Table 2.3 reports the estimation results with respect to different specifications. For brevity’s sake, we do not report the country fixed effect and time effect. We first report the estimation result without interaction terms entering our model. Model 1 shows the pooled estimation result where the coefficient of Gov is negative and statistically significant at the 1% level. This suggests that a country with a better governance environment has less home bias. Similarly, Model 2 represents the panel estimation results of country fixed effects with time dummies. The coefficient of Gov is negative, however it is insignificant.
For Model 3 to Model 5, each measurement for the channels of information penetration is entered separately. The coefficients for information penetration proxies are -0.035 (Internetnorm) and -0.016 (Serversnorm), respectively. However, they are negatively related to home bias, but are not significant. In addition, we find consistently significant and negative effects for financial openness and trade openness.
This implies that a market with more openness has less incentive to diversify its portfolios in foreign markets. The fact that financial openness can lower home bias is consistent with the global trend of financial integration (Baele et al., 2007). However, the negative and significant estimated coefficient for Size suggests that government size has a negative effect on reducing cross-border investment bias. The positive sign of market capitalization to GDP (Cap) can be interpreted that well developed markets not only make it possible for foreign countries to participate in the local country, but also prompt domestic investors to have less incentive to diversify their portfolios internationally. Moreover, both government size (Size) and total population (Pop) seem to have adverse effects on cross-border investment since the estimated
coefficients are significantly negative.
We now propose that these information penetration channels can either affect cross-border investment directly or indirectly. To identify the moderate effects of various information penetrations, we extend our basic model by adding the multiplicative interaction term of governance quality and information proxies.
Model 6 to Model 8 report estimation results with interaction terms added into our regression specifications. The estimated coefficients for Gov are respectively -0.509 and -0.283 in Model 6 and Model 7 and are significant at the 1% level. Since the coefficient of a multiplicative interaction term is significantly negative, it is important to notice the presence of the two attributes,
Internet
norm and Internetnorm×Gov. The negative and significant coefficients of the interaction term have critical implications for interpreting empirical results. The variables IP and IP×Gov modify the individual governance quality effect on cross-border investment. The total impact of governance quality on home bias is β7+β9Internet
norm instead of β7. In other words, since coefficients β7 < 0 and β9 < 0, the negative impact of the governance environment on home bias is strengthened by information penetration (Internetnorm, Serversnorm, andMobile
norm). Thus, greater information penetration reduces the investment bias in countries with higher governance quality. Following the same logic, the estimated coefficients β8 < 0 and β9 < 0, and greater governance quality appears to decrease cross-border investment bias in countries with higher information adoption. The adjusted R2 for our regression models range from 0.34 to 0.42, suggesting that home bias is well explained by the variation in cross-country governance quality and information penetration on a significant level.In summary, the coefficients of interaction terms Internetnorm×Gov and
Servers
norm×Gov are significantly negative. This implies that governance affects home bias by the marginal effect of information penetration. Furthermore, there is a negative and significant interaction between governance quality and Internetnorm, as well as governance quality and Serversnorm, supporting that information penetration strengthens the governance quality effect on home bias. However, the cross product of governance quality and Mobilenorm negatively interacts with the dependent variable, and it is insignificant. Nevertheless, the main message of our analysis is that we find evidence for the investment portfolio holdings in connection with a country’s information penetration.50
Table 2.3 Panel Estimation with a Fixed Effect for Equity Home Bias
The dependent variable is the equity home bias (Home bias). The explanatory variables include: logarithm of GDP (GDP); sum of imports and exports scaled by GDP (Trade); stock market capitalization (Cap); central government consumption as a share of GDP to proxy government size (Size); country size is proxied by the logarithm of total population (Pop); credit to the private sector as a share of GDP is used to proxy financial depth (Fin); the first principal component from various aspects of governance indices (Gov). We consider three different variables to proxy information penetration (IP): Internet users per 100 people (Internetnorm), number of secure Internet servers (Serversnorm), and number of mobile telephone subscribers (Mobilenorm) normalized by GDP per capita.
