The U. S. has experienced significant economic restructuring in recent decades.  In the cities, this has led to a decline in manufacturing and service jobs.

For example, in Baltimore the percentage of workers employed in blue-collar jobs declined from 33 to 19 percent of all jobs between 1970 and 1990.  And unemployment increased from 5 percent to 10 percent.

Economic restructuring has resulted in lower wages for lower-level jobs. It has encouraged increasing use of part-time workers.

This has been accompanied by growing social inequality in the U. S., with more wealth at the top and greater poverty at the bottom.  Compared to the poor children of yesterday, poor children of today are a larger percentage of the population, absolutely poorer, and more like to be chronically poor.

The deleterious consequences of these three trends (restructuring, inequality, and child poverty) come together within neighborhoods and families, and children.

The Effects on Children

How do these trends affect children, specifically? Let us explore several ways.

1. First, when unemployment is high, many families have lower incomes, and poverty increases.

   Poor families struggle to survive, and have fewer resources of time, money, and energy to devote to child-rearing.  Consequently, poverty constitutes a large risk-factor for healthy child development.

2. Second, if people cannot find work that pays a living wage, they have to survive somehow. One way is through participation in the illegal economy (crime).

Expansion of the illegal economy often reduces the number of employed people who provide positive role models of workers within the legal economy.  It also elevates the stature of those who work in the illegal economy, encouraging some youth to follow in their footsteps.

A strong illegal economy also may elevate the levels of neighborhood violence, particularly if drug trafficking is involved.

Neighborhood violence in turn affects how children grow up -- how they learn to resolve conflicts, and how they learn to deal with other people.

The Decline in Blue-Color Work and the Increase in Violence

We found: neighborhood violence is not related to the proportion of blue-collar jobs in a neighborhood (r = .11, not statistically significant).  But violence is related to a decline in jobs which are blue-collar (r = .30, p < .01).  And violence is related to the increases in unemployment following blue-collar job decline (r = .38, p < .01).  

The diagram below shows the use of structural equation modeling, where each concept (called a "latent variable") is measured by several kinds of data.  For example,  neighborhood economic opportunity is measured by census data on each neighborhood's degree of male employment, female employment, and full-time employment.

In this diagram, you see that the SEM model estimates the importance of the paths from employment to neighborhood economic health and the illegal economy, and the paths from the latter to neighborhood violence.  There are strong paths among all of these.

The coefficients inserted by each path indicate how strong is the relationship between the originating oval and the receiving oval.  Coefficients range from 0 to 1 or -1.  The diagram shows that the path from neighborhood employment opportunity to neighborhood economic health (as measured by household income, the percent of the families in the neighborhood who are not poor, and the percent of families who are not on on public assistance) is very strong.  (If people are not employed, then they tend to have less money.)  

The diagram also shows that neighborhoods that are not economically healthy tend to have more illegal activity (crime), and also tend to have more violence.  It also shows a relationship between crime and violence, but this relationship is not as strong as those between employment and economic health, and between economic health and crime and violence.  That is, while violence accompanies some crime, it does not accompany most crime.