Time-series analysis and policy research on dynamic externalities and endogenous economic growth in Tokyo and Osaka

本文利用1975-2003年日本东京和大阪地区个位数产业的时间序列数据，对动态外部性对经济增长的影响进行了协整分析。在分析中使用了最近发展起来进行单位根和协整检验的一些新的时间序列计量经济学方法，允许在所研究的时间段内由内生决定的结构变化。本文还提出了一种新型的动态外部性，称为网络动态外部性，用来表示整个集聚区通过交通运输网络产生的知识溢出，并表明它们与制造业、金融业、批发零售业以及整个行业的全要素生产率(TFP)之间存在协整关系。此外，证据还发现，与自身工业生产集中度相关的马歇尔-阿罗-罗默(MAR)动态外部性影响所选择的大多数行业的全要素生产率。然而，以工业生产多样性为代表的雅各布斯动态外部性只对服务业的全要素生产率有贡献，而以产业内部竞争力表示的波特动态外部性不会影响所选择的产业全要素生产率。

This research project conducts a cointegration analysis on the effects of dynamic externalities upon economic growth using time-series data from 1975 to 2003 on the one-digit industries of Tokyo and Osaka metropolitan areas in Japan. Some new time-series econometric methods that have been recently developed to conduct unit root and cointegration tests are used in the analysis, allowing for an endogenously determined structural change in the time period studied. It also proposes a new type of dynamic externalities, called Network dynamic externalities, to represent knowledge spillovers resulting from the whole agglomerated area via transportation networks, and shows that they have cointegrated relations with the total factor productivity (TFP) of the manufacturing, finance, wholesale and retail trade, as well as the overall industries. In addition, evidence is also found that Marshall-Arrow-Romer (MAR) dynamic externalities, which are associated with own industrial production concentration, affect the TFP of most industries selected for estimation. However, Jacobs dynamic externalities, which are represented by the diversity of industrial production, only contribute to the TFP of the services industry, and Porter dynamic externalities, which are expressed by the competitiveness within industries, do not influence the selected industrial TFP.