University and Local Innovation: Evidence from College Mergers in China

University and Local Innovation: Evidence from College Mergers in China | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article University and Local Innovation: Evidence from College Mergers in China Yuanrong Xu This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6657557/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract This paper investigates whether larger colleges bring greater benefits for local innovation and higher research productivity. Using college mergers in China as a case study with a difference-in-difference model, this paper finds that mergers lead to a significant increase in local patent applications, signifying enhanced innovation within the cities where the merged colleges are located. This rise in innovation coincides with a notable improvement in the merged college's research productivity, achieved without additional faculty or government funding. These findings suggest economies of scale in the college's impact on local innovation and research output. Further analysis reveals that mergers involving solely four-year research colleges have the most significant positive effect. This aligns with the notion that merging similar institutions facilitates more efficient utilization of research resources. Overall, the paper offers valuable insights for policymakers aiming to enhance local innovation and research efficiency. By promoting resource-sharing initiatives or strategic mergers, particularly among four-year research colleges, policies can unlock the full potential of these institutions for both research excellence and regional economic development. JEL Classification: I23, I25, O31 Merger Higher Education Economies of scale Local Innovation Research productivity Figures Figure 1 1. Introduction The existing literature underscores the crucial role of colleges in driving local innovation. Studies have consistently shown that firms located near colleges tend to be more innovative and productive (Abramovsky & Simpson, 2011 ; Charles, 2021 ; Furman & MacGarvie, 2007 ; Hausman, 2022 ; Jaffe, 1989 ; Woodward et al., 2006 ). Moreover, the establishment of new colleges has been found to generate positive externalities for regional innovation activities (Andersson et al., 2004 ; Andrews, 2023 ; Cowan & Zinovyeva, 2013 ; Fischer & Varga, 2003; Lehnert et al., 2020 ). However, it remains unclear how the size of the college can affect the influence on local innovation. As various countries experienced college mergers to create larger units with the goal of increasing efficiency and productivity (Aarrevaara et al. 2009 ; Norgard & Skodvin, 2002; Papadimitriou & Johnes, 2019 ), the question arises: do these larger colleges exert a more significant impact on local innovation? Addressing this question offers valuable insights into whether college size acts as a moderator in the college-local innovation relationship. To estimate whether larger colleges have a greater effect on local innovation, this paper analyzes data on public college mergers in China between 2004 and 2016. The study covers 54 mergers involving 114 colleges, all initiated by the government. Chinese universities underwent one of the largest-scale mergers globally (Kang & Liu, 2021 ), offering a unique opportunity to investigate the effects of increased college size on local innovation ecosystems. Estimating the causal impact of college mergers on local innovation is complicated by endogeneity. This arises because pre-existing trends in local innovation activity might influence the decision to merge colleges. For instance, cities with a strong track record of innovation might be more likely to see mergers among their colleges. This makes it difficult to isolate the true effect of the merger itself, as colleges located in naturally innovative regions might simply experience continued growth regardless of the merger. To address this endogeneity concern, I utilize a difference-in-difference (DID) model. The DID approach leverages the fact that colleges merged at different points in time. By comparing the changes in local innovation outcomes for cities with merged colleges to those for cities with colleges that have not yet merged, this approach can account for overall trends in local innovation activity over time, isolating the specific effect of the merger on local innovation. This paper reveals an increasing return to scale in the relationship between colleges and local innovation, particularly through mergers. The consolidation of colleges significantly enhances their influence on local innovation. Specifically, the merger results in an increase of 2.170 invention patent applications per 10,000 people annually in the cities where these colleges are located, compared to when these colleges operated independently. This surge in local innovation can be attributed to the increasing return in research productivity and increased collaboration with other institutions following the mergers. Despite no subsequent increase in faculty count or research funding post-merger, in comparison to the combined figures of the individual colleges prior to consolidation, there is a significant rise in both publications per faculty member and collaborative patent applications from the colleges. This finding aligns with Fritsch and Slavtchev's (2007) research that suggests a positive association between research intensity and regional innovation output. Furthermore, the findings reveal a heterogeneous effect based on the type of colleges involved in the merger. Mergers involving four-year research colleges are associated with the largest increase in local patent applications (3.110 increase per 10,000 people). This is followed by mergers of three-year research colleges. Mergers with a mix of these college types show the smallest impact on local innovation. These findings suggest that economies of scale play a more prominent role in fostering local innovation when mergers involve similar colleges. Such colleges can readily share resources and research orientations, leading to a more effective consolidation of expertise. This consolidation likely helps bridge resource gaps and allows the merged institutions to contribute more effectively to local innovation ecosystems. This paper contributes to the literature on college mergers, most of which focus on internal effects like operational efficiency and research output (Agasisti, 2021; Johnes & Tsionas, 2019 ; Kang & Liu, 2021 ; Kyvik, 2002 ; Liu et al., 2018 ; Mizutani et al., 2023 ; Papadimitriou & Johnes, 2019 ;). While previous studies show positive effects on colleges themselves, this paper reveals that mergers also positively impact local innovation, highlighting external benefits for the broader community. Moreover, this paper also adds to the literature on economies of scale in college research productivity in China. Our findings suggest that college mergers can increase research productivity, indicating the existence of economies of scale in research, which is consistent with findings in most countries. This consistency also provides the support for the external validity of the results of this paper. Previous studies show that economies of scale in research vary across countries. Positive effects have been observed in Japan, the US, the UK, Russia, and Norway (Agasisti, 2021; Cohn et al., 1989 ; Glass et al., 1995 ; Izadi et al., 2002 ; Johnes, 1996 ; Johnes & Tsionas, 2019 ; Kyvik, 2002 ; Laband & Lentz, 2003 ; Mizutani et al., 2023 ; Papadimitriou & Johnes, 2019 ), while Italy shows opposite findings (Agasisti, 2019 ; Bonaccorsi & Daraio, 2005 ). In China, results are mixed: some studies (Liu et al., 2018 ; Wan & Peterson, 2007 ) found evidence of economies of scale, while Kang and Liu ( 2021 ) found no such effect. Notably, in the context of China, only Kang and Liu ( 2021 ) address the endogeneity issue associated with mergers. They perform a difference-in-difference approach, but use colleges that never merged as a comparison group. However, this approach assumes that the research output trend for unmerged colleges represents the trend for merged institutions in the absence of a merger, which may not always hold due to significant differences between merged and unmerged colleges. This paper addresses this concern by including only colleges that are going to merge, providing an alternative estimate of the impact of mergers on college efficiency. Most importantly, this paper contributes to the understanding of how colleges influence local innovation by revealing the role of increasing returns to scale in college size. While prior research has documented the positive impact of colleges on local innovation activity (Abramovsky & Simpson, 2011 ; Andersson et al., 2004 ; Andrews, 2023 ; Charles, 2021 ; Cowan & Zinovyeva, 2013 ; Fischer & Varga, 2003; Furman & MacGarvie, 2007 ; Hausman, 2022 ; Jaffe, 1989 ; Lehnert et al., 2020 ; Woodward et al., 2006 ), less is known about the heterogeneous effects of college characteristics on innovation. Aghion et al. ( 2009 ) find positive growth effects in four-year colleges but not in two-year colleges, whereas Andrews (2020) report no differences in the innovation effect across college types. This paper builds on existing work to reveal that consolidated colleges exert a greater positive impact on local innovation compared to their pre-merger counterparts, demonstrating that college size significantly influences innovation outcomes. These findings hold significant policy implications, suggesting that policies promoting regional innovation could benefit from emphasizing economies of scale within the college sector. By encouraging mergers or strategic collaborations that create larger colleges, policymakers can potentially contribute to enhanced research productivity and a stronger positive influence on local innovation ecosystems. 2. Data I examine 54 mergers involving 114 colleges in China between 2004 and 2016, all of which were publicized on the Ministry of Education's website. Yu and Ertl (2014) show that public higher education institutions dominate China’s higher education market and generally hold a stronger reputation, while private colleges account for less than 15 percent of the market. Therefore, I focus exclusively on the mergers of public institutions. All mergers were initiated by the local government and the Ministry of Education. College mergers in China represent one of the largest consolidation efforts in the world, providing a unique opportunity to examine the impact of college size on local innovation. This scale of mergers surpasses those observed in other countries in the literature, such as Norway, which merged 98 colleges in 1994 (Kyvik, 2002 ), Japan, which merged 86 colleges since the mid-2010s (Mizutani et al., 2023 ), and Russia, which merged 38 colleges in 2013 (Agasisti, 2021). Mok ( 2005 ) suggests that the primary motives for university mergers in China are to enhance efficiency and effectiveness. The focus of these mergers is mainly on institutions with functional overlap, narrow specialization, and small scale, aiming to integrate them into comprehensive universities. These mergers are primarily categorized into three types: those consisting solely of four-year research colleges, those involving only three-year vocational colleges, and those combining four-year colleges with three-year vocational colleges. Of the total mergers, 13 belong to the first type, 28 to the second, and 13 to the third. The classification of the merger year, as per King and Liu (2021), is determined by whether the merger took place before or after July 1. If the merger occurs before July 1, the current year is assigned as the year of the merger. Conversely, if the merger takes place after July 1, the subsequent year is designated as the year of the merger. Patent Data To assess local innovation, I adopt the methodology of Aghion et al. ( 2009 ), utilizing the annual number of patent applications per 10,000 people in each city as a measure of the city's innovation level. Patents are commonly recognized as indicators of advancements in cutting-edge technologies, thus serving as a reliable proxy for innovation. This approach is consistent with the existing literature, which frequently uses patent application counts as a measure of innovation activity (Aghion et al., 2009 ; Andrews, 2020; Charles, 2021 ). The patent data used in this study are sourced from the Chinese Research Data Services (CNRDS) Platform, and city population data are obtained from the China City Statistical Yearbook. Spanning from 1990 to 2019, the patent data include patent applications at both the city and institution levels within China. The analysis focuses on i nvention patents, considered the strongest indicator of innovative activity. In China, patents are classified into three types: invention, utility model, and design. Invention patents, which protect new technical solutions relating to products, processes, or improvements thereof, are most closely associated with innovative activities. Utility model patents, focusing on new shapes or configurations of products, prioritize practical application over significant innovation. Design patents protect the ornamental aspects of manufactured articles and have the least connection to innovation activities. College Characteristics To investigate changes within colleges following mergers, I utilize data on the number of faculty, government research funding, and academic paper publications from "The Compilation of Scientific and Technological Statistics of Chinese Higher Education" (2001–2017, excluding 2003 and 2004 data). This dataset, combined with college-level patent application information, provides a comprehensive view of internal college dynamics post-merger. The number of faculty serves as a proxy for college size, potentially impacting research capacity and collaboration opportunities in the post-merger environment. Government research funding indicates whether the college receives increased governmental support post-merger. The number of publications per faculty member serves as an indicator of the college's research productivity. College-level patent data encompasses all three patent types (invention, utility, and design) and distinguishes between independent and collaborative applications, thus illustrating the college's research productivity and its influence on other organizations Table 1 presents a summary of the patent data and college characteristics. At the city level, invention and utility patents have similar application rates, both significantly higher compared to design patents. At the college level, the patent application data includes both patents applied for independently by the college and those collaboratively applied for with third parties. In both instances, patents outnumber the other two types, suggesting colleges focus more on innovation activities. Table 1 Descriptive Statistics N Mean SD Min Max Patent applications City level Invention Patent 1,102 3.867 9.275 0.014 86.447 Utility Patent 1,102 4.025 7.643 0.041 69.883 Design Patent 1,102 1.490 3.055 0 32.134 College Level Independent Invention Patent 1,620 49.787 212.880 0 2.617 Utility Patent 1,620 18.733 78.583 0 1,274 Design Patent 1,620 1.436 9.902 0 211 Collaborative Invention Patent 1,620 4.398 25.383 0 518 Utility Patent 1,620 1.553 6.021 0 78 Design Patent 1,620 0.089 0.996 0 24 College Characteristics Faculties 459 1452.837 2515.283 13 17170 Research Funding (million yuan) 434 127.231 381.268 0 3125.149 Publication/Faculty 459 1353.185 3119.5 0 21,134 Note. City-level patent data is calculated as patent applications per 10,000 people. 