Welfare Reform and Teenage Pregnancy,Childbirth, and School Dropout

This study estimates the effect of welfare reform on adolescent behaviors using a difference‐in‐differences approach. After defining the prereform and reform cohorts and considering the life course development of adolescent behavior by following each cohort from age 14 to age 16, we compare the welfare‐target and nontarget populations in the two cohorts. The difference‐in‐differences estimates are obtained using an event history model. Our analysis suggests that welfare reform has not reduced teenage fertility and school dropout. We find modest evidence that welfare reform is associated with higher risk of teenage births for girls in welfare families and higher risk of school dropout for girls in poor families. A combination of a difference‐in‐differences approach and a life course perspective can be a useful way to delineate the effect of societal‐level change on family phenomena.     

The Value of Life: Estimates with Risks by Occupation and Industry

The worker fatality risk variable constructed for this article uses BLS data on total worker deaths by both occupation and industry over the 1992–97 period rather than death risks by occupation or industry alone, as in past studies. The subsequent estimates using 1997 CPS data indicate a value of life of $4.7 million for the full sample, $7.0 million for blue-collar males, and $8.5 million for blue-collar females. Unlike previous estimates, these values account for the influence of clustering of the job risk variable and compensating differentials for both workers' compensation and nonfatal job risks.     

THE INFLUENCE OF RISK VARIABLE DEFINITION ON VALUE-OF-LIFE ESTIMATES

Empirical "value-of-life" estimates derived from labor market wage-risk premiums have varied widely. This paper examines the influence of risk variable definition on these estimates. Value-of-life estimates are derived for one sample from a set of several risk measures. The analysis reveals that the risk variable definition can markedly affect the value-of-life estimate. Further, the paradoxical pattern of "high" estimates from industry risk data and "low" estimates from occupation data is shown to be attributable to different risk definition, not differences in the characterization of risk faced by a given sample of works. Finally, by associating consistently low estimates with one particular risk variable this study suggests much more uniformity in the value-of-life estimates than previously believed.     

REGRESSION WITH MISSING YS: AN IMPROVED STRATEGY FOR ANALYZING MULTIPLY IMPUTED DATA

When fitting a generalized linear model—such as linear regression, logistic regression, or hierarchical linear modeling—analysts often wonder how to handle missing values of the dependent variable Y . If missing values have been filled in using multiple imputation, the usual advice is to use the imputed Y values in analysis. We show, however, that using imputed Y s can add needless noise to the estimates. Better estimates can usually be obtained using a modified strategy that we call multiple imputation, then deletion (MID). Under MID, all cases are used for imputation but, following imputation, cases with imputed Y values are excluded from the analysis. When there is something wrong with the imputed Y values, MID protects the estimates from the problematic imputations. And when the imputed Y values are acceptable, MID usually offers somewhat more efficient estimates than an ordinary MI strategy.     

Evaluating strategies to avoid AIDS: Number of partners vs. use of condoms

A probability model based on the best estimates we have today for prevalence and infectivity of Human Immunodeficiency Virus (HIV) has been developed. The model is used to compare the two most widely publicized risk reduction strategies: (1) Reducing the number of partners and (2) Using condoms. The results indicate that under almost all conditions of prevalence and infectivity, consistent and careful condom use is a far more effective method of reducing the risk of HIV infection. The analysis is applied to both high and low prevalence groups. In order to test more rigorously the conclusions, infectivity rates ten times higher than now estimated are examined, and infectivity is estimated on a per partner, as well as a per sexual act basis. Epidemic growth of prevalence is estimated to further check our findings. None of these conditions alters our basic conclusion. It is suggested that there is reluctance to publicize such findings about AIDS because they may be used to support having multiple sexual partners. Nevertheless, it is assumed to be more important to protect ourselves from infection than to sustain norms opposed to multiple sexual partners. Thus, our results may prove extremely useful to those who give advice to people concerning risk reduction strategies.     

HOW TO IMPUTE INTERACTIONS, SQUARES, AND OTHER TRANSFORMED VARIABLES

Researchers often carry out regression analysis using data that have missing values. Missing values can be filled in using multiple imputation, but imputation is tricky if the regression includes interactions, squares, or other transformations of the regressors. In this paper, we examine different approaches to imputing transformed variables; and we find one simple method that works well across a variety of circumstances. Our recommendation is to transform, then impute —i.e., calculate the interactions or squares in the incomplete data and then impute these transformations like any other variable. The transform-then-impute method yields good regression estimates, even though the imputed values are often inconsistent with one another. It is tempting to try and "fix" the inconsistencies in the imputed values, but methods that do so lead to biased regression estimates. Such biased methods include the passive imputation strategy implemented by the popular ice command for Stata.     

