Abstractions on steroids: A critical realist approach to computer simulations

Computer simulations are increasingly used within various fields of the social sciences, including analytical sociology and computational social science. However, the method has yet to fully find its place within critical realism, generally regarded as reductionist and methodological individualist and thus inadequate to the task of grasping the full and enigmatic complexity of social life. This article contributes to the discussion by suggesting an alternative approach to computer simulations in the social realm. Instead of representing reality, simulations are seen as a way of boosting abstraction by enabling us to isolate and study the effects of emergent mechanisms. The need for such tools is growing more urgent in an age characterized by rapid change and global networks of causal interrelation. Hence there is a need not only for new tools to deal with causal complexity within critical realism, but also for a critical realist perspective to fill the meta‐theoretical vacuum on which the simulation approach is largely based. The approach developed here provides a challenge to the predominant ways in which simulations are utilized today, with increasingly sophisticated models aiming towards realistic representation on the basis of empirical data.     

The Great Recession and Welfare State Reform: Is Retrenchment Really the Only Game Left in Town?

By 2010, when the Greek sovereign debt crisis changed into an existential crisis of the euro, all developed democracies entered a phase in which they had to consolidate their budgets, typically implying a politics of austerity. The scholarly literature, as well as the popular press, suggests that – consequently – welfare retrenchment and cost containment became the only games left in town. In this article, we study the welfare state reform measures taken between 2010 and 2012 in four countries characteristic of mature welfare state regimes (liberal, UK; conservative, Germany; social democratic, Denmark; and hybrid, the Netherlands) to examine empirically whether austerity has indeed become the only item left on the policy menu. Our analysis reveals that retrenchment features prominently on the agenda everywhere, but nowhere by itself. While compensation for income loss is rare since 2010, this still happens. More unexpectedly, reforms in line with a social investment agenda (like expansion of child care or active labour market policies) are still being pursued in all our four cases.     

Diverging Destinies: Maternal Education and the Developmental Gradient in Time With Children

Using data from the 2003?C2007 American Time Use Surveys (ATUS), we compare mothers?? (N = 6,640) time spent in four parenting activities across maternal education and child age subgroups. We test the hypothesis that highly educated mothers not only spend more time in active child care than less-educated mothers but also alter the composition of that time to suit children??s developmental needs more than less-educated mothers. Results support this hypothesis: not only do highly educated mothers invest more time in basic care and play when youngest children are infants or toddlers than when children are older, but differences across education groups in basic care and play time are largest among mothers with infants or toddlers; by contrast, highly educated mothers invest more time in management activities when children are 6 to 13?years old than when children are younger, and differences across education groups in management are largest among mothers with school-aged children. These patterns indicate that the education gradient in mothers?? time with children is characterized by a ??developmental gradient.??     

Performance Effects Related to the Sequence of Integration of Healthcare Technologies

There is a natural order to most events in life: Everything from learning to read to DNA sequences in molecular biology follows some predetermined, structured methodology that has been refined to yield improved results. Likewise, it would seem that firms could benefit by adopting and implementing technologies in some logical way so as to increase their overall performance. In this study of 555 hospitals, we investigate the order in which medical technologies are transformed into information technologies through a process of converting them from stand‐alone technologies to interoperable, integrated information systems and whether certain configurations of sequences of integration yield additional value. We find that sequence does matter and that hospitals that integrated foundational technologies first—which in this case are known to be more complex—tend to perform better. Theoretical and practical implications of this finding and others are discussed.     

Estimating the error distribution function in semiparametric additive regression models

We consider semiparametric additive regression models with a linear parametric part and a nonparametric part, both involving multivariate covariates. For the nonparametric part we assume two models. In the first, the regression function is unspecified and smooth; in the second, the regression function is additive with smooth components. Depending on the model, the regression curve is estimated by suitable least squares methods. The resulting residual-based empirical distribution function is shown to differ from the error-based empirical distribution function by an additive expression, up to a uniformly negligible remainder term. This result implies a functional central limit theorem for the residual-based empirical distribution function. It is used to test for normal errors.     

