A MODEL FOR IDENTIFYING GENTRIFIED AREAS WITH CENSUS-DATA

Empirical research on gentrification suffers from a dichotomy between richly detailed neighborhood case studies and macro-scale, census-base d analyses, perpetuating uncertainty over the extent and timing of gen trified areas in American cities. We develop a model relating tract-le vel census statistics to the results of a detailed field survey of 24 census tracts in Minneapolis-St. Paul. We use stepwise and canonical d iscriminant analysis to select nine variables distinguishing gentrifie d neighborhoods and to classify all central-city tracts for each decad e between 1960 and 1990. Results indicate a moderate level of overall accuracy, and the model is more than 90% accurate in distinguishing ar eas of heavy reinvestment from stable, middle-class districts. Compare d with other techniques, our approach more accurately distinguishes ge ntrification from other types of inner-city redevelopment, providing a useful tool for identifying the phenomenon with a measurable degree o f precision.