OSIPP Discussion Paper: DP-2016-E-007

Health insurance coverage and firm performance: Evidence
using firm level data from Vietnam
July 6, 2016
Hiroyuki Yamada†
Faculty of Economics, Keio University

Tien Manh Vu
International Research Fellow of the Japan Society for the Promotion of Science
Osaka School of International Public Policy, Osaka University[Key words] Health insurance, Medium and large-scale firms, Propensity-score matching,
Vietnam[JEL Codes] D22, I13, I15, I18, O25[Abstract]
In literature, there is limited direct evidence regarding the effect of health insurance coverage on
firm performance and worker productivity. In this paper, we study the impacts of healthinsurance on medium and large-scale domestic private firms’ performance and productivity in
Vietnam, using a large firm level census dataset. We deploy propensity-score matching methods,
and find statistically positive health insurance effects on both aggregate profit and profit per
worker for both complying and non-complying medium and large-scale firms. Given the fullsample results, we recommend an improvement in government monitoring as one of theimportant policy options to induce medium and large-scale firms to contribute to healthinsurance premiums for their employees.

†Corresponding author: Hiroyuki Yamada.

2–15–45 Mita, Minato-ku, Tokyo 108-8345, JAPAN.
Tel: +81-(0)3-5427-1271. E–mail: hyamada@econ.keio.ac.jp[Acknowledgments] We would like to thank Yasuharu Shimamura and Koji Yamazaki for theirhelpful comments. This research was supported by the Japan Society for the Promotion of
Science [Grant-in-Aid for Young Scientists 25780163].

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1. Introduction
How to achieve universal health coverage has become an important policy issue inadvanced, emerging, and developing countries alike. For instance, the World HealthOrganization’s (WHO) flagship publication, the World Health Report 2013, focuses entirely on“research for universal health coverage” (WHO 2013). The World Bank also released a report
titled “Going universal” (Cotlear et. al. 2015).
Vietnam is not an exception, and the Law on Health Insurance (enacted in 2008) has
proposed a grand design and time line to achieve universal health insurance coverage by 2014.
However, the speed of coverage expansion has recently decreased, and the coverage rate was
66% in 2011 (Vietnam Social Security (VSS) 2012). Moreover, in April 2013, the Viet Nam
News (Viet Nam News 2013:05/24/2013) reported that the newly ratified government proposal
demonstrates their changed plan to cover about 80% of the population by 2020.
One of the bottlenecks against universal health coverage in Vietnam is the low coveragerate among employees of domestic private firms. This group is one of the compulsory groups as
defined by the government and has to be provided with health insurance through the domestic
private firm they work for. However, compulsory does not mean legally enforceable, and thecoverage rate remains at 53.4% in 2010 (VSS 2011): there were 11.9 million targeted workers intotal, but only 6.3 million workers were covered by health insurance. The contribution rate tohealth insurance was 3% of the monthly gross salary (2% by the employer and 1% by theemployee) until 2009, and was increased to 4.5% (3% by the employer and 1.5% by theemployee) in 2010.

2

There are various reasons stemming from various stakeholders on why the healthinsurance compliance by domestic private firms is far from universal. For instance, thegovernment’s ability to enforce the laws is perceived as weak.1 Some employers might choose
not to provide health insurance to save the money spent on the contribution to health insurance
premium. Since the borrowing conditions are not flexible, and accessibility to firm loans is noteasy in Vietnam, keeping the unpaid health insurance premium could be a solution to
immediately pump more cash into their business. Alternately, employees might be willing to
avoid deduction of the contribution to the health insurance premium from their salaries or might
think health insurance is not useful.2
On the other hand, there are reasons why employers are willing to act as health insurance“agents” for their employees (O’Brien 2003), regardless of the government’s weak monitoring
ability. Particularly, health insurance may contribute to firms’ and workers’ productivity, as
healthy workers are usually more productive than unhealthy ones. Since workers with healthinsurance may be more likely to get needed treatment for illnesses and injuries, those with healthinsurance may be less likely to miss work or miss fewer days of work when they do fall ill.
Given this background, the question whether complying with the health insurance related
laws makes complying firms better off or not is ultimately empirical. Surprisingly, there isalmost no direct evidence regarding the effect of health insurance coverage on firm performanceand worker productivity (O’Brien 2003). Hence, our paper quantifies the effects of complying
1

