The Japanese Economic Review最新文献

Static supervised learning—in which experimental data serves as a training sample for the estimation of an optimal treatment assignment policy—is a commonly assumed framework of policy learning. An arguably more realistic but challenging scenario is a dynamic setting in which the planner performs experimentation and exploitation simultaneously with subjects that arrive sequentially. This paper studies bandit algorithms for learning an optimal individualised treatment assignment policy. Specifically, we study applicability of the EXP4.P (Exponential weighting for Exploration and Exploitation with Experts) algorithm developed by Beygelzimer et al. (Proceedings of the Fourteenth International Conference on Artificial Intelligence and Statistics, JMLR Workshop and Conference Proceedings, pp 19–26, 2011) to policy learning. Assuming that the class of policies has a finite Vapnik–Chervonenkis dimension and that the number of subjects to be allocated is known, we present a high probability welfare-regret bound of the algorithm. To implement the algorithm, we use an incremental enumeration algorithm for hyperplane arrangements. We perform extensive numerical analysis to assess the algorithm’s sensitivity to its tuning parameters and its welfare-regret performance. Further simulation exercises are calibrated to the National Job Training Partnership Act (JTPA) Study sample to determine how the algorithm performs when applied to economic data. Our findings highlight various computational challenges and suggest that the limited welfare gain from the algorithm is due to substantial heterogeneity in causal effects in the JTPA data.

We show that in all (whether generic or nongeneric) binary-action supermodular games, an extreme action profile is robust to incomplete information if and only if it is a monotone potential maximizer. The equivalence does not hold for nonextreme action profiles.

This study examines how the Bank of Japan’s (BOJ’s) exchange-traded fund (ETF) and corporate bond (CB) purchases affect the capital structure of Japanese listed firms. The results first suggest that the BOJ’s ETF purchases reduced the equity risk premium for firms included in the purchases, thereby lowering their cost of equity. These firms issued more stocks and became less dependent on bond debt and bank loans than control firms, resulting in a lower level of leverage. On the other hand, the BOJ’s CB purchases lowered the risk premium of bonds eligible for such purchases, which implies a decline in the cost of bond debt. Firms eligible for CB purchases issued more bonds, while reducing bank debt but to a smaller extent, thus having higher leverage than firms not eligible for CB purchases. Categorizing firms into four groups based on whether their stocks were included in ETF purchases and/or their bonds were eligible for CB purchases further shows that the policy impacts on firm financing have differed depending on which group a firm fell in. These results indicate that the BOJ’s ETF and CB purchases have had a considerable impact on the cost of capital, securities issuance activities, and corporate capital structure.

Using microdata from the Retail Price Survey (the basic statistics for the Consumer Price Index), we document facts regarding price stickiness in Japan. The main results are as follows: (1) The average frequency of price changes approximates (20%) on a monthly basis. (2) The frequency of price changes is more heterogeneous than that in the US (3) Whereas no clear relationship exists between the frequency and size of price changes, a positive correlation emerges between the size of price changes and price dispersion across stores. (4) Large cities tend to have a higher frequency of price changes and smaller price dispersion than small cities. (5) A positive relationship exists between price changes and jobs-to-applicants ratio for some services. (6) Behind the 2022–2023 price increase, the frequency of price changes exhibits a notable increase for certain goods and services such as eating out, while no distinct change is observed for the size of price changes or price dispersion.

The finding of Feldstein and Horioka (1980) that domestic saving and domestic investment are highly correlated across countries despite the rapid globalization and liberalization of financial markets in recent decades has been regarded as a Puzzle or Paradox. However, in this paper, we show that countries as a whole may not be able to transfer their capital abroad and that the Feldstein–Horioka Finding of domestic saving and domestic investment being highly correlated across countries may arise even if there are no frictions in financial markets and even if individual investors can freely transfer their capital abroad if there are frictions in goods markets such as transport costs, tariffs, nontariff barriers, the cost of regulatory compliance, etc. In fact, there is evidence that frictions in goods markets are a more serious impediment to countries as a whole being able to transfer their capital abroad than frictions in financial markets, especially in the short run.