Benchmarking Financial Development Around the...

Benchmarking Financial Development Around the World

January 11, 2012

Global Financial Development Report 2013 GFDR Seminar

• There is evidence that financial development has a causal impact on economic growth and a reduction in income inequality…

Introduction: why measure financial development? Introduction The 4x2 Framework Practical Uses Conclusion

ARG

AUS

AUT

BELBGD

BOL

BRA

CAN

CHE

CHL

CIV

CMR

COLCRIDNK

DOM

ECU

EGYESP

ETH

FIN FRA

GBR

GHA

GRC

GTMHKG

HND

HUN IDNIND

IRL

IRN

ITA

JAMJOR

JPN

KORLKA

LSO

LUX

MDG MEX

MUS

MYS

NER

NGA

NLD

NOR

NPL

NZL

PAK

PAN

PER

PHL

PRT

ROM

SEN

SGP

SLE

SLV

SWE

THATTO

TUN

TURTZA

UGA

URY USAVEN

ZMB

-0.03

-0.02

-0.01

0

0.01

0.02

0.03

-3 -2 -1 0 1 2

Change in Gini coefficient

Private credit to GDP

Source: Update on Beck, Demirgüç-Kunt, and Levine (2007). Note: Gini coefficient is on a scale from 0 (total equality) to 1 (maximum inequality). The chart is a partial scatter plot, visually representing the regression of changes in the Gini coefficient between 1960 and 2005 on the private sector credit to GDP ratio (logarithm, 1960-2005 average), controlling for the initial (1960) Gini coefficient. Variables on both axes are residuals.


• … and financial development has been far from evenly distributed …

Note: For illustration purposes only. Country sizes adjusted to reflect volume of financial sector assets in the jurisdiction. Authors’ estimates.

• But measuring financial development properly is a challenge (Levine, 2005) – Narrow indicators (private sector credit/GDP) are only proxies; do not capture other

features of financial development (access, efficiency, stability) and are too bank-centric

– Data spread over a number of databases, each with different gaps (tradeoff: more sophisticated measures usually available only for a sub-set of countries)

• Addressing this is important because it allows us to answer questions such as: – How do regions and countries stack up in terms of financial development?

– What are the key trends?

– Are there any surprises or new developments?

– What has been the effect of the financial crisis so far?

• Global Financial Development Database – Puts together and makes financial development data publicly available under one umbrella

– Extensive cleaning–up and updating of data series, going back to underlying sources

– Presentation of the data in a comprehensive framework

• To be made publicly available, together with the GFDR – The first GFDR (2013) to be launched in September; to be linked with Open Data


• Financial Structure Database (Beck, Demirguc-Kunt, and Levine) – Pioneering financial indicator database, started in 1999, regularly updated

– Global panel data of 30+ financial indicators from various sources

– Publicly available, with a focus on a research audience

– Will be folded into the Global Financial Development Database

• FinStats (Feyen, Kibuuka, Ren, Sourrouille, Al-Hussainy, Coppola) – Internal, Excel-based tool and database launched in 2009 and annually updated

– Draws on work done for the Financial Structure Database

– Support technical analysis of World Bank/IMF staff such as FSAPs – 500 internal users

– Build charts and tables for 40+ financial indicators; statistical benchmarking of indicators

• Other specialized financial datasets/measurement initiatives, e.g.: – Financial Soundness Indicators (http://fsi.imf.org/)

– Financial Access Survey (http://fas.imf.org/)

– World Economic Forum – Financial Development Report

Relationship with other data/measurement efforts Introduction The 4x2 Framework Practical Uses Conclusion

http://fsi.imf.org/�

http://fas.imf.org/�

• One-stop, cleaned database that – builds on previous efforts (data collection, tools)

– is for public consumption

– companion to the GFDR

– aims to reach a wide policy and research audience

• Defines a comprehensive yet relatively simple conceptual framework to measure financial development – 4x2 framework

