Statistical Distributions of Daily Breathing Rates for Narrow Age Groups of Infants and Children

Children may be more susceptible to toxicity from some environmental chemicals than adults. This susceptibility may occur during narrow age periods (windows), which can last from days to years depending on the toxicant. Breathing rates specific to narrow age periods are useful to assess inhalation dose during suspected windows of susceptibility. Because existing breathing rates used in risk assessment are typically for broad age ranges or are based on data not representative of the population, we derived daily breathing rates for narrow age ranges of children designed to be more representative of the current U.S. children's population. These rates were derived using the metabolic conversion method of Layton (1993) and energy intake data adjusted to represent the U.S. population from a relatively recent dietary survey (CSFII 1994–1996, 1998). We calculated conversion factors more specific to children than those previously used. Both nonnormalized (L/day) and normalized (L/kg-day) breathing rates were derived and found comparable to rates derived using energy estimates that are accurate for the individuals sampled but not representative of the population. Estimates of breathing rate variability within a population can be used with stochastic techniques to characterize the range of risk in the population from inhalation exposures. For each age and age-gender group, we present the mean, standard error of the mean, percentiles (50th, 90th, and 95th), geometric mean, standard deviation, 95th percentile, and best-fit parametric models of the breathing rate distributions. The standard errors characterize uncertainty in the parameter estimate, while the percentiles describe the combined interindividual and intra-individual variability of the sampled population. These breathing rates can be used for risk assessment of subchronic and chronic inhalation exposures of narrow age groups of children.     

A semi-parametric approach to robust parameter design

Parameter design or robust parameter design (RPD) is an engineering methodology intended as a cost-effective approach for improving the quality of products and processes. The goal of parameter design is to choose the levels of the control variables that optimize a defined quality characteristic. An essential component of RPD involves the assumption of well estimated models for the process mean and variance. Traditionally, the modeling of the mean and variance has been done parametrically. It is often the case, particularly when modeling the variance, that nonparametric techniques are more appropriate due to the nature of the curvature in the underlying function. Most response surface experiments involve sparse data. In sparse data situations with unusual curvature in the underlying function, nonparametric techniques often result in estimates with problematic variation whereas their parametric counterparts may result in estimates with problematic bias. We propose the use of semi-parametric modeling within the robust design setting, combining parametric and nonparametric functions to improve the quality of both mean and variance model estimation. The proposed method will be illustrated with an example and simulations.     

Refined Inference on Long Memory in Realized Volatility

There is an emerging consensus in empirical finance that realized volatility series typically display long range dependence with a memory parameter (d) around 0.4 (Andersen et al., 2001; Martens et al., 2004). The present article provides some illustrative analysis of how long memory may arise from the accumulative process underlying realized volatility. The article also uses results in Lieberman and Phillips (2004, 2005) to refine statistical inference about d by higher order theory. Standard asymptotic theory has an O(n^-1/2) error rate for error rejection probabilities, and the theory used here refines the approximation to an error rate of o(n^-1/2). The new formula is independent of unknown parameters, is simple to calculate and user-friendly. The method is applied to test whether the reported long memory parameter estimates of Andersen et al. (2001) and Martens et al. (2004) differ significantly from the lower boundary (d = 0.5) of nonstationary long memory, and generally confirms earlier findings.     

Intersensory Redundancy Enhances Memory in Bobwhite Quail Embryos

Information presented concurrently and redundantly to 2 or more senses (intersensory redundancy) has been shown to recruit attention and promote perceptual learning of amodal stimulus properties in animal embryos and human infants. This study examined whether the facilitative effect of intersensory redundancy also extends to the domain of memory. We assessed bobwhite quail chicks' ability to remember and prefer an individual maternal call presented either unimodally or redundantly and synchronously with patterned light during the period prior to hatching. Embryos provided with unimodal auditory exposure failed to prefer the familiar call over a novel maternal call postnatally at 48 hr and 72 hr following exposure. In contrast, embryos provided with redundant, synchronous audiovisual stimulation significantly preferred the familiar call at 48 hr following exposure, but not at 72 hr. A second experiment provided chicks with a single 10‐min refamiliarization with the familiar call at either 48 hr or 72 hr following hatching. Chicks given only unimodal auditory exposure prior to hatching did not appear to benefit from this brief postnatal refamiliarization, showing no preference for the familiar call at either 72 or 96 hr. Chicks that received redundant audiovisual stimulation prenatally showed a significant preference for the familiar call (following the brief reexpo sure 24 hr earlier) at both 72 and 96 hr of age. These results are the first to demonstrate that redundantly specified information is remembered longer and reactivated more easily than the same information presented unimodally. These findings provide further evidence of the salience of intersensory redundancy in guiding selective attention and perceptual learning during early development.     

Automobile prices and protection: The U.S.-Japan trade restraint

We examine the effects of the U.S.-Japan trade restraint on automobile prices and quality upgrading, for both Japanese imports and American small cars. From April 1981 to April 1984 the suggested retail price of all Japanese models increased by 15.8 percent, or 5.3 percent per year. We find that nearly the entire amount of this rise can be explained by the upgrading of individual models. This upgrading may benefit consumers who would purchase a luxury import in any case, but harms those who desire the basic imports. In addition to upgrading, we conclude that a second cost of the trade restraint has been to prevent the yen depreciation from being passed onto American consumers, in terms of lower imported auto prices. For U.S. small cars we find a 9.1 percent rise in the suggested retail price, or 3 percent per year, with a fraction of this amount due to model upgrading. If the yen depreciation had led to lower import prices without the trade restraint, then we expect that U.S. auto prices would have been lower, too.     

On the Evolution of Competitive Balance: The Impact of an Increasing Global Search

The Coase theorem maintains that where free-market precepts exist, the allocation of property rights does not impact the distribution of resources. An application to Major League Baseball suggests that institutions such as free agency and the reverse-order amateur draft would not impact player distributions and therefore would not impact competitive balance. The present study finds that the distribution of wins is generally consistent with the precepts of the Coase theorem and therefore suggests a course for those who wish to alter the level of competitive balance: Major League Baseball should increase its focus on expanding the size of its labor pool. (JEL O15 , L83 , C22 )     

Expectations, Capital Gains, and Income

A theoretical framework for the measurement of income under uncertainty is developed that addresses some long-standing controversies about the treatment of capital gains. The consequences for economic analysis and policy making are potentially serious, because the treatment of capital gains can significantly affect some major macroeconomic aggregates, including national income and savings, balance of payments deficits, government deficits, and depreciation. (JEL O47 , P44 , Q32 )