経済学部

Retail investors, who are the majority traders in the Chinese stock market, cannot participate in off-line roadshows of IPO firms. Online roadshows are an important channel for them to learn about the situation of IPO firms. This study takes the IPO firms which are new-listed in Shenzhen Stock Exchange from 2010 to 2018 as the research subject, investigates the relationship between question-answers relevance in online roadshows and the first-day performance of IPO firms. According to the results, a high-level of question-answers relevance leads to a high first-day return and high liquidity. Furthermore, the additional analysis shows that the IPO firms with a high-level of question-answers relevance show stable long-term stock returns, on the contrary, the IPO firms with a low-level of question-answers relevance show the trends to decrease. Online roadshows could mitigate the information asymmetry between the investors and IPO firms, and play an important role in assessing firm values.

This research aims to examine the relationship between political connections and bank performance during the COVID-19 pandemic in Indonesia, with data sample comprising banks listed on the Indonesia Stock Exchange （IDX）. The study employed a panel data linear regression and found an insignificant positive influence of political connections on banks' profitability. However, the result also indicates marginally lower profitability in politically connected banks compared to non-connected peers, and the event-study methodology reveals the tendency for affiliated banks to obtain substantial negative abnormal returns during the pandemic. Therefore, there is a negative effect of COVID-19 on stock performance of politically connected banks.

The non-efficiency of the government hospital is pointed out. Then, I compare the management in government hospitals and non-government hospitals, and show clearly what kind of difference there is. In this paper, the following things are clear. (1) Clarify the difference from a viewpoint of management in government hospitals and non-government hospitals. (2) Classify government hospitals into two kinds (cites・towns・and villages-hospitals and prefectural hospitals), and clarify the difference from a viewpoint of management. (3) Classify non-government hospitals into eight kind hospitals, and clarify the feature in management.

There is a risk of longevity i.e., the self-funds after retirement may deplete before the end of life. What is needed after retirement is to spend out of self-funds in addition to public pensions while investing self-funds over lifetime without depleting. We analyze a safe withdrawal rate based on varying self-funded amounts every month due to fluctuation in the market. According to this method, there is no longevity risk that self-funds are depleted throughout lifetime.

The purpose of this paper is to present an alternative macroeconomic model. The classical macroeconomic model and AD-AS model have some problems. The macroeconomic model presented in this paper solves them and is more realistic and logically consistent than the other models.

本稿では, 行動と成果の確率的関係について不確実性があるプリンシパルーエージェント関係を考え, 最適契約を特徴付ける.

Germany's energy transition （Energiewende） is a paradigm shift into a low-carbon and nuclear-free economy. As part of the European Union's climate neutralization drive, aiming to reduce greenhouse gases to net-zero by the middle of the century. Generous financial support for wind and solar power has boosted renewable energy to produce more electricity than fossil fuels for the first time in 2020. Germany's energy transition is not a policy shift after the Fukushima nuclear disaster, but a long-term process of policy making in response to public opinion and technological trends. Germany's energy transition is still underway and needs to be extended beyond the power supply. However, it may already be pushing more thoroughly through pricing and volume regulations, such as the European Emissions Trading Scheme （EU-ETS） and changes to the carbon tax, which provides incentives for changes to low-carbon technologies. This paper analyses Germany's energy transition and climate policy. The purpose of this paper is to clarify the actual conditions and issues of the reduction effects of greenhouse gas emissions, which are the main policy issues of the energy conversion policy that has been developed mainly on renewable energy for these 20 years.

In this study, we present a new method for estimating input coefficient matrix with deep learning. We use the data of prefectures of Japan as the training data. However, the data is small and is likely to cause overfitting. Therefore, we attempt to avoid the over-fitting by creating new data of virtual areas aggregating multiple prefectures. The approach is based on the concept of data augmentation. As a result of predicting the input coefficient matrix of Yamaguchi prefecture and Gujo city, we showed that the method using deep learning can estimate the matrix with more stable accuracy than RAS method for these areas.