Private and public cross-subsidization: financing Beijing’s health-insurance reform

Private and public cross-subsidization: financing Beijing’s health-insurance reform

Health Policy 72 (2005) 41–52 Private and public cross-subsidization: financing Beijing’s health-insurance reform Ming Wu a,b,d , Ying Xin b , Huihui...

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Health Policy 72 (2005) 41–52

Private and public cross-subsidization: financing Beijing’s health-insurance reform Ming Wu a,b,d , Ying Xin b , Huihui Wang c , Wei Yu a,d,e,∗ a

Center for Health Policy, Stanford University, 795 Willow Road (152MPD), Menlo Park, CA 94025, USA Beijing University School of Public Health, 38 Xue Yuan Road, Haidian District, Beijing 100083, China c Department of Health Policy and Management, University of California at Berkeley, USA d Center for Primary Care Outcomes and Research, Stanford University, 795 Willow Road (152MPD), Menlo Park, CA 94025, USA Health Economics Resource Center, U.S. Department of Veterans Affairs Palo Alto Health Care System, USA b

e

Abstract In 1998, the Chinese government proposed a universal health-insurance program for urban employees. However, this reform has been advancing slowly, primarily due to an unpractical financing policy. We surveyed over 2000 families and evaluated the financial impacts of Beijing’s reform on public and private enterprises. We found that most state-owned enterprises provided effective health insurance, whereas most private firms did not; overall, 33% of employees had little or no coverage. On average, employees of private firms were healthier and earned more compared to public firms. Because the premium was proportional to income, private firms would pay more for insurance than the predicted health-care expense of their employees. International firms subsidize the most, contributing more than 60% of their insurance premiums to the employees of the public sector. Such an aggressive cross-subsidization policy is difficult to be accepted by private firms. © 2004 Elsevier Ireland Ltd. All rights reserved. Keywords: Health insurance; Health-care financing; Chinese economics reform; Cross-subsidization; Business ownership

1. China’s urban health-insurance reform Expanding the insured population and raising the level of coverage are two major tasks of healthinsurance reforms in countries that do not currently provide a universal coverage. Although it is a societal desire to adopt a universal and comprehensive health-insurance program, the likelihood of any ∗ Corresponding author. Tel.: +1-650-493-5000x23157; fax: +1-650-617-2639. E-mail address: [email protected] (W. Yu).

reform’s success depends largely on the economic effects on those individuals and groups involved in the resulting resource reallocation. Therefore, economic evaluation is an important part of the policy-making process. China’s employment-based urban health-insurance programs have not been able to provide adequate coverage since the late 1970s, when the government started transforming its economy from a centrally planned system to a market-oriented system. To reestablish a universal health-insurance program for urban employees, the Chinese government has conducted various experiments. Because of

0168-8510/$ – see front matter © 2004 Elsevier Ireland Ltd. All rights reserved. doi:10.1016/j.healthpol.2004.06.007

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unrealistic financing policies, however, many of those experiments have not been successful. In this paper, we report our evaluation of a proposed health-insurance reform by the Beijing city government. The purpose of this reform is to consolidate existing insurance programs into a single system, and to extend coverage to all current and retired urban employees. The proposed universal insurance program is financed through a fixed-rate payroll tax; thus, firms such as international enterprises that pay higher wages/salaries must pay more for the insurance program than do firms with lower payroll expenses. The success of the proposed reform largely depends on the level and direction of such cross-subsidization among firms. We therefore analyzed the financing policy of the reform and potential cross-subsidization between the private sector and the public sector. To evaluate the cross-subsidization, we randomly surveyed over 2000 families in Beijing; for those people who were employed, we examined income, health status, health-insurance benefits, and health-care expenditures. Then, we simulated the potential cross-subsidization under the proposed insurance plan across employer–ownership groups. The results of our study could help the city government of Beijing to enhance acceptance of the reform by adjusting its financing policy. Our study results also demonstrate the importance of economic evaluation in the policy-making process worldwide. If we are to understand Beijing’s health-insurance reform, we must first understand the changes in China’s urban health-insurance program before and after the economic reform started in 1978. 1.1. Urban health insurance before the economic reform Before the economic reform, health insurance in urban areas was provided through two state schemes: the government insurance system (GIS) and the labor insurance system (LIS). GIS covered government employees, college teachers and students; LIS covered employees in all state-owned enterprises (SOEs) and in certain community-owned (collective) enterprises (COEs). Because the state and local communities owned almost all enterprises, LIS covered over 90% of the total urban-employee population from its