Small networks and selectivity bias in the analysis of survey network data

Selectivity bias is a danger whenever observations are systematically excluded from a data set on the basis of a dependent variable, whether this exclusion is explicit or implicit. If present, the problem has severe consequences for the validity of statistical estimates of effects. The problem is of importance to the analysis of survey network data, since many network measures (such as density) are available only for persons having networks of size two or larger, while others (such as percent kin) are defined only for those having networks of size one or more. Analysts can adjust for selectivity bias by estimating the risk of exclusion (in this case, of having a network of size 0 or 1), and including the modeled risk as a control in substantive equations. Such estimates are presented for the 1985 General Social Survey network data; in the course of this results of Fischer and Phillips on social isolation are replicated. Other ways of guarding against selection bias are also discussed; at a minimum, network size should be included among the set of regressors in analyses of survey network data, as a methodological control if not as a substantive variable.     

Estimation of seroprevalence, rape, and homelessness in the United States using a social network approach

The authors have developed and tested scale-up methods, based on a simple social network theory, to estimate the size of hard-to-count subpopulations. The authors asked a nationally representative sample of respondents how many people they knew in a list of 32 subpopulations, including 29 subpopulations of known size and 3 of unknown size. Using these responses, the authors produced an effectively unbiased maximum likelihood estimate of the number of people each respondent knows. These estimates were then used to back-estimate the size of the three populations of unknown size. Maximum likelihood values and 95% confidence intervals are found for seroprevalence, 800,000 +/- 43,000; for homeless, 526,000 +/- 35,000; and for women raped in the last 12 months, 194,000 +/- 21,000. The estimate for seroprevalence agrees strikingly with medical estimates, the homeless estimate is well within the published estimates, and the authors' estimate lies in the middle of the published range for rape victims.     

Children's exposure to paternal imprisonment: Incidence, evolution, and correlates among young nonmarital children

Although the well-being of nonmarital children has been the focus of recent public policy developments and academic research, relatively little is known about the risk of paternal imprisonment among these children. Particularly in a context of declining public assistance, the unprecedented imprisonment rate may place additional stress on nonmarital children if a substantial portion of their fathers are incarcerated and therefore unable to provide support. Research on this topic has been impeded by methodological difficulties, such as the lack of representative data on nonmarital children's fathers, and inaccurate or insufficient information on fathers' incarceration. Using unique combined administrative data sets from Wisconsin that largely overcome these methodological obstacles, I provide improved estimates of paternal imprisonment risk among young nonmarital children. I distinguish between point-in-time and cumulative risks and assess the length of paternal imprisonment, first considering only biological fathers and then also including the mothers' other partners. I also estimate the risks separately by socioeconomic and demographic characteristics. Results suggest that nonmarital children face a high risk of paternal imprisonment, a substantial proportion also face an elevated risk of lengthy paternal imprisonment, and the racial disparity in risk is significant.     

Evolution of Equity Market Risk During the Crisis: Europe, Americas and Asia

A set of regional and country??s equity indices have been evaluated and analysed in their Value at Risk (VaR) and Conditional Value at Risk (CVaR) in this paper, using computational methods based on the Johnson systems. Comparing the main statistics and the values of the two cited measures of financial risk obtained using a roll-over mechanism in the period January 2008?CJuly 2012, the impact of the crisis on equity market risk can be shown. It seems that for all regions and countries the patterns are very similar: there is a peak of all the risk measures adopted at the beginning of the crisis (September 2008?CFebruary 2009) and another turbulent period in 2011 (from July to December). In other terms, the global patterns of the main financially relevant countries and their regional aggregations demonstrate that ??One Financial system??, and just one, is already at work, in theory and in practice. On the other hand, the scale of the risk measures differs from one country to another: e.g., with a probability of 1?%, the potential daily loss on an equity position in Latin America in the worst period arrives to about 25?%, the Emerging Markets as a whole show values around 20?% and Asia arrives to 15?%, while the US and European corresponding values are below 14?%. This is true whatever the risk measure and whatever the confidence interval (which, again, influences strongly the scale of the risk values). Looking in detail to the last period (April 2012?CJuly 2012), a general improvement could be appreciated: the risk measures are all around 4?% if not on one hand Italy and Spain (around 6?%), Greece (around 10?%) and on the other hand the ??virtuous?? Chile (around 1.5?%), again with reference to a probability of 1?%. Nevertheless, indices of performance (expected return over risk measure) have been evaluated and compared. They give sometimes different answers to the risk measures themselves.     

ESTIMATION AND IMPACT OF GENDER DIFFERENCES IN RISK TOLERANCE

This paper provides numerical estimates of the distributions of risk tolerance for men and women. A simple model of individual portfolio choice is calibrated to data on Individual Retirement Accounts from the Health and Retirement Study to obtain the estimates. Results show that women tend to be less risk-tolerant than men. The estimates are then used to measure the impact of risk tolerance on wealth accumulation. Simulations show that the difference in risk tolerance can account for around 10% of the gender difference in accumulated wealth. ( JEL J16, G11, D81)     

Passive versus active parental permission in school-based survey research: does the type of permission affect prevalence estimates of risk behaviors?

