Healthcare Care & Insurance in China: What We Learned from CHARLS 2008

John StraussHao Hong

Lin LiAlbert Park

Li YangYaohui Zhao

Goal of the Paper

• Describe the state of health insurance and heath care utilization as of 2008

• Micro data allows more precise description– Who has it– What types– Who uses outpatient and inpatient services– Key parameters (premiums, out-of-pocket

costs)

Data Source

• China Health and Retirement Longitudinal Study (CHARLS) 2008 in Zhejiang and Gansu provinces

• Module D – health care and insurance– Health insurance– Health service utilizations

• We use information on people 45 and older• Descriptive tables are weighted

INSURANCE COVERAGE

Table 1. Insurance Coverage, by age and sex

% N % N90.3 447 92.0 493(2.5) (1.9)94.3 423 93.4 404(1.6) (1.9)90.9 279 90.1 229(2.5) (2.1)86.1 119 81.3 112(4.2) (4.8)91.1 1268 90.5 1238(1.5) (1.5)

Standard error in Parenthesis 、

75+

Total(45+)

Men Women

45-54

55-64

65-74

Most people are covered by some type of health insurance. Five years ago very few would have been covered, especially in rural areas.Coverage declines a little for the oldest cohort.No big difference between men and women.

020

4060

8010

0

40 50 60 70 80age

Any insurance

Urban employee medical insurance

Urban resident medical insurance

New cooperative medical insurance

Men

020

4060

8010

0

40 50 60 70 80age

Any insurance

Urban employee medical insurance

Urban resident medical insurance

New cooperative medical insurance

Women

Figure 1: Insurance Coverage, by Gender & Age, bandwidth = .75

NCMS is the largest form of insurance.Followed by urban employee medical insurance.Urban resident medical insurance is the least significant.

Regression Analysis for Having Any Insurance

• Age and education• Adding income (logPCE), nonlinear• Adding migrant status, marital status and

rural dummy• Adding interactions of rural and province

dummies• Adding community fixed effects• All linear probability models

Aged 55-64 0.028 0.031* 0.035* 0.035* 0.025Aged 65-74 0.022 0.029 0.044* 0.051** 0.033

Aged 75 and over -0.024 -0.017 0.011 0.025 0.027Can read and write 0.018 0.014 0.015 0.028 0.025Finished primary 0.017 0.011 0.013 0.021 0.018

Junior high and above 0.038 0.027 0.037 0.038* 0.024logPCE (< median) 0.023 0.024 0.032* 0.022

logPCE (> median, marginal) -0.006 0.009 0.007 0.000Migrant -0.225*** -0.224*** -0.162**

Widowed -0.089** -0.099*** -0.118***Divorced or never married 0.073*** 0.087*** 0.078***

Rural 0.050**Rural Zhejiang -0.000Urban Gansu -0.022Rural Gansu 0.083***

Community FE NO NO NO NO YESF-test for all age dummies 2.30* 2.32* 2.08 2.09 1.07

(p-value) (0.083) (0.081) (0.108) (0.106) (0.366)F-test for all education dummies 0.94 0.50 1.04 1.19 0.69

(p-value) (0.424) (0.682) (0.379) (0.316) (0.558)F-test for all logPCE splines 2.37* 3.68** 5.42*** 3.17**

(p-value) (0.099) (0.029) (0.006) (0.046)F-test for all marital status dummies 19.19*** 5.12*** 21.66***

(p-value) (0.000) (0.003) (0.000)F-test for all location dummies 18.42*** 1.98***

(p-value) (0.000) (0.000)Observations 1262 1262 1262 1262 1262

Table 1. Regression for having any insurance: men

Higher education positively related to having insurance;

Higher income positively related to having insurance;

Widowed men much less likely to be insured;

Migrants much less likely to be insured, by 15% points

Aged 55-64 0.015 0.015 0.022 0.024 0.020Aged 65-74 -0.028 -0.028 -0.011 -0.007 -0.009

