Voluntary Disclosure of Externally Sourced Technological Innovation and Managerial Opportunism: Evidence from the Korean Stock Market*

Transcription

1 Asia-Pacific Journal of Financial Studies (2018) 47, doi: /ajfs Voluntary Disclosure of Externally Sourced Technological Innovation and Managerial Opportunism: Evidence from the Korean Stock Market* Kyung Soon Kim College of Business Administration, Chosun University, Republic of Korea Jin Hwon Lee Business Management, Osan University, Republic of Korea Yun Woo Park** College of Business and Economics, Chung-Ang University, Republic of Korea Received 5 January 2017; Accepted 24 August 2017 Abstract This study aims to investigate the information effect of voluntary disclosure of externally sourced technological innovation by type of technological innovation, namely, in-bound technology transfer, out-bound technology transfer, and technological alliance. Long-term performance is lower for firms with lower quality accounting information and this effect is most evident in the disclosure of an in-bound technology transfer. Further, low disclosure quality firms undergo a greater decline in long-term performance after a seasoned equity offering following the disclosure of an in-bound technology transfer than high disclosure quality firms. This relationship is more pronounced during a bear market than during a bull market. Keywords Managerial opportunism; Accruals quality; Disclosure of externally sourced technological innovation; Seasoned equity offering; Long-term performance JEL Classification: D80, G10, L20, M40 1. Introduction Technological innovation can be divided into internally sourced technological innovation and externally sourced technological innovation. In internally sourced technological innovation a newly patented technology or innovative production process *This study was supported by research funds from Chosun University. **Corresponding author: College of Business and Economics, Chung-Ang University, 84 Heukseok-ro, Dongjak-gu, Seoul 06974, Korea. Tel: , Fax: , yunwpark@cau.ac.kr Korean Securities Association 81

2 K. S. Kim et al. is acquired through in-house research and development (R&D). In contrast, in externally sourced technological innovation, a firm buys technology from another firm (in-bound technology transfer), a firm sells technology to another firm (outbound technology transfer), or a firm licenses technology from another firm and enters into a cooperative relationship for a period of time (technological alliance). Generally speaking, as internally sourced technological innovation carries significant risk, the risk in disclosing it is likely to be high. As a result, firms tend to avoid disclosing information on internally sourced technological innovation to outsiders (Bhattacharya and Ritter, 1983; Holmstrom, 1989). On the other hand, as externally sourced technological innovation is relatively less uncertain, firms may be more motivated to disclose information on technological innovation to the capital market, all else held constant. In Korea, firms engaged in externally sourced technological innovation have been disclosing, on a voluntary basis, information such as type of technological innovation, its content, and the collaborating firm. We focus on investigating the short- and long-term market responses, as well as determinants of the market response, to a voluntary disclosure of externally sourced technological innovation (in-bound technology transfer, out-bound technology transfer, and technological alliance). Therefore, our investigation on the information effect of the disclosure of technological innovation is confined to externally sourced technological innovation. The objective of this research is to investigate whether voluntary disclosure of technological innovation lessens information asymmetry between the firm and investors, providing a positive signal on firm value to the market, or if it is opportunistic behavior to promote managerial self-interest. Unlike compulsory disclosure, which is mandated by regulators, voluntary disclosure is a disclosure which the manager of the firm undertakes only when he or she finds it advantageous to do so. Potentially, voluntary disclosure has a positive effect of restoring the market valuation of the firm to its intrinsic value by reducing information asymmetry in the market. However, a rent-seeking manager has an incentive to misuse voluntary disclosure by inflating information or providing false information to mislead investors. The disclosure of externally sourced technological innovation in Korea is voluntary. Generally speaking, voluntary R&D disclosure (i.e., disclosure on internally sourced technological innovation) is aimed at achieving specific goals, namely, reducing the cost of capital, reducing agency costs arising from conflicts of interest, and reducing the risk of a negative transfer of wealth. Verrecchia (2001) sees discretionary disclosure as a substitute for regulation and an attempt to mitigate information asymmetry. However, as the disclosure of information on R&D may provide sensitive information to competing firms, causing a disclosing firm to incur high proprietary costs of disclosure, not all firms would provide information on R&D (Verrecchia, 1983; Dye, 1985; Jones, 2007). Therefore, disclosure will prevail only if disclosure costs are sufficiently low, or if information asymmetry is sufficiently high. Jones (2007) finds that higher proprietary costs are associated with lower levels of disclosure about R&D activities Korean Securities Association

