Showing papers by "Hiroshi Morita published in 2019"
TL;DR: In this article, a profit ratio change index is proposed to measure productivity growth and suitable for situations when producers desire to maximize revenue and minimize expenses simultaneously, and the authors demonstrate the method on a Japanese banking data set.
Abstract: We propose a profit ratio (the ratio of revenue to expenses) change index, which can be applied to panel data to measure productivity growth and suitable for situations when producers desire to maximize revenue and minimize expenses simultaneously. To identify the drivers of changes in a profit ratio change index, we decompose the index into profit ratio efficiency change and change of profit ratio boundary. We also propose an alternative decomposition of the profit ratio change index, which is the product of the Malmquist input-oriented productivity index and an allocation Malmquist productivity index. We demonstrate the method on a Japanese banking data set.
6 citations
Posted Content•
TL;DR: In this paper, the authors developed a new approach to estimate a production function based on the economic axioms of the Regular Ultra Passum law and convex non-homothetic input isoquants.
Abstract: We develop a new approach to estimate a production function based on the economic axioms of the Regular Ultra Passum law and convex non-homothetic input isoquants. Central to the development of our estimator is stating the axioms as shape constraints and using shape constrained nonparametric regression methods. We implement this approach using data from the Japanese corrugated cardboard industry from 1997-2007. Using this new approach, we find most productive scale size is a function of the capital-to-labor ratio and the largest firms operate close to the largest most productive scale size associated with a high capital-to-labor ratio. We measure the productivity growth across the panel periods based on the residuals from our axiomatic model. We also decompose productivity into scale, input mix, and unexplained effects to clarify the sources the productivity differences and provide managers guidance to make firms more productive.
2 citations
01 Jul 2019
TL;DR: The total decision cost associated with rough regions is addressed and an attribute reduction algorithm will be designed based on minimum decision cost in a lattice-valued information system (LvIS).
Abstract: The decision-theoretic rough set utilizes Bayesian decision to interpret the thresholds of probabilistic rough set model. That provides a novel semantic description for rough regions in the viewpoint of three-way decision theory and has been applied to numerous fields. However, it lacks the ability to deal with lattice-valued information system (LvIS), in which the condition attribute set consists of multiple types of attributes and their domain constitute lattice. Therefore, this study concentrates on the decision-theoretic rough approach in a LvIS. Then, the total decision cost associated with rough regions is addressed and an attribute reduction algorithm will be designed based on minimum decision cost. Finally, a case study on medical diagnosis is conducted to illustrate the decision procedure and attribute reduction approach.