Aged 75 and over -0.142*** -0.144*** -0.089* -0.088* -0.117**Can read and write 0.043** 0.043** 0.061** 0.059** 0.053**Finished primary -0.003 -0.003 0.020 0.023 0.005

Junior high and above 0.044** 0.044* 0.073** 0.086*** 0.057**logPCE (< median) -0.003 -0.001 -0.001 -0.003

logPCE (> median, marginal) 0.004 0.026 0.021 0.016Migrant -0.293** -0.265** -0.158

Widowed -0.067** -0.063* -0.052Divorced or never married -0.032 -0.051 -0.114

Rural 0.085***Rural Zhejiang 0.043Urban Gansu -0.077Rural Gansu 0.070*

Community FE NO NO NO NO YESF-test for all age dummies 4.46*** 4.10*** 2.33* 2.21* 3.55**

(p-value) (0.006) (0.009) (0.079) (0.092) (0.017)F-test for all education dummies 2.39* 2.50* 3.19** 3.55** 3.20**

(p-value) (0.074) (0.064) (0.027) (0.018) (0.027)F-test for all logPCE splines 0.03 0.57 0.30 0.21

(p-value) (0.970) (0.568) (0.739) (0.814)F-test for all marital status dummies 2.10 3.15** 1.59

(p-value) (0.129) (0.029) (0.209)F-test for all location dummies 1.87 1.84***

(p-value) (0.159) (0.001)Observations 1233 1233 1233 1233 1233

Table 2. Regression for having any insurance: women

Higher education positively related to having insurance;

Widowed women much less likely to be insured;

Migrants much less likely to be insured;

As for men, Rural Gansu MORE likely to be insured.

Local community factors matter a lot

INSURANCE TYPES

Urbanemployeemedical

insurance

Urbanresidentmedical

insurance

Newcooperative

medicalinsurance

Otherinsurances

WithoutInsurance N

63.0 11.4 7.4 18.3 7.9 268(5.8) (2.6) (2.3) (3.5) (2.2)1.1 0.4 87.4 3.5 9.2 1001

(0.4) (0.3) (1.8) (1.2) (1.6)30.2 5.7 48.7 11.6 9.2 541(6.1) (1.4) (6.1) (2.4) (2.5)2.2 0.4 87.0 2.8 8.8 728

(0.6) (0.4) (1.9) (0.8) (1.7)14.9 2.8 69.7 6.8 8.9 1269(3.1) (0.7) (3.5) (1.3) (1.5)

Standard error in Parenthesis

Urban Hukou

Rural Hukou

Total

Table 2. Coverage of different Insurance type: men

Urban Area

Rural Area

Urban hukou: urban employee insurance is the largest type of insuranceRural hukou: NCMS is the dominant insuranceUrban area: a lot of residents with rural hukou

Urbanemployeemedical

insurance

Urbanresidentmedical

insurance

Newcooperative

medicalinsurance

Otherinsurances

WithoutInsurance N

43.5 21.5 12.6 18.0 12.9 229(7.2) (5.0) (4.3) (7.3) (3.3)0.6 0.1 89.9 1.9 8.5 1009

(0.3) (0.1) (1.7) (0.6) (1.6)19.4 9.5 54.4 10.1 11.3 565(4.8) (2.3) (7.0) (4.1) (2.5)0.4 0.0 91.9 0.8 7.6 673

(0.2) (0.0) (1.8) (0.5) (1.9)9.8 4.7 73.4 5.4 9.5 1238

(2.7) (1.2) (4.2) (2.2) (1.5)Standard error in Parenthesis

Total

Table 3. Coverage of different Insurance type: women

Urban Hukou

Rural Hukou

Urban Area

Rural Area

Similar patterns as men

Aged 55-64 -0.014 -0.012 -0.014 -0.014 -0.013Aged 65-74 -0.020 -0.016 -0.009 0.000 -0.009

