Table 2.

Effects of Base Closures on Resident Population Counts, Resident Case Mix and Rates of Hospitalization

	(1)	(2)	(3)	(4)
	Log Number of People in Original Catchment Area (Aggregated Sample of MHS Beneficiaries)	Log Mean Age of MHS Beneficiary (Aggregated Sample of MHS Beneficiaries)	Log Predicted Relative Weighted Product (Individual Sample of Inpatient Admissions)	Likelihood of Hospitalization Within a Year (Individual Sample of MHS Beneficiaries), Coefficient Multiplied
Active	0.69 (0.15)	0.51 (0.01)	0.21 (0.01)	−0.71 (0.13)
Post-Closing	0.01 (0.03)	−0.01 (0.01)	−0.00 (0.01)	−0.31 (0.23)
Active * Post-Closing	−0.12 (0.04)	0.01 (0.01)	−0.00 (0.01)	0.00 (0.29)

Notes: robust standard errors corrected for within-original-catchment area correlation in the error term are reported in parentheses. Post-Closing equals 0 for all zip codes unaffected by a base closure (that is, all zip codes whose closest-MTF measure was not altered by a base closure) and 0 for years prior to the closure for those zip codes affected by a base closure. Post-Closing equals 1 for years after closure for those zip codes affected by a base closure. Original catchment areas signify geographic areas of beneficiary residence, where regions are grouped according to the MHS Catchment Area Number assigned to that region at the beginning of the sample. The regressions in Column 3 and 4 includes zip code and year fixed effects. The regressions in Columns 1 and 2 are aggregated to the catchment-year level and include original catchment area and year fixed effects; while drawing on information from the full MHS beneficiary file regardless of receipt of inpatient care. The regression in Column 4 is organized at the individual-beneficiary-by-year level. Regressions include regions unaffected by a base closure as a control. Regressions are also limited to regions that were within 40 miles of an MTF hospital as of the beginning of the sample period.