Valuation and Segmentation in
Emerging Markets
Geert Bekaert, Columbia + NBER
Campbell R. Harvey, Duke + NBER
Christian T. Lundblad, UNC
Stephan Siegel, U. of Washington
May 16, 2008
I. The Setting
• 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?
`
II. The Plan
1. Segmentation
2. Valuation
`
III. Openness
Two aspects of (de jure) globalization
Economic Integration:
Financial Integration:
Trade Liberalization Indicator
[Wacziarg and Welch (2004)]
Capital Account Openness Index
[Quinn and Toyoda (2001)]
Equity Market Openness
[Bekaert and Harvey (2000)]
6
III. Openness
Trade and Financial Openness Have Increased
1.0
0.8
0.6
0.4
Open Capital Account
Investable Equity
Trade Openness
0.2
Open Equity Market
05
20
03
20
01
20
99
19
97
19
95
19
93
19
91
19
89
19
87
19
85
19
83
19
81
19
79
19
77
19
75
19
19
73
0.0
7
III. Openness
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
8
III. Openness
Equity Returns
Economic Integration:
• Specialization
• Exposure to world shocks
Cash Flows
Discount Rates
Real Rates
Term Premiums
Equity risk premiums
Financial Integration
Bond Returns
Inflation
Economic Integration
9
III. Four Contributions
1
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
10
(2004), Aizenman and Noy (2005), Lane and Milesi-Ferretti (2001)
III. Four Contributions
• 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
11
explores its determinants
III. Four Contributions
2
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)
12
III. Four Contributions
3
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)
13
III. Four Contributions
4
Related issues:
 Investigate industry-specific degrees of
segmentation
 “Segmentation” within the U.S.
 “Segmentation” within the EU
14
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
15
IV. A Measure of Market Segmentation
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:
N
SEGi ,t =
 IW
j 1
i , j ,t
| EYi , j ,t  EYw, j ,t |
16
IV. A Measure of Market Segmentation
Construct SEG for 50 Countries between 1973 and 2005
EYi,j,t
EYw,j,t
IWi,j,t
12 month trailing earnings yield,
negative yields set to zero
EMDB: 28 countries
DataStream: 22 countries
12 month global trailing earnings DataStream
yield, negative yields set to zero
(also considered U.S.)
Industry MCAP share in local
market
EMDB: 28 countries
DataStream: 22 countries
17
IV. A Measure of Market Segmentation
Segmentation
Segmentation over time
Average
Year of
segmenation
Average
first
over first five segmentation Change in
observation
years
2001 - 2005 segmentation
Country
Sample
Average
St. Dev.
ARG
CHN
DEU
GBR
IND
MEX
PHL
USA
VEN
EM
EM
DEV
DEV
EM
EM
EM
DEV
EM
5.3%
2.3%
2.1%
1.9%
3.2%
3.5%
2.9%
0.7%
6.8%
5.2%
1.0%
1.0%
1.2%
1.4%
3.6%
0.9%
0.2%
4.8%
1988
1995
1980
1980
1988
1988
1990
1980
1988
9.5%
2.6%
3.2%
4.2%
3.2%
5.8%
3.4%
0.6%
6.4%
4.9%
2.1%
2.4%
1.2%
2.7%
2.3%
2.5%
0.8%
10.0%
-48.4%
-18.1%
-25.7%
-72.8%
-13.8%
-61.0%
-26.0%
23.6%
55.0%
Averages of country-level data
DEV
EM
2.7%
4.4%
1.5%
2.6%
1982
1991
4.5%
5.8%
1.9%
3.9%
-45.0%
-20.1%
ALL
3.8%
2.2%
1988
5.3%
3.1%
-29.6%
18
IV. A Measure of Market Segmentation
Segmentation
Segmentation over time
Average
Average
segmentatio segmentatio Change in
n 1980 n
segmentatio
1984
2001 - 2005
n
Rank
Rank based Rank based
on average
on average
segmentation segmentation
1980 - 1984 2001 - 2005
Industry
Average
St. Dev.
Banks
Life Insurance
General Retailers
Nonlife Insurance
Electricity
Fixed Line Telecommunications
...
