On Long-Run Monetary Neutrality in Japan

This paper comprehensively investigates long-run monetary neutrality in Japan, with due consideration to the order of integration of the money stock and real output, mainly using long-term time-series data retroactively available from the Meiji Period (1868-1912). The empirical results indicate little evidence against the long-run neutrality of money (especially defined as M2) with respect to real GNP. In addition, such findings are robust to a wide range of identifying assumptions.

A Posteriori Probabilistic Bounds of Convex Scenario Programs with Validation Tests

Scenario programs have established themselves as efficient tools towards decision-making under uncertainty. To assess the quality of scenario-based solutions a posteriori, validation tests based on Bernoulli trials have been widely adopted in practice. However, to reach a theoretically reliable judgement of risk, one typically needs to collect massive validation samples. In this work, we propose new a posteriori bounds for convex scenario programs with validation tests, which are dependent on both realizations of support constraints and performance on out-of-sample validation data. The proposed bounds enjoy wide generality in that many existing theoretical results can be incorporated as particular cases. To facilitate practical use, a systematic approach for parameterizing a posteriori probability bounds is also developed, which is shown to possess a variety of desirable properties allowing for easy implementations and clear interpretations. By synthesizing comprehensive information about support constraints and validation tests, improved risk evaluation can be achieved for randomized solutions in comparison with existing a posteriori bounds. Case studies on controller design of aircraft lateral motion are presented to validate the effectiveness of the proposed a posteriori bounds

The reliability, validity, and accuracy of self-reported absenteeism from work: a meta-analysis

Because of a variety of access limitations, self-reported absenteeism from work is often employed in research concerning health, organizational behavior, and economics, and it is ubiquitous in large scale population surveys in these domains. Several well established cognitive and social-motivational biases suggest that self-reports of absence will exhibit convergent validity with records-based measures but that people will tend to underreport the behavior. We used meta-analysis to summarize the reliability, validity, and accuracy of absence self-reports. The results suggested that self-reports of absenteeism offer adequate test–retest reliability and that they exhibit reasonably good rank order convergence with organizational records. However, people have a decided tendency to underreport their absenteeism, although such underreporting has decreased over time. Also, self-reports were more accurate when sickness absence rather than absence for any reason was probed. It is concluded that self-reported absenteeism might serve as a valid measure in some correlational research designs. However, when accurate knowledge of absolute absenteeism levels is essential, the tendency to underreport could result in flawed policy decisions

Evolution of statistical analysis in empirical software engineering research: Current state and steps forward

Software engineering research is evolving and papers are increasingly based on empirical data from a multitude of sources, using statistical tests to determine if and to what degree empirical evidence supports their hypotheses. To investigate the practices and trends of statistical analysis in empirical software engineering (ESE), this paper presents a review of a large pool of papers from top-ranked software engineering journals. First, we manually reviewed 161 papers and in the second phase of our method, we conducted a more extensive semi-automatic classification of papers spanning the years 2001--2015 and 5,196 papers. Results from both review steps was used to: i) identify and analyze the predominant practices in ESE (e.g., using t-test or ANOVA), as well as relevant trends in usage of specific statistical methods (e.g., nonparametric tests and effect size measures) and, ii) develop a conceptual model for a statistical analysis workflow with suggestions on how to apply different statistical methods as well as guidelines to avoid pitfalls. Lastly, we confirm existing claims that current ESE practices lack a standard to report practical significance of results. We illustrate how practical significance can be discussed in terms of both the statistical analysis and in the practitioner's context.Comment: journal submission, 34 pages, 8 figure

Perceived Environmental Supportiveness Scale: Portuguese Translation, Validation and Adaptation to the Physical Education Domain

Aim: Grounded on Self-Determination Theory, this study aimed to translate, adapt and validate the Perceived Environmental Supportiveness Scale (PESS) in a sample of Portuguese physical education students. Methods: The global sample was comprised of 964 students (518 females), divided in two groups: the calibration (n = 469) and the validation one (n = 483), all of them enrolled in two Physical Education (PE) classes/week. Results: The analysis provided support for a one factor and 12 items model, which are in line with the values adopted in the methodology (χ² = 196.123, df = 54, p = <.001, SRMR = .035, NNFI = .943, CFI = .954, RMSEA = .074, 90% CI .063-.085). Results express that the models are invariant in all analysis (i.e., calibration vs. validation, male vs. female,and 3rd vs. secondary cycle; three and single factor models). Conclusion: The present study suggests that the PESS with one factor and 12 items has good psychometric properties and can be used to assess perceived need supportive motivational environments provided by PE teachers. Additionally, invariance analysis showed support for the use of the scale in both genders and in the 3rd and secondary cycles.info:eu-repo/semantics/publishedVersio

Reimagining the General Health Questionnaire as a measure of emotional wellbeing: A study of postpartum women in Malta

Background: Postpartum health has been subject to a focus on psychological morbidity, despite positive associations between postpartum recovery and maternal emotional wellbeing. There are currently many validated tools to measure wellbeing and related concepts, including non-psychiatric morbidity. The General Health Questionnaire, 12 items (GHQ-12) is one such instrument, widely used and validated in several languages. Its use in postpartum settings has been documented with disagreement about the instrument's utility in this population, particularly in relation to scoring method and threshold. The GHQ-12 has never been translated into Maltese. This study explored the psychometric properties of the GHQ-12 in a Maltese postpartum population to consider if the use of a different scoring method (visual analogue scale) in the GHQ-12 can determine postpartum wellbeing. Methods: One hundred and twenty-four postpartum women recruited from one hospital in Malta completed the translated and adapted GHQ-12 as a wellbeing measure (GHQ-12(WB)) at four postpartum time points. The psychometric properties of the GHQ-12(WB) were explored using confirmatory factor analysis, discriminant and divergent validity and reliability analysis. Results: The GHQ-12(WB) demonstrated good divergent and known-groups validity and internal consistency. No models offered a good fit to the data. The overall consistent best-fit to the data was an eight item, two factor model (GHQ-8). Model fit improved across all models in terms of CFI at 13 weeks. Conclusion: Findings generally support the reliability and validity of the Maltese version of the GHQ-12(WB). Model fit changes over time reflect the dynamic nature of postpartum recovery. Further evaluation of the GHQ-8(WB) is recommended. © 2013 Australian College of Midwives