– Indicator selection by bin

– Transparent adjustment of the data to allow for benchmarking

So what’s new? Introduction The 4x2 Framework Practical Uses Conclusion

Financial development outcomes (four empirical proxies) - Depth - Access - Efficiency - Stability

Financial sector policies (examples) - Regulation (micro- and macro-prudential, business conduct, etc.) - Direct interventions (state ownership, guarantees, subsidies, liquidity provision) - Competition policy in finance (level playing field, entry/exit, etc.) - Promotion of financial infrastructure / technology

Other policies and features (examples) - Macroeconomic policy framework (e.g., exchange rate regime, monetary policy, tax policy, capital controls) - Legal framework; social capital, etc. - Concentration in the system - Internationalization; dollarization

Financial Development

Enabling Environment

Financial sector functions (theoretical concept – Levine, 2005) Producing information about investments and allocating capital; Monitoring investments and exerting corporate governance; Managing risks; Pooling savings; and Easing the exchange of goods and services

The concept of financial development Introduction The 4x2 Framework Practical Uses Conclusion

For financial institutions and markets -> “the 4x2 framework”

… each to be addressed in one chapter of the forthcoming 2013 GFDR

• The 4x2 dimensions: based on comprehensive lit. review

• Basic principles : – Keep it transparent / easy to explain

– Careful about ‘mesh-ups’ and ‘rankings‘!

• Choice of variables within each “bin” – Some variables are additive (e.g., assets of banks and non-bank financial institutions, values

of different types of outstanding securities) – are added up

– When several competitive variables, pick one rather than “meshing up”

– Strong preference for variables that are (i) solidly grounded in the literature and (ii) available for a large number of countries.

– But we keep all the candidate variables in the database so that users can do their own

• For benchmarking, we do two simple but key adjustments: – Winsorizing (truncating top and bottom 5% to cut out extreme/idiosyncratic observations)

– Rescaling from 0 (‘lowest’) to 100 (‘highest’), but no ‘ranking’

Key features of the benchmarking approach Introduction The 4x2 Framework Practical Uses Conclusion

Stylized 4x2 matrix of financial development Introduction The 4x2 Framework Practical Uses Conclusion

FINANCIAL INSTITUTIONS FINANCIAL MARKETS

DEP

TH

Private sector credit (% GDP) Banking assets to GDP Non-bank financial institutions’ assets to GDP

Stock market capitalization plus outstanding domestic private debt securities (% of GDP)

ACC

ESS

Bank branches (per 100,000 adults) Bank accounts (per 1,000 adults) % of firms with line of credit (all firms) % of firms with line of credit (small firms)

Percent market capitalization outside of top 10 largest companies Percent value traded outside of top 10 traded companies

EFFI

CIE

NC

Y

Overhead costs (% of total assets) Net interest margin, lending-deposit spread Non-interest income to total income H-statistics, Lerner index Boone indicator Distance from efficiency frontier

Turnover ratio (turnover/capitalization in the stock market) Bid-ask spread (in the bond market) Synchronicity Price impact

STAB

ILIT

Y

z-score (weighted average) Distance-to-default Excessive credit growth / real credit decline Capital to assets, nonperforming loans to total loans Capital ratios, nonperforming loan ratios Loan/deposit ratios, wholesale funding ratios

Volatility (standard deviation / average)

Other variables (also in the database): ownership of financial institutions, structure (H-statistics etc), measures of internationalization, features of the regulatory and institutional framework

(with examples of variables in each “bin”)

• Metadata are a key part of the effort! – Series accompanied by detailed descriptions (underlying calculation methodology, original source)

• Combination of sources, including:

Where are all the data coming from? Introduction The 4x2 Framework Practical Uses Conclusion

Source Which part ?

