Economic structure, growth, and convergence

Economic structure, growth, and convergence

Dani Rodrik

August 2011

Lack of convergence over different time horizons

AUTBELDNKFIN

FRADEUITANLD

NORSWECHE

GBR

IRLGRC

PRTESP

AUSNZLCANUSA

CZEBRA

CHL

MEX

VEN

JAM

CHN

INDIDN

JPN

PHL

KOR

THA

TWN

MMR

HKG

MYS

NPL

SGP

LKA

PRK

VNM

IRN

IRQ

JORLBN

SYRTUR

WBG

DZAEGYMARZAFTUN

0

.01

.02

.03

4 5 6 7 8log GDP per worker, 1820

1820-2008

AUT

BELDNK

FIN

FRADEUITA

NLD

NORSWE

CHE

GBR

IRLGRC

PRT ESP

AUSNZL

CANUSA

ALB BGR CZEHUN

POL

ROM

YUGARGBRA CHLMEX

URY

VEN

JAM

CHN

INDIDN

JPN

PHL

KOR

THA

TWN

MMR

HKG

MYS

NPL

SGP

LKA

PRK

VNM

IRN

IRQ

JOR

LBN

SYRTUR

WBG

DZAEGY

GHA

MAR ZAF

TUN

0

.01

.02

.03

6 6.5 7 7.5 8log GDP per worker, 1870

1870-2008

AUTBELDNK

FIN

FRADEUITA

NLD

NOR

SWECHE

GBR

IRLGRCPRTESP

AUSNZL

CANUSAALB BGR CZE

HUNPOL

ROM

YUG

ARG

BRA

CHLCOL MEXPER

URY

VEN

JAM

CHN

IND IDN

JPN

PHL

KOR

THA

TWN

MMR

HKG

MYS

NPL

SGP

LKA

PRK

VNM

IRN

IRQ

JOR

LBN

SYRTUR

WBG

DZAEGY

GHA

MAR

ZAF

TUN

0

.01

.02

.03

.04

6.5 7 7.5 8 8.5log GDP per worker, 1913

1913-2008

AUTBEL

DNK

FINFRA

DEUITANLD

NORSWE

CHEGBR

IRLGRCPRTESP

AUSNZL

CANUSAALB

BGRCZEHUNPOLROMYUG

ARG

BRA CHLCOLMEXPER URY

VENBOL

CRI

CUB

DOM

ECUSLVGTM

HTI

HND

JAM

NIC

PAN

PRY

PRITTO

CHN

INDIDN

JPN

PHL

KOR

THA

TWN

BGD

MMR

HKG

MYS

NPLPAK

SGP

LKA

AFG

KHM

LAOMNG

PRK

VNMBHRIRN

IRQ

ISR

JOR

KWT

LBN

OMN

QAT

SAUSYRTUR

ARE

YEMWBGDZA

AGOBEN

BWA

BFA

BDICMR

CPV

CAF

TCDCOM

COG

CIVDJI

EGY

GNQ

ETH

GABGMB GHA

GINGNBKEN

LSO

LBR

LBY

MDG

MWIMLIMRT

MUS

MARMOZ NAM

NER

NGARWASTP

SEN

SYC

SLE SOM

ZAFSDN

SWZ

TZA

TGO

TUN

UGA

ZAR

ZMBZWE

-.02

0

.02

.04

.06

6 7 8 9 10log GDP per worker, 1950

1950-2008

Unconditional and conditional convergence -.

2-.