Aged 75 and over -0.090** -0.083* -0.073 -0.052 -0.023Can read and write 0.016 0.015 0.013 0.029 0.019Finished primary 0.018 0.015 0.014 0.024 0.012

Junior high and above -0.041 -0.041 -0.031 -0.033 -0.037logPCE (< median) 0.026 0.027 0.038* 0.034

logPCE (> median, marginal) -0.048 -0.034 -0.032 -0.039Migrant -0.426*** -0.416*** -0.377**

Widowed -0.065 -0.076* -0.097**Divorced or never married 0.064* 0.078** 0.060*

Rural 0.047Rural Zhejiang -0.006Urban Gansu -0.027Rural Gansu 0.087**

Community FE NO NO NO NO YESF-test for all age dummies 1.64 1.30 0.86 0.49 0.11

(p-value) (0.186) (0.281) (0.466) (0.687) (0.952)F-test for all education dummies 1.54 1.42 0.85 1.45 1.08

(p-value) (0.211) (0.244) (0.471) (0.235) (0.360)F-test for all logPCE splines 0.97 0.95 1.85 1.21

(p-value) (0.384) (0.393) (0.164) (0.303)F-test for all marital status dummies 3.59** 4.40*** 4.88***

(p-value) (0.032) (0.006) (0.010)F-test for all location dummies 4.88*** 1.58***

(p-value) (0.010) (0.009)Observations 996 996 996 996 996

Table 7. Regression for having new cooperative medical insurance:men with rural Hukou

NCMS is not associated with education or incomes;

Widowed men much less likely to be insured;

Migrants much less likely to be insured;

Rural Gansu MORE likely to be insured.

Local community factors matter

Aged 55-64 0.006 0.007 0.003 0.003 -0.002Aged 65-74 -0.013 -0.013 -0.015 -0.013 -0.022

Aged 75 and over -0.154*** -0.155*** -0.138*** -0.133*** -0.156***Can read and write 0.055** 0.054** 0.064** 0.068** 0.059**Finished primary -0.005 -0.007 0.007 0.011 0.007

Junior high and above -0.010 -0.011 -0.003 0.001 0.005logPCE (< median) -0.004 -0.001 0.000 -0.002

logPCE (> median, marginal) 0.018 0.032 0.034 0.032Migrant -0.412*** -0.405*** -0.371*

Widowed -0.023 -0.023 -0.018Divorced or never married 0.130*** 0.126** 0.052

Rural 0.084**Rural Zhejiang 0.062Urban Gansu -0.019Rural Gansu 0.094*

Community FE NO NO NO NO YESF-test for all age dummies 3.33** 3.02** 3.00** 2.67* 3.95**

(p-value) (0.024) (0.034) (0.035) (0.053) (0.011)F-test for all education dummies 2.16* 2.19* 2.26* 1.97 1.79

(p-value) (0.098) (0.095) (0.088) (0.124) (0.154)F-test for all logPCE splines 0.17 0.85 0.81 0.68

(p-value) (0.840) (0.430) (0.448) (0.509)F-test for all marital status dummies 3.63** 2.23* 1.10

(p-value) (0.031) (0.090) (0.337)F-test for all location dummies 2.65* 1.23

(p-value) (0.076) (0.162)Observations 1005 1005 1005 1005 1005

Table 8. Regression for having new cooperative medical insurance:women with rural Hukou

NCMS is associated with literacy but not incomes;

Migrants much less likely to be insured;

Rural Gansu MORE likely to be insured.

SERVICE UTILIZATION

% N % N11.7 395 20.0 459(2.0) (2.4)23.6 374 23.6 367(4.0) (3.8)15.4 249 16.7 204(2.5) (2.6)17.4 92 25.6 94(4.9) (6.5)16.5 1110 21.2 1124(1.7) (2.1)

Standard error in Parenthesis

Table 5. The percentage of people who usemedical service for outpatient in the last

month, by age and sex

75+

Total(45+)

Men Women

45-54

55-64

65-74

Women use outpatient care more frequently.

