In this section, results of empirical analyses in this paper is provided whether political connections impact the venture capital industry and whether reputation and innovative efficiency matter firms’ milestone; and hence, answer the question how venture capital markets relate to social capitals as an information dissemination channel. To examine effects of political connections on the entrepreneurial IPO milestone, this paper estimates a contingent fixed-effect logistic model to determine the probability of a firm achieved the IPO milestone. With fixed-effect model one can control for stable characteristics that are not measured in this paper and thus decrease the likelihood of suffering from omitted variable bias.
Results are reported in Table 4 for the hypotheses that political connections matter the IPO milestone. The dependent variable is a dummy variable that takes the value of one if the venture capital backed-up firm is IPO, and zero otherwise. Regressions (1)–(4) report the results from the fixed-effect analysis for each types of political connections with innovative efficiency measured by / & ; on the other hand, regressions (5)–(8) report the results when firm innovative efficiency is measured by /
& . Note that innovative efficiency variables are logarithmic transformed following method suggested by Lerner (1994) and Hirshleifer, Hsu and Li (2013) because the distribution of those measures are usually highly-skewed. Specifically, this paper use 1
& and 1
& in the regression. The standard error of each variable is reported
in the brackets below the coefficient.
5.1 Effect of Venture Capital Reputation
First of all, the results show that there is a positive and statistically significant probability of firm reaches the IPO milestone if it’s being backed-up by venture capital which possesses internationalism. This relation holds irrespective of the measures and types of political connections used in the regression. On average, for those new entrepreneurial firms backed-up by internationalized venture capital, the odds of reaching their IPO milestone are multiplied by 1.95. This paper shows consistent results with various literatures proving evidence that venture capital reputation do help in adding firm values
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(Hsu, 2004; Gompers and Lerner, 2005; Nahata, 2008; Krishnan, Ivanov, Masulis and Singh, 2011; Chemmanur, Krishnan and Nandy, 2011). This then raises the question: Whether firm's innovation efforts impact its valuation as well as venture capital reputation?
5.2 Effect of Firm Innovative Efficiency
This paper then analyzes the impact of firm’s innovative efficiency on the IPO milestone. Results indicate a positive and statistically significant relation between both innovative efficiency measures and the IPO milestone. Consistent with Hirshleifer, Hsu and Li (2013), innovative efficiency measured with number of patent granted impacts greater than that measured with number of citations; however, this paper uses number of patent applications instead of number of patent granted in the measurement of firm’s innovation output. In unreported results, this paper find that innovative efficiency measured with number of patent applications impacts even greater than that measured with number of patent granted. One might underestimate firm’s innovative output by choosing its number of patent granted or number of citations because of ignoring those rejected patents with R&D inputs. Also, results hold irrespective of the measures and types of political connections. On average, the odds of reaching firm’s IPO milestone are multiplied by 1.38 for each one-unit increase in firm’s innovative efficiency. All these effects are significant at 1%.
5.3 Effect of Political Connections
Finally, the most interesting finding in this paper is that political connections may not necessarily support firms in reaching their IPO milestone.
Results in Table 4 show that political connections are statistically significant in consistent with the conclusion of Faccio (2006) that connections are particularly common in countries with highly corruption.22 Corruption Perception Index (CPI), Global Corruption Barometer (GCB) and Index of Economic Freedom (IEF) indicate that the most corrupt institution in Taiwan is its political parties and its worse ranking; and hence, show evidences that Taiwan is seriously in a weak institution.
Regressions (1)–(4) and Regressions (5)–(8) indicate that political connections between entrepreneurial firms and National Development Fund
22 2013 Global Corruption Barometer (GCB, Transparency international) shows Taiwan is the 18th worst corruption country. Also, PERC’s 2014 Report indicate Taiwan is the 3rd worst corruption country in Asia.
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(NDF) are positive and statistically significant. Entrepreneurial firms connect with the NDF get a higher likelihood to enhance their value and hence achieve its entrepreneurial IPO milestone in Taiwan. This result is similar with past practical studies suggesting that political connections do benefit the society in weak institutional economies (Johnson and Mitton, 2003; Li et al., 2008;
Berkman, Cole and Fu, 2010; Chen et al., 2011).
Nonetheless, political connections between venture capitals and National Development Fund (NDF) are a completely different story. In the analysis of firms whether achieve their IPO milestone, this paper observes a decreasing effect of venture capital political connections. Specifically, based on Regressions (1)–(4), this paper finds that the coefficient of type 1 venture capital political connection is around -7% and is not significant, which decreases to around -200% at the 1% significant level.23 Similar results are found in Regressions (5)–(8). This finding further highlights the role of government in venture capital industry. In this paper’s results, venture capitals with a higher political connection usually invest in firms that have a lower likelihood to reach their IPO milestone. As discussed in the introduction of this paper, choices are often driven by political considerations or rent-seeking activities in market-oriented economies. In the case of venture capital and the NDF, the investment targets of venture capital may be strongly biased in favor of political considerations such as coordinating with national development policy in fostering industries or even bureaucrats’ willingness to abuse their powers when the connections are too close.
