政治連結對於新創企業公開發行的影響：以台灣創業投資產業為例 - 政大學術集成

全文

(1) . 國立政治大學經濟所碩士論文 Department of Economics National Chengchi University Master Thesis. 政治連結對於新創企業公開發行的影響：以台灣創業投資產業為例 Political connections under the IPO process of new ventures: Evidence from Taiwanese venture capital industry. 指導教授：李文傑、王信實 Advisor：Prof. Wen-Chieh Lee、Prof. Shinn-Shyr Wang 研究生：黃敬堡 Graduate： Jing-Bao Huang 中華民國一百零四年六月 June, 2015 1 .

(2) . Acknowledgement For all the constructive and improving suggestions on the early version of the article, I am indebted to all the committee members, Konan Chan, Wei-Yu Kuo, Chih-Hai Yang, Ching-Fu Chang, Wen-Chieh Lee, and Shinn-Shyr Wang. I also benefited from discussions with Po-Wei Hsiang and Chia-Wei Wang on the dissertation topic regarding data collection, construction and standardization. My best gratitude would be given to financial support for this venture capital research from Professor Konan Chan and Professor Wen-Chieh Lee. Last, and most importantly, I would like to thank all people associated with the collection and initial constructing of the data in the National Chen-chi University master theses, Oliver (2013) and Ryan (2013). Full acknowledgements to Oliver and Ryan kindly sharing their hand-collecting corporate social background database that accompany the venture capital’s financial investment records in Taiwan.. 2 .

(3) . Abstract This paper investigates how the political connections work on information dissemination in venture capital markets. The political connections are formed among new ventures, venture capitals measured by whether their directors or supervisors have the same educational backgrounds as those of the Taiwanese National Development Fund (NDF) board members. The political connection is hypothesized to affect the entrepreneurial Initial Public Offering (IPO) milestone in different connection settings. By using Taiwanese domestic venture capital investment records, this paper shows how reputation, firm innovative efficiency and political connections have impacts on the startup’s IPO. 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.. Keywords: Venture capital; Political connections; Initial public offerings (IPO); Innovative Efficiency; Taiwan. 3 .

(4) . 摘要本研究探討政治連結如何成為創業投資產業中資訊傳遞的橋樑，其中政治連結的指標分別由新創企業和創投董監事的教育背景，是否和國家發展基金委員會成員的教育背景有關係來定義。實證結果顯示政治連結透過不同的緊密程度對新創企業公開發行的里程碑造成影響。透過梳理過去發生在台灣的創投投資案記錄，本研究發現創投名聲和企業的研發效率對企業的初次公開發行有正面的影響。另外，政治連結在新創企業公開發行的里程碑上，扮演著相當有趣的角色。企業自身的政治連結確實有助於企業達到初次公開發行的里程碑；然而，創投的政治連結卻對企業的初次公開發行有負面的影響。. 關鍵字: 創業投資; 政治連結; 初次公開發行 (IPO); 研發效率; 台灣. 4 .

(5) . Content. 1.. Introduction 1.1 The Venture Capital Industry. .................................................................1. 1.2 Double-Sided Information Asymmetry Problem. ...................................1. 1.3 Mechanisms to Resolve Information Asymmetry. ..................................2. 1.4 Information Dissemination Channels. ....................................................3. 2.. Motivation and Institution Background. 3.. Hypothesis and Methodology. 4.. Data, Sample Selection, and Construction of Variables 4.1 Data Construction. ..........................................................................9. ................................................................................ 11. 4.2 Sample Selection Criteria 4.3 Variable constructions. ...........................................................7. ....................................................................13 ..........................................................................13. 4.4 Descriptive Statistics and Correlations 5.. ................................................18. Regression Analysis and Results 5.1 Effect of Venture Capital Reputation. ...................................................20. 5.2 Effect of Firm Innovative Efficiency. ...................................................21. 5.3 Effect of Political Connections. ............................................................21. 6.. Conclusion .........................................................................................................24. 7.. Appendix ............................................................................................................25. 8.. References ..........................................................................................................28. . 5 .

(6) . 1. Introduction 1.1 The Venture Capital Industry Promoting business with highly uncertainty is risky. As economic conditions well-recovered from the financial crisis, the increasing liquidity in the market and a more positive go public environment strengthen venture capitalists confidence in the global market, resulted in the rapid development of venture capital investment compared to before. With the tremendous boom of global venture capital activity, it is possible to discern great resemblance among venture capitalists and to group the processor pattern under equivalent functions: 1) investment screening; 2) process of due diligence; 3) structuring of the investment; 4) monitoring and adding value to the investment; 5) portfolio management and exit. Each procedure of the above functions requires particular skill 1 for venture capital to identify disruptive technologies of new entrepreneurial firms that have the capability to yield a significant return – something like 20x the original investment over five years. Nonetheless, investment prospects with potentially high-reward are scarce. Uncertainty and information asymmetry often characterize these young organizations; thus, venture capital usually copes with uncertainty by linking together in a social network so as to gather information. Through connections in the network, those linked groups gain the upper hand in risk diversification, sharing asset allocation strategies and having greater opportunity invest in companies with good prospects.. 1.2 Double-Sided Information Asymmetry Problem As Bygrave (1987, 1988) observes, the amount of co-investing by a firm is positively correlated with the level of the uncertainty it shoulders. He shows that high innovative technology companies (HIVCs)2 comprise a more rigid connection than low innovative technology companies (LIVCs) 3 because of facing more uncertainty. Fortunately, information asymmetries are double sided problems in venture industry (Trester, 1998; Schmidt, 2002; Kanniainen and Keuschnigg, 2003; Hellmann, 2006; Bernile et al., 2007). Not merely do investors look forward to                                                         1. As Gompers and Lerner (2005) mentioned, those skills are difficult and time-consuming to acquire. 2 See Bygrave (1988). The top 21 venture capital firms that invest mainly in high innovative technology companies are called HIVCs. 3 See Bygrave (1988). The top 21 venture capital firms that invest mainly in low innovative technology companies are called LIVCs. 1 .

(7) . coping with the uncertainty, but individuals or new entrepreneurial firms pursuit for stable financing sources throughout the life cycle of entrepreneurial companies from seed to mature stage. To date, accumulated evidence in literatures shows that individuals or new entrepreneurial firms, especially in the early-stage4 employ a wide variety of social capital pursuing for investment from venture capitals (Venkataraman, 1997; Shane, 2000). On the other hand, booming venture activities draw plenty of attentions to potential investors, forward-looking entrepreneurs, and even policy makers. Gompers and Lerner (2005) suggest, conflict of interest also generally emerges between entrepreneurs and investors, which is a form of information asymmetry attributed in the past bilateral conflicts studies. This problem of information asymmetry makes it difficult to evaluate companies and causes opportunistic behaviors either by entrepreneurs or by investors after the company is financed, and even hinders the potential investment match between investors and start-up managers even more seriously. Since Akerlof (1970), investors has faced highly uncertainty toward the entrepreneur. Most investors can only evaluate the companies by the performance of new entrepreneurial firms within a target industry on average. Consequently, this phenomenon would possibly drive the good new entrepreneurial firms out of the industry and then end up with those lemon new entrepreneurial firms in the industry.. 1.3 Mechanisms to Resolve Information Asymmetry Generally speaking, there is a large literature which is concerned with Information Economics that have merged with theoretical research on venture finance and have given plenty mechanisms to resolve adverse selection and moral hazard incurred in the venture industry. Such as optimal capital structure decisions in venture capital finance, optimal incentive contracts with convertible preferred equity and contingent control rights5. Pioneers of agency cost in for finance (Jensen and Meckling, 1976; Carleton and Cooper, 1976; Leland and Pyle, 1977) emphasized how new entrepreneurial firms and venture capitals restrain the diversion of project quality with making continuation decisions under information asymmetries.                                                         4. In this paper, companies are defined in the early-stage in which having testing or still developing products and are able to begin operations but are not fully prepared at the stage of commercial and generating revenue. 5 As Hart and Moore (1999) noted, nowadays it is hard to distinguish between specific and residual rights, and in fact equates residual rights with complete control rights. 2 .

