Valuation and Segmentation in Emerging Markets Geert Bekaert, Columbia + NBER Campbell R. Harvey, Duke + NBER Christian T. Lundblad, UNC Stephan Siegel,

Valuation and Segmentation in Emerging

MarketsGeert Bekaert, Columbia + NBER

Campbell R. Harvey, Duke + NBERChristian T. Lundblad, UNC

Stephan Siegel, U. of Washington

May 16, 2008

• Why has globalization treated some countries better

than others?• What drives valuation differentials?• Can we characterize the types of policies that change

the degree of segmentation – both across countries and through time?

`

I. The Setting

1. Segmentation

2. Valuation`

II. The Plan

6

Two aspects of (de jure) globalization

Economic Integration: Trade Liberalization Indicator

[Wacziarg and Welch (2004)]

Financial Integration: Capital Account Openness Index

[Quinn and Toyoda (2001)]

Equity Market Openness [Bekaert and Harvey

(2000)]

III. Openness

7

0.0

0.2

0.4

0.6

0.8

1.0

Open Capital Account

Investable Equity

Trade Openness

Open Equity Market

III. Openness

Trade and Financial Openness Have Increased

8

Globalization may have wide-ranging effects:

Expected Returns, Correlation and Volatility [International Finance]

Consumption Risk Sharing, Efficacy of Macroeconomic Policy[International Economics]

Investment, Economic Growth[Development Economics]

Our Focus: Effects on Stock Valuation

III. Openness

9

Equity Returns

Cash Flows

Discount Rates

Real Rates

Term Premiums

Equity risk premiums

Bond Returns

Inflation Economic Integration

Economic Integration:• Specialization• Exposure to world shocks

Financial Integration

III. Openness

10

Building on Bekaert, Harvey, Lundblad, Siegel (BHLS) (JF - June 2007), develop a measure of the degree of effective market segmentation

Measurement: De Jure Openness ≠ De Facto Integration• Liberalization process is gradual and complex• Capital controls may not have been effective• Liberalization may not be credible• Indirect access may already exist

Other factors may “segment” markets:• political risk• corporate governance issues• liquidity / financial development• domestic product and labor markets• “push” factors

Literature: Bekaert (1995), Bekaert and Harvey (1995), Nishiotis (2004), Aizenman and Noy (2005), Lane and Milesi-Ferretti (2001)

1

III. Four Contributions

11

• Combining real and financial variables to construct a new measure of exogenous growth opportunities

• On average, countries align realized future growth with available (exogenous) opportunities

countries with open equity markets and banking sectors are the most successful at exploiting available growth opportunities

financial development and investor protection are also important, but to a lesser degree

• Degree of integration / segmentation (as inferred from growth predictability regressions) depends on country characteristics and varies over time.

This paper develops a direct measure of segmentation and explores its determinants


12

Has the degree of segmentation decreased over time? What was the role of (de jure) globalization?

Literature:– Return comovements: Longin and Solnik (1995);

Bekaert, Hodrick, and Zhang (2007)– Factor Beta Models: Bekaert and Harvey (1997, JFE);

Ng (2000, JIMF); Fratzscher (2002, IJFE); Baele (2005, JFQA); Carrieri, Errunza, and Hogan (forthcoming, JFQA)

– Return and volatility distance: Eun and Lee (2005)– Effects of stock market liberalization on dividend

yields: Bekaert and Harvey (2000), Henry (2000)

2


13

Identify factors that determine the cross-sectional and time-series variation in segmentation:

Is de jure globalization first order?What is the impact of local institutions?

Literature: - Bhojraj and Ng (2007)- Hail and Leuz (2006)

3


14

Related issues:

Investigate industry-specific degrees of segmentation

“Segmentation” within the U.S.

“Segmentation” within the EU

4


15

IV. A Measure of Market Segmentation

Strong Concept of Market Integration:

• Industries have identical systematic risk across the globe

• Priced growth opportunities are global in nature

• Identical financial risk for each industry, independent of the country

• Constant real interest rates Each assumption relaxed later in our

analysis

16


Assume each country i is a basket of industries with industry weights IWi,j,t

Let EYi,j,t = earnings yields for country i, industry j

Valuation Differential: |EYi,j,t- EYw,j,t|(small and constant under strong market integration)

Measure a country’s degree of observed segmentation:

, , , , , , ,1

= | |

N

i t i j t i j t w j tj

SEG IW EY EY

17


EYi,j,tEMDB: 28 countriesDataStream: 22 countries

DataStream

EMDB: 28 countriesDataStream: 22 countries

12 month trailing earnings yield,negative yields set to zero

12 month global trailing earnings yield, negative yields set to zero(also considered U.S.)Industry MCAP share in local market

EYw,j,t

IWi,j,t

Construct SEG for 50 Countries between 1973 and 2005

18


Country Sample Average St. Dev.