3 Voluntary Disclosure of Technological Innovation Unlike studies that focus on internally sourced technological innovation, our research focuses on externally sourced technological innovation, which tends to have relatively low proprietary costs. As signaling effect tends to increase with signaling cost, investors may not perceive the disclosure of externally sourced technological innovation, which has a low cost of disclosure, as an unambiguously positive signal. Therefore, it is possible that the managerial signaling of positive information about the future performance of the firm and managerial opportunism coexist in the voluntary disclosure of externally sourced technological innovation. Thus, our research attempts to provide empirical evidence on whether the disclosure of externally sourced technological innovation serves the signaling role of reducing information asymmetry and the information risk of investors, or if it serves managerial self-interest, where misleading information increases the information risk of investors. In particular, we analyze whether the information risk found in the disclosure of technological innovation depends on the quality of accounting earnings, type of disclosure of technological innovation, or follow-on secondary equity offering. We make inferences regarding the motivation of voluntary disclosure of externally sourced technological innovation by investigating long-term performance. In Korea, disclosure of externally sourced technological innovation is classified into three types (in-bound technology transfer, out-bound technology transfer, and technological alliance). In-bound technology transfer refers to a firm acquiring a patented technology from another firm or securing the right for its use by making a payment. Out-bound technology transfer refers to a firm selling technology to another firm or granting the right for its use for a period of time in return for a payment. These two types of externally sourced technological innovation are either an outright sale or license of technology, but not a long-term partnership. In contrast, technological alliance refers to a firm contracting for the use of technology of another firm and developing a partnership relationship with the licensing firm. Therefore, technological alliance is different from the other types of externally sourced technological innovation in that the licensee firm develops a long-term strategic partnership with the licensing firm, in pursuit of their mutual interests. We expect that firms with low accounting earnings quality will experience low long-term performance following the disclosure of technological innovation. We also expect disclosure cost to vary with the technological innovation disclosure type. We hypothesize that the long-term performance following the disclosure of an inbound transfer of technological innovation is lower than the long-term performance following the disclosure of either an out-bound transfer of technological innovation or a technological alliance. In addition, we investigate the possibility that the manager of the firm uses voluntary disclosure of technological innovation prior to a seasoned equity offering (SEO) as a means of stock price manipulation to maximize the effect of the secondary equity offering. If the disclosure of technological innovation is used to manipulate the stock price for an SEO, the long-term holding period abnormal return will be negative. Moreover, as the tendency to manipulate the stock price for an SEO is likely to be greater during a bear market than a bull 2018 Korean Securities Association 83

4 K. S. Kim et al. market, we hypothesize that the predicted relationship is more pronounced during a bear market than a bull market. We construct our sample using the voluntary disclosures of technological innovation filed by listed firms in the Korean stock markets between 2002 and The final sample consists of 453 firms that fulfill the sample selection criteria. We investigate the relationship between the quality of accounting earnings and longterm performance using regression analysis. We measure the long-term performance using 12- and 24-month holding period abnormal returns after the disclosure of technological innovation. We estimate accruals quality following the cross-sectional estimation method of McNichols (2002), Francis et al. (2004), and Lee and Masulis (2009). We estimate discretionary accruals using Kothari et al. s (2005) model, which adds return on assets (ROA) to the Jones (1991) model. The main findings of our study are as follows. First, we find that long-term performance is lower for firms with lower quality accounting information, which is used as a measure of managerial opportunism. Second, the effect of the quality of accounting earnings on long-term performance is more evident in the disclosure of in-bound technology transfer than in other disclosure types. This result suggests that opportunistic disclosure occurs more frequently in in-bound technology transfer than in out-bound technology transfer and technological alliances. Next, we find that firms with poor quality accounting earnings undergo a greater decline in longterm performance when an SEO is made following the disclosure of an in-bound technology transfer than for firms with high-quality accounting earnings. This relationship is more pronounced during a bear market than during a bull market. This result suggests that a manager motivated by private interest is more likely to use the disclosure of an in-bound technology transfer prior to an SEO as a manipulative tool to maximize the effect of an SEO. The rest of the paper is organized as follows. Section 2 presents the research hypotheses. Section 3 discusses the research models, as well as the variable measurements. Section 4 presents the empirical results. Finally, Section 5 presents the conclusions and policy implications. 2. Research Hypotheses Existing research reports that there is a positive relationship between firm innovation and firm value. Therefore, if the disclosure of the firm s innovation initiatives is truthful, then a positive response in stock price would result. However, there is a possibility that management provides false information to the market for private benefit. Moreover, the Korean capital market is characterized by a high proportion of firms run by founder-managers and low equity ownership of institutional investors compared to more advanced capital markets. This may reduce the monitoring of management by outside investors, exacerbating opportunistic disclosure behavior by management. Therefore, by measuring the long-term stock price performance after disclosure, we investigate whether, in the Korean stock market, the disclosure Korean Securities Association

