Receptive Grammatical Knowledge of Familiar Content Words and Inflection in 16‐Month‐Olds

This study examines 16‐month‐olds' understanding of word order and inflectional properties of familiar nouns and verbs. Infants preferred grammatical sentences over ungrammatical sentences when the ungrammaticality was cued by both misplaced inflection and word order reversal of nouns and verbs. Infants were also sensitive to inflection alone as a cue to grammaticality, but not word order alone. The preference for grammatical sentence forms was also disrupted when adjacent function word cues were removed from the stimuli, and when familiar content words were replaced by nonce words. These results suggest that sensitivity to the relationship between functional morphemes and content words, rather than sensitivity to either independently, drives the development of early grammatical knowledge. Furthermore, infants showed some ability to generalize from familiar to nonce content word contexts.     

A decomposition of trends in the nonmarital fertility ratios of blacks and whites in the united states, 1960–1992*

We use a method of standardization and decomposition developed by Das Gupta to update Smith and Cutright’s analysis of demographic factors responsible for increases in the nonmarital fertility ratio (illegitimacy ratio) among blacks and whites in the United States. We create standardized rates for each year between 1960 and 1992, and consistent, exhaustive decompositions of the nonmarital fertility ratio for any interval during this period in terms of four components: (1) the age distribution of women of reproductive age, (2) the proportion of women unmarried at each age, (3) the age-specific birth rates of married women, and (4) the age-specific birth rates of unmarried women. Nonmarital fertility ratios are much higher among blacks than among whites, but both increased monotonically from 1960 to 1992. During the last 10 years, each increased by nearly 10 percentage points. Increases in the proportion of women not married, at all ages, account for the preponderance of the increase in black nonmarital fertility ratios. Increasing rates of unmarried childbearing, however, have played a role during the most recent decade (1983–1992). For whites, from 1960 until 1975, declines in marital fertility were most important in producing increases in the proportion of children born out of wedlock. Since then, these proportions have increased primarily because of increases in unmarried women s birth rates, and secondarily because of declines in the proportion of women who are married. These trends are consistent with arguments that emphasize declining economic incentives to marry and reduced access to, and acceptability of, abortion.     

The Social Demography of Internet Dating in the United States*

Objective. The objective of this article is to identify the sociodemographic correlates of Internet dating net of selective processes that determine who is “at risk.” We also examine the role of computer literacy, social networks, and attitudes toward Internet dating among single Internet users. Methods. We use multivariate logistic regression to analyze 3,215 respondents from the first nationally representative U.S. survey of Internet dating. Results. Sociodemographic factors have strong effects on Internet access and single status but weak effects on use of Internet dating services once the sample is conditioned on these factors. For this “at‐risk” subpopulation, computer literacy and social networks strongly influence the likelihood of Internet dating. Conclusions. Internet dating is a common mate selection strategy among the highly selective subpopulation of single Internet users and may continue to grow through social networks. Material and virtual elements of the digital divide have direct and indirect effects on Internet dating.     

Cointegration: Bayesian Significance Test

To estimate causal relationships, time series econometricians must be aware of spurious correlation, a problem first mentioned by Yule (1926 Yule , G. U. ( 1926 ). Why we do sometimes get nonsense-correlations between time-series? A study in sampling and the nature of time-series (with discussion) . J. Roy. Statist. Soc. 89 : 1 – 64 .[Crossref] , [Google Scholar]). To deal with this problem, one can work either with differenced series or multivariate models: VAR (VEC or VECM) models. These models usually include at least one cointegration relation. Although the Bayesian literature on VAR/VEC is quite advanced, Bauwens et al. (1999 Bauwens , L. , Lubrano , M. , Richard , J.-F. ( 1999 ). Bayesian Inference in Dynamic Econometric Models . Oxford : Oxford University Press . [Google Scholar]) highlighted that “the topic of selecting the cointegrating rank has not yet given very useful and convincing results”.

The present article applies the Full Bayesian Significance Test (FBST), especially designed to deal with sharp hypotheses, to cointegration rank selection tests in VECM time series models. It shows the FBST implementation using both simulated and available (in the literature) data sets. As illustration, standard non informative priors are used.