Comments on Levy’s“Health Insurance among Low-Skilled Adults

over the Business Cycle”

Rucker JohnsonUniv of California, Berkeley

Prepared for NPC “Working & Poor” Research Conference

June 9-10, 2005

Why Care about Loss of Health Insurance?Why Care about Loss of Health Insurance?(A little perspective on the paper)(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

Despite strong economic growth, and expanding public Despite strong economic growth, and expanding public coverage, the rate of health insurance coverage fell during the coverage, the rate of health insurance coverage fell during the 1990s.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)

PuzzlePuzzle: Low-skilled had largest gains in employment : Low-skilled had largest gains in employment and largest largest declines in HIdeclines in HI

Goal of Levy paperGoal of Levy paper: Explain decline in HI coverage among : Explain decline in HI coverage among less-skilled in booming ’90sless-skilled in booming ’90s

Approach:Approach: Use CPS (’90-’03), relate HI coverage trends in late Use CPS (’90-’03), relate HI coverage trends in late ’90s boom, and ’01 downturn to changes in income and ’90s boom, and ’01 downturn to changes in income and employment by educ/gender– 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: Overview of Trends in HI Coverage: 1990-20031990-2003

Econometric SpecificationEconometric 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

Main Concerns about Paper

Incomplete Characterization/Accounting Incomplete Characterization/Accounting

of Health Insurance Dynamics over periodof Health Insurance Dynamics over period

Decomposition Analysis—issues of interpretationDecomposition 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, 1990-2003

Total change can be decomposed as:

90

90909090

n

X

n

X

n

X

n

Xetotalchang i i

j

i ij

j

i ij

j

i jijj

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

Source: Brady & Lin, 2005

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 (1997-2003)

Nationally-representative sampleHealth 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

Merged State-Level Data,1997-2002Merged State-Level Data,1997-2002

State Unemp RateState Unemp Rate BLSBLS

Health Insur CostsHealth Insur Costs Medicare hospital wage indexMedicare hospital wage index

Medicaid Medicaid CoverageCoverage

John Cawley & Kosali Simon: John Cawley & Kosali Simon: Similar to Cutler/Gruber MethodSimilar to Cutler/Gruber Method

% Unionized% Unionized Hirsch et al. (2001)Hirsch et al. (2001)

Special thanks to John Cawley and Kosali Simon for sharing their state-level data for Special thanks to John Cawley and Kosali Simon for sharing their state-level data for 1997-2002.1997-2002.

Merged data on:Merged data on: SCHIP/Medicaid EligibilitySCHIP/Medicaid Eligibility

Computed from running detailed simulation programs Computed from running detailed simulation programs (created by Cawley and Simon) on March CPS (created by Cawley and Simon) on March CPS respondents as in Cutler and Gruber (1996)respondents as in Cutler and Gruber (1996)

Take Take allall March CPS children in 1996, and calculate March CPS children in 1996, and calculate the weighted fraction of them that would be eligible the weighted fraction of them that would be eligible for Medicaid or SCHIP in a particular state in a for Medicaid or SCHIP in a particular state in a particular year. That fraction is used as measure of particular year. That fraction is used as measure of Medicaid/SCHIP generosity. The measure varies by Medicaid/SCHIP generosity. The measure varies by state and year.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.

11.7

26.9

53.1

23.9

0

10

20

30

40

50

60

70

80

0Mos

0-12Mos

0-24Mos

0-36Mos

0-48Mos

0-60Mos

0-71Mos

72Mos

Whites

Minorities

Less-Educated Men Men (Especially Minorities)(Especially Minorities) Have High Uninsured Rates Have High Uninsured RatesPSID: #of Months w/PSID: #of Months w/Any HIAny HI,1997-2002,1997-2002

