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題名：三篇關於創新與研發外溢之實證研究
作者：廖貴燕
作者(外文)：Liao, Kuei-Yen
校院名稱：國立清華大學
系所名稱：經濟學系
指導教授：祁玉蘭
學位類別：博士
出版日期：2012
主題關鍵詞：創新；研發外溢；專利；科技外溢；產品市場競爭；群聚；科學園區；總要素生產力；勞動密度；Innovation；R&；D Spillover；Patent；Technology Spillover；Product Market Competition；Agglomeration；Science Park；TFP；Labor Density
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本論文研究創新、研發外溢與群聚的關係，文獻上認為造成各地區生產力差異因素與當地知識與勞動之密集程度有關，惟研發外溢對廠商創新表現之解釋力卻呈現各地不一，迄今尚無定論之現象。本論文共分三個章節，針對研究發展金額投入最高的北歐兩國（瑞典與芬蘭）、西歐三國（英、法、德）與台灣廠商進行實證研究，深入剖析不同研發外溢形成因素，對群聚廠商創新表現之可能影響。
在第一章，針對瑞典與芬蘭廠商的專利創新表現檢驗兩個問題，第一：高生產力廠商自我選擇(sorting)進入產業群聚後，是否可受惠於群聚並因而提高其創新能量。第二：當控制廠商sorting因素後，研發外溢是否為解釋廠商創新表現之重要因素。由於廠商專利申請數呈現過多的零 (excess zeros)資料特性，因此本研究使用一系列之Zero-inflated count data模型分析147家瑞典與芬蘭廠商在2002至2005期間之創新表現。結果顯示，廠商大小、生產力、累積研發投入強度與區域人力資本正面影響廠商創新表現，一旦控制廠商sorting因素後，產業群聚效應並非齊一性的提高群聚廠商專利申請數，端視產業別不同而有所差異。尤其，跨區(cross-cluster)研發外溢正面影響廠商專利研發表現，而同一區內(within-cluster) 研發外溢則呈現因產業別不同而各異，效果僅及於少數產業。基此，為更深入瞭解研發外溢效果，進一步區分不同研發外溢型態對廠商創新表現影響是一個重要研究課題。
第二章因此針對西歐研究發展金額投入最高的三國—英、德、法廠商進行跨區、跨產業之研發外溢效果實證分析，本研究係根據Bloom et al. (2012)的理論結果，引伸建立出一系列研發外溢衡量指標，主要包括研發透過廠商申請專利，計算彼此在專利科技項別之科技領域鄰近程度，所產生之科技外溢效果（technology spillover）；另一種則為研發藉由廠商面對該地同產業廠商相較全國之集中與競爭程度，所產生之商品市場競爭外溢效果（product market competition spillover），區域研發外溢效果為何，端視此兩種效果在該地展現之強弱而定。由於專利與研發投入關係具備內生性，本研究因而採用針對panel count data 所發展出的非線性（non-linear）GMM估計方法來建立計量模型進行迴歸估計。研究範圍涵蓋2002至2007年間，606家分別座落於76個NUTS 2地區之英、法、德廠商。結果發現，科技外溢效果對德、法兩國廠商創新表現呈現正向，而商品市場競爭外溢效果一旦衍生business stealing則不利法國廠商專利申請。一旦當一地前項效果強過後者，係造成該地研發外溢呈現正向激勵廠商創新之背後主因，此效果對在解釋德國廠商創新表現上尤為明顯，實證結果提供重要的政策意涵。
第三章則再探究廠商群聚政府政策規劃之科學園區，對其TFP生產效率與創新表現係受自我選擇(firm-selection) 效果、聚集經濟(agglomeration economies) 效果，抑或結合兩者所產生之綜合效果所影響。本章針對728家台灣上市櫃研發投入前四大電子製造相關產業廠商，2002至2006年間之表現，提出兩假說(Hypotheses)進行實證研究。一為「群聚科學園區之廠商較園區外廠商有較佳之TFP生產效率與專利創新」；另一為「當科學園區內廠商之科技外溢效果較強，當地同產業勞動密集度亦較高情況下，園區內廠商生產與創新表現均較佳」。為驗證假說一，本章採用Heckman selection model of the propensity score matching（PSM）估計法來驗證，結果顯示，科學園區內廠商確較園區外廠商有較佳之TFP生產效率與專利創新表現，此係受高生產力廠商自我選擇進入園區，以及聚集經濟效應兩因素所綜合產生之效果所影響。有關假說二則採用the system GMM panel dynamic model ，解決lagged dependent variables與內生性問題，建立動態模型進行檢驗。發現廠商表現與其大小及研發投入呈現正向，與廠商設立時間早晚呈現負向關係，科技外溢對群聚科學園區廠商，有利提高其TFP效率與專利申請，尤其當該地同產業勞動密集度高於全國平均，受惠於labor market pooling產生較佳labor matching的影響，該地廠商專利創新表現會更突出。由於廠商前期TFP與專利表現均正向持續影響其下期之表現，此造成更多高生產力廠商自我選擇（self-select）進入科學園區。
本論文研究結果進行跨國比較顯示，研發外溢與區域群聚對各國廠商創新表現正負效果不一，在北歐兩國，11個產業群聚有3個出現負向影響，惟在台灣科學園區則均為正向效果；有關區域研發外溢對該地廠商影響雖未獲一致結論，惟在科技外溢效果方面，則不論德、法與台灣廠商均呈現正面效果。本研究結果，帶給學術界與政策規劃者重要的啟示，有助促進研究者與政策制定者對研發外溢與群聚廠商創新行為之瞭解，從而引申出重要的政策意涵。
This dissertation studies the relations between innovation and R&;D spillover. While the spatial variations and productivity differences have been largely attributed to dense knowledge flows and local labor concentration, the explanatory power of R&;D spillover on firm innovation presents ambiguously and no consensus has been reached to date. To explore at greater depth, my research rigorously investigates what lies behind the R&;D spillover on innovation of clustered firms. Substantial progress has been achieved in unraveling the complicated composition of R&;D spillover on firm performances. It contains of three essays.