Year of first

observation

Average segmenation over first five

years

Average segmentation2001 - 2005

Change in segmentation

ARG EM 5.3% 5.2% 1988 9.5% 4.9% -48.4%CHN EM 2.3% 1.0% 1995 2.6% 2.1% -18.1%DEU DEV 2.1% 1.0% 1980 3.2% 2.4% -25.7%GBR DEV 1.9% 1.2% 1980 4.2% 1.2% -72.8%IND EM 3.2% 1.4% 1988 3.2% 2.7% -13.8%MEX EM 3.5% 3.6% 1988 5.8% 2.3% -61.0%PHL EM 2.9% 0.9% 1990 3.4% 2.5% -26.0%USA DEV 0.7% 0.2% 1980 0.6% 0.8% 23.6%VEN EM 6.8% 4.8% 1988 6.4% 10.0% 55.0%

Averages of country-level data

DEV 2.7% 1.5% 1982 4.5% 1.9% -45.0%EM 4.4% 2.6% 1991 5.8% 3.9% -20.1%

ALL 3.8% 2.2% 1988 5.3% 3.1% -29.6%

Segmentation Segmentation over time

19


Industry Average St. Dev.

Average segmentatio

n 1980 - 1984

Average segmentatio

n2001 - 2005

Change in segmentatio

n

Rank based on average

segmentation 1980 - 1984

Rank based on average

segmentation 2001 - 2005

Banks 5.8% 2.9% 10.0% 3.0% -69.8% 1 33Life Insurance 5.2% 3.5% 8.5% 2.9% -65.7% 2 34General Retailers 4.2% 2.6% 8.2% 4.1% -50.4% 3 12Nonlife Insurance 5.0% 2.0% 7.6% 4.1% -46.4% 4 13Electricity 4.5% 2.0% 7.5% 3.5% -52.5% 5 25Fixed Line Telecommunications 4.2% 2.1% 7.3% 3.8% -47.7% 6 18. . . Aerospace & Defense 3.0% 1.6% 3.4% 2.5% -25.7% 33 37Support Services 3.0% 1.7% 3.0% 3.2% 6.7% 34 30Pharmaceuticals & Biotechnology 3.0% 1.2% 3.0% 3.5% 16.1% 35 26Gas, Water & Multiutilities 2.6% 1.0% 2.9% 3.7% 28.3% 36 22Household Goods 3.6% 1.4% 2.8% 3.8% 35.6% 37 17Travel & Leisure 4.1% 2.0% 2.8% 5.4% 92.4% 38 3

Average of industry-level data 4.1% 1.7% 5.1% 3.9% -14.3%

RankSegmentation Segmentation over time

20


0.0%

0.5%

1.0%

1.5%

2.0%

2.5%

3.0%

3.5%

4.0%

4.5%

1973

1974

1975

1976

1977

1978

1979

1980

1981

1982

1983

1984

1985

1986

1987

1988

1989

1990

1991

1992

1993

1994

1995

1996

1997

1998

1999

2000

2001

2002

2003

2004

2005

Average Country Effect

Average Industry Effect

Average Country and Industry Segmentation (MAD)

1973 - 2005

21

V. Market Segmentation Dynamics

SEG: Industry-weighted Valuation Differentials

0.0%

2.0%

4.0%

6.0%

8.0%

10.0%

12.0%

Emerging Markets Segmentation

Developed Countries Segmentation

Linear (Developed Countries Segmentation)

Linear (Emerging Markets Segmentation)

22



0%

2%

4%

6%

8%

10%

12%

1973

1974

1975

1976

1977

1978

1979

1980

1981

1982

1983

1984

1985

1986

1987

1988

1989

1990

1991

1992

1993

1994

1995

1996

1997

1998

1999

2000

2001

2002

2003

2004

2005

EM (Advanced) Segmentation


EM (Frontier) Segmentation

23



0%

2%

4%

6%

8%

10%

12%

14%

16%

18%

20%

1973

1974

1975

1976

1977

1978

1979

1980

1981

1982

1983

1984

1985

1986

1987

1988

1989

1990

1991

1992

1993

1994

1995

1996

1997

1998

1999

2000

2001

2002

2003

2004

2005

North America

Africa

Asia (excl. JPN)

Europe

Latin America (incl. Caribbean)

Middle East / North Africa

24


Changes over time suggest we observe valuation convergence…Explore an unbalanced panel regression with a simple time trend

Econometrics (throughout): OLS on unbalanced panels; Newey-West and SUR correction (similar to Thompson (2006))Prais-Winsten on unbalanced panel with Beck-Katz (1995) correction

All Developed Emerging

Trend -0.0007 -0.0012 -0.0012(0.0003) (0.0003) (0.0008)