(8) . As Gompers (1995) and Neher (1999) both argue6, staging the capital infusions do help venture capitals mitigate the possibility of hold-up problem7 or repudiation by the entrepreneur; however, Neher (1999) focus on staging as strengthening venture capitals’ ability in diminishing hold-up problem whereas Gompers (1995) focus on staging as a reinforcement in monitoring entrepreneurs. Chan et al. (1990), Hansen (1992), and Boot and Thakor (1993) derive the optimal capital structure by debt-equity issuance decision and explain the optimal transition of control in well-devised agency models. Trester (1998) demonstrates that the preferred stock investment is the dominant strategy contract in venture capital financing. Hence suggesting policy makers ponder over actions conductive to stock equities, such as reducing or eliminating the double taxation of dividends 8 so as to facilitate development of venture industry. In the study of Admati and Pfleiderer (1991), entrepreneurs and venture capitalists consider project contingency at each stage in the project’s development, showing that fixed-fraction equity contracts9 are highly possible for inside investors, such as venture capitalists, to resolve a wide variety of multi-stage information asymmetry problem and to make optimal investment decisions. Misprice securities incentive erupts in later financing rounds; therefore, choice of securities to disclose all private information may not likely to be true.. 1.4 Information Dissemination Channels New ventures usually pursuits for a high level on financing stability throughout the life cycle of entrepreneurial company from seed to mature stage; nonetheless, theoretical discussions leave this issue out of consideration for long on this challenging research. Economic analysts point out that compiling superior information is the access to conspicuous investment performance in markets with high risk and uncertainty (e.g., Kaplan, Martel, and Stromberg, 2003; Hochberg, Ljungqvist, and Lu, 2007; Cohen, Frazzini and Malloy, 2008; Cohen, Frazzini and Malloy, 2010). Consequently, raising the following question: What are the factors                                                         6. Neher (1999) extends the model in the spirit of Admati and Perry (1991) to stage financing as an approach to determine the optimal investment path. 7 Hart and Moore (1994) point out that human capital takes the form of inalienability. Studied in Hart and Moore (1994), suppose that physical assets, such as cash, properties, equipment, owned by entrepreneur need to be transferred to investors once entrepreneur repudiate the contract . If physical assets are valueless without entrepreneur, then entrepreneur wins the bargaining power in the subsequent investment round. In a sense entrepreneur can “hold-up” investors after receiving financing from them. 8 Debates on elimination of double taxation of dividends have already persisted for decades. (e.g., Litzenberger and Ramaswamy, 1979; Bradford, 1981; Bagwell and Shoven, 1989; Trester, 1998) 9 As Admati and Pfleiderer (1991) defined, investors receive fixed fraction of project’s payout and finance fixed fraction of investment in the future under fixed-fraction contract. 3 .

(9) . that enable some entrepreneurs successfully obtain investment flow from venture capitalists even policy makers while others fail? To explore this question, Venkataraman (1997) concludes that cooperative relationships based on integrity and prior experience do help diminishing adverse selection and moral hazard problems intimate with economists; and hence, shows one of the most effective ways for information disseminating in new venture industry. Following basic ideas suggested by Venkataraman (1997), for example, Shane and Cable (2002) integrate in-depth field interviews and show that social ties actually provide an information dissemination mechanism allowing new entrepreneurial firms without high-capital endowments obtain financing to pursue entrepreneurial opportunities in the creation of global innovation and economic growth. However, Huber and Power (1985) and Golden (1992) indicate that retrospective recall bias10 incurred by field interviews are inevitable pitfalls in various reasons. For instance, attempts to retain socially superior image or their self-esteem, incentive to distort past experiences and even the hindsight bias and so on. Cohen, Frazzini and Malloy (2008) comments that evaluating or verifying social capital designs and mechanisms are the leading concern in information dissemination under market with wide varieties of risk and uncertainty, such as new venture investment business incurred by entrepreneurs and investors; therefore, they provide evidence in showing that network links formed through education give a natural framework to predict the flow of private information into stocks between portfolio managers and firm senior officers. Stam, Arzlanian and Elfring (2014) employ meta-analysis11 to synthesize longitudinal research social capital results. Consequently, once again enhance comprehension of the adding value of cultivating social capital for small firms and reveal that multiple networking strategies are required at different points in time and in different industries and countries. On the other hand, reputation and its effect on facilitating the information dissemination to reveal the true qualities of entrepreneurship12 is also a pivotal topic in recent economic and corporate finance studies. Process of reputation accumulation builds up relationships of credibility with a wider variety of sources and defines a corporate’s identity in its competitiveness and capacity. For this reason, reputation research has been theoretically and practically discussed in wide economics and market organization fields in the long run. (Kreps and Wilson, 1982;                                                         10. See some classical examples in Stott (1958). Hunter and Schmidt (2004) comment that the use of meta-analytic method helps in clarifying and making sense of the research literature. It not only demonstrates the cumulative knowledge that is there but provides more specific directions about what the remaining research needs are. 12 Venkataraman (1997) defines entrepreneurship as a talent in discovering, creating, and exploiting entrepreneurial opportunities while others cannot or do not. 11. 4 .