5 Voluntary Disclosure of Technological Innovation of technological innovation, on average, sends a positive signal or reflects the opportunistic intention of management. Furthermore, we investigate whether the effect of the disclosure of technological innovation on firm value depends on disclosure type by comparing the long-term stock return after the disclosure of technological innovation across disclosure types. In Korea, technological innovation disclosures are classified into disclosure of an in-bound transfer of technological innovation, an out-bound transfer of technological innovation, or a strategic alliance for technological innovation. We expect that the long-term effect of the disclosure of an in-bound, as well as an out-bound, transfer of technology is different from that of a technological alliance. Generally, an in-bound transfer of technology is interpreted as a positive signal of the management s desire to increase investment in technological innovation, while an outbound transfer of technology may be interpreted as a positive signal that old technology that has limited economic benefit due to new technology is sold to other firms. However, disclosures of both in-bound and out-bound technology transfers may be interpreted as negative signals by investors. In the case of an in-bound technology transfer, investors may reason that, because of internal inefficiency, the firm is forced to depend on innovation from outside parties. In contrast, the disclosure of an out-bound technology transfer may send a signal that the economic benefit of the exclusive technology or patent held by the firm may have been reduced. In short, since the disclosure of technology transfers, both in-bound and out-bound, has both positive and negative implications, the information risk faced by investors is greater for firms with higher information asymmetry. Furthermore, since a technological alliance is conducted according to contracts between strategic partners, the possibility that the disclosure of a technological alliance is exploited to enhance a manager s private benefit is lower relative to inbound and out-bound technology transfers. Therefore, we predict that disclosure of a technological alliance is more likely to produce a positive long-term stock return than the disclosure of in-bound and out-bound technology transfers. Third, we measure the truthfulness of the managerial disclosure of technological innovation with the quality of past disclosures of accounting information. The effect of the voluntary disclosure of technological innovation depends on the uncertainty of technological initiatives as well as managerial truthfulness. With regard to stock price, management is inclined to reflect good news quickly and bad news slowly. Therefore, management wants to avoid disclosure when the uncertainty of the outcome of technological innovation is significant, while it is far more inclined to make a disclosure of technological innovation with limited uncertainty. Therefore, the firm making a voluntary disclosure of technological innovation can send a positive signal to the market. However, the disclosure of technological innovation does not guarantee a positive market response, since the market knows that management may engage in deceptive disclosure of technological innovation. Given that low performance, 2018 Korean Securities Association 85

6 K. S. Kim et al. inefficient technological innovation activity, moral hazard of management, and information asymmetry may drive down the value of stock, which may engender a takeover threat, to deter a takeover, management may use the disclosure of technological innovation as a tool for stock price manipulation. Therefore, we measure the opportunistic behavior of management with the quality of accounting information disclosure and examine whether long-term stock performance depends on the quality of accounting information disclosure. Since disclosure of technological innovation by a firm that has persistently made low-quality disclosures of accounting earnings is likely to be opportunistic, we predict a decline in long-term performance after the disclosure of technological innovation made by opportunistic managers. However, the relationship between the disclosure quality of accounting earnings and long-term performance may depend on the type of disclosure of technological innovation. It is more problematic to use the disclosure of a technological alliance to send a false signal, since a technological alliance is based on contracts between strategic partners. Similarly, the disclosure of an out-bound technology transfer may not be suitable for market manipulation, since the firm must own a technology ex ante that is worth transferring. On the other hand, an in-bound technology transfer is not subject to this type of constraint, making it more suitable for deceptive disclosure of technological innovation in comparison to the other disclosure types. Therefore, we expect that the relationship between accruals quality and long-term performance is stronger for the disclosure of an in-bound technology transfer than for the other types of disclosure. Finally, we investigate whether management uses the disclosure of technological cooperation opportunistically with outside parties in an attempt to enhance the effect of an SEO. Some researchers point out the possibility of exploiting the disclosure of a financial event that is known to have a positive effect on the stock price to maximize the effect of the disclosure of another financial event. D Mello et al. (2003) and Kim et al. (2012) argue that a manager may execute a stock split before an SEO to maximize the effect of the SEO. Similarly, Gong et al. (2008) show that firms buying back a significant number of their shares in an open market over a short period tend to manipulatively reduce their earnings before the stock repurchases. Like preceding studies, we hypothesize that management has an incentive to disclose technological innovation prior to an SEO to inflate the stock price, allowing the firm to obtain required funds at a favorable price. In particular, an opportunistic manager is more likely to use an in-bound technology transfer than an outbound technology transfer or technological alliances as a manipulative tool to boost the effect of the SEO. The reason is that an in-bound technology transfer can be consummated more readily, as unimportant technology or inexpensive technology can be chosen willfully by the management, and the deal can be made unilaterally by the management, whereas in an out-bound technology transfer or a technological alliance, valuable technology must exist ex ante and the deal is made bilaterally, imposing a constraint on management Korean Securities Association