3. Empirical strategy To estimate the college merger on local innovation, it is essential to address the potential endogeneity issue. A pre-existing increasing (or decreasing) trend in local innovation activities might trigger the merger, leading to an upward (or downward) bias in the results. To mitigate the endogeneity issue and given the occurrence of college mergers in different years, I employ a difference-in-differences model, the regression equation is structured as follows: $$\:{Patent}_{it}={\beta\:}_{0}+{\beta\:}_{1}merg{e}_{it}+yea{r}_{t}+{college}_{i}+{ϵ}_{it}$$ 1 where \(\:{Patent}_{it}\) represents the number of patent applications in the city of college \(\:i\) in year \(\:t\) . \(\:me{rge}_{it}\) is an indicator function equal to 1 if the college has merged in year \(\:t\) . \(\:{college}_{i}\) and \(\:yea{r}_{t}\) are college fixed effect and year fixed effect, respectively, which control for local patent applications in the reference year and time-variant changes in patenting across cities. Consequently, \(\:{\beta\:}_{1}\) captures the change in local patent applications attributable to the merger. If there is an increasing return to scale in the size of the college on its effect on local innovation activities, a notable increase in patent applications in the cities where the college is located should be observed after the merger. This increase would amplify the difference in patent applications compared to other cities. Consequently, a significant and positive \(\:{\beta\:}_{1}\) should be observed. Conversely, if no such effect exists, the difference in patent applications among these cities should remain unchanged, resulting in an insignificant \(\:{\beta\:}_{1}\) ​. Recent studies (Callaway & Sant’Anna, 2020; De Chaisemartin & D’Haultfoeuille, 2020 ; Goodman-Bacon, 2021 ) highlight potential biases in the traditional two-way fixed effects approach (TWFE) when estimating treatment effects in DID models with varying treatment timing, if treatment effects vary across time or units. To address this issue, I adopt the robust approach developed by Callaway and Sant’Anna (2020). Their method estimates the treatment effect for each time period based on the group classified by the first treated time and aggregates these estimates to compute the average treatment effect. Furthermore, I provide estimates using several alternative approaches that address the bias caused by heterogeneous treatment effects, as recommended by Borusyak, Jaravel, & Spiess ( 2024 ), De Chaisemartin & D’Haultfoeuille ( 2020 ), Gardner ( 2022 ), and Wooldridge (2021), to confirm the robustness of the findings. These alternative approaches share similarities with Callaway and Sant’Anna (2020) but differ in constructing the control group and weighting across different groups and time periods. The model employs college fixed effects instead of city fixed effects due to the presence of cities with multiple college mergers occurring in different years. If there were no multiple mergers in the same city, college fixed effects and city fixed effects would be equivalent. However, in cases where multiple mergers exist, the college fixed effects allow for independent estimation for each merger within the model. Specifically, the model utilizes only the years in which the merger events do not overlap in a city. For the first merger, only data from before the second merger are used for estimation, and for the second merger, only data from after the first merger are used. The model restricts analysis to cities where at least one college merger occurred. This approach helps mitigate potential selection bias, as cities with merged colleges may inherently differ from those without mergers. To further validate the findings, a robustness check including all cities is also conducted. 4. Results 4.1 Local innovation This section investigates the impact of college mergers on the number of local patent applications, aiming to determine whether larger institutions have a greater influence on local innovations. Table 2 presents the findings regarding the number of invention, utility, and design patent applications per capita in the cities where the merged colleges are located. The results present a substantial increase in invention patent applications post-merger, with an average rise of 2.170 applications per 10,000 people. This suggests a strong positive effect of mergers on groundbreaking innovation within local contexts. Utility patent applications also exhibited an increase, averaging 1.313 applications, indicating a potential rise in practical innovation alongside fundamental advancements. However, there is no significant change observed in design patent applications, which aligns with expectations given their minimal connection to technological innovation activities. These findings suggest that college mergers can significantly enhance local innovation activities, reflecting an increasing return to scale of college size on local innovation effects. Consolidating multiple colleges into larger institutions appears to stimulate local innovation, highlighting the potential benefits of scaling up educational and research capacities through mergers. Table 2 The effect of college merger on local innovation Patent Invention Utility Design Merger 2.170*** 1.313** 0.597 (0.660) (0.564) (0.633) Observations 951 951 951 Note: * p < 0.1; ** p < 0.05; *** p < 0.01. The effect of college merger on patent applications within the city where the college is located. Standard errors in parentheses. Standard errors are clustered at the college level. All estimations control for year fixed effect and college fixed effect. The estimates follow the approach outlined by Callaway and Sant’Anna (2020). 4.2 Robustness check To ensure the robustness of the estimates presented in Table 2 , I conduct additional analyses as detailed in Table 3 . The estimates are examined under various scenarios to assess their sensitivity to different sample compositions and time periods. Columns 1 to 6 in Table 3 present estimates derived from Eq. ( 1 ) using different periods of data. Columns 7 to 9 provide estimates based on balanced data samples, and Columns 10 to 12 include cities that have never undergone a college merger. Across all these alternative estimations, the effect on invention patent applications remains significant. This reinforces the positive impact of mergers on innovation activities. For utility patents, which require a less stringent level of innovation, the significance level occasionally varies across estimations. However, the magnitude of the effect remains consistently positive, suggesting a potential increase in practical innovation alongside fundamental advancements. As expected, design patents, requiring the least innovative effort, show no significant effect in any of the estimates. Additionally, their point estimates are the smallest among the three patent categories. Table 4 examines the robustness of the findings by employing alternative approaches to address potential biases in the traditional TWFE model. These approaches, proposed by Gardner ( 2022 ), Borusyak, Jaravel, and Spiess ( 2024 ), Wooldridge (2021), and De Chaisemartin and D’Haultfoeuille ( 2020 ), utilize various methods for constructing control groups and weighting observations. The results across all these approaches (Columns 1–12) are consistent with initial findings, that invention patent applications exhibit the largest increase following mergers. Utility patent applications also show a positive but smaller increase. As expected, design patents, exhibit minimal change across all estimations. Table 3 The effect of college merger on local innovation with alternative sample (1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) 10 years 5 years Balanced Data Never-treated cities Patent Invention Utility Design Invention Utility Design Invention Utility Design Invention Utility Design Merger 1.434** 0.511 0.274 2.184** 0.642 -0.057 1.797** 1.323* 0.858 3.053*** 1.700* 0.247 (0.609) (0.596) (0.707) (0.881) (0.488) (0.326) (0.863) (0.740) (0.976) (1.133) (0.890) (0.561) Observations 654 654 654 320 320 320 563 563 563 8203 8203 8203 Note: * p < 0.1; ** p < 0.05; *** p < 0.01. The effect of college merger on patent applications within the city where the college is located with alternative samples. Columns 1 to 3 include samples where the relative treatment time ranges from − 10 years to 10 years. Columns 4 to 6 include samples where the relative treatment time ranges from − 5 years to 5 years. Columns 7 to 9 only include samples that span every year from 1990 to 2019. Columns 10 to 12 include samples from cities that have never experienced a college merger. Standard errors in parentheses. Standard errors are clustered at the college level. All estimations control for year fixed effect and college fixed effect. The estimates follow the approach outlined by Callaway and Sant’Anna (2020). Table 4 The effect of college merger on patent applications with alternative approach (1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) Gardner ( 2022 ) Borusyak et al. ( 2024 ) Wooldridge (2021) De Chaisemartin and D’Haultfoeuille ( 2020 ) Invention Utility Design Invention Utility Design Invention Utility Design Invention Utility Design Merger 5.650*** 5.249*** 1.601*** 2.421*** 1.432** 0.723 2.421*** 1.432** 0.723 2.131*** 1.257** 0.550 (1.253) (0.920) (0.539) (0.721) (0.573) (0.572) (0.614) (0.678) (0.557) (0.662) (0.587) (0.632) Observations 1102 1102 1102 953 953 953 951 951 951 456 456 456 Note: * p < 0.1; ** p < 0.05; *** p < 0.01. The effect of college merger on patent applications within the city where the college is located with alternative DID estimation approaches. Standard errors in parentheses. Standard errors are clustered at the college level. All estimations control for year fixed effect and college fixed effect. Parallel trend To validate the estimates of the DID model, it is essential to verify the parallel trend assumption, which suggests that these cities exhibited consistent differences in patent applications prior to the college merger. To test this assumption, an event study model is estimated. This model assesses the effect of the merger for each year before and after the merger. If changes in patent applications are induced by the college merger, significant changes in patent applications should only be observed in the periods following the merger. The estimated equation is as follows: $$\:{Patent}_{it}={\beta\:}_{0}+{\Sigma\:}{\beta\:}_{\text{t}}colleg{e}_{i}\text{*}{\text{t}\text{i}\text{m}\text{e}}_{\text{t}}+yea{r}_{t}+{college}_{i}+{ϵ}_{it}$$ 2 Where \(\:{\text{t}\text{i}\text{m}\text{e}}_{\text{t}}\) is the relative years to the merger, therefore \(\:{\beta\:}_{\text{t}}\) capture the change in patent applications in the cities that the merged colleges located in, in each year. Same as the estimates in Table 2 , The estimation is followed Callaway and Sant’Anna (2020)’s approach, to address the bias caused by the TWFE. Figure 1 plots the \(\:{\beta\:}_{\text{t}}\) for each time periods, As noted by Borusyak and Jaravel (2017), when there are no never-treated units in the sample, two relative time indicators must be omitted to avoid multicollinearity. Following their suggestions, the most negative time period (furthest in the past) and the period immediately before the merger are omitted. This omission allows the remaining coefficients \(\:{\beta\:}_{\text{t}}\) to represent the average differences in patent applications between the treatment and control groups for specific periods before the merger. Figure 1 demonstrates that the parallel trend assumption holds, as the difference in patent applications among these cities remains consistent before the merger. After the merger, invention patents show the most significant increase, followed by utility patents, which also exhibit a less significant increase. The change in design patent applications is subtle and insignificant. This finding aligns with the results in Table 1 , indicating that college mergers can significantly enhance local innovation, and this effect persists over time. Other cities Another concern with these estimates is whether simultaneous changes at the national or local level may have influenced innovation activities. Given that the mergers in the data occurred over different years spanning eight years, a nationwide trend is less likely. However, to address the possibility of simultaneous changes within a province that may induce an increase in innovation activities, I examine the effect of college mergers on patent applications in other cities within the same province. Table 5 provides the results of this analysis. The findings show no significant effect of college mergers on patent applications in other cities within the same province. This suggests that there is no increasing trend in patent applications coinciding with the year of the college merger within the province, thereby reinforcing the validity of the observed effects being attributed to the mergers themselves. Table 5 The effect of college merger on local innovation in other cities within the same province Patent Invention Utility Design Merger -0.563 -0.543 0.245 (0.684) (0.623) (0.607) Observations 6753 6753 6753 Note: * p < 0.1; ** p < 0.05; *** p < 0.01. The effect of college merger on patent applications in other cities within the same province. Standard errors in parentheses. Standard errors are clustered at the city level. All estimations control for year fixed effect and city fixed effect. The estimates follow the approach outlined by Callaway and Sant’Anna (2020). 4.2 Mechanism As noted by Cohen et al. ( 2002 ) and Zucker et al. ( 2002 ), knowledge spillovers are a key mechanism through which colleges impact local innovation. Building on the observed effect of college mergers on patent applications, I investigate the internal changes within colleges that may drive local innovation. Table 6 presents estimates on the impact of mergers on faculty size, research funding, and research productivity. The results indicate that the merged colleges maintain a size comparable to the sum of the independent colleges prior to consolidation, with no significant increase in the number of faculty post-merger. Similarly, government funding for research remains at the combined level of independent colleges before the merger. Despite these unchanged inputs, research productivity, measured by publications per faculty, increases by 0.281 publications after the merger. This finding suggests that the positive effects observed extend beyond just local patent applications. Mergers appear to lead to increased efficiency within colleges, potentially allowing them to utilize existing resources more effectively. This aligns with previous research on college mergers and operational efficiency in other contexts (Kyvik, 2002 ; Johnes & Papadimitriou, 2019 ; Mizutani et al., 2023 ). More importantly, this finding shows that the merger enables an increasing return not only in local patent applications but also in the research productivity of the college. As suggested by Fritsch & Slavtchev ( 2007 ), research intensity and quality play a crucial role in influencing regional innovation output. This heightened productivity likely contributes to the observed larger effect on local innovation. Table 7 further explores the changes within the college by examining college-level patent applications. The data encompasses both independent applications by the college and collaborative applications with other organizations. Here, an overall increase in patent applications post-merger is observed. Invention patents, representing the most innovative category, show the most significant rise, followed by utility patents and design patents. Notably, the number of collaborative patent applications also increases after the merger. These findings suggest that mergers can stimulate not only in-house research and development, but also external collaboration. This synergy between internal efficiency and external partnerships likely contributes to the enhanced local innovation observed after mergers. Table 6 The effect of college merger on college characteristics Number of Faculty Government research funding Publications per faculty Merger 843.240 182.108 0.281** (769.629) (125.862) (0.141) Observations 183 139 183 Note: * p < 0.1; ** p < 0.05; *** p < 0.01. The effect of college merger on college characteristics. Standard errors in parentheses. Standard errors are clustered at the college level. All estimations control for year fixed effect and college fixed effect. The estimates follow the approach outlined by Callaway and Sant’Anna (2020). Table 7 The effect of college merger on college-level patent applications Independent Collaborative Patent Invention Utility Design Invention Utility Design Merger 54.531*** 21.542*** 3.539** 5.179** 1.953*** 0.243* (17.175) (6.626) (1.644) (2.319) (0.526) (0.142) Observations 1404 1404 1404 1404 1404 1404 Note: * p < 0.1; ** p < 0.05; *** p < 0.01. The effect of college merger on college-level patent applications. Standard errors in parentheses. Standard errors are clustered at the college level. All estimations control for year fixed effect and college fixed effect. The estimates follow the approach outlined by Callaway and Sant’Anna (2020). 