Reaping the gains from globalization with high-end
products
Julien Martin
Universit´
e catholique de Louvain
IRES
Florian Mayneris
Universit´
e catholique de Louvain
IRES, CORE
University of Lausanne
Advanced seminar HEC-Lausanne
November 14th, 2012
Julien Martin and Florian Mayneris
Universit´
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Introduction
High-end products to escape competition from emerging countries
Trade deficits and desindustrialization in many developed countries (US,
France, UK...)
Emergence of new key players in the developing world that supply an
increasing number of manufacturing goods (Schott, 2008; Fontagn´e et al.,
2007)
Specialization in high-end products often seen as a way for developed
countries to escape competition from developing ones. Actually, developed
countries
produce higher quality goods (Schott, 2004; Fontagn´
e et al., 2007)
increase the quality of their exports through within-plant upgrading and/or
reallocations (Amiti and Khandelwal, 2011; Bloom et al., 2012; Martin and M´
ejean,
2012)
experience skill upgrading (Mion and Zhu, 2011)
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Introduction
High-end products to conquer emerging markets?
In the 2000’s, emerging countries become a new important source of growth
in the world (IMF, 2010)
Not only GDP growth, but also GDP per capita growth
New fast growing economies characterized by
surge in average and top incomes
high distance from Western developed countries
High-end products = “Superior” and more expensive goods
⇒ Income, income inequality and distance are likely to impact differently exports of
high- and low-end products
⇒ Geography of demand will consequently affect differently high and low-end products
exports
Two main questions addressed in this paper
1 Which sensitivity to “standard” determinants of firm-level exports for high-end
and low-end products?
2 Given these micro-determinants, how geography of growth/demand and
specialization along the quality ladder interact to determine aggregate export
performance?
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Introduction
What we do
Study of French firms exports from 2000 to 2007:
identification of high-end products exporters based on information about big names
in the French luxury industry
cohort analysis: focus on exports dynamics of firms active on export markets in 2000
Aggregate comparison of low- and high-end products exporters along three
dimensions:
share in aggregate exports
geographic distribution of exports
margin decomposition of exports growth
Estimation of firm-level gravity equations to investigate micro-determinants
of observed aggregate patterns
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Introduction
What we find
Increasing share of high-end products in aggregate French exports (from
28.6% in 2000 to 35.5% in 2007)...
...particularly pronounced in remote and fast growing emerging countries...
...linked to a more favorable evolution of both the intensive and the
extensive margins...
....explained by a higher (resp. lower) sensitivity of the level of exports of
high-end products to income per capita and inequality (resp. distance)
⇒ Specialization in top-quality varieties boosts aggregate export
performance when (unequal) income growth is high in distant
countries
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Introduction
Contribution to the literature (I)
Identifying high-end/high-quality products in the data
Unit value = quality (Schott, 2004; Fontagn´
e et al., 2008)
Parametric estimation of quality (Hallak and Schott, 2010; Khandelwal, 2010)