Aged 55-64 0.079*** 0.082*** 0.082*** 0.082*** 0.073**Aged 65-74 0.064** 0.069** 0.071** 0.073** 0.060

Aged 75 and over 0.065 0.069 0.072 0.083* 0.096**Can read and write 0.073** 0.069** 0.069** 0.080** 0.082**Finished primary 0.037 0.031 0.032 0.036 0.035

Junior high and above 0.080** 0.070** 0.073** 0.068* 0.074*logPCE (< median) 0.008 0.010 0.018 0.023*

logPCE (> median, marginal) 0.019 0.024 0.024 0.005Rural 0.026

Rural Zhejiang 0.001Urban Gansu 0.019Rural Gansu 0.064*

Community FE NO NO NO NO YESF-test for all age dummies 2.60* 2.70* 2.83** 3.04** 2.43*

(p-value) (0.057) (0.050) (0.043) (0.033) (0.070)F-test for all education dummies 2.52* 2.03 2.06 2.41* 2.36*

(p-value) (0.063) (0.116) (0.111) (0.072) (0.077)F-test for all logPCE splines 1.03 1.41 2.37* 1.75

(p-value) (0.363) (0.248) (0.099) (0.179)F-test for all location dummies 1.21 1.12

(p-value) (0.309) (0.231)Observations 1105 1105 1105 1105 1105

Table 9. Regression for using medical service for outpatient:men Outpatient service for

men is associated with education and to a lesser degree incomes;

Rural Gansu more likely to use outpatient care.

Aged 55-64 0.004 0.012 0.012 0.009 -0.011Aged 65-74 0.001 0.007 0.008 0.010 -0.014

Aged 75 and over 0.079 0.091 0.097 0.111* 0.100Can read and write -0.033 -0.045 -0.039 -0.016 -0.024Finished primary 0.020 0.003 0.012 0.027 -0.000

Junior high and above 0.035 0.006 0.016 0.011 -0.023logPCE (< median) 0.012 0.014 0.022* 0.019

logPCE (> median, marginal) 0.047 0.052 0.058* 0.046Rural 0.034

Rural Zhejiang 0.010Urban Gansu 0.077Rural Gansu 0.118***

Community FE NO NO NO NO YESF-test for all age dummies 0.62 0.80 0.93 1.21 1.15

(p-value) (0.605) (0.495) (0.429) (0.311) (0.332)F-test for all education dummies 0.80 0.75 0.69 0.25 0.19

(p-value) (0.494) (0.524) (0.562) (0.864) (0.900)F-test for all logPCE splines 3.30** 3.95** 6.70*** 4.50**

(p-value) (0.041) (0.023) (0.002) (0.014)F-test for all location dummies 3.53** 1.84***

(p-value) (0.018) (0.000)Observations 1120 1120 1120 1120 1120

Table 10. Regression for using medical service for outpatient:women Outpatient service for

women is strongly associated with incomes;

Rural Gansu more likely to use outpatient care.

Local community factors matter

% N % N2.9 395 4.5 459

(0.8) (1.0)9.3 374 5.1 367

(1.9) (1.4)10.3 249 7.3 204(2.6) (2.6)6.5 92 9.5 94

(2.8) (4.1)6.7 1110 5.9 1124

(0.9) (0.9)Standard error in Parenthesis

Table 7. The percentage of people who usemedical service for inpatient in the last year,

by age and sex

75+

Total(45+)

Men Women

45-54

55-64

65-74

Relatively few people used inpatient care; Not much difference between men and women.

