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14. Januar 2010
Does Export ConcentrationCause Volatility?Christian Busch
14. Januar 2010 2
Overview
� Countries with undiversified export structure are plausibly morevulnerable to external shocks.
� But difficult to evaluate “causal” influence of export concentration on external volatility (exchange rate, terms of trade, export growth)
� Use of a new instrument that is based entirely on geographic characteristics, and thus plausibly uncorrelated with other determinants, including institutions, income, and policies.
� Causal effect found for terms of trade and export growth, but not for exchange rates.
14. Januar 2010 3
Introduction
� Large variation in volatility of macroeconomic aggregates (output, exports, exchange rates, terms of trade etc.) across countries
� Volatility decreases with level of development
� Lack of access to financial markets to mitigate external risks� External shocks can be amplified by weak institutional environment
(Rodrik, 1999, JEG)
� Instability in economic performance critical for many developing countries
� Uncertainty lowers private investment and leads to slower growth� Increases inequality and poverty
� Instability can result in crises
14. Januar 2010 4
Determinants of Volatility
� Policy Mismanagement (Fatas and Mihov, 2003, QJE)
� Financial Institutions (Easterly et al. 2001, WB)
� Political Institutions (Acemoglu et al., 2003, JME)
� Export Concentration and Geography (Malik and Temple, 2009, JDE)
14. Januar 2010 5
Determinants of Volatility: Institutional Constraints and Export Concentration
ALB
DZA
AGO
ATGARGARM
AUSAUT
AZE
BGD
BRB
BLR
BEL
BLZ BENBOL
BWA
BRA
BGR
BFA
BDI
KHMCMR
CAN
CPV
CAFCHL
CHN
COL
COM
COG
CRIHRV
CUB
CYP
CZE
DNK
DMA
DOM ECUEGY
SLVEST
ETHFJI
FIN
FRA
GAB
GMB
GEO
DEU
GHA
GRCGRD
GTM
GIN
GNB
GUY
HTI
HND
HKG
HUN ISL
INDIDN
IRN
IRL
ISR
ITA
CIVJAM
JPN
JOR
KAZ
KEN
KOR
KGZ
LVA
LBN
LSO
LTU
LUX MAC
MKD
MDG
MWI
MYS
MLI
MLT
MRT
MUS
MEX
MDAMAR
MOZ
NAM
NPL
NLD
NZL
NICNER
NGA
NORPAK
PAN
PNG
PRY
PER
PHL
POL
PRT
ROM
RUS
RWA
KNA
LCA
VCT
STP
SEN
SYCSLE
SGP
SVK
SVN
ZAF
ESP
LKASWZ
SWECHE
SYR TJK
TZA
THA
TGOTTO
TUNTUR
UGAUKR
GBRUSA
URYVEN
VNM
YEM
ZMB
ZWE
0.0
5.1
.15
.2V
olat
ility
of G
DP
per
cap
ita g
row
th r
ate
1 2 3 4Export concentration
ALB
DZA
AGO
ATG
ARG
ARM
AUS
AUT
AZE
BGD
BRB
BLR
BEL
BLZBEN
BOL
BWA BRA
BGR
BFA
BDI
KHMCMR
CAN
CPV
CAF
TCD
CHL
CHN
COL
COM
ZAR
COG
CRI
HRV
CUB
CYP CZE
DNK
DMA
DOMECU
EGY
SLV EST
ETH
FJI
FIN
FRA
GAB
GMB
GEO
DEU
GHA
GRC
GRD
GTM
GIN
GNB
GUY
HTI
HND
HKGHUN
ISL
IND
IDN
IRN
IRL
ISRITA
CIV
JAM
JPN
JOR
KAZ
KEN
KOR
KGZ
LVA
LBN
LSOLTU
LUX
MKD
MDG
MWI
MYS
MLI
MLT
MRT
MUS
MEX
MDA
MAR
MOZ
NAM
NPL
NLD
NZL
NICNER
NGA
NORPAK
PAN
PNG
PRY
PER
PHL
POL
PRT
ROM
