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Financial integration and the information environment: Evidence from

emerging marketsQiyu Zhang

Lancaster University Management School

Wendy BeekesLancaster University Management School

Philip BrownUniversity of Western Australia & University of New South Wales

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Research Question

• What is the association between financial integration and the information environment of a firm in emerging markets?

– Financial integration: free access of foreign investors to local capital markets, and of local investors to foreign capital markets.

– Indicators of a listed firm’s information environment• Intra-year price timeliness : based on the Beekes and Brown (2006,

2007) approach

– Study is confined to listed firms in 24 emerging markets

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Research Motivation

• Financial liberalization in emerging markets since the late 1980s and early 1990s

• Relatively little is known about the effects of financial integration on the recognition of different types of news (e.g., good news versus bad news)

• What are the mechanisms?– E.g., Financial integration transmits higher quality disclosure and

governance standards to emerging-market firms (e..g, Obstfeld, 1998; Stulz, 1999; Aggarwal et al., 2011)

– Need a test

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Our findings

• Greater financial integration is associated with• More efficient (faster) price discovery• The effect is more pronounced for the timeliness of bad news relative to good

news • Indirect effects arise through improved corporate governance

Our contribution

• Benefits of financial integration in emerging markets• Integration can have a positive influence on the level of information available

about a firm in emerging markets

• New measures of intra-year price timeliness• Beekes and Brown (2006, 2007)

• Evidence of indirect effects of integration

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Related literature and hypotheses

• Information available to analysts improves after firms cross-list (Baker et al., 2002; Lang et al., 2003)

• When firms are cross-listed on advanced foreign exchanges, their home-market pricing efficiency is enhanced (Korczak and Bohl, 2005; Baily et al., 2006; Liu, 2007; Su and Chong, 2007)

• Financial market liberalization is associated with increases in firm-specific information, analyst coverage, and forecast accuracy (Bae et al., 2006)

H1: The degree of financial integration is positively associated with the timeliness of price discovery in emerging markets

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Related literature and hypotheses

• Managers tend to withhold bad news due to their private incentives (Kothari et al., 2009)

• Goverannce environment is positively associated with conditional (news-dependent) conservatism (Beekes et al., 2004; Bushman and Piotroski, 2006; Lobo and Zhou, 2006; Ahmed and Duellman, 2007; García Lara et al., 2007, 2009)

• The scrutiny of foreign investors, foreign equity analysts, and foreign stock market listing standards can help improve the information environment by transmitting higher quality disclosure and governance standards to emerging-market firms (e.g., Obstfeld, 1998; Stulz, 1999; Doidge et al., 2004; Aggarwal et al., 2011)

H2: The positive effect of financial integration is more pronounced on the timeliness of bad news than on the timeliness of good news

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Path analysis• Aggarwal et al. (2011) find a positive relationship between international

institutional investments and the corporate governance of local firms.• “Better” CG improves the information environment of a firm (Beekes and

Brown, 2006; Aman et al., 2011; Beekes et al, 2012; Hass et al., 2014)

• DRAW THE PATH GRAPHS!!

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Data and sample construction• Sample period: 1995-2011• Listed firms from 24 emerging markets

– Exclude financial firms– Exclude firm-year observations with missing timeliness and control

variables– Final sample consists of 9,983 firms and 55,790 firm-year

observations• Databases

– Datastream & Worldscope– Data on cross-listing: Bank of New York Mellon– Country level variables

• Chinn and Ito (2006), Lane and Milesi-Ferretti (2007)• World Development Indicators (World Bank)• La Porta et al. (1998)• KOF Index of Globalization

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Measuring Financial Integration (FINITI)

• A de jure openness index (KAOPEN) developed by Chinn and Ito (2006)– Measuring the extent of openness in capital controls– Higher values indicate greater openness of a country to cross-boarder

capital transactions – Used by papers such as Chinn and Ito (2008), and Umutlu et al. (2010)

• A de facto measure (LMF) constructed by Lane and Milesi-Ferretti (2007)– Measuring the degree to which a country has made use of the

international financial markets, in practice, over years– (Foreign equity assets and liabilities + foreign direct investment assets and

liabilities) / GDP– Used by papers such as Umutlu et al. ( 2010), and Lucey and Zhang (2011)

• A dummy variable (DR) that is equal to one if the firm is cross-listed on a foreign exchange in that year and zero otherwise

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Dependent variables

• Timeliness of price discovery (based on Beekes and Brown, 2006)

– where Pt is the market-adjusted share price, observed at daily intervals from day -365 until day -1, and P0 is the price 14 days after the annual EPS release date

– Sensitivity analysis: a deflated timeliness metric (TD), which is the timeliness metric divided by one plus the absolute rate of return on the share over the year.

