US Germany

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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.

Empirica (2013) 40:287324 289

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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)

Empirica (2013) 40:287324 291

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Table1

continued

Industry



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)

292 Empirica (2013) 40:287324

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Table1

continued

Industry



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)

Empirica (2013) 40:287324 293

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Table1

continued

Industry



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

1 3


9/38

Table1

continued

Industry



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

1 3


10/38

Table1

continued

Industry



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

1 3


11/38

Table1

continued

Industry



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

1 3


12/38

Table1

continued

Industry



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

1 3


13/38

Table1

continued

Industry



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

Empirica (2013) 40:287324 299

1 3


14/38

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


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


1.86

-0.22

(2.83)

1.48

10.39

S

S

0.2

4

0.039


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


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

300 Empirica (2013) 40:287324

1 3


15/38

Table2

continued

Industry

Diagnostics

F

ECMt-

1

LM

RESET

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

Empirica (2013) 40:287324 301

1 3


16/38

Table2

continued

Industry

Diagnostics

F

ECMt-

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

302 Empirica (2013) 40:287324

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Table2

continued

Industry

Diagnostics

F

ECMt-

1

LM

RESET

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

Empirica (2013) 40:287324 303

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18/38

Table2

continued

Industry

Diagnostics

F

ECMt-

1

LM

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

304 Empirica (2013) 40:287324

1 3


19/38

Table2

continued

Industry

Diagnostics

F

ECMt-

1

LM

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)


Empirica (2013) 40:287324 305

1 3


20/38

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

1 3


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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

1 3


22/38

Table3

Short-ru

nandlong-runcoefficientestimatesofU.S.importmodel(absolutevalueoftratiosinparentheses)

Industry

Short-runcoefficient

estimates


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)


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)


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)


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

1 3


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Table3

continue

d

Industry


estimates


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)


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

1 3


24/38

Table3

continue

d

Industry


estimates


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

1 3


25/38


26/38

Table3

continue

d

Industry


estimates


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

1 3


27/38

Table3

continue

d

Industry


estimates


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)

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Table3

continue

d

Industry


estimates


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)


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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


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


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


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


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

US Germany

Documents

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