previous research, we estimate each
model by imposing a maximum of four lags on each first-differenced variable. We
then use the AIC criterion to select the optimum model in each industry. We first
report the results for export demand model. Due to volume of the results, they are
reported in two tables. While Table 1reports coefficient estimates, Table 2reports
the diagnostic statistics.
Since variable of interest is exchange rate volatility and its impact on the U.S.
exports to Germany, for brevity we only report the short-run coefficient estimates
for this variable. However, as can be seen from Table 1, the long-run coefficientestimates are reported for all variables. From the short-run estimates we gather that
at the 10 % significance level, there are 96 industries in which there is at least one
significant coefficient, implying that almost 75 % of the industries that export from
2 For details of normalization see Bahmani-Oskooee and Tanku (2008).
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Table1
Short-ru
nandlong-runcoefficientestimatesofU.S.exportmodel(absolute
valueoftratiosinparentheses)
Industry
Short-runcoefficientestimates
Long-runcoefficientestimates
DLnVARt
DLnVARt-1
DLnVARt-2
DLnVARt-3
Constant
LnYG
LnRE
LnVAR
Eurodummy
001Liveanimals
0.289(1.66)
-22.85(3.98)
8.04(5.88)
0.35(0.32)
0.52(1.64)
-0.88(1.50)
013Meatinairtight
containersnes
0.18(1.33)
-6.89(1.33)
3.19(2.57)
4.67(4.31)
0.24(1.39)
-0.75(1.89)
031Fish,freshand
simply
preserved
-0.73(2.45)
1.40(2.45)
1.73(3.46)
1.08(3.31)
25.98(5.09)
-5.84(4.55)
-3.54(3.35)
-1.79(3.92)
0.54(1.15)
032Fishinairtight
containers,nes
-0.68(0.01)
-0.36(2.93)
-0.34(4.20)
4.31(0.47)
1.99(1.06)
-0.35(0.24)
1.68(0.87)
0.96(0.82)
048Cerealpreparationsand
preparationsoffl
our
0.04(0.94)
-0.03(0.40)
-0.08(1.75)
-12.53(1.74)
6.15(3.23)
2.09(0.95)
0.59(0.99)
-1.25(1.16)
052Driedfruit
0.34(2.15)
-0.12(0.42)
-0.20(0.83)
-0.28(1.84)
-67.63(1.13)
20.68(1.31)
19.07(1.03)
4.15(1.39)
-4.62(0.77)
053Fruit,preserve
dand
fruitpreparations
0.20(1.91)
940.93(0.09)
-190.47(0.09)
-135.22(0.09)
30.88(0.10)
26.29(0.09)
054Vegetables,ro
otsand
tubers
0.18(1.70)
0.35(2.16)
0.20(1.92)
14.57(6.11)
-0.96(1.57)
2.28(4.87)
0.10(0.39)
0.02(0.09)
055Vegetables,ro
otsand
tuberspreserved
0.02(0.26)
-0.18(1.67)
-0.17(2.52)
22.16(0.56)
-0.92(0.13)
-3.50(0.63)
2.62(0.80)
2.04(0.71)
061Sugarandhon
ey
0.72(2.61)
15.36(3.43)
-1.14(1.07)
-3.34(3.68)
1.14(3.44)
0.54(1.36)
062Sugarconfectionery
0.43(3.43)
-0.92(3.14)
-0.63(2.78)
-0.29(2.19)
-15.94(4.11)
8.22(8.72)
0.42(0.56)
2.91(8.02)
-1.29(3.88)
073Chocolateand
other
foodpreparations
-0.05(0.85)
-0.07(0.63)
-0.13(2.05)
1.79(0.54)
1.86(2.26)
-1.04(1.53)
-0.01(0.04)
0.64(2.53)
075Spices
-0.39(2.19)
-16.83(2.11)
6.32(3.23)
0.40(0.26)
1.02(1.91)
-0.04(0.06)
081Feed.-stufffor
animals
excludingunmill
edcreals
0.09(0.96)
-7.49(1.01)
4.43(2.51)
0.89(0.50)
0.35(1.05)
-1.53(2.22)
099Foodpreparations,nes
0.04(0.24)
-0.35(1.28)
-0.56(2.30)
-0.26(1.69)
18.19(1.32)
-0.81(0.23)
-4.47(1.76)
1.25(0.85)
0.66(0.53)
112Alcoholicbeverages
0.05(0.95)
10.59(2.38)
0.69(0.66)
-0.95(1.09)
0.26(1.03)
0.23(0.52)
211Hidesandskins,-
excludingfurskins
-0.22(1.71)
-17.63(4.37)
5.75(6.06)
1.43(1.75)
-0.29(1.58)
-0.68(1.91)
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Table1
continued
Industry
Short-runcoefficientestimates
Long-runcoefficientestimates
DLnVARt
DLnVARt-1
DLnVARt-2
DLnVARt-3
Constant
LnYG
LnRE
LnVAR
Eurodummy
212Furskins,undressed
0.53(1.83)
17.35(3.45)
-2.29(1.89)
-0.79(0.82)
0.53(1.83)
0.22(0.45)
231Cruderubber-including
synthetic
49.24(1.16)
49.24(1.16)
-7.17(0.77)
-8.39(1.31)
2.39(1.93)
4.48(1.38)
243Wood,shaped
or
simplyworked
0.12(0.89)
-37.28(1.92)
10.81(2.29)
5.43(1.45)
0.45(0.83)
1.49(1.02)
251Pulpandwastepaper
0.13(0.53)
-0.62(1.27)
-0.94(2.23)
-0.51(1.85)
-46.78(4.38)
14.40(5.00)
4.27(2.00)
2.41(1.76)
-2.61(2.42)
262Woolandotheranimal
hair
-0.54(2.99)
-0.53(1.94)
-0.43(2.49)
6.82(1.23)
-0.71(-0.5
2)
-2.34(2.08)
-0.96(1.86)
-0.21(0.45)
266Syntheticand
regeneratedfibers
0.01(0.04)
-0.39(2.02)
-0.45(2.63)
-0.20(1.78)
-0.77(0.24)
2.88(3.41)
0.72(1.11)
0.45(1.06)
0.29(0.94)
267Wastematerialsfrom
textilefabric
-0.04(0.36)
-0.91(4.10)
-0.73(3.52)
-0.31(2.42)
-7.80(2.30)
4.47(4.89)
1.70(2.47)
1.35(2.89)
-0.99(3.04)
273Stone,sandan
dgravel
0.14(0.72)
-0.39(0.03)
1.55(0.46)
-4.79(1.52)
0.41(0.70)
1.14(0.96)
276Othercrudem
inerals
0.04(0.55)
0.17(2.23)
1.22(0.33)
1.46(1.77)
-0.01(0.01)
-0.35(0.99)
1.22(0.33)
283Oresandconc
entrates
ofnon-ferrous
-0.03(0.07)
120.18(4.24)
-26.58(3.87)
-15.63(3.23)
-0.09(0.07)
8.12(2.83)
284Non-ferrousm
etal
scrap
0.18(0.89)
7.10(0.67)
1.22(0.47)
-2.88(1.28)
1.11(1.79)
-0.59(0.75)
291Crudeanimalm
aterials,
nes
-0.03(0.31)
-0.28(2.22)
-0.20(2.55)
7.13(1.21)
1.09(0.72)
0.90(0.56)
0.52(0.91)
-1.14(2.06)
292Crudevegetab
le
materials,nes
0.02(0.22)
-8.94(3.13)
4.39(6.32)
0.82(1.41)
0.03(0.22)
0.40(1.65)
321Coal,cokeand
briquetters
1.03(1.59)
-18.16(0.31)
7.08(0.48)
10.61(0.83)
2.59(1.22)
-0.35(0.10)
332PetroleumProducts
0.18(0.94)
-11.59(1.87)
4.89(3.24)
-1.52(1.26)
-0.47(0.73)
0.94(1.52)
411Animaloilandfats
0.01(0.04)
-0.31(2.09)
0.42(0.15)
1.89(2.62)
-1.73(2.86)
0.58(3.04)
-0.32(1.37)
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Table1
continued
Industry
Short-runcoefficientestimates
Long-runcoefficientestimates
DLnVARt
DLnVARt-1
DLnVARt-2
DLnVARt-3
Constant
LnYG
LnRE
LnVAR
Eurodummy
422Otherfixedve
getable
oils
0.07(0.36)
7.84(1.21)
-0.30(0.19)
0.28(0.23)
0.13(0.35)
1.95(3.13)
431Animalandvegetable
oils
-0.18(0.53)
-1.44(2.45)
-1.37(2.68)
0.99(3.09)
-22.50(5.03)
7.56(6.41)
2.45(2.70)
0.76(1.31)
0.19(0.44)
512Organicchemicals
0.16(2.93)
-0.11(1.83)
-1.04(0.74)
3.79(10.55)
0.02(0.07)
0.48(5.12)
0.10(1.01)
513Inorganicchem
ical
elements,oxides
and
halogensalts
0.15(1.95)
3.25(1.92)
2.29(5.54)
-0.53(1.67)
0.36(2.65)
-0.24(1.57)
514Otherinorganic
chemicals
0.21(2.09)
-0.19(1.23)
0.15(1.57)