RUS
RWA
KNA
LCA
VCT
STP
SEN
SYC
SLE
SGP
SVK
SVN
ZAF
ESPLKA
SWZSWECHE
SYR
TJK
TZA
THA
TGO
TTO
TUN
TUR
UGA
UKR
GBRUSA
URY
UZB
VEN
VNM
YEM
ZMB
ZWE
0.0
5.1
.15
Vo
latil
ity o
f G
DP
per
ca
pita
gro
wth
rat
e
0 .2 .4 .6 .8Political constraints
14. Januar 2010 6
Export Concentration versus Income per Capita
ALB
DZA
AGO
ATG
ARG
ARM
AUS
AUT
AZEBHS
BHRBGD
BRB
BLR
BEL
BLZ
BEN
BMU
BTN
BOLBWA
BRABGR
BFA
BDI
KHMCMR
CAN
CPV
CAF
CHL
CHN
COL
COMCOG
CRI
HRV
CUB
CYP
CZE
DNK
DJIDMA
DOM
ECU
EGY
SLV
ERI
EST
ETH
FJI
FIN
FRA
GAB
GMB
GEO
DEU
GHA
GRC
GRD
GTM
GIN
GNB
GUYHTI
HND
HKG
HUN
ISL
IND
IDN
IRN
IRL
ISR
ITA
CIV
JAM
JPN
JOR
KAZ
KEN
KOR
KWT
KGZ
LVALBN
LSO
LTU
LUX
MAC
MKD
MDG
MWI
MYS
MLI
MLT
MRT
MUS
MEX
MDA
MNG
MAR
MOZ
NAM
NPL
NLD
NZL
NIC
NER
NGA
NOR
OMN
PAK
PAN
PNGPRY
PER
PHL
POL
PRT
QAT
ROM
RUS
RWA
KNALCAVCT
STP
SAU
SEN
SYCSLE
SGP
SVKSVNZAF
ESP
LKA
SDN
SWZ
SWECHE
SYR
TJK
TZA
THA
TGOTTO
TUN
TUR
TKM
UGA
UKR
GBR USA
URY
VEN
VNMYEM
ZMB
ZWE
12
34
Exp
ort C
onc
entr
atio
n
6 7 8 9 10GDP per Capita
ALB
DZA
AGO
ATG
ARG
ARM
AUS
AUT
AZE
BGD
BRB
BLR
BEL
BLZBEN
BOL
BWABRA
BGR
BFA
BDI
KHM CMR
CAN
CPV
CAF
TCD
CHL
CHN
COL
COM
ZAR
COG
CRI
HRV
CUB
CYPCZE
DNK
DMA
DOMECU
EGY
SLV EST
ETH
FJI
FIN
FRA
GAB
GMB
GEO
DEU
GHA
GRC
GRD
GTM
GIN
GNB
GUY
HTI
HND
HKGHUN
ISL
IND
IDN
IRN
IRL
ISRITA
CIV
JAM
JPN
JOR
KAZ
KEN
KOR
KGZ
LVA
LBN
LSOLTU
LUX
MAC
MKD
MDG
MWI
MYS
MLI
MLT
MRT
MUS
MEX
MDA
MAR
MOZ
NAM
NPL
NLD
NZL
NICNER
NGA
NORPAK
PAN
PNG
PRY
PER
PHL
POL
PRT
PRI
ROM
RUS
RWA
KNA
LCA
VCT
STP
SEN
SYC
SLE
SGP
SVK
SVN
ZAF
ESPLKA
SWZSWECHE
SYR
TJK
TZA
THA
TGO
TTO
TUN
TUR
UGA
UKR
GBRUSA
URY
UZB
VEN
VNM
YEM
ZMB
ZWE
0.0
5.1
.15
Vo
latil
ity o
f G
DP
per
ca
pita
gro
wth
rat
e
6 7 8 9 10Income per capita
14. Januar 2010 7
Causality and Model Uncertainty
� Instrumental Variables
� Acemoglu et al. (2003, JME): Institutions versus policies
� Bayesian Methods
� Malik and Temple (2009, JDE): Geography and export concentration
� Panel Data
� Yang (2008, JM): Influence of democracy depends on ethnic homogeneity
� Here: New instrument for export concentration based on geographic characteristics
14. Januar 2010 8
Approach
� Use geographically determined component of export concentration as an instrument for actually observed export concentration to study influence on external volatility
� Remoteness as a natural barrier to trade (Malik and Temple, 2009)
� Transport costs affect sectors differently (imported intermediate goods)
� countries may be locked into concentrated export structures
� Export concentration determines how external shocks are absorbed
� Terms of trade: Undiversified countries are hit more severely by price shocks
� Exports: Diversification dampens exposure to demand shocks
� Exchange rates: currency demand fluctuates with exports
