Stock Market Liberalization and the Stock Market Liberalization and the Information EnvironmentInformation Environment

by by

Kee Hong Bae, Warren Bailey, Connie X MaoKee Hong Bae, Warren Bailey, Connie X Mao

Discussed by:

Campbell R. HarveyDuke University and NBER

Introduction

Purpose of paper:• Study association between equity market openness

and information environment for emerging market firms

Findings: • Information measures increase with openness.

Proxies for Openness

Proxies for Openness:

• Discrete Events:

– Official liberalization announcement

– Cross-listing or country fund in U.S./U.K.

– Breakpoint in U.S. portfolio flow to country

• Gradual Measures:

– Fraction of stocks available to foreign investors

– Gross U.S. portfolio flow to country

Proxies for Information

Proxies for Information:

• Firm specific volatility

• Earnings related measures:

– (1) Number of analysts (resources)

– (2) Absolute time series forecast error (naïve forecast precision)

– (3) Absolute analyst forecast error (analyst precision)

– (4) Analyst information advantage=|(3)-(2)| (analyst valued added)

– (5) Forecast dispersion (uncertainty)

Hypotheses

Openness increases

• H1: Number of analysts increases • H2: Firm specific volatility increases • H3: Reported earnings volatility increases • H4: Analyst information advantage improves • H5a: Earnings forecast dispersion decreases • H5b: Earnings forecast dispersion increases

What we know

Bekaert, Harvey and Lumsdaine (JFE 2002) “Dating Integration of World Equity Markets”

ADR introduction

Official liberalization

Country fund intro

Univariate: Holdings/mkt.

cap.

Stock Market DevelopmentTurnover 7.53 9.36 24.04 6.43 Std. error 1.30 1.24 1.20 1.39

Value traded/GDP 3.58 2.54 3.27 4.86 Std. error 0.35 0.29 0.19 0.36

What we know

Increased turnover and value traded imply:• Better information environment

What we know

Bekaert and Harvey (JF 2000) “Foreign Speculators”

Panel A: Official Liberalization Panel B: First Sign

Coefficient T-statistic Coefficient T-statisticCross-sectional standard deviation

0.0071 1.90 0.0222 5.69

What we know

Cross-sectional standard deviation increases:• Implying less cross-correlation and• More idiosyncratic volatility

Hence, contribution of the really focuses on the accounting based measures of information.

Suggestions

1. Econometric

Example regression would have firm specific volatility on LHS and other stuff on RHS.

• No correction for autocorrelation and heteroskedasticity – and the usual techniques do not apply. Need to correct for firm or country-specific autocorrelation and heteroskedacity.

• Correction detailed in Bekaert, Harvey and Lundblad (JDE 2001)

Suggestions

2. Inference

Regression evidence details changes in key variables after liberalization.

• Even with the correct BHL (2001) standard errors, there are issues with small sample properties

• Our experience suggests that it is best to do a Monte Carlo experiment with random liberalization dates to get the empirical cutoff for the t-ratios.

Suggestions

3. Specification

Regression uses dummy variables, one year before and one year after.

• Existing evidence suggests one year after is not enough time to measure impact of liberalization.

Suggestions

4. Omitted variables

Regression uses fixed and time effects.• This should take care of omitted variables. However, it

is often more economically interesting to specify a set of control variables.

Suggestions

4. Omitted variablesBhattacharya, Daouk, Welker (AR 2003)

• They dig deeper into the accounting number: ‘earnings aggressiveness’, ‘earning smoothing’, ‘overall opacity’ and ‘loss avoidance’

Suggestions

5. Heterogeneity

The impact of liberalization differs across countries.• However, the effect is forced to be the same across

countries in all but the Korean example in Table 8.

Suggestions

5. HeterogeneityBreak liberalization dummy into two pieces:

• one for countries with above average value of characteristic and

• the other for below average values.

Suggestions

5. HeterogeneityCandidate characteristics: • Financial development indicators

– Private credit/GDP– Market size

• Quality of institutions– Judicial efficiency– Speed of process– ICRG institutional quality

• Risks present in country– Conflict– Economic environment

Suggestions

6. EndogeneityWhat comes first liberalization or information environment?

• Econometrically, difficult to deal with. Lead-lag tests in the paper indicate some bi-directionality

• Usual technique is instrumental variables. However, one needs to come up with an instrument that predicts liberalization but is uncorrelated with the information environment.

Conclusions

• I believe the results

Off-line suggestions

• Update BHL “Growth volatility” reference. Actually, we find that economic volatility never increases after liberalization and most of the time significantly decreases

• Cite Bekaert (WBER 1995) for the first use of the investibility measure.