-5.93(1.36)
4.74(4.24)
1.24(1.32)
1.24(1.32)
0.35(1.06)
515Radioactivean
d
associatedmaterial
-0.33(1.62)
-0.66(3.23)
5.17(4.46)
87.80(1.55)
-16.34(1.25)
-18.90(1.86)
2.18(1.73)
6.39(1.62)
531Syntheticorga
nic
dyestuffs
-0.03(0.51)
-0.22(2.85)
-0.18(3.83)
-107.74(0.16)
22.09(0.19)
-4.07(0.12)
-6.83(0.13)
0.46(0.03)
532Dyeingandtanning
extracts,synthetictanning
materials
0.21(1.65)
-2.68(0.25)
3.22(1.31)
-2.16(1.12)
0.88(1.50)
-1.05(1.19)
533Pigments,pain
ts,
varnishes
-0.14(1.23)
-0.49(2.61)
-0.23(2.00)
-1.55(0.36)
3.82(3.59)
-0.90(1.20)
0.92(2.37)
-0.37(1.07)
541Medicinal
pharmaceuticalp
roducts
0.08(1.02)
-9.84(3.51)
5.20(7.97)
0.17(0.34)
-0.14(0.88)
0.78(2.94)
551Essentialoils,
perfume
andflavor
0.23(2.87)
-0.25(1.98)
-0.16(1.95)
-10.62(6.39)
5.05(12.35)
0.01(0.04)
0.68(4.57)
-0.41(2.78)
553Perfumery,cosmetics,
dentifrices
-0.02(0.24)
-0.48(3.68)
-0.18(2.31)
-6.63(1.05)
5.59(3.79)
-1.18(0.97)
1.93(4.04)
0.03(0.07)
554Soaps,cleansingand
polishing
-0.12(1.66)
-9.24(1.68)
4.23(3.48)
0.28(0.24)
-0.44(1.09)
-0.35(0.72)
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Table1
continued
Industry
Short-runcoefficientestimates
Long-runcoefficientestimates
DLnVARt
DLnVARt-1
DLnVARt-2
DLnVARt-3
Constant
LnYG
LnRE
LnVAR
Eurodummy
571Explosivesand
pyrotechnic
0.20(1.23)
-35.54(2.94)
10.55(3.55)
7.86(3.06)
0.47(1.11)
-1.19(1.34)
581Plasticmateria
ls,nes
0.02(0.52)
0.09(1.48)
-0.12(2.90)
-2.86(1.27)
4.17(7.36)
-0.12(0.23)
0.52(2.20)
-0.52(2.11)
599Chemicalmate
rialsand
products,nes
0.11(2.02)
2.57(1.38)
2.63(5.86)
-0.96(2.78)
0.40(2.49)
0.12(0.66)
611Leather
-0.21(2.64)
-0.61(4.58)
-0.39(4.57)
-9.45(3.20)
4.94(6.74)
2.37(4.01)
0.53(1.87)
-1.02(3.59)
612Manufacturers
of
leather
-0.14(2.97)
-0.14(1.78)
-0.13(2.89)
-3.91(0.77)
2.51(1.99)
-0.58(0.49)
-0.69(2.07)
0.50(1.34)
613Furskins,tann
edor
dressed
0.04(0.26)
20.33(5.61)
-2.96(3.40)
-1.26(1.79)
0.05(0.26)
0.35(0.95)
621Materialsofrubber
-0.22(3.07)
-0.14(0.95)
-0.24(3.03)
-8.84(5.47)
4.11(9.92)
0.56(1.72)
-0.58(3.28)
-0.14(0.89)
629Articlesofrub
ber,nes
-0.08(1.46)
0.09(1.51)
199.01(0.11)
-23.91(0.09)
-68.90(0.11)
30.15(0.11)
9.16(0.11)
631Veneers,plywood
boards
-0.07(1.06)
-0.63(5.00)
-0.52(4.58)
-0.18(2.34)
-24.01(4.62)
8.98(6.15)
4.45(3.76)
1.36(2.69)
1.31(2.37)
632Woodmanufactures,
nes
-0.73(5.41)
-1.48(0.89)
2.68(6.23)
-0.10(0.29)
0.24(1.51)
0.41(2.91)
633CorkManufac
turers
0.35(2.98)
-21.99(2.76)
8.17(4.11)
2.05(1.12)
1.79(3.64)
-2.10(3.44)
641Paperandpaperboard
0.14(1.47)
-0.84(3.73)
-0.62(3.45)
-0.26(2.48)
-20.54(6.77)
9.39(11.48)
2.11(3.24)
2.26(6.67)
-0.88(3.05)
642Articlesofpaperand
paperboard
0.08(1.32)
3.40(0.39)
2.16(1.07)
-1.43(0.92)
0.61(1.30)
0.27(0.37)
651Textileyarnandthread
0.09(1.11)
-0.17(1.32)
-0.17(1.32)
-11.66(1.97)
6.17(4.02)
4.70(3.35)
1.14(2.25)
-0.92(2.14)
652Cottonfabrics,woven
excludingnarrow
or
specialfabrics
0.02(0.21)
-0.42(3.20)
-0.27(3.33)
-6.03(1.42)
4.86(4.07)
1.67(1.87)
1.67(2.71)
-1.05(2.44)
653Textfabricsw
oven
excludingnarrow
or
specialfabrics
0.19(2.77)
-0.29(3.23)
-0.09(1.58)
-10.89(2.31)
6.28(5.37)
2.23(2.29)
1.58(3.52)
-1.34(3.82)
294 Empirica (2013) 40:287324
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Table1
continued
Industry
Short-runcoefficientestimates
Long-runcoefficientestimates
DLnVARt
DLnVARt-1
DLnVARt-2
DLnVARt-3
Constant
LnYG
LnRE
LnVAR
Eurodummy
654Tulle,lace,em
broidery,
ribbons
-0.09(0.97)
-14.57(4.64)
5.33(7.23)
2.29(3.71)
-0.17(0.98)
-0.87(2.78)
655Specialtextile
fabrics
0.06(0.95)
0.02(0.23)
-0.09(1.39)
-7.74(1.43)
4.43(3.41)
1.09(0.82)
0.08(0.19)
-0.06(0.13)
656Made-uparticles,
whollyorchiefly
0.12(1.53)
-9.39(2.28)
5.25(5.16)
1.19(1.33)
0.83(2.72
-0.84(2.04)
657Floorcovering
s,
tapestries,etc.
-0.15(1.69)
-3.64(0.28)
2.43(0.86)
2.11(0.66)
-1.23(0.83)
-0.92(0.59)
661Lime,cement
and
fabricatedbuilding
materials
0.17(1.01)
-0.26(0.87)
-0.62(2.21)
-0.34(1.85)
1.06(0.74)
1.68(4.33)
-1.12(3.69)
0.14(0.73)
0.68(5.14)
662Clayandrefra
ctory
constructionmaterials
0.43(3.69)
-0.36(1.55)
-0.32(1.70)
-0.35(2.86)
-4.79(1.35)
4.97(5.33)
-0.51(0.72)
1.95(4.16)
-0.82(2.38)
663Mineralmanufactures,
nes
0.20(3.03)
-0.29(2.26)
-0.20(1.92)
-0.12(1.90)
-3.82(3.47)
4.07(14.66)
-0.72(3.35)
0.74(6.08)
-0.32(3.24)
664Glass
-0.07(1.62)
-0.26(2.79)
-0.11(1.38)
0.06(1.12)
0.56(0.28)
3.00(6.06)
-0.19(0.48)
0.51(2.99)
0.06(0.35)
665Glassware
0.15(2.41)
-0.16(0.09)
3.16(7.99)
-0.08(0.27)
0.56(4.27)
-0.68(4.31)
667Pearlsandpreciousand
semi-precioussto
nes
0.01(0.34)
-0.14(2.15)
-0.10(2.45)
2.91(1.32)
2.34(4.20)
-0.26(0.61)
0.67(2.73)
-0.06(0.31)
671Pigironand
spiegeleisen,spongeiron
0.63(4.64)
-0.54(3.19)
16.48(7.89)
-0.33(0.62)
-1.69(4.04)
1.86(7.75)
0.78(3.37)
672Ingotsandothe
r
primaryformsofiron
0.11(0.75)
-0.90(3.29)
-1.56(0.37)
4.14(3.51)
1.28(1.37)
1.39(2.21)
-1.29(3.19)
673Ironandsteel
bars
0.04(0.42)
0.75(3.47)
0.20(1.61)
5.45(3.31)
0.97(2.39)
0.34(1.00)
-0.69(5.35)
0.12(0.86)
674Universals,platesand
sheetsofiron
0.07(0.71)
-0.42(2.15)
-0.57(3.12)
-0.31(2.82)
8.15(1.56)
1.74(1.21)
1.17(0.63)
0.96(1.17)
-0.05(0.09)
677Ironandsteel
wire
0.21(2.58)
-0.02(0.11)
-0.28(2.02)
-0.18(2.05)
6.79(2.52)
1.12(1.55)
-0.03(0.05)
0.61(1.77)
0.01(0.05)
Empirica (2013) 40:287324 295
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Table1
continued
Industry
Short-runcoefficientestimates
Long-runcoefficientestimates
DLnVARt
DLnVARt-1
DLnVARt-2
DLnVARt-3
Constant
LnYG
LnRE
LnVAR
Eurodummy
678Tubes,pipesa
nd
fittingsofiron
0.13(0.77)
23.89(1.98)
-2.56(0.90)
-3.74(1.79)
0.34(0.83)
1.69(1.58)
679Ironsteelcastings
forgings
-0.19(1.82)
-0.03(0.22)
0.18(1.91)
10.65(1.68)
-0.37(0.22)
-1.12(0.97)
-0.37(0.21)
0.31(0.47)
681Silverandplatinum
groupmetals
0.03(0.12)
-12.76(3.07)
5.84(5.75)
-0.21(0.27)
0.58(1.56)
0.26(0.65)
682Copper
0.07(0.96)
-0.50(3.19)
-0.55(3.66)
-0.19(1.90)
3.40(1.88)
0.64(2.89)
0.52(1.41)
0.64(2.89)
0.57(3.38)
683Nickel
-0.43(2.75)
0.54(2.04)
0.60(2.67)
0.30(2.31)
-35.01(0.69)
18.92(0.89)
2.39(0.33)
