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

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 ofc visit) Economic security & risk of bankruptcy in event of negative health shock

Despite strong economic growth, and expanding public coverage, the rate of health insurance coverage fell during the 1990s. 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) 13.7% of non-elderly uninsured (1987) 15.8% of non-elderly uninsured (2000) 15.8% of non-elderly uninsured (2000) Puzzle: Low-skilled had largest gains in employment largest declines in HI 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 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– 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? How much can be explained? Was decline driven by changes in public or private coverage? Was decline driven by changes in public or private coverage?

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

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?

Overview of Trends in HI Coverage:

Econometric Specification Identifying sources of variation: Exploit time and state variation in economic conditions Model : P(HI)= B 1 * (state unemp rate) + B 2 * (own emp) + B 3 * (spouse emp) + B 4 * (fam income) + B 5 * (demographic vars) + B 6 * (Medicaid generosity) + (year dummies) + (state dummies) Where HI = different health insurance outcomes

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

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

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?

Decomposition Analysis: Trends in HI Coverage, Total change can be decomposed as: Portion of Δs b/w yrs due to Δs in X Portion of Δs in HI not explained by Δs in X: “residual” effect 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

Source: Brady & Lin, 2005

Health Insurance is Dynamic Half of uninsured spells end within 5-6 months (Short, 2004) Number uninsured part of 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

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

Merged State-Level Data, State Unemp Rate BLS Health Insur Costs Medicare hospital wage index Medicaid Coverage John Cawley & Kosali Simon: Similar to Cutler/Gruber Method % Unionized Hirsch et al. (2001) Special thanks to John Cawley and Kosali Simon for sharing their state-level data for

Merged data on: Merged data on: SCHIP/Medicaid Eligibility SCHIP/Medicaid Eligibility Computed from running detailed simulation programs (created by Cawley and Simon) on March CPS respondents as in Cutler and Gruber (1996) 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. 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.

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.

Men (Especially Minorities) Have High Uninsured Rates PSID: #of Months w/Any HI, Less-Educated Men (Especially Minorities) Have High Uninsured Rates PSID: #of Months w/Any HI, HS Dropouts

Less-Educated Men (Especially Minorities) Have High Uninsured Rates PSID: #of Months w/ESI, HS Dropouts

Less-Educated Women (Especially Minorities) Have High Uninsured Rates PSID: #of Months w/Any HI, HS Dropouts

PSID: #of Months w/ESI, Less-Educated Women (Especially Minorities) Have High Uninsured Rates PSID: #of Months w/ESI, HS Dropouts

Less-Educated Adults PSID: % with ESI Full Yr, HS Dropouts

Less-Educated Women PSID: % with Govt HI (at any time), Less-Educated Women PSID: % with Govt HI (at any time), HS Dropouts

TABLE 1. TABLE 1. PSID men, HS dropout; whether HI as a fn of macroeconomic conditions Linear probability model coefficients (Robust std errors) Full-yr ESI Uninsured All-yr Govt HI any time (2-yr per) State unemp rate State unemp rate*non-white *** (.0181) State unemp rate*white (.0206) Individual-specific fixed effectsYes Yr-specific fixed effectsYes State-level controls for: Medicaid generosity, HI costs, Unionization Yes Mean of dependent var.4609 # Observations3,443

TABLE 1. PSID men, HS dropout; whether HI as a function of macroeconomic conditions Linear probability model coefficients (Robust std errors) Full-yr ESIUninsured All-yr Govt HI any time (2-yr per) State unemp rate State unemp rate*non-white ***.0444** (.0181)(.0227) State unemp rate*white (.0206)(.0219) Individual-specific fixed effectsYes Yr-specific fixed effectsYes State-level controls for: Medicaid generosity, HI costs, Unionization Yes Mean of dependent var # Observations 3,443

Full-yr ESIUninsured All-yrGovt HI any time (2-yr per) State unemp rate (.0113) State unemp rate*non-white ***.0444** (.0181)(.0227) State unemp rate*white (.0206)(.0219) Individual-specific fixed effects YesYesYes Yr-specific fixed effects YesYesYes State-level controls for: Medicaid generosity, HI costs, Unionization YesYesYes Mean of dependent var # Observations 3,4433,4431,759 TABLE 1. PSID men, HS dropout; whether HI as a function of macroeconomic conditions Linear probability model coefficients (Robust std errors)

TABLE 2. TABLE 2. PSID Women, HS dropout; whether HI as a fn of macroeconomic conditions Linear probability model coefficients (Robust std errors) Full-yr ESI Uninsured All-yr Govt HI any time (2-yr per) State unemp rate State unemp rate*non-white * (.0162) State unemp rate*white (.0229) Individual-specific fixed effects Yes Yr-specific fixed effects Yes State-level controls for: Medicaid generosity, HI costs, Unionization Yes Mean of dependent var.3885 # Observations 4,222

Full-yr ESIUninsured All-yr Govt HI any time (2-yr per) State unemp rate State unemp rate*non-white *.0044 (.0162)(.0112) State unemp rate*white (.0229)(.0201) Individual-specific fixed effects YesYes Yr-specific fixed effects YesYes State-level controls for: Medicaid generosity, HI costs, Unionization YesYes Mean of dependent var # Observations 4,2224,222 TABLE 2. TABLE 2. PSID Women, HS dropout; whether HI as a fn of macroeconomic conditions Linear probability model coefficients (Robust std errors)

Full-yr ESIUninsured All-yrGovt HI any time (2-yr per) State unemp rate (.0176) State unemp rate*non-white *.0044 (.0162)(.0112) State unemp rate*white (.0229)(.0201) Individual-specific fixed effects YesYesYes Yr-specific fixed effects YesYesYes State-level controls for: Medicaid generosity, HI costs, Unionization YesYesYes Mean of dependent var # Observations 4,2224,2222,149 TABLE 2. TABLE 2. PSID Women, HS dropout; whether HI as a fn of macroeconomic conditions Linear probability model coefficients (Robust std errors)

TABLE 3. PSID Children of HS dropout; whether HI as a fn of macroeconomic conditions Linear probability model coefficients (Robust std errors) Full-yr ESI Uninsured All-yr Govt HI any time (2-yr per) State unemp rate *** (.0151) Individual-specific fixed effects Yes Yr-specific fixed effects Yes State-level controls for: Medicaid generosity, HI costs, Unionization Yes Mean of dependent var.2792 # Observations 10,587

Full-yr ESI Uninsured All-yr Govt HI any time (2-yr per) State unemp rate ***.0317** (.0151)(.0126) Individual-specific fixed effects YesYes Yr-specific fixed effects YesYes State-level controls for: Medicaid generosity, HI costs, Unionization YesYes Mean of dependent var # Observations 10,58710,587 TABLE 3. PSID Children of HS dropout; whether HI as a fn of macroeconomic conditions Linear probability model coefficients (Robust std errors)

Full-yr ESIUninsured All-yrGovt HI any time (2-yr per) State unemp rate ***.0317**.0118 (.0151)(.0126)(.0180) Individual-specific fixed effectsYes Yr-specific fixed effectsYes State-level controls for: Medicaid generosity, HI costs, Unionization Yes Mean of dependent var # Observations10,587 5,234 TABLE 3. PSID Children of HS dropout; whether HI as a fn of macroeconomic conditions Linear probability model coefficients (Robust std errors)