(10) . Shapiro, 1983; Allen, 1984; Yoon, Guffey and Kijewski, 1993) Concepts of venture capital reputation in past studies have shown up in diversity, such as age, Initial Public Offerings (IPO) market share, and number of investment rounds (Megginson and Weiss, 1991; Gompers, 1995; Gompers, 1996; Gompers and Lerner, 2005; Nahata, 2008; Krishnan, Ivanov, Masulis and Singh, 2011). Not only venture industry highlight the great importance of reputation on understanding the implicit and explicit contracts, previous studies also provide evidence that other industries matters. In this study, however, it aims to bridge information dissemination between venture capitalists and new entrepreneurial firms by examining the roles of directors’ and supervisors’ networking building. So far, theoretical or empirical studies have addressed abundant information dissemination issues using reputation mechanism. Compared to reputation, less empirical work is done by social capital mechanism in venture capital issues, especially in political network connection field. One of the main reasons for economists suffer setbacks in government research is the frustrating data access from sources. Ex-ante, one may have believed that political-connected firms are subject to better scrutiny structure and governance; therefore, political connections would, in fact, be associated with better firm performance and quality. However, this is not the case at all. Previous studies in public choice literature discover that government interference in business activities makes economy more severe under weak financial and legal institution constraints while political connection may benefit the society. (Shleifer and Vishny, 1994; Fan, Wong and Zhang, 2007; Li et al., 2008; Woods, 2009) In market-oriented economies, choices even may have been driven by political considerations or rent seeking activities, taking forms such as bribery, corruption, campaign finance, smuggling, and black markets (Krueger, 1974; Venkataraman, 1997; Faccio, 2006; Fan, Wong and Zhang, 2007). Cross-country and country-specific event studies show that presence of political connections indeed affect economic outcomes; therefore, entrepreneurs usually have high incentives to build networks with politicians or governments. Beck and Levine (2002) and La Porta et al. (2002) both argue that government-owned banks (in another words, well-politically-connected banks) enable politicians to further their own political targets by financing the inefficient but politically desirable industries. As a result, government ownership of banks is related to a lower level of economic growth and financial development and may cause a higher likelihood of banking crisis. Fisman (2001) conducted a unique event study suggesting that an estimated 25 percent of the market capitalization of firms in Indonesia is related to the connection level of former Indonesian President. 5 .

(11) . Suharto.13 He analyzed the share price return drops in the firms highly-connected to President Suharto and discovered that the large decline proportion is attributed to series news announcements (or even rumors) of the President Suharto's health state. Chaney, Faccio and Parsley (2011) reveal that the presence of political connections is significantly negatively related to the quality of accounting information. Their evidence shows that political connections have incremental explanatory power beyond country and firm-specific characteristics, and that firms with tighter political connections have the poorer quality accounting earnings information. Despite the accumulation of theoretical and practical studies on political connections and its negative effects, other literatures show that cultivation of political connection still can have positive effects in the enhancement of firm’s value in transition economies or weak institutional countries. Entrepreneurs in transition economies such as China often encounters hindrance 14 in running their own businesses due to the lingering market-supporting institutions; therefore, incentive for entrepreneurs to establish political connections arises in order to overcome these market or state failures. As Li et al. (2008) indicated, entrepreneurial firms connect with Communist Party get a higher likelihood to enhance their performance and value in the weak institutional environment of China. A number of other papers also take an event-study approach and find similar results. (Johnson and Mitton, 2003; Berkman, Cole and Fu, 2010; Chen et al., 2011) Although vast evidence of positive performance effect contributed by government intervention in China is summarized, Fan et al. (2007) have already shown that highly political-connected firms’ accounting performance is poorer relative to their politically unconnected counterparts. That is to say, Fan et al. (2007) point out when government intervention goes too far, bad things happen due to rent-seeking activities. The remainder of this paper proceeds as follows. Section 2 shows the motivation for studying in this topic. Section 3 develops the hypotheses and the methodology. Section 4 describes how the database is manually compiled and sources. And then describe how the key variables are constructed and provide descriptive statistics. Regression outcomes and results are documented in Section 5. Section 6 summarizes the study and provides some concluding remarks..                                                         13. Despite the commonly held belief that every political connection is inherently worthwhile, literatures shows that the value of political connections varies significantly across country-level. (Fisman, 2001; Faccio, 2006; Faccio, Masulis and McConnell, 2006) 14 For instance, worse infrastructure (telecommunications, roads, electricity, water supply, etc.), unclear tax regulations, weak property rights institution. 6 .

(12) . 2. Motivation and Institution Background Generally speaking, past literatures do document different ways of information dissemination suggesting that fund managers and stock analysts benefit from connections with key persons that possess inside information of target firms’ prospects; nonetheless, relatively less work is done in the venture capital industry. How do venture capital markets relate to social capitals as an information dissemination mechanism? In the intuition, the long-established social networks should act as a catalyst to the settlement of information asymmetry problems; therefore, the process of venture capital development may contain social capital as a "factor" of production in a large extent. Taiwan is in a unique situation being the relatively low corruption country having neighbor countries that are dominated by high corruption, such as China and Philippines. The environment of Taiwanese political corruption, the likelihood of firm’s behavior in rent-seeking activities, the willingness of government officials to abuse their powers, may become severe as the shared social and cultural environment and the continuing increase in Cross-strait investments with China.15. CPI Score. As a result, Taiwan provides an interesting natural experiment for this study. 100 90 80 70 60 50 40 30 20 10 0. Year Taiwan CPI Score. China CPI Score. Figure 1. CPI Scores of Taiwan and China over time. Using a scoring methodology from 1 (cleanest) to 100 (most corrupt). Source: Transparency International. Figure1 shows the Corruption Perception Index (CPI)16 of Taiwan and China                                                         15. In 2000, total trade between Taiwan and China was only 18.5 billion U.S. dollars. However; by 2014, trade values between the two sides reached 198.31 billion U.S. dollars, representing a compound annual growth rate of over 18 percent. 16 Chaney, Faccio and Parsley (2011) also use the CPI index as their corruption control variable with measurement 1-10. 7 .

(13) . calculated by Transparency International (TI). 17. , a global non-government. CPI  Ranking Percent (%). organization, provide an annual index that scores countries and territories based on the perceived level of public sector corruption. The CPI scores indicate that Taiwan’s corruption level follows the trend with China; thus, give evidence in a weaker institutional environment in the future of Taiwan. Figure 2 shows the CPI ranking scaled by the total countries around the world and gives the same result as Figure 1. 100 90 80 70 60 50 40 30 20 10 0. Year China Ranking Percent. Taiwan Ranking Percent. Figure 2. CPI Ranking Percent of Taiwan and China over time. A lower percent CPI Ranking indicates a lower corruption level over the world. Source: Transparency International. Since the main topic here is to discuss how the social capitals, especially political networks act as an information dissemination channel in venture capital industry, this paper attempts to examine the political connection of firms and venture capitals with National Development Fund in Taiwan. The Taiwanese National Development Fund (NDF), a fund founded in 1973 by government and in alignment with Taiwan‘s strategic development directions. Acting as venture capital and private equity in specializing in seed, start up, restructuring, and mergers and acquisition investments, the mission of the NDF is to play an important role in spurring private investments and speeding up high value-added innovation in industries. As Figure 3 shows that the NDF investments break into two parts: 1) directly investments to enterprises and 2) indirectly investments to venture capitals. By the end of 2013, the NDF holds equity stakes in 40 enterprises, excluding those already divested, account for a 50 percent are already IPO. In support of the promotion of the venture capital, 62 venture capitals are                                                         17. For more information about CPI visit https://www.transparency.org/ 8 . .

