Table 4.

Nonlinear effects by quintiles of base rate changes

	Log number of admissions	Case‐mix index	Log revenues
	(1)	(2)	(3)
Quintile 1	0.110***	0.101***	0.192***
	(0.035)	(0.029)	(0.047)
Quintile 2	0.127***	0.002	0.145***
	(0.037)	(0.028)	(0.047)
Quintile 3	0.099***	0.006	0.119***
	(0.034)	(0.027)	(0.043)
Quintile 4	0.091***	0.006	0.115***
	(0.035)	(0.029)	(0.042)
Quintile 5	0.069*	−0.022	0.060
	(0.040)	(0.029)	(0.214)
Year effects	Yes	Yes	Yes
Regional characteristics	Yes	Yes	Yes
Average base rate of competitors	Yes	Yes	Yes
Hospital fixed effects	Yes	Yes	Yes
N (hospitals)	801	801	801

Note. The table shows estimation coefficients of a fixed effects linear regression model. The model includes hospital fixed effects. The dependent variables are the logarithmized number of admissions (column 1), the case‐mix index (column 2), and the logarithmized revenues (columns 3). Results for column 1 are also shown in Figure S6. Specifications refer to Equation (6). The sample includes observations for the years 2004 and 2009. Regional indicators include average age of men, average age of women, population density, and unemployment rate. All regional characteristics are measured for a hospital's catchment area. Parentheses show robust standard errors, clustered at the hospital level.

^* Significant at 10%.

^** Significant at 5%.

^*** Significant at 1%.