R 2 0.02 0.19 0.02

Number of Countries 50 19 31

25

VI. Market Segmentation: U.S. Study

Clearly, valuation differentials may be due to other factors beyond segmentation

Within the U.S., we explore valuation differentials across industries and states to

uncover any biases in our measure of segmentation explore other explanatory factors (e.g., leverage, earnings volatility, number of firms)

Design: (a) iteratively draw N random firms (resembling countries) or (b) consider U.S. states compare to overall U.S. market

26

Segmentation across random draws of U.S. firms grouped into pseudo-’countries’


0%

2%

4%

6%

8%

10%

12%

1973

1974

1975

1976

1977

1978

1979

1980

1981

1982

1983

1984

1985

1986

1987

1988

1989

1990

1991

1992

1993

1994

1995

1996

1997

1998

1999

2000

2001

2002

2003

2004

2005

2006

Average Segmentation within U.S.

5th percentile Segmentation

95th percentile Segmentation



27

Segmentation across random draws of U.S. firms by U.S. states


0%

2%

4%

6%

8%

10%

12%

1973

1974

1975

1976

1977

1978

1979

1980

1981

1982

1983

1984

1985

1986

1987

1988

1989

1990

1991

1992

1993

1994

1995

1996

1997

1998

1999

2000

2001

2002

2003

2004

2005

2006

Average Segmentation within U.S.



28

Treating U.S. States as "Countries" I II III IV

Trend -0.0005 -0.0002 -0.0003 -0.00030.0001 0.0001 0.0001 0.0001

Number of Public Firms (log) -0.0049 -0.0046 -0.00450.0009 0.0008 0.0008

Abs. Difference in Financial Leverage (|Local - US|) 0.0234 0.0177

0.0131 0.0108

Abs. Difference in Log Earnings Growth Volatility (|Local - US|) 0.0064

0.0027

N 1,495 1,495 1,495 1,495

R 2 0.05 0.15 0.15 0.16

1973 - 2006


29

Distribution of coefficient estimates 5th 10th 50th 90th 95th

Trend -0.0002 -0.0002 -0.0001 -0.0001 -0.0001

Number of Public Firms (log) -0.0034 -0.0032 -0.0026 -0.0021 -0.0020

Abs. Difference in Financial Leverage (|Local - US|) 0.0033 0.0052 0.0220 0.0407 0.0427

Abs. Difference in Log Earnings Growth Volatility (|Local - US|) 0.0027 0.0036 0.0068 0.0108 0.0121

Distribution of t - stats 5th 10th 50th 90th 95th

Trend -6.956 -6.366 -4.427 -2.407 -0.668

Number of Public Firms (log) -12.316 -11.814 -9.329 -6.554 -4.526

Abs. Difference in Financial Leverage (|Local - US|) 0.478 0.625 2.652 4.239 7.134

Abs. Difference in Log Earnings Growth Volatility (|Local - US|) 1.517 1.749 3.222 6.036 7.709

100 Random Samples of 50 "Countries" 1973 - 2006


30

Case study: we explore the role for valuation convergence in Europe

Direct analogue:Consider trends in European valuations relative to

“core” European basket (FRA, DEU, ITA, NLD, BEL, IRL, GBR, DNK)

Reconsider de jure openness: To what degree did EU membership or the entrance of the Euro Zone facilitate our notion of strong market integration? Do these factors explain the trend?

VI. Market Segmentation in the EU

31

SEG


32


33

SEG


34

There is a significant trend towards valuation convergence in Europe. Is that explained by (de jure) EU or Euro membership?

EU membership is important, but trend persists.

(1) (2) (3) (4) (5) (6) (7)

EU Membership -1.427 -1.221 -1.127 -1.234(0.521) (0.567) (0.649) (0.660)

Euro Zone -1.243 -0.902 0.314 0.664(0.399) (0.456) (0.455) (0.363)

Trend -0.109 -0.102 -0.116 -0.117(0.028) (0.030) (0.033) (0.033)

R-squared 0.061 0.038 0.170 0.080 0.204 0.168 0.211


35

VII. Market Segmentation Dynamics

(with controls)

All Countries (1980 - 2005) I II III IV

Trend -0.0007 -0.0007 -0.0008 -0.0008(0.0003) (0.0003) (0.0002) (0.0002)

Number of Public Firms (log) -0.0073 -0.0072 -0.0058(0.0021) (0.0020) (0.0019)

0.0972 0.0564(0.0544) (0.0508)

0.1279(0.0276)

N 906 906 906 906

R 2 0.02 0.09 0.10 0.16

Abs. Difference in Financial Leverage (|Local - Global|)

Abs. Difference in Log Earnings Growth Volatility (|Local - Global|)