Aerospace & Defense
Support Services
Pharmaceuticals & Biotechnology
Gas, Water & Multiutilities
Household Goods
Travel & Leisure
5.8%
5.2%
4.2%
5.0%
4.5%
4.2%
2.9%
3.5%
2.6%
2.0%
2.0%
2.1%
10.0%
8.5%
8.2%
7.6%
7.5%
7.3%
3.0%
2.9%
4.1%
4.1%
3.5%
3.8%
-69.8%
-65.7%
-50.4%
-46.4%
-52.5%
-47.7%
1
2
3
4
5
6
33
34
12
13
25
18
3.0%
3.0%
3.0%
2.6%
3.6%
4.1%
1.6%
1.7%
1.2%
1.0%
1.4%
2.0%
3.4%
3.0%
3.0%
2.9%
2.8%
2.8%
2.5%
3.2%
3.5%
3.7%
3.8%
5.4%
-25.7%
6.7%
16.1%
28.3%
35.6%
92.4%
33
34
35
36
37
38
37
30
26
22
17
3
Average of industry-level data
4.1%
1.7%
5.1%
3.9%
-14.3%
19
IV. A Measure of Market Segmentation
4.5%
4.0%
Average Country and Industry Segmentation (MAD)
1973 - 2005
Average Country Effect
Average Industry Effect
3.5%
3.0%
2.5%
2.0%
1.5%
1.0%
0.5%
19
73
19
74
19
75
19
76
19
77
19
78
19
79
19
80
19
81
19
82
19
83
19
84
19
85
19
86
19
87
19
88
19
89
19
90
19
91
19
92
19
93
19
94
19
95
19
96
19
97
19
98
19
99
20
00
20
01
20
02
20
03
20
04
20
05
0.0%
20
V. Market Segmentation Dynamics
12.0%
SEG: Industry-weighted Valuation Differentials
Emerging Markets Segmentation
Developed Countries Segmentation
10.0%
Linear (Developed Countries Segmentation)
Linear (Emerging Markets Segmentation)
8.0%
6.0%
4.0%
2.0%
0.0%
19
73
19
74
19
75
19
76
19
77
19
78
19
79
19
80
19
81
19
82
19
83
19
84
19
85
19
86
19
87
19
88
19
89
19
90
19
91
19
92
19
93
19
94
19
95
19
96
19
97
19
98
19
99
20
00
20
01
20
02
20
03
20
04
20
05
21
V. Market Segmentation Dynamics
SEG: Industry-weighted Valuation Differentials
12%
EM (Advanced) Segmentation
Developed Countries Segmentation
10%
EM (Frontier) Segmentation
8%
6%
4%
2%
05
04
22
20
03
20
02
20
01
20
00
20
99
20
98
19
97
19
96
19
95
19
94
19
93
19
92
19
91
19
90
19
89
19
88
19
87
19
86
19
85
19
84
19
83
19
82
19
81
19
80
19
79
19
78
19
77
19
76
19
75
19
74
19
19
19
73
0%
V. Market Segmentation Dynamics
SEG: Industry-weighted Valuation Differentials
20%
North America
18%
Africa
Asia (excl. JPN)
16%
Europe
Latin America (incl. Caribbean)
Middle East / North Africa
14%
12%
10%
8%
6%
4%
2%
05
04
23
20
03
20
02
20
01
20
00
20
99
20
98
19
97
19
96
19
95
19
94
19
93
19
92
19
91
19
90
19
89
19
88
19
87
19
86
19
85
19
84
19
83
19
82
19
81
19
80
19
79
19
78
19
77
19
76
19
75
19
74
19
19
19
73
0%
V. Market Segmentation Dynamics
Changes over time suggest we observe valuation convergence…
Explore an unbalanced panel regression with a simple time trend
Trend
R
2
Number of Countries
All
Developed
Emerging
-0.0007
-0.0012
-0.0012
(0.0003)
(0.0003)
(0.0008)
0.02
0.19
0.02
50
19
31
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
24
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
25
VI. Market Segmentation: U.S. Study
Segmentation across random
draws of U.S. firms grouped into pseudo-’countries’
12%
Average Segmentation within U.S.