11.57(0.83)
-3.54(0.67)
684Aluminum
0.05(0.58)
-0.50(2.86)
-0.59(3.85)
-0.25(2.34)
11.06(0.88)
1.19(0.41)
-2.87(1.14)
1.09(1.71)
0.85(1.21)
685Lead
0.32(0.88)
-0.69(1.06)
-1.49(2.57)
-1.47(3.89)
27.06(2.62)
-3.30(1.29)
-3.17(1.52)
1.58(2.14)
1.78(2.43)
686Zinc
-0.09(0.23)
47.10(2.42)
-9.63(2.04)
-3.46(0.89)
-0.27(0.23)
2.75(1.36)
687Tin
1.60(3.74)
-2.93(3.41)
-2.25(3.13)
-1.33(3.06)
-16.44(1.99)
9.18(4.47)
3.14(1.88)
4.95(6.26)
-0.68(0.95)
689Miscell.non-ferrous
basemetals
-0.01(0.09)
0.20(1.58)
0.22(2.00)
0.21(2.93)
-9.58(1.19)
4.09(2.26)
0.33(0.21)
-0.66(1.38)
0.14(0.28)
691Finishedstructural
parts
0.13(1.74)
0.18(1.63)
0.15(2.14)
-13.16(3.68)
5.75(6.58)
1.44(1.89)
0.32(1.39)
-0.12(0.47)
692Metalcontainersfor
storageortransport
0.11(0.75)
-0.39(2.38)
34.65(0.39)
0.60(0.05)
-5.31(0.49)
7.13(0.67)
-0.31(0.11)
693Wireproducts
and
fencinggrills
-0.01(0.05)
-0.35(2.84)
-0.31(2.94)
-0.14(1.98)
5.19(3.71)
1.58(4.24)
-0.51(1.78)
0.49(2.58)
-0.13(0.99)
694Nails,screws,
nuts,
bolts,rivets
0.03(0.50)
-0.12(1.01)
-0.25(2.30)
-0.12(1.78)
-3.66(1.36)
3.76(5.43)
-0.11(0.19)
0.49(1.71)
0.07(0.28)
695Toolsforuseinthe
handorinmachines
0.03(0.75)
-0.46(5.36)
-0.42(5.35)
-0.23(4.59)
-2.80(2.58)
4.01(13.73)
-0.03(0.11)
0.71(4.68)
-0.24(2.29)
696Cutlery
0.02(0.79)
-0.19(3.34)
-0.14(2.94)
-0.05(1.79)
-0.52(0.44)
3.06(9.62)
0.27(1.07)
0.49(3.42)
-0.32(2.52)
697Householdequipment
0.09(1.27)
-0.24(2.03)
-0.13(1.22)
-0.11(1.69)
-4.48(2.01)
3.66(6.66)
0.81(1.81)
0.52(2.39)
0.05(0.27)
296 Empirica (2013) 40:287324
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Table1
continued
Industry
Short-runcoefficientestimates
Long-runcoefficientestimates
DLnVARt
DLnVARt-1
DLnVARt-2
DLnVARt-3
Constant
LnYG
LnRE
LnVAR
Eurodummy
698Manufacturesofmetal,
nes
0.01(0.24)
-0.21(2.94)
-0.24(3.85)
-0.11(2.79)
-9.33(3.98)
5.61(8.86)
1.21(2.34)
0.80(3.24)
-0.34(1.77)
711Powergenerating
machinery,other
0.15(2.49)
-0.21(2.04)
-0.25(2.98)
-0.11(1.86)
-7.26(2.84)
5.62(8.25)
0.33(0.48)
0.75(2.39)
-0.78(1.91)
712Agriculturalm
achinery
0.04(0.48)
-0.20(1.56)
-0.25(2.15)
-0.20(2.80)
18.95(2.19)
-0.62(0.29)
2.14(2.10)
1.17(1.73)
1.09(1.41)
714Officemachines
-0.08(2.02)
-0.14(1.56)
-0.13(2.01)
-0.06(1.55)
-1.98(0.71)
4.46(6.55)
0.63(0.95)
1.17(3.11)
-0.79(3.00)
715Metalworking
machinery
-0.06(0.75)
-0.43(3.16)
-0.36(3.10)
-0.16(2.07)
1.44(0.55)
3.16(4.97)
-0.27(0.58)
0.61(2.48)
-0.54(2.57)
717Textileandleather
machinery
0.06(0.71)
-0.11(1.39)
2.08(0.81)
3.09(4.90)
0.24(0.49)
0.69(2.49)
-1.17(4.88)
718Machinesforspecial
industries
0.02(0.53)
-0.38(3.68)
-0.14(2.64)
-0.15(2.64)
-3.77(1.81)
4.76(8.59)
0.42(0.90)
0.79(3.18)
-0.86(3.68)
719Machineryand
appliances-nonelectrical
-0.01(0.07)
-2.53(0.24)
4.27(1.72)
1.18(0.40)
-0.04(0.07)
-1.11(0.76)
722Electricpower
machineryandswitches
-0.01(0.21)
-0.14(2.52)
-0.11(3.02)
-1.11(0.19)
3.98(2.83)
-0.82(0.92)
0.55(1.06)
-0.50(1.07)
723Equipmentfor
distributingelectricity
-0.01(0.01)
-0.47(2.71)
-0.35(3.35)
-10.62(2.30)
5.44(5.33)
0.07(0.08)
0.65(1.18)
0.22(0.60)
724Telecommunic
ations
apparatus
-0.14(2.99)
-0.24(3.08)
-0.14(2.64)
-7.11(2.38)
4.79(6.05)
0.62(1.08)
0.38(1.14)
0.18(0.56)
725Domesticelectrical
equipment
-0.01(0.02)
-0.69(3.48)
-0.29(1.81)
-0.12(1.19)
-24.59(4.55)
9.32(6.67)
3.28(2.79)
1.12(2.75)
-0.46(1.16)
726Electricalapparatusfor
medicalpurpose
0.03(0.59)
-1.01(0.16)
3.87(2.64)
-0.72(0.54)
0.81(1.77)
0.16(0.31)
729Otherelectrica
l
machinery
-0.02(0.28)
0.05(0.39)
-0.11(1.17)
-0.15(2.53)
6.40(0.06)
2.16(0.08)
-15.85(0.14)
3.47(0.19)
6.83(0.14)
731Railwayvehicles
0.27(1.94)
-0.14(0.03)
3.99(3.38)
-1.08(1.22)
1.88(3.78)
-0.82(1.76)
Empirica (2013) 40:287324 297
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Table1
continued
Industry
Short-runcoefficientestimates
Long-runcoefficientestimates
DLnVARt
DLnVARt-1
DLnVARt-2
DLnVARt-3
Constant
LnYG
LnRE
LnVAR
Eurodummy
732Roadmotorvehicles
0.01(0.19)
-2.03(0.48)
4.33(4.32)
1.67(1.78)
0.03(0.19)
-0.50(1.24)
733Roadvehicles
other
thanmotor
-0.19(2.33)
0.58(2.98)
0.18(1.77)
-3.63(1.95)
2.34(5.51)
1.49(4.10)
-1.03(6.31)
0.62(4.74)
734Aircraft
0.36(2.04)
-15.05(3.55)
6.78(6.54)
0.67(0.83)
0.51(1.86)
0.08(0.18)
735Shipsandboats
0.95(2.01)
4.07(0.77)
1.95(1.52)
-0.31(0.28)
0.62(1.92)
1.18(2.33)
812Sanitary,plum
bing,
heating
-0.05(0.72)
-0.34(3.28)
-0.24(3.67)
3.79(0.33)
2.19(0.88)
-1.13(0.53)
0.88(0.92)
1.14(1.35)
821Furniture
0.05(0.82)
-2.12(0.25)
3.87(1.97)
0.97(0.56)
0.39(0.88)
-0.87(1.08)
831Travelgoods,handbags
andsimilar
0.05(0.76)
-0.29(2.87)
-0.14(2.13)
3.37(0.69)
2.62(2.18)
0.02(0.03)
1.67(1.99)
0.26(0.52)
841Clothingexceptfur
clothing
0.01(0.09)
-0.37(3.34)
-0.18(1.85)
-0.09(1.63)
-13.79(2.52)
7.69(4.27)
3.05(2.26)
2.33(2.34)
-1.05(2.11)
842Furclothingand
articlesofartificial
clothing
-0.04(0.30)
-0.49(2.26)
-0.32(2.43)
47.46(1.92)
-6.55(1.13)
-7.28(1.65)
3.23(2.48)
1.02(0.65)
851Footwear
-0.05(0.91)
-13.36(2.95)
5.44(5.04)
2.78(2.95)
-0.16(0.91)
-0.67(1.80)
861Scientific,med
ical,
optical,instruments
0.12(2.15)
-0.08(1.43)
-2.83(2.08)
4.12(11.97)
0.63(2.13)
0.30(3.02)
0.14(1.29)
862Photographic,
cinematographic
supplies
-0.02(0.23)
-0.17(1.82)
1.21(0.44)
2.59(3.92)
-0.60(1.19)
0.29(1.18)
-0.54(2.21)
863Developed
cinematographic
film
-0.07(0.47)
31.35(3.15)
-6.44(2.55)
-4.97(2.57)
-0.22(0.44)
2.49(2.07)
864Watchesandc
locks
-0.01(0.19)
-0.03(0.33)
-0.08(1.56)
-4.47(0.21)
3.46(0.79)
4.07(0.59)
-0.46(0.32)
-1.00(0.69)
891Musicalinstruments,
soundrecorders
0.01(0.06)
-0.18(2.67)
-0.12(2.53)
-5.99(1.75)
4.78(5.52)
1.24(1.72)
0.78(2.65)
-0.49(1.96)
892Printedmatter
0.07(2.30)
-0.18(3.13)
-0.12(2.66)
-0.08(2.52)
-2.22(1.31)
3.73(8.11)
0.46(1.09)
0.64(3.77)
-0.33(2.22)
298 Empirica (2013) 40:287324
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Table1
continued
Industry
Short-runcoefficientestimates
Long-runcoefficientestimates
DLnVARt
DLnVARt-1
DLnVARt-2
DLnVARt-3
Constant
LnYG
LnRE
LnVAR
Eurodummy
893Articlesofartificial
