In recent decades, various cities in Sweden have implemented school closures as a desegregation strategy. Using simulation models calibrated with administrative data for all primary and lower secondary schools in Stockholm, Sweden, we assess the potential impact of school closure on ethnic school segregation. More specifically, we study how the characteristics of the school to be closed, the local opportunity structure for the displaced students, and the student reallocation criteria influence the effects of school closures on school segregation. Our findings show that the change in ethnic school segregation is highly dependent on reallocation criteria and local opportunity structures. Moreover, they demonstrate that the current practices associated with school closures in large urban areas (i.e., closing minority-dominated schools in minority-dominated neighborhoods) are likely to be ineffective in reducing school segregation, especially when students are reallocated to their nearest school or to schools whose composition resembles that of their former schools.

This article presents an analysis of the relationship between kin propinquity, residential mobility, and the persistence of segregation among ancestry groups living in Stockholm, Sweden. Residential segregation between Swedish and non-Swed­ish­ ances­try­ groups­ is­ established­ when­ immi­grants­ first­ set­tle­ in­ Stockholm, which creates disparities in the spatial distribution of kin for the children of immigrants compared with their Swedish counterparts. Using agent-­based models, we show how pref­er­ences­ to ­live­ near­ kin­ are­suf­fi­cient­ to ­main­tain­ existing­ seg­re­ga­tion­ but­ are­ not suf­fi­cient­ to­ gen­er­ate­ it.­We ­then apply­ dis­crete­ choice­ mod­els­ of ­res­id­en­tial­ mobil­ity to longitudinal residential history data from Swedish population registers to estimate the­ effects­ of­ kin­ on­ the­ neigh­bor­hood­ choices­ of­ mov­ers,­ ages­ 18‒30,­ dur­ing­ the 1998‒2017­ period.­ We­ find­ that­ peo­ple­ are­ more­ likely­ to­ move­ to­ neigh­bor­hoods that are near to kin, net of controls for sorting by ancestry, socioeconomic status, and life course characteristics. Counterfactual simulations of residential mobility show that kin propinquity contributes to higher levels of segregation between Swedish and non-Swed­ish­ ances­try­ groups.­These­ effects­ are larger­ for­ groups­ already­ expe­ri­enc­ing high­ lev­els­ of­ seg­re­ga­tion­ from­ the­ Swed­ish major­ity.­We­ sit­ua­te­ these­ find­ings­ in­ the emerging literature on social structural sorting.

Previous studies investigating how the school choice paradigm shapes school segregation have found that students' ethnic school preferences drive school segregation by leading students to rank and change current schools following ethnic homophily orientations. This study investigates an intermediate moment in which these preferences contribute to the exacerbation of school segregation: students changing schools after being allocated to following admission rules but before the start of the academic year. We refer to these changes as micro-changes. Using Swedish register data on 9th-grade students applying to upper secondary education in Stockholm schools, this study evaluates how micro-changes affect school segregation. Our findings reveal that micro-changes are not neutral and increase school segregation levels because (1) students tend to reject of schools with a low share of in-group members and low representation of 9th-grade classmates, and (2) micro-changers move into schools with a high share of in-group members and 9th-grade classmates. Furthermore, our simulation model shows that micro-changes impact on school segregation have a cumulative effect.

Although previous studies have investigated the contribution of several components of the school choice paradigm to school segregation, one critical aspect has not received attention from segregation scholars: schools priority rules, that is, the rules schools apply in case of oversubscription. We evaluate how three priority rules - grade-based, distance-based, and random-based - shape school segregation. Using Swedish register data on students applications to upper secondary education in Stockholm, Sweden, we assess the effect of these priority rules from two counterfactual frameworks. One uses actual students rank-ordered lists, and the other relies on a large-scale simulation framework. We show that grade-based and distance-based priorities produce higher levels of segregation than random-based priorities through different mechanisms. Our results hold, even when we control for students school preferences and residential segregation.

There are many theories that account for why households move between residential areas.In this paper, we advance on this by formulating a new mechanism whereby a household’sprobability of leaving a neighborhood is informed by the number of other households whohave previously left that neighborhood. We call this mechanism: the social influence (SI)effect. By applying matching to Swedish register data for Stockholm County (1998–2017),and after adjusting for theoretically relevant confounders from the existing literature, we findthat SI has a significant effect on neighborhood out-mobility. Furthermore, we find that theSI effect is moderated by the visibility with which others’ behaviors is observed, measuredas the number of previous out-movers, the distance to ego, and its salience in the socialenvironment. Our study also discusses some ways in which SI might be entangled withother mechanisms, and outlines future directions from which studies of residential segregation dynamics might be approached. 

The study of tax behavior is a research field which attracts increasing interest in social and behavioral sciences. Rational choice models have been traditionally used to account for that behavior, but they face the puzzle of explaining levels of observed tax compliance which are much higher than expected. Several social influence mechanisms have been proposed in order to tackle this problem. In this article, we discuss the interdisciplinary literature on this topic, and we claim that agent-based models are a promising tool in order to test theories and hypothesise in this field. To illustrate that claim, we present SIMULFIS, an agent-based model for the simulation of tax compliance that allows to combine rational choice with social influence mechanisms in order to generate aggregated patterns of tax behavior. We present and discuss the results of a simple virtual experiment in order to show the potentialities of the model.

In this paper, we present a new agent-based model for the simulation of tax compliance and tax evasion behavior (SIMULFIS). The main novelties of the model are the introduction of a "behavioral filter approach" to model tax decisions, the combination of a set of different mechanisms to produce tax compliance (namely rational choice, normative commitments and social influence), and the use of the concept of "fraud opportunity use rate" (FOUR) as the main behavioral outcome. After describing the model in detail, we display the main behavioral and economic results of 1,920 simulations calibrated for the Spanish case and designed to test for the internal validity of SIMULFIS. The behavioral outcomes show that scenarios with strict rational agents strongly overestimate tax evasion, while the introduction of social influence and normative commitments allows to generate more plausible compliance levels under certain deterrence conditions. Interestingly, the relative effect of social influence is shown to be ambivalent: it optimizes compliance under low and middle deterrence conditions, but not when deterrence is made harder. Finally, SIMULFIS economic outcomes are broadly in line with theoretical expectations, thus supporting the reliability of the model.