36

VII. Market Segmentation Dynamics:

De Jure OpennessEquity Market Openness I II III IV V

Equity Market Openness -0.0282 -0.0228 -0.0253 -0.0212(0.0070) (0.0062) (0.0063) (0.0055)

Trade Openness -0.0289 -0.0151 -0.0122 -0.0092(0.0117) (0.0116) (0.0117) (0.0107)

Trend -0.0008 -0.0009(0.0003) (0.0003)

Number of Public Firms (log) -0.0045(0.0016)

0.0339(0.0530)

0.1121(0.0277)

N 906 906 906 906 906

R 2 0.11 0.07 0.13 0.15 0.24



37

VII. Market Segmentation Dynamics:

De Jure OpennessCapital Account Openness I II III IV V

Capital Account Openness -0.0331 -0.0296 -0.0296 -0.0202(0.0086) (0.0080) (0.0083) (0.0071)

Trade Openness -0.0185 -0.0076 -0.0063 -0.0063(0.0087) (0.0091) (0.0092) (0.0072)

Trend -0.0006 -0.0007(0.0003) (0.0003)

Number of Public Firms (log) -0.0047(0.0011)

0.0478(0.0437)

0.1074

(0.0279)

N 880 880 880 880 880

R 2 0.08 0.03 0.09 0.11 0.23



38

VIII. Determinants of Market Segmentation

Benchmark: fixed effects + time dummies 42% R2

Regulatory openness: explains up to 13%

Univariate evidence suggests other factors (institutions, financial development, local market liquidity, U.S. “push” factors, etc.) are also important

Is regulatory financial openness primary?

39

Potential Variables

Lagged Dependent VariableCapital Account OpennessEquity Market OpennessTrade OpennessGross FDI/GDPTrade/GDPPolitical RiskQuality of InstitutionsInvestment ProfileLaw and OrderMinority Shareholder RightsInsider Trading LawInsider Trading ProsecutionLegal Origin (English)Legal Origin (French)Local Equity Market IlliquidityLocal Equity Market TurnoverLocal Equity Market Return AutocorrelationMYY R2 SynchronicityPrivate Credit/GDPPrivate Credit/GDP (adj.)Accounting StandardsEarnings ManagementU.S. Real RateU.S. Money Supply GrowthU.S. Risk AversionWorld GDP GrowthU.S. Corporate Default SpreadVIX Option IndexPast Local Equity Market ReturnWorld Equity Market VolatilityInitial Log GDPSecondary School EnrollmentLog Life ExpantancyPopulation GrowthPredicted Growth OpportunitiesFinancial Leverage (|Local - Global|)Local Market Earnings Growth VolatilityNumber of Public Firms (log )

examples

ConstantTrendCapital Account OpennessEquity Market OpennessTrade OpennessGross FDI/GDPTrade/GDPQuality of InstitutionsInvestment ProfileLaw and OrderInsider Trading LawInsider Trading ProsecutionLegal Origin (English)Legal Origin (French)Local Equity Market IlliquidityLocal Equity Market Turnover

MYY R2 SynchronicityPrivate Credit/GDPMCAP/GDP

Potential Variables

Lagged Dependent VariableCapital Account OpennessEquity Market OpennessTrade OpennessGross FDI/GDPTrade/GDPPolitical RiskQuality of InstitutionsInvestment ProfileLaw and OrderMinority Shareholder RightsInsider Trading LawInsider Trading ProsecutionLegal Origin (English)Legal Origin (French)Local Equity Market IlliquidityLocal Equity Market TurnoverLocal Equity Market Return AutocorrelationMYY R2 SynchronicityPrivate Credit/GDPPrivate Credit/GDP (adj.)Accounting StandardsEarnings ManagementU.S. Real RateU.S. Money Supply GrowthU.S. Risk AversionWorld GDP GrowthU.S. Corporate Default SpreadVIX Option IndexPast Local Equity Market ReturnWorld Equity Market VolatilityInitial Log GDPSecondary School EnrollmentLog Life ExpantancyPopulation GrowthPredicted Growth OpportunitiesFinancial Leverage (|Local - Global|)Local Market Earnings Growth VolatilityNumber of Public Firms (log )

G7 Real RateU.S. Money Supply GrowthU.S. Risk AversionWorld GDP GrowthU.S. Corporate Bond SpreadVIX Option Volatillity IndexPast Local Equity Market Return

World Equity Market VolatilityInitial Log GDPSecondary School EnrollmentLog Life ExpectancyPopulation GrowthAbs. Difference in Financial Leverage (|Local - Global|)Abs. Difference in Log Earnings Growth Volatility (|Local - Global|)Number of Public Firms (log)

RIS

K AP

PE

TIT

E

OP

EN

NE

SS

INS

T D

EV

FIN

D

EV

GR

OW

TH

CO

NT

RO

LS


40

Economic Effect on Market Segmentation (N= 906, R2 = 0.30)