plasticmate
-0.04(0.86)
106.45(0.06)
-26.86(0.04)
-97.18(0.06)
10.77(0.06)
23.63(0.05)
894perambulators,toys,
games
-0.04(1.02)
-0.29(4.56)
-0.28(4.72)
-0.12(3.02)
2.98(0.32)
2.88(1.67)
0.14(0.09)
0.98(1.26)
-0.64(1.60)
895Officeandstationary
supplies,nes
0.01(0.20)
-0.34(3.45)
-0.20(3.30)
-9.13(1.45)
6.11(2.87)
2.13(1.35)
1.92(1.53)
-1.42(1.77)
896Worksofart,collectors
pieces
0.02(0.16)
18.64(0.47)
-0.89(0.11)
-3.25(0.59)
0.18(0.16)
-0.73(0.38)
897Jewellery
0.05(0.74)
5.36(1.23)
1.61(1.67)
-0.18(0.25)
0.18(0.78)
0.15(0.40)
899Manufactured
articles,
nes
0.05(0.78)
0.01(0.12)
-0.12(1.84)
-9.92(1.43)
5.26(2.95)
1.49(1.06)
0.37(0.73)
0.35(0.77)
n.e.s.notelsewherespecified
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Table2
Diagnos
ticstatistics
Industry
Diagnostics
F
ECMt-
1
LM
RESET
CUSUM
CUSUMSQ
Adj.R2
Size
001Liveanimals
2.01
-0.43
(4.31)
13.95
2.04
S
S
0.2
6
0.013
013Meatinairtig
htcontainersnes
3.20
-0.21
(2.41)
2.87
0.11
S
S
0.0
6
0.006
031Fish,freshan
dsimplypreserved
4.56
-1.24
(5.16)
4.59
6.05
S
S
0.6
2
0.014
032Fishinairtightcontainers,nes
2.19
-0.17
(2.81)
0.34
4.26
S
S
0.3
8
0.005
048Cerealprepar
ationsandpreparationsofflour
2.11
-0.13
(3.13)
1.63
1.71
S
S
0.3
3
0.035
052Driedfruit
6.15
-0.14
(3.43)
0.62
6.84
US
S
0.8
0
0.002
053Fruit,preserv
edandfruitpreparations
2.35
-0.01
(3.15)
2.84
0.16
S
S
0.2
5
0.038
054Vegetables,rootsandtubers
7.42
-0.79
(6.42)
0.20
6.74
S
S
0.4
8
0.072
055Vegetables,rootsandtuberspreserved
1.38
-0.08
(2.57)
1.35
8.58
S
S
0.4
2
0.008
061Sugarandhoney
5.74
-1.24
(5.64)
0.45
1.27
S
S
0.5
2
0.003
062Sugarconfectionery
3.15
-0.42
(3.48)
0.03
0.39
US
S
0.2
8
0.032
073Chocolateandotherfoodpreparations
4.11
-0.55
(4.76)
0.39
5.63
S
S
0.5
1
0.035
075Spices
2.12
-0.28
(3.21)
0.16
5.09
S
S
0.2
7
0.006
081Feed.-stufffo
ranimalsexcludingunmilledcreals
3.01
-0.26
(4.08)
0.32
0.33
S
S
0.3
9
0.039
099Foodpreparations,nes
1.86
-0.22
(2.83)
1.48
10.39
S
S
0.2
4
0.039
112Alcoholicbeverages
2.45
-0.17
(3.58)
3.17
2.89
S
S
0.2
0
0.405
211Hidesandskins,-excludingfurskins
5.58
-0.67
(4.88)
0.21
0.13
S
S
0.4
5
0.004
212Furskins,undressed
5.96
-0.92
(5.45)
0.66
1.47
S
S
0.4
1
0.005
231Cruderubber-includingsynthetic
5.34
-0.15
(4.53)
4.13
4.18
S
US
0.6
4
0.024
243Wood,shapedorsimplyworked
3.31
-0.25
(3.77)
6.53
0.57
S
US
0.2
6
0.032
251Pulpandwas
tepaper
3.34
-0.39
(4.12)
0.06
0.92
S
S
0.3
0
0.004
262Woolandoth
eranimalhair
5.34
-0.69
(5.16)
2.31
0.58
S
US
0.3
8
0.007
266Syntheticand
regeneratedfibers
3.54
-0.55
(4.41)
0.86
3.11
S
US
0.3
4
0.110
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CUSUM
CUSUMSQ
Adj.R2
Size
267Wastematerialsfromtextilefabric
6.04
-0.58
(5.68)
0.29
0.53
S
S
0.4
1
0.006
273Stone,sanda
ndgravel
2.92
-0.33
(3.72)
2.48
3.80
S
S
0.2
1
0.001
276Othercrudem
inerals
3.84
-0.44
(4.62)
0.93
0.34
S
US
0.3
4
0.012
283Oresandconcentratesofnon-ferrous
4.69
-0.35
(4.39)
3.71
1.63
S
S
0.3
2
0.038
284Non-ferrousmetalscrap
3.77
-0.47
(4.21)
0.12
0.01
S
S
0.3
4
0.021
291Crudeanimalmaterials,nes
1.27
-0.20
(2.29)
1.05
1.23
S
S
0.5
1
0.052
292Crudevegetablematerials,nes
4.13
-0.46
(3.29)
2.38
0.17
US
S
0.1
6
0.032
321Coal,cokean
dbriquetters
2.52
-0.39
(3.76)
0.11
0.05
S
S
0.2
9
0.130
332PetroleumProducts
2.37
-0.54
(3.57)
0.54
1.02
S
US
0.3
9
0.189
411Animaloilan
dfats
5.82
-0.88
(5.06)
0.96
0.93
S
US
0.4
1
0.002
422Otherfixedvegetableoils
1.76
-0.44
(3.03)
3.11
0.21
S
S
0.4
7
0.008
431Animalandv
egetableoils
5.37
-1.07
(5.22)
1.63
0.92
S
S
0.4
1
0.007
512Organicchem
icals
7.34
-0.91
(6.22)
4.29
5.17
S
S
0.5
7
1.669
513Inorganicche
micalelements,oxidesandhalog
ensalts
4.23
-0.63
(4.78)
0.08
10.82
S
S
0.3
1
0.261
514Otherinorgan
icchemicals
2.38
-0.42
(3.56)
0.66
1.99
S
S
0.4
0
0.174
515Radioactivea
ndassociatedmaterial
7.62
-0.24
(6.46)
1.42
5.85
S
S
0.6
5
0.085
531Syntheticorg
anicdyestuffs
4.85
0.02
(5.15)
3.41
0.83
S
S
0.6
3
0.283
532Dyeingandtanningextracts,synthetictanning
materials
1.98
-0.27
(3.08)
0.30
7.74
S
US
0.1
9
0.005
533Pigments,paints,varnishes
2.44
-0.48
(3.45)
0.34
2.61
S
S
0.4
6
0.140
541Medicinalpharmaceuticalproducts
5.00
-0.61
(4.42)
1.15
1.33
S
S
0.3
4
1.101
551Essentialoils,perfumeandflavor
6.06
-0.85
(5.76)
1.59
5.68
S
S
0.4
8
0.013
553Perfumery,cosmetics,dentifrices
5.08
-0.31
(5.32)
0.17
0.21
S
S
0.4
7
0.084
554Soaps,cleans
ingandpolishing
1.88
-0.27
(3.15)
0.27
1.71
S
S
0.2
1
0.046
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F
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1
LM
RESET
CUSUM
CUSUMSQ
Adj.R2
Size
571Explosivesan
dpyrotechnic
2.78
-0.42
(3.65)
1.15
15.21
S
S
0.3
5
0.066
581Plasticmaterials,nes
3.63
-0.32
(4.54)
0.22
1.35
S
S
0.5
2
0.017
599ChemicalMa
terialsandproducts,nes
2.09
-0.32
(3.24)
0.36
0.59
S
S
0.1
8
0.649
611Leather
5.26
-0.54
(5.42)
1.74
3.19
S
S
0.5
6
0.560
612Manufacturer
sofleather
2.73
-0.25
(3.64)
3.58
6.79
S
S
0.5
8
0.084
613Furskins,tan
nedordressed
3.89
-0.61
(4.23)
0.69
1.20
S
S
0.2
8
0.020
621Materialsofrubber
4.09
-0.78
(4.31)
0.36
1.87
S
S
0.6
3
0.015
629Articlesofru
bber,nes
4.46
0.01
(5.01)
4.18
0.04
S
S
0.4
9
0.083
631Veneers,plyw
oodboards
6.61
-0.31
(6.11)
1.53
4.82
S
S
0.5
4
0.280
632Woodmanufactures,nes
7.48
-0.66
(6.47)
0.54
1.46
S
S
0.5
4
0.222
633CorkManufacturers
8.07
-0.32
(5.84)
0.07
0.81
S
S
0.5
5
0.003
641Paperandpaperboard
5.92
-0.48
(5.73)
1.56
4.04
S
S
0.5
1
0.092
642Articlesofpa
perandpaperboard
0.93
-0.14
(2.17)
0.08
0.03
S
US
0.0
6
1.121
651Textileyarnandthread
6.21
-0.27
(5.75)
0.08
0.11
S
S
0.4
5
0.659
652Cottonfabrics,wovenexcludingnarroworspe
cialfabrics
3.94
-0.32
(4.67)
0.27
2.19
S
S
0.5
0
0.071
653Textfabricswovenexcludingnarroworspecia
lfabrics
2.29
-0.22
(2.65)
9.63
4.42
S
S
0.2
2
0.111
654Tulle,lace,embroidery,ribbons
4.33
-0.59
(4.78)
0.45
0.90
S
S
0.3
7
0.067
655Specialtextilefabrics
3.10
-0.27
(4.19)
1.36
9.52
S
S
0.4
5
0.249
656Made-uparticles,whollyorchiefly
4.82
-0.33
(5.02)
0.62
7.47
S
S
0.4
2
0.001
657Floorcoverin
gs,tapestries,etc.