10%
5th percentile Segmentation
95th percentile Segmentation
Developed Countries Segmentation
8%
Emerging Markets Segmentation
6%
4%
2%
06
05
20
04
20
03
26
20
02
20
01
20
00
20
99
20
98
19
97
19
96
19
95
19
19
94
19
93
19
92
91
19
90
19
89
19
88
19
87
19
86
19
85
19
84
19
83
19
82
19
81
19
80
19
79
19
78
19
77
19
76
19
75
19
74
19
19
19
73
0%
VI. Market Segmentation: U.S. Study
12%
Segmentation across random
draws of U.S. firms by U.S. states
10%
Average Segmentation within U.S.
8%
Developed Countries Segmentation
Emerging Markets Segmentation
6%
4%
2%
06
05
27
20
04
20
03
20
02
20
01
20
00
20
99
20
98
19
97
19
96
19
95
19
94
19
93
19
92
19
91
19
90
19
89
19
88
19
87
19
86
19
85
19
84
19
83
19
82
19
81
19
80
19
79
19
78
19
77
19
76
19
75
19
74
19
19
19
73
0%
VI. Market Segmentation: U.S. Study
1973 - 2006
Treating U.S. States as "Countries"
Trend
I
II
III
IV
-0.0005
-0.0002
-0.0003
-0.0003
0.0001
0.0001
0.0001
0.0001
-0.0049
-0.0046
-0.0045
0.0009
0.0008
0.0008
0.0234
0.0177
0.0131
0.0108
Number of Public Firms (log)
Abs. Difference in Financial
Leverage (|Local - US|)
Abs. Difference in Log Earnings
Growth Volatility (|Local - US|)
0.0064
0.0027
N
1,495
1,495
1,495
1,495
R2
0.05
0.15
0.15
0.16
28
VI. Market Segmentation: U.S. Study
100 Random Samples of 50 "Countries" 1973 - 2006
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
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
Distribution of t - stats
29
VI. Market Segmentation in the EU
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?
30
VI. Market Segmentation in the EU
12
10
8
SEG
Core Europe relative to CE EY
Linear (Core Europe relative to CE EY)
6
4
2
0
31
VI. Market Segmentation in the EU
14
Example: Austria
|EY - CEEY| and EU Membership
12
EU - Membership: 1995
10
8
6
4
2
0
32
VI. Market Segmentation in the EU
2004 EU Entrants:
|EY - CEEY|
9
SEG
EU - Membership: 2004
EST, LTU, SVK, CZE, LVA, POL, HUN, SVN, CYP
8
7
6
5
4
3
2
1
0
33
VI. Market Segmentation in the EU
There is a significant trend towards valuation convergence in Europe.
Is that explained by (de jure) EU or Euro membership?
(1)
EU Membership
(2)
-1.427
(0.521)
Euro Zone
-1.243
(0.399)
Trend
R-squared
(3)
(4)
(5)
-1.221
(0.567)
-1.127
(0.649)
-0.902
(0.456)
-0.109
(0.028)
0.061
0.038
0.170
(6)
(7)
-1.234
(0.660)
0.314
(0.455)
0.664
(0.363)
-0.102
(0.030)
-0.116
(0.033)
-0.117
(0.033)
0.204
0.168
0.211
0.080
EU membership is important, but trend persists.