365

|)ln()ln(|1

3650

t

ttPP

T

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Dependent variables

Timeliness of good news/bad news (based on Beekes and Brown, 2007)

Procedure for estimating timeliness of good news (same for bad news)

• Positive market-adjusted daily log returns:

• Create cumulative log return series, , by setting , and combining the good news return series as from day -364 to day 0 (if day’s return was <0, set the good news return on that day to zero)

• Timeliness of good news is calculated as

0Gtr

0365 GC

GtC

Gt

Gt

Gt rCC 1

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• Control variables– GINFOR Information flow of a country, measured by internet users per

1,000 people, television per 1,000 people, and trade in newspaper percentage of GDP

– COMMON A dummy variable that is equal to one if the country adopts the British common law system and zero otherwise

– INFL The annual percentage change in the consumer price index– GDPPC The natural logarithm of GDP per capita in constant 2005 US

dollars– STKTRD Total value of stocks traded as a share of the GDP– SIZE Natural logarithm of market capitalization in US dollars– PROFIT EBITDA to total assets– LEV Total debt to total assets– MB Market capitalization to book value of shareholders’ equity– RETVOL standard deviation of daily stock returns over the 360 days prior

to the end of the year– GNEWS A dummy variable that is equal to one when the company’s share

price outperforms the market over the year and zero otherwise.• All time-varying variables are winsorized at the 1% and 99% levels

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• Descriptive statistics of variablesCountry Firm-year

Obs. T TD TG TB LMF KAOPEN GINFOR COMMON INFL GDPPC STKTRD SIZE PROFIT LEV MB RETVOL DR GNEWS

Argentina 472 0.211 0.148 0.497 0.493 0.402 0.364 65.676 0 6.161 8.406 0.043 18.550 0.124 0.255 1.326 0.023 0.106 0.415Brazil 1,750 0.227 0.155 0.494 0.490 0.478 0.025 58.223 0 6.777 8.501 0.277 19.731 0.160 0.270 2.181 0.026 0.106 0.495Chile 116 0.155 0.115 0.485 0.498 1.332 1.648 72.600 0 1.410 9.061 0.250 19.933 0.124 0.219 2.614 0.014 0.052 0.474China 8,547 0.197 0.149 0.499 0.476 0.344 -1.169 52.756 0 2.714 7.646 1.077 19.740 0.086 0.275 3.950 0.025 0.0001 0.524Colombia 226 0.194 0.136 0.496 0.501 0.305 -0.484 60.676 0 7.950 8.139 0.042 19.295 0.105 0.139 1.058 0.020 0.044 0.513Czech 160 0.195 0.139 0.476 0.496 0.584 1.589 88.076 0 2.921 9.373 0.137 19.069 0.134 0.145 1.151 0.018 0.094 0.456Egypt 335 0.232 0.155 0.486 0.471 0.374 2.254 57.882 0 10.953 7.246 0.304 19.317 0.181 0.185 2.684 0.025 0.122 0.457Hungary 286 0.224 0.152 0.502 0.503 0.928 1.641 80.733 0 7.477 9.216 0.210 18.260 0.115 0.178 1.474 0.027 0.101 0.423India 8,231 0.261 0.172 0.496 0.495 0.316 -1.169 40.248 1 8.432 6.739 0.709 17.653 0.137 0.286 2.295 0.030 0.060 0.429Indonesia 2,089 0.270 0.176 0.472 0.470 0.269 1.162 41.979 0 8.674 7.182 0.153 17.695 0.128 0.270 1.891 0.032 0.018 0.412Israel 1,605 0.208 0.146 0.507 0.500 0.926 2.220 57.580 1 2.668 9.915 0.515 17.878 0.087 0.292 2.142 0.024 0.033 0.487Jordan 425 0.221 0.154 0.482 0.488 1.120 2.439 75.463 0 5.829 7.906 0.821 17.018 0.066 0.178 1.661 0.019 0.012 0.546Korea 9,311 0.274 0.178 0.502 0.496 0.440 -0.058 56.718 0 3.267 9.759 1.406 17.803 0.071 0.255 1.355 0.031 0.008 0.402Malaysia 8,344 0.211 0.147 0.495 0.500 0.879 -0.031 69.764 1 2.358 8.613 0.475 17.588 0.081 0.223 1.363 0.029 0.007 0.371Mexico 1,159 0.211 0.144 0.495 0.494 0.398 0.972 62.236 0 9.425 8.946 0.075 19.739 0.127 0.236 1.680 0.021 0.167 0.431Morocco 136 0.167 0.121 0.497 0.516 0.533 -1.169 66.820 0 1.729 7.709 0.216 19.153 0.168 0.169 3.060 0.016 0.000 0.551Pakistan 685 0.223 0.156 0.505 0.503 0.161 -1.169 41.246 1 11.188 6.567 0.504 18.036 0.174 0.259 2.314 0.022 0.012 0.460Peru 572 0.241 0.162 0.486 0.486 0.425 2.428 51.984 0 2.729 8.021 0.035 18.244 0.167 0.213 1.705 0.023 0.040 0.514Philippines 928 0.249 0.167 0.500 0.496 0.275 -0.074 44.953 0 4.892 7.113 0.108 17.887 0.092 0.197 2.094 0.032 0.056 0.456Poland 1,403 0.243 0.164 0.497 0.497 0.545 0.033 88.362 0 3.148 9.106 0.133 17.959 0.097 0.160 2.199 0.026 0.020 0.448Russia 234 0.258 0.166 0.482 0.469 0.625 0.100 80.372 0 10.580 8.729 0.464 20.954 0.161 0.228 2.131 0.030 0.363 0.487South Africa 2,853 0.246 0.162 0.506 0.499 0.963 -1.133 48.706 1 6.273 8.539 0.824 18.410 0.158 0.156 2.369 0.030 0.094 0.457Thailand 4,038 0.229 0.154 0.498 0.501 0.541 -0.420 59.698 1 2.998 7.884 0.467 17.647 0.123 0.280 1.544 0.026 0.021 0.461Turkey 1,885 0.220 0.159 0.510 0.499 0.233 -0.744 63.173 0 16.391 8.849 0.407 18.398 0.148 0.210 2.239 0.027 0.032 0.465All countries 55,790 0.235 0.160 0.498 0.493 0.514 -0.294 56.264 0.462 5.078 8.262 0.720 18.239 0.107 0.249 2.131 0.028 0.033 0.443