establishment in 1950s through the late 1970s, when the economic reform began [1,2]. The government budgeted funds for GIS and LIS proportionally to wage and salary through a social-safety insurance fund. In each firm, a union office managed the social-safety fund. Different from a union in most countries, the union in China was an administrative branch built into each level of the government and industrial bureaus. About 30% of the health-insurance fund was pooled, and was managed at the next-higher level of the union administration. Because the government also controlled the prices of health care and medicine, both GIS and LIS were financially balanced. This balance, however, was drastically disturbed by the economic reform [3–6]. 1.2. Effects of the economic reform on urban health insurance The economic reform forced SOEs to be financially self-supporting. Thus, LIS became a strictly self-insured system through each individual firm, and its coverage depended completely on each firm’s financial status. Many SOEs could not afford the insurance coverage promised under LIS. Furthermore, many SOEs went through reconstruction, and laid off a large number of employees who thus lost their health insurance. While SOEs shrank, private enterprises expanded. To attract private investments for local economic growth and to increase employment, local governments did not require private firms to provide health insurance or pensions. Thus, social-safety programs suffered from the economic reform. How to rebuild an effective health-insurance system for the employed population under such a market-oriented economy has become one of the major challenges for the Chinese government. Certain cities have established a catastrophic health-insurance plan as supplemental insurance to assist self-insured SOEs in covering extremely expensive cases. However, SOEs that could not afford to pay the coverage under LIS were also not able to buy the catastrophic plan. In addition, many private employers are not willing to purchase catastrophic insurance, arguing that the higher wages they pay already redress the lack of benefits. There was also a strong selection bias. The firms that purchased catastrophic insurance were those that already incurred high health-care expenditures.

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For certain firms that had relatively healthier employees, catastrophic insurance was more expensive than self-insurance. Because of those factors, catastrophic insurance was not widely adopted in many cities. GIS, in contrast, was still financed through the government budget. Most changes in GIS were adopted to control the growth of health-care expenditures, such as the institution of co-payments and the placement of restrictions on expensive treatments and drugs. Therefore, GIS continued its coverage—including hospital care, for both current and retired government employees—through the economic reform. 1.3. Urban health-insurance reform The problems in urban health insurance stimulated a series of reforms. The Ministry of Health first piloted a universal health-insurance program in three mid-sized cities in 1995, then later extended the program to other cities. Although each city revised its financing policy, these programs had three common features: (1) they were managed by a local government agency; (2) they covered all urban employees, including those of government agencies; (3) they included a sophisticated financing structure consisting of personal savings accounts, a basic pooled account, a catastrophic account, and various types of co-payment and co-insurance to control over consumption of health-care services. At the end of 1998, the central government decided to expand this urban health-insurance program to all cities. To comply with the central policy, Beijing proposed its reform plan in 2001.