4.3 Heterogeneity effect Given the observed effect on local innovation, I also explore whether the impact of college mergers on local innovation, measured by patent applications, varies depending on the colleges involved. The analysis categorizes mergers into three groups: four-year research colleges only, three-year vocational colleges only, and mixed mergers involving both research and vocational colleges. Table 8 reveals that mergers involving solely four-year research colleges lead to the largest increase in invention patent applications, followed by mergers involving three-year vocational colleges. Mixed mergers have the smallest positive effect. This pattern likely stems from the more efficient utilization of research resources when merging similar institutions. Four-year research colleges, with their inherent focus on research activities, are likely to experience a more significant boost to innovation compared to vocational college mergers. Table 9 illustrates that changes in publications per faculty member within colleges correspond to their impact on local patent applications. Four-year colleges experience a significant rise in publications per faculty member after a merger, even without parallel increases in faculty size or research funding. In contrast, mixed mergers exhibit a smaller, statistically insignificant change in publication rates. Unfortunately, the limited number of vocational college merger cases with available data in The Compilation of Scientific and Technological Statistics of Chinese Higher Education prevents an estimation of their post-merger research productivity changes. Patent application data by college type further illuminate the differential effects. Mergers involving four-year colleges lead to a substantial increase in both independent and collaborative patent applications, suggesting a broad-based boost to innovation activity. Mixed mergers show a larger increase in independent invention patent applications but no change in collaborative patent applications. Conversely, vocational college mergers exhibit a smaller increase in independent patent applications compared to mixed mergers but show a significant rise in collaborative patent applications. This contrasting pattern, coupled with the observed larger positive effect of vocational college mergers on local innovation, suggests that collaboration plays a crucial role in enhancing local innovation. Table 8 The heterogeneity effect on local innovation Four-year colleges Three-year colleges Mixed merger Patent Invention Utility Design Invention Utility Design Invention Utility Design Merger 3.110*** 2.502*** 2.398* 2.233* 0.834 -0.447 1.174** 0.987* 0.587 (0.945) (0.876) (1.444) (1.220) (0.883) (0.590) (0.537) (0.578) (0.527) Observations 197 197 197 467 467 467 278 278 278 Note: * p < 0.1; ** p < 0.05; *** p < 0.01. The effect of college merger on patent applications within the city where the college is located by the type of merger. Standard errors in parentheses. Standard errors are clustered at the college level. All estimations control for year fixed effect and college fixed effect. The estimates follow the approach outlined by Callaway and Sant’Anna (2020). Table 9 The heterogeneity effect of college merger on college characteristics and college-level patent application College Characteristics Independent patent Collaborative patent Number of Faculty Government research funding Publications per faculty Invention Utility Design Invention Utility Design Four-year colleges Merger 1477.500 191125.375 0.352*** 72.573*** 28.208*** 3.789** 14.906* 3.842*** 0.229 (1345.103) (1.48e + 05) (0.129) (17.141) (8.691) (1.811) (7.848) (1.282) (0.302) Observations 64 42 64 338 338 338 338 338 338 Three-year colleges Merger 9.665** 19.593** 10.383 1.504* 2.049** 0.846 (4.128) (9.362) (7.808) (0.893) (0.829) (0.711) Observations 728 728 728 728 728 728 Mixed merger Merger 142.713 73194.483 0.142 104.266** 14.742 3.348* 3.098 0.953 0.701 (129.825) (58036.328) (0.310) (51.606) (15.973) (2.014) (2.391) (1.097) (0.518) Observations 73 55 73 338 338 338 338 338 338 Note: * p < 0.1; ** p < 0.05; *** p < 0.01. The effect of college merger on college characteristics and college-level patent application by the type of merger. Standard errors in parentheses. Standard errors are clustered at the college level. All estimations control for year fixed effect and college fixed effect. The estimates follow the approach outlined by Callaway and Sant’Anna (2020). 5. Conclusion This paper explores the relationship between college mergers and local innovation and research productivity. The analysis reveals that mergers lead to a significant increase in patent applications within the city, suggesting economies of scale in the impact of colleges on local innovation activities. Additionally, merged colleges experience a boost in research productivity, potentially contributing to the rise in local innovation. Further investigation into different merger types highlights that mergers involving four-year research colleges are the primary driver of these positive effects. This aligns with their research-oriented focus, suggesting that merging similar institutions leads to a more efficient utilization of research resources, potentially fueling local innovation. These findings offer valuable insights for policymakers aiming to enhance local innovation and research efficiency. By encouraging strategic mergers or facilitating resource-sharing initiatives, policies can be designed to specifically support the creation of larger research colleges. This, in turn, could unlock their full potential for both research productivity and local economic development. Declarations Author Contribution X.Y. conceived and designed the study, collected and analyzed the data, interpreted the results, and wrote the manuscript. As the sole author, X.Y. is responsible for all aspects of the work. Data Availability The data supporting the findings of this study are not publicly available. They were obtained from the Chinese Research Data Services Platform (CNRDS) at https://www.cnrds.com and are subject to access restrictions. References Aarrevaara, T., Dobson, I., & Elander, C. (2009). Brave new world: Higher education reform in Finland. Higher Education Management and Policy , 21 (2), 1–18. Abramovsky, L., & Simpson, H. (2011). Geographic proximity and firm–university innovation linkages: Evidence from Great Britain. Journal of Economic Geography , 11 (6), 949–977. Agasisti, T., Egorov, A., & Maximova, M. (2021). Do merger policies increase universities’ efficiency? Evidence from a fuzzy regression discontinuity design. Applied Economics , 53 (2), 185–204. https://doi.org/10.1080/00036846.2020.1803488 Agasisti, T., & Gralka, S. (2019). The transient and persistent efficiency of Italian and German universities: A stochastic frontier analysis. Applied Economics , 51 (46), 5012–5030. https://doi.org/10.1080/00036846.2019.1606409 Aghion, P., Boustan, L., Hoxby, C., & Vandenbussche, J. (2009). The causal impact of education on economic growth: Evidence from US. Brookings Papers on Economic Activity , 1 (1), 1–73. Andersson, R., Quigley, J. M., & Wilhelmson, M. (2004). University decentralization as regional policy: The Swedish experiment. Journal of Economic Geography , 4 (4), 371–388. https://doi.org/10.1093/jnlecg/lbh031 Andrews, M. J. (2023). How Do Institutions of Higher Education Affect Local Invention? Evidence from the Establishment of US Colleges. American Economic Journal: Economic Policy , 15 (2), 1–41. https://doi.org/10.1257/pol.20200320 Bonaccorsi, A., & Daraio, C. (2005). Exploring size and agglomeration effects on public research productivity. Scientometrics , 63 (1), 87–120. https://doi.org/10.1007/s11192-005-0205-3 Borusyak, K., Jaravel, X., & Spiess, J. (2024). Revisiting event-study designs: Robust and efficient estimation. Review of Economic Studies , rdae007. Callaway, B., & Sant’Anna, P. H. (2021). Difference-in-differences with multiple time periods. Journal of Econometrics , 225 (2), 200–230. Charles, C. (2021). Company-College Co-Location: Do Universities Create Local Innovation Clusters? (SSRN Scholarly Paper 3499277). https://doi.org/10.2139/ssrn.3499277 Cohen, W. M., Nelson, R. R., & Walsh, J. P. (2002). Links and Impacts: The Influence of Public Research on Industrial R&D. Management Science , 48 (1), 1–23. https://doi.org/10.1287/mnsc.48.1.1.14273 Cohn, E., Rhine, S. L. W., & Santos, M. C. (1989). Institutions of Higher Education as Multi-Product Firms: Economies of Scale and Scope. The Review of Economics and Statistics , 71 (2), 284–290. https://doi.org/10.2307/1926974 Cowan, R., & Zinovyeva, N. (2013). University effects on regional innovation. Research Policy , 42 (3), 788–800. https://doi.org/10.1016/j.respol.2012.10.001 De Chaisemartin, C., & d’Haultfoeuille, X. (2020). Two-way fixed effects estimators with heterogeneous treatment effects. American Economic Review , 110 (9), 2964–2996. Fritsch, M., & Slavtchev, V. (2007). Universities and Innovation in Space. Industry & Innovation , 14 (2), 201–218. https://doi.org/10.1080/13662710701253466 Furman, J. L., & MacGarvie, M. J. (2007). Academic science and the birth of industrial research laboratories in the US pharmaceutical industry. Journal of Economic Behavior & Organization , 63 (4), 756–776. Gardner, J. (2022). Two-stage differences in differences (arXiv:2207.05943). arXiv. http://arxiv.org/abs/2207.05943 Glass, J. C., McKillop, D. G., & Hyndman, N. (1995). Efficiency in the provision of university teaching and research: An empirical analysis of UK universities. Journal of Applied Econometrics , 10 (1), 61–72. https://doi.org/10.1002/jae.3950100106 Goodman-Bacon, A. (2021). Difference-in-differences with variation in treatment timing. Journal of Econometrics , 225 (2), 254–277. Hausman, N. (2022). University innovation and local economic growth. Review of Economics and Statistics , 104 (4), 718–735. Izadi, H., Johnes, G., Oskrochi, R., & Crouchley, R. (2002). Stochastic frontier estimation of a CES cost function: The case of higher education in Britain. Economics of Education Review , 21 (1), 63–71. https://doi.org/10.1016/S0272-7757(00)00044-3 Jaffe, A. B. (1989). Real effects of academic research. The American Economic Review , 957–970. Johnes, G. (1996). Multi-product cost functions and the funding of tuition in UK universities. Applied Economics Letters , 3 (9), 557–561. https://doi.org/10.1080/135048596355943 Johnes, J., & Tsionas, M. G. (2019). Dynamics of Inefficiency and Merger in English Higher Education From 1996/97 to 2008/9: A Comparison of Pre‐Merging, Post‐Merging and Non‐Merging Universities Using Bayesian Methods. The Manchester School , 87 (3), 297–323. https://doi.org/10.1111/manc.12262 Kang, Y., & Liu, R. (2021). Does the merger of universities promote their scientific research performance? Evidence from China. Research Policy , 50 (1), 104098. Kyvik, S. (2002). The merger of non-university colleges in Norway. Higher Education , 44 (1), 53–72. https://doi.org/10.1023/A:1015561027230 Laband, D. N., & Lentz, B. F. (2003). New Estimates of Economies of Scale and Scope in Higher Education. Southern Economic Journal , 70 (1), 172–183. https://doi.org/10.1002/j.2325-8012.2003.tb00562.x Lehnert, P., Pfister, C., & Backes-Gellner, U. (2020). Employment of R&D personnel after an educational supply shock: Effects of the introduction of Universities of Applied Sciences in Switzerland. Labour Economics , 66 , 101883. Liu, Q., Patton, D., & Kenney, M. (2018). Do university mergers create academic synergy? Evidence from China and the Nordic Countries. Research Policy , 47 (1), 98–107. Mizutani, F., Tanaka, T., & Nakayama, N. (2023). Economies of scale and scope, merger effects, and ownership difference: An empirical analysis of universities in Japan. Education Economics , 0 (0), 1–24. https://doi.org/10.1080/09645292.2023.2260574 Mok, K. (2005). Globalization and educational restructuring: University merging and changing governance in China. Higher Education , 50 (1), 57–88. https://doi.org/10.1007/s10734-004-6347-z Norgård, J. D., & Skodvin, O.-J. (2002). The importance of geography and culture in mergers: A Norwegian institutional case study. Higher Education , 44 (1), 73–90. https://doi.org/10.1023/A:1015513111300 Papadimitriou, M., & Johnes, J. (2019). Does merging improve efficiency? A study of English universities. Studies in Higher Education , 44 (8), 1454–1474. https://doi.org/10.1080/03075079.2018.1450851 Wan, Y., & Peterson, M. W. (2007). A case study of a merger in Chinese higher education: The motives, processes, and outcomes. International Journal of Educational Development , 27 (6), 683–696. https://doi.org/10.1016/j.ijedudev.2006.07.007 Woodward, D., Figueiredo, O., & Guimaraes, P. (2006). Beyond the Silicon Valley: University R&D and high-technology location. Journal of Urban Economics , 60 (1), 15–32. Yu, K., & Ertl, H. (2010). Equity in Access to Higher Education in China. Chinese Education & Society . https://doi.org/10.2753/CED1061-1932430602 Zucker, L. G., Darby, M. R., & Armstrong, J. S. (2002). Commercializing Knowledge: University Science, Knowledge Capture, and Firm Performance in Biotechnology. Management Science , 48 (1), 138–153. https://doi.org/10.1287/mnsc.48.1.138.14274 Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6657557","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":456294012,"identity":"8c438596-9d69-4bb8-8443-30e902da3f60","order_by":0,"name":"Yuanrong Xu","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAtElEQVRIiWNgGAWjYLCCDzYgkrHxANE6GGekgakG4rUw86RBGMRpMbiRY/bZJsEmcW37YaAtNTbRBLVIzsgxnp2TkGZsdiYRqOVYWm4DIS38EjnGzLk/DsuZHQBqYWw4TFgLG0iLRcJhHrPzD4nUAraFIQFoyw1ibZHseVbM2APyyw2gLQnE+MXgePJmhh/AENt2Pv3hgw81NoS1MDBwGCDYCYSVgwD7A+LUjYJRMApGwcgFAD2gQT4Tb+iDAAAAAElFTkSuQmCC","orcid":"","institution":"Shanghai Lixin University of Accounting and Finance","correspondingAuthor":true,"prefix":"","firstName":"Yuanrong","middleName":"","lastName":"Xu","suffix":""}],"badges":[],"createdAt":"2025-05-13 16:53:05","currentVersionCode":1,"declarations":{"humanSubjects":false,"vertebrateSubjects":false,"conflictsOfInterestStatement":false,"humanSubjectEthicalGuidelines":false,"humanSubjectConsent":false,"humanSubjectClinicalTrial":false,"humanSubjectCaseReport":false,"vertebrateSubjectEthicalGuidelines":false},"doi":"10.21203/rs.3.rs-6657557/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6657557/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":83337182,"identity":"7484e8e6-ff26-444a-8ca2-9c42e3ca5a4d","added_by":"auto","created_at":"2025-05-23 09:26:53","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":109715,"visible":true,"origin":"","legend":"\u003cp\u003eThe average treatment effect of college merger on patent applications. As noted by Borusyak and Jaravel (2017), when there are no never-treated units in the sample, two relative time indicators must be omitted. The most negative time period (furthest in the past) and the period before the merger are omitted. The estimates follow the approach outlined by Callaway and Sant’Anna (2020).