Hierarchical Bayesian Modeling of Post-Earthquake Ignition Probabilities Considering Inter-Earthquake Heterogeneity

Post-earthquake fires are high-consequence events with extensive damage potential. They are also low-frequency events, so their nature remains underinvestigated. One difficulty in modeling post-earthquake ignition probabilities is reducing the model uncertainty attributed to the scarce source data. The data scarcity problem has been resolved by pooling the data indiscriminately collected from multiple earthquakes. However, this approach neglects the inter-earthquake heterogeneity in the regional and seasonal characteristics, which is indispensable for risk assessment of future post-earthquake fires. Thus, the present study analyzes the post-earthquake ignition probabilities of five major earthquakes in Japan from 1995 to 2016 (1995 Kobe, 2003 Tokachi-oki, 2004 Niigata–Chuetsu, 2011 Tohoku, and 2016 Kumamoto earthquakes) by a hierarchical Bayesian approach. As the ignition causes of earthquakes share a certain commonality, common prior distributions were assigned to the parameters, and samples were drawn from the target posterior distribution of the parameters by a Markov chain Monte Carlo simulation. The results of the hierarchical model were comparatively analyzed with those of pooled and independent models. Although the pooled and hierarchical models were both robust in comparison with the independent model, the pooled model underestimated the ignition probabilities of earthquakes with few data samples. Among the tested models, the hierarchical model was least affected by the source-to-source variability in the data. The heterogeneity of post-earthquake ignitions with different regional and seasonal characteristics has long been desired in the modeling of post-earthquake ignition probabilities but has not been properly considered in the existing approaches. The presented hierarchical Bayesian approach provides a systematic and rational framework to effectively cope with this problem, which consequently enhances the statistical reliability and stability of estimating post-earthquake ignition probabilities.     

Finding environmentally important industry clusters: Multiway cut approach using nonnegative matrix factorization

This paper proposes an optimal combinatorial method for finding groups of industries with relatively large CO₂ emissions through industrial relations. Using an economic input–output table, we estimated a non-symmetric matrix describing how much CO₂ is emitted in producing the commodity of industry i, which was purchased to produce commodity of industry j, to meet the final demand for a specific commodity. A symmetric strength of relations matrix describing the CO₂ emissions associated with the industrial relations was further estimated using the non-symmetric matrix. The strength of relations matrix can be viewed as a representation of the supply-chain network of the final commodity. In this study, we estimated the strength of relations matrix associated with the final demand for automobiles and applied the multiway cut approach using nonnegative matrix factorization to the matrix in order to find environmentally important industry clusters in the Japanese automobile supply chain. According to our empirical results, the optimal number of industry clusters is 19, and 4 industry clusters are playing a key role in CO₂ emission reduction.     

Spatio-temporal distribution patterns of two tachinid flies,Epicampocera succincta andCompsilura concinnata parasitizingPieris

Summary Larvae of genusPieris in the northern part of Kyoto City are parasitized by two tachinid flies:Epicampocera succincta, a specialist on genusPieris, andCompsilura concinnata, a generalist with very wide host-range. We surveyed the parasitism rates ofPieris by both flies for two years at six study areas. In these study areas, there lived three host species in the genusPieris: P. rapae, P. melete, andP. napi, but neither tachinid parasitizedP. napi to any significant extent. In the mountainous district,P. rapae andP. melete coexisted and their populations were relatively continuous, while in the lowland, onlyP. rapae larvae were abundant in spring and autumn, but even they disappeared in summer. Parasitisms byE. succincta occurred mainly in mountainous district and never in the lowland.C. concinnata parasitizedPieris in all the areas, but its parasitisms occurred mainly in autumn. We analyzed the factors affecting the spatial and temporal patterns of parasitism rates and presumed that the temporal discontinuity of host population restricted the distribution of the specialist parasitoid.     

Asymptotics for Statistical Treatment Rules

This paper develops asymptotic optimality theory for statistical treatment rules in smooth parametric and semiparametric models. Manski (2000, 2002, 2004) and Dehejia (2005) have argued that the problem of choosing treatments to maximize social welfare is distinct from the point estimation and hypothesis testing problems usually considered in the treatment effects literature, and advocate formal analysis of decision procedures that map empirical data into treatment choices. We develop large‐sample approximations to statistical treatment assignment problems using the limits of experiments framework. We then consider some different loss functions and derive treatment assignment rules that are asymptotically optimal under average and minmax risk criteria.     