34
VII. Market Segmentation Dynamics
(with controls)
All Countries (1980 - 2005)
Trend
I
II
III
IV
-0.0007
-0.0007
-0.0008
-0.0008
(0.0003)
(0.0003)
(0.0002)
(0.0002)
-0.0073
-0.0072
-0.0058
(0.0021)
(0.0020)
(0.0019)
0.0972
0.0564
(0.0544)
(0.0508)
Number of Public Firms (log)
Abs. Difference in Financial Leverage
(|Local - Global|)
Abs. Difference in Log Earnings
Growth Volatility (|Local - Global|)
0.1279
(0.0276)
N
906
906
906
906
R2
0.02
0.09
0.10
0.16
35
VII. Market Segmentation Dynamics:
De Jure Openness
Equity Market Openness
Equity Market Openness
I
III
IV
V
-0.0282
-0.0228
-0.0253
-0.0212
(0.0070)
(0.0062)
(0.0063)
(0.0055)
-0.0289
-0.0151
-0.0122
-0.0092
(0.0117)
(0.0116)
(0.0117)
(0.0107)
-0.0008
-0.0009
(0.0003)
(0.0003)
Trade Openness
II
Trend
Number of Public Firms (log)
-0.0045
(0.0016)
0.0339
Abs. Difference in Financial Leverage
(|Local - Global|)
(0.0530)
0.1121
Abs. Difference in Log Earnings
Growth Volatility (|Local - Global|)
(0.0277)
N
906
906
906
906
906
R2
0.11
0.07
0.13
0.15
0.24
36
VII. Market Segmentation Dynamics:
De Jure Openness
Capital Account Openness
Capital Account Openness
I
III
IV
V
-0.0331
-0.0296
-0.0296
-0.0202
(0.0086)
(0.0080)
(0.0083)
(0.0071)
-0.0185
-0.0076
-0.0063
-0.0063
(0.0087)
(0.0091)
(0.0092)
(0.0072)
-0.0006
-0.0007
(0.0003)
(0.0003)
Trade Openness
II
Trend
Number of Public Firms (log)
-0.0047
(0.0011)
0.0478
Abs. Difference in Financial Leverage
(|Local - Global|)
(0.0437)
0.1074
Abs. Difference in Log Earnings
Growth Volatility (|Local - Global|)
(0.0279)
N
880
880
880
880
880
R2
0.08
0.03
0.09
0.11
0.23
37
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?
38
VIII. Determinants of Market Segmentation
RISK APPETITE
GROWTH
Lagged Dependent Variable
Constant
Capital Account Openness
Trend
Equity Account
Market Openness
Capital
Openness
Trade Market
Openness
Equity
Openness
GrossOpenness
FDI/GDP
Trade
Trade/GDP
Gross
FDI/GDP
Political Risk
Trade/GDP
Qualityof
ofInstitutions
Institutions
Quality
InvestmentProfile
Profile
Investment
Lawand
andOrder
Order
Law
Minority
Shareholder
Insider
Trading
Law Rights
InsiderTrading
Trading Prosecution
Law
Insider
Insider
Trading
Prosecution
Legal
Origin
(English)
LegalOrigin
Origin(French)
(English)
Legal
LegalEquity
Origin Market
(French)Illiquidity
Local
LocalEquity
EquityMarket
Market Turnover
Illiquidity
Local
Local Equity Market Turnover
MYY R2 Synchronicity
Local Equity Market Return Autocorrelation
Private Credit/GDP
MYY examples
R2 Synchronicity
MCAP/GDP
Private Credit/GDP
Private Credit/GDP (adj.)
Potential Variables
CONTROLS
FIN DEV
INST DEV
OPENNESS
Potential Variables
Lagged Dependent Variable
Capital
Account Openness
Real Rate
G7
Equity
Market
Openness
Growth
Supply
Money
U.S.
Trade
Openness
Aversion
Risk
U.S.
Gross GDP
FDI/GDP
Growth
World
Trade/GDP
Corporate Bond Spread
U.S.
Political
Risk
Volatillity Index
Option
VIX
Quality
ofEquity
Institutions
Market Return
Local
Past
Investment
Market Volatility
EquityProfile
World
Law
and
Order
Initial Log GDP
Minority Shareholder
Rights
School Enrollment
Secondary
Insider
Law
Expectancy
LifeTrading
Log
Insider Trading
Prosecution
Growth
Population
Legal
Origin (English)
in Financial Leverage (|Local Difference
Abs.
Legal Origin (French)
Global|)
Earnings Growth
in LogIlliquidity
Difference
Abs.
Local
Equity Market
- Global|)
(|Local
Volatility
Local Equity
Market
Turnover
(log)Autocorrelation
Firms
of Public
Number
Local Equity
Market
Return
MYY R2 Synchronicity
Private Credit/GDP
39
Private Credit/GDP (adj.)
