1. Financial integration and the information environment: Evidence from emerging markets Qiyu Zhang Lancaster University Management School Wendy Beekes Lancaster University Management School Philip Brown University of Western Australia & University of New South Wales 1

2. 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 firms 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 2

3. 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 3

4. 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 4

5. 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) H 1 : The degree of financial integration is positively associated with the timeliness of price discovery in emerging markets 5

6. 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) H 2 : The positive effect of financial integration is more pronounced on the timeliness of bad news than on the timeliness of good news 6

7. 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!! 7

8. 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 8

9. 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 9

10. Dependent variables Timeliness of price discovery (based on Beekes and Brown, 2006) – where P t is the market-adjusted share price, observed at daily intervals from day -365 until day -1, and P 0 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. 10

11. 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 days return was <0, set the good news return on that day to zero) Timeliness of good news is calculated as 11

12. 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 companys share price outperforms the market over the year and zero otherwise. All time-varying variables are winsorized at the 1% and 99% levels 12

13. Descriptive statistics of variables 13 Country Firm-year Obs. TTDTGTBLMFKAOPENGINFORCOMMONINFLGDPPCSTKTRDSIZEPROFITLEVMBRETVOLDRGNEWS Argentina4720.2110.1480.4970.4930.4020.36465.67606.1618.4060.04318.5500.1240.2551.3260.0230.1060.415 Brazil1,7500.2270.1550.4940.4900.4780.02558.22306.7778.5010.27719.7310.1600.2702.1810.0260.1060.495 Chile1160.1550.1150.4850.4981.3321.64872.60001.4109.0610.25019.9330.1240.2192.6140.0140.0520.474 China8,5470.1970.1490.4990.4760.344-1.16952.75602.7147.6461.07719.7400.0860.2753.9500.0250.00010.524 Colombia2260.1940.1360.4960.5010.305-0.48460.67607.9508.1390.04219.2950.1050.1391.0580.0200.0440.513 Czech1600.1950.1390.4760.4960.5841.58988.07602.9219.3730.13719.0690.1340.1451.1510.0180.0940.456 Egypt3350.2320.1550.4860.4710.3742.25457.882010.9537.2460.30419.3170.1810.1852.6840.0250.1220.457 Hungary2860.2240.1520.5020.5030.9281.64180.73307.4779.2160.21018.2600.1150.1781.4740.0270.1010.423 India8,2310.2610.1720.4960.4950.316-1.16940.24818.4326.7390.70917.6530.1370.2862.2950.0300.0600.429 Indonesia2,0890.2700.1760.4720.4700.2691.16241.97908.6747.1820.15317.6950.1280.2701.8910.0320.0180.412 Israel1,6050.2080.1460.5070.5000.9262.22057.58012.6689.9150.51517.8780.0870.2922.1420.0240.0330.487 Jordan4250.2210.1540.4820.4881.1202.43975.46305.8297.9060.82117.0180.0660.1781.6610.0190.0120.546 Korea9,3110.2740.1780.5020.4960.440-0.05856.71803.2679.7591.40617.8030.0710.2551.3550.0310.0080.402 Malaysia8,3440.2110.1470.4950.5000.879-0.03169.76412.3588.6130.47517.5880.0810.2231.3630.0290.0070.371 Mexico1,1590.2110.1440.4950.4940.3980.97262.23609.4258.9460.07519.7390.1270.2361.6800.0210.1670.431 Morocco1360.1670.1210.4970.5160.533-1.16966.82001.7297.7090.21619.1530.1680.1693.0600.0160.0000.551 Pakistan6850.2230.1560.5050.5030.161-1.16941.246111.1886.5670.50418.0360.1740.2592.3140.0220.0120.460 Peru5720.2410.1620.486 0.4252.42851.98402.7298.0210.03518.2440.1670.2131.7050.0230.0400.514 Philippines9280.2490.1670.5000.4960.275-0.07444.95304.8927.1130.10817.8870.0920.1972.0940.0320.0560.456 Poland1,4030.2430.1640.497 0.5450.03388.36203.1489.1060.13317.9590.0970.1602.1990.0260.0200.448 Russia2340.2580.1660.4820.4690.6250.10080.372010.5808.7290.46420.9540.1610.2282.1310.0300.3630.487 South Africa2,8530.2460.1620.5060.4990.963-1.13348.70616.2738.5390.82418.4100.1580.1562.3690.0300.0940.457 Thailand4,0380.2290.1540.4980.5010.541-0.42059.69812.9987.8840.46717.6470.1230.2801.5440.0260.0210.461 Turkey1,8850.2200.1590.5100.4990.233-0.74463.173016.3918.8490.40718.3980.1480.2102.2390.0270.0320.465 All countries55,7900.2350.1600.4980.4930.514-0.29456.2640.4625.0788.2620.72018.2390.1070.2492.1310.0280.0330.443