Aged 55-64 0.048*** 0.052*** 0.052*** 0.052*** 0.059***Aged 65-74 0.077*** 0.085*** 0.084*** 0.079*** 0.087***

Aged 75 and over 0.035 0.041 0.040 0.042 0.051Can read and write 0.024 0.017 0.017 0.020 0.021Finished primary -0.005 -0.016 -0.016 -0.019 -0.019

Junior high and above 0.018 0.000 -0.001 -0.015 -0.012logPCE (< median) 0.013* 0.012* 0.015* 0.017**

logPCE (> median, marginal) 0.036 0.034 0.039 0.032Rural -0.015

Rural Zhejiang 0.012Urban Gansu 0.097***Rural Gansu 0.023

Community FE NO NO NO NO YESF-test for all age dummies 3.43** 3.91** 3.88** 3.85** 4.74***

(p-value) (0.020) (0.011) (0.012) (0.012) (0.004)F-test for all education dummies 0.82 0.68 0.69 1.18 1.17

(p-value) (0.488) (0.567) (0.560) (0.323) (0.327)F-test for all logPCE splines 5.69*** 4.52** 5.54*** 6.03***

(p-value) (0.005) (0.013) (0.005) (0.003)F-test for all location dummies 2.46* 1.09

(p-value) (0.068) (0.337)Observations 1105 1105 1105 1105 1105

Table 11. Regression for using medical service for inpatient: menInpatient service for men is strongly associated with incomes;

Urban Gansu more likely to use inpatient care.

Aged 55-64 -0.003 0.003 0.003 0.001 0.005Aged 65-74 0.008 0.012 0.012 0.012 0.012

Aged 75 and over 0.039 0.045 0.047 0.052 0.055Can read and write -0.024 -0.033* -0.031* -0.021 -0.023Finished primary 0.012 -0.001 0.002 0.007 0.009

Junior high and above 0.001 -0.023 -0.020 -0.024 -0.024logPCE (< median) -0.000 0.000 0.004 0.007

logPCE (> median, marginal) 0.058*** 0.059*** 0.062*** 0.060**Rural 0.010

Rural Zhejiang 0.008Urban Gansu 0.046**Rural Gansu 0.047**

Community FE NO NO NO NO YESF-test for all age dummies 0.58 0.69 0.73 0.92 0.94

(p-value) (0.628) (0.562) (0.539) (0.436) (0.423)F-test for all education dummies 0.91 1.24 1.28 0.88 1.06

(p-value) (0.439) (0.300) (0.286) (0.453) (0.371)F-test for all logPCE splines 4.82** 4.65** 6.20*** 5.91***

(p-value) (0.010) (0.012) (0.003) (0.004)F-test for all location dummies 2.61* 0.71

(p-value) (0.056) (0.890)Observations 1120 1120 1120 1120 1120

Table 12. Regression for using medical service for inpatient:women Inpatient service for

women is strongly associated with incomes;

Gansu more likely to use inpatient care.

KEY PARAMETERS OF INSURANCE

Table 4. Mean of premium of different medical insurances

Men Women Men WomenMean 289.0 337.4 18.1 18.7

(116.4) (114.6) (6.0) (6.5) = 0 6% 0% 1% 0%N 41 20 67 86

Mean 13.0 12.9(0.7) (0.7)

= 0 0% 0%N 368 340

Mean 608.1 324.3 18.2 24.1(173.3) (158.9) (3.6) (6.2)

= 0 12% 11% 18% 17%N 70 52 211 220

Mean 28.2 26.8(4.7) (4.6)

= 0 20% 22%N 267 273

Mean 495.4 318.3 20.3 21.8(127.4) (123.4) (2.1) (2.6)

= 0 5% 3% 10% 10%N 122 76 913 919

Standard error in Parenthesis "= 0" represents the number of people whose premium is zero 、

New cooperativemedical insurance

Zhejiang Urban

Zhejiang Rural

Total

Gansu Urban

Gansu Rural

Urban employeemedical insurance

Insurance premiums are very low in rural areas of Zhejiang and Gansu- 20-30 yuan per year compared to average rural annual expenditures of 3,800-7,500 RMB;

In urban areas, premiums are higher, but still affordable compared to annual expenditures of 7,500-10,000 yuan

In Zhejiang about 1 in 5 elderly persons don’t have to pay any premium; premiums are also lower than Gansu.