VIII. Determinants of Market Segmentation
Economic Effect on Market Segmentation (N= 906, R2 = 0.30)
OLS
Estimate Emerging Developed
Equity Market Openness
Trade Openness
Investment Profile
MCAP/GDP
World GDP Growth
U.S. Corporate Bond Spread
VIX Option Volatility Index
Abs. Difference in Log Earnings
Growth Volatility (|Local - Global|)
Number of Public Firms (log)
-0.0149
-0.0082
-0.0277
-0.0056
0.2315
2.0605
0.0465
0.49
0.81
0.59
0.46
0.0911
-0.0042
0.13
5.47
Standard
Deviation of
Time Series
Variation
1.00
1.00
0.73
0.65
-0.0075
-0.0016
-0.0038
-0.0010
0.0048
0.0725
0.09
5.89
 SEG
0.0098
0.0034
-0.0035
-0.0018
40
VIII. Determinants of Market Segmentation
Economic Effect on Market Segmentation (N= 880, R2 = 0.33)
OLS Estimate Emerging Developed
Standard
Deviation of
Time Series
Variation
 SEG
Capital Account Openness
Trade Openness
Investment Profile
-0.0164
-0.0014
-0.0300
0.56
0.84
0.61
0.91
1.00
0.73
-0.0058
-0.0002
-0.0038
Legal Origin (French)
MCAP/GDP
U.S. Money Supply Growth
U.S. Corporate Bond Spread
VIX Option Volatility Index
Abs. Difference in Log Earnings
Growth Volatility (|Local - Global|)
Number of Public Firms (log)
-0.0042
-0.0054
0.1026
1.6139
0.0471
0.61
0.48
0.25
0.65
0.0015
-0.0009
0.0036
0.0077
0.0034
0.1044
-0.0044
0.13
5.52
0.0355
0.0048
0.0725
0.09
5.89
-0.0039
-0.0016
41
Eq
ui
ty
O
pe
Tr
nn
ad
es
e
O
s
In
pe
ve
nn
st
es
m
s
en
tP
ro
M
W
CA fil e
or
P/
ld
U
G
.S
D
. C GD
P
P
or
G
p.
Bo row
th
nd
VI
Ea
Sp
X
Vo
rn
re
in
ad
l
at
gs
ilit
G
y
N
ro
In
um
w
de
th
be
Vo x
ro
la
fP
til
ub
ity
lic
Fi
rm
s
VIII. Determinants of Market Segmentation
0.250
Cross Section
Time-Series
0.200
0.150
0.100
0.050
0.000
-0.050
42
VIII. Determinants of Market Segmentation
U.S. as a Benchmark
Equity Market Capital Account
Capital Account Openness
Determinants relative to World
Average
Equity Market Capital Account
-0.0190
-0.0174
(0.0061)
Equity Market Openness
Trade Openness
Investment Profile
(0.0053)
-0.0156
-0.0145
(0.0048)
(0.0048)
-0.0104
-0.0032
-0.0115
-0.0027
(0.0107)
(0.0077)
(0.0104)
(0.0073)
-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)
MCAP/GDP
-0.0061
-0.0042
-0.0041
(0.0031)
(0.0031)
(0.0035)
(0.0036)
U.S. Money Supply Growth
World GDP Growth
U.S. Corporate Bond Spread
VIX Option Volatility Index
Abs. Difference in Log Earnings
Growth Volatility (|Local - U.S.|)
Number of Public Firms (log)
(0.0036)
-0.0061
0.0958
-0.0173
(0.0393)
(0.0366)
0.2149
0.0630
(0.1140)
(0.1120)
2.4939
2.0609
1.7539
1.7090
(0.3930)
(0.3010)
(0.3510)
(0.2600)
0.0506
0.0522
0.0153
0.0218
(0.0154)
(0.0110)
(0.0192)
(0.0143)
0.0783
0.0808
0.0940
0.1043
(0.0251)
(0.0226)
(0.0316)
(0.0299)
-0.0042
-0.0045
-0.0045
-0.0045
(0.0018)
(0.0015)
(0.0016)
(0.0013)
43
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
44
IX. Valuation
Valuation (switch to log PE ratios):
VALi ,t   IWi , j ,t PEi , j ,t  PEw, j ,t 
N
j 1
45
IX. Valuation
1: What explains the emerging markets discount?
Use some of the same variables to try to explain variation
in price to earnings ratios (both across countries and
through time).