(14) . invested by the NDF with re-investments in a total of 2,893 enterprises.. Figure 3. The Taiwanese National Development Fund investment structure and real effects constructed by this paper.. However, past reports and released news indicated that NDF usually encounters financial loss in their investment portfolios; and hence raising questions about what is really happening in the process of NDF’s portfolio selection and evaluation. For reasons outlined above, the intention of this study is to come up with a model that can explain relationships among types of political network links from the Taiwanese National Development Fund and firm performance. And eventually, provide a better specified empirical model shedding some light on the unraveling of the venture capital investment black box.. 3. Hypothesis and Methodology In this section, the main hypothesis is described regarding the role played by venture capitals and new entrepreneurial firms in political connection cases. For the sake of accessing superior information in those high risk and uncertainty markets, both venture capital and venture capital backed firms would cultivate political network linkage with the policies makers (even bureaucrats) or those who have final 9 .

(15) . word in the policy directions as suggested in Cohen, Frazzini and Malloy (2008, 2010). Overall, the logic suggests the following null hypotheses:. Hypothesis 1: The venture capital backed-up firms with political connections will perform better in terms of exit (IPO events).. Hypothesis 2: The venture capitalists with political connections will perform worse in terms of exit (IPO events). This paper employs multivariate analysis to test the hypotheses and investigates the association between terms of exit and political connections by performing contingent fixed-effect logistic analysis of IPO events against alternative political connection definition. Therefore, the empirical model used in this paper is expressed without constant term in the following main function:. . 1 1 where. 1. . ,. ,. ,. ,. ,. ∀. ∈ 1,2,3,4. The subscript i indexes each venture capital backed-up firm in the dataset extended from year one. Based on the proposed hypotheses, Y indicates the venture capital backed-up firms achieved the IPO milestone. A Y dummy takes on a value of one when a new entrepreneurial firm is IPO, and zero if otherwise. Specifically, the constructed dataset here is utilize from year one; focusing on venture capital backed-up entrepreneurial firms. The hypothesis test on Initial Public Offering events will use the samples from the full dataset excluding 101 venture capital backed-up firms that haven’t achieved the IPO milestone. This paper also deals with potentially biased standard errors suggested by Petersen (2009). In addition to the control variables of characteristics of the new entrepreneurial and venture capitalists ( firms , , , the main variables of interest within the above function are the firm political connection measures ( , ) and venture capital political connection measures ( , ). Similar to the metric defined in Oliver (2013) and Ryan (2013) to measure educational connectedness, 10 .

(16) . this paper defines four types of the political connections (. ,. ), measured as. whether the National Development Fund board members and new venture’s directors and supervisors: attend the same school ( type 1 connection ), attended the same school and received the same degree ( type 2 connection ), attended the same school at the same time ( type 3 connection ) and attended the same school and received the same degree at the same time ( type 4 connection ). Following the same logic, this paper defines four types of the political connections ( , ), measured as whether the National Development Fund members and venture capital managers: attend the same school ( type 1 connection ), attended the same school and received the same degree ( type 2 connection ), attended the same school at the same time ( type 3 connection ) and attended the same school and received the same degree at the same time ( type 4 connection ).. 4. Data, Sample Selection, and Construction of Variables 4.1 Data Construction The empirical evidence provided in this study is derived from several databases: 1) Social background for members in venture capital invested firms and venture capital; 2) stock market and financial data for companies traded on the Taiwan Stock Exchange (TWSE); 3) historical data of patent applications and citations for selected companies; 4) data on the joined venture capital affiliations of venture capitals in the selected seven countries. 5) Social background for board members in the specific government fund as a measurement of the political connection of the selected companies. First of all, I employ a large firm-level dataset on corporate social background data developed by Oliver (2013) and Ryan (2013). One of the main challenge with studying the social networks between venture capital and entrepreneurial firms is that no database that contains comprehensive information on social capital of founders and venture capital partners; however, Oliver (2013) and Ryan (2013) overcome this limitation by a hand-collecting hard work and hence create a unique database by merging information from sources 18 . They focus on the historical                                                         18. Oliver (2013) and Ryan (2013) start with tracking comprehensively the venture capital investment histories from the year of 1985 in VentureXpert database, which includes all the self-reported registered venture capital funds in the world. Focusing the analysis on actively Taiwanese venture capital funds with investment records listed in the VentureXpert, they manually check all funds and exclude those without any investment records in Taiwan. With those venture capital and venture capital backed-up firms, they obtain the names of individual board members from Commerce Industrial Services Portal data link provided by the Ministry of Economic Affairs in Taiwan and start constructing biographical information on web pages by 11 .

(17) . investment link between venture capitals and new entrepreneurial firms in the Taiwanese venture capital industry to track for the bilateral social connections. As an improvement of this database, this study collected the missing biographical information from web pages, prospectus, news reports, financial magazines even telephone interviews or in-depth personal interviews conducted by employing part-time workers. In addition, the venture capital characteristics taken from the database are cross-checked by comparing them with the information on the Taiwan Venture Capital Association (TVCA) yearbook. Second, I use Taiwan Economic Journal (TEJ) database in collecting firm annual accounting data for the variable constructing as well as in firm specific characteristics. In addition to firm R&D expenses data, stock returns data and other performance indicators (Sales, Return on assets (ROA) and Return on Equity, etc.) are also collected for extend study in the future. Third, for the purpose of considering firm innovative efficiency I bring together three datasets and merge their all patent application, all patent granted and all patent citation data via an elaborate matching process: the first is the US Patent and Trademark Office (USPTO) database; the second is the Mtrends database; the third is the NBER patent database19. The matching of three databases by firm name tied up this research for a long time as a great deal of spelling mistakes in the names and some bewildering abbreviation. Fourth, a surprising fact in the past studies is noticed that venture capital internationalization exposure has very less included in the discussion of VC reputational impact. As Ardichvili et al. (2003) and Fernhaber and McDougallCovin (2009) both indicate that new ventures with greater stocks of international knowledge are easier to spot opportunities and thus having higher probability to reach the entrepreneurial milestone (IPO) in areas where they have experience and are knowledgeable. Multi-market exposure of venture capital investment experience may have better mixed effect between global investment talents and some local features. That is to say, a venture capital with international branches or knowledge is in a position to have strong capability in pushing local new ventures to succeed. Specifically, the venture capital cross-country investment experience should be a promising indicator to shed light on the unexplored field in reputation studies. In view of above mentioned perspectives, I construct an internationalization database for worldwide venture capital from VentureXpert database. This database contains of 52 worldwide venture capital associations listed in VentureXpert and all of its                                                                                                                                                                    employing part-time workers. 19 Hall, Jaffe, and Trajtenberg (2005) originally developed an updated NBER patent database and is available to download at https://sites.google.com/site/patentdataproject/Home/downloads. 12 .