2. Beijing health-insurance reform The proposed Beijing insurance program would replace all existing government plans, and would extend coverage to all currently employed or retired employees. However, the proposed plan would not cover employees’ dependents or family members [7]. 2.1. Beijing’s current health insurance Beijing has a population of more than 10 million people. Similar to that in other cities, health insurance in Beijing is based completely on employment, and there are three major types of insurance programs:

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GIS, LIS, and catastrophic. The city-managed catastrophic insurance plan covers 80–90% of the total expenditures for hospital inpatient care and for treatment of any condition that cost more than 2000 Yuan over 30 days [8]. The remaining 10–20% of the total cost is shared between employer (70%) and employee (30%). 2.2. Premium collection for the proposed insurance plan Under the proposed plan, both employers and employees contribute. Employees pay 2% of their total income, including wages and other types of compensation, in the previous year. For employee contribution, there are caps on both the high and low ends. Those people whose current income is less than 60% of the city average in the previous year pay premiums based on the 60% of the city average. People whose income is more than 300% of the city average pay premiums based on 300% of the city average. Retired employees do not pay any premium. Employers pay 9% of the total payroll cost in the previous year, including wages and other types of payments. (It is not clear to us, how the government plan to measure bonuses and other types of compensation that are usually not reported.) 2.3. Personal savings account The proposed insurance program consists of two components: a personal savings account and a pooled account. Funds collected from insurance premiums are distributed between these two accounts. An employee’s personal savings account includes all of his/her own premium payment, as well as a small proportion of the employer’s contribution. The employer’s contribution to the personal savings account varies by employee age: 0.8% of the income of people aged 34 or fewer years, 1% of that of people aged 35–44 years, and 2% of that of people aged 45 or more years. The program distributes 4.3% of the city average wage to the personal savings account of retired employees who are fewer than 70 years old, and 4.8% to those aged 70 or more years. Money saved in personal savings accounts is portable across locations; if the owner moves to a location that has no similar health-insurance program, she or he can

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cash out the account. If a person dies, money left in the personal savings account is passed to his or her spouse or nearest relatives. The plan does not specify whether money transferred in this manner can be used for other purposes than health care. 2.4. Coverage under the proposed insurance plan The personal savings account pays for outpatient care, emergency outpatient visits, drugs purchased at contracted stores, and any expenditures that fall below the coverage level or that exceed the limits covered by the pooled account. The pooled account pays for expenses of hospital inpatient care and for selected expensive outpatient care, such as chemotherapy for patients who have cancer or dialysis for those with renal disease. To encourage people to seek care at appropriate facilities, the rate of co-payment varies by type of hospital. For inpatient care provided at tertiary hospitals, the pooled account pays 80% of the cost below 10,000 Yuan, 85% of the cost between 10,000 and 30,000 Yuan, 90% between 30,000 and 40,000 Yuan, and 95% of the cost that exceeds 40,000 Yuan. Employees pay the remainder of the cost, usually from their personal savings accounts. A patient’s rate of co-payment is reduced if he or she uses low-level hospitals. The payment cap from the pooled account is equal to four times of the city average annual income.

3. Methods Using our survey data from Beijing, we examined the relations between the type of business ownership and the three factors described in Section 2.5. We predicted expenses for hospitalization, estimated employers’ contributions to the pooled account, and simulated cross-subsidization across ownership groups using the proposed insurance payment plan. 3.1. Data and measurements

2.5. Cross-subsidization

We surveyed over 2000 families in a district of Beijing in May 2000, immediately before the Beijing health-insurance reform was announced. The original purpose of this survey was to collect data for a study on health-care management and insurance coverage. Using a stratified, systematic sampling method, we sampled 2064 households consisting of 7165 individuals. We first selected six of the 10 sub-districts according to the average income level (two from the high income, two from the middle income, and two from the low income); then, we randomly sampled three neighborhoods from each sub-district. In each neighborhood, households were sampled systematically. We recruited medical students at Peking University to conduct this survey through face-to-face interviews. The surveyed population contained 3016 currently employed people. After we excluded those people for whom we did not have information either on employer ownership type or insurance coverage, the final analytic file contained 2951 people.

Cross-subsidization occurs only through the pooled account, because funds distributed to personal accounts are never pooled. Three factors determine the level of cross-subsidization: employee income, age, and health status. Firms that pay higher wages contribute more to the pooled account. Because an employer’s contribution to personal savings accounts increases with employee age, firms that have more old and/or retired employees contribute less to the pooled account. Firms that have healthier employees incur lower costs for health care; in turn, more money from their contribution to the pooled account is used for employees of other firms. An employer’s willingness to adopt the reformed insurance program undoubtedly will be influenced by the level and direction of cross-subsidization.