3.71
-0.14
(3.57)
3.17
0.28
S
S
0.2
0
0.187
661Lime,cementandfabricatedbuildingmaterials
6.99
-1.93
(5.79)
1.93
0.17
S
S
0.6
5
1.100
662Clayandrefr
actoryconstructionmaterials
3.19
-0.51
(3.77)
1.38
7.82
S
S
0.3
9
0.010
663Mineralmanufactures,nes
5.55
-1.02
(5.57)
1.22
1.03
S
S
0.4
5
0.034
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CUSUM
CUSUMSQ
Adj.R2
Size
664Glass
3.36
-0.56
(3.71)
6.14
3.12
S
S
0.4
5
0.021
665Glassware
4.38
-0.49
(4.51)
0.76
1.62
S
S
0.2
9
0.054
667Pearlsandpreciousandsemi-preciousstones
2.63
-0.39
(3.31)
0.16
2.53
S
S
0.2
3
0.022
671Pigironandspiegeleisen,spongeiron
5.12
-0.76
(4.66)
0.04
2.58
S
S
0.3
9
0.659
672Ingotsandoth
erprimaryformsofiron
4.67
-0.58
(4.84)
0.01
0.16
S
US
0.4
2
0.561
673Ironandsteelbars
9.25
-1.18
(6.89)
0.43
0.32
S
S
0.5
9
0.081
674Universals,platesandsheetsofiron
3.78
-0.33
(4.49)
0.09
0.01
S
US
0.4
9
0.020
677Ironandsteelwire
1.75
-0.48
(3.15)
0.33
3.46
S
US
0.4
5
0.233
678Tubes,pipes
andfittingsofiron
2.44
-0.33
(3.63)
0.77
0.61
S
US
0.3
6
0.078
679Ironsteelcas
tingsforgings
12.06
-0.29
(8,29)
12.49
13.83
S
S
0.6
8
0.782
681Silverandplatinumgroupmetals
6.38
-0.87
(5.91)
4.15
2.56
S
S
0.4
9
0.007
682Copper
4.97
-0.56
(4.08)
0.54
0.30
S
US
0.3
6
0.072
683Nickel
3.50
0.09
(4.03)
4.73
6.15
S
S
0.4
3
0.044
684Aluminum
3.19
-0.29
(4.24)
0.41
0.29
S
S
0.5
2
0.137
685Lead
5.29
-0.92
(5.52)
3.31
15.03
S
US
0.6
9
0.170
686Zinc
2.24
-0.31
(3.17)
4.17
1.19
S
S
0.1
2
0.005
687Tin
6.19
-0.96
(5.53)
0.79
2.13
S
S
0.5
5
0.002
689Miscell.non-ferrousbasemetals
4.72
-0.34
(5.19)
0.25
2.67
S
S
0.6
8
0.001
691Finishedstructuralparts
4.04
-0.51
(4.63)
0.06
0.09
S
S
0.3
9
1.889
692Metalcontain
ersforstorageortransport
1.60
-0.09
(2.75)
0.01
0.09
S
S
0.3
5
0.241
693Wireproductsandfencinggrills
3.57
-0.59
(4.21)
4.64
0.61
S
S
0.3
1
0.122
694Nails,screws,nuts,bolts,rivets
2.93
-0.40
(3.78)
5.24
0.96
S
S
0.3
7
0.047
695Toolsforuse
inthehandorinmachines
9.22
-0.68
(7.14)
0.20
6.95
S
S
0.6
5
0.331
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F
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RESET
CUSUM
CUSUMSQ
Adj.R2
Size
696Cutlery
5.43
-0.41
(5.34)
0.01
1.61
S
S
0.5
6
0.002
697Householdeq
uipment
2.56
-0.51
(3.69)
1.10
4.40
S
S
0.4
0
0.025
698Manufactures
ofmetal,nes
5.07
-0.31
(5.17)
1.07
0.18
S
S
0.5
4
0.007
711Powergenera
tingmachinery,other
3.38
-0.35
(4.29)
3.32
0.31
S
S
0.6
8
0.044
712Agriculturalmachinery
7.06
-0.24
(6.24)
2.99
2.42
S
S
0.5
6
0.117
714Officemachines
3.51
-0.30
(4.44)
3.06
6.84
S
S
0.5
7
0.190
715Metalworking
machinery
4.13
-0.59
(4.80)
3.23
1.51
S
US
0.5
4
0.003
717Textileandleathermachinery
2.77
-0.37
(3.13)
0.20
0.29
S
US
0.1
2
0.007
718Machinesfor
specialindustries
4.24
-0.41
(4.67)
0.04
0.14
S
US
0.4
8
0.002
0.98
-0.06
(2.31)
1.09
0.01
S
US
0.2
9
1.454
719Machineryan
dappliances-nonelectrical
3.17
-0.15
(3.82)
0.69
4.91
S
S
0.6
2
0.332
722Electricpowe
rmachineryandswitches
1.26
-0.41
(2.49)
2.29
8.87
S
S
0.6
4
0.125
723Equipmentfo
rdistributingelectricity
4.40
-0.29
(3.79)
0.53
0.17
S
S
0.2
5
0.078
724Telecommunicationsapparatus
4.60
-0.48
(4.92)
0.01
3.29
S
S
0.4
9
0.333
725Domesticelectricalequipment
2.54
-0.12
(3.23)
1.28
0.23
S
US
0.3
0
0.001
726Electricalapp
aratusformedicalpurpose
2.12
0.01
(3.31)
0.61
0.23
S
US
0.4
4
0.179
729Otherelectric
almachinery
5.01
-0.44
(5.21)
2.85
12.25
S
S
0.6
9
1.106
731Railwayvehicles
5.30
-0.31
(5.43)
0.58
2.99
S
US
0.4
1
0.015
732Roadmotorv
ehicles
3.91
-0.82
(4.64)
1.07
4.27
S
S
0.5
9
0.005
733Roadvehiclesotherthanmotor
4.47
-0.70
(4.84)
0.15
1.89
S
S
0.3
8
0.013
734Aircraft
7.19
-1.56
(6.01)
0.21
0.18
S
S
0.5
6
0.006
735Shipsandboats
1.33
-0.12
(2.09)
0.38
1.39
S
S
0.3
4
0.056
812Sanitary,plumbing,heating
3.07
-0.13
(3.92)
0.05
0.02
S
S
0.3
5
0.001
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Diagnostics
F
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RESET
CUSUM
CUSUMSQ
Adj.R2
Size
821Furniture
2.27
-0.21
(3.52)
0.05
0.21
S
S
0.1
8
0.038
831Travelgoods,handbagsandsimilar
1.51
-0.11
(2.58)
1.47
1.24
S
S
0.5
6
0.066
841Clothingexceptfurclothing
5.10
-0.19
(5.05)
0.34
0.48
S
S
0.4
5
0.009
842Furclothingandarticlesofartificialclothing
2.27
-0.27
(3.39)
0.15
0.14
S
US
0.4
6
0.002
851Footwear
5.12
-0.66
(5.01)
7.75
10.15
S
S
0.3
4
0.066
861Scientific,me
dical,optical,instruments
4.34
-0.56
(4.64)
0.17
3.53
S
S
0.3
8
0.032
862Photographic,cinematographicsupplies
2.04
-0.25
(2.90)
0.01
0.23
S
S
0.2
7
0.033
863Developedcinematographicfilm
3.01
-0.09
(3.85)
4.61
3.17
S
S
0.3
6
0.061
864Watchesand
clocks
0.63
-0.14
(1.54)
4.34
0.96
S
S
0.3
6
0.088
891Musicalinstruments,soundrecorders
6.01
-0.34
(4.46)
1.46
10.43
S
S
0.6
9
0.301
892Printedmatte
r
1.96
0.01
(3.10)
1.74
0.01
S
US
0.3
2
0.001
893Articlesofar
tificialplasticmate
2.11
-0.16
(2.94)
5.60
6.42
S
S
0.5
2
0.001
894perambulators,toys,games
3.43
-0.21
(4.12)
4.63
0.03
S
S
0.3
1
0.054
895Officeandstationarysupplies,nes
1.16
-0.15
(2.24)
3.17
0.17
S
S
0.1
0
0.092
896Worksofart,collectorspieces
1.36
-0.28
(2.75)
0.01
8.58
S
US
0.4
7
0.023
897Jewellery
2.91
-0.35
(3.56)
11.63
2.08
S
S
0.4
3
0.752
Absolutevaluesofthetstatisticareinparentheses.CriticalvaluesfortheFtestare4.02fortheupperbound,perNarayan(2005),CaseIII,withanunrestrictedintercept,
notrend,
k=
3,a
nd40observations.Thecriticalt
statisticfortheECMtestis-2.9
5,perBanerjeeetal.(1998)
n.e.s.notelsewherespecified
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U.S. to Germany are affected by exchange rate volatility. In what per cent of these
industries short-run effects last into the long run? To answer this question we shift to
the long-run results in the same Table1. Again, at the 10 % level of significance we
observe that the variability measure of the real exchange rate (Ln VAR) carries a
significant coefficient in 67 industries. While in five of them (i.e., industries coded031, 613, 621, 673, and 733), the coefficient is negative, in the remaining 62
industries it is positive. Thus, it appears that almost all affected U.S. exporting
industries benefit from variability of the real dollareuro rate in the long run. Note
that almost all of the affected industries are small, as reflected by their export shares
reported in Table2as their size.3 The only large industries that are affected are 512
(Organic chemicals) with almost 1.7 % market share and 731 (Railway vehicles)
with 1.1 % market share. Furthermore, included among the affected industries are
durables as well as non-durables.
As for the long-run effects of the other two variables, Germanys income carriesits expected positive sign and significant coefficient in almost every case, signifying
the importance of economic activity in Germany as a main determinant of U.S.
exports. Note that there are seven industries (i.e., industries coded 031, 212. 231,
283, 613, 686, and 863) in which German income carries a significantly negative
coefficient. These industries could be industries that produce import-substitute
goods. As German economy grows, these industries produce more of import-
substitute goods leading to a decline in German imports or U.S. exports.4 The real
exchange rate itself does not seem to have a significant effect in most industries.
Real depreciation of the dollar only benefits 27 of the 131 industries since it carriesa positive coefficient only in 27 industries. Finally, the euro dummy carries a
significant coefficient in a total of 49 cases. However, the coefficient is positive only
in 14 industries. Thus, U.S. exporting industries that have benefitted from the
introduction of euro are identified to be those that are coded 073, 283, 321, 422, 541,
631, 632, 661, 671, 682, 685, 733, 735, and 863.
For the above long-run coefficient estimates to be meaningful, we now need to
establish joint significance of lagged level variables or cointegration using the
F test. As mentioned Pesaran et al. (2001), provide new critical values. However,
they are for large sample sizes. For small sample sizes like ours, the critical values
come from Narayan (2005). Given the upper bound critical value of 3.973 from
Narayan, there are 61 industries in which our calculated F is significant, supporting
cointegration. In many of the remaining industries cointegration is established by an
alternative test. Following Bahmani-Oskooee and Tanku (2008) and Bahmani-
Oskooee and Hegerty (2009a), we use long-run coefficient estimates and form an
error-correction term using Eq. (1). Denoting this error-correction term by ECM, we
then replace the linear combination of lagged level variables in (3) by ECMt-1and
re-estimate each model one more time using the same optimum number of lags as
before. A significantly negative coefficient obtained for ECMt-1 will be an
alternative way of supporting cointegration. However, the distribution of this
3 The trade share for each industry is defined as exports of each industry as a percent of total US exports
to Germany.4 For more on this see Bahmani-Oskooee (1986).