10

.1.2

.3

Gro

wth

of G

DP

per

work

er,

ort

hogonal part

6 8 10 12 14log of initial real GDP per worker

coeff = -0.034 (clustered t-stat = 4.69)

-.5

-.4

-.3

-.2

-.1

Gro

wth

of G

DP

per

work

er,

ort

hogonal part

6 8 10 12 14log of initial real GDP per worker

Each observation corresponds to one country over a specific decade. Right panel includes country dummies.

unconditional (left panel) and conditional (right panel)

Pooled decadal convergence regressions, 1970-2008

No unconditional sectoral convergence

ALB ARG AUSAUT

AZE

BEL

BGR

BRA

CANCHECHL

CRICUB

CZE DEUDNKDOM

ECU

EGYESP

EST

FIN

FRAGBRGRC

HRVHUN

IDN

IRLISL

ITAJAM JPN

KGZ

KOR

LKA

LUX

LVA

MDA MEX

MNGMUS

MYS

NIC

NLD NORNZLPAK PAN

PER

PHL

POL

PRT

ROMRUS SGP

SLV

SVKSVN SWE

THATUR

UKR

USA

VEN

Industry

-.1

-.05

0

.05

.1.1

5

2 4 6 8Log industry value added per worker in initial year

ARG

AUSAUT

AZE

BELBGR

BHSBRA

CANCHECHL

CRI

CUBCZE

DEUDNK

DOM

ECUEGY

ESP

EST

FINFRAGBRGRC

HRVHUN

IDN

IRLISL

ITAJAM JPNKGZ KOR

LKALUX

LVAMDA

MEXMNG

MUSMYS

NIC

NLDNOR

NZLPAKPAN

PER

PHLPOL

PRTROMRUS SGP

SLV

SVK SVN SWE

THATUR

UKR

USA

VEN

Services

-.1

-.05

0

.05

.1.1

5

2 3 4 5 6 7Log services value added per worker in initial year

ARG

AUS

AUTAZEBEL

BGR

BHSBRA CAN

CHE

CHLCRI

CUB

CZE

DEUDNK

DOM

ECUEGY

ESP

EST

FIN

FRA

GBRGRC

HRV

HUN

IDNIRL

ISLITA

JAM

JPN

KGZ KOR

LKA

LUX

LVAMDA

MEX

MNG

MUSMYS

NIC

NLD

NOR

NZL

PAK

PAN

PER

PHL

POL

PRT

ROMRUSSLV

SVK

SVN

SWE

THA

TURUKR

USA

VEN

Agriculture

-.1

-.05

0

.05

.1.1

5

0 2 4 6 8 10Log agricultural value added per worker in initial year

Unconditional convergence at sectoral level, 1996-2006

Is (aggregate) manufacturing different?

GHA

CHN

ETH

NGAIND

ZMB

MWIKEN

PER

BOL

HKG

IDN

BRA

MUS

SEN

COL

MEX

CRI

KOR

MYS

THA

CHLTWN

PHLTUR

ARG

SWE

DNKVEN

SGP

ITA

JPNFRAUKM

ESP

NLD

ZAF

USA

0

.05

.1.1

5.2

8 9 10 11log MVA per worker, 1990

Cross section, 1990-2005

GGDC + MR data

BGR

ERI

ETH

ROU

MKD

SVK

LVA

CZE

HUN

JOR

POL

MAC

IRN

ECU

PSE

ZAF

OMN

MLT

PRT

SVN

TUR

BRA

NZL

ISRESP

DNKGBR

NOR

SGP

FRACANITASWE

AUT

AUS

KOR

FINNLD

LUX

JPN

IRL

-.3

-.25

-.2

-.15

-.1

Com

ponent plu

s r

esid

ual

8 9 10 11 12log initial MVA per worker

Pooled decadal cross-sections, 1990-2007 (nominal)

UNIDO data

Details on data and methods

• UNIDO INDSTAT4 dataset: 4-digit manufacturing

• Coverage: largely organized firms

• Data on employment and (nominal) value added– labor productivity = VA/employment

• Time series tend to be short– I pool cross-sections over overlapping decades between 1990-2007 to

maximize no. of countries

– No. of countries: 40 (for 10-year horizon); 72 (for 5-year horizon)

• Number of industries included per country: 1-152, in double digits in most cases

Methods (I)Let denote (nominal) labor productivity in industry i¸country j,

time t.