7 Voluntary Disclosure of Technological Innovation For this reason, we expect that the agency problem is acute when an opportunistic manager conducts an SEO following the disclosure of an in-bound technology transfer, and, as a result, the firm will experience a long-term performance decline. We test this hypothesis empirically by examining the long-term performance of firms with a history of low disclosure quality that disclose an in-bound technology transfer, and an SEO soon thereafter. 3. Measurements of Variables and Research Method 3.1. Measurements of Short- and Long-term Excess Returns: Dependent Variables We estimate the excess returns around the disclosure of a technological innovation using a size-adjusted market model. First, we estimate the size-adjusted excess return by subtracting the return of portfolio j that firm i belongs to on day t from the return of firm i on day t. We form five equally weighted portfolios on the basis of market capitalization and estimate the return of each portfolio on a given day. We estimate the size-adjusted cumulative abnormal return between 5 days before and 5 days after the disclosure date for 11 days, CAR( 5, 5), and use it as a measure of the short-term effect of the disclosure of a technological innovation. We also use the holding period abnormal return, or buy-and-hold abnormal return, (BHAR) as a measure of the long-term effect of the disclosure of a technological innovation. BHAR i (t,t) is the holding period abnormal return of firm i for T periods from the disclosure date t relative to the return of the benchmark portfolio at time t, where five benchmark portfolios are formed by market capitalization. We measure the long-term performance after the disclosure of a technological innovation using 12-, 24- and 36-month holding period abnormal returns. Using these measures of long-term performance as dependent variables, we study the effect of accounting earnings quality on long-term performance Measurement of Managerial Opportunism: Explanatory Variables Accruals Quality. We measure the credibility of the disclosure of technological innovation using the accounting earnings quality prior to the disclosure. As a proxy for the degree of managerial opportunism, we use the quality of accruals as well as discretionary accruals, which reflect accounting earnings quality. Francis et al. (2004) investigate whether the characteristics of accounting earnings can proxy for information risk by examining the capital cost implicit in stock prices and a variety of earnings characteristics. They find that accruals quality has the strongest relationship with capital cost. In a followup study, Francis et al. (2005) report that the signaling effect reduces information risk, while discretionary accruals produced by managerial opportunism amplify information risk. They argue that accruals quality affects stock prices, and low accruals quality increases capital cost by reducing returns. Similarly, Lambert et al. (2007) report evidence that high-quality accruals affect the correlation between the cash flows of the firm and those of other firms, which in turn affects the firm value Korean Securities Association 87

8 K. S. Kim et al. We estimate accruals quality using the models of Francis et al. (2004), which are modifications of the regression models of McNichols (2002) and Dechow and Dichev (2002). To estimate accruals quality, we classify all the listed firms, which are listed either on the Main Board Market or KOSDAQ Market, into 15 industry groups for each market using the standard industry codes. Then, we estimate crosssectional regression models for each industry for each year between year t 3 and t 1; calculate residuals (m i,t ) of firm i in year t; and calculate the standard deviation of cross-sectional residuals for the 3-year period, which we use as a proxy for accruals quality. The higher (lower) value of the measure corresponds to lower (higher) earnings quality Decomposition of Accruals Quality into Discretionary and Innate Factors. According to Francis et al. (2004) accruals quality can be decomposed into discretionary and innate factors. Since the managerial agency risk stems from information asymmetry between the manager and outside investors, it is related to the discretionary component of accruals quality. Therefore, we decompose accruals quality into discretionary accruals quality (DiscAQ) and innate accruals quality (InnateAQ), following Francis et al. (2004), Lee and Masulis (2009), and Demirkan et al. (2012). We decompose accruals quality as follows. First, we estimate the effects of fundamental operating factors on accruals quality. Following existing studies, we choose as factors related to operating activities, firm size, variability of operating cash flows, variability of sales, operating cycle, and the proportion of loss-reporting years. Then, we obtain the innate accruals quality by substituting the actual values of the regression variables of the firm into the estimated regression equation. Finally, we obtain the discretionary factor of accruals quality (DiscAQ) by subtracting innate accruals quality (InnateAQ) from accruals quality (AQ). We use the discretionary accruals quality (DiscAQ) and the innate accruals quality (InnateAQ) as explanatory variables of the long-term performance of the disclosure of technological innovation Discretionary Accruals. Previous studies report that earnings management may serve as a market manipulation tool. In particular, earnings management has been shown to be used as a market manipulation tool in financial events such as initial public offerings (IPOs), SEOs, and stock-for-stock mergers, among others. According to Teoh et al. (1998a, b) and Shivakumar (2000), managers have an incentive to manage earnings prior to an IPO and an SEO to raise the offer price of IPO and SEO shares. In a stock-forstock merger, firms have an incentive to raise the stock price higher through earnings management prior to the merger announcement, in an attempt to reduce the number of shares conveyed for the takeover (Erickson and Wang, 1999). We use the absolute value of discretionary accruals as a measure of managerial opportunism. We estimate discretionary accruals using cross-sectional regressions as in DeFond and Jiambalvo (1994) and Subramanyam (1996). We classify firms into 15 industry categories using the standard industry codes. Then, we estimate non-discretionary accruals using the Jones (1991) model Korean Securities Association