(18) . venture capital members. Thus, one can discern whether a venture capital joined more than one venture capital association; and hence, define its status of internationalization. Finally, the most important contribution in this research is the constructed government fund member list and their social backgrounds. The Taiwanese National Development Fund is considered to be the political connection target here. This paper focus on the three board members of National Development Fund, including management committee, investment review committee, and venture capital investment review committee. Biographical information of board members is collected manually from web pages, news reports, press releases and proprietary surveys similarly done in venture capital industry.. 4.2 Sample Selection Criteria The final constructed dataset contains 390 domestic investment records in Taiwan, including 40 active venture capital management firms, 223 venture capital backed firms and one government fund. Nonetheless, the main issue in this paper is trying to test the certification role of government fund as well as venture capitals in the entrepreneurial milestone in the life of a firm, that is to say IPO. Consequently, those venture capital backed-up firms without reaching its entrepreneurial milestone are excluded by performing contingent fixed-effect logistic regression in this study. After eliminating those firms without Initial Public Offering, the remaining dataset consists of a total of 6520 samples with 289 domestic investment records inside. Each venture capital backed-up firm in the dataset is extended from year one; and hence, connections are also calculated by years from year one.. 4.3 Variable constructions Prior to reporting the regression results, one may need to know the definitions and frequency of the variables used in this paper. Table 1 describes the key variables as well as a number of firm and venture capital characteristics. Among various variables used in this paper, Network Connectedness Measure and Firm Innovative efficiency Measure are relatively complicated than others; therefore they are both described in detail next. Due to the connection to an academic university is defined as one has received a degree in a university; thus one is able to find that multiple academic institutions are connected between to organizations. In view of above mentioned reason, four types of the network connection is defined in this paper measured as whether the 13 .

(19) . directors and supervisors between two organizations: attend the same school (type 1 connection), attended the same school and received the same degree (type 2 connection), attended the same school at the same time (type 3 connection) and attended the same school and received the same degree at the same time (type 4 connection). As regards the Innovative Efficiency, this paper measures venture capital backed-up firm ’s innovation output as: 1) the number of patent applications in year and 2) the accumulated patent citations in years 1 to 5. Similar to Hirshleifer, Hsu and Li (2013)20, Innovative Efficiency in year is measured as two proxies in here: 1) / & and 2) / & . / & is defined as the number of firm ’s patent applications in / & year scaled by its R&D capital21 in year . Specifically, is defined as in the following function:. ∑. & where. & . ,. 1. ,. 0.2. & . , ,. denotes venture capital backed-up firm. ’s R&D. expenses in fiscal year ending in year . On the other hand, / & is defined as the number of firm ’s accumulated patent citations in years 1 to 5 scaled by its accumulated R&D expense in years 3 to 7. And hence, / & can also be specifically defined as in the following function:. & . ∑ ∑. & . ,. .. ,.                                                         20. Hirshleifer, Hsu and Li (2013) use the number of patent granted to firm in year as its first innovation output; however, this paper choose the number of patent applied in year . 21 R&D capital is calculated with a 5-year cumulative R&D expenses assuming an 20% annual depreciation suggested by Chan, Lakonishok and Sougiannis (2001) and Hirshleifer, Hsu and Li (2013). 14 .

(20) . Table 1 Definition of variables. This table reports the variables used in the regression analyses and their description. A detailed description of the construction of Firm Innovative efficiency Measure and Network Connectedness are in the main text.. Variable name. Data frequency. Variable explanation. Dependent variable: Exit IPO Venture Capital Reputation Internationalization. Constant. An index that is 1 for the invested company achieved IPO.. Constant. An index that is 1 for venture capital affiliated with at least two venture capital associations across countries.. Firm Innovative efficiency Patent/R&D Capital. Yearly. Citation/R&D Expenses. Yearly. The number of firm ’s patent applications in current year scaled by its R&D capital. The number of firm ’s accumulated patent citations scaled by its accumulated R&D expense.. Social network connectedness SN_T1. Yearly. SN_T2. Yearly. SN_T3. Yearly. SN_T4. Yearly. At least one of the directors and supervisors in the invested company and the venture capital firm graduated from the same school. True: 1 ; False: 0 At least one of the directors and supervisors in the invested company and the venture capital firm graduated from the same school and received same degree. True: 1 ; False: 0 At least one of the directors and supervisors in the invested company and the venture capital firm graduated from the same school at the same time. True: 1 ; False: 0 At least one of the directors and supervisors in the invested company and the venture capital firm graduated from the same school and received same degree at the same time. True: 1 ; False: 0. 15 .

(21) . Table 1 (continued) Variable name Firm Political connectedness _ 1.1. Data Frequency Yearly. Variable explanation. At least one of the directors and supervisors in the invested company and the board members in National Development Fund graduated from the same school. True: 1 ; False: 0. _ 2.1. Yearly. At least one of the directors and supervisors in the invested company and the board members in National Development Fund graduated from the same school and received same degree. True: 1 ; False: 0. _ 3.1. Yearly. At least one of the directors and supervisors in the invested company and the board members in National Development Fund graduated from the same school at the same time. True: 1 ; False: 0. _ 4.1. Yearly. At least one of the directors and supervisors in the invested company and the board members in National Development Fund graduated from the same school and received same degree at the same time. True: 1 ; False: 0. Venture Capital Political connectedness Yearly _ 1.1. At least one of the directors and supervisors in the venture capital and the board members in National Development Fund graduated from the same school. True: 1 ; False: 0. _. 2.1. Yearly. At least one of the directors and supervisors in the venture capital and the board members in National Development Fund graduated from the same school and received same degree. True: 1 ; False: 0. _. 3.1. Yearly. At least one of the directors and supervisors in the venture capital and the board members in National Development Fund graduated from the same school at the same time. True: 1 ; False: 0. _. 4.1. Yearly. At least one of the directors and supervisors in the venture capital and the board members in National Development Fund graduated from the same school and received same degree at the same time. True: 1 ; False: 0. Macro environment IPO_mkt. Yearly. The number of IPOs approved in current year 16 . .

(22) . Table 1 (continued) Variable name Firm feature f_twtop. Data frequency. Variable explanation. Yearly. At least one of the top five managers in the invested company graduated from the National Taiwan University, National Tsing Hua University, National Chiao Tung University, and National Cheng Kung University. True: 1 ; False: 0. f_ustop. Yearly. At least one of the top five managers in the invested company graduated from the Ivy League schools and the University of California. True: 1 ; False: 0. fNCCUBaep. Yearly. At least one of the top five managers in the invested company graduated from Baep of the National Chengchi University. True: 1 ; False: 0. fMBA. Yearly. The ratio of the top five managers having a MBA degree in the invested company. fScience. Yearly. The ratio of the top five managers having an engineering degree in the invested company.. AR. Yearly. Accumulated Rounds, the accumulated times of investment for the invested company. VC feature vc_twtop. Yearly. At least one of the top five managers in the venture capital firm graduated from the National Taiwan University, National Tsing Hua University, National Chiao Tung University, and National Cheng Kung University. True: 1 ; False: 0. vc_ustop. Yearly. At least one of the top five managers in the venture capital firm graduated from the Ivy League schools and the University of California. True: 1 ; False: 0. vcNCCUBaep. Yearly. At least one of the top five managers in the venture capital firm graduated from Baep of the National Chengchi University. True: 1 ; False: 0. vcMBA. Yearly. The ratio of the top five managers having a MBA degree in the venture capital firm. vcScience. Yearly. The ratio of the top five managers having an engineering degree in the venture capital firm. Syn. Yearly. Syndication, more than two venture capital firms jointly fund in the same investment project. True: 1 ; False: 0. 17 .