The rate of growth of labor productivity in real terms:

,

where is the increase in the industry-level deflator

Let growth depend both on convergence and country-specific

factors:

,

where is a dummy variable that stands in for all time-invariant

country-specific factors.

is the convergence coefficient we are interested in estimating.

Methods (II)Assume a common global (U.S. dollar) inflation rate for each

individual industry, , up to a random error term.

Then

ln ,

This can be expressed equivalently as

,

Or, when the regression is run as pure cross-section.

A test of unconditional convergence consists of dropping country

dummies and checking whether the estimated coefficient

remains negative and statistically coefficient.

Unconditional convergence in manufacturing

coefficient = -0.031 (clusteret t-stat = -8.14)

-1.2

-1-.

8-.

6-.

4-.

2

gro

wth

of la

bor

pro

ductivity, ort

hogonal part

6 8 10 12 14log of initial labor productivity

coefficient = -0.063 (clustered t-stat = -11.90)

-1.4

-1.2

-1-.

8-.

6-.

4

gro

wth

of la

bor

pro

ductivity, ort

hogonal part

6 8 10 12 14log of initial labor productivity

Each observation corresponds to a 4-digit manufacturing industry. Regressions include decade, industry, and (for right panel) country dummies.

Unconditional (left panel) and conditional (right panel)

