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  • and It should be remembered that the hypothesis

    2018-11-15

    and It should be remembered that the hypothesis to be tested is: the risk of criminal victimization increases as the spending rises, but it reaches a maximum level from which the risk drops as spending levels increase. This hypothesis will not be rejected if coefficients and in the two models specified above are statistically significant and have positive and negative signs, respectively. Moreover, maximum spending should remain within the interval of the data analysis. For both types of theft/robbery, the figures for minimum and maximum spending are, respectively, 6 and 7000 reals. Expectations about the signs of the other coefficients in the model expressed in Eqs. (7) and (8) are compared with empirical evidence in Section 5. Except for the proxy for observed wealth, expectations for the other variables are limited to the patterns identified in the descriptive analyses presented in the next section. This is so because apart from the fact that there is no well-structured theoretical model to guide expectations, it is almost impossible to identify the syk inhibitor through which these control variables influence the risk of victimization, as they are determinants, to a greater or lesser degree, of the factors that hypothetically have a bearing on the risk of criminal victimization, described in Section 2. Table 1 shows the names, definitions, means, and standard deviations of the variables.
    Preliminary analyses For household thefts/robberies, we see that 5.1% of individuals were victimized once in the one-year interval considered in the surveys; 1.0% were victimized twice and 0.5% were victimized at least three times. For crimes of theft/robbery of persons, the percentages were, 6.8%, 1.2%, and 0.4%, respectively (Table 2). The low frequency of individuals who were victimized more than once during the period covered by the surveys made it impossible to develop a robust modelling of the determinants of repeat victimization through the estimation of count models as made, for instance, by Ybarra and Lohr (2002) and Carvalho and Lavor (2008). Nevertheless, for the sole purpose of visualizing patterns in the data, apart from calculating certain statistics conditional on victimization, we calculated other conditionals on the number of victimizations involving the same type of crime during the period covered by the surveys. Tables 3 and 4 show the frequency of victimization and repeat victimization, respectively, conditional on the categories of qualitative control variables. As for the average age of individuals, a clear pattern was detected both for victimizations and repeat victimizations (Tables 5 and 6). Regardless of the type of crime, the average age of victimized individuals is lower than the average age of non-victimized ones. The difference is more pronounced for theft/robbery of persons, whose victims are about 5.8 years younger than non-victimized individuals in average. Because this difference is relatively large, it is suspected that younger individuals are more exposed to the risk of having something stolen/being robbed outside syk inhibitor the home. This suspicion grows stronger when one observes the behavior of age averages according to the number of victimizations and sees that the average age is lower as the number of times that individuals are victimized increases. As regards spending, the proxy for wealth observed by criminals, it can be seen that the mean of this variable is higher among victimized individuals than among non-victimized ones. It can be observed that this difference is more pronounced among victims and non-victims of theft/robbery of persons (Table 5). Specifically, in the case of repeat victimization to household theft/robbery, it can be observed that the average spending is higher in the group of individuals who were victimized twice than in that of individuals who were victimized once and that it is higher in the group of individuals who were victimized at least three times than in the group of those who were victimized twice. However, for theft/robbery of persons, a clear pattern can be observed between spending and repeat victimization (Table 6). The differences observed in average spending among groups of victimized and non-victimized individuals might indicate that wealth, proxied by spending, is one of the determinants of the risk of property victimization.