In the first essay, “Innovation, Clustering, and Knowledge Spillovers: An Empirical Study of Finnish and Swedish Firms,” I assess two questions. One is that whether high-productivity firms sorting into industrial clusters, can benefit from agglomeration and thus advance their innovation. The second one is that whether, controlling for firm sorting, R&;D spillover is vital in explaining firm patenting. Due to the patent data containing excess zeros, I apply two Zero-inflated count data models to a panel of 147 Swedish and Finnish firms during 2002-2005. Firm size, productivity, R&;D stock intensity and regional human capital contribute mostly in boosting firm patenting. After controlling for firm sorting effects, industrial clustering may not be overwhelmingly effective across industries in initiating patenting by located firms. The cross-cluster R&;D spillover positively affects patenting intensity, while the effects of within-cluster R&;D spillover vary substantially among industries. The positive influences of local R&;D spillover on firm patent applications are limited to specific industries. To dig deeper into the regional R&;D spillover, further efforts are made on disentangling different R&;D spillover effects.
The second essay “R&;D Spillover and Patent Production in British, French and German Firms” thereby investigates the impacts of R&;D spillover across regions and industries on the innovation performance of top R&;D investing firms in France, Germany, and the United Kingdom. Based on a theoretical framework in Bloom et al. (2012), two new measures of technological spillover and product market competition spillover are constructed by using R&;D investment and patent data for 606 firms and 76 regions during years 2002-2007. Application of the non-linear GMM panel count method to solve the endogeneity of RD input and patent production, the results showed that technological spillovers positively associate with patenting by French and German firms, whilst French firms have experienced negative business stealing effects from product market rivals. Especially, the encouraging effect of regional R&;D spillover experienced by German firms is substantial in stimulating located firm patenting due to the dominating beneficial technological spillover effect over the unfavorable spillover effect driven by product market competition.
The third essay, “Policy-induced Agglomeration, R&;D Spillover and Firm Performance,” I revisit how a policy-induced science park experiment on firm performance is affected by firm-selection, or by agglomeration economies, or a combined effect of the both. The Heckman selection model of the PSM method is applied to avoid sampling selection bias arising from observable differences between the 128 target Taiwanese stock-listed electronics firms locating in science parks and the 600 non-target firms placed elsewhere. My findings show that the target firms persistently outperform those non-target ones in terms of total factor productivity (TFP) efficiency and patent applications during 2002-2006 due to a combined effect of agglomeration economies and of self-selection by high performance firms. The system GMM panel dynamic models were established to lessen the endogeneity and performance dynamics problems in the examination of the second hypothesis assuming that the effects of technology spillover and local labor density positively affect performances of target firms. The results partially support the second supposition, especially in that firms concentrated in an area with the prevalence of technology spillover and higher labor density are best suited for reaping agglomeration benefits in innovation. As performance feedbacks reinforce agglomeration premium of clustered firms; this in turn, drives more high-performance firms to science parks.
My findings have important policy implications. Regarding whether policy efforts should encourage more clusters, the results are mixed. In Nordic countries, firms in three out of eleven industrial clusters have fewer patents than those in isolated areas, whereas firms locating in science parks outperform those placed elsewhere in Taiwan. While the regional R&;D spillover effect on firm innovation is ambiguous, the beneficial technology spillover effect overwhelmingly boosts firm patenting across different regions and industries in France, Germany and Taiwan. A country or region can improve its innovation performance by encouraging spatial agglomeration only when the firm-region interaction of R&;D activities is implemented in the close technology fields. Otherwise, a pro-cluster subsidy simply attracts the less efficient firms to relocate leading to no gains from agglomeration.
Keywords: Innovation; R&;D Spillover; Patent; Technology Spillover; Product Market Competition; Agglomeration; Science Park; TFP; Labor Density

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