Pooled decadal industry convergence regressions, 1990-2007

Variation in unconditional convergence rates

ETH

ERI

ERI

ERI

ERIETH

ECUBGR

ETHBGRBGR

ETHECU

SVKSVKSVK

ETHERI

LVA

ERI

ECULVASVK

ERI

LVASVKSVKJOR

HUNCZEHUNCZE

ERI

LVALVA

HUN

IRNECUECUJOR

POL

ECUCZESVK

POLJORPOLPOLCZE

HUN

POLIRNPOLECU

JORECUCZEECUPSE

LVAPOLCZECZEIRNJOR

ETHCZEPOLLVAIRNIRNIRNIRNPOLECUIRNPOLZAFIRNJOR

SVN

JORIRN

CZE

JOR

BRAOMN

JOR

MACPRTIRNSVNBRA

OMN

SVNOMNTUR

SVN

PRTIRNTURTURTURTURPRTECUMLTSVN

MLT

SVNTURMLTOMN

ISRMLTSVNPRT

IRL

SGPTUR

ISRBRASVNSVNPRT

TURISRESPESPGBR

TUR

GBR

ESPTUR

SVN

TURIRL

MLT

ESPGBRCANGBR

ESPGBRCAN

SGP

GBRESPTUR

CANESPCANNORNORNOR

SGP

CANESPCANAUTESPESPFRAFRACANIRLESPNORFIN

OMN

ITAITAGBRGBRSWEFRAFRAFRAKORNORFINAUTFINIRLIRLFRALUXNLD

GBR

FRAKORJPNFINESPITAIRLFINKORKORSWEITAFINDNKDNKCANITADNKGBRSWEKORCANFRAKORNORSWESWEFRAAUTFINFRAGBRCANFINSWEDNKCAN

FINITAAUTFINKORCANNLDFRANORNORITAAUTSWEITAGBRKORJPNKORFIN

FRADNKSWESWE

IRL

NLDNLDITANLDITANORITAAUTSWEKORAUTITAAUTJPNSWENORKORJPNDNKAUT

JPNKORJPNDNKJPNNLDJPNNLDNLDFINNLDJPN

NLDSVNAUTJPNJPNJPN

Textiles and clothing

coeff. = -0.015

-.6

-.4

-.2

0.2

Com

ponent plu

s r

esid

ual

7 8 9 10 11 12Log of Labor Productivity, 10 years prior

HUN

ECU

ETHETHETHBGR

ETHERI

ECU

ERIERI

ETH

ERI

ETHSVKJORPOL

JOR

ETH

SVKHUNSVKLVA

SVK

HUN

POL

JORJORPOLLVAETHLVAPOLECUECUHUNSVK

JORLVA

JORPOLCZE

ERI

IRN

SVKCZESVKETHIRNHUNETHLVAHUNECUPOLCZEECUSVKIRNETHSVKERI

BGRSVKIRNLVAIRN

ERI

ECUOMNSVKIRNHUN

SVK

ERI

HUNECUOMNECUECUIRN

PRTPOLCZEPOL

IRN

LVAHUN

SVK

ECUECUECU

ECUOMN

ETH

IRNIRN

JORPRT

OMNHUN

IRNJORHUNOMNPOLECU

TURPOLTURMLTMLTPRTECUMLT

IRNPOLIRNIRN

SVNOMNHUN

MLTETHLVATURLVAJORIRNTURTUR

ECUIRN

OMNMLTHUNSVNSVNJORTURPRTOMNPRTSGPPOLSGPIRNESPMLTETHSVN

ERI

PSE

PRT

MLT

ROUOMNESP

SVK

NORTURSVNPRTSGPNORFINSVN

GBRDNK

KORSGPCAN

IRL

ERIBRAPRTKORGBR

OMN

SVN

TURSGPESPNORMLTESPLUX

TURITAGBRDNKSGPTUR

PRT

TURMLTIRLESPFRAFRASVNNLD

NOR

FRANOR

LUXDNKDNK

JORAUTFINCANFRAFIN

LVATURSWEAUTSWEAUTIRLFRAHUNNLDFRACANTURFINTUR

ESPSWEESPITAKORHUN

FINISRSWEAUT

TURESPITAFINITAESPNLDKORDNKITADNKAUTESPAUTFRAFRANORGBRFRAKORFINSGPSGPESPITASWEESP

NLD

FRAJPNGBRFINCANSWECANNORCANESPKORAUTSWE

GBRIRLJPNBRA

ITA

ITADNKGBRITAITACANJPNNOR

ITASWEGBRKORPRTFINJPNGBRKORITAFINITAFINJPNNORITA

IRLSWE

CAN

AUTAUTCANITAITAJPNNLDAUTNORFINFRA

TUR

NLDCANITANLDFRACAN

FIN

IRLFINOMNGBRKORKORNORFINSWESWEGBRNLDFRACANESPESPSVNKORAUSNLDFRA

KOR

CANCANLUXCANAUTIRLIRLJOR

FINNLD

POL

JPNESPNLDJPNCAN

DNKCANKORKORITAJPNKORJPNJPNJPN

CAN

POL

GBRJPNECUNLD

KORJPNNORJPNKORJPNJPNJPN

KORAUT

Food, beverages and tobacco

coeff. = -0.031

-.6

-.4

-.2

0.2

Com

