Race and ethnic representation in home ownership is an important public policy topic for addressing inequality issues within society. Although US home ownership rates are rising, the growth is unequal among different ethnic and racial groups. Here we analyze the Homeowner Assistance Fund Data provided by the Urban Institute, supplemented by external data from the US Census American Community Survey. The goal is to conduct an exploratory and predictive analysis to seek plausible explanations for racial and ethnic inequality, and use the results to inform policymaking. We use spatial-temporal models to capture geographic and temporal effects for obtaining more accurate estimates and predictions. Different model estimation strategies such as MLE and Bayesian are used to check consistency between different methods, leverage prior information from previous studies, and make additional inferences about parameters. We then address questions such as: what factors are related to a reduction in poverty and unemployment; what factors are related to an improvement in equitable representation in home ownership; and how the COVID-19 pandemic has affected yearly home ownership trends.