Comments on Levy’s

1. Comments on Levy’s “Health Insurance among Low-Skilled Adults over the Business Cycle” Rucker Johnson Univ of California, Berkeley Prepared for NPC “Working & Poor” Research Conference June 9-10, 2005

2. Why Care about Loss of Health Insurance?(A little perspective on the paper) • Some lose employer-sponsored HI & join public HI-- adds to budget strain • Uninsured may get less med treatment (Doyle 2001) • Uninsured may impose costs due to inefficient care mgmt (ER care was preventable if treated @ ofc visit) • Economic security & risk of bankruptcy in event of negative health shock

3. Despite strong economic growth, and expanding public coverage, the rate of health insurance coverage fell during the 1990s. • 13.7% of non-elderly uninsured (1987) • 15.8% of non-elderly uninsured (2000) • Puzzle: Low-skilled had largest gains in employment and largest declines in HI • Goal of Levy paper: Explain decline in HI coverage among less-skilled in booming ’90s • Approach: Use CPS (’90-’03), relate HI coverage trends in late ’90s boom, and ’01 downturn to changes in income and employment by educ/gender– • How much can be explained? • Was decline driven by changes in public or private coverage?

4. Factors that Affect HI Coverage • Labor market conditions • Much of cyclical var in coverage related to change in economic conditions (Cawley & Simon, 2005) • Health care costs-- rising premiums • 1% increase in premium  drop of 300,000 (Lewin) • Much of secular trend in HI coverage due to higher health care costs (Chernew, Cutler, Keenan, 2002) • Availability of public coverage • Medicaid/SCHIP expansions (Currie & Gruber, 1996) • Structural changes of economy • Explain little of change in HI coverage over time (Glied & Stabile, 2000; Acs, 1995) • Demographic changes • Changing value of alternatives (charity care) • Regulatory changes • Changing Load • Taxes

5. What about Changing Distribution of Coverage? • Decline not evenly distributed, concentrated among low-income adults • Prior research examines either effects of costs or economic conditions; • But rarely both or distributional effects across groups • How does effect of macroeconomy on HI coverage differ for men, women, & children, by education and race? • To what extent does public HI coverage compensate for secular and cyclical changes in private coverage, by gender, education, and race?

6. Overview of Trends in HI Coverage: 1990-2003

7. Econometric Specification • Identifying sources of variation: • Exploit time and state variation in economic conditions Model: • P(HI)= B1 * (state unemp rate) + B2 * (own emp) + B3* (spouse emp) + B4 * (fam income) + B5 * (demographic vars) + B6 * (Medicaid generosity) + (year dummies) + (state dummies) Where HI = different health insurance outcomes

8. Main Concerns about Paper • Incomplete Characterization/Accounting of Health Insurance Dynamics over period • Decomposition Analysis—issues of interpretation

9. Issues of Measurement that Raise Concern w/Analysis • Limitations of CPS • Records whether covered by HI at any time in last 12 mos • Cannot use CPS to determine HI coverage in specific month matched w/macroeconomic cond’ns for that month • Multiple changes in survey question over time • captured by year FE • Use of cross-sectional data • Inability to remove unobserved time-invariant person-specific heterogeneity • Longitudinal data reveal much larger share of pop at risk for being uninsured • Short (‘04), using SIPP, finds ½ of persistently uninsured are missed in svys that count only those uninsur for 12 consecutive months

10. Some Unresolved Issues • Does paper decompose relative roles of economic conditions, health care costs, Medicaid/SCHIP expansions, employment status, for health insurance coverage trends among low-skilled adults? • Does paper adequately acc’t for competing explanations over this time period? • Does paper help us to understand where risks of future gaps in coverage are likely to be greatest?

