Smart and Dangerous: How Cognitive Skills Drive the
Intergenerational Transmission of Retaliation

Continual inter-gang violence exemplifies the degree to which retaliation is entrenched
in gang societies.  In fact, previous research shows that retaliatory acts actually help gangs
grow.  Furthermore, because mortality is high in gangs, their vitality also rests in
recruiting new members who believe in retaliation. This motivates the need to
understand how people develop an aggressive, retaliatory conflict resolution policy vs. a
more passive reconciliation stance.  I contribute a choice-theoretic model that explains
how cognitive skills drive the transmission of conflict resolution policies. A child’s
resolution policy depends on parental effort and the influence of the outside
environment.  The model has the implication that high-cognitive parents socialize
children to their conflict resolution culture more successfully than parents with low
cognitive skills. Indeed, I test the model using the cognitive skills and conflict resolution
skills of parents and children from the UK National Childhood Development Survey.  I
find that the parent's effort is reinforced by the prevalence of their conflict resolution
values in society. The data confirm that children of retaliating high-cognitive parents are
more likely to be socialized to that resolution culture than children of low-cognitive
retaliating parents when retaliation is more prominent in society. In relevant
socioeconomic contexts, parents who believe in forgiveness could deter the growth of
gangs by socializing children to reconciliation, which is incompatible with the retaliatory
gang ideology, thus reducing the pool of potential gang recruits.

Keywords: socioemotional skills, cultural transmission
Combining Bias Correction Methods:
Does Basing Indirect Inference on Han and Phillips
Yield Better Small Sample Results
?

I propose a new bias correction method for dynamic panel data models with fixed effects:
that of Indirect Inference (II) with the Han and Phillips bias-corrector (HP) as the base
estimator. I compare the performance of this new approach with that of several known
bias correction methods. The results are strong. The new estimator of the auto-regressive
coefficient outperforms both the HP bias corrector and Maximum Likelihood based II in
terms of bias reduction, while also exhibiting a significantly lower root mean square error.
The relative benefit of the new estimator increases for small N, T, and also increases as the
auto-regressive coefficient approaches 1.

Keywords: Bias reduction, Indirect Inference, Dynamic Panel

                                         
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