Spatial interaction, spatial multipliers and hospital competition

Abstract

The hospital competition literature shows that estimates of the effect of local market structure (concentration) on pricing (competition) are sensitive to geographic market definition. Our spatial lag model approach effects smoothing of the explanatory variables across the discrete market boundaries, resulting in robust estimates of the impact of market structure on hospital pricing, which can be used to estimate the full effect of changes in prices inclusive of spillovers that cascade through the neighboring hospital markets. The full amount, generated by the spatial multiplier effect, is a robust estimate of the impacts of market factors on hospital competition. We contrast ordinary least squares and spatial lag estimates to demonstrate the importance of robust estimation in analysis of hospital market competition. In markets where concentration is relatively high before a proposed merger, we demonstrate that Ordinary Least Squares (OLS) can lead to the wrong policy conclusion while the more conservative lag estimates do not.