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CHAPTER 2. HEALTH PLAN CHOICE 81 where rf denotes the average risk of employees in firm f, which the insurer forecasts using the available demographic information, xf. 16 We model expected plan bids as a mark-up over expected cost. So plan j’s bid for firm f is: Bjf = δj · (aj + bj · (E[rf|xf] − 1)) + νjf, (2.7) where νjf is an independent mean zero random variable. The new parameter intro- duced in the bid model is the mark-up, δj. We constrain the mark-up to be constant across the plans offered by a particular insurer. Although in theory an insurer could vary the mark-up across its different plans, because the cost data are at the insurer- firm level, we are unable to identify separately the mark-up and the fixed costs for each plan offered by an insurer. Naturally we expect the mark-up parameters to be larger than one. Employer Contribution Setting The last part of our model specifies how employers set required plan contributions. We adopt a simple model in which employers pass on a fraction of their cost for the lowest cost plan, and then a fraction of the incremental cost for higher cost plans. We allow these fractions, denoted β and γ, to vary across firm-years and coverage tiers. Let B lf denote the minimum bid received for coverage tier l in firm-year f, denote plan j’s bid for coverage tier l in firm-year f as Bjlf. We model the required contribution as: pjlf = βlf · B lf + γlf · (Bjlf − B lf)+ξjlf. (2.8) This model describes employer behavior in our data remarkably well. The resid- uals from the linear regression (2.8) have a standard deviation of 7.64, and the R- squared is 0.99. As noted above, approximately half of the firms in our data choose a ”proportional pass-through” strategy where β = γ. The others choose an ”incremental pass-through” strategy in which β
CHAPTER 2. HEALTH PLAN CHOICE 82 2.4.2 Discussion of Model and Identification The key quantities in our model are plan costs and plan demand as functions of forecastable risk, and the price elasticity of demand. The former determine the efficient allocation of households to plans, while the latter determines how price changes affect self-selection. We now discuss the variation in the data that identifies each of these quantities in estimation. Identifying plan costs is straightforward. The effect of forecastable risk on plan costs is identified by variation across firms in the average risk scores of workers and dependents, and how it affects insurer bids and realized costs. We identify the mark- up parameters, δj, by the difference between the plan bids and reported costs. A maintained assumption in estimating mark-ups is that insurers base their bids on only the information about employees that is provided by the intermediary. We discuss this assumption more below, but we believe it is reasonable given the small size of the contracts and the fact that we consider only the first year of plan bids. The effect of household risk on choice behavior (i.e. the coefficients αrj in the demand equation) is identified by variation in observable risk across households. Our model also allows private information about health status to affect choice. The key parameter here is the variance of the private information, σ 2 µ, which is identified by the correlation between consumers’ enrollment decisions and plans’ realized costs. This identification is aided by cross-firm variation in contribution policies and demo- graphics that, conditional on observable health risk, affect enrollment but not realized costs. 17 The identification obtained from price variation is similar to the identification in standard selection models, and relies on the exclusion restriction if a given individual i is enrolled in a given plan j, his or her utilization does not depend on the per-month premium (although of course it may depend on other elements of the plan such as the copayment rate). The most subtle identification issues arise in estimating the effect of plan contributions on demand. Plan contributions are the result of plan bids and employer pass-through decisions. Our model allows four sources of variation in contributions: 17 Our demand model also includes plan characteristics such as coinsurance and deductible. Their coefficients are identified off cross-firm and cross-tier variation in the characteristics.
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ESSAYS IN PUBLIC FINANCE AND INDUST
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I certify that I have read this dis
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insurance choice. Among other thing
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Acknowledgements I am deeply thankf
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Contents Preface iv Acknowledgement
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2.5.3 The Value of Plan Choice ....
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List of Tables 1.1 Asset Exemption
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4.9 First Week Contract Spending fo
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4.3 I.T. Contracting by Week ......
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CHAPTER 1. BANKRUPTCY 2 of the dead
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CHAPTER 1. BANKRUPTCY 4 relevant le
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CHAPTER 1. BANKRUPTCY 6 superficial
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CHAPTER 1. BANKRUPTCY 8 After treat
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CHAPTER 1. BANKRUPTCY 20 or coverag
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CHAPTER 1. BANKRUPTCY 22 homestead
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CHAPTER 1. BANKRUPTCY 24 log seizab
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CHAPTER 1. BANKRUPTCY 26 on the bas
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CHAPTER 3. MEDIGAP 130 of costs and
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CHAPTER 3. MEDIGAP 132 policy that
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CHAPTER 3. MEDIGAP 134 3.6.2 Causal
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CHAPTER 3. MEDIGAP 136 3.6.3 Robust
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CHAPTER 3. MEDIGAP 138 calculated u
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CHAPTER 3. MEDIGAP 140 (10000,11000
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CHAPTER 3. MEDIGAP 142 Table 3.2: S
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CHAPTER 3. MEDIGAP 144 Table 3.4: H
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CHAPTER 3. MEDIGAP 146 Table 3.6: S
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CHAPTER 3. MEDIGAP 148 Table 3.8: R
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CHAPTER 3. MEDIGAP 150 Table 3.10:
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CHAPTER 3. MEDIGAP 152 Table 3.12:
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CHAPTER 4. YEAR-END SPENDING 154 bu
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CHAPTER 4. YEAR-END SPENDING 156 in
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