HS Dropouts

26.7

47.6

38.7

15.1

0

10

20

30

40

50

60

70

80

90

0Mos

0-12Mos

0-24Mos

0-36Mos

0-48Mos

0-60Mos

0-71Mos

72Mos

Whites

Minorities

Less-Educated Men Less-Educated Men (Especially Minorities)(Especially Minorities) Have High Uninsured Rates Have High Uninsured RatesPSID: #of Months w/PSID: #of Months w/ESI,ESI,1997-20021997-2002

HS Dropouts

10.5

21.7

54.2

34.6

0

10

20

30

40

50

60

70

0Mos

0-12Mos

0-24Mos

0-36Mos

0-48Mos

0-60Mos

0-71Mos

72Mos

Whites

Minorities

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

HS Dropouts

33.5

51.6

33.9

18.2

0

10

20

30

40

50

60

70

80

90

0Mos

0-12Mos

0-24Mos

0-36Mos

0-48Mos

0-60Mos

0-71Mos

72Mos

Whites

Minorities

Less-Educated Women (Especially Minorities) Have High Uninsured RatesPSID: #of Months w/PSID: #of Months w/ESIESI,1997-2002,1997-2002

HS Dropouts

25

30

35

40

45

50

55

60

65

1997 1998 1999 2000 2001 2002

White Men

White Women

Minority Men

Minority Women

Less-Educated AdultsLess-Educated AdultsPSID: % with PSID: % with ESI Full YrESI Full Yr,1997-2002,1997-2002

HS Dropouts

10

15

20

25

1997-1998 1999-2000 2001-2002

White Women

Minority Women

Less-Educated WomenLess-Educated WomenPSID: % with PSID: % with Govt HI (at any time)Govt HI (at any time),,1997-2002

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 -.0546***

(.0181)

State unemp rate*white -.0211

(.0206)Individual-specific fixed effects Yes

Yr-specific fixed effects Yes

State-level controls for: Medicaid generosity, HI costs, Unionization

Yes

Mean of dependent var .4609

# Observations 3,443

TABLE 1. PSID men, HS dropout; whether HI as a function 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 -.0546*** .0444**

(.0181) (.0227)

State unemp rate*white -.0211 -.0019

(.0206) (.0219)

Individual-specific fixed effects Yes Yes

Yr-specific fixed effects Yes Yes

State-level controls for: Medicaid generosity, HI costs, Unionization

Yes Yes

Mean of dependent var .4609 .3312

# Observations 3,443 3,443

Full-yr ESI Uninsured All-yr Govt HI any time (2-yr per)

State unemp rateState unemp rate -.0140-.0140

(.0113)(.0113)

State unemp rate*non-whiteState unemp rate*non-white -.0546***-.0546*** .0444**.0444**

(.0181)(.0181) (.0227)(.0227)

State unemp rate*whiteState unemp rate*white -.0211-.0211 -.0019-.0019

(.0206)(.0206) (.0219)(.0219)

Individual-specific fixed effectsIndividual-specific fixed effects YesYes YesYes YesYes

Yr-specific fixed effectsYr-specific fixed effects YesYes YesYes YesYes

State-level controls for: Medicaid State-level controls for: Medicaid generosity, HI costs, Unionizationgenerosity, HI costs, Unionization

YesYes YesYes YesYes

Mean of dependent varMean of dependent var .4609.4609 .3312.3312 .0981.0981

# Observations# Observations 3,4433,443 3,4433,443 1,7591,759

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 ESIFull-yr ESI Uninsured Uninsured All-yrAll-yr

Govt HI any Govt HI any time (2-yr per)time (2-yr per)

State unemp rateState unemp rate

State unemp rate*non-whiteState unemp rate*non-white -.0289*-.0289*

(.0162)(.0162)

State unemp rate*whiteState unemp rate*white -.0112-.0112

(.0229)(.0229)Individual-specific fixed effectsIndividual-specific fixed effects YesYes

Yr-specific fixed effectsYr-specific fixed effects YesYes

State-level controls for: Medicaid State-level controls for: Medicaid generosity, HI costs, Unionizationgenerosity, HI costs, Unionization