46
IX Valuation
Emerging
MarketMarket
Discount (LEGO)
(ex Japan)
“Emerging
Discount”
0.4
0.2
Ave. Discount
Relative PE Ratios
-0.2
-0.4
-0.6
Important factors? Financial openness, political and
institutional risks, illiquid equity markets, and U.S. default
premia
-0.8
20
05
20
04
20
03
20
02
20
01
20
00
19
99
19
98
19
97
19
96
19
95
19
94
19
93
19
92
19
91
19
90
19
89
19
88
19
87
19
85
-1
19
84
DISCOUNT
0
19
86
PREMIUM
Figure 3
47
IX. Valuation
2: Decomposing PE Ratios
Are they driven by growth opportunities or discount rate
effects?
48
IX. Valuation
2: Decomposing PE Ratios
Are they driven by growth opportunities or discount rate
effects?
49
IX. Valuation
2: Decomposing PE Ratios
Empirical model for 5-year real returns
Empirical model for 5-year real earnings growth
Project current PE on these two variables.
50
IX. Valuation
3: Market Efficiency
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
51
Conclusions
•Sementation
 New 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
52
Conclusions
•Valuation
 Valuation in developing markets is challenging for
investors
 Our 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.
53
Conclusions
• Why does this matter?
 Market segmentation and or undervaluation raises the
cost of capital
 Higher cost of capital means less investment and less
employment growth
 Lower investment and employment growth means lower
GDP growth
 For 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
54
Supplementary Materials
(not for reproduction)
55
I. Motivation and Goals
Outline
I. Motivation and Goals
II. Measure of Market Segmentation
III. Market Segmentation Dynamics
IV. Determinants of Market Segmentation
V. Robustness Checks
VI. Conclusions and Future Work
57
IV. A Measure of Market Segmentation
Pricing industry portfolios:
Earnings growth:
 ln Earni , j ,t  GOw, j ,t 1  GOi , j ,t 1   i , j ,t
GOw, j ,t   j   j GOw, j ,t 1   w, j ,t
GOi , j ,t  i  i , j GOi , j ,t 1   i , j ,t
where:
i is country
j is industry
w is world
58
IV. A Measure of Market Segmentation
Pricing industry portfolios:
Discount Rate:
 i , j ,t = rf (1-i , j -i , j ) + i , j  w,t + i , j  i , t
 w,t = d w  w  w, t 1  w,t
 i ,t = di  i  i , t 1  i ,t
where:
i is country
j is industry
w is world
59
IV. A Measure of Market Segmentation
Pricing industry portfolios:
Valuation:

PEi , j ,t =
 exp(a
k 1
i , j ,k
 bi , j ,k  w,t  ci , j ,k GOw, j ,t  ei , j ,k  i ,t  fi , j ,k GOi , j ,t )
H0: (Strong) Market Integration:
 i , j  0;  i , j   j ;  (GOi , j ,t )  0

PEi , j ,t =
 exp(a
k 1
i , j ,k
 b j,k w,t  c j,k GOw, j ,t )
H0: (Strong) Market Segmentation:
i , j  0;  (GOw, j ,t )  0

PEi , j ,t =
 exp(a
k 1
i , j ,k
 ei , j , k  i ,t  f i , j , k GOi , j ,t )
60
VI. Market Segmentation: U.S. Study
12.0%
Segmentation across U.S. States
10.0%
Average Segmentation
8.0%
Developed Countries Segmentation
Emerging Markets Segmentation
6.0%
4.0%
2.0%
0.0%
19
7
19 3
74
19
7
19 5
7
19 6
7
19 7
7
19 8
7
19 9
8
19 0
8
19 1
82
19
8
19 3
8
19 4
8
19 5
8
19 6
8
19 7
8
19 8
8
19 9
9
19 0
9
19 1
9
19 2
9
19 3
9
19 4
9
19 5
9
19 6
97
19
9
19 8
9
20 9
0
20 0
0
20 1
0
20 2
0
20 3
0
20 4
05
20
06
61
VIII. Determinants of Market Segmentation
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))
62
IV. General-to-Specific Modeling
Potential Variables
World Equity Market Volatility
Initial Log GDP
Secondary School Enrollment
Log Life Expectancy
Population Growth
