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The purpose of this article is to contribute to our stock of knowledge about who uses networks, how they are used, and what contribution the networks make to advancing the scientific enterprise. Between 1985 and 1990, the Survey of Income and Program Participation (SIPP) ACCESS data facility at the University of Wisconsin‐Madison provided social scientists in the United States and elsewhere with access through the electronic networks to complex and dynamic statistical data; the 1984 SIPP is a longitudinal panel survey designed to examine economic well‐being in the United States. This article describes the conceptual framework and design of SIPP ACCESS; examines how network users communicated with the SIPP ACCESS project staff about the SIPP data; and evaluates one outcome derived from the communications, the improvement of the quality of the SIPP data. The direct and indirect benefits to social scientists of electronic networks are discussed. The author concludes with a series of policy recommendations that link the assessment of our inadequate knowledge base for evaluating how electronic networks advance the scientific enterprise and the SIPP ACCESS research network experience to the policy initiatives of the High Performance Computing Act of 1991 (P.L. 102–194) and the related extensive recommendations embodied in Grand Challenges 1993 High Performance Computing and Communications (The FY 1993 U.S. Research and Development Program).

The “collaboratory” concept has recently entered the vernacular of the scientific community to reflect new modes of scientific communication, cooperation and collaboration made possible by information technology. The collaboratory represents a scientific research center “without walls” for accessing and sharing data, information, instrumentation and computational resources. The principal applications of the collaboratory concept have been in the physical and biological sciences, including space physics, oceanography and molecular biology. Discusses the attributes of the collaboratory, and applies the concept developed by computer and physical scientists to the design and operation of the SIPPACCESS prototype information system for complex data to be used through the Internet by sociologists, demographers and economists. Examines obstacles to collaboratory development for the social sciences. Concludes that four major obstacles will inhibit the development of collaboratories in the social sciences.

Responses to minimum income and minimum spending questions are used to produce economic well-being thresholds. Thresholds are estimated using a regression framework. Regression coefficients are based on U.S. Survey of Income and Program Participation (SIPP) data and then applied to U.S. Consumer Expenditure Survey (CE) data. Three different resource measures are compared to the estimated thresholds. The first resource measure is total before-tax money income, and the other two are expenditure based. The first of these two refers to expenditure outlays and the second to outlays adjusted for the value of the service flow of owner-occupied housing (rental equivalence). The income comparison is based on SIPP data while the outlays comparisons are based on CE data. Results using official poverty thresholds are shown for comparison. This is among the earliest work in the U.S. in which expenditure outlays have been used for economic well-being determinations in combination with personal assessments, and the first time rental equivalence has been used in such an exercise. Comparisons of expenditures for various bundles of commodities are compared to the CE derived thresholds to provide insight concerning what might be considered minimum or basic.

Results reveal that CE and SIPP MIQ thresholds are higher than MSQ thresholds, and resulting poverty rates are also higher with the MIQ. CE-based MSQ thresholds are not statistically different from average expenditure outlays for food, apparel, and shelter and utilities for primary residences. When reported rental equivalences for primary residences that are owner occupied are substituted for out-of-pocket shelter expenditures, single elderly are less likely to be as badly off as they would be with a strict outlays approach in defining resources.

The purpose of this paper is to develop an enhanced framework for workforce management in a modern call center environment, called the consecutive staffing using simulation (CSS) approach. The paper aims to investigate the value of a time‐dependent approach to determine staffing levels without making an assumption that call centers to be a queuing model in a steady state.

Staffing is usually accomplished through the use of simple queuing models, Erlang‐C (M/M/c). It is common to adopt a stationary independent period by period (SIPP) approach. However, staffing based on SIPP does not consider uncompleted calls and each planning interval cannot achieve a steady state in most cases, since the lengths of planning intervals are short in fact. In this context, the CSS approach considers uncompleted calls and determines staffing levels by using simulation.

Staffing based on the CSS approach needed fewer agents, compared with staffing based on the SIPP approach. Hiring less agents during a single planning horizon lead to a decrease in total operational costs for the call center. Staffing based on SIPP became less accurate when the average service duration became longer or the arrival rate fluctuation was large, which often occurred in the morning and around lunch break.

The CSS approach is based on the dynamic staffing proposed by Whitt. However, CSS extends the basic idea of dynamic staffing to combine a simulation experiment with a number of repetitions and the same run length of planning intervals. In a call center with shorter planning intervals, management should adopt staffing based on CSS for accurate planning and updating of staffing levels during a single planning horizon.