(23) . 4.4 Descriptive Statistics and Correlations Table 2 presents the summary statistics for the full dataset constructed by this paper including 40 active venture capital management firms, 223 venture capital backed firms and one government fund. Table 2 Summary statistics.. Variable. Observations. Mean. IPO Internationalization Patent/R&D Capital Citation/R&D Expenses SN_T1 SN_T2 SN_T3 SN_T4. 8175 8175 7216 6835 8170 8170 8170 8170. 0.412 0.400 0.512 0.997 0.432 0.423 0.296 0.283. POL_F1. 8170 8170 8170 8170 8170 8170 8170 8170 8175 8175 8175 8175 8175 8175 8175 8175 8175 8175 8175 8175. 0.489 0.476 0.336 0.325 0.580 0.580 0.562 0.560 0.476 0.058 0.197 0.180 0.278 0.582 0.092 0.507 0.262 0.208 129.862 0.028. POL_F2 POL_F3 POL_F4 POL_VC1 POL_VC2 POL_VC3 POL_VC4 f_twtop fNCCUBaep f_ustop fMBA fScience vc_twtop vcNCCUBaep vc_ustop vcMBA vcScience IPO_mkt Syn. Std.. Minimum. Maximum. Skewness. Kurtosis. 0.492 0.490 1.267 2.015 0.495 0.494 0.457 0.451. 0 0 0 0 0 0 0 0. 1 1 13.136 9.721 1 1 1 1. 0.357 0.406 2.682 1.828 0.276 0.312 0.893 0.962. 1.127 1.165 10.491 5.023 1.076 1.097 1.797 1.925. 0.500 0.499 0.472 0.468 0.494 0.494 0.496 0.496 0.499 0.235 0.398 0.228 0.315 0.493 0.289 0.500 0.236 0.199 119.171 0.165. 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0. 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 489 1. 0.046 0.096 0.696 0.749 -0.326 -0.324 -0.252 -0.244 0.098 3.764 1.526 1.234 0.588 -0.331 2.818 -0.029 0.042 0.279 1.418 5.707. 1.002 1.009 1.484 1.561 1.106 1.105 1.063 1.059 1.010 15.165 3.329 4.274 1.956 1.110 8.944 1.001 1.526 1.784 4.775 33.572. Deviation. 18 .

(24) . Among the sample of 40 venture capitals, 16(40%) are viewed as internationalization. The average Patent/ R&D Capital and Citation/ R&D Expenses are 0.512 and 0.997, respectively. Table 3 reports correlations between reputation measure and innovative efficiency measures and other characteristics. Table 3. Correlation Matrix 1. 2. 3. 4. 1.. Internationalization. 1.000. 2.. IPO. 0.040. 1.000. 3.. Patent/R&D Capital. 0.015. 0.014. 1.000. 4.. Citation/R&D 0.023. 0.106. 0.003. 1.000. 5. 6. 7. 8. 9. 10. 11. 12. 13. 14. 15. 16. 17. Expenses 5.. f_twtop. 0.125. 0.516. -0.012. 0.089. 1.000. 6.. fNCCUBaep. 0.050. 0.117. -0.002. 0.044. 0.215. 1.000. 7.. f_ustop. 0.100. 0.286. -0.005. 0.109. 0.468. 0.181. 1.000. 8.. fMBA. 0.150. 0.418. 0.044. 0.063. 0.608. 0.211. 0.295. 1.000. 9.. fScience. 0.117. 0.431. -0.010. 0.090. 0.822. 0.167. 0.401. 0.387. 1.000. 10.. vc_twtop. 0.375. 0.364. 0.010. 0.071. 0.529. 0.126. 0.311. 0.456. 0.454. 1.000. 11.. vcNCCUBaep. -0.131. 0.183. -0.004. 0.025. 0.188. 0.042. 0.084. 0.166. 0.118. 0.251. 1.000. 12.. vc_ustop. 0.454. 0.340. 0.012. 0.062. 0.463. 0.137. 0.289. 0.412. 0.374. 0.854. 0.293. 1.000. 13.. vcMBA. 0.220. 0.373. 0.008. 0.080. 0.513. 0.117. 0.310. 0.437. 0.435. 0.925. 0.254. 0.742. 1.000. 14.. vcScience. 0.303. 0.338. 0.003. 0.063. 0.485. 0.104. 0.265. 0.405. 0.440. 0.872. 0.278. 0.690. 0.724. 1.000. 15.. IPO_mkt. 0.218. 0.341. -0.006. 0.040. 0.455. 0.111. 0.272. 0.376. 0.390. 0.562. 0.172. 0.498. 0.516. 0.536. 1.000. 16.. Syn. 0.026. 0.024. -0.002. -0.005. 0.052. -0.010. 0.065. 0.048. 0.045. 0.032. -0.001. 0.019. 0.028. 0.030. 0.040. 1.000. AR. 0.313. 0.282. -0.005. 0.017. 0.451. 0.180. 0.329. 0.318. 0.383. 0.527. 0.033. 0.480. 0.517. 0.405. 0.382. 0.095 19 1.000. 17.. .

(25) . 5. Regression Analysis and Results 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 20 .

(26) . (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. 21 .

(27) . (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. 22 .