14. Januar 2010 9
Geography-based Instrument for Export Concentration
� Appropriately weighted average of countries’ remoteness (based on Frankel and Romer, 1999)
� Include information about distance, population, area, landlocked, border
� Do not use common geographic variables
� Distance from equator and tropical area (Sachs, 2003)
� Soil quality (Sokoloff and Engerman, 2000)� Coastal area (Acemoglu et al., 2005)
� Control for trade � Remoteness reduces trade; Increased specialization induces more
volatility (di Giovanni and Levchenko, RES, forthcoming)
14. Januar 2010 10
New Zealand: Influence of Distance on Export Concentration
Argentina
Australia
AustriaBahrain
BangladeshBarbadosBelgium
Bolivia
Brazil
Bulgaria
Canada
ChileChina
Colombia
Cook Islands
Costa Rica Cyprus
Denmark
EcuadorEgypt
Fiji
Finland
FranceGermany West
GhanaGreece
Guatemala
Hong Kong
HungaryIceland
India
Indonesia
IranIraq
IrelandIsrael
Italy
Jamaica
Japan
Jordan
Kenya
Kiribati
Korea South
Kuwait
Malaysia
MaltaMauritiusMexico
Myanmar (Burma)
Nepal
Netherlands
New Caledonia
Nigeria
Niue
Norway
OmanPakistan
Panama
Papua New Guinea
Peru
Philippines
PolandPortugalQatar
Romania
Saudi Arabia
Seychelles
Singapore
Solomon Islands
South Africa
Spain
Sri Lanka
SwedenSwitzerland
Syria
Tanzania
Thailand
Trinidad and TobagoTurkey
Tuvalu
USSR
United Arab Emirates
United Kingdom
United States
Uruguay
Venezuela
Vietnam
Zimbabwe
1.5
22
.53
3.5
4ex
port
con
cent
ratio
n
7 7.5 8 8.5 9 9.5log distance
14. Januar 2010 11
Belgium: Influence of Trading Partner‘s Size on Export Concentration (Controlling for Distance)
Seychelles
Bahamas
Malta
Djibouti
Iceland
SurinameBarbados
Qatar
Bahrain
Comoros
Fiji
Cyprus
GuyanaGambia
OmanGabon
Guinea-Bissau
Trinidad and Tobago
Mauritania
Jordan
Kuwait
Mauritius
United Arab Emirates
Congo Republic
Liberia
Panama
Mongolia
Costa Rica
Ireland
Nicaragua
JamaicaTogo
Uruguay
Central African Republic
Singapore
Paraguay
Sierra Leone
Honduras
Israel
Norway
El Salvador
New Zealand
Chad
Benin
TunisiaDominican Republic
Denmark
Finland
Bolivia
Guinea
MaliSwitzerland
SyriaYemenZambia
Guatemala
Burundi
Haiti
Austria
Senegal
Ecuador
Rwanda
Niger
Greece
Zimbabwe
Malawi
Sweden
Saudi Arabia
AngolaNetherlandsBulgariaCameroon
Portugal
Hong Kong
Iraq
Ivory Coast
Burkina Faso
Hungary
AlgeriaGhana
Chile
Madagascar
Morocco
Venezuela
Sri Lanka
Uganda
Peru
Malaysia
Sudan
Nepal
Mozambique
Kenya
Australia
Yugoslavia
Romania
Colombia
Tanzania
Spain
Egypt
ArgentinaSouth Africa
Congo Democratic Republic
Canada
Iran
Poland
Myanmar (Burma)
Korea SouthFrance
Italy
Ethiopia
Turkey
United Kingdom
Philippines
Mexico
PakistanThailand
Bangladesh
Nigeria
BrazilIndonesia
Japan
United States
India
China
-1-.