ponent plu

s r

esid

ual

6 8 10 12 14log initial labor productivity

LVA

BGRBGRETHLVASVKLVA

ERI

ERI

JORCZELVA

MKD

BGRECUECULVAPOL

ECUHUNHUNIRNECU

SVK

LVAPOLPOLPOLPOLOMNSVKETH

MLT

HUN

CZE

IRNJOR

CZE

IRN

POLHUNHUN

LVAJOR

POLIRNIRNIRNIRN

MLT

PRTTUR

SVN

PRT

OMNIRN

NOR

TUR

PSE

PRTPRTPOL

HUNMLT

SVN

MLTBRAPRT

SVN

BRAESPECUTUR

KORIRLESPSVN

TUR

ESPESPIRL

SGP

ISR

SGP

NORBRAGBRIRLGBRNOR

KORGBRSWEESPSWECANTURFRAIRNIRLITAKORNORCANITAITAHUNFRAFRAFINITA

KORFINFINSWESGP

ESPGBRITAFRAAUTITANORDNKGBRNORFRAFINSWEFINFRADNKNOR

ISRITAGBRNLDESPAUTGBRITAESPFINNLD

MLTITASWESWEITAKOR

NLDSWEAUTFINSWEFRAFIN

NORKORNORAUTGBRCANESPCANFRAPRTFRAFRA

TURIRN

NLDBRASWECANBRAGBRNLDGBRCANESPKORKORKORSGPNLD

NLDJPNCANKOR

AUTJPNJPNJPN

CANJPNJPNJPN

JPN

Transport equipment

coeff. = -0.031

-.6

-.4

-.2

0.2

Com

ponent plu

s r

esid

ual

7 8 9 10 11 12log initial labor productivity

ERI

ERI

ECUBGR

SVK

BGR

ETHETH

LVAECUBGRBGRLVA

ETH

BGRBGRBGR

BGR

ECU

BGRBGRSVKLVASVK

LVA

LVA

ETH

OMNSVKSVKSVK

SVKLVAECUJORLVASVKECUSVKBGR

JOR

HUNSVKLVALVAJORSVKSVKECULVAECULVAMKDLVAIRNLVABGR

ERI

LVASVKSVKSVKCZEJOR

SVK

IRNLVAPOLSVKLVAJORCZELVAJORSVKSVK

ECU

OMNCZESVKECUCZECZEHUN

SVKECUSVKECUPOLSVKPOLPOLECUCZEIRNPOLJORIRNHUNPOLCZEIRN

IRNPOLCZE

IRNIRNCZE

POLIRNCZE

ECUPOLPOLPSE

CZE

IRN

POLPOL

IRNIRNPOLIRNECUIRNPOLPOL

IRN

SVN

IRNIRNCZEPOLCZEPOLPOLPOLCZEPOLSVKJORPOLOMNPOLIRN

POLIRNOMN

IRNSVK

OMN

ECUJORIRNHUNECUIRNPOLMLTIRNTUR

HUN

LVA

LVA

CZECZEIRNPOLTURCZECZE

HUN

TURCZESVNECUTURTURIRNPRT

IRL

POLSVNPOLSVNSVNSVN

OMN

GBR

SVN

SVNMLTIRNIRNPRTTUROMNMLTPOLJORSVNIRNPRTMLTTUR

TURSVNBRAPRTSVNPRTPRT

SVNSVN

BRASVNSVN

TURPRTMLTPOLPRTSVNPRTTURPRTSVNSVNIRNHUNPRTPRTIRLESP

SGPTUROMNMLTPRTTURSVN

TURJORPRTTUR

SVN

NORGBR

ISR

OMN

MLTSVNIRL

BRASVNMLTTURPRTSGP

KORPRT

OMN

IRLTURESPSVNBRA

TURTUR

GBRSWETURDNKSGPDNK

ECUTUR

SGPESPSVNESPESPIRL

ISR

SVNMLTIRLFRASGPBRAGBRSGPTUR

SWEGBR

ESPFINTUR

GBRNORDNKBRA

FRA

SGP

IRLNORGBR

BRAIRLESPIRLKORCANISRESPGBRFRAKORDNKCANCAN

BRASWEKORGBRMLTSGP

GBRCANNLDESPDNKIRLFINDNKDNKFRADNKESPKORSGPESPNORESPGBRNOR

BRA

IRL

NORISRBRAESPDNKKORSGPESPESPGBRAUT

ESPESPFINESPESPFRAKORSGPAUTCANGBRKORKORNORFRADNK

ITAFRAGBRNLDSWECANITASGPITABRAFIN

GBRNORKORCANESPFRAITAIRLIRLITA

TUR

NORCANNORNLDNLDDNK

TURISRDNKNORITAESPFINFINSWELUXCANSWECANSWEFRAFINFRA

OMN

DNKDNKFINAUT

ESPSGPITANORESPDNKDNKESPGBRFRAITANOR

PSE

CANGBRKORESPFINDNKDNKNLDFRAKORFRASGPGBRSWEGBRNLDKOR

SWE

NLDFRAAUTISRFRANLDDNKSWEKORDNKNORITAKORFRAITACANSGPNLDCANSWEFRACANFRAITAFRASWENORNLDESPESPCANAUTKORIRLNORNLDITAFRAKORSWEFRAGBRGBRSWEIRLDNKNORNORITAFINDNKSWENLDKORSGPFRASWEGBRAUTNLDFRASVNBRANLDAUTAUTAUTFINCANITACANFINSWEAUTNLDITATUR