WB Database on Financial Development and Structure basic aggregate indicators

Calculations on Bankscope by Bureau van Dijk individual bank data used to calculate country aggregates for banking sector

Calculations on Bloomberg, Dealogic, and Thomson Reuters Datastream

higher frequency data on stock exchange and bond markets

Calculations on BIS statistics aggregate data on bond statistics

WB’s Doing Business database institutional variables

IMF’s access to finance database financial access

IMF’s financial stability indicators cross-referred (but coverage limited and does not include z-score)

WB Banking Regulation and Supervision Survey regulatory framework data

Financial development: summary Financial development: summary (2009/latest) Introduction The 4x2 Framework Practical Uses Conclusion

Financial Institutions: Depth: Private Credit / GDP (%); Access: Number of Branches Per 100,000 Adults, Commercial Banks; Efficiency: Inverse of Overhead Costs / Total Assets (%); Stability: Z Score – Weighted Average Commercial Banks. Financial Markets: Depth: (Stock Market Capitalization + Outstanding Domestic Private Debt Securities)/GDP Access: Percent Market Capitalization Out of the Top 10 Largest Companies (%);. Efficiency: Stock Market Turnover Ratio (%); Stability: Inverse of Asset Price Volatility.

Financial development: summary Financial development: summary (changes since 2000) Introduction The 4x2 Framework Practical Uses Conclusion

Financial Institutions: Depth: Private Credit / GDP (%); Access: Number of Branches Per 100,000 Adults, Commercial Banks; Efficiency: Inverse of Overhead Costs / Total Assets (%); Stability: Z Score – Weighted Average Commercial Banks. Financial Markets: Depth: (Stock Market Capitalization + Outstanding Domestic Private Debt Securities)/GDP Access: Percent Market Capitalization Out of the Top 10 Largest Companies (%);. Efficiency: Stock Market Turnover Ratio (%); Stability: Inverse of Asset Price Volatility.

Notes: Financial Institutions: Depth: Private Credit / GDP (%); Access: Number of Branches Per 100,000 Adults, Commercial Banks; Efficiency: Overhead Costs / Total Assets (%); Stability: Z Score – Weighted Average Commercial Banks.

Financial institutions development, by income level

Depth

Access

Efficiency

Stability

25

50

75

100

High Income Low IncomeLower Middle Income Upper Middle Income

Center is at 0

Introduction The 4x2 Framework Practical Uses Conclusion


Financial institutions development, by region Introduction The 4x2 Framework Practical Uses Conclusion

Depth

Access

Efficiency

Stability

25

50

75

100

East Asia & Pacific Europe & Central AsiaHigh Income Latin America & The CaribbeanMiddle East & North Africa South AsiaSubsaharan Africa

Center is at 0


Financial institutions development, by region

020

4060

8010

0

Depth Access Efficiency Stability

East Asia & Pacific Europe & Central AsiaHigh Income Latin America & CaribbeanMiddle East & North Africa South AsiaSub-Saharan Africa


Financial markets development, by region

Financial Markets: Depth: (Stock Market Capitalization + Outstanding Domestic Private Debt Securities)/GDP Access: Percent Market Capitalization Out of the Top 10 Largest Companies (%);. Efficiency: Stock Market Turnover Ratio (%); Stability: Asset Price Volatility.

020

4060

80


East Asia & Pacific Europe & Central AsiaHigh Income Latin America & CaribbeanMiddle East & North Africa South AsiaSub-Saharan Africa


0

25

50

75

100Depth

Efficiency

Stability

Access

High GOB Share Low GOB Share

Source: GFDR Financial Benchmarking Database, BRSS (The World Bank). Elaboration: GFDR Team.

Illustration: financial development and government Introduction The 4x2 Framework Practical Uses Conclusion

Industrial Countries Developing Countries

Source: GFDR Financial Benchmarking Database, BRSS (The World Bank). Elaboration: GFDR Team.

0

25

50

75

100Depth

Efficiency

Stability

Access


0

25

50

75

100Depth

Efficiency

Stability

Access


Illustration: financial development and government Introduction The 4x2 Framework Practical Uses Conclusion

Financial institutions development, country by country

Notes: All charts are calculated using 2009’s values. If data is not available for 2009, missing values are replaced using 2008’s figures. A 90% winsorization is applied to all variables.

