大学院生のみなさま、
名古屋市立大学・経済学研究科では、毎月、火曜研究会というセミナーを開催しています。
経済学を専門にしている後期課程在学中の方はもちろんのこと、後期課程への進学を考えて いる方はなるべく参加してください。
（もちろん、他の専門の方や前期課程の方も、関心があるセミナーには積極的に参加してください。。）
2月の研究会は以下のとおり開催します。
（※教授会日程の関係で変則的に月曜日の開催となっております）
開催日時：2017年2月27日(月）16:30-17:30
場所：3号館1階セミナー室
報告者：山田恵里氏（名古屋市立大学）
使用言語：日本語
報告タイトル・要旨：
The micro-geographies of productivity growth: Evidence from the auto-related industries in Japan (Tetsu Kawakami, Eri Yamada and Jiro Nemoto)
The purpose of this study is to provide basic quantitative facts about the clusters representing productivity growth, in particular, focusing on transportation equipment and its related industries in Japan. The Japanese transportation equipment industry uses cutting-edge technologies and is expected to play an important role in developing the regions designated in the cluster projects. Because of the characteristics of vertical and hierarchical organizational structures, consistent clustered productivity growth is believed to be associated with extensive knowledge spillover among related industries. We use data extracted from the Census of Manufactures, which includes information for firms, such as production, value added, employment, fixed assets, and aggregate wages. The extensive and detailed information about company aspects enables us to make the following analytical contributions. First, we are able to relate the structure of the local clusters to company productivity. Second, we capture each company’s productivity growth by using the measurement of the Malmquist total factor productivity (TFP) index. A desirable property of this index is that it is applicable without any ad hoc adjustment to the input data, even if the varying intensity of input usage conceals true productivity. Third, based on the address information of the companies, the estimated results of the technical change component of the TFP index are visualized on maps using a geographic information system. This approach for detecting clusters allows us to uncover more realistic geographical areas and decaying patterns with distance rather than research relying on political borders or predetermined geographical units. Thus, we explore whether the company’s productivity growth forms clusters, and if so, the degree of the productivity growth relates to the proximity to diversified industries or its own-industry activity. The findings would help infer the path of knowledge transfer that contributes to productive growth and establish effective regional policies.
経済学研究科
稲垣、岡野、樋口