306 Empirica (2013) 40:287324
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statistic is not normal and the new critical values are tabulated by Banerjee et al.
(1998). Given the critical value of-2.95 from Banerjee et al. (1998), cointegration
is supported in most remaining industries. The size of the coefficient measures the
speed of adjustment among the variables in each model.
In Table2 we have also reported several other diagnostics. To test for serialcorrelation, the Lagrange Multiplier (LM) statistic is reported and to test for
functional misspecification, Ramsys RESET test is reported. These tests are
distributed as v2 with one degree of freedom. Given the critical value of 3.89,
majority of the optimum models pass these tests, implying autocorrelation free
residuals and correctly specified error-correction models. To establish stability of
the short-run as well as long-run coefficient estimates, the well-known CUSUM and
CUSUMSQ tests are applied to the residuals of each optimum model. Stable
coefficients are denoted by S and unstable ones by US. As can be seen, clearly
most estimated coefficients are stable. Finally, size of the adjusted R2
reveals thatmost models enjoy reasonable goodness of fit.
We now shift to the estimate of U.S. import demand error-correction model
outlined by Eq. (4). The results from each optimum model are reported in Tables 3
and their diagnostics in Table 4. From the short-run coefficient estimates in Table 3,
we identify 75 industries in which there is at least one significant coefficient,
implying that exchange rate uncertainty has short-run effects in most industries
imports. Again, while in some industries the short-run effects are negative (e.g.,
industry coded 001), in some others they are positive (e.g., industry coded 048).
However, only in 51 industries the short-run effects are translated into the long run.Furthermore, unlike U.S. exporting industries in which most of them were affected
positively by exchange rate volatility, most importing industries are adversely
affected. More precisely, while 32 of the 51 industries are adversely affected, the
remaining 19 are positively affected. The 32 industries are those that are coded: 048,
054, 055, 081, 112, 211, 283, 321, 513, 514, 541, 551, 612, 641, 655, 656, 657, 662,
672, 673, 674, 677, 682, 684, 698, 711, 715, 717, 718, 729, 862, and 897. Again,
most of these adversely affected industries are small. The large importing industries
reflected by their import shares (as their size in Table4) are: 663 (Mineral
manufactures with 2.1 % market share), 664 (Glass with 1.76 % market share), 684
(Aluminum with 1.5 % market share), 685 (Lead with 1.6 % share), and 714 (Office
machines with almost 1 % share). Among these five largest importing industries
only 684 is adversely affected.
Turning to other variables we gather that the U.S. income carries its expectedly
positive and significant coefficient in 56 cases supporting the notion that as U.S.
economy grows, so does imports of these industries from Germany. However, there
are also 13 industries in which U.S. income carries a significantly negative
coefficient. These industries could be those that as U.S. economy grows, it produces
close substitutes of these commodities. The real exchange rate itself carries its
expectedly negative coefficient in 60 cases, implying that as dollar depreciates
against the euro in real term, U.S. imports less of these commodities which signify
importance of the real exchange rate as determinants of U.S. imports from
Germany. Finally, the euro dummy carries a significant coefficient in 54 cases and
Empirica (2013) 40:287324 307
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Table3
Short-ru
nandlong-runcoefficientestimatesofU.S.importmodel(absolutevalueoftratiosinparentheses)
Industry
Short-runcoefficient
estimates
Long-runcoefficientestimates
DLnVARt
DLn
VARt-1
DLnVARt-2
DLnVAR
t-3
Constant
LnYU.S.
LnRE
LnVAR
Dummy
001Liveanimals
-0.01(0.07)
-0.8
4(3.34)
-0.62(2.95)
-0.25(1.98)
2.14(0.90)
1.92(3.21)
-3.09(5.19)
0.72(3.35)
-1.72(6.31)
013Meatinairtightcontainers
nes
0.18(1.33)
-6.89(1.33)
3.19(2.57)
4.67(4.31)
0.24(1.39)
-0.75(1.89)
031Fish,freshandsimply
preserved
-0.73(2.45)
1.4
0(2.45)
1.73(3.46)
1.08(3.31)
25.98(5.09)
-5.84(4.55)
-3.54(3.35)
-1.79(3.92)
0.54(1.15)
032Fishinairtightcontainers,
nes
-0.68(0.01)
-0.3
6(2.93)
-0.34(4.20)
4.31(0.47)
1.99(1.06)
-0.35(0.24)
1.68(0.87)
0.96(0.82)
048Cerealprepara
tionsand
preparationsoffl
our
0.04(0.94)
-0.0
3(0.40)
-0.08(1.75)
-12.53(1.74)
6.15(3.23)
2.09(0.95)
0.59(0.99)
-1.25(1.16)
052Driedfruit
0.34(2.15)
-0.1
2(0.42)
-0.20(0.83)
-0.28(1.84)
-67.63(1.13)
20.68(1.31)
19.07(1.03)
4.15(1.39)
-4.62(0.77)
053Fruit,preserve
dandfruit
preparations
0.20(1.91)
940.93(0.09)
-190.4(0.09)
-135.2(0.09)
30.88(0.10)
26.29(0.09)
054Vegetables,ro
otsand
tubers
0.18(1.70)
0.3
5(2.16)
0.20(1.92)
14.57(6.11)
-0.96(1.57)
2.28(4.87)
0.10(0.39)
0.02(0.09)
055Vegetables,ro
otsand
tuberspreserved
0.02(0.26)
-0.1
8(1.67)
-0.17(2.52)
22.16(0.56)
-0.92(0.13)
-3.50(0.63)
2.62(0.80)
2.04(0.71)
061Sugarandhon
ey
0.72(2.61)
15.36(3.43)
-1.14(1.07)
-3.34(3.68)
1.14(3.44)
0.54(1.36)
062Sugarconfectionery
0.43(3.43)
-0.9
2(3.14)
-0.63(2.78)
-0.29(2.19)
-15.94(4.11)
8.22(8.72)
0.42(0.56)
2.91(8.02)
-1.29(3.88)
073Chocolateand
otherfood
preparations
-0.05(0.85)
-0.0
7(0.63)
-0.13(2.05)
1.79(0.54)
1.86(2.26)
-1.04(1.53)
-0.01(0.04)
0.64(2.53)
075Spices
-0.39(2.19)
-16.83(2.11)
6.32(3.23)
0.40(0.26)
1.02(1.91)
-0.04(0.06)
081Feed.-stufffor
animals
excludingunmilledcreals
0.09(0.96)
-7.49(1.01)
4.43(2.51)
0.89(0.50)
0.35(1.05)
-1.53(2.22)
099Foodpreparations,nes
0.04(0.24)
-0.3
5(1.28)
-0.56(2.30)
-0.26(1.69)
18.19(1.32)
-0.81(0.23)
-4.47(1.76)
1.25(0.85)
0.66(0.53)
112Alcoholicbeverages
0.05(0.95)
10.59(2.38)
0.69(0.66)
-0.95(1.09)
0.26(1.03)
0.23(0.52)
211Hidesandskins,-excluding
furskins
-0.22(1.71)
-17.63(4.37)
5.75(6.06)
1.43(1.75)
-0.29(1.58)
-0.68(1.91)
308 Empirica (2013) 40:287324
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Table3
continue
d
Industry
Short-runcoefficient
estimates
Long-runcoefficientestimates
DLnVARt
DLn
VARt-1
DLnVARt-2
DLnVAR
t-3
Constant
LnYU.S.
LnRE
LnVAR
Dummy
212Furskins,und
ressed
0.53(1.83)
17.35(3.45)
-2.29(1.89)
-0.79(0.82)
0.53(1.83)
0.22(0.45)
231Cruderubber-including
synthetic
49.24(1.16)
49.24(1.16)
-7.17(0.77)
-8.39(1.31)
2.39(1.93)
4.48(1.38)
243Wood,shaped
orsimply
worked
0.12(0.89)
-37.28(1.92)
10.81(2.29)
5.43(1.45)
0.45(0.83)
1.49(1.02)
251Pulpandwastepaper
0.13(0.53)
-0.6
2(1.27)
-0.94(2.23)
-0.51(1.85)
-46.78(4.38)
14.40(5.00)
4.27(2.00)
2.41(1.76)
-2.61(2.42)
262Woolandothe
ranimalhair
-0.54(2.99)
-0.5
3(1.94)
-0.43(2.49)
6.82(1.23)
-0.71(-0.52)
-2.34(2.08)
-0.96(1.86)
-0.21(0.45)
266Syntheticand
regenerated
fibers
0.01(0.04)
-0.3
9(2.02)
-0.45(2.63)
-0.20(1.78)
-0.77(0.24)
2.88(3.41)
0.72(1.11)
0.45(1.06)
0.29(0.94)
267Wastemateria
lsfrom
textilefabric
-0.04(0.36)
-0.9
1(4.10)
-0.73(3.52)
-0.31(2.42)
-7.80(2.30)
4.47(4.89)
1.70(2.47)
1.35(2.89)
-0.99(3.04)
273Stone,sandan
dgravel
0.14(0.72)
-0.39(0.03)
1.55(0.46)
-4.79(1.52)
0.41(0.70)
1.14(0.96)
276Othercrudem
inerals
0.04(0.55)
0.1
7(2.23)
1.22(0.33)
1.46(1.77)
-0.01(0.01)
-0.35(0.99)
1.22(0.33)
283Oresandconc
entratesof
non-ferrous
-0.03(0.07)
120.18(4.24)
-26.58(3.87)
-15.63(3.23)
-0.09(0.07)
8.12(2.83)
284Non-ferrousm
etalscrap
0.18(0.89)
7.10(0.67)
1.22(0.47)
-2.88(1.28)
1.11(1.79)
-0.59(0.75)
291Crudeanimal
materials,
nes
-0.03(0.31)
-0.2
8(2.22)
-0.20(2.55)
7.13(1.21)
1.09(0.72)
0.90(0.56)
0.52(0.91)
-1.14(2.06)
292Crudevegetab
lematerials,
nes
0.02(0.22)
-8.94(3.13)
4.39(6.32)
0.82(1.41)
0.03(0.22)
0.40(1.65)
321Coal,cokeandbriquetters
1.03(1.59)
-18.16(0.31)
7.08(0.48)
10.61(0.83)
2.59(1.22)
-0.35(0.10)
332PetroleumPro
ducts
0.18(0.94)
-11.59(1.87)
4.89(3.24)
-1.52(1.26)
-0.47(0.73)
0.94(1.52)
411Animaloilandfats
0.01(0.04)
-0.3
1(2.09)
0.42(0.15)
1.89(2.62)
-1.73(2.86)
0.58(3.04)
-0.32(1.37)
422Otherfixedve
getableoils
0.07(0.36)
7.84(1.21)
-0.30(0.19)
0.28(0.23)
0.13(0.35)
1.95(3.13)
431Animalandvegetableoils
-0.18(0.53)
-1.4
4(2.45)
-1.37(2.68)
0.99(3.09)
-22.50(5.03)
7.56(6.41)
2.45(2.70)
0.76(1.31)
0.19(0.44)
512Organicchemicals
0.16(2.93)
-0.1
1(1.83)
-1.04(0.74)
3.79(10.55)
0.02(0.07)
0.48(5.12)
0.10(1.01)
Empirica (2013) 40:287324 309
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Table3
continue
d
Industry
Short-runcoefficient
estimates
Long-runcoefficientestimates
DLnVARt
DLn
VARt-1
DLnVARt-2
DLnVAR
t-3
Constant
LnYU.S.