IRL

ITAKORSWENLDCANSWEAUTAUTAUTFINGBRITAITASWEFRASGPITA

AUTITANORSWEAUTITAAUTKORJPNKORCANAUTDNKAUTAUTAUTITA

NLD

DNKAUTITATURKORITAITAFRANLDGBRNORAUTNORFRASGPSWESGPITAIRLGBRCANESPAUTSWEISRMLTJPNFINAUTSWEFINSWEFINFINSGPFRADNKKORNLDSWENLDITAFINNLDFINITANORKORGBRFINFINFINESP

KORFRANLDDNKAUTNORFINSWE

NOR

SWEAUTSWEAUTSWEFINNORITANOR

TUR

IRLAUTNORKORGBRAUTNLD

NLD

CANSGPAUTJPNISRIRL

KORKORJPNFINITA

JPNNORKORJPNFIN

FRA

JPNJPNNORGBRIRLJPNJPNJPNCAN

JPNFRAGBRJPNJPNJPNSGPBRAJPNJPNJPNSGPIRLJPN

AUS

OMNESP

JPNGBRJPNJPNJPNJPNFINJPNKORJPNJPNJPNJPNJPN

Machinery and equipment

coeff. = -0.038-.

6-.

4-.

20

.2

Com

ponent plu

s r

esid

ual

6 8 10 12 14log initial labor productivity

Unconditional convergence by industry groups

Aggregating unconditional convergence up

beta = convergence coefficient y = labor productivityalpha = employment share y* = frontier labor productivitytheta = relative productivity within country i industries; j countries

How structure dampens convergence

AUT

BRA

BGR

CAN

CZE

DNK

ECU

ERI

ETH

FIN

FRA

HUN

IRN

IRL

ISR

ITA

JPN

JOR

LVA

LUXMLT

NLD NOR

PSE

OMN

POLPRT

KORSGP

SVK

SVN

ZAF

ESP

SWE

MKD TUR

GBRAUTBRA

BGR

CANCZE

DNKECU

ERI

ETH

FIN

FRAHUN

IRN

IRL

ISR

ITA

JPN

JOR

LVA LUX

MLT NLD NOR

PSE

OMN

POL

PRT

KOR

SGP

SVK SVN

ZAF

ESP

SWEMKD

TUR

GBR

-10

-50

51

01

5

0 .2 .4 .6 .8 1MVA_ratio

term1 (normalized)

term2 (normalized)

Re-allocation effect (term 3)are resources moving in the right direction within

manufacturing?

151

153

154

155

171172

191

202

210

221

222

241

242

251

269

273

281

289

291

292331

351

359

369

above average productivity

below average productivity

textiles, spinning, weaving

basic chemicals

transport equip. nec

gen. purpose mach.

other chemicals

grain mill products, etc

-1-.

50

.51

1.5

-.04 -.02 0 .02change in employment share, 1998-2005

Structural change within manufacturing has reduced labor productivity growth of the sector by 0.9% p.a. during 1998-2005.

(Economy-wide) productivity growth decomposition in Latin America

Productivity decomposition in Latin America across different periods

(annual growth rates)

-0.01 -0.005 0 0.005 0.01 0.015 0.02 0.025 0.03 0.035 0.04 0.045

1990 - 2005

1975 - 1990

1950 - 1975

Sectoral productivitygrowth

Structural change

Data from Pages, Carmen ed., The Age of Productivity, Inter-American Development Bank, Washington, D.C., 2010.