3.1.1. Survey forms The survey comprised four forms. The first collected information about the family, including the number of family members living in the house, total family income, average monthly expenses, and so on. The second form collected information for each adult in the family, including common demographics, employment type, health insurance, health-care utilization, and health-care expenses. The second form also asked whether the surveyed adult had been ill during the past 2 weeks. If he or she responded affirmatively, then we collected detailed information about the health problem, health care obtained, and health-care expenses in the third form, the “2-week sickness” form. The second form also asked whether the person had been hospitalized during the past 12 month; for

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people who responded affirmatively, we used the fourth form, the “hospitalization” form, to collect information about reason for hospitalization, type and location of the hospital used, total expenses, insurance payment, out-of-pocket expenses, and so on. 3.1.2. Health-care expenditure We collected only hospital expenditures from the survey; those expenditures reflected the total payment for the admission, including both insurance and out-of-pocket payments. Because both GIS and LIS are managed through employers, hospitals usually have no direct financial transactions with employers for health-care payment. Except for emergency admissions, patients are required to pay a deposit equal to the projected total expenses for treatment, both on admission and before any additional expensive surgery or treatment. People who have insurance are expected to pay for their care in advance, and then to receive reimbursement from their employers after treatment had been completed. Some employers are willing to pay the deposit and to clear the payment with employees later. Because of such a payment structure, patients usually know their total hospital expenses, as well as their share of the cost. A small number of the respondents in our survey—especially those who had never used hospital care—did not know their insurance coverage. For those people, we presumed their coverage level based on the type of insurance plan (e.g. catastrophic insurance or GIS). There were 80 respondents who did not know neither their insurance plan nor their coverage level; we excluded them from the study. 3.1.3. Average income by ownership group To evaluate employers’ contribution to the pooled account, we estimated average income per employee for each ownership group. Because we asked only total family income in the survey, we could not distinguish the income difference between the members in a family who worked for firms under different types of ownerships. To estimate the average income of each ownership group for the entire sample, we first calculated an average income under each type of ownership by using the families in which the employed member(s) worked for the same type of employer. Using the average incomes calculated from those selected families, we then calculated an income index for each

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ownership group that reflects the deviation of average income of each ownership group from the overall average. Finally, we estimated the average income of each ownership group for the entire sample, by multiplying the average income of the entire sample by the income index of each ownership group. To validate our income estimates, we compared our estimates with the statistics published by the Beijing Statistic Bureau. In 2000, the average wage/salary for the Beijing public sector, including both government agencies and SOEs, was 1369 Yuan, whereas that from our data was 1225 Yuan (government = 1441 Yuan, SOE = 1102 Yuan); the average wage/salary for private firms in Beijing was 1480 Yuan and our estimate was 1582; for international firms, the Beijing average was 2468 Yuan and our estimate was 2754 Yuan. Because the Beijing statistics report only wage and salary and our reported income includes bonuses, our estimates should be higher, especially for private firms. Overall, our estimated average incomes across ownership groups are consistent with the reported statistics in Beijing. 3.1.4. Ownership classification We classified employment into six categories by firm ownership: government agencies (including schools and universities), SOEs, collectively owned enterprises, domestic private enterprises, self-employed, international enterprises. Some enterprises in the international group might also have domestic partners (both private and public); however, those firms usually were managed by foreign investors and obtained the benefits thereof, such as tax reduction as international firms. 3.1.5. Coverage of health insurance We used three classification levels to reflect insurance coverage in this study: high, low, and no coverage. High-level coverage was defined as covering at least 75% of hospital expenditures; low-level insurance covered anything below that level but greater than zero. We used 75% as a cut-off point because both GIS and catastrophic insurance covered at least 80% of hospital expenditures. Therefore, the high-coverage group included all government employees under GIS and all employees who had catastrophic insurance. Most employees in the low-coverage group worked for enterprises that could not afford catastrophic