Without Interaction With Interaction Pooled OLS Fixed effects Fixed effects
(1) (2) (3) (4) (5) (6) (7) (8)
Note: *, **, and *** indicate significance at the 0.1, 0.05, and 0.01 levels, respectively. Numbers in parentheses are White’s heteroskedasticity-robust standard errors. Estimated coefficients of country effect and time dummies are not reported to save space.
2.5 Robustness Checks
This section performs a variety of robustness checks of our primary findings. We first address the problem of sensitivity for the estimated coefficients using the bootstrap method. We then analyze the panel data regression after trimming some extreme observations. Table 2.4 presents the robust results for information penetration as a role of a moderate variable for the governance quality-home bias relationship. From Model 9 to Model 11, the coefficients are estimated by the bootstrap method with 2,000 replications to ensure estimation stability. The estimated coefficients for
Internet
norm×Gov and Serversnorm×Gov are respectively -0.168 and -0.075. They aresignificant at the 5% and 10% statistical levels, respectively. The coefficient for
Mobile
norm×Gov is -0.103 and statistically significant at the 10% level. We find a robust result that all interaction terms negatively interact with investment bias.We re-estimate our regressions after trimming 10% of existing extreme values in our data to avoid estimation bias. The analytic result is equivalent. For Model 12 to Model 14, we find a negative and significant interaction effect for Internetnorm×Gov,
Servers
norm×Gov, and Mobilenorm×Gov, indicating that countries with more information penetration are more diversified and have less home bias. The estimated coefficients for interaction terms Internetnorm×Gov and Serversnorm×Gov are respectively -0.221 and -0.090. Both estimated coefficients are statistically significant at the 1% level. The coefficient for Mobilenorm×Gov is -0.145 and is also significant at the 10% level. The overall R2 exceeds 0.41 for all models, which is greater than acceptable. The estimation results from the bootstrap procedure and trimming extreme values indicate that information penetration has a moderate effect on international asset allocation. These negative and significant coefficients for the multiplicative interaction term of information penetration and governance quality imply that information penetration can affect the strength of the relationship between governance quality and home bias. Overall, the robust analysis consistently suggests that information penetration moderates the governance quality-home bias relationship.52
Table 2.4 Robust Estimation
The dependent variable is the equity home bias (Home bias). The explanatory variables include: logarithm of GDP (GDP); sum of imports and exports scaled by GDP (Trade); stock market capitalization (Cap); central government consumption as a share of GDP to proxy government size (Size); country size is proxied by the logarithm of total population (Pop); credit to the private sector as a share of GDP is used to proxy financial depth (Fin); the first principal component from various aspects of governance indices (Gov). We consider three different variables to proxy information penetration (IP): Internet users per 100 people (Internetnorm), number of secure Internet servers (Serversnorm), and number of mobile telephone subscribers (Mobilenorm) normalized by GDP per capita.
F stastistics 12.01 11.90 11.61
R-square within 0.42 0.43 0.41 0.44 0.44 0.44
Note: *, **, and *** indicate significance at the 0.1, 0.05, and 0.01 levels, respectively. Estimated coefficients of country effect and time dummies are not reported to save space.
2.6 Concluding Remarks
This study examines whether the difference in governance quality can explain cross-country heterogeneity in international investment behavior. A panel dataset of 44 countries for the period 2001-2009 is employed to test the analytical arguments.
We provide theoretical insights that governance quality and information penetration have a stimulative effect on reducing home bias. In addition, we argue that information penetration can affect the strength of the relationship between governance quality and home bias.
We find that a superior governance quality significantly impacts on reducing
cross-border investment bias. In fact, a country with a better governance quality can improve its economic performance and attract foreign institutional investors.