\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-6657557/v1/e599c2e03ed074490322187f.png"},{"id":84188500,"identity":"9313377f-04fc-4940-bf34-6f90c0eb5783","added_by":"auto","created_at":"2025-06-09 06:08:51","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1030786,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6657557/v1/408d13a0-0666-455a-854e-4aacdbedf9af.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"University and Local Innovation: Evidence from College Mergers in China","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eThe existing literature underscores the crucial role of colleges in driving local innovation. Studies have consistently shown that firms located near colleges tend to be more innovative and productive (Abramovsky \u0026amp; Simpson, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Charles, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Furman \u0026amp; MacGarvie, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2007\u003c/span\u003e; Hausman, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Jaffe, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e1989\u003c/span\u003e; Woodward et al., \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2006\u003c/span\u003e). Moreover, the establishment of new colleges has been found to generate positive externalities for regional innovation activities (Andersson et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2004\u003c/span\u003e; Andrews, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Cowan \u0026amp; Zinovyeva, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Fischer \u0026amp; Varga, 2003; Lehnert et al., \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2020\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eHowever, it remains unclear how the size of the college can affect the influence on local innovation. As various countries experienced college mergers to create larger units with the goal of increasing efficiency and productivity (Aarrevaara et al. \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2009\u003c/span\u003e; Norgard \u0026amp; Skodvin, 2002; Papadimitriou \u0026amp; Johnes, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2019\u003c/span\u003e), the question arises: do these larger colleges exert a more significant impact on local innovation? Addressing this question offers valuable insights into whether college size acts as a moderator in the college-local innovation relationship.\u003c/p\u003e \u003cp\u003eTo estimate whether larger colleges have a greater effect on local innovation, this paper analyzes data on public college mergers in China between 2004 and 2016. The study covers 54 mergers involving 114 colleges, all initiated by the government. Chinese universities underwent one of the largest-scale mergers globally (Kang \u0026amp; Liu, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), offering a unique opportunity to investigate the effects of increased college size on local innovation ecosystems.\u003c/p\u003e \u003cp\u003eEstimating the causal impact of college mergers on local innovation is complicated by endogeneity. This arises because pre-existing trends in local innovation activity might influence the decision to merge colleges. For instance, cities with a strong track record of innovation might be more likely to see mergers among their colleges. This makes it difficult to isolate the true effect of the merger itself, as colleges located in naturally innovative regions might simply experience continued growth regardless of the merger.\u003c/p\u003e \u003cp\u003eTo address this endogeneity concern, I utilize a difference-in-difference (DID) model. The DID approach leverages the fact that colleges merged at different points in time. By comparing the changes in local innovation outcomes for cities with merged colleges to those for cities with colleges that have not yet merged, this approach can account for overall trends in local innovation activity over time, isolating the specific effect of the merger on local innovation.\u003c/p\u003e \u003cp\u003eThis paper reveals an increasing return to scale in the relationship between colleges and local innovation, particularly through mergers. The consolidation of colleges significantly enhances their influence on local innovation. Specifically, the merger results in an increase of 2.170 invention patent applications per 10,000 people annually in the cities where these colleges are located, compared to when these colleges operated independently.\u003c/p\u003e \u003cp\u003eThis surge in local innovation can be attributed to the increasing return in research productivity and increased collaboration with other institutions following the mergers. Despite no subsequent increase in faculty count or research funding post-merger, in comparison to the combined figures of the individual colleges prior to consolidation, there is a significant rise in both publications per faculty member and collaborative patent applications from the colleges. This finding aligns with Fritsch and Slavtchev's (2007) research that suggests a positive association between research intensity and regional innovation output.\u003c/p\u003e \u003cp\u003eFurthermore, the findings reveal a heterogeneous effect based on the type of colleges involved in the merger. Mergers involving four-year research colleges are associated with the largest increase in local patent applications (3.110 increase per 10,000 people). This is followed by mergers of three-year research colleges. Mergers with a mix of these college types show the smallest impact on local innovation.\u003c/p\u003e \u003cp\u003eThese findings suggest that economies of scale play a more prominent role in fostering local innovation when mergers involve similar colleges. Such colleges can readily share resources and research orientations, leading to a more effective consolidation of expertise. This consolidation likely helps bridge resource gaps and allows the merged institutions to contribute more effectively to local innovation ecosystems.\u003c/p\u003e \u003cp\u003eThis paper contributes to the literature on college mergers, most of which focus on internal effects like operational efficiency and research output (Agasisti, 2021; Johnes \u0026amp; Tsionas, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Kang \u0026amp; Liu, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Kyvik, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2002\u003c/span\u003e; Liu et al., \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Mizutani et al., \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Papadimitriou \u0026amp; Johnes, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2019\u003c/span\u003e;). While previous studies show positive effects on colleges themselves, this paper reveals that mergers also positively impact local innovation, highlighting external benefits for the broader community.\u003c/p\u003e \u003cp\u003eMoreover, this paper also adds to the literature on economies of scale in college research productivity in China. Our findings suggest that college mergers can increase research productivity, indicating the existence of economies of scale in research, which is consistent with findings in most countries. This consistency also provides the support for the external validity of the results of this paper.\u003c/p\u003e \u003cp\u003ePrevious studies show that economies of scale in research vary across countries. Positive effects have been observed in Japan, the US, the UK, Russia, and Norway (Agasisti, 2021; Cohn et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e1989\u003c/span\u003e; Glass et al., \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e1995\u003c/span\u003e; Izadi et al., \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2002\u003c/span\u003e; Johnes, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e1996\u003c/span\u003e; Johnes \u0026amp; Tsionas, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Kyvik, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2002\u003c/span\u003e; Laband \u0026amp; Lentz, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2003\u003c/span\u003e; Mizutani et al., \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Papadimitriou \u0026amp; Johnes, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2019\u003c/span\u003e), while Italy shows opposite findings (Agasisti, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Bonaccorsi \u0026amp; Daraio, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2005\u003c/span\u003e). In China, results are mixed: some studies (Liu et al., \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Wan \u0026amp; Peterson, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2007\u003c/span\u003e) found evidence of economies of scale, while Kang and Liu (\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) found no such effect.\u003c/p\u003e \u003cp\u003eNotably, in the context of China, only Kang and Liu (\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) address the endogeneity issue associated with mergers. They perform a difference-in-difference approach, but use colleges that never merged as a comparison group. However, this approach assumes that the research output trend for unmerged colleges represents the trend for merged institutions in the absence of a merger, which may not always hold due to significant differences between merged and unmerged colleges. This paper addresses this concern by including only colleges that are going to merge, providing an alternative estimate of the impact of mergers on college efficiency.\u003c/p\u003e \u003cp\u003eMost importantly, this paper contributes to the understanding of how colleges influence local innovation by revealing the role of increasing returns to scale in college size. While prior research has documented the positive impact of colleges on local innovation activity (Abramovsky \u0026amp; Simpson, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Andersson et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2004\u003c/span\u003e; Andrews, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Charles, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Cowan \u0026amp; Zinovyeva, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Fischer \u0026amp; Varga, 2003; Furman \u0026amp; MacGarvie, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2007\u003c/span\u003e; Hausman, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Jaffe, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e1989\u003c/span\u003e; Lehnert et al., \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Woodward et al., \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2006\u003c/span\u003e), less is known about the heterogeneous effects of college characteristics on innovation. Aghion et al. (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2009\u003c/span\u003e) find positive growth effects in four-year colleges but not in two-year colleges, whereas Andrews (2020) report no differences in the innovation effect across college types.\u003c/p\u003e \u003cp\u003eThis paper builds on existing work to reveal that consolidated colleges exert a greater positive impact on local innovation compared to their pre-merger counterparts, demonstrating that college size significantly influences innovation outcomes. These findings hold significant policy implications, suggesting that policies promoting regional innovation could benefit from emphasizing economies of scale within the college sector. By encouraging mergers or strategic collaborations that create larger colleges, policymakers can potentially contribute to enhanced research productivity and a stronger positive influence on local innovation ecosystems.\u003c/p\u003e"},{"header":"2. Data","content":"\u003cp\u003eI examine 54 mergers involving 114 colleges in China between 2004 and 2016, all of which were publicized on the Ministry of Education's website. Yu and Ertl (2014) show that public higher education institutions dominate China\u0026rsquo;s higher education market and generally hold a stronger reputation, while private colleges account for less than 15 percent of the market. Therefore, I focus exclusively on the mergers of public institutions. All mergers were initiated by the local government and the Ministry of Education. College mergers in China represent one of the largest consolidation efforts in the world, providing a unique opportunity to examine the impact of college size on local innovation. This scale of mergers surpasses those observed in other countries in the literature, such as Norway, which merged 98 colleges in 1994 (Kyvik, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2002\u003c/span\u003e), Japan, which merged 86 colleges since the mid-2010s (Mizutani et al., \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), and Russia, which merged 38 colleges in 2013 (Agasisti, 2021).\u003c/p\u003e \u003cp\u003eMok (\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2005\u003c/span\u003e) suggests that the primary motives for university mergers in China are to enhance efficiency and effectiveness. The focus of these mergers is mainly on institutions with functional overlap, narrow specialization, and small scale, aiming to integrate them into comprehensive universities. These mergers are primarily categorized into three types: those consisting solely of four-year research colleges, those involving only three-year vocational colleges, and those combining four-year colleges with three-year vocational colleges. Of the total mergers, 13 belong to the first type, 28 to the second, and 13 to the third.\u003c/p\u003e \u003cp\u003eThe classification of the merger year, as per King and Liu (2021), is determined by whether the merger took place before or after July 1. If the merger occurs before July 1, the current year is assigned as the year of the merger. Conversely, if the merger takes place after July 1, the subsequent year is designated as the year of the merger.