This study investigates whether the type of parental permission affects prevalence estimates for risk behaviors from the national 2001 Youth Risk Behavior Survey. Participants were 13,195 students from 143 schools, of which 65% used passive permission and 35% active permission. Student participation rates were 86.7% in passive permission schools and 77.3% in active permission schools. For 24 of 26 behaviors tested, no significant differences were seen in the prevalence of risk behavior by type of parental permission. As long as high response rates are obtained, type of parental permission does not affect prevalence estimates for risk behaviors that are based on self-report.     

Sex,marital status,and suicide in Canada: 1951-1981

Data from Canada for the period 1951-1981 are used to analyze the influence of marital status on suicide. "Using a standardization procedure, it was discovered that a transition from single or widowed to married would entail a greater reduction in suicide risk for men than for women. In the case of a transition from divorced to married status, both sexes would benefit equally in reducing suicide potential. The analysis further demonstrates only weak support for the thesis that over time there would be a convergence in sex differences in the potential protective significance of marriage in reducing suicide risk."     

An overview of how sports, out-of-school time, and youth well-being can and do intersect

This article examines the benefits and disadvantages of participation in organized youth sports and describes a youth development approach to sports programming. The authors summarize what is known about the physical, socioemotional, and cognitive benefits of sports participation. These include health benefits (for example, a reduction in heart disease and diabetes) as well as socioemotional benefits, among them the coping skills of being able to bounce back from problems. The authors describe some of the disadvantages of participation as well. In particular, studies in this area have focused on health risk behaviors and engagement in problem behaviors. The authors present an innovative approach to youth sports and the advantages of implementing this approach using the emerging community youth development framework. Specific examples of youth sports programs are provided that use a positive youth development framework.     

LABOR'S SHARE,THE FIRM'S MARKET POWER,AND TOTAL FACTOR PRODUCTIVITY

We investigate the relationship between labor's share, firm's market power, and the elasticity of output with respect to labor input using an approach based on an unobserved components model. The approach yields time‐varying estimates of market power and the elasticity. Evidence on the market power of firms (which we find to be rising since 2000) gives a deeper understanding of movements in labor's share and the labor wedge. The generated values of the elasticity yield revised estimates of total factor productivity growth which is informative about the extent of the downward bias inherent in traditional estimates which use labor's share as a proxy for the elasticity. (JEL O47, C32, E25)     

Urban forest structure,ecosystem services and change in Syracuse,NY

The tree population within the City of Syracuse was assessed using a random sampling of plots in 1999, 2001 and 2009 to determine how the population and the ecosystem services these trees provide have changed over time. Ecosystem services and values for carbon sequestration, air pollution removal and changes in building energy use were derived using the i-Tree Eco model. In addition, photo interpretation of aerial images was used to determine changes in tree cover between the mid-1990s and 2009. Between the mid-1990s and 2003, tree cover in Syracuse exhibited a decline from 27.5 to 25.9 %, but subsequently increased to 26.9 % by 2009. The total tree population exhibited a similar pattern, dropping from 881,000 trees in 1999 to 862,000 in 2001, and then increasing to 1,087,000 trees in 2009. Most of this increase in the urban tree population is due to invasive or pioneer trees species, particularly Rhamnus cathartica, which has more than tripled in population between 2001 and 2009. Insects such as gypsy moth and emerald ash borer pose a substantial risk to altering future urban forest composition. The annual ecosystem services provided by the urban forest in relation to carbon sequestration, air pollution removal and reduction in building energy use are estimated at about $2.4 million per year. An improved understanding of urban forests and how they are changing can facilitate better management plans to sustain ecosystem services and desired forest structure for future generations.     

MENTAL ILLNESS AND THE DEMAND FOR ALCOHOL, COCAINE, AND CIGARETTES

This article estimates the effect of mental illness on demand for addictive substances, allowing for structural endogeneity and simultaneity between mental illness and addictive consumption. Results show that individuals with a history of mental illness are 26% more likely to consume alcohol, 66% more likely to consume cocaine, and 89% more likely to consume cigarettes. This high-participation group is also price-responsive, although their price elasticities differ somewhat from those without mental illness. The results provide added justification for higher taxes and supply reduction activities. Furthermore, subsidizing the treatment of mental illness can reduce addictive consumption.(JEL I1 )     

Comparing Networks Across Space and Time, Size and Species

We describe and illustrate methodology for comparing networks from diverse settings. Our empirical base consists of 42 networks from four kinds of species (humans, nonhuman primates, nonprimate mammals, and birds) and covering distinct types of relations such as influence, grooming, and agonistic encounters. The general problem is to determine whether networks are similarly structured despite their surface differences. The methodology we propose is generally applicable to the characterization and comparison of network–level social structures across multiple settings, such as different organizations, communities, or social groups, and to the examination of sources of variability in network structure. We first fit a p^* model (Wasserman and Pattison 1996) to each network to obtain estimates for effects of six structural properties on the probability of the graph. We then calculate predicted tie probabilities for each network, using both its own parameter estimates and the estimates from every other network in the collection. Comparison is based on the similarity between sets of predicted tie probabilities. We then use correspondence analysis to represent the similarities among all 42 networks and interpret the resulting configuration using information about the species and relations involved. Results show that similarities among the networks are due more to the kind of relation than to the kind of animal.