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insurance. These firms were thus unlikely to provide any significant coverage for hospital inpatient care by themselves. 3.1.6. Health status We assigned health status based on the chronic diseases that respondents reported having. We defined chronic disease as any disease that required care for more than 6 months. Because health status was self-reported, we did not classify specific diseases, as such groupings might not be accurate. 3.2. Analysis We carried out the analysis in three steps. First, we classified employment into groups by the firm’s ownership and examined variations in age, gender, income, health-insurance coverage, and health status across those ownership groups. Then, we investigated differences in employee health status across ownership groups. Third, using a simulation model of the proposed health-insurance plan, we predicted hospital expenses and employer contribution for each ownership group and analyzed cross-subsidization. 3.2.1. Health status To estimate the difference in health status between employees of the public versus the private sector, we examined the prevalence of chronic diseases. We first classified patients into two groups—those who had and those who did not have any chronic disease—and examined the differences across employer–ownership groups. We then used a Probit regression model to control for age and gender while examining whether the likelihood that a person had a chronic disease was correlated with the type of employer ownership. We controlled for the cluster effect of members from the same family and used the robust estimating method in the regression. We divided employees’ age into four groups: fewer than 30 years, from 30 to 49 years, from 50 to 64 years, and 65 or more years. 3.2.2. Cross-subsidization We simulated cross-subsidization on only hospital expense for the employed people because it would be mostly paid from the pooled account. We first predicted average hospital expense per person for each ownership group, using a two-part regression model.

We then calculated the average premium per person paid by each ownership group using the proposed formula. We compared the mean hospital expense and employer contribution of each ownership group to that of the entire sample. Because we did not have data on person-level income, we did not adjust the contribution to the pooled account for the age differences. Including the age effects will increase the level of cross-subsidization although the amount is trivial. We reported the deviation from the sample mean in percentage for each ownership group. To simulate gains and losses, we adjusted the employer contribution proportionally so that the total contribution was equal to the total predicted hospital expense. We then calculated the gain or loss by subtracting the total expense by the total contribution for each ownership group, and reported the percentage of gain or loss by dividing the total gain or loss by their total contribution. Because hospital utilization and expense would be affected by insurance status, we set the insurance status to the high level for everyone when predicting hospital expense under the proposed insurance program. The two-part regression model is a common method used to estimate health-care expenses [9]. In part 1, we used a Probit model to estimate the probability of each respondent’s being hospitalized in a given year. In part 2, we estimated hospital expense during the past 12 months from the survey. The predicted hospital expense for each person was equal to the predicted value (expense) from the part-2 model multiplied by the predicted probability of being hospitalized from the part-1 model. For the part-2 model, we first estimated the coefficients using only those people who had been hospitalized during the past 12 months. We then predicted hospital expense for each person using the estimated coefficients. Because the hospital expenses had a skewed distribution, we took a log transformation of hospital expenses for the regression (the semi-log model). When predicting hospital expense in the part-2 model, we retransformed the predicted log expenses into raw values (Yuan) by the smearing method described by Duan [9] and Manning [10]. We tested the regression model for heteroscedasticity and established that the smearing method was appropriate for the retransformation [11]. In the right-hand side of the two regression models, we included age (18–29, 30–49, 50–64, and >64

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years), gender, number of chronic diseases (0, 1, 2, and >3 diseases), level of insurance coverage (high, low, no), and average family income per person. We used the largest group in each variable (age ≤ 30, male, 0 chronic diseases, and high coverage) as the reference group in the regression. We performed the regression analysis using the STATA software, Version 8.0.