Therefore, such a country is more capable to allocate its assets internationally. Our empirical results suggest that information penetration consistently has a negative effect on reducing home bias, although the individual estimated coefficient is insignificant. Finally, the information infrastructure such as Internet users, the number of secure Internet servers, and the number of mobile telephone subscribers moderates the form of the governance quality and home bias relationship. By including a set of multiplicative interaction terms of information penetration and governance quality in our empirical model, we show that the implied effect of governance quality on home bias is negative for countries with higher information adoption. This evidence can be attributed to the fact that an information infrastructure can improve governance effectiveness and accelerate information diffusion. Actually, countries with a higher information adoption have a negative effect of governance quality on home bias.
The empirical insight is that countries trying to attract more foreign investment and reduce home bias should devote more energy into maintaining governance quality and the information infrastructure. Hence, a country with a lower home bias will benefit from reducing global systematic risks.
Although we have found possible factors to explain the home bias, this research is not without limitations. The potential shortcomings of this research are as follows:
(1) we follow the analytical procedure of Sharma et al. (1981) to identify the moderating effect of selected information penetration channels. This implies that the two effects, governance quality and information infrastructure, are mutually exclusive.
However, in reality, an information infrastructure may have both direct and indirect effects. For example, the Internet may not only have a direct effect on the governance quality-home bias relationship when it influences the governance environment, but it also may have an indirect effect in improving the country’s general investment activities. Thus, future research may shed more light to identify and separate these effects when the Internet may engender both direct and indirect effects. (2) Our results confirm that heterogeneity of governance quality and information penetration can explain cross-sectional international investment behavior. The home bias measure is more severe for emerging countries than that for developed countries. The emerging countries may have their own unique country attributes and specified constraints such as investment size and capital control that influence international portfolio allocation.
Future research may provide insights into the country specific factors that impact various managerial behaviors in different settings.
54
Conclusions
The famous puzzle home bias is observed in many fields and a body of literature suggests many explanations for this phenomenon. This dissertation investigates the role of unique culture characteristics, governance environment and how they interact with information penetration. In Chapter 1, we provide evidence that culture characteristics can affect cross-border investment differently while the culture distance discourages originating countries to hold foreign portfolio which leads to higher home bias. In addition, our study shows that information distance can further increase culture distance that prevents international diversification. In Chapter 2, we find that better regulatory has a negative but insignificant effect on reducing home bias. Nevertheless, we further find that a country with effective governance regime appears to decrease cross-border investment bias under higher information penetration.
Since home bias exists in various markets, the latest research relates culture characteristics to banking and international investment literature. Aggarwal and Goodell (2009) examine the role of national culture in determining the preferences of financial intermediation, showing a country characterized by higher uncertainty avoidance prefers bank-based financial intermediation instead of market-based.
Beugelsdijk and Frijns (2010) apply a society’s culture and the cultural distance between two markets to explain the foreign bias. Moreover, Anderson et al. (2011) conclude that culture characteristics indeed influence institutional investors’ foreign diversification. To examine the role of information distance and culture distance in cross-border investment. Diyarbakirlioglu (2011) finds that the observed geographical patterns of bilateral portfolio investments can be explained by information asymmetries rather than cultural affinities between countries. Thus, the cultural difference between countries could be an obstacle or barrier in foreign investment.
For further research, we can investigate the home bias in debt market instead of that in equity investment. For example, a country characterized by higher uncertainty avoidance can behave more conserve to equity investment than debt investment. As research topics for corporate finance, future research can relate cultural traits to capital structure and CEO’s overinvestment issues in the future. Furthermore, we argue that the cross-border investment behavior can be connected to Euro crisis and global aging. The series problem of fiscal deficit and aged population in developed countries can affect foreign investment directly or indirectly. We conjecture that demographics in a country are expected to have significant effects on home bias. This phenomenon indicates that developed countries with aged population may encounter
serious fiscal deficits, and therefore allows capital flow, such as pension fund, from countries to emerging countries with higher growth and asset return. These addressed topics are influential for financial market and world economics in the future. We left these important international finance and macroeconomics issues for further research.
56
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