essays in public finance and industrial organization a dissertation ...
essays in public finance and industrial organization a dissertation ...
essays in public finance and industrial organization a dissertation ...
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CHAPTER 1. BANKRUPTCY 15<br />
bound of the effect of bankruptcy <strong>in</strong>surance on household f<strong>in</strong>ancial risk.<br />
I use Relative Risk Scores to control for medical utilization. As I discuss <strong>in</strong> Section<br />
1.4, controll<strong>in</strong>g for utilization is important because the direction of the unconditional<br />
relationship between out-of-pocket payments <strong>and</strong> seizable assets <strong>in</strong> theoretically am-<br />
biguous. To control for utilization, I use the Relative Risk Score variable constructed<br />
us<strong>in</strong>g the RiskSmart Version 2.2 software created by DxCG Inc. 23 This software uses<br />
<strong>in</strong>formation on age, sex, <strong>and</strong> medical diagnoses to project expected medical utiliza-<br />
tion based on regression models developed by the company. Because the software<br />
does not use geographical <strong>in</strong>formation to project utilization, the Relative Risk Score<br />
is orthogonal to asset exemption laws <strong>and</strong> other state-level factors.<br />
1.3.4 Insurance Premiums<br />
I conduct additional analysis us<strong>in</strong>g data on health <strong>in</strong>surance premiums <strong>in</strong> the <strong>in</strong>di-<br />
vidual market. In particular, I use data on premium quotes <strong>in</strong> each state that are<br />
listed on eHealthInsurance, a website that aggregates premium quotes from most of<br />
the major <strong>in</strong>surance providers. The data I use were collected <strong>in</strong> November, 2010.<br />
I collect premiums <strong>in</strong> each state for a 30-year-old non-smok<strong>in</strong>g male. Because pre-<br />
miums quotes are zip code specific, the data are collected for a zip code r<strong>and</strong>omly<br />
selected from the 10 most populous zip codes <strong>in</strong> the state. Along with premiums,<br />
I collect data on the <strong>in</strong>surance provider, plan br<strong>and</strong> name, deductible, co<strong>in</strong>surance<br />
rate, <strong>and</strong> co-payment for a office visit. I def<strong>in</strong>e an <strong>in</strong>surance plan as all observations<br />
with the same <strong>in</strong>surer, br<strong>and</strong> name, deductible, co<strong>in</strong>surance <strong>and</strong> co-payment. Table<br />
1.14 shows basic summary statistics for the data. The data set covers 41 states <strong>and</strong><br />
1,891 plans. The mean premium is $103 per month, the mean deductible is $3,351,<br />
<strong>and</strong> the mean co<strong>in</strong>surance rate is 15 percent.<br />
23 See form HC-092 on the MEPS website for a full description of the construction of this variable.