OLS Estimate Emerging Developed

Standard Deviation of Time Series

Variation SEG

Equity Market Openness -0.0149 0.49 1.00 -0.0075Trade Openness -0.0082 0.81 1.00 -0.0016Investment Profile -0.0277 0.59 0.73 -0.0038MCAP/GDP -0.0056 0.46 0.65 -0.0010World GDP Growth 0.2315U.S. Corporate Bond Spread 2.0605 0.0048 0.0098VIX Option Volatility Index 0.0465 0.0725 0.0034Abs. Difference in Log Earnings Growth Volatility (|Local - Global|) 0.0911 0.13 0.09 -0.0035Number of Public Firms (log) -0.0042 5.47 5.89 -0.0018


41

Economic Effect on Market Segmentation (N= 880, R2 = 0.33)

OLS Estimate Emerging Developed

Standard Deviation of Time Series

Variation SEG

Capital Account Openness -0.0164 0.56 0.91 -0.0058Trade Openness -0.0014 0.84 1.00 -0.0002Investment Profile -0.0300 0.61 0.73 -0.0038

Legal Origin (French) -0.0042 0.61 0.25 0.0015MCAP/GDP -0.0054 0.48 0.65 -0.0009U.S. Money Supply Growth 0.1026 0.0355 0.0036U.S. Corporate Bond Spread 1.6139 0.0048 0.0077VIX Option Volatility Index 0.0471 0.0725 0.0034Abs. Difference in Log Earnings Growth Volatility (|Local - Global|) 0.1044 0.13 0.09 -0.0039Number of Public Firms (log) -0.0044 5.52 5.89 -0.0016


42

-0.050

0.000

0.050

0.100

0.150

0.200

0.250 Cross Section

Time-Series


43

Equity Market Capital Account

Capital Account Openness -0.0190 -0.0174(0.0061) (0.0053)

Equity Market Openness -0.0156 -0.0145(0.0048) (0.0048)

Trade Openness -0.0104 -0.0032 -0.0115 -0.0027(0.0107) (0.0077) (0.0104) (0.0073)

Investment Profile -0.0278 -0.0293 -0.0228 -0.0337(0.0074) (0.0076) (0.0115) (0.0093)

Legal Origin (French) -0.0039 -0.0042(0.0040) (0.0036)

MCAP/GDP -0.0061 -0.0061 -0.0042 -0.0041(0.0031) (0.0031) (0.0035) (0.0036)

U.S. Money Supply Growth 0.0958 -0.0173(0.0393) (0.0366)

World GDP Growth 0.2149 0.0630(0.1140) (0.1120)

U.S. Corporate Bond Spread 2.4939 2.0609 1.7539 1.7090(0.3930) (0.3010) (0.3510) (0.2600)

VIX Option Volatility Index 0.0506 0.0522 0.0153 0.0218(0.0154) (0.0110) (0.0192) (0.0143)

Abs. Difference in Log Earnings Growth Volatility (|Local - U.S.|) 0.0783 0.0808 0.0940 0.1043

(0.0251) (0.0226) (0.0316) (0.0299)

Number of Public Firms (log) -0.0042 -0.0045 -0.0045 -0.0045(0.0018) (0.0015) (0.0016) (0.0013)

Determinants relative to World Average

Equity Market Capital Account U.S. as a Benchmark


44

IX. Valuation

1) Segmentation is a measure of the absolute

difference between local and world (industry adjusted) earnings yields

2) Valuation attempts to explain the difference itself. The goal is to understand the drivers of ‘under’ and ‘over’ valuation

45

IX. Valuation

Valuation (switch to log PE ratios):

N

jtjwtjitjiti PEPEIWVAL

1,,,,,,,

46

IX. Valuation

Use some of the same variables to try to explain

variation in price to earnings ratios (both across countries and through time).

1: What explains the emerging markets discount?

47

IX Valuation

Figure 3

Emerging Market Discount (LEGO) (ex Japan)

-1

-0.8

-0.6

-0.4

-0.2

0

0.2

0.4

D I

S C

O U

N T

P R

E M

I U

M

Relative PE RatiosAve. Discount

“Emerging Market Discount”

Important factors? Financial openness, political and institutional risks, illiquid equity markets, and U.S. default premia

48

IX. Valuation

Are they driven by growth opportunities or

discount rate effects?

2: Decomposing PE Ratios

49

IX. Valuation

Are they driven by growth opportunities or

discount rate effects?


50

IX. Valuation

Empirical model for 5-year real returnsEmpirical model for 5-year real earnings growth

Project current PE on these two variables.


51

IX. Valuation

Given our model of expected (industry-adjusted) PE ratios, we can take a stand on whether a market is over or undervalued.