(28) . Table 4. Regression Results. This table reports the contingent fixed-effect logit regression results using IPO as dependent variable Explanatory variable Internationalization 1. & . 1. (1) 0.66** (0.27). (2) 0.66** (0.27). (3) 0.67** (0.28). (4) 0.64** (0.27). 0.40*** (0.07). 0.39*** (0.07). 0.40*** (0.07). 0.40*** (0.07). & . SN_T4 _ 1 _ 2. 0.78*** (0.24) 1.25*** (0.30). 0.75*** (0.24). _. 2. _. 3. _. 4. f_twtop f_ustop fNCCUBaep fMBA fScience vc_twtop vc_ustop vcNCCUBeap vcMBA vcScience IPO_mkt Syn AR Number of Observations. (7) 0.69** (0.29). (8) 0.67** (0.29). 0.24*** (0.05). 0.23*** (0.05). 0.25*** (0.05). 0.24*** (0.05). 0.88*** (0.25) 1.22*** (0.31). 0.83*** (0.25). 0.94*** (0.25). 0.93*** (0.25). 1.45*** (0.29) 0.57*** (0.21). _ 4 1. 0.80*** (0.24). (6) 0.67** (0.29). 1.36*** (0.28). _ 3. _. 0.81*** (0.24). (5) 0.67** (0.29). 0.36 (0.22) 0.70*** (0.22). -0.07 (0.90). 0.55** (0.22) -0.11 (0.90). -0.45 (0.77). -0.47 (0.79) -2.42*** (0.45). -2.41*** (0.46). 1.93*** (0.35) 1.54*** (0.25) -0.29 (0.27) 1.54*** (0.40) -2.39*** (0.45) 1.15 (1.09) 0.18 (0.40) 1.05** (0.42) -2.10 (1.31) 0.52 (1.10) 0.01*** (0.00) 0.13 (0.31) 1.29*** (0.11). 1.84*** (0.36) 1.59*** (0.25) -0.28 (0.27) 1.58*** (0.40) -2.34*** (0.45) 1.45 (1.07) 0.16 (0.41) 1.04** (0.43) -1.96 (1.29) 0.65 (1.10) 0.01*** (0.00) 0.12 (0.31) 1.30*** (0.11). 2.39*** (0.32) 1.41*** (0.25) -0.24 (0.27) 2.29*** (0.38) -1.86*** (0.42) 2.39*** (0.82) 0.78* (0.41) 1.18*** (0.43) -1.82* (1.09) 1.54 (1.04) 0.01*** (0.00) 0.06 (0.32) 1.36*** (0.11). -2.00*** (0.44) 2.34*** (0.32) 1.35*** (0.25) -0.23 (0.27) 2.28*** (0.38) -1.87*** (0.42) 2.24*** (0.83) 0.73* (0.41) 1.17*** (0.42) -2.06* (1.11) 1.33 (1.05) 0.01*** (0.00) 0.08 (0.32) 1.34*** (0.11). 5409. 5409. 5409. 5409. 2.22*** (0.37) 1.53*** (0.26) -0.19 (0.30) 1.29*** (0.41) -2.50*** (0.47) 2.11** (1.04) -0.08 (0.44) 1.07** (0.44) -2.95** (1.29) -0.53 (1.14) 0.01*** (0.00) 0.78** (0.36) 1.28*** (0.12). 2.11*** (0.37) 1.59*** (0.26) -0.19 (0.30) 1.27*** (0.41) -2.52*** (0.47) 2.37** (1.04) -0.09 (0.45) 1.05** (0.44) -2.80** (1.27) -0.35 (1.14) 0.01*** (0.00) 0.80** (0.36) 1.30*** (0.12). 2.68*** (0.34) 1.45*** (0.26) -0.13 (0.30) 2.02*** (0.38) -2.00*** (0.44) 3.23*** (0.83) 0.55 (0.45) 1.23*** (0.45) -2.60** (1.09) 0.53 (1.07) 0.01*** (0.00) 0.64* (0.37) 1.39*** (0.12). -2.14*** (0.46) 2.64*** (0.33) 1.38*** (0.26) -0.13 (0.31) 2.03*** (0.38) -2.00*** (0.44) 3.12*** (0.83) 0.53 (0.45) 1.22*** (0.45) -2.80** (1.10) 0.45 (1.08) 0.01*** (0.00) 0.67* (0.37) 1.37*** (0.12). 4834. 4834. 4834. 4834. “ *** “, ‘‘ ** ’’ and “ * ” indicate significance at the 1% level, 5% level, and 10% level, respectively. 23 .

(29) . 6. Conclusion This paper has provided significant evidence of political connection as well as reputation and innovative efficiency showing how they impact the entrepreneurial firms’ Initial Public Offering (IPO) milestone in Taiwanese venture capital industry. Extant literatures have shown that political connections matter firm value; specifically, researchers have quantified the value of political connections for firms in prospects of long-run performance or financing strategies. Yet entrepreneurial milestone in the life of an entrepreneurial firm, that is to say the IPO, has less been empirically discussed. This paper addresses the question how social capital in managerial resources matter the new entrepreneurial firms in Taiwan economy; and hence, tries to answer this question by examining the role of managers’ political connections in firms’ Initial Public Offering process. Using a sample of 390 domestic investment records in Taiwan, I find that political connections gradually play a significantly negative and economically meaningful role in the process of Initial Public Offering. Overall, this paper contribute to extant research by providing a better understanding of how firm managers’ political connections and educational connections are related to firm performance, especially in the IPO process. As a result, this paper tests levels of political connection and indicates that entrepreneurial firms with great political connections may get a higher likelihood in their IPO milestone; however, venture capitals with great political connections impact in a totally opposite way. Crony capitalism may provide a simple explanation to the quandary. Given the increasing importance of Crony capitalism this paper provides an evidence of the political connections and economic tradeoffs that have been made in venture capital industry.. 24 .

(30) . Appendix: Colleges and Departments Integration Checklist. I. Colleges Engineering. Mechanical Engineering, Chemical Engineering, Material Sciences and Engineering, Civil Engineering, Transportation Engineering, Industrial Engineering, Engineering, Physics, Chemistry, Mathematics, Statistics, Earth Sciences, Psychology, Sciences, Electronic Engineering, Computer Science and Information Engineering. Commerce. Finance, Accounting, Commerce, EMBA, Business Administration Executive Program. Social Sciences. Economics, Public Finance, Land Economics, Political Science, Social Sciences, Chinese Literature, Foreign Languages and Literatures, Literature. Law. Law. Medicine. Medicine, Pharmacy, Life Science, Agriculture, Genetics. Other. Mass Communication, Design, Architecture, Education, Honor. II. Departments Mechanical Engineering. Machine, Chemical Mechatronics, Power Mechanical Engineering, Bio-Industrial Mechatronics, Aviation Mechanical Engineering, Naval Mechanical Engineer, Marine Engineering, Mechanical Engineering, Mechatronics, Industrial Technology, Energy and Refrigerating Air-Conditioning Engineering, Agricultural Engineering. Chemical Engineering. Chemical Engineering, Textile Engineering, Polymer Engineering, Industrial Chemistry, Biochemical Engineering. Material Sciences and Engineering. Material Sciences and Engineering, Mining and Metallurgical Engineering, Water Resource Engineering, Environmental Engineering, Resource Engineering, Systems Science, Paper-Making and Printing, Nuclear Sciences, Metallurgy. Civil Engineering. Civil Engineering, Civil and Construction Engineering. Transportation Engineering. Transportation Engineering, Aeronautics and Astronautics, Naval Architecture, Automobile, Vessel. Industrial Engineering. Industrial Engineering, Industrial Sciences, Industrial Management, Printing Engineering, Industrial and Systems Engineering, Industrial Technology, Industrial and Applied Engineering 25 . .

(31) . Engineering. Only include Keyword “Engineering” without specifying departments. Physics. Physics, Applied Physics, Astrophysics, Quantum Physics, Electrophysics, Applied Mechanics. Chemistry. Chemistry, Applied Chemistry, Agricultural Chemistry, Organic Chemistry, Polymer Chemistry. Mathematics. Mathematics, Applied Mathematics. Statistics. Statistics, Actuarial Science, Statistics. Earth Sciences. Earth Sciences, Geography, Atmospheric Sciences, Ocean Sciences, Geosciences, Earth Physics, Atmospheric Physics. Psychology. Psychology. Sciences. Only include Keyword “Sciences” without specifying departments. Electronic Engineering. Electronic Engineering, Electrical Engineering, Communications Engineering, Photonics, Automation and Control, Nuclear Engineering, Nuclear Engineering, Electrical Engineering and Computers, Energy Engineering. Computer Science and Information Engineering. Computer Science and Information Engineering, Information Management, Information Sciences, Computer Sciences, Computer Engineering, MIS, Computer, Operations Research, Computing and Control Sciences. Finance. Finance, Finance, Financial Management, Money, Banking, Insurance, Risk Management, Real Estate Management. Accounting. Accounting, Accounting and Statistics, Management Accounting. Commerce. Commerce, Business Administration, International Business, International Trade, Business Management, Marketing, Industry and Business Management, Human Resource, Transportation Management, Sport Management, Business Administration, Marketing, Managerial Philosophy, Operating and Management, Government Management, Management Sciences, Industrial Relations, Decision Sciences, Enterprise Innovative Development, Commerce Automation and Management, Technology Management. Economics. Economics, Economic Cooperation, Applied Economics, International Economics, Agricultural Economics, Labor, Political Economics. Public Finance. Public Finance, Public Finance and Taxation, Taxation. Land Economics. Land Economics, Land Resource. Political Sciences. Political Sciences, Public Administration, Public Policy and Management, Urban Policy, Diplomacy, Three Principles of the 26 . .