ARE

AUSAUT

BEL

BHRBHS

BRB

BRN

CANCHE CYP

CZE

DEUDNK ESP

ESTFIN

FRAGBR

GNQ

GRC

HKG

HRVHUN

IRL

ISR

ITAJPNKOR

KWT

LUX

MAC

MLTNLDNZL

OMN POL

PRT

QATSAU

SGP

SVK

SVN

SWE

TTO

USA

BDIBENBFA

BGD

CAFERI

ETH GMB

GNB

HTI

KENKHM

LBR

MDGMLI

MMR

MOZ

MWINER

NPL

SLETCD

TGOTZA

UGAZAR

AGO ARM

BLZ

BOLBTN

CIVCMR

COG

CPV

DJIEGY

FSM

GEOGHAGTM

GUYHND

IDN

IND

LAO

LKA

LSO

MAR

MDA

MNG

NGANIC

PAKPHL

PNGPRY

SDN

SEN

SLV

SWZSYR

UKR

VNM

VUT

WSM

YEMZMB

ALB

ARGAZE

BGR

BIH

BLR

BRA

BWA

CHL

CHN

COL

CRI

DMA

DOMDZA

ECU

GAB

GRD

JAM

JOR

KAZ

KNA

LBN

LBY

LCA

LTU

LVAMDV

MEX

MKD

MUS

MYS

NAM

PAN

PER

ROMRUSSRBSUR

SYC

THA

TUN

TUR

URY

VCT

VEN

ZAF

050

100

Priv

ate

Cre

dit t

o G

DP

(%)

0 2 4 6 8 10Bank Overhead Costs to Total Assets

High Income Low Income Lower Middle Income Upper Middle Income

*Indicates a significant correlation coefficient at the 5% level or better

Correlation=-0.56*Depth vs Efficiency

ARE

AUSAUT

BEL

CAN CHE

CZE

DEU DNKESP

ESTFIN

FRAGBR

GNQ

GRC

HKG

HUN

IRL

ISR

ITAJPN KOR

LUX

MAC

MLTNLD NZL

OMN POL

PRT

QATSAU

SGP

USA

BGD

CAF

COMETH

HTI

KENKHM

MDG

MOZ

SLETCD

TGOTZA

UGA

AGO ARM

BLZ

CMRCOG

GEOGHA GTM

GUY

IDN

IND

LAOLSO

MAR

MDA

MNG

PAKPHL

PNGSLB

STP

SWZ

TON

UKR

VNM

YEM

ALB

ARG

ATG

AZE

BGR

BLR

BRA

BWA

CHL

DMA

DZAGAB

GRD

IRNJAM

JOR

KAZ

KNA

LBN

LBY

LCA

LTU

LVAMDV

MEX

MKD

MUS

MYS

NAM

PER

SRB

SYC

THA

TUN

TUR

URY

VCT

ZAF

050

100

Priv

ate

Cre

dit t

o G

DP

(%)

0 10 20 30 40 50Number of Branches Per 100,000 Adults, Commercial Banks



Correlation=0.63*Depth vs Access




ABW

ARE

AUSAUT

BEL

BHRBHS

BRB

BRN

CANCHE CYP

CZE

DEUDNK ESP

ESTFIN

FRAGBR

GNQ

GRC

HKG

HRVHUN

IRL

ISR

ITAJPN KOR

KWT

LUX

MAC

MLTNLDNZL

OMNPOL

PRT

QATSAU

SGP

SVK

SVN

SWE

TTO

USA

BDI BENBFA

BGD

CAFERI

ETHGMB

GNB

HTI

KENKHM

LBR

MDGMLI

MMR

MOZ

MWINER

NPL

SLETCD

TGOTZA

UGAZAR

AGOARM

BLZ

BOLBTN

CIVCMR

COG

CPV

DJI

EGY

FJI

FSM

GEOGHAGTM

GUYHND

IDN

IND

LAO

LKA

LSO

MAR

MDA

MNG

NGANIC

PAK

PHLPNG

PRY

SDN

SEN

SLV

STP

SWZSYR

UKR

VNM

VUT

WSM

YEMZMB

ALB

ARG

ATG

AZE

BGR

BIH

BLR

BRA

BWA

CHL

CHN

COL

CRI

DMA

DOMDZA

ECU

GAB

GRD

IRNJAM

JOR

KAZ

KNA

LBN

LBY

LCA

LTU

LVAMDV

MEX

MKD

MUS

MYS

NAM

PAN

PER

ROMRUS SRBSUR

SYC

THA

TUN

TUR

URY

VCT

VEN

ZAF

050

100

Priv

ate

Cre

dit t

o G

DP

(%)