\u003c/p\u003e \u003cp\u003e \u003cb\u003ePatent Data\u003c/b\u003e \u003c/p\u003e \u003cp\u003eTo assess local innovation, I adopt the methodology of Aghion et al. (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2009\u003c/span\u003e), utilizing the annual number of patent applications per 10,000 people in each city as a measure of the city's innovation level. Patents are commonly recognized as indicators of advancements in cutting-edge technologies, thus serving as a reliable proxy for innovation. This approach is consistent with the existing literature, which frequently uses patent application counts as a measure of innovation activity (Aghion et al., \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2009\u003c/span\u003e; Andrews, 2020; Charles, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe patent data used in this study are sourced from the Chinese Research Data Services (CNRDS) Platform, and city population data are obtained from the China City Statistical Yearbook. Spanning from 1990 to 2019, the patent data include patent applications at both the city and institution levels within China. The analysis focuses on \u003cb\u003ei\u003c/b\u003envention patents, considered the strongest indicator of innovative activity.\u003c/p\u003e \u003cp\u003eIn China, patents are classified into three types: invention, utility model, and design. Invention patents, which protect new technical solutions relating to products, processes, or improvements thereof, are most closely associated with innovative activities. Utility model patents, focusing on new shapes or configurations of products, prioritize practical application over significant innovation. Design patents protect the ornamental aspects of manufactured articles and have the least connection to innovation activities.\u003c/p\u003e \u003cp\u003e \u003cb\u003eCollege Characteristics\u003c/b\u003e \u003c/p\u003e \u003cp\u003eTo investigate changes within colleges following mergers, I utilize data on the number of faculty, government research funding, and academic paper publications from \"The Compilation of Scientific and Technological Statistics of Chinese Higher Education\" (2001\u0026ndash;2017, excluding 2003 and 2004 data). This dataset, combined with college-level patent application information, provides a comprehensive view of internal college dynamics post-merger.\u003c/p\u003e \u003cp\u003eThe number of faculty serves as a proxy for college size, potentially impacting research capacity and collaboration opportunities in the post-merger environment. Government research funding indicates whether the college receives increased governmental support post-merger. The number of publications per faculty member serves as an indicator of the college's research productivity. College-level patent data encompasses all three patent types (invention, utility, and design) and distinguishes between independent and collaborative applications, thus illustrating the college's research productivity and its influence on other organizations\u003c/p\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e presents a summary of the patent data and college characteristics. At the city level, invention and utility patents have similar application rates, both significantly higher compared to design patents. At the college level, the patent application data includes both patents applied for independently by the college and those collaboratively applied for with third parties. In both instances, patents outnumber the other two types, suggesting colleges focus more on innovation activities.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDescriptive Statistics\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eN\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMean\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSD\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eMin\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eMax\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePatent applications\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c7\" namest=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCity level\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c7\" namest=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInvention Patent\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1,102\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.867\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9.275\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.014\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e86.447\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c7\" namest=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUtility Patent\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1,102\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.025\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7.643\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.041\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e69.883\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c7\" namest=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDesign Patent\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1,102\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.490\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.055\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e32.134\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c7\" namest=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCollege Level\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c7\" namest=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eIndependent\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c7\" namest=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInvention Patent\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1,620\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e49.787\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e212.880\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.617\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c7\" namest=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUtility Patent\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1,620\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e18.733\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e78.583\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1,274\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c7\" namest=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDesign Patent\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1,620\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.436\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9.902\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e211\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c7\" namest=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCollaborative\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c7\" namest=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInvention Patent\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1,620\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.398\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e25.383\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e518\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c7\" namest=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUtility Patent\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1,620\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.553\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6.021\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c7\" namest=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDesign Patent\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1,620\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.089\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.996\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c7\" namest=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCollege Characteristics\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c7\" namest=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFaculties\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e459\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1452.837\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2515.283\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e17170\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c7\" namest=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eResearch Funding (million yuan)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e434\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e127.231\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e381.268\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3125.149\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c7\" namest=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePublication/Faculty\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e459\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1353.185\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3119.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e21,134\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c7\" namest=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e \u003cp\u003eNote. City-level patent data is calculated as patent applications per 10,000 people.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c7\" namest=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e"},{"header":"3. Empirical strategy","content":"\u003cp\u003eTo estimate the college merger on local innovation, it is essential to address the potential endogeneity issue. A pre-existing increasing (or decreasing) trend in local innovation activities might trigger the merger, leading to an upward (or downward) bias in the results. To mitigate the endogeneity issue and given the occurrence of college mergers in different years, I employ a difference-in-differences model, the regression equation is structured as follows:\u003cdiv id=\"Equ1\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ1\" name=\"EquationSource\"\u003e\n$$\\:{Patent}_{it}={\\beta\\:}_{0}+{\\beta\\:}_{1}merg{e}_{it}+yea{r}_{t}+{college}_{i}+{ϵ}_{it}$$\u003c/div\u003e\u003cdiv class=\"EquationNumber\"\u003e1\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003ewhere \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{Patent}_{it}\\)\u003c/span\u003e\u003c/span\u003e represents the number of patent applications in the city of college \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:i\\)\u003c/span\u003e\u003c/span\u003e in year \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:t\\)\u003c/span\u003e\u003c/span\u003e. \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:me{rge}_{it}\\)\u003c/span\u003e\u003c/span\u003e is an indicator function equal to 1 if the college has merged in year \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:t\\)\u003c/span\u003e\u003c/span\u003e. \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{college}_{i}\\)\u003c/span\u003e\u003c/span\u003e and \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:yea{r}_{t}\\)\u003c/span\u003e\u003c/span\u003e are college fixed effect and year fixed effect, respectively, which control for local patent applications in the reference year and time-variant changes in patenting across cities. Consequently, \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{\\beta\\:}_{1}\\)\u003c/span\u003e\u003c/span\u003e captures the change in local patent applications attributable to the merger.\u003c/p\u003e \u003cp\u003eIf there is an increasing return to scale in the size of the college on its effect on local innovation activities, a notable increase in patent applications in the cities where the college is located should be observed after the merger. This increase would amplify the difference in patent applications compared to other cities. Consequently, a significant and positive \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{\\beta\\:}_{1}\\)\u003c/span\u003e\u003c/span\u003e should be observed. Conversely, if no such effect exists, the difference in patent applications among these cities should remain unchanged, resulting in an insignificant \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{\\beta\\:}_{1}\\)\u003c/span\u003e\u003c/span\u003e​.\u003c/p\u003e \u003cp\u003eRecent studies (Callaway \u0026amp; Sant\u0026rsquo;Anna, 2020; De Chaisemartin \u0026amp; D\u0026rsquo;Haultfoeuille, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Goodman-Bacon, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) highlight potential biases in the traditional two-way fixed effects approach (TWFE) when estimating treatment effects in DID models with varying treatment timing, if treatment effects vary across time or units. To address this issue, I adopt the robust approach developed by Callaway and Sant\u0026rsquo;Anna (2020). Their method estimates the treatment effect for each time period based on the group classified by the first treated time and aggregates these estimates to compute the average treatment effect. Furthermore, I provide estimates using several alternative approaches that address the bias caused by heterogeneous treatment effects, as recommended by Borusyak, Jaravel, \u0026amp; Spiess (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2024\u003c/span\u003e), De Chaisemartin \u0026amp; D\u0026rsquo;Haultfoeuille (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2020\u003c/span\u003e), Gardner (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2022\u003c/span\u003e), and Wooldridge (2021), to confirm the robustness of the findings. These alternative approaches share similarities with Callaway and Sant\u0026rsquo;Anna (2020) but differ in constructing the control group and weighting across different groups and time periods.\u003c/p\u003e \u003cp\u003eThe model employs college fixed effects instead of city fixed effects due to the presence of cities with multiple college mergers occurring in different years. If there were no multiple mergers in the same city, college fixed effects and city fixed effects would be equivalent. However, in cases where multiple mergers exist, the college fixed effects allow for independent estimation for each merger within the model. Specifically, the model utilizes only the years in which the merger events do not overlap in a city. For the first merger, only data from before the second merger are used for estimation, and for the second merger, only data from after the first merger are used.\u003c/p\u003e \u003cp\u003eThe model restricts analysis to cities where at least one college merger occurred. This approach helps mitigate potential selection bias, as cities with merged colleges may inherently differ from those without mergers. To further validate the findings, a robustness check including all cities is also conducted.\u003c/p\u003e"},{"header":"4. Results","content":"\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e4.1 Local innovation\u003c/h2\u003e \u003cp\u003eThis section investigates the impact of college mergers on the number of local patent applications, aiming to determine whether larger institutions have a greater influence on local innovations. Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e presents the findings regarding the number of invention, utility, and design patent applications per capita in the cities where the merged colleges are located.\u003c/p\u003e \u003cp\u003eThe results present a substantial increase in invention patent applications post-merger, with an average rise of 2.170 applications per 10,000 people. This suggests a strong positive effect of mergers on groundbreaking innovation within local contexts. Utility patent applications also exhibited an increase, averaging 1.313 applications, indicating a potential rise in practical innovation alongside fundamental advancements. However, there is no significant change observed in design patent applications, which aligns with expectations given their minimal connection to technological innovation activities.