Impossibility Results for Nondifferentiable Functionals

We examine challenges to estimation and inference when the objects of interest are nondifferentiable functionals of the underlying data distribution. This situation arises in a number of applications of bounds analysis and moment inequality models, and in recent work on estimating optimal dynamic treatment regimes. Drawing on earlier work relating differentiability to the existence of unbiased and regular estimators, we show that if the target object is not differentiable in the parameters of the data distribution, there exist no estimator sequences that are locally asymptotically unbiased or α‐quantile unbiased. This places strong limits on estimators, bias correction methods, and inference procedures, and provides motivation for considering other criteria for evaluating estimators and inference procedures, such as local asymptotic minimaxity and one‐sided quantile unbiasedness.     

自然科学知识的积累对电子元器件产业发展的影响

假设研究活动存在与产品生命周期中的市场扩大现象相似的活跃化现象,按照时间序列对电子元器件领域的评审论文篇数和注册专利件数的增减情况进行了分析。由分析结果可知:在市场真正产生前,评审论文篇数和注册专利件数剧增;同时,在这些剧增的论文和专利中,有很多研究给商品化和商业化带来了巨大影响。这些与商品化和商业化有关的信息,不仅包括对产品制造业有用的信息,而且还包括对支撑产品制造业的设备产业同样有用的信息。因此,将本分析法作为考量新事业进入机会的客观方法推荐给大家。     

COLLATERAL CONSTRAINTS AND THE CURRENT ACCOUNT: THEORY AND EVIDENCE

We investigate the impact of domestic financial frictions on the current account dynamics in Asian countries before and after the Asian financial crisis in 1997–1998 by introducing collateral constraints into the intertemporal current account approach. We examine six Asian countries. Before the crisis, collateral constraints significantly impact the current account in Korea, Malaysia, the Philippines, and Thailand, but after the crisis, they do not. Our study shows that the impact of domestic financial frictions on the current account changes before and after a financial crisis. (JEL F32, F41)     

Inter- and intraspecific interactions among larvae of specialist and generalist parasitoids

Intra- and interspecific larval interactions that take place in a host body were investigated for two tachnid fliesEpicampocera succincta andCompsilura concinnata (Diptera: Tachinidae) parasitizingPieris butterfly larvae.E. succincta, a specialist onPieris butterflies, showed contest-type intraspecific competition, eliminating all the other conspecific larvae. On the other hand, an extreme generalist parasitoidC. concinnata exhibited scramble-type competition, sharing the host with other conspecifics and suffering reduced body size as a result. However, when these two species occurred together in a single host,C. concinnata had a much higher chance of survival. Moreover,C. concinnata could often survive in the presence of a parasitoid waspCotesia glomerata (Hymenoptera: Braconidae) whileE. succincta could not. The high tolerance ofC. concinnata could be attributable to its being an extreme generalist: To attack and survive on many different hosts, one has to be able to deal with various competitors. The competitive inferiority of the specialistE. succincta, on the other hand, may be a result of relatively recent encounter with, those competitors.     

Statistical Modeling of Fire Occurrence Using Data from the Tōhoku,Japan Earthquake and Tsunami

In this article, we develop statistical models to predict the number and geographic distribution of fires caused by earthquake ground motion and tsunami inundation in Japan. Using new, uniquely large, and consistent data sets from the 2011 Tōhoku earthquake and tsunami, we fitted three types of models—generalized linear models (GLMs), generalized additive models (GAMs), and boosted regression trees (BRTs). This is the first time the latter two have been used in this application. A simple conceptual framework guided identification of candidate covariates. Models were then compared based on their out‐of‐sample predictive power, goodness of fit to the data, ease of implementation, and relative importance of the framework concepts. For the ground motion data set, we recommend a Poisson GAM; for the tsunami data set, a negative binomial (NB) GLM or NB GAM. The best models generate out‐of‐sample predictions of the total number of ignitions in the region within one or two. Prefecture‐level prediction errors average approximately three. All models demonstrate predictive power far superior to four from the literature that were also tested. A nonlinear relationship is apparent between ignitions and ground motion, so for GLMs, which assume a linear response‐covariate relationship, instrumental intensity was the preferred ground motion covariate because it captures part of that nonlinearity. Measures of commercial exposure were preferred over measures of residential exposure for both ground motion and tsunami ignition models. This may vary in other regions, but nevertheless highlights the value of testing alternative measures for each concept. Models with the best predictive power included two or three covariates.