Search

This paper describes our work on developing a new business sentiment index using daily newspaper articles. We adopt a recurrent neural network (RNN) with Gated Recurrent Units to predict the business sentiment score of a given text and aggregate the scores to define an index, named S-APIR. An RNN is initially trained on Economy Watchers Survey and then fine-tuned on news texts for domain adaptation. Also, a one-class support vector machine is applied to filter out texts irrelevant to business sentiment. Moreover, we propose a simple yet useful approach to temporally analyzing how much and when any given factor influences the predicted business sentiment. The validity and utility of the proposed approach are empirically demonstrated through a series of experiments on Nikkei Newspaper articles published from 2013 to 2018.

Policy making and the practice of competition policy requires an assumption to be made on the type or mode of competition, and it is important to accurately anticipate the outcome from the assumed competition mode. It is well known that outputs under hard competition (Bertrand competition) are larger than under soft competition (Cournot competition) in a conventional setting. The aim of this study is to examine the standard outcome by comparing soft competition to hard competition in a vertically related market. The main analytical contribution of this study is the analysis of policy making and practice by building a supply function model. Supply function competition models a situation where competing firms set their production schedules under given market prices. The degree of competition is judged by the slope. When the slope is zero, the strength of the market competition represents Cournot competition. When the slope is large enough, it represents Bertrand competition. Thus, an intermediate degree of the slope seems to reflect an intermediate degree of competition. The market structure in this paper consists of an upstream monopolist and two downstream firms. I assume that the upstream firm faces a commitment problem due to secret offerings for a trading contract by a linear pricing contract or two-part tariff contract. I model the negotiation for the contract by Nash bargaining considering observability of a breakdown in the negotiation. At equilibrium, I obtained unconventional results under the two-part tariff contract in the supply function model, as well as in comparison to Cournot competition and Bertrand competition. Specifically, wholesale prices under soft competition are lower than under hard competition. Thus, my results show that the total quantity and total surplus under soft competition are larger.

Mergers can bring with them not only efficiency gains but also anticompetitive effects. Moreover, when firms announce mergers with limited lead time and information, it is crucial that regulatory bodies be able to judge them appropriately. This paper examines a merger between NKK and Kawasaki Steel that had a deep economic impact. I employ the conventional event study approach using abnormal stock returns. In addition to investigating these two firms and their rival firms, I examine customer firms in four steel-consuming industries in order to paint a broader picture of mergers. I consider the reactions of abnormal returns as measured by twelve patterns, and identify several merger effects. Firms in the steel industry anticipated a significant increase in their future profits as a result of this merger. Of the customer firms, some anticipated an increase in their profits, whereas others expected to suffer losses. However, the statistical significance of their reactions was weak, and, thus, the merger’s effects on customer firms could not be measured accurately. The results suggest that the primary intent of this merger was to improve efficiency. Future studies should investigate the results of the merger in real terms, including its effects on steel prices and steel production, for example, rather than merely in financial terms.