Abs. Difference in Financial Leverage (|Local Global|)
Abs. Difference in Log Earnings Growth
Volatility (|Local - Global|)
Number of Public Firms (log)
Positive
Encompassing
Negative
Multiple search paths
MYY R2 Synchronicity
Private Credit/GDP
MCAP/GDP
G7 Real Rate
U.S. Money Supply Growth
U.S. Risk Aversion
World GDP Growth
U.S. Corporate Bond Spread
VIX Option Volatillity Index
Past Local Equity Market Return
Positive
Pre-search reduction
Constant
Trend
Capital Account Openness
Equity Market Openness
Trade Openness
Gross FDI/GDP
Trade/GDP
Quality of Institutions
Investment Profile
Law and Order
Insider Trading Law
Insider Trading Prosecution
Legal Origin (English)
Legal Origin (French)
Local Equity Market Illiquidity
Local Equity Market Turnover
Equity Market Capital Account
Negative
Negative
Negative
Negative
Negative
Negative
Negative
Negative
Positive
Positive
Positive
Positive
Positive
Positive
Positive
Positive
Negative
Negative
63
IV. Determinants of Market Segmentation
Explained Variation in SEG
All Factors:
R 
2
Var  SEGi ,t 
Var  SEGi ,t 
where
SEGi ,t  ˆ  ˆ xi ,t
Contribution of individual factors (xj) to predicted segmentation:
Cov (SEGi ,t , ˆ j xi , j ,t )
Var  SEGi ,t 
64
IV. Determinants of Market Segmentation
Variance Decomposition
Equity Market Openness
Trade Openness
Investment Profile
MCAP/GDP
World GDP Growth
U.S. Corporate Bond Spread
VIX Option
Abs.
Difference
Volatility
in LogIndex
Earnings
Growth Volatility (|Local Global|)
Number of Public Firms (log)
Estimate
-0.0149
-0.0082
-0.0277
-0.0056
0.2315
2.0605
0.0465
Overall
Contribution
0.192
0.056
0.152
0.100
-0.009
0.141
0.034
yit-yi
(TS)
0.040
0.012
0.063
0.043
-0.009
0.141
0.034
remainder
(CS)
0.152
0.044
0.089
0.057
0.000
0.000
0.000
yit-yt
(CS)
0.191
0.053
0.146
0.087
0.000
0.000
0.000
remainder
(TS)
0.001
0.003
0.006
0.013
-0.009
0.141
0.034
0.0911
-0.0042
0.195
0.138
0.087
0.015
0.108
0.122
0.207
0.138
-0.011
-0.001
The sample includes 19 developed and 31 emerging-market countries detailed in Table 1. We regress the annual country-level segmentatio
following variables: 1) the degree of equity market openness (investability) for a given country and year, 2) a 0/1 indicator of trade openne
liberalization dates from Wacziarg and Welch (2003) for a given country and year, 3) a the investment profile from ICRG for a given coun
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,
volatility index (VIX) for a given year, 5) the absolute difference between the industry log earnings growth rate volatility in a given countr
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
We report coefficient estimates from pooled OLS regressions as well as the overall contribution of a variable to the variation 66
of the predict
segmentation, defined as the ratio of the covariance between the given variable and the predicted degree of segmentation relative to the var
IV. Determinants of Market Segmentation
Estimate
-0.0149
Overall
Contribution
0.192
yit-yi
(TS)
0.040
remainder
(CS)
0.152
yit-yt
(CS)
0.191
remainder
(TS)
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]
-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]
-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]
-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]
0.2315
-0.009
-0.009
0.000
0.000
-0.009
[-0.1029, 0.2339]
[-0.009, 0.005]
[-0.009, 0.004]
2.0605
0.141
0.141
[0.9646, 2.3691]
[0.077, 0.195]
[0.077, 0.195]
0.0465
