Suicide and unemployment in Japan: Evidence from municipal level suicide rates and age-specific suicide rates

Most previous studies on the relationship between unemployment and suicide use either individual level data or large unit aggregate level data. The former typically fail to distinguish the observed association from the causal link, and the latter often produce inconsistent findings on the unemployment-suicide relationship, making it difficult to draw policy implications. The present study contributes to this line of research by using two semi-aggregate level data in Japan. The results show that unemployment is significantly associated with male suicide rates, especially those of prime age working men, while the results are not straightforward for female suicide rates.     

New Classification of Research Misconduct from the Viewpoint of Truth,Trust, and Risk

ABSTRACT

Fabrication, Falsification and Plagiarism (FFP) and Questionable Research Practice (QRP) have been used worldwide in the classification of research misconduct. However, FFP comprises two distinct categories of misconduct: FF is extreme research misconduct that betrays truth, while P undermines trust of science community. Irreproducibility and inadequate practice of research also betray trust. Research misconduct has the potential to cause serious risk of safety in daily life. The proposed classification system is outlined as follows: Class I misconduct: Betrayal of the truth: (1) Fabrication and (2) Falsification. Class II misconduct: Betrayal of trust: (1) Plagiarism of text ; Irreproducibility; and (3) Inadequate research practice. Class III misconduct: Risk to safety of health and industrial products: (1) Risk to safety of health and (2) Risk to safety of industrial products. The proposed classification reflects deeper values of truth, trust, and risk more directly than the previous classification and elucidates issues about nature and significance of misconduct.     

Racial diversity,immigrants and the well-being of residents: evidence from US counties

This paper presents empirical evidence that racial diversity and immigrant population at the local level tend to be associated with lower life satisfaction for Whites by matching individual data with the county-level population data during the period 2005–2010. The magnitudes I find suggest that a ten-percentage-point increase in the share of the non-White population (approximately one half of a standard deviation) is associated with 0.006 and 0.007 points reduction in life satisfaction on a four-point scale for White men and White women, respectively. For White men, this effect appears to be driven by the percentage of the population that is Black. I also find that a ten-percentage-point increase in the percentage of the immigrant population (approximately 2 standard deviations) is associated with 0.009 and 0.021 points reduction in life satisfaction for White men and White women, respectively. The percentage of the non-White population seems to reduce older Whites’ life satisfaction more than that of younger Whites. Though the scale of the findings relating to the impact of local racial compositions and immigrant population is relatively modest, the findings may pose a challenge in the coming years as the percentage of the population that is non-White rises in the USA.     

Risk Assessment of the Carbon Nanotube Group

This study assessed the health risks via inhalation and derived the occupational exposure limit (OEL) for the carbon nanotube (CNT) group rather than individual CNT material. We devised two methods: the integration of the intratracheal instillation (IT) data with the inhalation (IH) data, and the “biaxial approach.” A four‐week IH test and IT test were performed in rats exposed to representative materials to obtain the no observed adverse effect level, based on which the OEL was derived. We used the biaxial approach to conduct a relative toxicity assessment of six types of CNTs. An OEL of 0.03 mg/m³ was selected as the criterion for the CNT group. We proposed that the OEL be limited to 15 years. We adopted adaptive management, in which the values are reviewed whenever new data are obtained. The toxicity level was found to be correlated with the Brunauer‐Emmett‐Teller (BET)‐specific surface area (BET‐SSA) of CNT, suggesting the BET‐SSA to have potential for use in toxicity estimation. We used the published exposure data and measurement results of dustiness tests to compute the risk in relation to particle size at the workplace and showed that controlling micron‐sized respirable particles was of utmost importance. Our genotoxicity studies indicated that CNT did not directly interact with genetic materials. They supported the concept that, even if CNT is genotoxic, it is secondary genotoxicity mediated via a pathway of genotoxic damage resulting from oxidative DNA attack by free radicals generated during CNT‐elicited inflammation. Secondary genotoxicity appears to involve a threshold.     