\u003c/p\u003e \u003cp\u003eThese findings suggest that college mergers can significantly enhance local innovation activities, reflecting an increasing return to scale of college size on local innovation effects. Consolidating multiple colleges into larger institutions appears to stimulate local innovation, highlighting the potential benefits of scaling up educational and research capacities through mergers.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eThe effect of college merger on local innovation\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePatent\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eInvention\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eUtility\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eDesign\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMerger\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.170***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.313**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.597\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(0.660)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(0.564)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(0.633)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eObservations\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e951\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e951\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e951\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003eNote: * p\u0026thinsp;\u0026lt;\u0026thinsp;0.1; ** p\u0026thinsp;\u0026lt;\u0026thinsp;0.05; *** p\u0026thinsp;\u0026lt;\u0026thinsp;0.01. The effect of college merger on patent applications within the city where the college is located. Standard errors in parentheses. Standard errors are clustered at the college level. All estimations control for year fixed effect and college fixed effect. The estimates follow the approach outlined by Callaway and Sant\u0026rsquo;Anna (2020).\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e4.2 Robustness check\u003c/h2\u003e \u003cp\u003eTo ensure the robustness of the estimates presented in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, I conduct additional analyses as detailed in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e. The estimates are examined under various scenarios to assess their sensitivity to different sample compositions and time periods.\u003c/p\u003e \u003cp\u003eColumns 1 to 6 in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e present estimates derived from Eq.\u0026nbsp;(\u003cspan refid=\"Equ1\" class=\"InternalRef\"\u003e1\u003c/span\u003e) using different periods of data. Columns 7 to 9 provide estimates based on balanced data samples, and Columns 10 to 12 include cities that have never undergone a college merger.\u003c/p\u003e \u003cp\u003eAcross all these alternative estimations, the effect on invention patent applications remains significant. This reinforces the positive impact of mergers on innovation activities. For utility patents, which require a less stringent level of innovation, the significance level occasionally varies across estimations. However, the magnitude of the effect remains consistently positive, suggesting a potential increase in practical innovation alongside fundamental advancements. As expected, design patents, requiring the least innovative effort, show no significant effect in any of the estimates. Additionally, their point estimates are the smallest among the three patent categories.\u003c/p\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e examines the robustness of the findings by employing alternative approaches to address potential biases in the traditional TWFE model. These approaches, proposed by Gardner (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2022\u003c/span\u003e), Borusyak, Jaravel, and Spiess (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2024\u003c/span\u003e), Wooldridge (2021), and De Chaisemartin and D\u0026rsquo;Haultfoeuille (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2020\u003c/span\u003e), utilize various methods for constructing control groups and weighting observations. The results across all these approaches (Columns 1\u0026ndash;12) are consistent with initial findings, that invention patent applications exhibit the largest increase following mergers. Utility patent applications also show a positive but smaller increase. As expected, design patents, exhibit minimal change across all estimations.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eThe effect of college merger on local innovation with alternative sample\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"14\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c12\" colnum=\"12\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c13\" colnum=\"13\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c14\" colnum=\"14\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(1)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(2)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(3)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(4)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e(5)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e(6)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003e(7)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003e(8)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003e(9)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c11\"\u003e \u003cp\u003e(10)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c12\"\u003e \u003cp\u003e(11)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c13\"\u003e \u003cp\u003e(12)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"1\" nameend=\"c14\" namest=\"c14\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003e10 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e \u003cp\u003e5 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c10\" namest=\"c8\"\u003e \u003cp\u003eBalanced Data\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c14\" namest=\"c11\"\u003e \u003cp\u003eNever-treated cities\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePatent\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eInvention\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eUtility\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eDesign\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eInvention\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eUtility\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eDesign\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eInvention\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eUtility\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eDesign\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003eInvention\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003eUtility\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003eDesign\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c14\" namest=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMerger\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.434**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.511\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.274\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.184**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.642\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-0.057\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.797**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1.323*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.858\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e3.053***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e1.700*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e0.247\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c14\" namest=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(0.609)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(0.596)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(0.707)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(0.881)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e(0.488)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e(0.326)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e(0.863)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e(0.740)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e(0.976)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e(1.133)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e(0.890)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e(0.561)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c14\" namest=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eObservations\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e654\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e654\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e654\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e320\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e320\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e320\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e563\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e563\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e563\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e8203\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e8203\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e8203\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c14\" namest=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"14\" nameend=\"c14\" namest=\"c1\"\u003e \u003cp\u003eNote: * p\u0026thinsp;\u0026lt;\u0026thinsp;0.1; ** p\u0026thinsp;\u0026lt;\u0026thinsp;0.05; *** p\u0026thinsp;\u0026lt;\u0026thinsp;0.01. The effect of college merger on patent applications within the city where the college is located with alternative samples. Columns 1 to 3 include samples where the relative treatment time ranges from \u0026minus;\u0026thinsp;10 years to 10 years. Columns 4 to 6 include samples where the relative treatment time ranges from \u0026minus;\u0026thinsp;5 years to 5 years. Columns 7 to 9 only include samples that span every year from 1990 to 2019. Columns 10 to 12 include samples from cities that have never experienced a college merger. Standard errors in parentheses. Standard errors are clustered at the college level. All estimations control for year fixed effect and college fixed effect. The estimates follow the approach outlined by Callaway and Sant\u0026rsquo;Anna (2020).\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eThe effect of college merger on patent applications\u0026nbsp;with alternative approach\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"14\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c12\" colnum=\"12\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c13\" colnum=\"13\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c14\" colnum=\"14\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(1)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(2)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(3)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(4)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e(5)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e(6)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003e(7)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003e(8)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003e(9)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c11\"\u003e \u003cp\u003e(10)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c12\"\u003e \u003cp\u003e(11)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c13\"\u003e \u003cp\u003e(12)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"1\" nameend=\"c14\" namest=\"c14\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003eGardner (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2022\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e \u003cp\u003eBorusyak et al. (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2024\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c10\" namest=\"c8\"\u003e \u003cp\u003eWooldridge (2021)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c14\" namest=\"c11\"\u003e \u003cp\u003eDe Chaisemartin and D\u0026rsquo;Haultfoeuille (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2020\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eInvention\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eUtility\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eDesign\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eInvention\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eUtility\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eDesign\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eInvention\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eUtility\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eDesign\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003eInvention\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003eUtility\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003eDesign\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c14\" namest=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMerger\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5.650***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.249***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.601***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.421***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.432**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.723\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e2.421***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1.432**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.723\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e2.131***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e1.257**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e0.550\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c14\" namest=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(1.253)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(0.920)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(0.539)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(0.721)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e(0.573)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e(0.572)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e(0.614)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e(0.678)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e(0.557)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e(0.662)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e(0.587)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e(0.632)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c14\" namest=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eObservations\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1102\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1102\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1102\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e953\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e953\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e953\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e951\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e951\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e951\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e456\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e456\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c13\"\u003e \u003cp\u003e456\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c14\" namest=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"14\" nameend=\"c14\" namest=\"c1\"\u003e \u003cp\u003eNote: * p\u0026thinsp;\u0026lt;\u0026thinsp;0.1; ** p\u0026thinsp;\u0026lt;\u0026thinsp;0.05; *** p\u0026thinsp;\u0026lt;\u0026thinsp;0.01. The effect of college merger on patent applications within the city where the college is located with alternative DID estimation approaches. Standard errors in parentheses. Standard errors are clustered at the college level. All estimations control for year fixed effect and college fixed effect.