9 Voluntary Disclosure of Technological Innovation augmented with ROA as in the Kothari et al. (2005) model. Next, we estimate discretionary accruals by subtracting the non-discretionary accruals of firm i in year t from the total accruals of firm i in year t. We use the discretionary accruals as a measure of earnings management. We assume that discretionary accruals increase with managerial opportunism and use them as an alternative measure of managerial opportunism. 1 We expect that the firms that have positive discretionary accruals (upward earnings management) are likely to be motivated by managerial opportunism in making technological innovation disclosures Research Model The primary objective of this study is to examine how the motivation for voluntary disclosure of technological innovation affects firm value after the disclosure. To evaluate this research question, we estimate the following regression model: BHAR i;t ¼ b 0 þ b 1 AQ i;t þ b 2 DA Dummy i;t þ b 3 SIZE i;t þ b 4 BETA i;t þ b 5 BM i;t þ b 6 LEV i;t þ b 7 ROA i;t þ b 8 Cash i;t þ b 9 DPPE i;t þ b 10 DEquity i;t þ b 11 HHI i;t þ b 12 HighTec i;t þ / t X YearDummyi;t þ e i;t ðmodel1 1Þ Model 1-1 is the regression model we use to study the effect of accruals quality (AQ) and upward earnings management (DA_dummy) prior to the disclosure of technological innovation on long-term performance after the disclosure of technological innovation. In Model 1-2 we replace accruals quality (AQ) with discretionary accruals quality (DiscAQ) and innate accruals quality (InnateAQ). The dependent variable is 12-month holding period abnormal returns (BHAR 12M) or 24-month holding period abnormal returns (BHAR 24M) after the disclosure of technological innovation. In Model 1-1 we assume that accruals quality (AQ) and discretionary accruals (DA) measure the quality of accounting information, and add these measures to the regression models as proxies for managerial opportunism. We measure AQ using the methodology explained in Section DA_dummy takes the value of one if discretionary accruals (DA), which is calculated as per Section 3.2.3, is positive, and zero otherwise. DiscAQ and InnateAQ in Model 1-2 are obtained decomposing AQ as explained in Section We add several firm characteristics that can influence stock returns and investments in technological innovation into the regression equations as control variables. We estimate the model not only for the whole sample of firms that disclose technological innovations, but also for the subsamples of each disclosure type (in-bound transfer, out-bound transfer, and alliance). 1 As discretionary accruals may not reflect managerial opportunism unambiguously, we use accrual quality as the primary measure of managerial opportunism, and use discretionary accruals as an alternative measure Korean Securities Association 89

10 K. S. Kim et al. As control variables that can influence the stock price response surrounding disclosure, we use firm size (SIZE), beta (BETA), and book-to-market ratio (BM). We measure firm size using the log of the sum of the market values of the common and preferred stock in the year prior to the disclosure. We estimate BETA using the slope of the market model estimated over 210 day to 30 day (180 days). We estimate the book-to-market ratio by dividing the book value of equity by the market value of common stock. We obtain the debt ratio (LEV) by dividing total debt by total assets in the year prior to the disclosure, and return on assets (ROA) by dividing operating income by total assets in the year prior to the disclosure. We add cash holdings (Cash), as a measure of the capacity to invest in R&D, capital expenditure (DPPE), and equity-based funding (DEquity). We use the log of the sum of cash, cash equivalents, and short-term financial securities (in million Korean won) to measure cash holdings. We obtain the capital expenditure by subtracting the end-of-year tangible assets from the beginning-ofyear tangible assets, then dividing this difference by the beginning-of-year tangible assets. We estimate the equity-based funding by first subtracting the end-of-year equity (common stock + cumulative retained earnings) from the beginning-of-year equity, then dividing this difference by the beginning-of-year equity. We also add the Herfindahl-Hirschman Index (HHI), which is a measure of competition in an industry, as a control variable. HHI i,t is obtained as the sum of the squares of the ratios of the sales of firm i to the aggregate sales of the industry j that firm i belongs to, estimated at the beginning of year t. HHI takes a value between zero and one. A large HHI means greater competition in the industry and a lower HHI indicates less competition in the industry. We add a high-tech industry dummy (HighTec), which takes the value of one if firm i belongs to a high-tech industry, and zero otherwise. High-tech industries are pharmaceutical, computer, electronics, and communication. BHAR i;t ¼ b 0 þ b 1 AQ D i;t þ b 2 AQ D i;t Inbound D i;t þ b 3 AQ D i;t ESO D i;t þ b 4 AQ D i;t Inbound D i;t SEO D i;t þ b 5 Inbound D i;t þ b 6 SEO D i;t þ b 7 SIZE i;t þ b 8 BETA i;t þ b 9 BM i;t þ b 10 LEV i;t þ b 11 ROA i;t þ b 12 Cash i;t þ b 13 DPPE i;t þ b 14 DEquity i;t þ b 15 HHI i;t þ b 16 HighTec i;t X þ / t YearDummyi;t þ e i;t ðmodel2þ We use Model 2 to test whether a firm with a more opportunistic manager experiences a greater decline in stock price than other firms in the case of an SEO following the disclosure of technological innovation. AQ_D is a dummy variable taking the value of one if accruals quality (AQ) is larger than the median, and zero otherwise. In-bound_D is one if the disclosure type of technological innovation is an in-bound technology transfer, and zero otherwise. SEO_D is a dummy variable taking the value of one if the firm making the disclosure of the technological Korean Securities Association