The impact of jumps and leverage in forecasting covolatility

ABSTRACT

The paper investigates the impact of jumps in forecasting covolatility, accommodating leverage effects. We modify the preaveraged truncated covariance estimator of Koike (2016 Koike, Y. (2016). Estimation of integrated covariances in the simultaneous presence of non-synchronicity, microstructure noise and jumps. Econometric Theory 32:533–611.[Crossref], [Web of Science ®] , [Google Scholar]) such that the estimated matrix is positive definite. Using this approach, we can disentangle the estimates of the integrated covolatility matrix and jump variations from the quadratic covariation matrix. Empirical results for three stocks traded on the New York Stock Exchange indicate that the cojumps of two assets have a significant impact on future covolatility, but the impact is negligible for forecasting weekly and monthly horizons.     

Marital Dissolution and Formation for Interracial Couples: Evidence from Parents of Biracial Children

There is a large amount of literature on whether interracial relationships are more unstable than same-race relationships. This study utilizes data on the race of respondents’ children and examines how marital dissolution and formation differ for those who mate interracially. Contrary to several previous studies, this study finds that some interracial couples are more likely to proceed to marriage and have more stable marriage than same-race couples. White men with Asian biracial children are more likely to be married than other white male parents, black women with white biracial children are more likely to be married than other black female parents, and Asian women with white biracial children are more likely to get married (but more likely to get divorced or separated once married) than other Asian female parents.     

Asymmetric Multivariate Stochastic Volatility

This paper proposes and analyses two types of asymmetric multivariate stochastic volatility (SV) models, namely, (i) the SV with leverage (SV-L) model, which is based on the negative correlation between the innovations in the returns and volatility, and (ii) the SV with leverage and size effect (SV-LSE) model, which is based on the signs and magnitude of the returns. The paper derives the state space form for the logarithm of the squared returns, which follow the multivariate SV-L model, and develops estimation methods for the multivariate SV-L and SV-LSE models based on the Monte Carlo likelihood (MCL) approach. The empirical results show that the multivariate SV-LSE model fits the bivariate and trivariate returns of the S&P 500, the Nikkei 225, and the Hang Seng indexes with respect to AIC and BIC more accurately than does the multivariate SV-L model. Moreover, the empirical results suggest that the univariate models should be rejected in favor of their bivariate and trivariate counterparts.     

Asymmetric Multivariate Stochastic Volatility

This paper proposes and analyses two types of asymmetric multivariate stochastic volatility (SV) models, namely, (i) the SV with leverage (SV-L) model, which is based on the negative correlation between the innovations in the returns and volatility, and (ii) the SV with leverage and size effect (SV-LSE) model, which is based on the signs and magnitude of the returns. The paper derives the state space form for the logarithm of the squared returns, which follow the multivariate SV-L model, and develops estimation methods for the multivariate SV-L and SV-LSE models based on the Monte Carlo likelihood (MCL) approach. The empirical results show that the multivariate SV-LSE model fits the bivariate and trivariate returns of the S&P 500, the Nikkei 225, and the Hang Seng indexes with respect to AIC and BIC more accurately than does the multivariate SV-L model. Moreover, the empirical results suggest that the univariate models should be rejected in favor of their bivariate and trivariate counterparts.     

Covariate selection for estimating the causal effect of control plans by using causal diagrams

Summary. Consider a case where cause–effect relationships between variables can be described by a causal path diagram and the corresponding linear structural equation model. The paper proposes a graphical selection criterion for covariates to estimate the causal effect of a control plan. For designing the control plan, it is essential to determine both covariates that are used for control and covariates that are used for identification. The selection of covariates used for control is only constrained by the requirement that the covariates be non-descendants of a treatment variable. However, the selection of covariates used for identification is dependent on the selection of covariates used for control and is not unique. In the paper, the difference between covariates that are used for identification is evaluated on the basis of the asymptotic variance of the estimated causal effect of an effective control plan. Furthermore, the results can be also described in terms of a graph structure.     

Variance Estimators for Three "Probabilities of Causation"

This article introduces the definitions of three "probabilities of causation" suggested by Pearl (1999), which are used to evaluate the causal effect of an exposure on a disease in epidemiological studies. Pearl (1999) and Tian and Pearl (2000a, 2000b) provided identification formulas for three "probabilities of causation" from statistical data under some assumptions. In order to examine the estimation accuracy problem, this article derives variance estimators for three "probabilities of causation" correspondent to each case in Pearl (1999) and at the same time clarify their properties. In addition, we conduct simulation experiments and show that the proposed method can approximate sufficiently to the variance of "probabilities of causation." The results of this article provide a complete framework for using "probabilities of causation" effectively in order to analyze responsibility and susceptibility in epidemiological studies.