262 N. Brooks J. of Economic Behavior Org. 44 2001 249–267
prefer to deviate. This equilibrium is stable so even if the distribution of returns improves, no individual will have an incentive to be cooperative. This results potentially limits the
effectiveness of income redistribution implied by the first two results. This analysis is simplistic in that we are only considering the case of heterogeneous returns
to cooperative behavior w
i
. It may be important to analyze the case of heterogeneous returns to deviant behavior. It may be that some individuals while having a low return to cooperative
behavior may have an even lower return to deviant behavior. Merton 1957 discussed how the “absence of realistic opportunities for advancement
results in a marked tendency toward deviant behavior”.
18
Wilson 1987, 1996 conjectures that a likely cause of the pathological social patterns of the urban poor result in part from
the absence of a middle class or stable working class in the post-industrial inner city. These groups not only reinforced societal norms but they maintained social institutions such as
churches, shops, etc. He also points out that high rates of neighborhood poverty are less likely to create problem of social organization if residents are working in the mainstream
labor market. This model illustrates a mechanism that is consistent with these conjectures and consistent with the observations that increases in deviant behavior have been observed
in areas with increasing concentrated poverty.
6. Empirical issues and estimation
Empirical research on neighborhood effects has hit a dead-end recently as economists have discovered the difficulties of trying to correctly estimate neighborhood effects given
that the neighborhood choice is at least partially endogenous. Manski’s 1993 paper on the “reflection problem” explains that because of the endogeneity of the neighborhood
choice it is difficult if not impossible to discern in an econometric analysis of individual behavior whether a significant coefficient on a neighborhood characteristic implies that
this variable is influencing the individual or merely capturing something about the average characteristics of the community. Economists, as mentioned in Section 1, have tried to
control for the individual characteristics that might influence neighborhood choice by either trying to eliminate the individual fixed effects using panel data or by trying to control for
every possible individual background variable. Unfortunately, both of these approaches suffer from an omitted variable bias problem. The problem with the panel data approach is
that there may be unobservable factors influencing both the decision to move to a different neighborhood and the choice of the new neighborhood that will cause omitted variable
bias. The problem with the second approach of trying to control directly for every possible background variable is that it is impossible to control for many of these background variables
because they are unobservable and thus also cause omitted variable bias. Another difficulty with trying to measure neighborhood effects using US data is that confidentiality restrictions
limit the amount of neighborhood information available for micro level data.
19
While this empirical analysis would, no doubt, be strengthened by the availability of better data
18
See Merton 1957, p. 145.
19
The panel study of income dynamics PSID, the national longitudinal survey of youth NLSY and the national longitudinal study of adolescent health will allow zip code and tract level identification for certain variables under
special conditions.
N. Brooks J. of Economic Behavior Org. 44 2001 249–267 263
sources,
20
it demonstrates how a theoretical model enables the development of a testable structural empirical model which is purged of omitted variable bias arising from the potential
endogeneity of the neighborhood choice. In Section 7 of this paper, a reduced form equation which is derived from structural
equations developed from the theoretical model presented earlier will be estimated. This empirical work will test the validity of the theoretical mechanism itself, not the comparative
statics results of the model. It is important to test the model itself in that it will allow us to differentiate between a pure sorting model and the model of neighborhood effects. In a pure
sorting model, such as the model developed by Tiebout 1956, individuals who behave in a similar way may also have other similar characteristics or preferences that may make them
tend to choose to live in the same neighborhoods. In this model individuals efficiently sort themselves and neighbors do not influence each other. In the model of neighborhood effects
developed in the previous chapter, an individual’s behavioral choice is instead influenced by his neighbors through their use of sanctioning. The difficulty in differentiating between
a pure sorting model and a model with neighborhood effects is what Manski is calling the “reflection problem”.
7. Results of the estimation