Overall, the analysis of political connection in this paper suggests that political connections do benefit the venture capital industry when connections are not too close. While the reputation and firm innovative efficiency are positively correlated with the probability of firm’s IPO, the political connections play a significant but tricky role in the entrepreneurial IPO milestone. Specifically, firms’ political connections affect their IPO milestone positively; however, venture capitals’ political connections are adversely related with the probably of the IPO milestone. When government intervenes too far in venture capital industry, bad things may happen due to rent-seeking activities in consistent with the result of Fan et al. (2007). Other unreported regressions give the same conclusion thus are ignored in this paper.
23 Note that type1 connection, type2 connection and type 4 connection is in a monotonically increasing relationship. Type1 connection is for same school; type2 is for same school and same degree; type 3 is for same school and same time; type 4 is for same school and same degree at the same time.
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Table 4.
Regression Results.
This table reports the contingent fixed-effect logit regression results using IPO as dependent variable
Explanatory variable (1) (2) (3) (4) (5) (6) (7) (8) Internationalization 0.66** 0.66** 0.67** 0.64** 0.67** 0.67** 0.69** 0.67**
(0.27) (0.27) (0.28) (0.27) (0.29) (0.29) (0.29) (0.29)
1 & 0.40***
(0.24) (0.24) (0.24) (0.24) (0.25) (0.25) (0.25) (0.25)
_ 1 1.25*** 1.22***
(0.35) (0.36) (0.32) (0.32) (0.37) (0.37) (0.34) (0.33) f_ustop 1.54*** 1.59*** 1.41*** 1.35*** 1.53*** 1.59*** 1.45*** 1.38***
(0.25) (0.25) (0.25) (0.25) (0.26) (0.26) (0.26) (0.26) fNCCUBaep -0.29 -0.28 -0.24 -0.23 -0.19 -0.19 -0.13 -0.13 (0.27) (0.27) (0.27) (0.27) (0.30) (0.30) (0.30) (0.31) fMBA 1.54*** 1.58*** 2.29*** 2.28*** 1.29*** 1.27*** 2.02*** 2.03***
(0.40) (0.40) (0.38) (0.38) (0.41) (0.41) (0.38) (0.38) fScience -2.39*** -2.34*** -1.86*** -1.87*** -2.50*** -2.52*** -2.00*** -2.00***
(0.45) (0.45) (0.42) (0.42) (0.47) (0.47) (0.44) (0.44) vc_twtop 1.15 1.45 2.39*** 2.24*** 2.11** 2.37** 3.23*** 3.12***
(1.09) (1.07) (0.82) (0.83) (1.04) (1.04) (0.83) (0.83) vc_ustop 0.18 0.16 0.78* 0.73* -0.08 -0.09 0.55 0.53
(0.40) (0.41) (0.41) (0.41) (0.44) (0.45) (0.45) (0.45) vcNCCUBeap 1.05** 1.04** 1.18*** 1.17*** 1.07** 1.05** 1.23*** 1.22***
(0.42) (0.43) (0.43) (0.42) (0.44) (0.44) (0.45) (0.45) vcMBA -2.10 -1.96 -1.82* -2.06* -2.95** -2.80** -2.60** -2.80**
(1.31) (1.29) (1.09) (1.11) (1.29) (1.27) (1.09) (1.10) vcScience 0.52 0.65 1.54 1.33 -0.53 -0.35 0.53 0.45
(1.10) (1.10) (1.04) (1.05) (1.14) (1.14) (1.07) (1.08) IPO_mkt 0.01*** 0.01*** 0.01*** 0.01*** 0.01*** 0.01*** 0.01*** 0.01***
(0.00) (0.00) (0.00) (0.00) (0.00) (0.00) (0.00) (0.00) Syn 0.13 0.12 0.06 0.08 0.78** 0.80** 0.64* 0.67*
(0.31) (0.31) (0.32) (0.32) (0.36) (0.36) (0.37) (0.37) AR 1.29*** 1.30*** 1.36*** 1.34*** 1.28*** 1.30*** 1.39*** 1.37***
(0.11) (0.11) (0.11) (0.11) (0.12) (0.12) (0.12) (0.12)
Number of Observations 5409 5409 5409 5409 4834 4834 4834 4834
“ *** “, ‘‘ ** ’’ and “ * ” indicate significance at the 1% level, 5% level, and 10% level, respectively.
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