Panel Paper:
Three New Indicators of Neighborhood Economic Opportunity
*Names in bold indicate Presenter
However, existing measures of economic opportunity are inadequate due to their overwhelming focus on the outcomes of opportunity, rather than the conditions that make opportunity possible. To this end, we propose the creation of interrelated composite indicators, at the census tract level, that capture a more comprehensive measure of neighborhood disparities that may have a long-term impact on the socioeconomic outcome of the residents. These composite indicators are (1) Economic Opportunity, (2) Risk and Vulnerability, and (3) Connectedness.
Through these three composite indicators, the proposed research develops three identifiable dimensions of opportunity and the interactions between them. Together, they provide a comprehensive approach that covers the social, economic, environmental conditions that shape neighborhoods and affect the lives of residents. Examining these three indicators will provide a better understanding of both sides of the opportunity divide—the factors that produce opportunity as well as those that constrain it—in order to add important nuance to the concept of opportunity. Additionally, it will allow the measurement of a third set of factors, which is often unmeasured but critically important: the institutional assets and complex social interactions that underpin neighborhood dynamics and provide linkages with networks beyond neighborhood boundaries.
We create three indicators through the following process: First, through an extensive literature review, we have identified from the theory the suggestion of creating categories based on the three constructs of Economic Opportunity, Risk and Vulnerability, and Connectedness. Next, we use factor analysis to identify the best possible variables (as measured at the census tract level, which we define as neighborhood) to incorporate under each of these three constructs. Thirdly, we develop an indicator using these variable groups using alternative weighting schemes. Finally, we investigate how closely the proposed indicators track traditional measures and then explain and describe how they differ.