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employer–ownership groups. Beijing, the capital of China, houses many government agencies and colleges. Therefore, it is not surprising that 26% of the 2951 employees in our sample worked in the government sector. SOEs still dominated Beijing’s labor force; they accounted for 45% of the sampled working population. Nearly 20% of the sampled employees worked at a privately held enterprise. Almost one-half of the employees were female; the exception was among employees of domestic private enterprises and the self-employed, of whom about 40% were female. On average, employees who worked in government agencies or SOEs were about 7-year older than were those in the private sector (both domestic and foreign enterprises). Young employees (age 29 or fewer years) accounted for about one-half of the total employees in international firms and for 42% in domestic private firms, but for only 16% of those in the public sector. On average, employees in private enterprises earned more than did those in government agencies and SOEs. Government employees and the self-employed earned

4. Results We found substantial differences in age, income, and health status across employer–ownership groups. The results of our simulation suggest that the proposed universal coverage would require substantial contribution from the private sector, especially from international firms. 4.1. Demographic differences Table 1 lists differences in demographics, income, and prevalence of chronic disease across

Table 1 Demographics, income, insurance coverage, and health status of the study sample by enterprise ownership

No. of people Percent

Gov

State

Collect

Private

Self

Intl

Total

770 26.1

1335 45.2

277 9.4

183 6.2

211 7.2

175 5.9

2951 100.0

Female

49.7

47.3

50.5

38.3

39.3

50.9

47.3

Mean age Age distribution (%) <30 30–49 50–64 >65

41

40

38

34

36

33

39

15.7 69.2 13.5 1.6

16.2 74.4 9.4 0.0

22.4 72.2 5.1 0.4

41.5 54.6 3.8 0.0

34.1 59.2 5.2 1.4

49.1 47.4 3.4 0.0

21.5 68.9 9.1 0.5

Monthly family income per person Mean 818 STD 461 Income indexa % w Chronic disease Insurance High Low None a

1.02

674 425 0.78

713 626 1.10

879 778 1.12

777 772 1.00

1093 783 1.95

760 549 1.00

21.0

16.0

13.7

5.5

10.9

8.0

15.6

90.8 1.9 7.3

74.8 17.2 8.0

50.9 18.8 30.3

15.8 12.0 72.1

12.8 2.4 84.8

49.1 23.4 27.4

67.1 12.3 20.5

coverageb

Income index was calculated by dividing the average income per person in each ownership group by the average income per person of the entire sample. b High: insurance covered at least 75% of the expenses for hospital inpatient care; low: insurance covered anything below the high coverage; none: no insurance coverage.

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the same amount, which was also close to the sample average. People who worked in international enterprises earned the highest income—almost twice of the sample average. The 45% who were SOE employees earned the lowest income—their average income was only 78% of the sample average. 4.2. Insurance coverage Table 1 also summarizes health-insurance coverage by employer–ownership group. Over 90% of the government agencies and 75% of SOEs provided high-level health insurance, whereas only 50% of collectively owned and international firms did so. Seventy-two percent of domestic private enterprises provided no health insurance. About 85% of self-employed people had no insurance. Although international firms paid the highest wages and salaries, 28% of these firms did not provide any health insurance. Overall, 67% of the sample had high-level, 12% had low-level, and 21% had no insurance coverage. 4.3. Health status There was a large variation in health status across the employment–ownership groups (Table 1). At least one chronic disease was self-reported by 21% of employees in the government group, 16% in the SOE group, 11% among the self-employed, 8% in international firms, and only 6% in domestic private firms. Table 2 shows the coefficients and statistics of the

Probit regression model. The regression analysis indicated that the probability of having a chronic condition is highly associated with age. After controlling for age and gender, however, we found that employees in the government sector (the reference group in the regression) were more likely to have chronic diseases. The regression coefficients were statistically significant at the 5% or lower level of significance for all ownership groups except the collectively owned firms. 4.4. Projected cross-subsidization under the proposed policy Our simulation indicated that, under the proposed health-insurance plan, private firms would subsidize substantially the public sector (i.e. government agencies and SOEs). The predicted average hospital expense of international firms was more than 30% lower, and the predicted average hospital expense of government employees was 30% higher than that of the average of the entire study population (Fig. 1). The premium, however, varied in the opposite direction. International firms paid almost twice the total average, whereas SOEs paid 20% less than the average (Fig. 2). Our simulation indicated that, on average, international firms would spend less than 40% of their payment, private firms would spend about half of their payment, and government agencies and SOEs would spend from 20 to 30% more than their payment (Fig. 3).

