Demographic implications of the New United States certificates

To assist in developing uniform reporting of vital events among the fifty states, Puerto Rico, and the Virgin Islands, the United States government prepares standard certificates of birth, fetal death, death, marriage, and divorce. These model forms are revised, with the assistance of the states, approximately every ten years. Revisions are now being prepared by the National Center for Health Statistics which will become effective beginning January 1, 1968. Important new source material for demography will be introduced.Most changes will appear in the Standard Certificate of Live Birth and in the Standard Certificate of Fetal Death. An item on education of father and mother will provide detailed national data on education and fertility. The date of the last live birth to the mother and the date of the last fetal death will provide information on previous pregnancy outcome and on child-spacing. The recording of state file numbers for mates born alive and dead in the same delivery will make it easier to match live birth and fetal death certificates for the preparation of detailed tabulations on multiple births. Several new items related to maternal and child health have also been added. No significent changes were planned for the Standard Certificate of Death.The Standard Certificate of Marriage will include as new items the education of the bride and groom, the date on which the last marriage, if any, ended, and specification of the officiant as a religious or civil official. The Standard Certificate of Divorce or Annulment will obtain information on the education of husband and wife, the approximate date on which the couple separated, the mode of dissolution of the previous marriage, and the total number of living children. It is anticipated that most of the new items will be included in the certificates of all the states. The National Center for Health Statistics will provide detailed tabulations related to these items, beginning with data year 1968.Demographers are making an increased use of vital records and at the same time are extending their contacts with state health departments; in some states collaborative projects have been undertaken. Because of the importance of the source documents, which in some cases have not been exploited fully, demographers should increase their contact with the state vital statistics offices which develop, collect, and process the records. By indicating an interest in vital registration and by making their research needs known, demographers can encourage the acceptance of new concepts and collaborate in the improvement of vital records for demographic research purposes.     

Moving Average-Based Estimators of Integrated Variance

We examine moving average (MA) filters for estimating the integrated variance (IV) of a financial asset price in a framework where high-frequency price data are contaminated with market microstructure noise. We show that the sum of squared MA residuals must be scaled to enable a suitable estimator of IV. The scaled estimator is shown to be consistent, first-order efficient, and asymptotically Gaussian distributed about the integrated variance under restrictive assumptions. Under more plausible assumptions, such as time-varying volatility, the MA model is misspecified. This motivates an extensive simulation study of the merits of the MA-based estimator under misspecification. Specifically, we consider nonconstant volatility combined with rounding errors and various forms of dependence between the noise and efficient returns. We benchmark the scaled MA-based estimator to subsample and realized kernel estimators and find that the MA-based estimator performs well despite the misspecification.     

Being Under Pressure to Sext: Adolescents' Experiences,Reactions, and Counter-Strategies

This study explored adolescents' experiences of being under pressure to sext (sending nude images), offering insights into what situations adolescents view as pressuring, how adolescents react to the pressure, and what counter-strategies they use. Written statements from 225 adolescents (age 13–16 years, M = 14.4 years, SD = 0.93) were analyzed using thematic analysis. Results indicated a range of situations including both explicit and implicit pressure. The pressure elicited different emotional responses, including severe physical and psychological reactions, becoming distressed, and being seemingly unconcerned. A majority of the adolescents reported successful strategies on how to ward off the unwanted sexual requests. This study provides insight into how young people cope with potentially harmful situations online.     

Estimating the Nitrous Oxide Emission Rate from the Soil Surface by Means of a Diffusion Model

Soil cover methods are probably the most widely used methods for measuring the nitrous oxide emission rate from the soil surface. The methodology involves estimation of the emission rate from repeated measurements of the nitrous oxide concentration beneath a soil cover. Based on a deterministic model proposed by Hutchinson & Mosier (1981) we propose to use a diffusion process as a stochastic model for the evolution of the nitrous oxide concentrations beneath a soil cover. From this model we derive methods for statistical inference about the emission rate that significantly extend the method proposed by Hutchinson & Mosier (1981). In particular, the derived methods provide solutions to important problems with the method proposed by Hutchinson & Mosier (1981).     

Integer‐valued Trawl Processes: A Class of Stationary Infinitely Divisible Processes

This paper introduces a new continuous‐time framework for modelling serially correlated count and integer‐valued data. The key component in our new model is the class of integer‐valued trawl processes, which are serially correlated, stationary, infinitely divisible processes. We analyse the probabilistic properties of such processes in detail and, in addition, study volatility modulation and multivariate extensions within the new modelling framework. Moreover, we describe how the parameters of a trawl process can be estimated and obtain promising estimation results in our simulation study. Finally, we apply our new modelling framework to high‐frequency financial data.     

The local fractional bootstrap

We introduce a bootstrap procedure for high‐frequency statistics of Brownian semistationary processes. More specifically, we focus on a hypothesis test on the roughness of sample paths of Brownian semistationary processes, which uses an estimator based on a ratio of realized power variations. Our new resampling method, the local fractional bootstrap, relies on simulating an auxiliary fractional Brownian motion that mimics the fine properties of high‐frequency differences of the Brownian semistationary process under the null hypothesis. We prove the first‐order validity of the bootstrap method, and in simulations, we observe that the bootstrap‐based hypothesis test provides considerable finite‐sample improvements over an existing test that is based on a central limit theorem. This is important when studying the roughness properties of time series data. We illustrate this by applying the bootstrap method to two empirical data sets: We assess the roughness of a time series of high‐frequency asset prices and we test the validity of Kolmogorov's scaling law in atmospheric turbulence data.     

The Model Confidence Set

This paper introduces the model confidence set (MCS) and applies it to the selection of models. A MCS is a set of models that is constructed such that it will contain the best model with a given level of confidence. The MCS is in this sense analogous to a confidence interval for a parameter. The MCS acknowledges the limitations of the data, such that uninformative data yield a MCS with many models, whereas informative data yield a MCS with only a few models. The MCS procedure does not assume that a particular model is the true model; in fact, the MCS procedure can be used to compare more general objects, beyond the comparison of models. We apply the MCS procedure to two empirical problems. First, we revisit the inflation forecasting problem posed by Stock and Watson (1999), and compute the MCS for their set of inflation forecasts. Second, we compare a number of Taylor rule regressions and determine the MCS of the best regression in terms of in‐sample likelihood criteria.     

Moving Average-Based Estimators of Integrated Variance

We examine moving average (MA) filters for estimating the integrated variance (IV) of a financial asset price in a framework where high-frequency price data are contaminated with market microstructure noise. We show that the sum of squared MA residuals must be scaled to enable a suitable estimator of IV. The scaled estimator is shown to be consistent, first-order efficient, and asymptotically Gaussian distributed about the integrated variance under restrictive assumptions. Under more plausible assumptions, such as time-varying volatility, the MA model is misspecified. This motivates an extensive simulation study of the merits of the MA-based estimator under misspecification. Specifically, we consider nonconstant volatility combined with rounding errors and various forms of dependence between the noise and efficient returns. We benchmark the scaled MA-based estimator to subsample and realized kernel estimators and find that the MA-based estimator performs well despite the misspecification.