Immigration (Political science - International relations)

This entry discusses ‘immigration,’ which is the permanent movement of people across states, seen from the perspective of the receiving (rather than sending) states. The focus is on the relationship between immigration and states, a neglected topic in classic immigration research, but receiving more attention in recent scholarly literature. The entry discusses, in particular, some explanatory models of immigration policy and how the immigration experience has changed or reconfirmed the institution of citizenship.

PSHARE: Stata module to compute and graph percentile shares

-pshare- computes and graphs percentile shares from individual level data. Percentile shares are often used in inequality research to study the distribution of income or wealth. They are defined as differences between Lorenz ordinates of the outcome variable. Technically, the observations are sorted in increasing order of the outcome variable and the specified percentiles are computed from the running sum of the outcomes. Percentile shares are then computed as differences between percentiles, divided by total outcome. pshare requires moremata to be installed on the system; see ssc describe moremata.

A new Stata command for computing and graphing percentile shares

Percentile shares provide an intuitive and easy-to-understand way for analyzing income or wealth distributions. A celebrated example are the top income shares sported by the works of Thomas Piketty and colleagues. Moreover, series of percentile shares, defined as differences between Lorenz ordinates, can be used to visualize whole distributions or changes in distributions. In this talk, I present a new command called pshare that computes and graphs percentile shares (or changes in percentile shares) from individual level data. The command also provides confidence intervals and supports survey estimation.

A Validation Study on Voter Turnout Bias in Switzerland

Surveys on voting behavior typically overestimate turnout rates substantially. To disentangle different sources of bias - coverage error, nonresponse bias, and overreporting - we conducted a validation study in which respondents' self-reported voting behavior was compared to administrative voting records (N = 2000). Our results show that all three sources of error inflate the survey estimate of the turnout rate and also bias estimates from political participation models, although coverage error is only moderate compared to the more pronounced biases due to nonresponse and overreporting. Furthermore, results from a wording experiment do not provide evidence that revised wording reduces measurement bias.

Anticipatory and reactive forms of blame avoidance: of foxes and lions

Blame avoidance behavior (BAB) encompasses all kinds of integrity-protecting activities by officeholders in the face of potentially blame-attracting events. Although considered essential for a realistic understanding of politics and policymaking, a general understanding of this multi-faceted behavioral phenomenon and its implications has been lacking to date. We argue that this is due to the lack of careful conceptualization of various forms of BAB. Crucially, the difference between anticipatory and reactive forms of BAB is largely neglected in the literature. This paper links anticipatory and reactive forms of BAB as two consecutive decision situations. It exposes dependence relationships between the situations that trigger BAB, the rationalities at work, the resources and strategies applied by blame-avoiding actors, and the various consequences thereof. The paper concludes that anticipatory and reactive BAB are distinct phenomena that require specific research approaches to assess their relevance for the workings of polities.

Sozialer Status und Hup-Verhalten: Ein Feldexperiment zum Zusammenhang zwischen Status und Aggression im Strassenverkehr

Der Frage nach dem Zusammenhang zwischen sozialem Status und Aggressionsverhalten im Straßenverkehr wurde bereits verschiedentlich mit Hilfe des so genannten Hup-Experiments nachgegangen. Die Zeit, die vergeht, bis ein durch ein experimentelles Fahrzeug an der Weiterfahrt gehinderter Verkehrsteilnehmer die Hupe betätigt, wird dabei als (umgekehrt proportionaler) Indikator für das Ausmaß an geäußerter Aggression verwendet. Während bisherige Studien jeweils nur auf den blockierenden oder den blockierten Verkehrteilnehmer fokussierten, wird im vorliegenden Beitrag argumentiert, dass es sich um soziale Interaktionen handelt, in denen das Zusammenspiel der Eigenschaften beider Akteure für die unternommenen Handlungen von Bedeutung ist. Es werden Ergebnisse eines in der Schweiz durchgeführten Feldexperiments (N = 123) berichtet, die dafür sprechen, dass das Ausmaß an Aggression allgemein mit größerer sozialer Distanz zunimmt, und Aggression nicht, wie man aufgrund von Befunden zum Zusammenhang zwischen Status und Aggression in anderen Kontexten erwarten würde, vor allem gegenüber statustieferen Akteuren ausgedrückt wird.