Table 2 Estimated regression coefficients expressed in change of probability of having any chronic disease

Age 30–49 Age 50–64 Age >65 Female State Collect Private Self International

dF/dxa

z

P > |z|

95% Confidence interval

0.17 0.51 0.68 −0.01 −0.03 −0.04 −0.09 −0.05 −0.05

8.38 11.46 6.02 −0.56 −2.18 −1.68 −3.41 −2.08 −1.87

0.000 0.000 0.000 0.579 0.029 0.094 0.001 0.038 0.061

0.14 0.42 0.50 −0.03 −0.06 −0.07 −0.12 −0.09 −0.10

0.19 0.60 0.86 0.02 0.00 0.00 −0.06 −0.01 −0.01

Model—Probit: the reference group is government employees, age <30, and male; dependent variable: indicator of having any chronic disease. a Predicted change in probability of having any chronic disease for each of the indicator variable.

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Fig. 1. Average hospital expense per person predicted by the two-part model: deviation from the total mean.

Fig. 2. Average premium per person proposed by the formula: deviation from the total mean.

5. Discussion The significant differences in employee income, health status, and age between public and private

enterprises in Beijing reflect a unique feature of financing social-safety programs during the transition from a centrally planned to a market-oriented system. When the economic reform forced SOEs to compete

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Fig. 3. Percent of gain (positive) or loss (negative) for each type of employer ownership (percent gain (or lose) = (total expenditure − total contribution)/(total contribution)).

with private enterprises on the market, labor and capital started flowing between private and public sectors. Since private enterprises usually are more efficient and profitable than are public enterprises, they are capable of paying higher wages and salaries and thus tend to recruit younger, healthier, and more skilled employees. Although some private employers do not provide health insurance, younger and healthier people often prefer higher income to better insurance benefits. This adverse selection has drained the healthier cohort from the risk pool of GIS and LIS. Thus, the public sector must support almost all retired employees and a higher proportion of those current employees who need health care. How to correct such imbalanced distribution of social responsibility between private and public enterprises is a challenge for policy makers and the society at large. The proposed insurance plan is one of the actions taken by the government to correct such imbalance. The proposed insurance plan would significantly improve the level of risk pooling and would re-

dress the imbalanced social responsibility. However, its financing policy, which requires substantial cross-subsidization from private enterprises to government agencies and SOEs, may be too aggressive to be accepted by private firms—particularly by international firms. Our estimates did not include retired employees due to lack of information on types of ownership of former employers. The proposed insurance plan, however, covers all retired people as well. Because almost all retired employees formerly worked at either government agencies or SOEs, the amount of cross-subsidization from private enterprises to government agencies and SOEs would be much larger than that we estimated. Our data suggested that including retired population would at least double the simulated contribution of international firms. A request that a firm to pay three or four times their expected health-care expense for an insurance program is unlikely to be accepted easily. For example, an international firm could argue that it is willing to provide the same insurance coverage through a commercial