11 Voluntary Disclosure of Technological Innovation innovation conducts an SEO in the same year or 1 year thereafter, and zero otherwise. In other words, firms are divided into subgroups by managerial opportunism, disclosure type of technological innovation, and SEO; then their long-term performances are compared. We posit that the subgroup with the value of one for AQ_D (or DiscAQ), In-bound_D, and SEO_D will experience a greater decline in long-term performance than all the other subgroups. 4. Empirical Results 4.1. Effect of Opportunistic Information Provision by the Manager on the Longterm Performance of the Disclosure of Technological Innovation For the initial sample, we select 555 firms that have made disclosures of technological innovation in the 12 years between 2002 and 2013 from the firms listed on the Main Board market (KOSPI) and the KOSDAQ market. From the initial sample, we remove: (i) 22 firms that have not stated the type of technological innovation disclosure; (ii) 33 firms for which it is not possible to calculate stock returns for reasons such as delisting after the disclosure of technological innovation; (iii) five firms for which financial information is not available; and (iv) 42 firms for which we cannot estimate accruals quality and/or discretional accruals. As a result, the final sample consists of 453 firms (or instances of disclosures), which are 257 cases of in-bound technological transfer, 134 cases of out-bound technological transfer, and 62 cases of technological alliance. From the final sample of 453 cases of voluntary disclosure of technological innovation, SEOs take place either in the year of disclosure or the next year in 159 cases. We show the sample selection process and the distribution of the sample firms by year in Table 1. We obtain information on disclosures from the disclosure database of the Korea Exchange, and stock price and accounting information from the Data Guide Pro. 2 Since the disclosure of technological innovation may be due either to signaling motivation or opportunistic motivation, its effect on firm value is expected to vary with the managerial motivation of the disclosure. That is, the level of trust is likely to be high on voluntary disclosure of technological innovation by firms that have striven to provide high-quality accounting information in the past, while it is likely to be low on the disclosure of technological innovation by firms that have managed accounting information arbitrarily to promote managerial self-interest. Therefore, we investigate the relationship between the quality of accounting accruals and the long-term effect of disclosure of technological innovation. We estimate accruals quality and discretionary accruals quality using of Francis et al. (2005) method as principal measures of managerial opportunism, and discretionary accruals based on Kothari et al. (2005) as an alternative measure of managerial opportunism. 2 Data Guide Pro is a widely used market and accounting database provided by FnGuide, a leading financial information provider in Korea Korean Securities Association 91

12 K. S. Kim et al. Table 1 Sample selection Panel A: Sample selection process Classification KOSPI KOSDAQ N Initial sample (all technological innovation disclosures) Disclosure type missing Types of technological innovation disclosure In-bound transfer Out-bound transfer Alliance Total In-bound transfer Out-bound transfer Alliance Total Total Stock market data missing Financial information missing Quality of accounting earnings missing Final sample Korean Securities Association

13 Voluntary Disclosure of Technological Innovation Table 1 (Continued) Panel B: Distribution of the final sample by year Final sample SEO after disclosure Year In-bound transfer Out-bound transfer Alliance Total In-bound transfer Out-bound transfer Alliance Total Total Korean Securities Association 93

14 K. S. Kim et al. Table 2 shows short- and long-term abnormal stock returns for two groups that are formed based on accruals quality. AQ1 is the subsample of firms that have accruals quality below the median, and AQ2 is the subsample of firms that have accruals quality above the median. Panel A of Table 2 shows the results for the whole sample. We find no statistically significant difference in the short-term effect of the disclosure between AQ1 and AQ2. On the other hand, the long-term abnormal returns of AQ1 are more negative than AQ2, and the difference is statistically significant. Table 2 Short- and long-term effects of technological innovation disclosure by disclosure type and accruals quality *, **, and *** denote significance at the 0.1, 0.05, and 0.01 levels, respectively. Short-term effect Long-term effect N CAR( 1, 0) CAR( 5, 5) BHAR 12M BHAR 24M Panel A: Full sample (N = 453) AQ 1 (Low quality) 226 Mean t-stat 2.680*** *** 4.647*** AQ 2 (High quality) 227 Mean t-stat 4.464*** 2.148** AQ 1 AQ 2 Mean t-stat * 3.268*** 3.150*** Panel B: In-bound transfer (N = 257) AQ 1 (Low quality) 129 Mean t-stat 2.851*** *** 3.894*** AQ 2 (High quality) 128 Mean t-stat 4.094*** 2.518** 2.145** AQ 1 AQ 2 Mean t-stat ** 2.151** Panel C: Out-bound transfer (N = 134) AQ 1 (Low quality) 73 Mean t-stat *** 2.428*** AQ 2 (High quality) 61 Mean t-stat AQ 1 AQ 2 Mean t-stat ** Panel D: Technological alliance (N = 62) AQ 1 (Low quality) 25 Mean t-stat AQ 2 (High quality) 37 Mean t-stat 2.468** 1.828** 2.238** AQ 1 AQ 2 Mean t-stat * Korean Securities Association

