Macro-econometric Models and the Outline of the MEAD-RIETI Model (Japanese)

The global financial crisis, triggered by the subprime mortgage problem and resulting in the collapse of a major American investment bank in September 2008, has seriously affected the Japanese economy. The Japanese government has instigated certain policies in response to the global economic recession and volatility in financial markets. In formulating policies, it has become increasingly necessary to forecast different economic scenarios by taking into account the possible impact of policies and risks, including contributing factors from abroad. Using macro-econometric models is one way to respond to this. In recent years, the governments, central banks and international organizations of many nations have placed more emphasis on aligning their macro-econometric models with macroeconomic theory, in order to better respond with the "Lucas Critique." This paper will attempt to achieve two things: 1) to illustrate the macro-econometric models of foreign countries and Japan and the macroeconomic theory behind those models, and 2) to explain the "MEAD-RIETI Model" (MRM) which we have constructed. While the aim of the MRM is to evaluate quantitatively the risks and impacts of policy decisions, it is a hybrid model which attaches a high degree of importance to how it fits with empirical data considering the consistency of the model with macroeconomic theory. Although MRM comprehensively covers SNA and other key economic variables, MRM prefers simplicity over complexity with regards to model specification and avoids the use of too many variables.

Development of Study on Current Account Imbalances and Foreign Sectors in Macro-econometric Models (Japanese)

Venture businesses serve an important role for economic development. Since the 1990s, the Japanese government has been seeking to boost the activities of venture businesses with its policy programs. Nevertheless, Japan has not yet realized an economy in which venture businesses lead the economy, and its venture policy is now at a turning point. To enhance the activities of venture businesses, it is essential to attract venture capitalists and their risk money. Accordingly, the Japanese government established the "Venture Fund Program" in 1999. The program finances private venture funds, providing venture businesses in the early stages with risk money and management support. The program supports 85 funds, and over 2000 venture businesses have received financing. Following 10 years of program implementation, it is high time to evaluate the performance of this policy. Not many evaluation studies on venture policy programs in Japan have been conducted. This research evaluates the program via data analysis and interviews. Our research has found that the program contributes to the growth of venture businesses and fosters the venture capital industry. On the other hand, we also found that those venture funds with multiple purposes other than promoting venture businesses experienced difficulties in terms of implementation. In order to enhance a venture economy, it is important to get an objective policy evaluation from academia.

Comprehensive Network Analysis of Anther-Expressed Genes in Rice by the Combination of 33 Laser Microdissection and 143 Spatiotemporal Microarrays

Co-expression networks systematically constructed from large-scale transcriptome data reflect the interactions and functions of genes with similar expression patterns and are a powerful tool for the comprehensive understanding of biological events and mining of novel genes. In Arabidopsis (a model dicot plant), high-resolution co-expression networks have been constructed from very large microarray datasets and these are publicly available as online information resources. However, the available transcriptome data of rice (a model monocot plant) have been limited so far, making it difficult for rice researchers to achieve reliable co-expression analysis. In this study, we performed co-expression network analysis by using combined 44 K agilent microarray datasets of rice, which consisted of 33 laser microdissection (LM)-microarray datasets of anthers, and 143 spatiotemporal transcriptome datasets deposited in RicexPro. The entire data of the rice co-expression network, which was generated from the 176 microarray datasets by the Pearson correlation coefficient (PCC) method with the mutual rank (MR)-based cut-off, contained 24,258 genes and 60,441 genes pairs. Using these datasets, we constructed high-resolution co-expression subnetworks of two specific biological events in the anther, “meiosis” and “pollen wall synthesis”. The meiosis network contained many known or putative meiotic genes, including genes related to meiosis initiation and recombination. In the pollen wall synthesis network, several candidate genes involved in the sporopollenin biosynthesis pathway were efficiently identified. Hence, these two subnetworks are important demonstrations of the efficiency of co-expression network analysis in rice. Our co-expression analysis included the separated transcriptomes of pollen and tapetum cells in the anther, which are able to provide precise information on transcriptional regulation during male gametophyte development in rice. The co-expression network data presented here is a useful resource for rice researchers to elucidate important and complex biological events

Prediction Errors of Macroeconomic Indicators and Economic Shocks for ASEAN Member States, 1990‒2021

In this study, we analyze how economic shocks affect six ASEAN Member States --Indonesia, Malaysia, Philippines, Singapore, Thailand, and Vietnam --in three dimensions: global, domestic, and uncertainty shocks. We collect macroeconomic indicators for 1990-2021 and calculate macroeconomic shocks based on the prediction errors of real GDP growth rates. First, we demonstrate that countries were significantly subjected to unforeseen negative economic shocks on average. Second, we show high synchronization of economic fluctuations and shocks within these countries and with the world. Third, by conducting regression analyses separately, we derive the following: (i) positive association between variations of the global real GDP growth rates and countries' economic shocks; (ii) different quantitative significance of previous estimates among countries; (iii) country-specific domestic shocks; and (iv) correlation of global- and country-level uncertainty indices with negative economic shocks in some AMS. Our results highlight the relative importance of global, domestic, and uncertainty shocks in the AMS as 56.3%, 39.6%, and 2.8%, respectively. Finally, based on this dataset and conducted analysis, we also review the effect of the COVID-19 pandemic on these countries

Preoperative Fall Risk Assessment Score as a Prognostic Factor in Esophageal Cancer Patients after Esophagectomy

The current study investigated the impact of preoperative fall risk assessment score (FRAS) on long-term prognoses in patients with esophageal cancer (EC). A total of 161 patients with EC who underwent curative surgery were classified into a high-risk (95, 41.0%) and low-risk (66, 41.0%) groups according to their FRAS. This study investigated the relationships between the FRAS and clinicopathological findings and prognoses. Accordingly, patients in the high-risk group were significantly older and had a significantly higher Charlson comorbidity index than those in the low-risk group. No significant difference was found in pathological findings between both groups. The high-risk group had significantly lower overall survival (OS) and relapse-free survival (RFS) rates than the low-risk group (p = 0.004 and 0.001, respectively). Multivariate analysis identified high FRAS as an independent prognostic factor for poor OS, with a hazard ratio of 1.75 (p = 0.033). Moreover, re-analysis of the data after excluding age as a category showed that the high-risk group had significantly worse OS (p = 0.004) and RFS (p = 0.003) than the low-risk group. The FRAS can, therefore, be considered a useful method for assessing frailty and a potential prognostic factor for EC

Molecular characterization of DXCF cyanobacteriochromes from the cyanobacterium Acaryochloris marina identifies a blue-light power sensor

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