Exogenous measure of quality (Verhoogen, 2008; Crozet et al., 2011)
⇒ We combine an exogenous measure of quality and firm-level unit value information
Different sensitivity of high-end product exports to income and distance
Demand for high-quality goods more sensitive to income per capita (Hallak, 2006)
evidence of non-homotheticity (Fieler, 2011a-2011b, Dalgin et al., 2008 )
Expensive products less sensitive to distance (Alchian & Allen 1964; Hummels &
Skiba, 2004)
⇒ We provide direct evidence on the relative impact of distance and income
distribution on high-end products exports on both firm-level extensive and the
intensive margins
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Introduction
Contribution to the literature (II)
Micro determinants shaping the dynamics of aggregate exports
Bernard et al., 2012 (survey): importance of firm heterogeneity, focus on
productivity
⇒ we explore the question through the lens of quality differentiation
Martin & Mejean, 2012: determinants of the increase in the quality content of
French aggregate exports - focus on competition from low-wage countries and
between-firms reallocations
⇒ We study the dynamics of aggregate exports and the interplay between quality and
demand in emerging countries
Quality in the business cycle
Berthou & Emlinger, 2010: 2007 crisis → shift of exports in favor of low-quality
varieties
Levchenko et al., 2011: No support for the collapse in quality during the crisis
⇒ Role of the geography of shocks to understand the quality content of aggregate
exports (during the crisis)
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Introduction
Outline of the talk
Data
Aggregate descriptive statistics
Econometric analysis: firm-product level gravity equations
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Data
Database
Merge of two main data sources:
French customs: Export data at the firm, product (nc8) and destination country
level, from 2000 to 2009
Comit´
e Colbert members: export promotion and lobbying association of French
luxury firms. Currently, 75 members, including Baccarat, Cartier, Champagne
Bollinger, Chanel, Christian Dior, Herm`
es, Louis Vuitton or Yves Saint-Laurent
Luxury industries = HS4 product lines that represent a significant share of
exports of at least one Colbert firm:
On average, 39 HS4 per Colbert firm
Very skewed distribution of exports across HS4 at the firm level: top product
represents at least a bit less than 20% and on average 63% of firm-level total
exports
Luxury industries = HS4 product lines representing at least 5% of overall exports of
at least one Colbert firm
⇒ 65 luxury industries in total, representing 60% of export flows and 94% of
total exports of Colbert firms, and around 10% of total French exports
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Data
Identification of high-end products exporters
Colbert firms: 0.07% only of French firms active in luxury industries
⇒ too narrow definition
Alternative: high-end products exporters = firms exporting the same HS6
products as Colbert firms at the same price :
High-end products export flows: at the firm-HS6 level, high-end product export flow
if flow with uv>1st quartile of the uv observed for this same hs6 product among
Colbert firms
High-end products exporters: firms for which at least 85% of overall exports
correspond to high-end products exports
⇒ In 2000, 2,976 high-end products exporters identified among almost 45,000
exporters in considered sectors
→ add Hennessy, Moet et Chandon, Lalique, Kenzo Perfumes, Thierry Mugler...
Cohort analysis: Focus on the dynamics of exporters active in luxury