• The Harvey website is now referred to as Bekaert, G. and Harvey, C.R. “A Chronology of Important Economic, Financial and Political Events in Emerging Markets” http://www.duke.edu/~charvey/chronology.htm

• Footnote #17 says no EIV because variable on LHS and footnote #18 says you used lagged dependent variable in some of the analysis

Off-line suggestions

• Lagged dependent correction is problematic for many reasons, best to go with BHL 2001.

• Some results seem at odds with BCN (JFE 2003), in particular, their Table 5.

• Overall, nice work!

Tests – Discrete Openness Events2. Table 3 – Difference in Means

Panel A, Panel B Findings support:• H1: Number of analysts increases• H2: firm specific volatility increases• H3: naïve forecast error increases• H4: analyst advantage increases• H5b: dispersion increasesNote:• Portfolio Flow Breakpoints significant both before & after

Tests – Discrete Openness Events 3. Table 4 – Regression Tests

Panel A (firm-specific volatility):• Openness firm-specific volatility increases.

Panel B (earnings related measures):• Openness measures increase.

Note: De-liberalization has no effect (different from Table 3)Critique:- Why does ‘before’ & ‘after’ dummy only include obs 1 year before & after event?

Why not all years before & after event? Is it to avoid other shocks unrelated to liberalization event? Include crisis dummy for Mexico 1994, Asia 1997-1998?

- Are std errors adjusted for heteroskedasticity and contemporaneous cross-correlation?

Summary of before & after analysisTables 3 & 4

Ranking of importance of liberalization events:

• 1) Portfolio flow breakpoints, cross-listing and country fund events

• 2) Official liberalization announcements

Critique:

Compare H2 with Table 5 in BCN(2003): BCN find idiosyncratic firm volatility is not linearly related to firm investibility. Differences: BCN strip out more systematic factors – investibility, country, industry, size. BMM only accounts for local market index (and global market index but not reported). BCN uses firm level time series investibility (more comparable to Table 5 BBM). BBM use country level before & after dummies.

Tests – Gradual measures of openness Table 5 – Investibility, Portfolio flows

Panel A: (Investibility), find support for :• H3: absolute time series forecast error increases• H4: analyst advantage increases• H5b: forecast dispersion increases• H2: firm volatility - insignificant, agrees with BCN (2003), Panel B: (Portfolio Flows), find support for:• H1: Number of analysts increases• H3: Absolute time series forecast error increases• H4: analyst advantage increases• H5b: Forecast dispersion increasesOverall note: lagged investibility important for firm volatility. Contemporaneous investibility

important for earnings related variables takes time for attention to spread from specific earnings events to general coverage.

Critique:• Use firm-country-year to increase sample size & adjust std errors for contemporaneous

correlation across firms within each country?

Local vs foreign analystsTable 6

Findings:• Number of foreign analysts increases by more than local analysts with

openness• Foreign analyst advantage increases relative to local• Forecast dispersion increases more for foreign analysts• Forecast error increases more for foreign analysts (mixed evidence)BMM concludes: “openness increases amount of skilled foreign resources applied

to local market”.Critique:- what’s defn of ‘foreign’ - foreign firm or analyst of foreign origin? Alternative

explanation: foreign firms attract experienced skilful local analysts with high pay. Local firms hire new analysts with less skill. Results reflect movement of skilful analysts from local to foreign firms rather than increased resources. (partly based on anecdotal evidence from Malaysia)

Old vs New analystsTable 7

Findings:

• Old analyst advantage don’t change after openness

• More forecasts per earnings event after openness

BMM conclude: openness analysts work harder

Critique:

Related issue to previous Table 6. Does ‘old’ analyst refer to firms or to individual analysts? My guess is it refers to firms reporting to IBES. Individual analysts could be different while firm name remains the same.

Case study: Korea Table 8 – Firm level analysis

Panel A (Investibility):- Consistent with country level analysis- H2: openness leads to increased firm volatility (different from BCN(2003))- Interactive terms (chaebol dummy*openness): strongly negativePanel B (Portfolio Flows):- Results similar to Panel A.BMM conclude: Interaction among openness, information and corporate governance.Firms with poor governance attract more attention (more analysts) but experience less

improvement in info environment with openness.Critique:• Sign on Market Cap coefficient for firm specific volatility is opposite to sign in

Table 5 for country level analysis. Why? • Are std errors adjusted for contemporaneous correlation across firms for each year?

Failure to do this could bias t-statistics upwards

Openness information ?Table 9 – VAR Causality Test

Findings: • Portfolio Flow Firm specific volatility• Portfolio flow Number of analysts • Investibility Forecast error• Investibility Forecast dispersion• Other pairs show insignificant results

BMM conclude: (weak) evidence in support of openness leading improved information

environment