… and across regions

-0.02 -0.01 0 0.01 0.02 0.03 0.04 0.05

HI

ASIA

AFRICA

LAC

within

structural

Decomposition of productivity growth by country group, 1990-2005

Productivity growth

within sectors

Productivity growth due

to structural change

The actual numbers

Country details

Patterns of structural change: Asia versus Latin America

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man

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wrt

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cspsgs

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wrtagr

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wrt

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wrt

-10

12

3

Lo

g o

f S

ecto

ral P

rod

uctivity/T

ota

l P

rodu

ctiv

ity

-.2 -.1 0 .1 .2

Change in Employment Share(Emp. Share)

Fitted values

*Note: denotes coef f . of independent v ariable in regression equation: ln(p/P) = + Emp. Share

Source: Authors' calculations with data f rom Timmer and de Vries (2009)

= -2.6866; t-stat = -1.17

Correlation Between Sectoral Productivity andChange in Employment Shares in Latin America (1990-2005)

agr

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tsc wrt

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tsc wrt

agr

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wrt

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wrtagr

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wrt

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min

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tscwrt

agr

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tsc

wrt

agr con

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tsc

wrt

-2-1

01

23

Lo

g o

f S

ecto

ral P

rod

uctivity/T

ota

l P

rodu

ctiv

ity

-.2 -.1 0 .1


Fitted values

*Note: denotes coef f . of independent v ariable in regression equation: ln(p/P) = + Emp. Share

Source: Authors' calculations with data f rom Timmer and de Vries (2009) and China's National Bureau of Statistics

= 3.5826; t-stat = 2.20

Correlation Between Sectoral Productivity andChange in Employment Shares in Asia (1990-2005)

Asia Latin America

Argentina

agrcon

cspsgsfire

man

min

pu

tsc

wrt

-.5

0.5

11.5

2

Lo

g o

f S

ecto

ral P

rod

uctivity/T

ota

l P

rodu

ctiv

ity

-.06 -.04 -.02 0 .02 .04


Fitted values

*Note: Size of circle represents employ ment share in 1990**Note: denotes coef f . of independent v ariable in regression equation: ln(p/P) = + Emp. Share


= -7.0981; t-stat = -1.21

Correlation Between Sectoral Productivity andChange in Employment Shares in Argentina (1990-2005)

Brazil

agr

con

cspsgs

fire

man

min

pu

tsc

wrt

-10

12

Lo

g o

f S

ecto

ral P

rod

uctivity/T

ota

l P

rodu

ctiv

ity

-.1 -.05 0 .05


Fitted values



= -2.2102; t-stat = -0.17

Correlation Between Sectoral Productivity andChange in Employment Shares in Brazil (1990-2005)

Nigeria

agr

con

cspsgs

fire

man

min

putsc

wrt

-4-2

02

46

Lo

g o

f S

ecto

ral P

rod

uctivity/T

ota

l P

rodu

ctiv

ity

-.15 -.1 -.05 0 .05 .1


Fitted values


Source: Authors' calculations with data f rom Nigeria's National Bureau of Statistics and ILO's LABORSTA

= -12.2100; t-stat = -1.06

Correlation Between Sectoral Productivity andChange in Employment Shares in Nigeria (1990-2005)

Zambia

agr

con

cspsgs

fire

man

min pu

tsc

wrt

-2-1

01

23

Lo

g o

f S

ecto

ral P

rod

uctivity/T

ota

l P

rodu

ctiv

ity

-.1 0 .1 .2


Fitted values


Source: Authors' calculations with data f rom CSO, Bank of Zambia, and ILO's KILM

= -10.9531; t-stat = -3.25

Correlation Between Sectoral Productivity andChange in Employment Shares in Zambia (1990-2005)

India

agr

concspsgs

fire

man

min

pu

tsc

wrt

-10

12

Lo

g o

f S

ecto

ral P

rod

uctivity/T

ota

l P

rodu

ctiv

ity

-.04 -.02 0 .02


Fitted values



= 35.2372; t-stat = 2.97

Correlation Between Sectoral Productivity andChange in Employment Shares in India (1990-2005)

Thailand

agr

con

cspsgsfire

man

min

pu

tsc

wrt

-10

12

3

Lo

g o

f S

ecto

ral P

rod

uctivity/T

ota

l P

rodu

ctiv

ity

-.2 -.1 0 .1


Fitted values



= 5.1686; t-stat = 1.27

Correlation Between Sectoral Productivity andChange in Employment Shares in Thailand (1990-2005)