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eParallel trend\u003c/b\u003e \u003c/p\u003e \u003cp\u003eTo validate the estimates of the DID model, it is essential to verify the parallel trend assumption, which suggests that these cities exhibited consistent differences in patent applications prior to the college merger. To test this assumption, an event study model is estimated. This model assesses the effect of the merger for each year before and after the merger. If changes in patent applications are induced by the college merger, significant changes in patent applications should only be observed in the periods following the merger. The estimated equation is as follows:\u003cdiv id=\"Equ2\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equ2\" name=\"EquationSource\"\u003e\n$$\\:{Patent}_{it}={\\beta\\:}_{0}+{\\Sigma\\:}{\\beta\\:}_{\\text{t}}colleg{e}_{i}\\text{*}{\\text{t}\\text{i}\\text{m}\\text{e}}_{\\text{t}}+yea{r}_{t}+{college}_{i}+{ϵ}_{it}$$\u003c/div\u003e\u003cdiv class=\"EquationNumber\"\u003e2\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003eWhere \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{\\text{t}\\text{i}\\text{m}\\text{e}}_{\\text{t}}\\)\u003c/span\u003e\u003c/span\u003e is the relative years to the merger, therefore \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{\\beta\\:}_{\\text{t}}\\)\u003c/span\u003e\u003c/span\u003e capture the change in patent applications in the cities that the merged colleges located in, in each year. Same as the estimates in Table \u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, The estimation is followed Callaway and Sant\u0026rsquo;Anna (2020)\u0026rsquo;s approach, to address the bias caused by the TWFE.\u003c/p\u003e \u003cp\u003eFigure \u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e plots the \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{\\beta\\:}_{\\text{t}}\\)\u003c/span\u003e\u003c/span\u003e for each time periods, As noted by Borusyak and Jaravel (2017), when there are no never-treated units in the sample, two relative time indicators must be omitted to avoid multicollinearity. Following their suggestions, the most negative time period (furthest in the past) and the period immediately before the merger are omitted. This omission allows the remaining coefficients \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{\\beta\\:}_{\\text{t}}\\)\u003c/span\u003e\u003c/span\u003e to represent the average differences in patent applications between the treatment and control groups for specific periods before the merger.\u003c/p\u003e \u003cp\u003eFigure \u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e demonstrates that the parallel trend assumption holds, as the difference in patent applications among these cities remains consistent before the merger. After the merger, invention patents show the most significant increase, followed by utility patents, which also exhibit a less significant increase. The change in design patent applications is subtle and insignificant. This finding aligns with the results in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, indicating that college mergers can significantly enhance local innovation, and this effect persists over time.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eOther cities\u003c/b\u003e \u003c/p\u003e \u003cp\u003eAnother concern with these estimates is whether simultaneous changes at the national or local level may have influenced innovation activities. Given that the mergers in the data occurred over different years spanning eight years, a nationwide trend is less likely. However, to address the possibility of simultaneous changes within a province that may induce an increase in innovation activities, I examine the effect of college mergers on patent applications in other cities within the same province.\u003c/p\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e provides the results of this analysis. The findings show no significant effect of college mergers on patent applications in other cities within the same province. This suggests that there is no increasing trend in patent applications coinciding with the year of the college merger within the province, thereby reinforcing the validity of the observed effects being attributed to the mergers themselves.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eThe effect of college merger on local innovation in other cities within the same province\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePatent\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eInvention\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eUtility\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eDesign\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMerger\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.563\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.543\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.245\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(0.684)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(0.623)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(0.607)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eObservations\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6753\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6753\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6753\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003eNote: * p\u0026thinsp;\u0026lt;\u0026thinsp;0.1; ** p\u0026thinsp;\u0026lt;\u0026thinsp;0.05; *** p\u0026thinsp;\u0026lt;\u0026thinsp;0.01. The effect of college merger on patent applications in other cities within the same province. Standard errors in parentheses. Standard errors are clustered at the city level. All estimations control for year fixed effect and city fixed effect. The estimates follow the approach outlined by Callaway and Sant\u0026rsquo;Anna (2020).\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e4.2 Mechanism\u003c/h2\u003e \u003cp\u003eAs noted by Cohen et al. (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2002\u003c/span\u003e) and Zucker et al. (\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2002\u003c/span\u003e), knowledge spillovers are a key mechanism through which colleges impact local innovation. Building on the observed effect of college mergers on patent applications, I investigate the internal changes within colleges that may drive local innovation.\u003c/p\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e6\u003c/span\u003e presents estimates on the impact of mergers on faculty size, research funding, and research productivity. The results indicate that the merged colleges maintain a size comparable to the sum of the independent colleges prior to consolidation, with no significant increase in the number of faculty post-merger. Similarly, government funding for research remains at the combined level of independent colleges before the merger. Despite these unchanged inputs, research productivity, measured by publications per faculty, increases by 0.281 publications after the merger.\u003c/p\u003e \u003cp\u003eThis finding suggests that the positive effects observed extend beyond just local patent applications. Mergers appear to lead to increased efficiency within colleges, potentially allowing them to utilize existing resources more effectively. This aligns with previous research on college mergers and operational efficiency in other contexts (Kyvik, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2002\u003c/span\u003e; Johnes \u0026amp; Papadimitriou, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Mizutani et al., \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eMore importantly, this finding shows that the merger enables an increasing return not only in local patent applications but also in the research productivity of the college. As suggested by Fritsch \u0026amp; Slavtchev (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2007\u003c/span\u003e), research intensity and quality play a crucial role in influencing regional innovation output. This heightened productivity likely contributes to the observed larger effect on local innovation.\u003c/p\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab7\" class=\"InternalRef\"\u003e7\u003c/span\u003e further explores the changes within the college by examining college-level patent applications. The data encompasses both independent applications by the college and collaborative applications with other organizations. Here, an overall increase in patent applications post-merger is observed. Invention patents, representing the most innovative category, show the most significant rise, followed by utility patents and design patents. Notably, the number of collaborative patent applications also increases after the merger. These findings suggest that mergers can stimulate not only in-house research and development, but also external collaboration. This synergy between internal efficiency and external partnerships likely contributes to the enhanced local innovation observed after mergers.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab6\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 6\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eThe effect of college merger on college characteristics\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNumber of Faculty\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eGovernment research funding\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePublications per faculty\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMerger\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e843.240\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e182.108\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.281**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(769.629)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(125.862)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(0.141)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eObservations\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e183\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e139\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e183\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003eNote: * p\u0026thinsp;\u0026lt;\u0026thinsp;0.1; ** p\u0026thinsp;\u0026lt;\u0026thinsp;0.05; *** p\u0026thinsp;\u0026lt;\u0026thinsp;0.01. The effect of college merger on college characteristics. Standard errors in parentheses. Standard errors are clustered at the college level. All estimations control for year fixed effect and college fixed effect. The estimates follow the approach outlined by Callaway and Sant\u0026rsquo;Anna (2020).\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab7\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 7\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eThe effect of college merger on college-level patent applications\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003eIndependent\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e \u003cp\u003eCollaborative\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePatent\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eInvention\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eUtility\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eDesign\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eInvention\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eUtility\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eDesign\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMerger\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e54.531***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e21.542***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.539**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5.179**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.953***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.243*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(17.175)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(6.626)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(1.644)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(2.319)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e(0.526)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e(0.142)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eObservations\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1404\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1404\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1404\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1404\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1404\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1404\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"7\" nameend=\"c7\" namest=\"c1\"\u003e \u003cp\u003eNote: * p\u0026thinsp;\u0026lt;\u0026thinsp;0.1; ** p\u0026thinsp;\u0026lt;\u0026thinsp;0.05; *** p\u0026thinsp;\u0026lt;\u0026thinsp;0.01. The effect of college merger on college-level patent applications. Standard errors in parentheses. Standard errors are clustered at the college level. All estimations control for year fixed effect and college fixed effect. The estimates follow the approach outlined by Callaway and Sant\u0026rsquo;Anna (2020).\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003e4.3 Heterogeneity effect\u003c/h2\u003e \u003cp\u003eGiven the observed effect on local innovation, I also explore whether the impact of college mergers on local innovation, measured by patent applications, varies depending on the colleges involved. The analysis categorizes mergers into three groups: four-year research colleges only, three-year vocational colleges only, and mixed mergers involving both research and vocational colleges.\u003c/p\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab8\" class=\"InternalRef\"\u003e8\u003c/span\u003e reveals that mergers involving solely four-year research colleges lead to the largest increase in invention patent applications, followed by mergers involving three-year vocational colleges. Mixed mergers have the smallest positive effect. This pattern likely stems from the more efficient utilization of research resources when merging similar institutions. Four-year research colleges, with their inherent focus on research activities, are likely to experience a more significant boost to innovation compared to vocational college mergers.