LnRE
LnVAR
Dummy
513Inorganicchem
ical
elements,oxides
andhalogen
salts
0.15(1.95)
3.25(1.92)
2.29(5.54)
-0.53(1.67)
0.36(2.65)
-0.24(1.57)
514Otherinorganicchemicals
0.21(2.09)
-0.1
9(1.23)
0.15(1.57)
-5.93(1.36)
4.74(4.24)
1.24(1.32)
1.24(1.32)
0.35(1.06)
515Radioactivean
dassociated
material
-0.33(1.62)
-0.6
6(3.23)
5.17(4.46)
87.80(1.55)
-16.34(1.25)
-18.90(1.86)
2.18(1.73)
6.39(1.62)
531Syntheticorganicdyestuffs
-0.03(0.51)
-0.2
2(2.85)
-0.18(3.83)
-107.7(0.16)
22.09(0.19)
-4.07(0.12)
-6.83(0.13)
0.46(0.03)
532Dyeingandtanning
extracts,syntheti
ctanning
materials
0.21(1.65)
-2.68(0.25)
3.22(1.31)
-2.16(1.12)
0.88(1.50)
-1.05(1.2)
533Pigments,pain
ts,varnishes
-0.14(1.23)
-0.4
9(2.61)
-0.23(2.00)
-1.55(0.36)
3.82(3.59)
-0.90(1.20)
0.92(2.37)
-0.37(1.07)
541Medicinalpha
rmaceutical
products
0.08(1.02)
-9.84(3.51)
5.20(7.97)
0.17(0.34)
-0.14(0.88)
0.78(2.94)
551Essentialoils,
perfumeand
flavor
0.23(2.87)
-0.2
5(1.98)
-0.16(1.95)
-10.62(6.39)
5.05(12.35)
0.01(0.04)
0.68(4.57)
-0.41(2.78)
553Perfumery,cosmetics,
dentifrices
-0.02(0.24)
-0.4
8(3.68)
-0.18(2.31)
-6.63(1.05)
5.59(3.79)
-1.18(0.97)
1.93(4.04)
0.03(0.07)
554Soaps,cleansingand
polishing
-0.12(1.66)
-9.24(1.68)
4.23(3.48)
0.28(0.24)
-0.44(1.09)
-0.35(0.72)
571Explosivesand
pyrotechnic
0.20(1.23)
-35.54(2.94)
10.55(3.55)
7.86(3.06)
0.47(1.11)
-1.19(1.34)
581Plasticmaterials,nes
0.02(0.52)
0.0
9(1.48)
-0.12(2.90)
-2.86(1.27)
4.17(7.36)
-0.12(0.23)
0.52(2.20)
-0.52(2.11)
599ChemicalMaterialsand
products,nes
0.11(2.02)
2.57(1.38)
2.63(5.86)
-0.96(2.78)
0.40(2.49)
0.12(0.66)
611Leather
-0.21(2.64)
-0.6
1(4,58)
-0.39(4.57)
-9.45(3.20)
4.94(6.74)
2.37(4.01)
0.53(1.87)
-1.02(3.59)
612Manufacturers
ofleather
-0.14(2.97)
-0.1
4(1.78)
-0.13(2.89)
-3.91(0.77)
2.51(1.99)
-0.58(0.49)
-0.69(2.07)
0.50(1.34)
613Furskins,tannedor
dressed
0.04(0.26)
20.33(5.61)
-2.96(3.40)
-1.26(1.79)
0.05(0.26)
0.35(0.95)
310 Empirica (2013) 40:287324
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Table3
continue
d
Industry
Short-runcoefficient
estimates
Long-runcoefficientestimates
DLnVARt
DLn
VARt-1
DLnVARt-2
DLnVAR
t-3
Constant
LnYU.S.
LnRE
LnVAR
Dummy
664Glass
-0.07(1.62)
-0.2
6(2.79)
-0.11(1.38)
0.06(1.12)
0.56(0.28)
3.00(6.06)
-0.19(0.48)
0.51(2.99)
0.06(0.35)
665Glassware
0.15(2.41)
-0.16(0.09)
3.16(7.99)
-0.08(0.27)
0.56(4.27)
-0.68(4.31)
667Pearlsandpre
ciousand
semi-preciousstones
0.01(0.34)
-0.1
4(2.15)
-0.10(2.45)
2.91(1.32)
2.34(4.20)
-0.26(0.61)
0.67(2.73)
-0.06(0.31)
671Pigironandspiegeleisen,
spongeiron
0.63(4.64)
-0.5
4(3.19)
16.48(7.89)
-0.33(0.62)
-1.69(4.04)
1.86(7.75)
0.78(3.37)
672Ingotsandothe
rprimary
formsofiron
0.11(0.75)
-0.9
0(3.29)
-1.56(0.37)
4.14(3.51)
1.28(1.37)
1.39(2.21)
-1.29(3.19)
673Ironandsteel
bars
0.04(0.42)
0.7
5(3.47)
0.20(1.61)
5.45(3.31)
0.97(2.39)
0.34(1.00)
-0.69(5.35)
0.12(0.86)
674Universals,platesand
sheetsofiron
0.07(0.71)
-0.4
2(2.15)
-0.57(3.12)
-0.31(2.82)
8.15(1.56)
1.74(1.21)
1.17(0.63)
0.96(1.17)
-0.05(0.09)
677Ironandsteel
wire
0.21(2.58)
-0.0
2(0.11)
-0.28(2.02)
-0.18(2.05)
6.79(2.52)
1.12(1.55)
-0.03(0.05)
0.61(1.77)
0.01(0.05)
678Tubes,pipesandfittingsof
iron
0.13(0.77)
23.89(1.98)
-2.56(0.90)
-3.74(1.79)
0.34(0.83)
1.69(1.58)
679Ironsteelcastingsforgings
-0.19(1.82)
-0.0
3(0.22)
0.18(1.91)
10.65(1.68)
-0.37(0.22)
-1.12(0.97)
-0.37(0.21)
0.31(0.47)
681Silverandplatinumgroup
metals
0.03(0.12)
-12.76(3.07)
5.84(5.75)
-0.21(0.27)
0.58(1.56)
0.26(0.65)
682Copper
0.07(0.96)
-0.5
0(3.19)
-0.55(3.66)
-0.19(1.90)
3.40(1.88)
0.64(2.89)
0.52(1.41)
0.64(2.89)
0.57(3.38)
683Nickel
-0.43(2.75)
0.5
4(2.04)
0.60(2.67)
0.30(2.31)
-35.01(0.69)
18.92(0.89)
2.39(0.33)
11.57(0.83)
-3.54(0.67)
684Aluminum
0.05(0.58)
-0.5
0(2.86)
-0.59(3.85)
-0.25(2.34)
11.06(0.88)
1.19(0.41)
-2.87(1.14)
1.09(1.71)
0.85(1.21)
685Lead
0.32(0.88)
-0.6
9(1.06)
-1.49(2.57)
-1.47(3.89)
27.06(2.62)
-3.30(1.29)
-3.17(1.52)
1.58(2.14)
1.78(2.43
686Zinc
-0.09(0.23)
47.10(2.42)
-9.63(2.04)
-3.46(0.89)
-0.27(0.23)
2.75(1.36)
687Tin
1.60(3.74)
-2.9
3(3.41)
-2.25(3.13)
-1.33(3.06)
-16.44(1.99)
9.18(4.47)
3.14(1.88)
4.95(6.26)
-0.68(0.95)
689Miscell.non-fe
rrousbase
metals
-0.01(0.09)
0.2
0(1.58)
0.22(2.00)
0.21(2.93)
-9.58(1.19)
4.09(2.26)
0.33(0.21)
-0.66(1.38)
0.14(0.28)
691Finishedstructuralparts
0.13(1.74)
0.1
8(1.63)
0.15(2.14)
-13.16(3.68)
5.75(6.58)
1.44(1.89)
0.32(1.39)
-0.12(0.47)
312 Empirica (2013) 40:287324
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Table3
continue
d
Industry
Short-runcoefficient
estimates
Long-runcoefficientestimates
DLnVARt
DLn
VARt-1
DLnVARt-2
DLnVAR
t-3
Constant
LnYU.S.
