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Although a broad-based increase in house prices has been observed over the past year, not everyone is convinced the rise of house prices will persist and lead to a steady recovery of the economy. The main reason for this skepticism is uncertainty about the 'shadow inventory': foreclosed homes held by investors or as REOs, which have not yet hit the market but likely will as market prices rise. The volume of shadow inventory itself in local markets is largely unknown, as is its impact on the housing market. This study quantifies the size of the shadow inventory and investigates the spatial impact of the out-flow of shadow inventory. The scope of our study is a set of housing markets (AZ, CA, and FL) that vary in both their historic housing price volatility as well as institutional factors - such as foreclosure law statutes - that may influence the relationship between the shadow inventory and house price dynamics. To address the endogeneity that characterizes the spatial interaction of house prices and the out-flow of the shadow inventory, we utilize a simultaneous equation system of spatial autoregressions (SESSAR). The model is estimated using measures of the shadow inventory derived from DataQuick's national transaction history database and county-level house price indices provided by Black Knight. Lastly, because our estimate - as well as all other existing estimates - of the shadow inventory relies upon string matching algorithms to identify entry into and exit out of REO status, we validate the accuracy of our measures of REOs using loss mitigation data from the OCC Mortgage Metrics database. [ABSTRACT FROM AUTHOR]