Inpatient Out of Pocket Shares: By Residence

Table 12. Inpatient cost for people with insurance, by urban/rural and province

Total CostMean

The share ofout-of-pocket

cost (%)

ReimbursementRate (%) N Total Cost

Mean

The share ofout-of-pocket

cost (%)

ReimbursementRate (%) N

3329.3 57.6 42.4 33 3631.6 67.9 32.1 37(658.5) (5.9) (5.9) (732.4) (5.7) (5.7)14591.7 61.2 38.8 34 9449.0 70.2 29.8 25(4844.3) (9.7) (9.7) (1316.4) (6.0) (6.0)10562.9 59.9 40.1 67 6981.1 69.3 30.7 62(3223.4) (6.5) (6.5) (995.8) (4.2) (4.2)

Standard error in Parenthesis

Total

Urban Rural

Gansu

Zhejiang

OOP cost shares are much lower in urban areas than in rural areas, reflecting the much higher insurance premiums in urban areas.OOP cost shares are much lower in Zhejiang than in Gansu.

Inpatient Out of Pocket Share: By Hukou

Table 13. Inpatient cost for people with insurance, by Hukou and province

Total CostMean

The share ofout-of-pocket

cost (%)

ReimbursementRate (%) N Total Cost

Mean

The share ofout-of-pocket

cost (%)

ReimbursementRate (%) N

4080.7 54.4 45.6 17 3284.6 65.2 34.8 53(974.1) (7.3) (7.3) (592.2) (4.8) (4.8)18165.4 35.6 64.4 14 10086.0 76.9 23.1 45(9372.0) (12.4) (12.4) (1430.0) (3.9) (3.9)13247.0 42.1 57.9 31 7351.6 72.4 27.6 98(6131.9) (8.9) (8.9) (1012.1) (3.2) (3.2)

Standard error in Parenthesis

Total

Urban Hukou Rural Hukou

Gansu

Zhejiang

The urban-rural contrast is sharper if we use the hukou distinction, especially in Zhejiang province.

Table 9. Outpatient cost for people with insurance, by urban/rural and province

Total CostMean

The share ofout-of-pocket

cost (%)

ReimbursementRate (%) N Total Cost

Mean

The share ofout-of-pocket

cost (%)

ReimbursementRate (%) N

229.4 85.6 14.4 58 180.8 92.5 7.5 131(73.1) (4.7) (4.7) (36.9) (2.3) (2.3)318.0 63.6 36.4 96 614.6 90.5 9.5 76(59.1) (9.8) (9.8) (178.1) (1.7) (1.7)293.4 70.1 29.9 154 413.0 91.5 8.5 207(46.0) (7.5) (7.5) (99.6) (1.5) (1.5)

Standard error in Parenthesis

Total

Urban Rural

Gansu

Zhejiang

OOP shares are much higher for outpatient care than inpatient care;Reimbursement rates are higher in urban than in rural areas;Reimbursement rates are higher in Zhejiang than in Gansu.

Table 10. Outpatient cost for people with insurance, by Hukou and province

Total CostMean

The share ofout-of-pocket

cost (%)

ReimbursementRate (%) N Total Cost

Mean

The share ofout-of-pocket

cost (%)

ReimbursementRate (%) N

192.0 82.6 17.4 41 201.6 92.3 7.7 148(28.1) (8.6) (8.6) (44.9) (2.4) (2.4)250.6 37.3 62.7 41 526.5 89.6 10.4 131(67.0) (9.7) (9.7) (114.5) (1.9) (1.9)231.4 53.6 46.4 82 400.5 90.7 9.3 279(46.3) (10.1) (10.1) (73.7) (1.5) (1.5)

Standard error in Parenthesis

Total

Urban Hukou Rural Hukou

Gansu

Zhejiang

Among rural hukou holders, outpatient reimbursement rates are very low; this reflects the design of NCMSUrban Zhejiang has the highest reimbursement rate for outpatient care.