LnRE
LnVAR
Dummy
692Metalcontainersfor
storageortransport
0.11(0.75)
-0.3
9(2.38)
34.65(0.39)
0.60(0.05)
-5.31(0.49)
7.13(0.67)
-0.31(0.11)
693Wireproducts
andfencing
grills
-0.01(0.05)
-0.3
5(2.84)
-0.31(2.94)
-0.14(1.98)
5.19(3.71)
1.58(4.24)
-0.51(1.78)
0.49(2.58)
-0.13(0.99)
694Nails,screws,
nuts,bolts,
rivets
0.03(0.50)
-0.1
2(1.01)
-0.25(2.30)
-0.12(1.78)
-3.66(1.36)
3.76(5.43)
-0.11(0.19)
0.49(1.71)
0.07(0.28)
695Toolsforuseinthehandor
inmachines
0.03(0.75)
-0.4
6(5.36)
-0.42(5.35)
-0.23(4.59)
-2.80(2.58)
4.01(13.73)
-0.03(0.11)
0.71(4.68)
-0.24(2.29)
696Cutlery
0.02(0.79)
-0.1
9(3.34)
-0.14(2.94)
-0.05(1.79)
-0.52(0.44)
3.06(9.62)
0.27(1.07)
0.49(3.42)
-0.32(2.52)
697Householdequipment
0.09(1.27)
-0.2
4(2.03)
-0.13(1.22)
-0.11(1.69)
-4.48(2.01)
3.66(6.66)
0.81(1.81)
0.52(2.39)
0.05(0.27)
698Manufacturesofmetal,nes
0.01(0.24)
-0.2
1(2.94)
-0.24(3.85)
-0.11(2.79)
-9.33(3.98)
5.61(8.86)
1.21(2.34)
0.80(3.24)
-0.34(1.77)
711Powergenerat
ing
machinery,other
0.15(2.49)
-0.2
1(2.04)
-0.25(2.98)
-0.11(1.86)
-7.26(2.84)
5.62(8.25)
0.33(0.48)
0.75(2.39)
-0.78(1.91)
712Agriculturalm
achinery
0.04(0.48)
-0.2
0(1.56)
-0.25(2.15)
-0.20(2.80)
18.95(2.19)
-0.62(0.29)
2.14(2.10)
1.17(1.73)
1.09(1.41)
714Officemachines
-0.08(2.02)
-0.1
4(1.56)
-0.13(2.01)
-0.06(1.55)
-1.98(0.71)
4.46(6.55)
0.63(0.95)
1.17(3.11)
-0.79(3.00)
715Metalworking
machinery
-0.06(0.75)
-0.4
3(3.16)
-0.36(3.10)
-0.16(2.07)
1.44(0.55)
3.16(4.97)
-0.27(0.58)
0.61(2.48)
-0.54(2.57)
717Textileandleather
machinery
0.06(0.71)
-0.1
1(1.39)
2.08(0.81)
3.09(4.90)
0.24(0.49)
0.69(2.49)
-1.17(4.88)
718Machinesforspecial
industries
0.02(0.53)
-0.3
8(3.68)
-0.14(2.64)
-0.15(2,64)
-3.77(1.81)
4.76(8,59)
0.42(0.90)
0.79(3.18)
-0.86(3.68)
-0.01(0.07)
-2.53(0.24)
4.27(1.72)
1.18(0.40)
-0.04(0.07)
-1.11(0.76)
719Machineryandappliances-
nonelectrical
-0.01(0.21)
-0.1
4(2.52)
-0.11(3.02)
-1.11(0.19)
3.98(2.83)
-0.82(0.92)
0.55(1.06)
-0.50(1.07)
722Electricpowermachinery
andswitches
-0.01(0.01)
-0.4
7(2.71)
-0.35(3.35)
-10.62(2.30)
5.44(5.33)
0.07(0.08)
0.65(1.18)
0.22(0.60)
723Equipmentfor
distributing
electricity
-0.14(2.99)
-0.2
4(3.08)
-0.14(2.64)
-7.11(2.38)
4.79(6.05)
0.62(1.08)
0.38(1.14)
0.18(0.56)
Empirica (2013) 40:287324 313
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8/13/2019 US Germany
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Table3
continue
d
Industry
Short-runcoefficient
estimates
Long-runcoefficientestimates
DLnVARt
DLn
VARt-1
DLnVARt-2
DLnVAR
t-3
Constant
LnYU.S.
LnRE
LnVAR
Dummy
863Developed
cinematographic
film
-0.01(0.19)
-0.0
3(0.33)
-0.08(1.56)
-4.47(0.21)
3.46(0.79)
4.07(0.59)
-0.46(0.32)
-1.00(0.69)
864Watchesandc
locks
0.01(0.06)
-0.1
8(2.67)
-0.12(2.53)
-5.99(1.75)
4.78(5.52)
1.24(1.72)
0.78(2.65)
-0.49(1.96)
891Musicalinstruments,sound
recorders
0.07(2.30)
-0.1
8(3.13)
-0.12(2.66)
-0.08(2.52)
-2.22(1.31)
3.73(8.11)
0.46(1.09)
0.64(3.77)
-0.33(2.22)
892Printedmatter
-0.04(0.86)
106.45(0.06)
-26.86(0.04)
-97.18(0.06)
10.77(0.06)
23.63(0.05)
893Articlesofartificialplastic
mate
-0.04(1.02)
-0.2
9(4.56)
-0.28(4.72)
-0.12(3.02)
2.98(0.32)
2.88(1.67)
0.14(0.09)
0.98(1.26)
-0.64(1.60)
894Perambulators,toys,games
0.01(0.20)
-0.3
4(3.45)
-0.20(3.30)
-9.13(1.45)
6.11(2.87)
2.13(1.35)
1.92(1.53)
-1.42(1.77)
895Officeandstationary
supplies,nes
0.02(0.16)
18.64(0.47)
-0.89(0.11)
-3.25(0.59)
0.18(0.16)
-0.73(0.38)
896Worksofart,collectors
pieces
0.05(0.74)
5.36(1.23)
1.61(1.67)
-0.18(0.25)
0.18(0.78)
0.15(0.40)
897Jewellery
0.05(0.78)
0.0
1(0.12)
-0.12(1.84)
-9.92(1.43)
5.26(2.95)
1.49(1.06)
0.37(0.73)
0.35(0.77)
n.e.s.notelsewherespecified
Empirica (2013) 40:287324 315
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Table4
Diagnos
ticStatistics
Industry
Diagnostics
F
ECMt-
1
LM
RESET
CUSUM
CUSUMSQ
Adj.R2
Size
001Liveanimals
6.39
-0.79
(5.18)
1.34
0.04
S
S
0.47
0.018
013Meatinairtightcontainersnes
6.70
-0.67
(6.04)
1.85
1.79
S
S
0.46
0.005
031Fish,freshan
dsimplypreserved
4.20
-0.42
(4.43)
0.03
0.32
S
S
0.30
0.005
032Fishinairtightcontainers,nes
8.22
-1.60
(5.56)
0.09
7.98
S
S
0.49
0.022
048Cerealpreparationsandpreparationsofflour
1.46
-0.49
(2.54)
0.44
0.18
S
US
0.49
0.013
052Driedfruit
4.25
-0.48
(4.64)
0.79
4.84
S
S
0.45
0.064
053Fruit,preserv
edandfruitpreparations
4.62
-0.52
(3.98)
0.03
4.41
S
S
0.37
0.006
054Vegetables,r
ootsandtubers
4.56
-0.66
(4.90)
1.28
0.48
S
S
0.38
0.008
055Vegetables,r
ootsandtuberspreserved
7.42
-0.72
(6.10)
1.20
7.11
S
S
0.56
0.046
061Sugarandho
ney
7.78
-0.94
(6.33)
1.55
0.14
S
S
0.74
0.006
062Sugarconfectionery
2.69
-0.46
(3.60)
0.84
6.86
S
S
0.46
0.003
073Chocolateandotherfoodpreparations
1.03
-0.22
(2.33)
1.87
0.32
S
S
0.33
0.052
075Spices
2.94
-0.34
(2.42)
0.03
3.19
US
US
0.15
0.174
081Feed.-stufffo
ranimalsexcludingunmilledcreals
6.49
-0.24
(5.81)
0.07
0.06
S
S
0.47
0.079
099Foodprepara
tions,nes
6.74
-0.25
(6.10)
1.11
2.07
S
S
0.65
0.070
112Alcoholicbeverages
7.08
-0.18
(6.11)
0.39
1.31
S
S
0.56
0.010
211Hidesandskins,-excludingfurskins
3.38
-0.06
(3.94)
5.55
0.37
S
S
0.45
0.051
212Furskins,undressed
2.29
-0.03
(3.47)
2.74
1.96
S
S
0.22
0.004
231Cruderubber
-includingsynthetic
2.18
-0.45
(3.92)
0.02
9.98
S
S
0.38
0.016
243Wood,shapedorsimplyworked
6.60
-0.27
(5.98)
0.13
2.38
S
S
0.66
0.042
251Pulpandwastepaper
1.94
-0.14
(2.67)
0.16
0.68
S
S
0.12
0.004
262Woolandotheranimalhair
0.60
-0.26
(1.47)
1.28
8.98
S
US
0.06
0.043
266Syntheticand
regeneratedfibers
1.85
-0.32
(3.08)
0.11
1.41
S
US
0.25
0.003
316 Empirica (2013) 40:287324
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Table4
continue
d
Industry
Diagnostics
F
ECMt-
1
LM
RESET
CUSUM
CUSUMSQ
Adj.R2
Size
267Wastematerialsfromtextilefabric
0.85
-0.14
(2.04)
0.01
0.14
S
S
0.11
0.006
273Stone,sanda
ndgravel
3.48
-0.44
(4.18)
0.04
0.82
S
S
0.39
0.003
276Othercrudeminerals
4.25
-0.33
(4.67)
0.05
2.89
S
US
0.28
0.049
283Oresandcon
centratesofnon-ferrous
11.21
-1.08
(6.07)
3.35
9.00
S
US
0.49
0.989
284Non-ferrousmetalscrap
2.69
-0.58
(3.89)
0.29
0.04
S
S
0.37
0.048
291Crudeanimalmaterials,nes
7.31
-0.43
(6.31)
5.43
0.25
S
S
0.49
0.047
292Crudevegeta
blematerials,nes
10.51
-0.60
(7.46)
0.29
5.53
S
S
0.57
0.484
321Coal,cokeandbriquett
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