Doctoral Dissertation Research: A Statistical Analysis of the Location Factors of High-Tech Centers in the United States, 1950-1997: An Evaluation Using Quasi-Experimental Method

高科技中心成功的区位因素是什么？以前对高科技产业的研究是否揭示了这个问题？如果不是，我们如何确定合理的因素和原因？本论文将通过对美国高科技中心的统计研究来解决这些问题。高科技产业作为主要的就业创造者和主要的产业创新者，在解释战后美国经济繁荣方面发挥了关键作用。关于如何复制硅谷、128号公路或三角研究园等高科技中心的成功，人们进行了相当多的讨论。研究的重点是关于主要高科技中心的关键位置因素的问题，以期协助希望发展类似创新中心的规划人员和决策者。以前的研究集中在：(1)联邦支持的作用；(2)大学作为基础研究的提供者和受过教育的工人的提供者；(3)商业条件，如当地产业规模、专利、风险资本和外国直接投资；(4)生活质量，包括气候、生活成本、犯罪、娱乐和教育；(5)各种因素的组合被认为是重要的。最近的大多数研究都试图找出解释已建立中心的健壮性的因素，但这些讨论中的一个严重缺陷是，它们只关注高科技中心群体本身的表现。这些研究结论的合理性是有限的，因为据我们所知，没有使用对照组。本文提出的研究将填补这一空白，首先确定合适的对照组，然后系统地检验有关高科技中心成功解释的假设。除非对这些中心的成长和发展有明确的了解，否则很难理解制定成功的高科技中心发展政策的过程。其他方法，如转移份额，计量经济分析和面板数据分析，也将需要充分检验假设。本研究项目必须采用统计方法来确定解释成功的高科技中心的可靠位置因素。具体而言，将采用准实验控制组方法。这涉及到选择一个初始条件与成功的高科技中心相似的对照组，并需要测量对照组与高科技中心之间的差异。为了排除大多数内生效应，将使用1950年以来的美国县级人口普查数据。为了防止在适当配对比较的选择过程中出现变量之间的尺度问题，我们将采用马氏距离；这是一种在人类学、生物统计学、流行病学和其他学科中经常使用的测量方法（Isserman 1999）。回归分析将用于比较和确定重要的因果因素。将检验相互竞争的假设，并提出结论和政策影响。本研究的结果应有助于我们更好地理解选定的高科技中心的成功。研究结果比现有的高新技术中心文献更能为高新技术中心的发展提供指导。这样一来，这项研究将阐明许多地方和地区政府及规划者感兴趣的合理的高科技选址政策。

What are the location factors that explain successful high-tech centers? Do previous studies of the high-tech industry shed light on this question? If not, how can we identify plausible factors and causes? These questions will be addressed in this dissertation research project through a statistical study of U.S. high-tech centers. High-tech industries, as a major job generator and as a major industrial innovator, play a key role explaining the postwar U.S. economic prosperity. There has been considerable discussion of how to possibly duplicate the success of high-tech centers such as Silicon Valley, Route 128, or Research Triangle Park. Research has been directed at questions on the pivotal location factors of the major high-tech centers, in an attempt to assist planners and policy makers who desire to develop similar centers of innovation. Previous research has focused on: (1) the role of federal support, (2)universities as providers of basic research and as suppliers of educated workers, (3)business conditions such as local industry size, patent, venture capital, and foreign direct investment, (4) quality of life, which includes climate, cost of living, crime, recreation, and education, and (5) combinations of factors are considered significant. Most recent studies seek to identify the factors that explain the robustness of established centers, but a serious gap in these discussions is that they focus on the performance of the group of high-tech centers by themselves. The plausibility of conclusions from such studies is limited because, to our knowledge, no control groups were used. The proposed research would fill this gap by first identifying suitable control groups and then systematically testing hypotheses on the explanation of high-tech center success. Until the growth and development of these centers is clearly understood, it will be difficult to fathom the process on which a successful high-tech centers growth policy can be built. Other methods such as shift-share, econometric analysis, and panel data analysis will also be required to fully test the hypotheses. This research project will necessarily employ statistical approaches to identify reliable location factors that explain successful high-tech centers. Specifically, a quasi-experimental control group method will be used. This involves the selection of a control group with similar initial conditions as the successful high-tech centers, and requires measuring the differences between the control group and high-tech centers. County-level U.S. census data from 1950 will be utilized in order to exclude most endogenous effects. To prevent a scale problem among variables in the selection process of properly paired comparisons, Mahalanobis distance will be adopted; this is a measure frequently used in anthropology, biostatistics, epidemiology, and other disciplines (Isserman 1999). Regression analysis will be utilized to compare and to identify significant causal factors. Competing hypothesis will be tested, and conclusions and policy implications will be suggested. The results of this study should provide a better understanding of the success of selected high-tech centers. The results can offer guidelines for high-tech center development, more so than the available high-tech centers literature. In so doing, the study will shed light on plausible high-tech location policies that many local and regional governments and planners are interested in.