0 50 100 150Z-Score - Weighted Average Commercial Bank


Correlation=-0.11Depth vs Stability

ARE

AUS

AUT

BEL

CAN

CHE

CZE

DEU

DNK

ESP

EST

FIN

FRA

GBR

GNQ

GRC

HKG

HUN

IRLISL

ISR

ITA

JPN

KOR

LUX

MAC

MLT

NLD

NOR

NZL

OMN

POL

PRT

QAT

SAUSGP

USA

BGD

CAFETHHTI

KENKGZ

KHMMDG

MOZ RWA SLETCD

TGOTZA UGA

AGO

ARM

BLZ

CMR COGGEO GHA

GTM

GUYIDN

IND

LAO LSO

MAR

MDA

MNG

MRT

PAK PHL

PNG

SWZUKR UZBVNM

YEM

ALB

ARG

AZE

BGR

BLR

BRA

BWA

CHLDMA

DZA GAB

GRD

JAM

JOR

KAZ

KNA

LBN

LBY

LCA

LTU

LVA

MDVMEX

MKD

MUS

MYS

NAMPERSRB

SYC

THA

TUNTUR

URY

VCT

ZAF

010

2030

4050

Num

ber o

f Bra

nche

s Pe

r 100

,000

Adu

lts, C

omm

erci

al B

anks




Correlation=-0.41*Access vs Efficiency




ADO

ARE

AUSAUT

BEL

BHR

BHS

BMU

BRB

BRN

CAN

CHECYM

CYPCZE

DEUDNK

ESP

EST

FIN

FRA

GBR GNQGRC

HKG

HRV

HUN

IRLISL

ISR

ITAJPN

KOR

KWTLUXMAC

MLT

NLD

NORNZL

OMN POLPRT

QAT

SAU

SGP

SMR

SVK

SVNSWE

TTOUSAVIR

AFG

BDIBEN

BFA

BGD

CAF

ERI

ETH

GINGMB

GNB

HTI

KEN

KGZ

KHM

LBR

MDGMLI

MMR

MOZ

MWI

NER

NPL

RWASLE

TCDTGOTJK

TZA

UGAZAR

AGO ARM

BLZ

BOL

BTN

CIV

CMR

COG

CPVDJI

EGY

FSM

GEO

GHAGTM

GUY

HND

IDN

IND

IRQ

LAO

LKA

LSOMAR

MDA

MNG

MRT

NGANIC

PAKPHL

PNG

PRY

SDN

SEN

SLV

SWZ

SYR

TKM

UKR

UZBVNM

VUT

WSM

YEM

ZMB

ALB ARG

AZEBGR

BIH BLR

BRA

BWA CHL

CHN

COL

CRICUB

DMA

DOM

DZA

ECU

GABGRD

JAM

JOR

KAZKNA

LBN

LBY

LCA

LTULVAMDV

MEXMKDMNEMUS

MYS

NAM

PAN

PER

ROMRUS

SRBSUR

SYC

THA

TUN

TUR

URYVCT

VEN

ZAF

050

100

150

Z-S

core

- W

eigh

ted

Ave

rage

Com

mer

cial

Ban

k



Correlation=0.01Efficiency vs Stability

ARE

AUSAUT

BEL

CAN

CHE

CZE

DEUDNK

ESP

EST

FIN

FRA

GBRGNQGRC

HKGHUN

IRLISL

ISR

ITAJPN

KOR

LUXMAC

MLT

NLD

NORNZL

OMN POL PRT

QAT

SAU

SGP

USABGD

CAF

ETH

HTI

KEN

KGZ

KHMMDG

MOZ

RWASLE

TCD TGO

TZA

UGAAGO ARM

BLZ

CMR

COGGEO

GHAGTM

GUY

IDN

IND

LAO

LSOMAR

MDA

MNG

MRT

PAKPHL

PNG

STP

SWZ

UKR

UZBVNM

YEMALBARG

ATG

AZEBGR

BLR

BRA

BWA CHLDMA

DZAGAB

GRD

IRN

JAM

JOR

KAZKNA

LBN

LBY

LCA

LTU LVAMDV

MEXMKD

MUS

MYS

NAM

PER

SRB

SYC

THA

TUN

TUR

URY VCT

ZAF

050

100

150

Z-Sc

ore

- Wei

ghte

d Av

erag

e C

omm

erci

al B

ank

0 10 20 30 40 50Number of Branches Per 100,000 Adults, Commercial Banks


Correlation=-0.20*Access vs Stability


Correlation coefficient = 0.8607

010

020

030

040

0Do

mes

tic B

ank A

sset

s / G

DP (%

)

0 100 200 300Private Credit / GDP (%)

