A Bayesian Time Series Model of Multiple Structural Changes in Level,Trend, and Variance

We investigate whether seasonal-adjustment procedures are, at least approximately, linear data transformations. This question was initially addressed by Young and is important with respect to many issues including estimation of regression models with seasonally adjusted data. We focus on the X-11 program and rely on simulation evidence, involving linear unobserved component autoregressive integrated moving average models. We define a set of properties for the adequacy of a linear approximation to a seasonal-adjustment filter. These properties are examined through statistical tests. Next, we study the effect of X-11 seasonal adjustment on regression statistics assessing the statistical significance of the relationship between economic variables. Several empirical results involving economic data are also reported.     

Testing for a Unit Root in a Time Series With a Changing Mean

This study considers testing for a unit root in a time series characterized by a structural change in its mean level. My approach follows the “intervention analysis” of Box and Tiao (1975) in the sense that I consider the change as being exogenous and as occurring at a known date. Standard unit-root tests are shown to be biased toward nonrejection of the hypothesis of a unit root when the full sample is used. Since tests using split sample regressions usually have low power, I design test statistics that allow the presence of a change in the mean of the series under both the null and alternative hypotheses. The limiting distribution of the statistics is derived and tabulated under the null hypothesis of a unit root. My analysis is illustrated by considering the behavior of various univariate time series for which the unit-root hypothesis has been advanced in the literature. This study complements that of Perron (1989), which considered time series with trends.     

On the Choice of Functional Forms: Summary of a Monte Carlo Experiment

The use of flexible functional forms is a standard practice in applied econometrics. Many flexible forms have been proposed. In this study, we investigate the behavior of three of them—the translog, the symmetric McFadden, and the symmetric generalized Barnett. Based on Monte Carlo experiments, we assess the ability of these forms to test theoretical properties and to measure technological characteristics.     

United but (un)equal: human capital,probability of divorce,and the marriage contract

This paper studies how the risk of divorce affects the human capital decisions of a young couple. We consider a setting where complete specialization is optimal with no divorce risk. Couples can self-insure through savings which offers some protection to the uneducated spouse, but at the expense of a distortion. Alternatively, for large divorce probabilities, symmetry in education, where both spouses receive an equal amount of education, may be optimal. This eliminates the risk associated with the lack of education, but reduces the efficiency of education choices. We show that the symmetric allocation will become more attractive as the probability of divorce increases, if risk aversion is high and/or labor supply elasticity is low. However, it is only a “second-best” solution as insurance protection is achieved at the expense of an efficiency loss. Finally, we study how the (economic) use of marriage is affected by the possibility of divorce.     

Toward Probabilistic Prediction of Flash Flood Human Impacts

This article focuses on conceptual and methodological developments allowing the integration of physical and social dynamics leading to model forecasts of circumstance‐specific human losses during a flash flood. To reach this objective, a random forest classifier is applied to assess the likelihood of fatality occurrence for a given circumstance as a function of representative indicators. Here, vehicle‐related circumstance is chosen as the literature indicates that most fatalities from flash flooding fall in this category. A database of flash flood events, with and without human losses from 2001 to 2011 in the United States, is supplemented with other variables describing the storm event, the spatial distribution of the sensitive characteristics of the exposed population, and built environment at the county level. The catastrophic flash floods of May 2015 in the states of Texas and Oklahoma are used as a case study to map the dynamics of the estimated probabilistic human risk on a daily scale. The results indicate the importance of time‐ and space‐dependent human vulnerability and risk assessment for short‐fuse flood events. The need for more systematic human impact data collection is also highlighted to advance impact‐based predictive models for flash flood casualties using machine‐learning approaches in the future.     

Bootstrapping mean‐squared errors of robust small‐area estimators: Application to the method‐of‐payments surveys data

This paper proposes a new bootstrap procedure for mean‐squared errors of robust small‐area estimators. We formally prove the asymptotic validity of the proposed bootstrap method and examine its finite‐sample performance through Monte Carlo simulations. The results show that our procedure performs well and competes with existing ones. We also provide an application to the estimation of the total volume and value of cash, debit card, and credit card transactions in Canada as well as in its provinces and subgroups of households. In particular, we found that there is a significant average annual decline rate of 3.1% in the volume of cash transactions and that this decline is relatively higher among high‐income households living in heavily populated provinces. Our bootstrap estimator also provides indicators of quality useful in selecting the best small‐area predictor among several alternatives in practice.     

Consumption Over the Life Cycle

This paper estimates a structural model of optimal life‐cycle consumption expenditures in the presence of realistic labor income uncertainty. We employ synthetic cohort techniques and Consumer Expenditure Survey data to construct average age‐profiles of consumption and income over the working lives of typical households across different education and occupation groups. The model fits the profiles quite well. In addition to providing reasonable estimates of the discount rate and risk aversion, we find that consumer behavior changes strikingly over the life cycle. Young consumers behave as buffer‐stock agents. Around age 40, the typical household starts accumulating liquid assets for retirement and its behavior mimics more closely that of a certainty equivalent consumer. Our methodology provides a natural decomposition of saving and wealth into its precautionary and life‐cycle components.     

Children’s Recognition and Discrimination of Fear and Disgust Facial Expressions

Facial expressions of fear and disgust have repeatedly been found to be less well recognized than those of other basic emotions by children. We undertook two studies in which we investigated the recognition and visual discrimination of these expressions in school-age children. In Study 1, children (5, 6, 9, and 10 years of age) were shown pairs of facial expressions, and asked to tell which one depicted a target emotion. The results indicated that accuracy in 9- and 10-year-olds was higher than in 5- and 6-year-olds for three contrasts: disgust–anger, fear–surprise, and fear–sadness. Younger children had more difficulty recognizing disgust when it was presented along with anger, and in recognizing fear when it was presented along with surprise. In Study 2, children (5, 6, 9, and 10 years of age) were shown a target expression along with two other expressions, and were asked to point to the expression that was the most similar to the target. Contrary to our expectations, even 5- and 6-year-olds were very accurate in discriminating fear and disgust from the other emotions, suggesting that visual perception was not the main limiting factor for the recognition of these emotions in school-age children.     

The Social Media Release as a public relations tool: Intentions to use among B2B bloggers

The Social Media Release (SMR) is emerging as a potentially powerful public relations tool in a world of social network media, particularly when targeted at influential bloggers. The research described here studies the factors that influence bloggers to use SMRs, using the Technology Acceptance Model as a theoretical framework, concentrating specifically on their perceptions of usefulness and ease of use.     

Key decisions in child protection services in cases of domestic violence: maintaining services and out‐of‐home placement

This paper looks at the response of the child protection services (CPS) system in cases where exposure to domestic violence occurs alone or together with abuse or neglect, focusing on the factors involved in decisions to maintain the case open for ongoing services or remove children from the home. The study is based on an analysis of clinical and administrative data from the files on children reported to a CPS agency in Montreal, Canada. A total of 1 071 substantiated reports were documented, including 337 cases of co‐occurrence (32%). Analysis of the data shows that domestic violence does not by itself constitute a factor liable to lead to more intrusive intervention. The CPS response appears to be influenced more by the existence of other forms of maltreatment and risk factors. Additionally, while domestic violence may be associated with more severe individual and family problems, it does not influence the decision to keep the case open because the child still need services. The lack of any connection between domestic violence and this decision is a cause for concern, as results indicate that such families need help. Knowing how to respond to their needs therefore remains a major challenge.