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Correlation coefficients[2] [3] [4] [5] [6] [7] [8] [9] [10] [11] [12] [13] [14] [15] [16] [17] [18]

T [1] 0.922 0.155 0.191 -0.057 0.003 -0.066 -0.006 0.049 0.014 0.058 -0.210 -0.188 0.097 0.038 0.446 -0.046 0.004TD [2] 0.168 0.198 -0.073 -0.013 -0.071 -0.024 0.056 0.006 0.078 -0.209 -0.177 0.097 0.028 0.436 -0.052 0.030TG [3] 0.582 -0.058 -0.032 -0.016 0.004 0.026 0.020 -0.051 -0.062 -0.045 0.036 -0.085 0.065 -0.005 -0.035TB [4] -0.009 0.002 0.010 0.068 0.002 0.025 -0.035 -0.023 -0.022 0.026 0.008 0.063 -0.002 -0.032LMF [5] 0.284 0.512 0.407 -0.318 0.403 0.035 -0.109 -0.080 -0.135 -0.081 -0.010 0.011 -0.020KAOPEN [6] 0.357 -0.163 -0.105 0.426 -0.195 -0.084 -0.057 -0.044 -0.142 -0.041 0.022 -0.012GINFOR [7] -0.109 -0.303 0.598 -0.130 -0.020 -0.134 -0.119 -0.114 -0.071 -0.027 -0.012COMMON [8] 0.002 -0.307 -0.217 -0.241 0.078 0.007 -0.093 0.026 0.021 -0.037INFL [9] -0.242 -0.189 -0.040 0.184 0.021 -0.011 0.090 0.061 0.005GDPPC [10] 0.285 -0.040 -0.157 -0.079 -0.151 0.034 -0.033 -0.020STKTRD [11] 0.086 -0.114 -0.003 0.177 0.133 -0.069 0.033SIZE [12] 0.298 -0.026 0.382 -0.393 0.233 0.159PROFIT [13] -0.181 0.114 -0.287 0.067 0.188LEV [14] 0.008 0.122 0.025 -0.055MB [15] -0.035 0.015 0.141RETVOL [16] -0.068 -0.013DR [17] 0.008GNEWS [18]

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Estimation Methods

• Pooled ordinary least squares (OLS) with standard errors clustered by firm

• Path analysis• Source variable: financial integration• Mediating variable: corporate governance• Outcome variable: timeliness• Structural equation model (SEM): a regression of one of the outcome

variables on the mediating variable, and a regression of the mediating variable on the source variable

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Regression results - OLS

Dependent variable Timeliness (T) Timeliness Deflated (TD)(1) (2) (3) (4) (5) (6)

