要旨：近年、人工知能・ロボット・自動化に関する急速な技術進歩により人々の雇用が奪われるのではないかという懸念が高まっている。そこで本研究では、職業別のコンピュータ化確率と日本の雇用データを用いて、コンピュータ化に対する雇用リスクを分析する。本研究の特徴として、職業の地理分布は国内で均一ではなく、ある職業は都市に多く、またある職業は地方に多いということが観測されていることから、特に地域の異質性を考慮することにある。同様に、職業の地理分布は男女別にも異なることから、男女別・都市規模別という観点からコンピュータ化に対する雇用リスクを分析する。分析の結果、男性の場合、大都市圏ほどコンピュータ化されにくい職業に就いている労働者の割合が高く、コンピュータ化に対する雇用リスクが低くなる一方で、女性の場合、全く逆の傾向を示すことがわかった。つまり、大都市圏ほど、男性に対して女性はコンピュータ化に対する雇用リスクが相対的に高いということである。また、コンピュータ化確率の高い職業ほど就業者の平均教育年数の値が低い傾向にあり、コンピュータ化されにくい職業へ転職するには追加的な人的資本投資が必要とされることが示唆される。政策的含意として、多くの先行研究が指摘するように、コンピュータによって代替されにくい職業や今後生まれる新たな職業へ容易に転職ができるよう、人的資本の底上げは重要であると考えられる。また十分な人的資本を保有しているにも関わらず、コンピュータ化確率の高い職業に留まっている就業者も観測されており、潜在的に持っている能力を十分活用できるような雇用流動化を支える政策が重要になってくる。さらに、人工知能の支援によってビジネス効率化とよりよいワーク・ライフ・バランスの双方が実現されれば長時間労働が必要でなくなり、労働者の能力に基づいて評価される雇用環境を整備することは、女性活躍推進という点からも必要になってくるだろう。

要旨：In recent decades, some large terminal operators has strengthen their presence in seaports and they are called "mega terminal operators." One remarkable feature of the mega operator is its operations at multiple ports in foreign countries. This has completely changed competition structures in seaports all over the world. In this paper, we present a formal economic model of maritime transportation which incorporates foreign operation by mega terminal operators. We investigate how the emergence of a mega terminal operator affects the port charges and the welfare of two countries by comparing two cases, i.e., with and without a mega terminal operator. We also examine whether the international operation by the mega operator could be an equilibrium outcome, by looking at the incentives of the operators and the government. It is shown that the emergence of the mega operator is world welfare improving, but the effect on the foreign country is ambiguous: the welfare of the foreign country tends to be greater when the relative demand size of the foreign country is larger and the substitutability of two services are sufficiently low. Furthermore, in the entry game, there exist equilibria where one operator chooses to be the mega terminal operator and the other chooses not, when the substitutability of two services are sufficiently high and the costs for entry are intermediate.

応用ミクロ経済学ワークショップと共催

要旨：In this paper, we revisit a wide variety of existing economic geography models in a many-region setup, and investigate the spatial scale of agglomeration and dispersion intrinsic to each model. By characterizing spontaneous agglomerations specific to each model in a unified analytical framework, we show that these models reduce to two canonical classes: one with global dispersion force and the other with local dispersion force. Their formal distinction is that the global dispersion force is dependent, while the local one is independent of the distance structure of the model. These classes exhibit two stark differences. First, on the response to transport costs, local dispersion is triggered by lower costs, while global one by higher costs. Second, on the agglomeration pattern, multiple agglomerations emerge and are spread over the regions in the former, while the agglomeration always takes the form of a unimodal regional distribution of mobile agents in the latter. The knowledge of these variations in agglomeration behavior is crucial for empirical analyses of agglomerations. The prevailing reduced-form regressions (e.g. Redding and Turner, 2015, §20.4) typically assume a monotonic relation between interregional transport accessibility and the size of agglomeration in a given region. But, it is not generally the case when agglomerations are endogenous. The well-accepted structural approaches (e.g., Redding and Rossi-Hansberg, 2017, §3) adopt the models of the latter class, which in turn implies a negative correlation between the level of transport costs and the size of agglomeration. But, this correlation is specific to the class of their model, and the estimated impacts would differ (in fact would be opposite) if models of the other class were adopted.

要旨：With the tremendous progress of technology in recent years, the automation of production is proceeding. Moreover, it is said that the development of artificial intelligence will accelerate production automation in the future. Does automation bring growth or decline of the regions? In order to investigate the problem, this paper constructs a measure which shows how much impact of automation each state has. The measure is used to analyze the effect of automation on interstate migration in the period 2004 - 2015. It is shown that people migrate to a state with more impact of automation. Especially, skilled occupations and some unskilled occupations, which is related to skilled occupations, tend to migrate. These results suggest that automation may accelerate agglomeration of skilled occupations.