11. Decomposition Analysis: Trends in HI Coverage, 1990-2003 Total change can be decomposed as: Portion of Δs in HI not explained by Δs in X: “residual” effect Portion of Δs b/w yrs due to Δs in X • Cannot decompose residual component–- state dummies included • State*yr dummies capture Δs in economic conditions, health care costs, public program generosity • Sensitivity of decomposition estimates to inclusion of state unemp rate and proxy for state HI costs? • Relate time profile of residual effect with known trends of other factors that may have driven Δs in HI

12. Source: Brady & Lin, 2005

13. Source: Brady & Lin, 2005

14. Source: Brady & Lin, 2005

15. Health Insurance is Dynamic • Half of uninsured spells end within 5-6 months (Short, 2004) • Number uninsured partof a yearnumber uninsured all year • As many people lose or gain coverage as remain uninsured • Considerable turnover in uninsured population • Timing matters in counting, characterizing, and covering the uninsured

16. Analyzing HI Dynamics using PSID(1997-2003) Nationally-representative sample Health Insurance Info • Individuals asked: • # of mos w/HI coverage in each yr b/w 1997-2002 • Type of coverage in each yr b/w 1997-2002 • HI premium costs • Total HH medical care costs • Out-of-pocket costs (hospital, Dr.office, Rx drugs) • Health status measures

17. Merged State-Level Data,1997-2002 Special thanks to John Cawley and Kosali Simon for sharing their state-level data for 1997-2002.

18. Merged data on: • SCHIP/Medicaid Eligibility • Computed from running detailed simulation programs (created by Cawley and Simon) on March CPS respondents as in Cutler and Gruber (1996) • Take all March CPS children in 1996, and calculate the weighted fraction of them that would be eligible for Medicaid or SCHIP in a particular state in a particular year. That fraction is used as measure of Medicaid/SCHIP generosity. The measure varies by state and year.

19. Empirical Approach (using PSID)(similar to Cawley & Simon, ’05) • Separate models for men, women, children, by education (interactions w/race)—restrict to non-elderly • Estimate models w/dependent vars: • Whether employer-sponsored HI full yr • Whether uninsured all yr • Govt-sponsored HI at any time (2-yr period) • Medical care expenditures (2-yr period) • Explanatory var of interest: • State unemp rate • Include individual-specific & yr-specific fixed effects • State-level controls for Medicaid generosity, HI costs, % unionized • Identification of effect of macroeconomic conditions on probability of HI coverage comes from variation w/in people over time in deviations from nat’l mean in that yr.

20. Less-Educated Men (Especially Minorities) Have High Uninsured RatesPSID: #of Months w/Any HI,1997-2002 HS Dropouts

21. Less-Educated Men (Especially Minorities) Have High Uninsured RatesPSID: #of Months w/ESI,1997-2002 HS Dropouts

22. Less-Educated Women (Especially Minorities) Have High Uninsured RatesPSID: #of Months w/Any HI,1997-2002 HS Dropouts

23. Less-Educated Women (Especially Minorities) Have High Uninsured RatesPSID: #of Months w/ESI,1997-2002 HS Dropouts

24. Less-Educated AdultsPSID: % with ESI Full Yr,1997-2002 HS Dropouts

25. Less-Educated WomenPSID: % with Govt HI (at any time),1997-2002 HS Dropouts

26. TABLE 1. PSID men, HS dropout; whether HI as a fn of macroeconomic conditions Linear probability model coefficients(Robust std errors)

27. TABLE 1. PSID men, HS dropout; whether HI as a function of macroeconomic conditions Linear probability model coefficients (Robust std errors)

28. TABLE 1. PSID men, HS dropout; whether HI as a function of macroeconomic conditions Linear probability model coefficients (Robust std errors)

29. TABLE 2. PSID Women, HS dropout; whether HI as a fn of macroeconomic conditions Linear probability model coefficients (Robust std errors)

30. TABLE 2. PSID Women, HS dropout; whether HI as a fn of macroeconomic conditions Linear probability model coefficients (Robust std errors)

31. TABLE 2. PSID Women, HS dropout; whether HI as a fn of macroeconomic conditions Linear probability model coefficients (Robust std errors)

32. TABLE 3. PSID Children of HS dropout; whether HI as a fn of macroeconomic conditions Linear probability model coefficients (Robust std errors)

33. TABLE 3. PSID Children of HS dropout; whether HI as a fn of macroeconomic conditions Linear probability model coefficients (Robust std errors)

34. TABLE 3. PSID Children of HS dropout; whether HI as a fn of macroeconomic conditions Linear probability model coefficients (Robust std errors)