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Abstract
There is a large variation across countries of origin in the gender composition of migrants coming to Germany. We argue that women's economic rights in developing countries of origin have three effects on their migration prospects to a place like Germany that is far away and difficult to reach. First, the lower are women's economic rights the fewer women have access to and control over the resources needed to migrate to Germany. Second, the lower are the rights the lower is women's agency to make or otherwise influence migration decisions. These two constraining effects on the female share in migrant populations dominate the opposing third effect that stems from low levels of women's economic rights generating a potentially powerful push factor. We find corroborating evidence in our analysis of the gender composition of migration to Germany over the period 2009–2017.

AbstractThis article evaluates the reliability of sensitivity tests. Using Monte Carlo methods we show that, first, the definition of robustness exerts a large influence on the robustness of variables. Second and more importantly, our results also demonstrate that inferences based on sensitivity tests are most likely to be valid if determinants and confounders are almost uncorrelated and if the variables included in the true model exert a strong influence on outcomes. Third, no definition of robustness reliably avoids both false positives and false negatives. We find that for a wide variety of data-generating processes, rarely used definitions of robustness perform better than the frequently used model averaging rule suggested by Sala-i-Martin. Fourth, our results also suggest that Leamer's extreme bounds analysis and Bayesian model averaging are extremely unlikely to generate false positives. Thus, if based on these inferential criteria a variable is robust, it is almost certain to belong into the empirical model. Fifth and finally, we also show that researchers should avoid drawing inferences based on lack of robustness.

Objectives: We examined the effects of market income inequality (income inequality before taxes and transfers) and income redistribution via taxes and transfers on inequality in longevity. Methods: We used life tables to compute Gini coefficients of longevity inequality for all individuals and for individuals who survived to at least 10 years of age. We regressed longevity inequality on market income inequality and income redistribution, and we controlled for potential confounders, in a cross-sectional time-series sample of up to 28 predominantly Western developed countries and up to 37 years (1974-2011). Results: Income inequality before taxes and transfers was positively associated with inequality in the number of years lived; income redistribution (the difference between market income inequality and income inequality after taxes and transfers were accounted for) was negatively associated with longevity inequality. Conclusions. To the extent that our estimated effects derived from observational data are causal, governments can reduce longevity inequality not only via public health policies, but also via their influence on market income inequality and the redistribution of incomes from the relatively rich to the relatively poor.

In spatial econometrics,Wrefers to the matrix that weights the value of the spatially lagged variable of other units. As unimportant as it may appear,Wspecifies, or at least ought to specify, why and how other units of analysis affect the unit under observation. This article shows that theory must inform five crucial specification choices taken by researchers. Specifically, the connectivity variable employed inWmust capture the causal mechanism of spatial dependence. The specification ofWfurther determines the relative relevance of source units from which spatial dependence emanates, and whether receiving units are assumed to be identically or differentially exposed to spatial stimulus. Multiple dimensions of spatial dependence can be modeled as independent, substitutive or conditional links. Finally, spatial effects need not go exclusively in one direction, but can be bi-directional; recipients can simultaneously experience positive spatial dependence from some sources and negative dependence from others. The importance ofWstands in stark contrast to applied researchers' typical use of crude proxy variables (such as geographical proximity) to measure true connectivity, and the practice of adopting standard modeling conventions rather than substantive theory to specifyW. This study demonstrates which assumptions these conventions impose on specification choices, and argues that theories of spatial dependence will often conflict with them.

We revisit the old and well-established theory of free-riding in military alliances. Existing empirical evidence infers free-riding from the larger military expenditures per gross domestic product (GDP) of countries of larger GDP. Yet, larger countries have broader military and geostrategic interests that result in larger defense burdens, thus creating an identification problem for existing tests of free-riding behavior. We therefore develop alternative predictions that ignore differences in the level of military spending and instead relate to growth in spending over time. The safety level of smaller members of an alliance is affected, simultaneously, by changes to military spending of the largest alliance member as well as by spending changes of the main enemy. Using the North Atlantic Treaty Organization (NATO) as test case, we estimate country-specific response functions of the smaller alliance members to growth in US military spending on the one hand and to growth of Soviet spending (if in excess of US growth) on the other, covering the period 1956–1988. Results from our quasi-spatial approach corroborate one part of the theory in that we find the vast majority of the smaller NATO allies to be free-riders. However, our empirical evidence flatly contradicts the other part of the free-riding theory: the extent of free-riding is not a function of country size. Smaller allies free-ride, but the relatively larger of the smaller allies do not free-ride any less than the relatively even smaller alliance partners.

In this commentary, we make the case that the analysis of terrorism and counterterrorism must be based on an integrated theory that links both issues together. Terrorist groups' ultimate goals must be distinguished from their strategic goals and the strategic logic by which they employ terror and select targets to further their ultimate goals. The strategic logic of terrorism is thus key to understanding patterns of terrorism and the counter-reaction by governments against it. We make the case for a unified approach and suggest major areas for future research.(International Interactions (London)/ FUB)