最新区域经济发展战略.docx

1、最新区域经济发展战略区域经济发展战略区域经济发展战略课程作业 专 业 区域经济学 班 级 经管院研1022 学 号 1002021085 姓 名 尚天祥 2010 年 秋季 学期Evolutionary economic geography and its implications for regional innovation policy Ron BoschmaAbstractRelated variety is important to regional growth because it induces knowledge transfer between complementary

2、sectors at the regional level. This is accomplished through three mechanisms: spinoff dynamics, labor mobility and network formation. They transfer knowledge across related sectors, which contributes to industrial renewal and economic branching in regions. Since these mechanisms of knowledge transfe

3、r are basically taking place at the regional level, and because they make regions move into new growth paths while building on their existing assets, regional innovation policy should encourage spinoff activity, labor mobility and network formation. Doing so, policy builds on region-specific assets

4、that provides opportunities but also sets limits to what can be achieved by policy. Public intervention should neither apply one-size-fits-all approaches nor adopt picking-the-winner strategies, but should aim to connect complementary sectors and exploit related variety as a source of regional diver

5、sification. Key words: related variety, evolutionary economic geography, regional innovation systems,regional growth.1. IntroductionWhy do some regions grow more than others? Till the late 1980s, neo-classical theory argued that technology is a key determinant of regional growth. However, technology

6、 was treated as an exogenous factor and, therefore, the geography of innovation was left unexplained (Alcouffe and Kuhn, 2004). Inspired by Schumpeters work, economic geographers played a prominent role in criticizing this neo-classical framework. From the early 1980s onwards, they focus attention o

7、n the explanation of the geography of innovation. Some regions are more innovative than others, and region-specific characteristics like institutions may be underlying forces. This even led to the claim that regions are drivers of innovation and economic growth. Concepts like industrial districts (B

8、ecattini, 1987), clusters (Porter, 1990), innovative milieux (Camagni, 1991), technology districts (Storper, 1992), regional innovation systems (Cooke, 2001) and learning regions (Asheim, 1996) have been launched in the last decades to incorporate this view. Many of these regional concepts have draw

9、n inspiration from evolutionary economics (Nelson and Winter, 1982; Dosi et al., 1988). This chapter aims to outline the drivers of regional growth, as proposed by evolutionary economic geographers (Boschma and Lambooy, 1999; Boschma and Martin, 2007). We claim that regional growth is based primaril

10、y on exploiting intangible assets such as tacit knowledge and institutions, rather than static cost advantages. More in particular, we will argue that related variety may be a key source of economic diversification of regions. The objective of this chapter is to set out how these insights taken from

11、 evolutionary economic geography may be incorporated in regional innovation policy. This is anything but easy. Wegner and Pelikan (2003) state that evolutionary economics consists of two distinctive strands of thought, that is, the neo-Schumpeterian (Nelson and Winter) and the Austrian approach (Hay

12、ek), which hold quite diverging views on policy. While the former advocates active government intervention, the latter does not. Another problem is that the empirical literature on regional policy tends to be rather fragmented and inconclusive (see e.g. Brons, et al., 2000; Nijkamp and Stough, 2000)

13、. An obvious reason is that we do not know what would have happened if policy had not been installed. Notwithstanding these difficulties, we come up with some policy recommendations that incorporate recent thinking in evolutionary economic geography.2. Variety, related variety and regional developme

14、ntOur starting point is a fundamental departure from how conventional neo-classical economics treats knowledge. Knowledge is not a public good that is characterized by diminishing returns to scale. On the contrary, knowledge evolves: it is not reduced when it is used, but it accumulates through proc

15、esses of learning-by-doing (Arrow, 1962). This cumulative and irreversible nature of knowledge development is embodied in individuals (skills) and in firms (routines): they develop different cognitive capacities over time (Nelson and Winter, 1982; Dosi et al., 1988).Knowledge also tends to accumulat

16、e in space, leading to inter-regional variety of knowledge. There are many examples of regions and countries that specialize in a particular knowledge field, and which continue to do so for a long time. Many industries tend to concentrate in space, like the film industry in Hollywood, the financial

17、sector in the city of London, and the American car industry in Detroit. There are also huge differences between countries and regions as far as investments in R&D and human capital are concerned, leading to persistent income differentials between countries over time (Grossman and Helpman, 1991). Res

18、earch and Development is extremely spatially concentrated, favoring only a small number of regions, and empirical studies show this pattern is quite stable over time (Feldman and Audretsch, 1999). Many studies have found strong relationships between regional stocks of knowledge (as embodied in unive

19、rsity research and private R&D) and economic performance (e.g. Anselin, Varga and Acs, 2000).6. ConclusionsWe have built on insights drawn from evolutionary economic geography to present some recommendations for effective regional innovation policy. Since knowledge tends to accumulate mainly at the