Trading simulations where you buy the undervalued markets and sell of the overvalued markets

3: Market Efficiency

52

Conclusions

•SementationNew price-based measure of market segmentation

Downwar trend in segmentation over time, partially explained by de jure globalization.

Identify most and least segmented industries over time.

Explain about 30% of the variation in degree of segmentation across countries and time:

Mostly from the cross-section Mainly from financial openness, financial

development, but “global risk” factors also matter

53

Conclusions

•ValuationValuation in developing markets is challenging for

investorsOur framework of industry adjusting compares

‘apples to apples’Our framework of considering the institutional

environment, the degree of openness as well as fundamental information, allows us to understand cross country differences in valuation – as well as time-series patterns.

54

Conclusions

• Why does this matter?Market segmentation and or undervaluation

raises the cost of capitalHigher cost of capital means less investment and

less employment growthLower investment and employment growth means

lower GDP growthFor example, Bekart, Harvey and Lundblad (JFE

2005) estimate that a market liberalization which reduces the cost of capital is associated with a increment in real GDP growth of 1% a year for five years

55

Supplementary Materials (not for reproduction)

57

I. Motivation and Goals

OutlineI. Motivation and GoalsII. Measure of Market SegmentationIII. Market Segmentation DynamicsIV. Determinants of Market SegmentationV. Robustness ChecksVI. Conclusions and Future Work

58


Earnings growth:

where:i is countryj is industryw is world

Pricing industry portfolios:

, , , , 1 , , 1 , ,

, , , , 1 , ,

, , , , , 1 , ,

ln i j t w j t i j t i j t

w j t j j w j t w j t

i j t i i j i j t i j t

Earn GO GO

GO GO

GO GO

59


Discount Rate:

where:i is countryj is industryw is world


, , , , , , , ,

, , 1 ,

, , 1 ,

= (1- - ) + +

=

=

i j t f i j i j i j w t i j i t

w t w w w t w t

i t i i i t i t

r

d

d

60


Valuation:

H0: (Strong) Market Integration:

H0: (Strong) Market Segmentation:


, , , , , , , , , , , , , , , , , ,1

= exp( )i j t i j k i j k w t i j k w j t i j k i t i j k i j tk

PE a b c GO e f GO

, , , ,

, , , , , , ,1

0; ; ( ) 0

= exp( )

i j i j j i j t

i j t i j k w t w j tk

GO

PE a GO

j,k j,kb c

, , ,

, , , , , , , , , , ,1

0; ( ) 0

= exp( )

i j w j t

i j t i j k i j k i t i j k i j tk

GO

PE a e f GO

61

Segmentation across U.S. States

0.0%

2.0%

4.0%

6.0%

8.0%

10.0%

12.0%

1973

1974

1975

1976

1977

1978

1979

1980

1981

1982

1983

1984

1985

1986

1987

1988

1989

1990

1991

1992

1993

1994

1995

1996

1997

1998

1999

2000

2001

2002

2003

2004

2005

2006

Average Segmentation




62

Methodology:

– General multivariate model: Which factors account for most of the explained variance?

Need to be able to interpret evidence in the face of severe multi-collinearity

Must reduce the number of factors Lack theoretical guidance

Model reduction techniques (e.g. PCGets (Hendry))


63

IV. General-to-Specific Modeling

Pre

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ConstantTrendCapital Account OpennessEquity Market OpennessTrade OpennessGross FDI/GDPTrade/GDPQuality of InstitutionsInvestment ProfileLaw and OrderInsider Trading LawInsider Trading ProsecutionLegal Origin (English)Legal Origin (French)Local Equity Market IlliquidityLocal Equity Market Turnover

MYY R2 SynchronicityPrivate Credit/GDPMCAP/GDPG7 Real RateU.S. Money Supply GrowthU.S. Risk AversionWorld GDP GrowthU.S. Corporate Bond SpreadVIX Option Volatillity IndexPast Local Equity Market Return

World Equity Market VolatilityInitial Log GDPSecondary School EnrollmentLog Life ExpectancyPopulation GrowthAbs. Difference in Financial Leverage (|Local - Global|)Abs. Difference in Log Earnings Growth Volatility (|Local - Global|)Number of Public Firms (log)

Positive

NegativeNegative

Negative

Negative

PositivePositivePositive

Positive

Negative

Positive

Negative

Negative

Negative

Negative

Negative

Positive

PositivePositive

Positive

Negative

Potential Variables Equity MarketCapital Account

64

Explained Variation in SEG

Contribution of individual factors (xj) to predicted segmentation:

All Factors:

where

, , ,

,

ˆ( , )i t j i j t

i t

Cov SEG x

Var SEG

,2

,

i t

i t

Var SEGR

Var SEG , ,

ˆˆi t i tSEG x

IV. Determinants of Market Segmentation

66

Variance Decomposition


EstimateOverall

Contributionyit-yi

(TS)remainder

(CS)yit-yt

(CS)remainder

(TS)Equity Market Openness -0.0149 0.192 0.040 0.152 0.191 0.001Trade Openness -0.0082 0.056 0.012 0.044 0.053 0.003Investment Profile -0.0277 0.152 0.063 0.089 0.146 0.006MCAP/GDP -0.0056 0.100 0.043 0.057 0.087 0.013World GDP Growth 0.2315 -0.009 -0.009 0.000 0.000 -0.009U.S. Corporate Bond Spread 2.0605 0.141 0.141 0.000 0.000 0.141VIX Option Volatility Index 0.0465 0.034 0.034 0.000 0.000 0.034Abs. Difference in Log Earnings Growth Volatility (|Local - Global|) 0.0911 0.195 0.087 0.108 0.207 -0.011Number of Public Firms (log) -0.0042 0.138 0.015 0.122 0.138 -0.001The sample includes 19 developed and 31 emerging-market countries detailed in Table 1. We regress the annual country-level segmentation measure SEG onto the following variables: 1) the degree of equity market openness (investability) for a given country and year, 2) a 0/1 indicator of trade openness based on trade liberalization dates from Wacziarg and Welch (2003) for a given country and year, 3) a the investment profile from ICRG for a given country and year, 4) the ratio of equity market capitalization to gross domestic product for a given country and year, 5) the U.S. corporate bond spread for a given year, 6) the implied option volatility index (VIX) for a given year, 5) the absolute difference between the industry log earnings growth rate volatility in a given country and the U.S. market as a whole, averaged across all industries in a given country and year, and 6) the natural logarithm of the number of publicly traded firms in a given country and year. We report coefficient estimates from pooled OLS regressions as well as the overall contribution of a variable to the variation of the predicted degree of segmentation, defined as the ratio of the covariance between the given variable and the predicted degree of segmentation relative to the variance of the predicted degree of segmentation. We further distinguish between the time-series (TS) and cross-sectional (CS) component of this overall contribution in two different ways. For details on this distinction, see the corresponding chapter of the paper. N denotes the number of country-years and R2 denotes the coefficient of determination.

67


Equity Market EstimateOverall

Contributionyit-yi

(TS)remainder

(CS)yit-yt

(CS)remainder

(TS)Equity Market Openness -0.0149 0.192 0.040 0.152 0.191 0.001

[-0.0195, -0.0064] [0.095, 0.321] [0.013, 0.065] [0.081, 0.257] [0.094, 0.319] [-0.005, 0.006]

Trade Openness -0.0082 0.056 0.012 0.044 0.053 0.003[-0.0134, -0.0036] [0.028, 0.133] [0.005, 0.028] [0.023, 0.108] [0.027, 0.126] [0.001, 0.008]

Investment Profile -0.0277 0.152 0.063 0.089 0.146 0.006[-0.0328, -0.0074] [0.049, 0.238] [0.019, 0.106] [0.029, 0.132] [0.039, 0.216] [0.002, 0.029]

MCAP/GDP -0.0056 0.100 0.043 0.057 0.087 0.013[-0.0145, -0.006] [0.105, 0.324] [0.044, 0.153] [0.091, 0.287] [0.096, 0.304] [0.012, 0.041]

World GDP Growth 0.2315 -0.009 -0.009 0.000 0.000 -0.009[-0.1029, 0.2339] [-0.009, 0.005] [-0.009, 0.004] [-0.009, 0.005]

U.S. Corporate Bond Spread 2.0605 0.141 0.141 0.000 0.000 0.141[0.9646, 2.3691] [0.077, 0.195] [0.077, 0.195] [0.077, 0.195]

VIX Option Volatility Index 0.0465 0.034 0.034 0.000 0.000 0.034[-0.0048, 0.0551] [-0.004, 0.049] [-0.004, 0.049] [-0.004, 0.049]

Abs. Diff. in Log Earnings Growth Volatility (|Local - Global|) 0.0911 0.195 0.087 0.108 0.207 -0.011

[0.0905, 0.132] [0.178, 0.304] [0.074, 0.162] [0.185, 0.315] [0.186, 0.327] [-0.014, -0.003]

Number of Public Firms (log) -0.0042 0.138 0.015 0.122 0.138 -0.001[-0.0069, -0.004] [0.141, 0.292] [0.012, 0.042] [0.142, 0.293] [0.140, 0.299] [-0.003, 0.002]