14. Correlation coefficients 14 [2][3][4][5][6][7][8][9][10][11][12][13][14][15][16][17][18] T [1] 0.9220.1550.191-0.0570.003-0.066-0.0060.0490.0140.058-0.210-0.1880.0970.0380.446-0.0460.004 TD [2] 0.1680.198-0.073-0.013-0.071-0.0240.0560.0060.078-0.209-0.1770.0970.0280.436-0.0520.030 TG [3] 0.582-0.058-0.032-0.0160.0040.0260.020-0.051-0.062-0.0450.036-0.0850.065-0.005-0.035 TB [4] -0.0090.0020.0100.0680.0020.025-0.035-0.023-0.0220.0260.0080.063-0.002-0.032 LMF [5] 0.2840.5120.407-0.3180.4030.035-0.109-0.080-0.135-0.081-0.0100.011-0.020 KAOPEN [6] 0.357-0.163-0.1050.426-0.195-0.084-0.057-0.044-0.142-0.0410.022-0.012 GINFOR [7] -0.109-0.3030.598-0.130-0.020-0.134-0.119-0.114-0.071-0.027-0.012 COMMON [8] 0.002-0.307-0.217-0.2410.0780.007-0.0930.0260.021-0.037 INFL [9] -0.242-0.189-0.0400.1840.021-0.0110.0900.0610.005 GDPPC [10] 0.285-0.040-0.157-0.079-0.1510.034-0.033-0.020 STKTRD [11] 0.086-0.114-0.0030.1770.133-0.0690.033 SIZE [12] 0.298-0.0260.382-0.3930.2330.159 PROFIT [13] -0.1810.114-0.2870.0670.188 LEV [14] 0.0080.1220.025-0.055 MB [15] -0.0350.0150.141 RETVOL [16] -0.068-0.013 DR [17] 0.008 GNEWS [18]

15. 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 15

16. Regression results - OLS 16 Dependent variableTimeliness (T)Timeliness Deflated (TD) (1)(2)(3)(4)(5)(6) LMF-0.036*** -0.012**-0.011** KAOPEN0.001 0.002-0.001 DR-0.019*** -0.009*** No. of Observations55,790 Adjusted R-squared0.24 0.22 Control variablesYes Country, year and industry effects Yes

17. Regression results - OLS 17 Dependent variableTimeliness 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*** -0.005***-0.004*** DR0.005*** -0.004** No. of Observations55,790 Adjusted R-squared0.07 0.08 Control variablesYes Country, year and industry effects Yes

18. 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 18

19. Summary statistics and correlation of the governance attributes of Chinese listed firms 19 Panel 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]0.1670.4790.5370.3760.3280.362 INDIV[2]-0.016-0.007-0.021-0.0110.042 BOARDSIZE[3]-0.0002-0.0280.033-0.056 DUAL[4]-0.007-0.1000.052 TOP10RELATION[5]-0.045-0.014 MANAGEMENT[6]-0.045 BIG4[7]

20. Regression results - Chinese sample 20 Dependent variableCGTTDTGTBTTDTGTB (1)(2)(3)(4)(5)(6)(7)(8)(9) FINITI 0.4325***-0.0014 0.0022-0.0007-0.0104**-0.00080.0026-0.0003-0.0096** CG -0.0014-0.0009-0.0007-0.0019** N0. of observations 12,497 Adjusted R-squared 0.530.320.190.130.530.320.19 0.13 Control variables Yes Year and industry effects Yes

21. Path analysis of direct and indirect effects of integration on timeliness 21 Outcome variable (OV) TTDTGTB (1)(2)(3)(4) Direct path p[FINITI, OV] -0.00080.0026-0.0003-0.0096** Mediated path I. p[FINITI, CG] 0.4271*** 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** N12,497 Goodness of fit0.00 Control variablesYes Year and industry effectsYes

22. 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! 22

23. Thank you 23