Correlations within the same ‘bin’ tend to be higher… Introduction The 4x2 Framework Practical Uses Conclusion

Summary across dimensions of financial development

Financial Institutions (levels in 2009)



Financial Markets (levels in 2009)



Financial Institutions (variation 2007-2009)



Financial Markets (variation 2007-2009)


Conclusion Introduction The 4x2 Framework Practical Uses Conclusion

• We build on existing databases/tools (Financial Structure, FinStats, …) – Cleaning –up , going back to underlying sources.

– Result: a comprehensive data set, to be publicly available, linked with Open Data

• We introduce the 4x2 framework (choice of vars, wisorization, rescaling) to measure differentiation and trends in financial development.

• This framework is a stepping stone for related work: – Financial sector policies need to take into account the level of economic development, as

well as the accompanying changes in financial structures.

– As economies develop, demand for the services provided by securities markets increases relative to those provided by banks, such that securities markets become increasingly important for future economic development.

• More work being done: – Measuring impact of various policies on financial development.

– Further work on sophisticated indicators for sub-goups of countries.

Additional Slides

Global Financial Development Report 2013 GFDR Seminar

Financial markets development, country by country


AUS

AUT

CAN

CHE

CYP

DEU

ESP

GBR

GRC

HKG

HUN

IRL

ISRITAJPN

KOR

LUX

MLT

NOR

NZL

POL

SAU

SGP

SVN

USA

EGY

IDN

IND

LKA

PHL

ARG

BRA

CHL

CHN

COL

IRN

JOR

MEXMUS

MYS

PERRUS THA

TUR

ZAF

050

100

150

200

(Sto

ck M

arke

t Cap

italiz

atio

n +

Out

stan

ding

Dom

estic

Priv

ate

Deb

t Sec

uriti

es)/G

DP

0 20 40 60 80Percent Market Capitalization Out of the Top 10 Largest Companies (%)



Correlation=0.43*Depth vs Access

ARE

AUS

AUT

BEL

BHR

BRB

CAN

CHE

CYP

CZE

DEU

DNKESP

EST

FIN

FRA

GBR

GRC

HKG

HRVHUN

IRL

ISLISR ITA

JPN

KOR

KWT

LUX

MLT

NLD

NOR

NZL

OMNPOL

PRT

SAU

SGP

SVK

SVN

SWE

TTO

USA

BGD

KEN

KGZ

MWINPL

ARM

CIV

EGY

FJIGEOGHA

IDN

IND

LKA

MAR

MNGNGA PAK

PHL

UKRVNMARGBGR

BRA

BWA

CHL

CHN

COL

CRI ECUIRN

JAM

JOR

KAZ

KNA

LBN

LTULVA

MEX

MKD

MUS

MYS

NAM

PAN

PER

ROM

RUS

SRB

THA

TUN

TUR

ZAF

050

100

150

200

(Sto

ck M

arke

t Cap

italiz

atio

n +

Out

stan

ding

Dom

estic

Priv

ate

Deb

t Sec

uriti

es)/G

DP

0 50 100 150 200Stock Market Turnover Ratio (%)