This paper examines several measures of poverty and hardship for the United States to illustrate how a single measure of poverty may identify different groups of people as “in need.” Individuals and families may encounter difficulty meeting needs on many dimensions and there are a variety of measures designed to identify those who experience poverty or difficulty making ends meet. In general, there is agreement that all of the approaches capture different pieces of the puzzle while no single indicator can yield a complete picture. To understand this multidimensional aspect of poverty, several measures are examined in this paper: the official U.S. poverty measure, a relative poverty measure, a new supplemental measure that follows recommendations of the U.S. National Academy of Sciences (NAS), an index of material hardship, a measure of household debt, and responses to a question about inability to meet expenses. This study uses the 2008 panel of the Survey of Income and Program Participation (SIPP) and updates a similar analysis that used the 1996 panel of SIPP (Short, 2005). The SIPP is a longitudinal survey that allows us to examine all of these various indicators for the same people over the period from 2009 to 2010. The study uses regression analysis to assess the relationship among several indicators of economic hardship. Results suggest that an understanding of relationships between various indicators can allow only one indicator of poverty alone to be interpreted more appropriately and used more wisely to target the needs of the disadvantaged.

A varying number of work hours from week to week creates considerable hardships for workers and their families, like volatile earnings and work–family conflict. Yet little empirical work has focused on racial/ethnic differences in varying work hours, which may have increased substantially in the Great Recession of the late 2000s. We extend literatures on racial/ethnic stratification in recessions and occupational segregation to this topic. Analyses of the Survey of Income and Program Participation show varying weekly hours became significantly more common for White and Black, but especially Latino workers in the late 2000s. The growth of varying weekly hours among White and Latino workers was greatest in predominantly minority occupations. However, the growth among Black workers was greatest in predominantly White occupations. The chapter discusses implications for disparities in varying hours and the salience of occupational composition beyond earnings.

We investigate the question of whether investing in a child’s development by having a parent stay at home when the child is young is correlated with the child’s adult outcomes. Specifically, do children with stay-at-home mothers have higher adult earnings than children raised in households with a working mother? The major contribution of our study is that, unlike previous studies, we have access to rich longitudinal data that allows us to measure both the parental earnings when the child is very young and the adult earnings of the child. Our findings are consistent with previous studies that show insignificant differences between children raised by stay-at-home mothers during their early years and children with mothers working in the market. We find no impact of maternal employment during the first five years of a child’s life on earnings, employment, or mobility measures of either sons or daughters. We do find, however, that maternal employment during children’s high school years is correlated with a higher probability of employment as adults for daughters and a higher correlation between parent and daughter earnings ranks.

Data from the 1984 Survey of Income and Program Participation are linked to longitudinal records from the Social Security Administration to examine the relationship between the long-term unemployment that prime-aged (ages 25–55) male workers experienced around the time of the 1980–1982 twin recessions with earnings, receipt of either Disability Insurance or Supplemental Security Income (DI-SSI) benefits, and mortality. Separate estimations are made for those who voluntarily and involuntarily left employment and the combined sample of these two groups. We find that 20 years later, long-term joblessness was associated with significantly lower earnings and higher likelihoods of the receipt of DI-SSI benefits as well as mortality.

Using data from the Survey of Income and Program Participation (SIPP) matched to administrative records, we examine mortality risk and participation in the Disability Insurance (DI) and Supplemental Security Income (SSI) disability programs from a long-term perspective. Over a period of 14 years, we analyze the effect of self-reported health and disability on the probability of death and disability program entry among individuals aged 18–48 in 1984. We also assess DI and SSI programs from a life-cycle perspective. Self-reported poor health and severe disability at baseline are strongly correlated with death over the 14-year follow-up period. These variables also are strong predictors of disability program participation over the follow-up period among non-participants at baseline or before, with increasing marginal probabilities in the out-years. Our cross-sectional models are consistent with recent studies that find that the work-prevented measure is useful in modeling DI entry. However, once self-reported health and functional limitations are accounted for, the longitudinal entry models provide conflicting DI results for the work-prevented measure, suggesting that, contrary to claims based on cross-sectional or short-time horizon application models, the work-prevented measure is an unreliable indicator of severity. The risk of SSI and DI participation is significantly greater for individuals who die, suggesting that future mortality captures the effect of case severity and deterioration of health during the follow-up period. From a life-cycle perspective, a substantially greater proportion of individuals participate in SSI or DI at some point in their lives compared to typical cross-sectional estimates of participation, especially among minorities, people with less than a high school education, and those with early onset of poor health and/or disabilities. Cross-sectional estimates for the Social Security area population indicate SSI and DI participation rates of no more than 5% combined in 2000. In contrast, for individuals aged 43–48 in 1984, we observe a cumulative lifetime SSI and/or DI participation rate of 14%. The corresponding figure is 32% for individuals in that age group who did not graduate from high school, suggesting the need for human capital investments and/or improved work incentives.

This article raises five questions: What kinds of persons and families are poor? How do they become poor? How long do they remain poor? How do they cope with being poor? How do they escape from being poor? These questions are significant for one central and obvious reason: answering them improves our understanding of the nature of poverty or unmet human physical need, thereby contributing to the development of forms of aid to remedy that need. To the extent that we are successful in helping the needy, our social economics is enhanced, and any economic order based on that social economics should function more effectively. Two main sources of information on poverty from the Census Bureau are used to address those questions: the Current Population Survey and the Survey of Income and Program Participation. Both use the same absolute standard of poverty but each source produces a different estimate of poverty because they are fundamentally different in design and coverage. The data presented herein cover the period 1985 through 1993.