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insurance firm, which could reduce its insurance cost substantially. In the long run, however, the differences in income, health status, and age between the private and the public sectors will decline. The proportion of old and retired employees will decrease in the public sector and increase in the private sector. Hence, a short-term policy to smooth the cross-subsidization may be feasible both financially and politically. One way to ameliorate the economic effects of the insurance reform on private enterprises would be to adjust premiums temporarily by the average health status (risk) of each firm’s employees. The purpose of this method, however, should not be to adjust the premium such that the total contribution is equal to the expected total expense of each firm. Such an approach would lead the insurance program back to a self-insured scheme. One possible method is to collect a portion of the premium (e.g. 50%) based on health status, and to reduce that portion gradually over a period of time such as 10 years. After 10 years, the differences in health status and income across ownership groups probably will be much smaller than they are now. Another possible policy adjustment to reduce the disproportionate financial burden on private enterprises is for the government to subsidize older and retired employees by using general tax revenue. The rationale of such a policy would be to shift specific burdens from the payroll tax to other taxes, such as sales or property tax. The difference between sales tax and payroll tax is that sales tax will immediately transfer the cost to consumers, whereas the money collected through the payroll tax will be absorbed by employers in the short run, then be passed to employees through reductions in wage increase, or to consumers through price increase in the long run [12,13]. Another difference is that sales tax can be designed to target the wealthy population directly, whereas any payroll tax would exempt those people whose income is not reflected by wages or salaries. The proposed reform policy might also have a short-term effect on the local economy. It might slow capital flow, especially of foreign investment into Beijing. The costs of doing business and of living in Beijing are already higher than those in many large cities in China. When regions compete for private investment, the proposed health-insurance policy could

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put Beijing at a disadvantage. In the long run, when the urban health-insurance policy mandated by the central government is implemented across the nation, international enterprises will have to cover health insurance in every city, limiting the effect of Beijing’s health-insurance reform on foreign investment in the capital city. A similar pattern could be extended to global competition. The gap in labor costs between developed and developing countries is narrowing with improvement in social benefits and rising income. Once the reformed insurance program is established, another big challenge will loom: how to manage the delivery system. Almost all urban health-insurance programs use the fee-for-service method for their payment. Although a single-payer system has strong power to control prices, the experiences of many developed countries show that a fee-for-service system may not lead to efficient use of limited health-care resources, and total expense may still increase with controlled prices. For example, it has been commonly observed that hospitals in China aggressively promote profitable services regardless of the effectiveness of those services [14].

6. Limitations Our results have limitations. We conducted our survey in only one district. We compared our data with the distribution of employment ownership in 2000 Beijing statistics [15]. We found that 64.3% of the general Beijing population, versus 71% in our sample, worked for either government agencies or SOEs. Because our sample contained more people who worked for the public sector, the cross-subsidization from private to public enterprises in our sample is stronger than it would be for the entire city population. Similar as other survey data, the reported total family income could be lower than the actual income, usually happens in high-income families. Thus, our estimated cross-subsidization could be lower than the actual level. However, employers also have incentive to underreport their total labor expense, particularly the bonuses. Hence, the employer reported total payroll cost would be close to the total reported income by employees. Another limitation is that the sample size for the simulation analysis was small. In the second part of

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our two-part model, only 73 surveyed people had been hospitalized during the last 12 months. A larger sample would provide a more reliable economic forecast. Besides, the health-status measure used in this study was simple. Nonetheless, self-reported chronic disease has been shown to be a good predictor of hospital use and health-care expenses. Our part-1 model showed that the three disease indicators were all positive and statistically significant at the 5% level (data are not reported).

7. Conclusions The proposed health-insurance reform in Beijing reflects the societal desire to revamp the health-care financing system. The sustainable high rate of economic growth in China during the past two decades makes it financially possible to establish such a comprehensive insurance program. However, the proposed plan would place a sharp cost-increase burden on the private sector, especially on international firms. Such a dramatic cost increase, accounting for at least 5% of such firms’ total labor costs, is difficult to be accepted. In many cases, the success or failure of a reform is due not to principles, but rather to financial feasibility. Because most of the Beijing insurance reforms lie in resource reallocation, increasing the period over which the reform is instituted might well reduce the burden on those who would contribute (or lose) most heavily. Overall, the insurance reform would improve the risk pooling and the imbalanced financial responsibility on social-safety programs—outcomes consistent with societal desire.

Acknowledgements This study was supported by the Fogarty International Center, U.S. National Institutes of Health and

the Center for Health Policy, Stanford University. We thank Lyn Dupré for editing this manuscript.

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