YesYes

Mean of dependent varMean of dependent var .3885.3885

# Observations# Observations 4,2224,222

Full-yr ESI Uninsured All-yr Govt HI any Govt HI any time (2-yr per)time (2-yr per)

State unemp rateState unemp rate

State unemp rate*non-whiteState unemp rate*non-white -.0289*-.0289* .0044.0044

(.0162)(.0162) (.0112)(.0112)

State unemp rate*whiteState unemp rate*white -.0112-.0112 -.0154-.0154

(.0229)(.0229) (.0201)(.0201)Individual-specific fixed effectsIndividual-specific fixed effects YesYes YesYes

Yr-specific fixed effectsYr-specific fixed effects YesYes YesYes

State-level controls for: Medicaid State-level controls for: Medicaid generosity, HI costs, Unionizationgenerosity, HI costs, Unionization

YesYes YesYes

Mean of dependent varMean of dependent var .3885.3885 .3161.3161

# Observations# Observations 4,2224,222 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 ESI Uninsured All-yr Govt HI any time (2-yr per)

State unemp rateState unemp rate -.0188-.0188

(.0176)(.0176)

State unemp rate*non-whiteState unemp rate*non-white -.0289*-.0289* .0044.0044

(.0162)(.0162) (.0112)(.0112)

State unemp rate*whiteState unemp rate*white -.0112-.0112 -.0154-.0154

(.0229)(.0229) (.0201)(.0201)Individual-specific fixed effectsIndividual-specific fixed effects YesYes YesYes YesYes

Yr-specific fixed effectsYr-specific fixed effects YesYes YesYes YesYes

State-level controls for: Medicaid State-level controls for: Medicaid generosity, HI costs, Unionizationgenerosity, HI costs, Unionization

YesYes YesYes YesYes

Mean of dependent varMean of dependent var .3885.3885 .3161.3161 .2149.2149

# Observations# Observations 4,2224,222 4,2224,222 2,1492,149

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 Uninsured All-yrAll-yr

Govt HI any Govt HI any time (2-yr per)time (2-yr per)

State unemp rateState unemp rate -.0402***-.0402***

(.0151)(.0151)

Individual-specific fixed effectsIndividual-specific fixed effects YesYes

Yr-specific fixed effectsYr-specific fixed effects YesYes

State-level controls for: Medicaid State-level controls for: Medicaid generosity, HI costs, Unionizationgenerosity, HI costs, Unionization

YesYes

Mean of dependent varMean of dependent var .2792.2792

# Observations# Observations 10,58710,587

Full-yr ESIFull-yr ESI Uninsured All-yrUninsured All-yr Govt HI any Govt HI any time (2-yr per)time (2-yr per)

State unemp rateState unemp rate -.0402***-.0402*** .0317**.0317**

(.0151)(.0151) (.0126)(.0126)

Individual-specific fixed effectsIndividual-specific fixed effects YesYes YesYes

Yr-specific fixed effectsYr-specific fixed effects YesYes YesYes

State-level controls for: Medicaid State-level controls for: Medicaid generosity, HI costs, Unionizationgenerosity, HI costs, Unionization

YesYes YesYes

Mean of dependent varMean of dependent var .2792.2792 .2715.2715

# Observations# Observations 10,58710,587 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 ESI Uninsured All-yr Govt HI any time (2-yr per)

State unemp rate -.0402*** .0317** .0118

(.0151) (.0126) (.0180)

Individual-specific fixed effects Yes Yes Yes

Yr-specific fixed effects Yes Yes Yes

State-level controls for: Medicaid generosity, HI costs, Unionization

Yes Yes Yes

Mean of dependent var .2792 .2715 .3914

# Observations 10,587 10,587 5,234

TABLE 3. PSID Children of HS dropout; whether HI as a fn of macroeconomic conditions

Linear probability model coefficients (Robust std errors)