Correlation=0.45*Depth vs Efficiency

Introduction The 4x2 Framework Practical Uses Conclusion Additional Slides



ARE

AUS

BEL

BHR

CAN

CHE

CYP

CZE

DEU

DNKESP

EST

FIN

FRA

GBR

GRC

HKG

HRVHUN

IRL

ISLISR ITA

JPN

KOR

KWT

LUX

MLT

NLD

NOR

NZL

OMNPOL

PRT

SAU

SGP

SVK

SVN

SWE

USA

KEN

TZA

EGY

IDN

IND

LKA

MAR

MNGNGA PAK

PHL

UKRVNM ARGBGR

BRA

BWA

CHL

CHN

COL

CRI

JAM

JOR

KAZ

LBN

LTULVA

MEX

MKD

MUS

MYS

NAM

PAN

PER

ROM

RUS

SRB

THA

TUN

TUR

VEN

ZAF

050

100

150

200

(Sto

ck M

arke

t Cap

italiz

atio

n +

Out

stan

ding

Dom

estic

Priv

ate

Deb

t Sec

uriti

es)/G

DP

10 20 30 40 50 60Asset Price Volatility


Correlation=0.20Depth vs Stability

AUS

AUT

CAN

CHE

CYP

DEU

ESPGBR

GRC

HKG

HUN

IRL

ISR

ITA

JPN

KOR

LUXMLT

NOR

NZLPOL SAU

SGP

SVN

USA

EGY

IDN

IND

LKAPHL

ARG

BRA

CHL

CHN

COL

IRN

JOR

MEXMUS

MYS

PER RUS

THATUR

ZAF

020

4060

80P

erce

nt M

arke

t Cap

italiz

atio

n O

ut o

f the

Top

10

Larg

est C

ompa

nies

(%)

0 50 100 150 200Stock Market Turnover Ratio (%)



Correlation=0.56*Access vs Efficiency




ARE

AUS

BEL

BHR

CANCHE

CYP

CZE

DEU

DNK

ESP

EST

FINFRA

GBR

GRCHKG

HRV

HUN

IRL

ISL

ISR

ITA

JPN

KOR

KWT

LUXMLT

NLDNOR

NZL

OMN

POLPRT

QAT

SAU

SGP

SVKSVN

SWE

USA

KEN

EGY

IDN

IND

LKA

MAR

MNGNGA

PAK

PHL

UKR

VNM

ARGBGR

BRA

BWA

CHL

CHN

COLCRIJAM

JOR

KAZLBN LTULVA

MEX

MKDMUS

MYS

NAMPAN PERROM

RUS

SRB

THA

TUN

TUR

ZAF

050

100

150

200

Sto

ck M

arke

t Tur

nove

r Rat

io (%

)10 20 30 40 50 60

Asset Price Volatility



Correlation=0.38*Efficiency vs Stability

AUS

CAN

CHE

CYP

DEU

ESPGBR

GRC

HKG

HUN

IRL

ISR

ITA

JPN

KOR

LUXMLT

NOR

NZL POLSAU

SGP

SVN

USA

EGY

IDN

IND

LKAPHL

ARG

BRA

CHL

CHN

COLJOR

MEXMUS

MYS

PERRUS

THATUR

ZAF

020

4060

80P

erce

nt M

arke

t Cap

italiz

atio

n of

Top

10

Larg

est C

ompa

nies

(%)

10 20 30 40 50 60Asset Price Volatility


Correlation=-0.02Access vs Stability


Correlation matrix

FINANCIAL INSTITUTIONS DEPTH ACCESS EFFICIENCY STABILITY

DEPTH Private Credit to GDP (%)

