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      Religious Minorities and Resistance to Genocide: The Collective Rescue of Jews in the Netherlands during the Holocaust

      American Political Science Review
      Cambridge University Press (CUP)

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          Abstract

          This article hypothesizes that minority groups are more likely to protect persecuted groups during episodes of mass killing. The author builds a geocoded dataset of Jewish evasion and church communities in the Netherlands during the Holocaust to test this hypothesis. Spatial regression models of 93 percent of all Dutch Jews demonstrate a robust and positive correlation between the proximity to minority churches and evasion. While proximity to Catholic churches increased evasion in dominantly Protestant regions, proximity to Protestant churches had the same effect in Catholic parts of the country. Municipality level fixed effects and the concentric dispersion of Catholicism from missionary hotbed Delft are exploited to disentangle the effect of religious minority groups from local level tolerance and other omitted variables. This suggests that it is the local configuration of civil society that produces collective networks of assistance to threatened neighbors.

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          Religion, terrorism and public goods: Testing the club model

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            Location, Location, Location: An MCMC Approach to Modeling the Spatial Context of War and Peace

            This article demonstrates how spatially dependent data with a categorical response variable can be addressed in a statistical model. We introduce the idea of an autologistic model where the response for one observation is dependent on the value of the response among adjacent observations. The autologistic model has likelihood function that is mathematically intractable, since the observations are conditionally dependent upon one another. We review alternative techniques for estimating this model, with special emphasis on recent advances using Markov chain Monte Carlo (MCMC) techniques. We evaluate a highly simplified autologistic model of conflict where the likelihood of war involvement for each nation is conditional on the war involvement of proximate states. We estimate this autologistic model for a single year (1988) via maximum pseudolikelihood and MCMC maximum likelihood methods. Our results indicate that the autologistic model fits the data much better than an unconditional model and that the MCMC estimates generally dominate the pseudolikelihood estimates. The autologistic model generates predicted probabilities greater than 0.5 and has relatively good predictive abilities in an out-of-sample forecast for the subsequent decade (1989 to 1998), correctly identifying not only ongoing conflicts, but also new ones.
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              THE IMPORTANCE OF BEING ASKED

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                Author and article information

                Journal
                applab
                American Political Science Review
                Am Polit Sci Rev
                Cambridge University Press (CUP)
                0003-0554
                1537-5943
                February 2016
                March 2016
                : 110
                : 01
                : 127-147
                Article
                10.1017/S0003055415000544
                39369540-5b1d-4cec-be29-4897d056e616
                © 2016
                History

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