Estimating Lorenz and concentration curves in Stata

Lorenz and concentration curves are widely used tools in inequality research. In this paper I present a new Stata command called -lorenz- that estimates Lorenz and concentration curves from individual-level data and, optionally, displays the results in a graph. The -lorenz- command supports relative as well as generalized, absolute, unnormalized, or custom-normalized Lorenz or concentration curves, and provides tools for computing contrasts between different subpopulations or outcome variables. Variance estimation for complex samples is fully supported.

More Is Not Always Better: An Experimental Individual-Level Validation of the Randomized Response Technique and the Crosswise Model

Social desirability and the fear of sanctions can deter survey respondents from responding truthfully to sensitive questions. Self-reports on norm breaking behavior such as shoplifting, non-voting, or tax evasion may therefore be subject to considerable misreporting. To mitigate such misreporting, various indirect techniques for asking sensitive questions, such as the randomized response technique (RRT), have been proposed in the literature. In our study, we evaluate the viability of several variants of the RRT, including the recently proposed crosswise-model RRT, by comparing respondents’ self-reports on cheating in dice games to actual cheating behavior, thereby distinguishing between false negatives (underreporting) and false positives (overreporting). The study has been implemented as an online survey on Amazon Mechanical Turk (N = 6,505). Our results indicate that the forced-response RRT and the unrelated-question RRT, as implemented in our survey, fail to reduce the level of misreporting compared to conventional direct questioning. For the crosswise-model RRT, we do observe a reduction of false negatives (that is, an increase in the proportion of cheaters who admit having cheated). At the same time, however, there is an increase in false positives (that is, an increase in non-cheaters who falsely admit having cheated). Overall, our findings suggest that none of the implemented sensitive questions techniques substantially outperforms direct questioning. Furthermore, our study demonstrates the importance of distinguishing false negatives and false positives when evaluating the validity of sensitive question techniques.

Benford's Law and Fraud Detection. Facts and Legends

Is Benford's law a good instrument to detect fraud in reports of statistical and scientific data? For a valid test the probability of "false positives" and "false negatives" has to be low. However, it is very doubtful whether the Benford distribution is an appropriate tool to discriminate between manipulated and non-manipulated estimates. Further research should focus more on the validity of the test and test results should be interpreted more carefully.

Sensitive Questions in Online Surveys: Experimental Results for the Randomized Response Technique (RRT) and the Unmatched Count Technique (UCT)

Gaining valid answers to so-called sensitive questions is an age-old problem in survey research. Various techniques have been developed to guarantee anonymity and minimize the respondent's feelings of jeopardy. Two such techniques are the randomized response technique (RRT) and the unmatched count technique (UCT). In this study we evaluate the effectiveness of different implementations of the RRT (using a forced-response design) in a computer-assisted setting and also compare the use of the RRT to that of the UCT. The techniques are evaluated according to various quality criteria, such as the prevalence estimates they provide, the ease of their use, and respondent trust in the techniques. Our results indicate that the RRTs are problematic with respect to several domains, such as the limited trust they inspire and non-response, and that the RRT estimates are unreliable due to a strong false "no" bias, especially for the more sensitive questions. The UCT, however, performed well compared to the RRTs on all the evaluated measures. The UCT estimates also had more face validity than the RRT estimates. We conclude that the UCT is a promising alternative to RRT in self-administered surveys and that future research should be directed towards evaluating and improving the technique.

Relative Distribution Methods in Stata

The concept of the relative density seems like a fruitful nonparametric approach to studying distributional differences between groups (Handcock and Morris 1999), yet it appears that the technique has gone more or less unnoticed in applied social science research. A scarcity of canned software might be one of the reasons the method is underutilized. Therefore, I present a new Stata command called reldist to plot the relative density, decompose distributional differences into location and shape effects, and compute relative distribution summary measures. The command is illustrated by an application comparing earnings by sex.

Online Reputation Systems and Cumulative Advantage

The study of online reputation systems and their importance for promoting trust and cooperation and, therefore, the smooth functioning of online markets has received considerable attention over the last few years. In the first part of our talk we will try to give a brief overview of the existing theoretical and empirical work in this field, summarize the main findings from this research and identify open questions where results are either controversial or do not yet exist. The second part of our talk will focus on one of these issues that deserve further research, namely the relation between online reputation systems and processes of "cumulative advantage." Cumulative advantage is the mechanism where a favorable relative position of having a good reputation becomes a resource for further relative gains. The process leads to increased status inequality and a heavily skewed distribution of number of feedbacks, i.e. the ties in the reputation network. We present empirical evidence for direct and indirect reputation effects on the micro level of an auction reputation system and discuss the distributional consequences for the market level.