15 Voluntary Disclosure of Technological Innovation Panels B through D show the responses of AQ1 and AQ2 groups by disclosure type (in-bound transfer, out-bound transfer, and alliance). There is no difference in short-term cumulative abnormal returns (CAR( 1, 0)) between AQ1 and AQ2 for any technological transfer disclosure type. In contrast, the long-term abnormal return, BHAR, of AQ1 is lower than that of AQ2, and the difference is statistically significant for in-bound as well as out-bound technology transfers. However, the difference in the long-term performance measure between AQ1 and AQ2 is not statistically significant for technological alliances. In summary, there is a difference in long-term performance depending on past accruals quality. This difference is observed only in the in-bound technology transfer and out-bound technology transfer groups. We can explain this finding by noting that it is more difficult to use technological alliance, which involves a serious partner, than to use in-bound or out-bound technology transfers, which are more one-sided transactions, in the context of opportunistic disclosure of technological innovation. Next, we investigate the relationship between earnings quality and long-term performance after the disclosure of technological innovation by conducting a regression analysis where we control for relevant firm characteristics. In Table 3, we show the descriptive statistics of variables used in the regression analysis. We have winsorized all the variables in Table 3 at 1%. We examine the relationship between accounting earnings quality and the effect of the disclosure of technological innovation by disclosure type, and show the Table 3 Descriptive statistics Variables Mean Std Min. 25% Median 75% Max. BHAR12M BHAR24M AQ Disc AQ Innate AQ DA_dummy SEO_D In-bound_D Size BETA BM LEV ROA Cash DPPE DEquity HHI HighTech Korean Securities Association 95

16 K. S. Kim et al. estimation results in Table 4. We find that the coefficient of AQ is negative and statistically significant only for an in-bound transfer of technology, while the regression coefficient of DA_dummy is not statistically significant in any disclosure type. This result is consistent with Francis et al. (2005), who show that AQ, which is measured with the volatility of abnormal accruals, reflects the firm s unique information risk better than DA. This result is also consistent with Subramanyam (1996), who shows that DA reflects both managerial opportunism and managerial signaling. Overall, we infer that the negative effect of managerial opportunism on long-term performance of the disclosure of technological innovation is most evident in an in-bound transfer of technology, which is easier to manipulate than the other types of technological transfer. In Table 5, we show the results of the regression of BHAR on the discretionary component (DiscAQ) and innate component of accruals quality (InnateAQ). Here we also find that the negative relationship between the effect of the disclosure of technological innovation and accounting earnings quality is statistically significant only for the in-bound transfer of technology. Since DiscAQ is a more accurate measure of managerial opportunism than AQ, the fact that the coefficient of DiscAQ is significant only for the in-bound transfer of technology reinforces the inference that managerial opportunism surrounding the disclosure of technological innovation is more likely for an in-bound technology transfer than in the other types of technological innovation. These findings suggest that the voluntary disclosure of technological innovation made by a manager who has reported earnings opportunistically in the past may not be a truthful signal. Moreover, they suggest that, if the management of the firm intends to use the disclosure of technological innovation with the idea of manipulating the stock price to exploit information asymmetry, it is likely to choose the costminimizing disclosure type. Overall, the empirical findings support the main hypothesis of this paper, that there is a significant relationship between the manager s opportunistic tendency and the effect of the disclosure of technological innovation Seasoned Equity Offering Following the Disclosure of Technological Innovation As shown in Table 1, there are 159 firms that conduct SEOs soon after the disclosure of technological innovation, corresponding to 35% of the sample. We posit that managers who pursue private welfare may use the disclosure of technological innovation as a vehicle to send a misleading signal to the market to enhance the outcome of the SEO. Therefore, the detrimental effect on long-term firm performance of the combination of the SEO and the disclosure of technological innovation may be more severe. To test this conjecture, we examine the long-term performance of firms that conduct SEOs soon after the disclosure of technological innovation. We form eight subgroups by dividing the sample first by accruals quality, then by whether the disclosure is an in-bound technology transfer, and finally by whether Korean Securities Association

17 Voluntary Disclosure of Technological Innovation Table 4 Regression analysis of long-term performance of technological innovation disclosure by disclosure type *, **, and *** denote significance at the 0.1, 0.05, and 0.01 levels, respectively. Dependent variable: BHAR 12M (1) Whole sample (2) In-bound (3) Out-bound (4) Alliance Variable (predicted sign) Coefficient t-stat Coefficient t-stat Coefficient t-stat Coefficient t-stat Intercept AQ( ) ** *** DA_dummy ( ) * SIZE *** ** * BETA *** *** BM LEV ** ROA Cash *** ** ** DPPE ** *** DEquity * * HHI * HighTech Year controlled Yes Yes Yes Yes Adj. R Korean Securities Association 97