industries in 2000
⇒ Firms of the cohort =70.92% of export flows and 79.19% of overall exports in 2009
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Data
Price premium of high-end products exporters
exp.
UV premium ( high-end
low-end exp. )
Industry
Miscellaneous
Apparel and footwear
Clocks & watches
Jewels
Food
Beverages
Leather articles
Home art
Cosmetics
Textile
Paper - books
Wood articles
6.5
4.7
4.0
3.8
3.6
3.6
3.6
2.9
2.8
2.2
1.8
1.6
Table: High-end exporters price premium
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Descriptive statistics
Growth rate and share of luxury industries in French
exports
10.6
Share sectors with luxury firms
10
0
ï10
ï20
10.4
10.2
10
9.8
2001
2002
2003
2004
2005
Sectors with luxury firms
2006
2007
2008
Growth rate of exports
Julien Martin and Florian Mayneris
2009
Sectors w/o luxury firms
2000
2003
2006
2009
Share in French exports (in %)
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Descriptive statistics
Share of high-end products exporters in luxury industries
25
36
34
Share luxury
20
15
32
30
10
2000
2003
Luxury
2006
2009
Non luxury
Value of exports (billions euro)
Julien Martin and Florian Mayneris
28
2000
2003
2006
2009
Share of high-end products (in %)
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Descriptive statistics
Gowth of high-end products exports
10
5
0
ï5
ï10
ï15
2001
2002
2003
2004
Luxury
Julien Martin and Florian Mayneris
2005
2006
2007
2008
2009
Non luxury
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Descriptive statistics
2000-07: exports per firm increased steeply for high-end
products
Tot. exports (billions)
growth 00-07
X/firm’00
growth 00-07
# dest.’00
difference 00-07
# HS4’00
difference 00-07
All firms
Non-Lux. Luxury
20.5
10.8
-6%
+16%
-
Stayers
Non-Lux. Luxury
16.4
9.7
+17%
+ 30%
106,819 268,448
+12%
+23%
3.7
5.7
+0.8
+0.7
2.9
2.2
-0.3
-0.2
Table: Decomposition of export growth
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Descriptive statistics
High-end products turning towards emerging markets
Destinations
Africa
America
Asia
China
Europe
Japan
MiddleEast
NorthAmerica
Pacific
Russia
Non-luxury
Share 2000 Change 00-07
0.25
+0.1 %
0.07
-1.6 %
0.16
-0.2 %
0.06
+3.5 %
0.74
-5.8 %
0.17
-1.4 %
0.20
-1.7 %
0.34
-1.2 %
0.19
+0.7 %
0.08
+2.5 %
Luxury
Share 2000 Change 00-07
0.22
+1.5 %
0.13
-2.0 %
0.29
+4.1 %
0.10
+6.2 %
0.76
-8.6 %
0.31
-1.8 %
0.24
+2.7 %
0.57
-1.4 %
0.25
+1.9 %
0.12
+3.4 %
Table: Share of stayers exporting to different regions of the world
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Descriptive statistics
Growth rate by regions
Africa
Africa
Asia (w/o China)
Asia (w/o China)
Europe
Europe
Japan
Japan
Latin America
Latin America
Middle East
Middle East
North America
North America
Pacific
Pacific
China (x10)
China (x10)
Russia (x10)
Russia
ï.4
ï.2
High end products
0
.2
.4
Growth rate of exports 2000-2006
Julien Martin and Florian Mayneris
ï.4
Low end products
ï.2
0
High end products
.2
.4
Low end products
Growth rate of exports 2006-2009
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Descriptive statistics
Geographic distribution of high-end products exports (1)
80
50
40
60
30
40
20
20
10
0
0
2000
2003
2006
2009
2000
2003
year
Asia (w/o China)
Europe
Middle East
Russia
Low-end products
Julien Martin and Florian Mayneris
2006
2009
year
China
Japan
North America
Asia (w/o China)
Europe
Middle East
Russia
China
Japan
North America
High-end products
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Descriptive statistics
World income and income growth
Destinations
Africa
America
Asia
China
Europe
Japan
MiddleEast
NorthAmerica
Pacific