20、firm level, variety is the rule, and the more diversified a regional economy is, the higher regional growth. However, knowledge may also diffuse between firms, having an additional impact on regional development. If knowledge externalities are geographically bounded, knowledge will also accumulate a

21、t the regional level. In addition, knowledge will spill over more intensively when regions are endowed with related industries that share a common knowledge base. Related variety favors economic branching in regions through spinoff dynamics, labor mobility and networks. Because these mechanisms tran

22、sfer knowledge across related sectors mainly at the regional level, they contribute to a successful process of regional diversification, which is crucial for long-term regional development.However, knowledge creation and knowledge spillovers alone will not lead to innovation. Regions require a criti

23、cal mass of organizations that provide necessary inputs to the innovation process, such as knowledge, skills and capital. Besides a critical mass, these organizations need to connect and interact, to enable flows of knowledge, capital and labor. In addition, organizations and institutions need to be

24、 flexible and responsive to implement change. In reality, almost by nature, organizations and institutions are not, because they suffer from lock-in, due to routines, sunk costs and path dependency.We have used these insights as key inputs and underpinnings for effective regional innovation policy.

25、Following system failure arguments, public policy has the task to establish key organizations of innovation systems in regions where these are found missing, or public policy has to ensure that these missing inputs to the innovation process will flow into the region. Once available, public intervent

26、ion should encourage key organizations to connect, for example, firms need to be linked with research institutes and capital suppliers. In addition, public policy can make organizations more flexible and innovative, for instance, by upgrading their routines through the supply of new knowledge and sk

27、ills. Finally, regional innovation policy can stimulate the effective transfer of knowledge at the regional level by means of spinoff activity, labor mobility and networks. Since these mechanisms of knowledgetransfer are basically taking place at the regional level, and because they make regions mov

28、e into new growth paths while building on existing assets, these policy actions put in practice the idea that related variety may contribute to long-term regional development.To increase the probability of policy success, regional innovation policy needs to account for the region-specific context th

29、at provides opportunities but also sets limits to what can be achieved by policy. Doing so, public intervention should neither apply one-size-fits-all frameworks nor adopt picking-the-winner policies. This is the main message that transcends this OECD report (Cooke, 2009; Iammarino and McCann, 2009)

30、. Instead of copying best practice models or selecting winners, policy should take the history of each region as a starting point, and identify regional potentials and bottlenecks accordingly. To avoid regional lock-in, it is crucial that policy is open to newcomers and policy experiments. 演化经济地理学及其

31、在区域创新政策中的应用摘要：相关品种对于区域增长是很重要的,因为它导致互补部门之间在区域水平方面的知识转化。这是依靠三种机制完成的:分离动力学、劳动力流动和网络的形成。他们会将知识转化成有助于工业更新和经济在地区的分支的相关板块。由于这些知识转移的机制基本上发生在地方,也因为他们使地区进入新的增长阶段。因此，为了不断扩大他们现有的资产，区域创新政策应该鼓励分离活动,劳动力流动和网络的形成。这么做,政策建立在特殊的地区资产上，既能提供机会,也能专门设置限制政策。公共干预不能用千篇一律申请的方法，也不能用挑选成功案例的策略,而应该将目标放在连接互补部门和利用相关的转化作为区域多样化的一个来源。关键

32、词：相关品种 演化经济地理学 区域创新系统 经济增长1 .引言为什么有些地区发展较快？一直到19世纪80年代，eo-classical理论认为技术是地区发展的主要决定因素。但是技术被看作是外源性因素并且区域的创新是难以解释的，受到Schumpeter的启发，经济地理学家们在批评新古典的框架上起到了突出的作用, 从20世纪80年代早期开始,他们开始把注意力集中在地理创新理论的解释工作上。一些地区的创新已经超过了其他地区,并且特殊地区类似机构具有潜在力量。这甚至导致有人声称地区是创新和经济增长的导向。相关文章比如工业园区(Becattini,1987年)、创新milieux(Camagni,1991)、技术地区(Storper,1992)、区域创新系统(库克,2001)和区域性研究(Asheim,1996)已经在过去的几十年将这一观点开始执行。许多这些区域获取灵感观念来自于演化经济学(纳尔逊和维特,1982;Dosi ,1988)。这一章旨在概述地区协调发展方向,就像经济地理学家所倡导的(Boschma进化和Lambooy学杂志,2003;Boschma和Martin,2007)。我们提出区域增长主要依据利用隐性知识等无形资产、制度等因素的影响,而不是静态的成本优势。更具体而言,我们认为相关的变化可能是地区经济来源多样化的关键。本章主要是从这些观点出发，阐述如何把演化经济地理学结