(32) . People, National Development Social Sciences. Sociology, Social Work, Other unspecified Departments. Chinese Literature. Chinese Literature, Taiwanese Literature. Foreign Languages and Literatures. Foreign Languages and Literatures, Japanese, Any Foreign Languages. Literature. Literature, History, Philosophy, Drama and Theatre, Library and Information Sciences. Medicine. Medicine, Dentistry, Health Care Management, Public Health, Veterinary, Biomedical Sciences, Biomedical Engineering, Health Care Management, Laboratory Medicine. Pharmacy. Pharmacy. Life Sciences. Biology, Life Sciences, Biotechnology, Biochemical Technology, Food Sciences, Genetics，Any about Food or Biology, Biochemistry. Agriculture. Agriculture, Agronomy, Horticulture, Forestry, Agricultural Management, Entomology, Agricultural Extension, Fishing Industry, Fishing, Plant Pathology, Fermentation Science. Law. Law, Economic and Financial Law, Law, Justice, Comparative Law. Mass Communication. Mass Communication, Journalism, Advertising, Public Relations, Marketing and Advertising. Design. Design, Industrial Design, Commercial Design, Visual Communication Design, Multimedia Design, Fashion Design, Music, Art. Architecture. Architecture, Urban Planning. Education. Any about Education EMBA, Executive MBA，In-service student is excluded. EMBA Business Administration Executive Program. Business Administration Executive Program. Honor Degree. Honor Degree. other. Tourism, Home Economics, Other unspecified Departments. 27 .

(33) . References Akerlof, G. A., 1970. The market for" lemons": Quality uncertainty and the market mechanism. The Quarterly Journal of Economics, 84(3), 488-500. Allen, F., 1984. Reputation and product quality. The RAND Journal of Economics, 15(3), 311-327. Admati, A. R., and Perry, M., 1991. Joint projects without commitment. The Review of Economic Studies, 58(2), 259-276. Admati, A. R., and Pfleiderer, P., 1994. Robust financial contracting and the role of venture capitalists. Journal of Finance, 49(2), 371-402. Ardichvili, A., Cardozo, R., and Ray, S., 2003. A theory of entrepreneurial opportunity identification and development. Journal of Business venturing, 18(1), 105-123. Bradford, D. F., 1981. The incidence and allocation effects of a tax on corporate distributions. Journal of Public Economics, 15(1), 1-22. Bagwell, L. S., and Shoven, J. B., 1989. Cash distributions to shareholders. The Journal of Economic Perspectives, 129-140. Beck, T., and Levine, R., 2002. Industry growth and capital allocation: does having a market-or bank-based system matter?. Journal of Financial Economics, 64(2), 147-180. Bernile, G., Cumming, D., and Lyandres, E., 2007. The size of venture capital and private equity fund portfolios. Journal of Corporate Finance, 13(4), 564-590. Bygrave, W. D., 1987. Syndicated investments by venture capital firms: A networking perspective. Journal of Business Venturing, 2(2), 139-154. Bygrave, W. D., 1988. The structure of the investment networks of venture capital firms. Journal of Business Venturing, 3(2), 137-157. Boot, A. W., and Thakor, A. V., 1993. Security design. Journal of Finance, 48(4), 1349-1378. Berkman, H., Cole, R. A., and Fu, L. J., 2010. Political connections and minority-shareholder protection: Evidence from securities-market regulation in China. Journal of Financial and Quantitative Analysis, 45(2), 1391-1417 Carleton, W. T. and Cooper, I. A., 1976. Estimation and Uses of the Term Structure of Interest Rates. Journal of Finance, 31(4), 1067-1083. Chan, Y. S., Siegel, D., and Thakor, A. V., 1990. Learning, corporate control and performance requirements in venture capital contracts. International Economic Review, 31(2), 365-381. Chan, L. K., Lakonishok, J., and Sougiannis, T., 2001. The stock market valuation of research and development expenditures. Journal of Finance, 56(6), 2431-2456. 28 .

(34) . Cohen, L., Frazzini, A., and Malloy, C., 2008. The small world of investing: Board connections and mutual fund returns. Journal of Political Economy, 116(5), 951-979. Cohen, L., Frazzini, A., and Malloy, C., 2010. Sellside school ties. Journal of Finance, 65(4), 1409-1437. Chemmanur, T. J., Krishnan, K., and Nandy, D. K., 2011. How does venture capital financing improve efficiency in private firms? A look beneath the surface. Review of Financial Studies, 24(12), 4037-4090. Chen, S., Sun, Z., Tang, S., and Wu, D., 2011. Government intervention and investment efficiency: Evidence from China. Journal of Corporate Finance, 17(2), 259-271. Chaney, P. K., Faccio, M., and Parsley, D., 2011. The quality of accounting information in politically connected firms. Journal of Accounting and Economics, 51(1), 58-76. Hsu, D. H., 2004. What do entrepreneurs pay for venture capital affiliation?. Journal of Finance, 59(4), 1805-1844. Fisman, R., 2001. Estimating the value of political connections. The American economic review, 91(4), 1095-1102. Faccio, M., 2006. Politically Connected Firms. The American economic review, 96(1), 369-386 Faccio, M., Masulis, R. W., and McConnell, J., 2006. Political connections and corporate bailouts. The Journal of Finance, 61(6), 2597-2635. Fan, J. P., Wong, T. J., and Zhang, T., 2007. Politically connected CEOs, corporate governance, and Post-IPO performance of China's newly partially privatized firms. Journal of Financial Economics, 84(2), 330-357. Fernhaber, S. A., and McDougallCovin, P. P., 2009. Venture capitalists as catalysts to new venture internationalization: the impact of their knowledge and reputation resources. Entrepreneurship Theory and Practice, 33(1), 277-295. Golden, B. R., 1992. Research notes. The past is the past—or is it? The use of retrospective accounts as indicators of past strategy. Academy of Management Journal, 35(4), 848-860. Gompers, P. A., 1995. Optimal investment, monitoring, and the staging of venture capital. Journal of Finance, 50(5), 1461-1489. Gompers, P. A., 1996. Grandstanding in the venture capital industry. Journal of Financial Economics, 42(1), 133-156. Gompers Paul, and Josh Lerner, 2005. The venture capital cycle. MIT press.. 29 .

政治連結對於新創企業公開發行的影響： 以台灣創業投資產業為例 - 政大學術集成

政治連結對於新創企業公開發行的影響：以台灣創業投資產業為例 - 政大學術集成