Russia
Inc. per cap.
2007
1227
6038
1734
2480
29455
37650
6256
46260
26259
7590
Julien Martin and Florian Mayneris
Inc. per cap.
growth 00-07
108.7%
55.9 %
91.7%
166.7%
76.3%
7.4%
114.5%
37.5%
72.2%
343.9%
Inc. growth
00-07
146.3%
70.6%
111.6%
178.3%
79.7%
8.2%
147.6%
47%
91.9%
331.1%
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# Million. hh 2011
(in thous.)
52
236
833
1432
2236
1587
453
5319
141
111
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Econometric analysis
Why determinants of high-end products should be
different?
High-end products similar to “luxury”/“superior” goods: their consumption
should increase more than proportionately with income
Non-homothetic preferences
Aggregate demand for high-end products more sensitive to income per capita
Strictily non-homothetic preferences: not only average income matters, but
also income per capita (Dalgin et al., 2008; Bekkers et al., 2012)
Aggregate demand for high-end products more sensitive to the share of top incomes
in aggregate income, and thus to income inequality
Original proxy for share of top incomes = Share of millionaire households in total
population (BCG Wealth Report)
High-end products more expensive due to higher production costs (Baldwin
and Harrigan, 2011) and/or to lower elasticity of substitution (Fajgelbaum
et al., 2011; Latzer and Mayneris, 2012)
Aggregate demand for high-end products less sensitive to trade costs/distance, due
to an Alchian-Allen effect and/or lower substitutability with domestic varieties
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Econometric analysis
Methodology
Aim: Explaining the aggregate patterns observed for our cohort using
firm-level gravity equations
⇒ Coefficients on gravity determinants of exports possibly different for high-end
products exporters (interaction terms)
⇒ Cross-sectional estimation of our coefficients, in order to get rid of any dynamic
determinant of exports
Both extensive and intensive margin analysis
Determinants of the presence on a given market in 2007
Determinants of the value of (positive) exports for year 2007
“Market” defined as an HS4-destination couple
All regressions run with firm-HS4 fixed effects:
⇒ Coefficients based on cross-country comparisons for a given firm-HS4
For computational reasons, restriction to the 60 most important countries
for French exports, representing 97% of overall French exports
Data on distance and income distribution from CEPII, World Bank and BCG
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Econometric analysis
Country-product type fixed effects and gravity
determinants (1)
3
3
USA
RUS
CHE
BEL
HKG
SAU
SGP
BEL
DZA
UKR
1
0
GAB
GAB
MUS
MUS
MDG
MDG
ï1
22
ESP
CAN
DEU
USA
KOR
CHN
NLD
ESP ITAGBR JPN
AUSRUS
MAR KWT
DEU
GRCCHE
TUN
TUR MEX
CAN
TUN MAR DZA
DNK
BRA
PANLBN
ISRPRT
NOR
AUT
ZAF
EGY
SAU TUR
KOR
ARG
CHL HKG
SWE NLD
FIN
THA
CHN
AUS
KWT
UKR PRT NOR
MEX
NZL
CIV LBN
BRA
CIV
GRC
EGY
SGP
ISR
POL
MYS DNK
CYP
ZAFPOL
LVA
SWE
PAN
IND
THA
ROM
LTU
ARGAUT
CHL
IND
MYS
ROM FIN
SVKNZL
BGR
HUN
SVN
BGR
SVN
CYP
LTU
LVA
SVK
24
26
Income (log)
Fitted values
Fitted values
USA
28
GBR
ITA
2
country fixed effect
country fixed effect
2
GBR
JPN
ITA
CHE
BEL
DEU
ESP
CAN
HKG
USA
SGP
KOR
BEL
DZA
CHN
GBRITA
UKR
NLD
ESP
RUS KWT
JPN
MAR
DEU
GRC
CHE
TUN
MEX
TUR
DZA
CAN BRA
DNK
TUN MAR
PAN
ISR
LBN
AUT PRTNOR
ZAF
TUR EGY
SAU
KOR
ARG
NLD
CHL
HKG
SWE FIN
THA
CHN
KWT
PRTNOR UKR LBN
MEX
CIVGAB
BRA SGP
CIV
GRC
GAB
EGY
ISR
POL
MYS
DNK
CYP
POLSWE
ZAF
LVA
MUS
IND PAN
THA
ROM
LTU
AUT
MUS
ARG
CHL
IND MDG
MDGMYS
ROM
SVK
BGRFIN
HUN
SVN
BGR
SVN
CYP
LTU
LVA
SVK
SAU
1
0
ï1
30
6
HighïEnd products
LowïEnd products
Income