18 K. S. Kim et al. Table 5 Regression analysis of long-term effect of technological innovation disclosure by disclosure type using discretionary accruals quality *, **, and *** denote significance at the 0.1, 0.05, and 0.01 levels, respectively. Dependent variable: BHAR 12M (1) Whole sample (2) In-bound (3) Out-bound (4) Alliance Variable (predicted sign) Coefficient t-stat Coefficient t-stat Coefficient t-stat Coefficient t-stat Intercept DiscAQ( ) * * InnateAQ( ) ** *** ** ** SIZE *** *** ** BETA *** *** BM LEV * ** *** ROA Cash *** ** ** DPPE ** *** DEquity ** HHI ** HighTech Year controlled Yes Yes Yes Yes Adj. R Korean Securities Association

19 Voluntary Disclosure of Technological Innovation an SEO is made soon after the disclosure. We measure the holding period abnormal returns for 12 months (BHAR 12M) and 36 months (BHAR 36M) after the disclosure date, and report the results in Table 6. Panel A of Table 6 shows the 12- and 36-month BHAR of firms that conducted an SEO within 1 year of the disclosure of technological innovation (159 firms) and of firms that did not (294 firms). The 36-month BHAR of the SEO follow-on subsample is negative 60.3% and is statistically significant. While not shown as a table, we investigate the frequency of positive long-term performance firms versus negative long-term performance firms using the follow-on SEO subsample (159 firms). We find that there are 23 firms with positive 36-month BHAR and 136 firms with negative 36-month BHAR. In contrast, the long-term performance of firms that did not combine the disclosure of technological innovation with an SEO is not statistically different from zero. These results suggest that the disclosure of an externally sourced technological innovation is used more to manipulate the stock price with a view to maximizing the effect of an SEO than as a signal of positive investment opportunity. Panel B shows the long-term performance of the sample firms divided by the degree of AQ, disclosure types, and the status of SEO combination. AQ1(AQ2) is the subsample with AQ greater (less) than the median AQ and corresponds to firms with lower (higher) earnings quality. In-bound refers to firms that made the disclosure of in-bound technology transfer, and non in-bound refers to firms that did not. SEO refers to firms that combined the disclosure of technology transfer with a follow-on SEO, and non-seo refers to firms that did not. The BHAR 12M and BHAR 36M are 40.6% (t = 7.317) and 67.6% (t = 2.886), respectively, for firms with low earnings quality (AQ1) that undertook the combination of the disclosure of an in-bound technology transfer and a follow-on SEO (N = 59), which corresponds to the lowest long-term performance of all subgroups. This result suggests that opportunistic management uses the disclosure of technological innovation as a false signal prior to an SEO in an attempt to prop up the SEO. We divide the sample into two subperiods and show the respective long-term performance in Panels C and D. The stock market experienced an overall expansion during the period, while it contracted during the period due to the Global Financial Crisis. For this reason, we classify the sample period prior to 2008 as the bull market subperiod, and the sample period after 2008 as the bear market subperiod. Then, we measure long-term performance by subperiods. We find that the AQ1/in-bound/SEO subgroup underperformed the AQ2/non inbound/non-seo subgroup in both the bull market and bear market subperiods. Using regression analysis, we examine whether the combination of accruals quality, in-bound technology transfer, and SEO is a significant determinant of longterm performance, and report the results in Table 7. Panel A shows the regression result based on the full sample period, while Panels B and C show the regression results based on the bull and bear market subperiods, respectively. In the regression model, AQ_D is a dummy variable which is one if accruals quality is greater than 2018 Korean Securities Association 99

20 K. S. Kim et al. Table 6 Long-term performance of technological innovation disclosure with follow-on SEO *, **, and *** denote significance at the 0.1, 0.05, and 0.01 levels, respectively. Panel A: Long-term performance of firms that conducted an SEO within one year of technological innovation disclosure versus those that did not SEO N BHAR 12M BHAR 36M SEO 159 Mean t-stat 5.751*** 5.967*** Non-SEO 294 Mean t-stat Panel B: Full sample period ( ) AQ LEVEL Disclosure type SEO N BHAR 12M BHAR 36M AQ 1 (Low quality) In-bound SEO 59 Mean t-stat 7.317*** 2.886*** Non-SEO 70 Mean t-stat Non in-bound SEO 46 Mean t-stat *** Non-SEO 52 Mean t-stat 2.482** 1.849* AQ 2 (High quality) In-bound SEO 36 Mean t-stat 3.218*** 5.307*** Non-SEO 92 Mean t-stat Non in-bound SEO 18 Mean t-stat Non-SEO 80 Mean t-stat Panel C: Bull market subperiod (pre-gfc period: ) AQ LEVEL Disclosure type SEO N BHAR 12M BHAR 36M AQ 1 (Low quality) In-bound SEO 39 Mean t-stat 5.618*** 2.130** Non-SEO 51 Mean t-stat Non in-bound SEO 36 Mean t-stat 2.740*** 5.532*** Non-SEO 37 Mean t-stat 2.419** Korean Securities Association