144 The Impact of the Act for the Development of Biotech and New Pharmaceuticals Industry on Firm Innovation in Taiwan R&D expenditure usually exhibits a cumulative effect, and previous studies suggest using lagged R&D expenditure or lagged R&D intensity as the variable to explain the innovation output such as patent count, patent citations, or patent adjusted citations (Artz, Norman, Hatfield, and Cardinal, 2010; Beck-Blease, 2011; Kong, 2020). Griliches (1990) finds that there is a lagged relation between patent and R&D expenditure. Artz et al. (2010) examine the effect of R&D, patent, and product innovation on the firm performance and consider the time lag effect for these variables in their regression model. In particular, Artz et al. (2010) set R&D as invested at year t-3 whereas the patent is granted at year t-2 and thus they define the time lag between R&D and patent as about one year. In addition, Beck-Blease (2011) and Kong (2020) use lag R&D one year in explaining the patent output. Thus, following prior literature, we use all control variables and R&D expenditure in year t-1 to explain the patent adjusted citations in year t.18 Appendix Table A1 shows the definitions of all variables. 3.3 Methodology 3.3.1 Intra-industry Analysis and Inter-industry Analysis We could di rect ly and s imply examine the innovat ion of the approved biopharmaceutical firms before and after the Biopharmaceutical Act to show the impact of the Biopharmaceutical Act. However, this methodology may neglect endogeneity problems, which means that changes in innovation may result from omitted variables bias, such as changes in the macroeconomic environment and other unobserved factors.19 To eliminate the endogeneity concern, we identify control firms which have characteristics similar to those of approved biopharmaceutical firms (treated firms), and then compare the difference in innovation between these two groups.20 Specifically, we perform an intra18 We follow previous studies (Aghion et al., 2013; Becker-Blease, 2011) and use the patent application date to identify the year of the patent. This can reduce the time gap problem between innovation input and innovation output because there are usually 2 or 3 years between the patent application date and the publication (or granted) date. Therefore, several empirical studies (Aghion et al., 2013; Chang, Fu, Low, and Zhang, 2015; Chang et al., 2019) use the contemporaneous R&D to explain the patent number or patent citations without considering the time lag between R&D and patent. 19 For example, unapproved biopharmaceutical firms may have the same innovation effect after Biopharmaceutical Act as the approved biopharmaceutical firms. Thus, we cannot infer that the Biopharmaceutical Act improves the innovation of approved biopharmaceutical firms. 20 This is the concept of Difference-in-difference (DID) method, which is widely used to deal with the endogeneity problem.
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