Wage differentials and the spatial concentration of high-technology industries*
Wage differentials and the spatial concentration of high-technology industries*
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工资差异与高科技产业的空间集中度*
DOI：
10.1111/j.1435-5957.2008.00199.x
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发表时间：
2009
期刊：
影响因子：
--
通讯作者：
Sofia G. Ayala
中科院分区：
文献类型：
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作者：
Elsie L. Echeverri;Sofia G. Ayala
莫雷蒂（Moretti，2004）发现，在20世纪90年代，美国各城市的人力资本分布变得更加不平等。他认为，人力资本日益集中在一些大都市地区的一个原因是那十年的高科技繁荣，因为它使少数已经拥有高技能的城市受益。这一趋势反映了技术工人和雇用他们在同一城市或地区（高技术集群）共同选址的技术密集型产业的决定。例如，Zucker等人（1998年）发现，新的生物技术公司进入城市的决定取决于那里杰出科学家的人力资本存量，这是以相关学术出版物的数量来衡量的。主机代管既有利于工人（他们享受与当地学习过程相关的提高生产力的效果），也有利于高科技公司（它们从提高公司创新过程的高生产力和创造力的工人中获利）。高技术集群中的主要合作联系与知识交流有关。正如Fingleton等人（2004年）指出的那样，共享知识是产生和维持创新流的关键，而创新流在这些集群中尤其重要。学习网络-创新关系的一个强有力的证据来自研究，研究表明，专利（创新的代表）更有可能出现在与引用的专利相同的州或大都市地区，而不是人们基于先前存在的相关研究活动的集中而预期的（Jaffe et al. 1993）。
Moretti (2004) finds that the distribution of human capital across cities in the United States became more unequal during the 1990s. He believes that one reason for the increased concentration of human capital in some metropolitan areas was the high-tech boom of that decade, since it benefited a handful of already highly skilled cities. This trend reflects the decisions of skilled workers and the skill-intensive industries that employed them to colocate in the same cities or regions (high-tech clusters). Zucker et al. (1998), for instance, find that the entry decisions of new biotechnology firms in cities depends on the stock of human capital in outstanding scientists there, as measured by the number of relevant academic publications. Colocation benefits workers (who enjoy the productivity-enhancing effects associated with local learning processes) as well as high-tech firms (which profit from highly productive and creative workers who enhance the firms’ innovation processes). The primary cooperative linkages in high-technology clusters are those related to knowledge exchange. As Fingleton et al. (2004) note, sharing knowledge is the key to the generation and maintenance of innovation flows that are particularly relevant in these clusters. A strong evidence of the learning networks-innovation relationship comes from studies showing that patents (a proxy for innovations) are more likely to emerge from the same states or metropolitan areas as the cited patents than one would expect based in the preexisting concentration of related research activity (Jaffe et al. 1993).