68

Variance Decomposition


EstimateOverall

Contributionyit-yi

(TS)remainder

(CS)yit-yt

(CS)remainder

(TS)Capital Account Openness -0.0164 0.123 0.032 0.091 0.125 -0.001Trade Openness -0.0014 0.005 0.001 0.003 0.004 0.000Investment Profile -0.0300 0.161 0.079 0.081 0.153 0.007Legal Origin (French) -0.0042 -0.011 0.000 -0.011 -0.017 0.000MCAP/GDP -0.0054 0.110 0.052 0.058 0.093 0.016U.S. Money Supply Growth 0.1026 0.040 0.048 0.000 0.000 0.040U.S. Corporate Bond Spread 1.6139 0.149 0.182 0.000 0.000 0.149VIX Option Volatility Index 0.0471 0.049 0.040 0.000 0.000 0.049Abs. Difference in Log Earnings Growth Volatility (|Local - Global|) 0.1044 0.224 0.106 0.118 0.237 -0.013Number of Public Firms (log) -0.0044 0.149 0.020 0.129 0.152 -0.003

The sample includes 19 developed and 31 emerging-market countries detailed in Table 1. We regress the annual country-level segmentation measure SEG onto the following variables: 1) the degree of equity market openness (investability) for a given country and year, 2) a 0/1 indicator of trade openness based on trade liberalization dates from Wacziarg and Welch (2003) for a given country and year, 3) a the investment profile from ICRG for a given country and year, 4) the ratio of equity market capitalization to gross domestic product for a given country and year, 5) the U.S. corporate bond spread for a given year, 6) the implied option volatility index (VIX) for a given year, 5) the absolute difference between the industry log earnings growth rate volatility in a given country and the U.S. market as a whole, averaged across all industries in a given country and year, and 6) the natural logarithm of the number of publicly traded firms in a given country and year. We report coefficient estimates from pooled OLS regressions as well as the overall contribution of a variable to the variation of the predicted degree of segmentation, defined as the ratio of the covariance between the given variable and the predicted degree of segmentation relative to the variance of the predicted degree of segmentation. We further distinguish between the time-series (TS) and cross-sectional (CS) component of this overall contribution in two different ways. For details on this distinction, see the corresponding chapter of the paper. N denotes the number of country-years and R2 denotes the coefficient of determination.

70


Capital Account EstimateOverall

Contributionyit-yi

(TS)remainder

(CS)yit-yt

(CS)remainder

(TS)Capital Account Openness -0.0164 0.123 0.032 0.091 0.125 -0.001

[-0.0181, -0.0035] [0.03, 0.191] [0.006, 0.038] [0.024, 0.154] [0.03, 0.189] [-0.004, 0.003]

Trade Openness -0.0014 0.005 0.001 0.003 0.004 0.000[-0.0052, 0.0038] [-0.02, 0.032] [-0.003, 0.009] [-0.017, 0.023] [-0.018, 0.029] [-0.002, 0.003]

Investment Profile -0.0300 0.161 0.079 0.081 0.153 0.007[-0.0353, -0.0082] [0.053, 0.256] [0.023, 0.13] [0.031, 0.13] [0.043, 0.242] [-0.006, 0.034]

Legal Origin (French) -0.0042 -0.011 0.000 -0.011 -0.017 0.000[-0.009, -0.0007] [-0.031, -0.003] [-0.031, -0.003] [-0.044, -0.004]

MCAP/GDP -0.0054 0.110 0.052 0.058 0.093 0.016[-0.013, -0.0048] [0.091, 0.345] [0.04, 0.163] [0.05, 0.187] [0.078, 0.31] [0.011, 0.045]

U.S. Money Supply Growth 0.1026 0.040 0.048 0.000 0.000 0.040[0.0225, 0.1821] [0.013, 0.103] [0.013, 0.103] [0.013, 0.103]

U.S. Corporate Bond Spread 1.6139 0.149 0.182 0.000 0.000 0.149[1.0317, 2.545] [0.109, 0.296] [0.109, 0.296] [0.109, 0.296]

VIX Option Volatility Index 0.0471 0.049 0.040 0.000 0.000 0.049[-0.0045, 0.0611] [-0.005, 0.078] [-0.005, 0.078] [-0.005, 0.078]

Abs. Diff. in Log Earnings Growth Volatility (|Local - 0.1044 0.224 0.106 0.118 0.237 -0.013

[0.1003, 0.1299] [0.215, 0.36] [0.096, 0.193] [0.116, 0.172] [0.227, 0.369] [-0.017, -0.002]

Number of Public Firms (log) -0.0044 0.149 0.020 0.129 0.152 -0.003[-0.0054, -0.0032] [0.116, 0.268] [0.011, 0.032] [0.104, 0.241] [0.117, 0.269] [-0.004, 0.001]

Documents

Valuation and Segmentation in Emerging Markets Geert Bekaert, Columbia + NBER Campbell R. Harvey, Duke + NBER Christian T. Lundblad, UNC Stephan Siegel,