Revenue Management with End‐of‐Period Discounts in the Presence of Customer Learning

Consider a firm that sells identical products over a series of selling periods (e.g., weekly all‐inclusive vacations at the same resort). To stimulate demand and enhance revenue, in some periods, the firm may choose to offer a part of its available inventory at a discount. As customers learn to expect such discounts, a fraction may wait rather than purchase at a regular price. A problem the firm faces is how to incorporate this waiting and learning into its revenue management decisions. To address this problem we summarize two types of learning behaviors and propose a general model that allows for both stochastic consumer demand and stochastic waiting. For the case with two customer classes, we develop a novel solution approach to the resulting dynamic program. We then examine two simplified models, where either the demand or the waiting behavior are deterministic, and present the solution in a closed form. We extend the model to incorporate three customer classes and discuss the effects of overselling the capacity and bumping customers. Through numerical simulations we study the value of offering end‐of‐period deals optimally and analyze how this value changes under different consumer behavior and demand scenarios.     

Child care policy: A need for greater advocacy

While some scholars have recognized the importance of child care to families in the United States (Kamerman, 2001; Waldfogel, 1998), child care has not been viewed as a core social policy concern in the United States. In this article, we provide an overview of child care needs in the U.S. followed by an analysis of three major federal programs that shape U.S. child care policy. The first, the Child Care Development Fund (CCDF), provides financial child care supplements to low-income parents to enable them to engage in paid labor. The second policy, The Family Medical Leave Act (FMLA), is technically a universally applicable policy enabling people to care for a family member in need, including all parents who choose to spend a few weeks of unpaid leave with a newborn child. The third is the U.S. tax policy, including child care exemptions, deductions and credits. We suggest that, though all of these policies exist to help families care for children, they fail the children and families that they are purportedly designed to help. We then discuss the crucial role that professionals who work with families and children can play in shaping U.S. child care policies.     

Prediction in moving average processes

For the stationary invertible moving average process of order one with unknown innovation distribution F, we construct root-n   consistent plug-in estimators of conditional expectations E(h(_Xn+1)|_X1,…,_Xn)$E(h(X_{n+1})|X_1,\dots ,X_n)$. More specifically, we give weak conditions under which such estimators admit Bahadur-type representations, assuming some smoothness of h or of F. For fixed h it suffices that h   is locally of bounded variation and locally Lipschitz in _L2(F)$L_2(F)$, and that the convolution of h and F   is continuously differentiable. A uniform representation for the plug-in estimator of the conditional distribution function P(_Xn+1?·|_X1,…,_Xn)$P(X_{n+1}?·|X_1,\dots ,X_n)$ holds if F has a uniformly continuous density. For a smoothed version of our estimator, the Bahadur representation holds uniformly over each class of functions h that have an appropriate envelope and whose shifts are F-Donsker, assuming some smoothness of F. The proofs use empirical process arguments.     

A Factor Analysis Approach Toward Reconciling Community Vulnerability and Resilience Indices for Natural Hazards

The concepts of vulnerability and resilience help explain why natural hazards of similar type and magnitude can have disparate impacts on varying communities. Numerous frameworks have been developed to measure these concepts, but a clear and consistent method of comparing them is lacking. Here, we develop a data-driven approach for reconciling a popular class of frameworks known as vulnerability and resilience indices. In particular, we conduct an exploratory factor analysis on a comprehensive set of variables from established indices measuring community vulnerability and resilience at the U.S. county level. The resulting factor model suggests that 50 of the 130 analyzed variables effectively load onto five dimensions: wealth, poverty, agencies per capita, elderly populations, and non–English-speaking populations. Additionally, the factor structure establishes an objective and intuitive schema for relating the constituent elements of vulnerability and resilience indices, in turn affording researchers a flexible yet robust baseline for validating and expanding upon current approaches.