1

ACCESS Number of Branches Per 100,000 Adults, Commercial Banks

0.63* 1

EFFICIENCY Bank Overhead Costs to Total Assets

-0.56* -0.41* 1

STABILITY Z-Score - Weighted Average Commercial Bank

-0.11 -0.20* 0.01 1

FINANCIAL MARKETS DEPTH ACCESS EFFICIENCY STABILITY

DEPTH (Stock Mkt Cap. + Outstanding Dom. Priv. Debt Secur.)/GDP

1

ACCESS % Market Cap. Out of the Top 10 Largest Companies (%)

0.43* 1

EFFICIENCY Stock Market Turnover Ratio (%)

0.45* 0.56* 1

STABILITY Asset Price Volatility

0.20 -0.02 0.38* 1

* Indicates a significant correlation coefficient at the 5% level or better.


Correlation matrix

FINANCIAL INSTITUTIONS

DEPTH ACCESS EFFICIENCY STABILITY

Private Credit to GDP (%)

Domestic Banks

Assets to GDP (%)

# of Branches

Per 100,000

Adults, CB

Account Per

Thousand Adults, CB

Bank Overhead Costs to

Total Assets

Net Interest

Margin (%)

Z-Score Weighted Average Comm.

Bank

(NPLs to Total Gross Loans (%) +

Bank Capital to

Assets (%)) / 2

DEP

TH Private Credit to GDP (%) 1

Domestic Banks Assets to GDP (%) 0.84* 1

ACCE

SS Number of Branches Per 100,000 Adults, Comm. Banks

0.63* 0.60* 1

Account Per Thousand Adults, Comm. Banks 0.80* 0.66* 0.55* 1

EFFI

CIEN

CY

Bank Overhead Costs to Total Assets -0.56* -0.56* -0.41* -0.42* 1

Net Interest Margin (%) -0.59* -0.56* -0.50* -0.47* 0.64* 1

STA

BILI

TY

Z-Score - Weighted Average Commercial Bank -0.11 -0.06 -0.20* -0.14 0.01 0.12 1

(NPLs to Total Gross Loans (%) + Bank Capital to Assets (%)) / 2 -0.21* -0.22* -0.20 -0.05 0.22* 0.36* 0.14 1



Correlation matrix

FINANCIAL MARKETS

DEPTH ACCESS EFFICIENCY STABILITY

(Stock Mkt. Cap. +

Outstanding Dom. Priv.

Debt Securities) /

GDP

Stock Market Total Value Traded to GDP (%)

Percent Market Cap. Out of the

Top 10 Largest

Companies (%)

Corporate to Total Bond and Notes

Outstanding

Stock Market Turnover Ratio (%)

Asset Price Volatility

DEP

TH

(Stock Market Capitalization + Outstanding Domestic Private Debt Securities)/GDP 1

Stock Market Total Value Traded to GDP (%) 0.67* 1

ACC

ESS

Percent Market Capitalization Out of the Top 10 Largest Companies (%) 0.43* 0.46* 1

Corporate to Total Bond and Notes Outstanding 0.50* 0.53* 0.17 1

EFF.

Stock Market Turnover Ratio (%) 0.45* 0.76* 0.56* 0.16 1

STA

B.

Asset Price Volatility 0.20 0.28* -0.02 0.11 0.38* 1



Financial market development, by region


Depth

Access

Efficiency

Stability

25

50

75

100

East Asia & Pacific Europe & Central AsiaHigh Income Latin America & The CaribbeanMiddle East & North Africa South AsiaSubsaharan Africa

Center is at 0



Financial institutions development, by income level

020

4060

80


High Income Low incomeLower middle income Upper middle income


Financial markets development, by income level


020

4060

80


High Income Lower middle incomeUpper middle income


Financial markets development, by income level


Depth

Access

Efficiency

Stability

25

50

75

100

High Income Low IncomeLlower Middle Income Upper Middle Income

Center is at 0


Benchmarking Financial Development Around the...

Documents

Transcript of Benchmarking Financial Development Around the...