LMF -0.036*** -0.036*** -0.012** -0.011**

KAOPEN 0.001 0.002 -0.001 -0.001

DR -0.019*** -0.019*** -0.019*** -0.009*** -0.009*** -0.009***

No. of Observations 55,790 55,790 55,790 55,790 55,790 55,790

Adjusted R-squared 0.24 0.24 0.24 0.22 0.22 0.22Control variables Yes Yes Yes Yes Yes YesCountry, year and industry effects

Yes Yes Yes Yes Yes Yes

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Regression results - OLS

Dependent variable Timeliness of good news (TG) Timeliness of bad news (TB)(1) (2) (3) (4) (5) (6)

LMF -0.002 -0.0001 -0.023*** -0.021***

KAOPEN -0.003*** -0.003*** -0.005*** -0.004***

DR 0.005*** 0.005*** 0.005*** -0.004** -0.004** -0.004**

No. of Observations 55,790 55,790 55,790 55,790 55,790 55,790

Adjusted R-squared 0.07 0.07 0.07 0.08 0.08 0.08Control variables Yes Yes Yes Yes Yes YesCountry, year and industry effects

Yes Yes Yes Yes Yes Yes

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Path analysis• Sample period: 2003 -2011• Chinese listed firms

– Exclude financial firms– Exclude firm-year observations with missing timeliness, corporate

governance, and control variables– Final sample consists of 2,134 firms and 12,497 firm-year observations

• China Stock Market and Accounting Research (CSMAR) platform– CG attributes: China Listed Firms Corporate Governance Research

Database– Accounting data: China Stock Market Financial Statements Database– Prices, Returns, Trading data: China Stock Market Trading Database – Information on auditors: China Stock Market Financial Database – Audit

Opinion

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Summary statistics and correlation of the governance attributes of Chinese listed firmsPanel A: Criteria used to construct the CG score

The proportion of observations that meet the criterion

1. The board is controlled by more than 50% independent directors (INDIV). 1%2. The board size is greater than 6 but fewer than 13 (BOARDSIZE). 89%3. Then chairman and general manager are not the same person (DUAL). 85%4. There are no relationships among the top ten shareholders (TOP10RELATION). 8%5. Management ownership (directors, supervisors, and executives) is greater than 1% but less than 30% (MANAGEMENT).

7%

6. The firm is audited by one of the joint ventures between a Big Four international audit firm and a domestic audit firm (BIG4).

6%

Panel B: Correlations of corporate governance attributes

[2] [3] [4] [5] [6] [7]

CG [1] 0.167 0.479 0.537 0.376 0.328 0.362INDIV [2] -0.016 -0.007 -0.021 -0.011 0.042BOARDSIZE [3] -0.0002 -0.028 0.033 -0.056DUAL [4] -0.007 -0.100 0.052TOP10RELATION [5] -0.045 -0.014MANAGEMENT [6] -0.045BIG4 [7]

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Regression results - Chinese sample

Dependent variable CG T TD TG TB T TD TG TB

(1) (2) (3) (4) (5) (6) (7) (8) (9)

FINITI 0.4325*** -0.0014 0.0022 -0.0007 -0.0104** -0.0008 0.0026 -0.0003 -0.0096**

CG -0.0014 -0.0009 -0.0007 -0.0019**

N0. of observations 12,497 12,497 12,497 12,497 12,497 12,497 12,497 12,497 12,497

Adjusted R-squared 0.53 0.32 0.19 0.13 0.53 0.32 0.19 0.13

Control variables Yes Yes Yes Yes Yes Yes Yes YesYear and industry effects

Yes Yes Yes Yes Yes Yes Yes Yes

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Path analysis of direct and indirect effects of integration on timeliness

Outcome variable (OV) T TD TG TB

(1) (2) (3) (4)

Direct path p[FINITI, OV] -0.0008 0.0026 -0.0003 -0.0096**

Mediated path I. p[FINITI, CG] 0.4271*** 0.4271*** 0.4325*** 0.4325*** II. p[CG, OV] -0.0014 -0.0009 -0.0007 -0.0019**

Indirect effect (I×II) -0.0006 -0.0004 -0.0003 -0.0008**

N 12,497 12,497 12,497 12,497Goodness of fit 0.00 0.00 0.00 0.00Control variables Yes Yes Yes YesYear and industry effects Yes Yes Yes Yes

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Key findings so far....

• Benefits of financial integration in emerging markets• More timely price discovery• Financial integation improves the timeliness of bad news relative to

good news. • We find evidence of a mechanism through which financial integration

enhances the information environment: improved corporate governance

• There is still much to do!

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Thank you