50
.51
e( e
xpor
t co
ncen
tra
tion
| X )
-4 -2 0 2 4 6e( lpop2 | X )
coef = -.08958648, se = .01800051, t = -4.98
14. Januar 2010 12
Method
� Estimate bilateral export concentration equation
� Include only purely geographic determinants
� Aggregate fitted values to estimate a geographic component of countries’ overall export concentration
� Problem: bilateral export concentration cannot be easily aggregated across countries (as is the case for trade)
� Solution: use an additively decomposable inequality measure
14. Januar 2010 13
Generalized Entropy Inequality Measure…
� x value of trade in product h between country i and country j� n number of products traded
� µ mean value of trade flows across products
� α inequality weighting parameter (set to 0.5)
14. Januar 2010 14
Concentration Measures Compared
0.2
.4.6
.81
Her
finda
hl c
onc
entr
atio
n
1 2 3 4Generalized entropy concentration
14. Januar 2010 15
… allows Decomposition by Export Country
� Where the first term is the concentration between all bilateral trade relationships for country i,
� and the second term is the concentration within each bilateral trade relationship
� Thus, we need to estimate Xi,j, Ni,j, and GEi,j
14. Januar 2010 16
Data
� Export concentration: � Concentration across products (4-digit SITC)� Comtrade dataset; averaged over 1980-2000
� Volatility (standard deviation; WDI)� Terms of trade� Real effective exchange rate� Export growth
� Gravity variables from Frankel and Romer (1999)
� Trade openness (EX+IM / GDP; WDI)
� Institutional environment (Aggregate Governance Indicators)
14. Januar 2010 17
How does Geography Influence Concentration? Dependent Variable
ln Export ln Numberall > 50 value of sectors original
valuesComtrade
values
ln distance 0.213*** 0.212*** -0.583*** -0.243*** -0.85*** -1.225***(0.007) (0.008) (0.033) (0.011) (0.04) (0.036)
ln population (country i) -0.262*** -0.246*** 0.663*** 0.270*** -0.24*** -0.411***(0.003) (0.005) (0.020) (0.006) (0.03) (0.030)
ln area (country i) 0.100*** 0.094*** -0.164*** -0.094*** -0.12*** -0.012 (0.003) (0.003) (0.016) (0.005) (0.02) (0.023)
ln population (country j) -0.042*** -0.025*** 0.718*** 0.085*** 0.61*** 1.400***(0.004) (0.005) (0.019) (0.007) (0.03) (0.028)
ln area (country j) 0.010*** -0.005 -0.184*** -0.011** -0.19*** -0.307***(0.003) (0.004) (0.016) (0.005) (0.02) (0.023)
Landlocked dummy 0.107*** 0.033** -0.905*** -0.148*** -0.36*** -1.149***(0.011) (0.014) (0.060) (0.021) (0.08) (0.103)
Common border dummy-0.231*** -0.075** 0.426*** 0.123***(0.039) (0.038) (0.156) (0.045)
Constant 4.800*** 4.275*** 7.103*** 3.120*** -6.38*** -7.725***(0.068) (0.086) (0.351) (0.120) (0.42) (0.469)
R2 0.358 0.304 0.319 0.226 0.360 0.455
Observations 12'503 6'773 6'773 6'773 3'220 6'284
Bilateral trade flows
Frankel/Romer
Bilateral export concentration Bilateral exports
Number of sectors
14. Januar 2010 18
Actual versus Constructed Export Concentration
DZA
AGO
ARG
AUS
AUT
BHS
BHRBGD
BRB
BEL
BLZ
BENBTN
BOL
BRABGR
BFA
BDI
CMR
CAN
CAF
CHL
CHN
COL
COMCOG
CRI
CYP
DNK
DJIDMA
DOM
ECU
EGY
SLV
ETH
FJI
FIN
FRA
GAB
GMBGHA
GRC
GRD
GTM
GIN
GNB
GUYHTI
HND
HKG
HUN
ISL
IND
IDN
IRN
IRL
ISR
ITA
CIV
JAM
JPN
JORKEN
KOR
KWT
LBR
MDG
MWI
MYS
MLI
MLT
MRT
MUS
MEX
MNG
MAR
MOZ
MMRNPL
NLD
NZL
NIC
NER
NGA
NOR
OMN
PAK
PAN
PNGPRY
PER
PHL
POL
PRT
QAT
ROM
RWA
LCAVCT
SAU
SEN
SYCSLE
SGP
SLBSOM
ZAF
ESP
LKA
SDN
SUR
SWECHE
SYR
TZA
THA
TGOTTO
TUN
TUR
UGAARE
GBRUSA
URY
VEN
YEM
ZMB
ZWE
12
34
Act
ual E
xpor
t Con
cent
ratio
n
2 2.5 3 3.5 4Constructed Export Concentration
14. Januar 2010 19
External Volatility and Export Concentration
Dependent Variable
OLS IV OLS IV OLS IV(1) (2) (3) (4) (5) (6)
Export 0.068*** 0.043*** 0.054*** 0.006 0.076*** 0.054***Concentration (0.008) (0.013) (0.012) (0.023) (0.010) (0.019)
Trade -0.040*** -0.038*** -0.066*** -0.056*** -0.040*** -0.035***Openness (0.009) (0.009) (0.019) (0.019) (0.012) (0.013)
Constant 0.087** 0.143*** 0.248*** 0.326*** 0.121** 0.161***(0.039) (0.055) (0.071) (0.098) (0.047) (0.058)
R2 0.404 0.353 0.323 0.139 0.324 0.296 N 110 110 73 73 127 127
Excluded Instrument Predicted Predicted PredictedConcentration Concentration Concentration
Levels of statistical significance indicated by: *** p<0.01; ** p<0.05; * p<0.1
Numbers reported in parentheses are heteroscedasticity-robust standard errors.