What’s going on? Some possibilities:

• Some countries have more “surplus labor” in agriculture than others

• Role of comparative advantage: primary products versus manufactures

• Labor market rigidity: large hiring/firing costs may prevent employment growth in dynamic sectors

• Trade/industrial/currency policies have:– Not encouraged new tradable activities sufficiently

– Exposed tradables to import competition too early and excessively

Large reservoir of “excess labor” helps, but only conditionally

SGP

HKG

USAUKM

SWENLDDNKFRA

ITAJPNESP

ARG

TWN

VEN

ZAF

MUS

KOR

CHL

MEX

BRA

MYSCRI

COLPER

BOL

PHL

TUR

NGA

IDN

ZMB

CHN

THA

GHA

SEN

IND

KEN

MWI

ETH

-.08

-.06

-.04

-.02

0

.02

Com

pon

en

t plu

s r

esid

ual

0 .2 .4 .6 .8 1Labor share of agriculture, 1990

SGP

HKG

USAUKM

SWE

NLD

DNK

FRA

ITA

JPN

ESPARG

VEN

ZAF

MUS

KOR

CHL

MEX

BRAMYS

CRI

COL

PER

BOLPHL

TUR

NGA

IDN

ZMB

CHN

THA

GHA

SEN

IND

KEN

MWIETH

-.04

-.02

0

.02

.04

Com

pon

en

t plu

s r

esid

ual

0 .2 .4 .6 .8 1Labor share of agriculture, 1990

Association between the initial labor share in agriculture and the contribution

of structural change to growth

unconditional conditional

Comparative advantage in primary products is bad news

JPN

HKG

KOR

ITASWETWN

UKMUSASGP

PHL

TUR

CHN

ESPFRA

IND

MUS

THA

MEX

MYSDNKNLD

ZAF

BRA

SEN

KENCRI

IDNETH

COLARG

GHA

PERCHL

BOL

ZMB

MWI

VEN

NGA

-.1

-.08

-.06

-.04

-.02

0

Com

pon

en

t plu

s r

esid

ual

0 .2 .4 .6 .8 1index_exp_rawmat

Partial association between the share of primary products in

exports and the contribution of structural change to growth

But policy can clearly help: currency undervaluation

JPN

DNK

SWE

NLDFRA

UKM

ITA

NGA

ESP

USA

ZMB

MEX

TWN

SGP

KOR

HKGTURPER

ARG

SEN

VEN

BRA

CRIZAF

BOL

KEN

GHA

CHL

MWI

MYSCOL

THA

ETH

PHL

CHN

IDN

IND

MUS

-.06

-.04

-.02

0

.02

Com

pon

en

t plu

s r

esid

ual

-1 -.5 0 .5 1underval

Partial association between an index of currency “undervaluation”

and the contribution of structural change to growth

But policy can clearly help: labor market rigidity

Partial association between an index of labor market rigidity and

the contribution of structural change to growth

HKG

USA

SGP DNK

NGA

UKM

MYS

COL

THA

JPN

KEN

MUSCHL

MWI

ARG

ZMB

GHA

ETH

PHLINDCHN

ZAFTUR

SWE

KOR

ITA

PER

CRI

IDN

MEX

NLD

BRAESP

FRA

SEN

VEN

BOL

-.06

-.04

-.02

0

.02

Com

pon

en

t plu

s r

esid

ual

0 .2 .4 .6 .8Employment rigidity index (0=less rigid, 1=more rigid)

Conclusions

• The presence of a large convergence gap ensures significant potential for rapid economic growth in developing world, regardless of what happens in the rich countries

• Fulfilling this potential requires ongoing process of diversification and structural change– towards industries that are higher productivity and on the automatic

escalator up

• This process is not automatic, especially in countries with an initial comparative advantage in primary products

Documents

Economic structure, growth, and convergence