0.034
0.034
[-0.0048, 0.0551]
[-0.004, 0.049]
[-0.004, 0.049]
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]
-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]
Equity Market
Equity Market Openness
Trade Openness
Investment Profile
MCAP/GDP
World GDP Growth
U.S. Corporate Bond Spread
VIX Option Volatility Index
Abs. Diff. in Log Earnings Growth
Volatility (|Local - Global|)
Number of Public Firms (log)
[-0.009, 0.005]
0.000
0.000
0.141
[0.077, 0.195]
0.000
0.000
0.034
[-0.004, 0.049]
67
IV. Determinants of Market Segmentation
Variance Decomposition
Overall
Estimate Contribution
-0.0164
0.123
-0.0014
0.005
-0.0300
0.161
-0.0042
-0.011
-0.0054
0.110
0.1026
0.040
1.6139
0.149
0.0471
0.049
Capital Account Openness
Trade Openness
Investment Profile
Legal Origin (French)
MCAP/GDP
U.S. Money Supply Growth
U.S. Corporate Bond Spread
VIX Option Volatility Index
Abs. Difference in Log Earnings
Growth Volatility (|Local - Global|) 0.1044
Number of Public Firms (log)
-0.0044
0.224
0.149
yit-yi
(TS)
0.032
0.001
0.079
0.000
0.052
0.048
0.182
0.040
remainder
(CS)
0.091
0.003
0.081
-0.011
0.058
0.000
0.000
0.000
yit-yt
(CS)
0.125
0.004
0.153
-0.017
0.093
0.000
0.000
0.000
remainder
(TS)
-0.001
0.000
0.007
0.000
0.016
0.040
0.149
0.049
0.106
0.020
0.118
0.129
0.237
0.152
-0.013
-0.003
The sample includes 19 developed and 31 emerging-market countries detailed in Table 1. We regress the annual country-level segmentation measu
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
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 y
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 im
68 and the
volatility index (VIX) for a given year, 5) the absolute difference between the industry log earnings growth rate volatility in a given country
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 co
IV. Determinants of Market Segmentation
Capital Account
Capital Account Openness
Trade Openness
Investment Profile
Legal Origin (French)
MCAP/GDP
U.S. Money Supply Growth
U.S. Corporate Bond Spread
VIX Option Volatility Index
Abs. Diff. in Log Earnings
Growth Volatility (|Local Number of Public Firms (log)
yit-yi
(TS)
0.032
Estimate
-0.0164
Overall
Contribution
0.123
remainder
(CS)
0.091
[-0.0181, -0.0035]
[0.03, 0.191]
-0.0014
0.005
[-0.0052, 0.0038]
[-0.02, 0.032]
-0.0300
0.161
0.079
0.081
[-0.0353, -0.0082]
[0.053, 0.256]
[0.023, 0.13]
[0.031, 0.13]
-0.0042
-0.011
0.000
-0.011
[-0.009, -0.0007]
[-0.031, -0.003]
-0.0054
0.110
0.052
0.058
[-0.013, -0.0048]
[0.091, 0.345]
[0.04, 0.163]
[0.05, 0.187]
0.1026
0.040
0.048
0.000
[0.0225, 0.1821]
[0.013, 0.103]
[0.013, 0.103]
1.6139
0.149
0.182
[1.0317, 2.545]
[0.109, 0.296]
[0.109, 0.296]
0.0471
0.049
0.040
[-0.0045, 0.0611]
[-0.005, 0.078]
[-0.005, 0.078]
0.1044
0.224
0.106
[0.1003, 0.1299]
[0.215, 0.36]
-0.0044
0.149
[-0.0054, -0.0032]
[0.116, 0.268]
[0.006, 0.038] [0.024, 0.154]
0.001
0.003
[-0.003, 0.009] [-0.017, 0.023]
yit-yt
(CS)
0.125
remainder
(TS)
-0.001
[0.03, 0.189] [-0.004, 0.003]
0.004
0.000
[-0.018, 0.029] [-0.002, 0.003]
0.153
0.007
[0.043, 0.242] [-0.006, 0.034]
-0.017
0.000
[-0.031, -0.003] [-0.044, -0.004]
0.016
[0.078, 0.31] [0.011, 0.045]
0.000
0.040
[0.013, 0.103]
0.000
0.000
0.149
[0.109, 0.296]
0.000
0.000
0.049
[-0.005, 0.078]
0.118
[0.096, 0.193] [0.116, 0.172]
0.020
0.093
0.129
[0.011, 0.032] [0.104, 0.241]
0.237
-0.013
[0.227, 0.369] [-0.017, -0.002]
0.152
-0.003
[0.117, 0.269] [-0.004, 0.001]
70