Regressions of Volatility
Terms of Trade Real Effective Exchange Rate Export Growth
14. Januar 2010 20
Importance of Controlling for Trade (e.g. ToT)-1
.5-1
-.5
0.5
1R
esid
uals
from
Re
gre
ssin
g E
xp. C
onc.
on
Pre
d. T
rad
e
-1 -.5 0 .5 1Resdiuals from Regressing Predicted Export Concentration on Predicted Trade
-2-1
01
2R
esid
uals
from
Re
gre
ssin
g T
rade
on
Pre
d. E
xp. C
on
c.
-2 0 2 4 6Resdiuals from Regressing Predicted Trade on Predicted Export Concentration
-1-.
50
.51
1.5
Res
idu
als
fro
m R
egr
ess
ing
Exp
. Con
c. o
n P
red.
Exp
.Con
.
-2 0 2 4 6Resdiuals from Regressing Predicted Trade on Predicted Export Concentration
-3-2
-10
12
Res
idua
ls fr
om R
egre
ssin
gTra
de o
n P
red
. Tra
de
-1 -.5 0 .5 1Resdiuals from Regressing Predicted Export Concentration on Predicted Trade
14. Januar 2010 21
Export Concentration and InstitutionsRegressions of Volatility in Terms of Trade
Method OLS OLS IV IV IV2SLS First Stage First Stage
Exp. Conc. Governance(1) (2) (3) (4) (5)
Export 0.046*** 0.047*** 0.042* Concentration (0.010) (0.014) (0.025)
Trade -0.017** -0.011 -0.011 0.008 1.130 Openness (0.008) (0.008) (0.007) (0.107) (0.928)
Aggregate -0.005*** -0.004** -0.003 Governance (0.001) (0.002) (0.004)
Predicted Exp. 0.505** 2.540
Concentration (0.230) (2.067)
Settler 0.323*** -2.394***
Mortality (0.044) (0.458)
Constant 0.057* 0.024 0.042 -0.302 -1.394 (0.034) (0.036) (0.067) (0.964) (6.893)
R2 0.468 0.384 0.374 0.512 0.431 N 104 58 58 58 58
Excluded Instrument Predicted Predicted PredictedConcentration, Concentration, Concentration,Settler Mortality Settler Mortality Settler Mortality
Levels of statistical signif icance indicated by: *** p<0.01; ** p<0.05; * p<0.1
Numbers reported in parentheses are heteroscedasticity-robust standard errors.
14. Januar 2010 22
Robustness Checks
� Overidentification tests using concentration across countries (predicted from weighted bilateral distance) as additional IV
� Control for export shares of various natural resources (oil, agriculture, various raw materials)
� Control for the size of the manufacturing sector: inconclusive results
14. Januar 2010 23
Conclusions
� Bilateral export concentration is well described by a gravity equation
� Inequality decomposition methods allow to aggregate bilateral export concentration to an overall measure of export concentration
� Predicted export concentration contains valuable information about actual concentration
� Using predicted export concentration as an IV, export concentration exhibits a causal influence on volatility in terms of trade and growth in exports, but not so on volatility in exchange rates
� The instrumental variable is not suited to elucidate the separate roles of institutions and export concentration in determining aggregate volatility