Aged 55-64 -0.116** -0.115** -0.083* -0.085* -0.047Aged 65-74 -0.245*** -0.247*** -0.223*** -0.232*** -0.206***

Aged 75 and over -0.353*** -0.351*** -0.341*** -0.380*** -0.298**Can read and write -0.032 -0.051 -0.047 -0.039 -0.045Finished primary -0.047 -0.051 -0.028 -0.055 -0.040

Junior high and above -0.073 -0.071 -0.048 -0.108 -0.048logPCE (< median) -0.071 -0.044 -0.014 -0.017

logPCE (> median, marginal) 0.075 0.073 0.030 0.036Widowed 0.073 0.064 0.063

Divorced or never married 0.018 0.018 -0.014Rural 0.121*

Rural Zhejiang 0.233**Urban Gansu 0.316***Rural Gansu 0.230**

Community FE NO NO NO NO YESF-test for all age dummies 4.03** 4.38*** 4.22*** 5.39*** 4.00**

(p-value) (0.011) (0.007) (0.008) (0.002) (0.011)F-test for all education dummies 0.28 0.25 0.15 0.65 0.12

(p-value) (0.842) (0.859) (0.932) (0.588) (0.949)F-test for all logPCE splines 1.50 0.33 0.05 0.08

(p-value) (0.230) (0.718) (0.952) (0.923)F-test for all marital status dummies 0.47 3.25** 0.34

(p-value) (0.624) (0.027) (0.714)F-test for all location dummies 0.34 5.09***

(p-value) (0.713) (0.000)Observations 162 162 162 162 162

Table 15. Regression for the share of out-of-pocket cost in the totalcost of the last visit for medical service for outpatient in the last month:

men Out-of-pocket shares are strongly associated with locations.

No SES gradient is observed.

Aged 55-64 -0.030 -0.041 -0.028 -0.031 -0.027Aged 65-74 -0.114* -0.120* -0.113* -0.102* -0.131**

Aged 75 and over -0.077 -0.078 -0.041 -0.025 -0.040Can read and write 0.021 0.034 0.049 0.061 0.048Finished primary -0.161 -0.136 -0.112 -0.094 -0.091

Junior high and above -0.121 -0.079 -0.054 -0.087 -0.082logPCE (< median) 0.002 0.004 0.008 0.005

logPCE (> median, marginal) -0.082 -0.070 -0.056 -0.051Widowed -0.012 -0.026 -0.018

Divorced or never married 0.143** 0.206*** 0.040Rural 0.057

Rural Zhejiang 0.143**Urban Gansu 0.172**Rural Gansu 0.133*

Community FE NO NO NO NO YESF-test for all age dummies 1.07 1.15 1.01 1.01 1.37

(p-value) (0.367) (0.334) (0.391) (0.395) (0.257)F-test for all education dummies 1.20 0.91 0.79 1.15 0.86

(p-value) (0.317) (0.441) (0.503) (0.334) (0.467)F-test for all logPCE splines 1.09 0.75 0.38 0.33

(p-value) (0.342) (0.477) (0.688) (0.722)F-test for all marital status dummies 3.11* 1.62 0.18

(p-value) (0.050) (0.191) (0.834)F-test for all location dummies 4.55** 2.79***

(p-value) (0.014) (0.003)Observations 226 226 226 226 226

Table 16. Regression for the share of out-of-pocket cost in thetotal cost of the last visit for medical service for outpatient in the

last month: women OOP shares are strongly associated with locations.

No SES gradient is observed.

Summary: Descriptive• China achieved almost universal insurance

coverage in about 6 years• Reimbursement rates are much lower than in

industrial countries, but much higher than they have been recently in China

• The new urban and rural insurance is mostly designed to reimburse inpatient care expenses

• Recent improvements have included coverage of chronic illnesses

Summary: SES Correlations• Insurance coverage has some SES

correlations even within communities• Utilization of health services has strong SES

correlations• But not much SES correlation with

reimbursement rates, which is arguably a sign that rules apply to everyone regardless of SES

• Important community differences exist in almost all aspects, even within provinces