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Do Employers Respond to Public Hospitals Crowding Out of Private Insurance? Eric Seiber Clemson University.

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Presentation on theme: "Do Employers Respond to Public Hospitals Crowding Out of Private Insurance? Eric Seiber Clemson University."— Presentation transcript:

1 Do Employers Respond to Public Hospitals Crowding Out of Private Insurance? Eric Seiber Clemson University

2 Rationale 1.Repeated studies find public services crowding out private ins. coverage –Medicaid expansions –Public hospitals 2.Fewer workers eligible for ESI plans Question: Does hospital crowd out affect both Take-up and Supply of ESI?

3 Methodology Data: –1995 CPS: Contingent Workers Supplement –1995 AHA Annual Hospital Survey Choice Set 1.Offered ESI; (ESI, Pvt, No Insurance) 2.Not Offered ESI; (Pvt, No Insurance) –IIA Problem –Estimate with Nested Multinomial Logit Public Hospital Presence = % public beds

4 Methodology Prob(Ch ij = 1) = exp(β ij ’X t +  i ’Y t ) (i=1,2; j=1,2,3) Σ 2 m=1 Σ 3 n=1 exp(β mn ’X t +  m ’Y t ) where: X t = vector of characteristics determining both i and j Y t = vector of characteristics determining only I Y t necessary to resolve IIA Problem Two Models: 1.No income interactions 2.Pct Public Beds interacted with income levels

5 Results - Simulations Public hospitals had expected effect on Take-up Public bed change from 15% to 25% produced: Negligible effect for entire sample ESI decreases: 81.8% to 81.5% Uninsured increases: 16.0% to 16.6% Substantial effects for Poor and Near-Poor ESI decreases: 38.8% to 34.3% and 59.3% to 56.4% Uninsured increases: 58.3% to 63.3% and 37.5% to 40.5%

6 Results - Simulations Effect on ESI supply varies Public bed change from 15% to 25% produced: Negligible effect for entire sample ESI Offer decreases: 89.2% to 88.7% Change in ESI (0.3%) matched by reduction in Offer (0.5%) Not Offered, No Ins:9.6%, 10.2% Offered, No Ins:6.4%, 6.4% Substantial effects for Poor, smaller for Near-Poor ESI Offer decreases : 59.3% to 55.1% and 75.4% to 74.5% Change in ESI (4.5%) matched by reduction in Offer (4.2%) Not Offered, No Ins:38.8%, 43.0% Offered, No Ins:14.9%, 17.0%

7 Conclusions & Implications The public hospital crowd-out effect varies by income level Crowd-out effects matched by reduction in eligibility –Sequencing of change is unknown Question: Will the market catch workers if a public hospital converts from public status? –Simulations produced symmetrical results


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