Residents’ Reactions to Earthquake Early Warnings in Japan

This article empirically examines the effectiveness of earthquake early warning (EEW) in Japan based on experiences of residents who received warnings before earthquake shaking occurred. In Study 1, a survey (N = 299) was conducted to investigate residents’ experiences of, and reactions to, an EEW issued in Gunma and neighboring regions on June 17, 2018. The main results were as follows. (1) People's primary reactions to the EEW were mental, not physical, and thus motionless. Most residents stayed still, not for safety reasons, but because they were focusing on mentally bracing themselves. (2) Residents perceived the EEW to be effective because it enabled them to mentally prepare, rather than take physical protective actions, before strong shaking arrived. (3) In future, residents anticipate that on receipt of an EEW they would undertake mental preparation as opposed to physical protective actions. In Study 2, a survey (N = 450) was conducted on another EEW issued for an earthquake offshore of Chiba Prefecture on July 7, 2018. Results were in line with those of Study 1, suggesting that the findings described above are robust. Finally, given people's lack of impetus to undertake protective action on receipt of an EEW, this article discusses ways to enhance such actions.     

Central Bank Macroeconomic Forecasting During the Global Financial Crisis: The European Central Bank and Federal Reserve Bank of New York Experiences

This article documents macroeconomic forecasting during the global financial crisis by two key central banks: the European Central Bank and the Federal Reserve Bank of New York. The article is the result of a collaborative effort between staff at the two institutions, allowing us to study the time-stamped forecasts as they were made throughout the crisis. The analysis does not exclusively focus on point forecast performance. It also examines methodological contributions, including how financial market data could have been incorporated into the forecasting process.     

For Bourdieu, Against Alexander: Reality and Reduction

Jeffrey Alexander argues that despite Bourdieu's considerable achievements ultimately his work is reductionist and determinist. He further argues that though Bourdieu is a middle range theorist he is implicitly realist in his meta-theoretical assumptions. This article accepts these conclusions but argues that Bourdieu's meta-theoretical realism is a virtue rather than a vice and that the manner in which he is a reductionist and determinist necessitate a re-thinking of what is meant by these notions. Alexander uses Bourdieu's concept of habitus to demon-strate a fundamental contradiction in Bourdieu's theorising. According to him habitus presents us with the oxymoron of unconscious strategisation. This article uses a discussion of habitus in order to demonstrate that in its relationship with the concept of field it instead produces a practical resolution of long standing theoretical problems concerning structural determination and human agency. It is also argued that these problems are resolved at the meta-theoretical level in the form of critical realist ontology and that it is Alexander's misunderstandings on this level which cause him to fail to appreciate the significance of Bourdieu's achievements.     

A Behavioral Look at the Training of Alex: A Review of Pepperberg’s The Alex Studies: Cognitive and Communicative Abilities of Grey Parrots

The Analysis of Verbal Behavior - The Alex Studies: Cognitive and Communicative Abilities of Grey Parrots by Irene Pepperberg is reviewed from a behavior analytic orientation. The results of the...     

SERVICES OUTSOURCING AND INNOVATION: AN EMPIRICAL INVESTIGATION

We provide a comprehensive empirical analysis of the links between international services outsourcing, domestic outsourcing, profits, and innovation using plant‐level data. We find a positive effect of international outsourcing of services on innovative activity at the plant level. Such a positive effect can also be observed for domestic outsourcing, but the magnitude is smaller. We also find that international services outsourcing has a positive effect on profitability, as predicted by theory, whereas this is not true for domestic sourcing. The results are robust to various specifications and an instrumental variables analysis. (JEL F19, O31)     

Review of Literature on Media Literacy

Media literacy is a topic that has attracted a wide variety of scholars as well as non‐scholars. This review begins with an analysis of how media literacy has been defined by the range of contributors to the huge and growing literature on media literacy. The review then lays out the big picture concerning media literacy interventions as well as how media literacy has been regarded within the institution of public education. The review concludes with a series of recommendations about conceptualizations, research, and instruction.     

Mapping the Timing,Pace, and Scale of the Fertility Transition in Brazil

Between 1960 and 2000, fertility fell sharply in Brazil, but this transition was unevenly distributed in space and time. Using Bayesian spatial statistical methods and microdata from five censuses, we develop and apply a procedure for fitting logistic curves to the fertility transitions in more than 500 small regions of Brazil over this 40‐year period. Doing so enables us to map the main features of the Brazilian fertility transition in considerable detail. We detect early declines in some regions of the country and document large differences between early and late transitions in regard to both the initial level of fertility and the speed of the transition. We also use our results to test hypotheses regarding changes in the level of development at the onset of the fertility transition and identify a temporary stall in the Brazilian transition that occurred in the late 1990s. A web site with project details is at http://schmert.net/BayesLogistic .     

ESTIMATING WITHIN-SCHOOL CONTACT NETWORKS TO UNDERSTAND INFLUENZA TRANSMISSION

Many epidemic models approximate social contact behavior by assuming random mixing within mixing groups (e.g., homes, schools, and workplaces). The effect of more realistic social network structure on estimates of epidemic parameters is an open area of exploration. We develop a detailed statistical model to estimate the social contact network within a high school using friendship network data and a survey of contact behavior. Our contact network model includes classroom structure, longer durations of contacts to friends than non-friends and more frequent contacts with friends, based on reports in the contact survey. We performed simulation studies to explore which network structures are relevant to influenza transmission. These studies yield two key findings. First, we found that the friendship network structure important to the transmission process can be adequately represented by a dyad-independent exponential random graph model (ERGM). This means that individual-level sampled data is sufficient to characterize the entire friendship network. Second, we found that contact behavior was adequately represented by a static rather than dynamic contact network. We then compare a targeted antiviral prophylaxis intervention strategy and a grade closure intervention strategy under random mixing and network-based mixing. We find that random mixing overestimates the effect of targeted antiviral prophylaxis on the probability of an epidemic when the probability of transmission in 10 minutes of contact is less than 0.004 and underestimates it when this transmission probability is greater than 0.004. We found the same pattern for the final size of an epidemic, with a threshold transmission probability of 0.005. We also find random mixing overestimates the effect of a grade closure intervention on the probability of an epidemic and final size for all transmission probabilities. Our findings have implications for policy recommendations based on models assuming random mixing, and can inform further development of network-based models.     

Estimation for High‐Dimensional Linear Mixed‐Effects Models Using ℓ1‐Penalization

Abstract. We propose an ?₁‐penalized estimation procedure for high‐dimensional linear mixed‐effects models. The models are useful whenever there is a grouping structure among high‐dimensional observations, that is, for clustered data. We prove a consistency and an oracle optimality result and we develop an algorithm with provable numerical convergence. Furthermore, we demonstrate the performance of the method on simulated and a real high‐dimensional data set.