Julien Martin and Florian Mayneris
JPN
RUS
7
8
Distance (log)
Fitted values
Fitted values
AUS
AUS
NZL
NZL
9
10
HighïEnd products
LowïEnd products
Distance
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Econometric analysis
Country-product type fixed effects and gravity
determinants (2)
3
3
USA
1
0
CIV
CIV
MDG
MDG
IND
IND
ï1
6
7
8
9
Income per capita (log)
Fitted values
Fitted values
10
11
USA
2
country fixed effect
country fixed effect
2
GBR
JPN
ITA
RUS
DEU
BEL CHE
ESP
HKGCAN
USA
SAU
KOR SGPBEL
CHN DZA
GBR
ITA
UKR
NLD
ESP
AUS
RUS
MAR
KWT
DEU
GRC JPN
CHE
TUN
MEX
TUR
DZA
CAN DNK
BRA
MAR TUN PAN
PRT
ISR
NO
LBN
ZAF
EGY
SAU KOR
ARG TUR
NLD
CHL
HKG AUT
SWE
FIN
CHNTHA
AUS
KWT NO
PRT NZL
UKR
MEX
LBN
GAB
BRA
GRC
GAB
EGY
ISR SGP
MYS POL
DNK
CYP
POL
ZAF
LVA
MUS
SWE
PAN
THA
ROMCHL
LTU
AUT
MUS
ARG
MYS
FIN
NZL
SVK
BGR ROM
HUN
SVN
BGR
SVN
CYP
LTU
LVA
SVK
1
UKR
PAN
UKR
CIV
GAB
CIV
GAB
CYP
LVA
MUS
PAN
ROM
LTU
MUS
MDG
MDG
ROM
SVK
BGR
SVN
BGR
SVN
CYP
LTU
LVA
SVK
0
ï1
GBR
ITA
RUS
CHE
DEU
BEL
ESP
CAN
HKG
SAU SGP
KOR
BEL
DZA
NLD ITA GBR
ESP
AUS
MAR
KWT RUS
DEU
GRC MEX
CHE
TUN
TUR
CAN
TUN MAR DZA
DNK BRA
PRT
ISR
NOREGY
LBN
AUT
ZAF
SAU
KORNLDHKG
ARG
CHL FIN TUR
SWE
THA
KWT AUS
MEX
LBN NZL NOR PRT
BRA
GRC
SGP
POL EGY MYS
DNK ISR
POL
ZAFSWE
IND
THAARG AUT
CHL
IND
MYS
NZL FIN
HUN
0
HighïEnd products
LowïEnd products
Income per capita
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2
4
# of Millionaires (log)
Fitted values
Fitted values
6
JPN
USA
CHN
JPN
CHN
8
HighïEnd products
LowïEnd products
Millionaires
November 14th, 2012
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Econometric analysis
Intensive and Extensive margins of exports
(1)
Income/cap (log)
-×LUX
Population (log)
-×LUX
Distance (log)
-×LUX
∗∗∗
0.280
(4.726)
0.275∗∗∗
(6.442)
0.345∗∗∗
(8.596)
0.076∗∗
(2.508)
-0.232∗∗∗
(-3.000)
0.162∗∗∗
(2.856)
Sh. Millionaires
-×LUX
Country dummy
Firm-Prod. FE
Obs.
No
Yes
180,480
Intensive margin
(2)
(3)
∗∗∗
0.183
(2.835)
0.223∗∗∗
(4.893)
0.363∗∗∗
(9.490)
0.088∗∗∗
(3.142)
-0.226∗∗∗
(-3.012)
0.135∗∗∗
(3.046)
0.019∗∗∗
(3.110)
0.008∗∗∗
(2.684)
No
Yes
180,480
(4)
∗∗∗
0.183∗∗∗
(5.095)
0.101∗∗∗
(4.164)
0.083∗∗∗
(2.809)
0.010∗∗∗
(4.173)
Yes
Yes
180,480
0.028
(4.939)
0.024∗∗∗
(5.713)
0.018∗∗∗
(4.785)
0.011∗∗∗
(3.411)
-0.043∗∗∗
(-5.384)
0.016∗∗∗
(2.856)
No
Yes
2,575,118
Extensive margin
(5)
(6)
∗∗∗
0.023
(3.852)
0.017∗∗∗
(5.026)
0.018∗∗∗
(4.711)
0.011∗∗∗
(3.560)
-0.045∗∗∗
(-5.480)
0.014∗∗∗
(2.875)
1.219∗∗
(2.252)
1.762∗∗∗
(3.162)
No
Yes
2,575,118
0.017∗∗∗
(4.984)
0.014∗∗∗
(2.870)
1.751∗∗∗
(3.130)
Yes
Yes
2,575,118
Table: Exports by firm product destination - 2007
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Econometric analysis
Robustness checks
Are results similar across time?
⇒ Yes (at least for 2000)
Sensitive to our measure of income?
⇒ Same results with GDP and GDP per capita instead of GNI
Sensitive to other gravity variables?
⇒ Results robust to the introduction of borders, common language, colony
Importance of the sample of countries, sectors used?
⇒ Focus on ”final” product, drop ”extreme” countries: same result
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Conclusion
Conclusion
High-end producers benefits more from emerging countries growth
⇒ increasing share of luxury products in aggregate exports - in particular in
emerging countries
Micro underpinnings explain this aggregate trend
⇒ high-end products more sensitive to income per capita
⇒ high-end products more sensitive to top incomes
⇒ high-end products less sensitive to distance
What’s next?
Focus on the 2008-crisis
Implications for the labor market
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