\u003c/p\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab9\" class=\"InternalRef\"\u003e9\u003c/span\u003e illustrates that changes in publications per faculty member within colleges correspond to their impact on local patent applications. Four-year colleges experience a significant rise in publications per faculty member after a merger, even without parallel increases in faculty size or research funding. In contrast, mixed mergers exhibit a smaller, statistically insignificant change in publication rates. Unfortunately, the limited number of vocational college merger cases with available data in \u003cem\u003eThe Compilation of Scientific and Technological Statistics of Chinese Higher Education\u003c/em\u003e prevents an estimation of their post-merger research productivity changes. Patent application data by college type further illuminate the differential effects. Mergers involving four-year colleges lead to a substantial increase in both independent and collaborative patent applications, suggesting a broad-based boost to innovation activity. Mixed mergers show a larger increase in independent invention patent applications but no change in collaborative patent applications. Conversely, vocational college mergers exhibit a smaller increase in independent patent applications compared to mixed mergers but show a significant rise in collaborative patent applications. This contrasting pattern, coupled with the observed larger positive effect of vocational college mergers on local innovation, suggests that collaboration plays a crucial role in enhancing local innovation.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab8\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 8\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eThe heterogeneity effect on local innovation\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"10\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003eFour-year colleges\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e \u003cp\u003eThree-year colleges\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c10\" namest=\"c8\"\u003e \u003cp\u003eMixed merger\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePatent\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eInvention\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eUtility\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eDesign\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eInvention\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eUtility\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eDesign\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eInvention\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eUtility\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eDesign\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMerger\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.110***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.502***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.398*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.233*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.834\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-0.447\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.174**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.987*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.587\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(0.945)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(0.876)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(1.444)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(1.220)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e(0.883)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e(0.590)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e(0.537)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e(0.578)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e(0.527)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eObservations\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e197\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e197\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e197\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e467\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e467\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e467\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e278\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e278\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e278\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"10\" nameend=\"c10\" namest=\"c1\"\u003e \u003cp\u003eNote: * p\u0026thinsp;\u0026lt;\u0026thinsp;0.1; ** p\u0026thinsp;\u0026lt;\u0026thinsp;0.05; *** p\u0026thinsp;\u0026lt;\u0026thinsp;0.01. The effect of college merger on patent applications within the city where the college is located by the type of merger. Standard errors in parentheses. Standard errors are clustered at the college level. All estimations control for year fixed effect and college fixed effect. The estimates follow the approach outlined by Callaway and Sant\u0026rsquo;Anna (2020).\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab9\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 9\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eThe heterogeneity effect of college merger on college characteristics and college-level patent application\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"10\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003eCollege Characteristics\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e \u003cp\u003eIndependent patent\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c10\" namest=\"c8\"\u003e \u003cp\u003eCollaborative patent\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNumber of Faculty\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eGovernment research funding\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePublications per faculty\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eInvention\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eUtility\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eDesign\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eInvention\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eUtility\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eDesign\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"10\" nameend=\"c10\" namest=\"c1\"\u003e \u003cp\u003eFour-year colleges\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMerger\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1477.500\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e191125.375\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.352***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e72.573***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e28.208***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e3.789**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e14.906*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e3.842***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.229\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(1345.103)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(1.48e\u0026thinsp;+\u0026thinsp;05)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(0.129)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(17.141)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e(8.691)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e(1.811)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e(7.848)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e(1.282)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e(0.302)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eObservations\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e338\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e338\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e338\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e338\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e338\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e338\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"10\" nameend=\"c10\" namest=\"c1\"\u003e \u003cp\u003eThree-year colleges\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMerger\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e9.665**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e19.593**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e10.383\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.504*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e2.049**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.846\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(4.128)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e(9.362)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e(7.808)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e(0.893)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e(0.829)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e(0.711)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eObservations\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e728\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e728\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e728\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e728\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e728\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e728\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"10\" nameend=\"c10\" namest=\"c1\"\u003e \u003cp\u003eMixed merger\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMerger\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e142.713\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e73194.483\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.142\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e104.266**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e14.742\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e3.348*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e3.098\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.953\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.701\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(129.825)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(58036.328)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(0.310)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(51.606)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e(15.973)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e(2.014)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e(2.391)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e(1.097)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e(0.518)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eObservations\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e338\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e338\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e338\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e338\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e338\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e338\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"10\" nameend=\"c10\" namest=\"c1\"\u003e \u003cp\u003eNote: * p\u0026thinsp;\u0026lt;\u0026thinsp;0.1; ** p\u0026thinsp;\u0026lt;\u0026thinsp;0.05; *** p\u0026thinsp;\u0026lt;\u0026thinsp;0.01. The effect of college merger on college characteristics and college-level patent application by the type of merger. Standard errors in parentheses. Standard errors are clustered at the college level. All estimations control for year fixed effect and college fixed effect. The estimates follow the approach outlined by Callaway and Sant\u0026rsquo;Anna (2020).\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"5. Conclusion","content":"\u003cp\u003eThis paper explores the relationship between college mergers and local innovation and research productivity. The analysis reveals that mergers lead to a significant increase in patent applications within the city, suggesting economies of scale in the impact of colleges on local innovation activities. Additionally, merged colleges experience a boost in research productivity, potentially contributing to the rise in local innovation.\u003c/p\u003e \u003cp\u003eFurther investigation into different merger types highlights that mergers involving four-year research colleges are the primary driver of these positive effects. This aligns with their research-oriented focus, suggesting that merging similar institutions leads to a more efficient utilization of research resources, potentially fueling local innovation.\u003c/p\u003e \u003cp\u003eThese findings offer valuable insights for policymakers aiming to enhance local innovation and research efficiency. By encouraging strategic mergers or facilitating resource-sharing initiatives, policies can be designed to specifically support the creation of larger research colleges. This, in turn, could unlock their full potential for both research productivity and local economic development.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eX.Y. conceived and designed the study, collected and analyzed the data, interpreted the results, and wrote the manuscript. As the sole author, X.Y. is responsible for all aspects of the work.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eThe data supporting the findings of this study are not publicly available. They were obtained from the Chinese Research Data Services Platform (CNRDS) at https://www.cnrds.com and are subject to access restrictions.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAarrevaara, T., Dobson, I., \u0026amp; Elander, C. (2009). 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Commercializing Knowledge: University Science, Knowledge Capture, and Firm Performance in Biotechnology. \u003cem\u003eManagement Science\u003c/em\u003e, \u003cem\u003e48\u003c/em\u003e(1), 138\u0026ndash;153. https://doi.org/10.1287/mnsc.48.1.138.14274\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":true,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Merger, Higher Education, Economies of scale, Local Innovation, Research productivity","lastPublishedDoi":"10.21203/rs.3.rs-6657557/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6657557/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThis paper investigates whether larger colleges bring greater benefits for local innovation and higher research productivity. Using college mergers in China as a case study with a difference-in-difference model, this paper finds that mergers lead to a significant increase in local patent applications, signifying enhanced innovation within the cities where the merged colleges are located. This rise in innovation coincides with a notable improvement in the merged college's research productivity, achieved without additional faculty or government funding. These findings suggest economies of scale in the college's impact on local innovation and research output. Further analysis reveals that mergers involving solely four-year research colleges have the most significant positive effect. This aligns with the notion that merging similar institutions facilitates more efficient utilization of research resources. Overall, the paper offers valuable insights for policymakers aiming to enhance local innovation and research efficiency. By promoting resource-sharing initiatives or strategic mergers, particularly among four-year research colleges, policies can unlock the full potential of these institutions for both research excellence and regional economic development.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eJEL Classification:\u003c/strong\u003e I23, I25, O31\u003c/p\u003e","manuscriptTitle":"University and Local Innovation: Evidence from College Mergers in China","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-05-23 09:26:49","doi":"10.21203/rs.3.rs-6657557/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"225caead-47da-4533-b6c6-84b0a1b02d8a","owner":[],"postedDate":"May 23rd, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-06-09T06:08:33+00:00","versionOfRecord":[],"versionCreatedAt":"2025-05-23 09:26:49","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6657557","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6657557","identity":"rs-6657557","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}