For instance, the reports of VSS (2010, 2011, and 2012) do not mention at all penalties in the case a firm does notobserve the Law on Health Insurance. Moreover, it is not very clear who is in charge of auditing private firms.
2
For example, this could be because of the fear that getting reimbursed by health insurance agencies is difficult.
Conversely, this could be because of discrimination in terms of public clinic/hospital treatment against healthinsurance holders. The existence of a voluntary paying system gives priority to patients who pay higher fees in orderto get faster access to health services in public clinics/hospitals. The long queue for health checks for healthinsurance holders with limitedly available facilities and health service prevents employees from holding healthinsurance.

3

with the health insurance related laws on firm profit and productivity using a large-scale datasetof domestic private firms in Vietnam.
We believe this study makes a significant contribution to the existing literature because
many advanced countries adopt employment-based health insurance, and many developing andemerging countries that consider expanding health insurance coverage mimic the mechanism.
Vietnam is one of the leading countries, among developing and emerging, working rigorously
towards universal health coverage, including employment-based health insurance. Therefore, ourpaper provides an informative picture for the case of a developing or emerging country
introducing a similar insurance system.
We use the Vietnamese Enterprise Survey (VES) to conduct the analyses. In the survey,
the General Statistics Office of Vietnam (GSO) has collected information on economic activities
annually since 2001. Specifically, we use cross section data of 2009 because the amount ofcontribution by a firm to health insurance for employees is available only in the 2009 dataset.3
Hence, we use these data to conduct propensity-score matching (PSM). Another feature of ouranalysis is its focus on medium and large-scale firms. This is because medium and large-scale
firms provide more stable employment over longer periods than small and micro firms.
Additionally, all domestic private firms with at least 30 employees were surveyed in the VES
2009, implying that we have a census of medium and large-scale private domestic firms in
Vietnam, which mitigates sampling biases.
We find positive health insurance effects for both aggregate profit and profit per worker
for complying and non-complying medium and large-scale firms. By industry, we find similar
3

In all other years, only the sum of the contribution amounts to health insurance, pension, and unions is available,
which makes it difficult for us to judge whether a firm indeed contribute to health insurance premiums for its
employees.

4positive effects in the construction and wholesale/retail sectors, except insignificant influence inthe manufacturing sector.
The rest of this paper is organized as follows: in section 2, we briefly describe the healthinsurance system in Vietnam; section 3 depicts empirical strategies; section 4 explains the data
and reports the first stage probit results; in section 5, we discuss the estimation results; andsection 6 concludes the paper.
2. Background: brief description of the health insurance system in Vietnam and healthinsurance scheme for non-state owned enterprises
For health insurance, the Ministry of Finance and the Ministry of Health (MoH) take theinitiative, along with the government, and VSS is a governmental policy implementing agency.4
Under VSS, the provincial social security offices are followed by the district ones. Under theprovision of district social security offices, pay-agents and collection agents are employed. Inorder to give management advice, the provincial health departments of MoH work together with
provincial social security offices. District-level health facilities are also expected to cooperatewith provincial and district social security offices.
The foundations of Vietnam’s health insurance system were established between 1992
and 1998 in order to achieve improve the health of the population. Figure 1 presents the timeline
and the roadmap of health insurance with universal coverage. As for health insurance forworkers of private domestic firms, Decree No.299/HDBT was issued by the Council of Ministers
in 1992, aiming to cover workers at state owned and non-state owned enterprises with more than
10 workers, as well as pensioners, socially disadvantaged people, and staff of international

4

See Matsushima and Yamada (2014) for the more detailed description.

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representative organizations in the country. In 2005, Decree No. 63/2005/ND-CP was introduced
for the expansion of compulsory enrolment of workers from non-state owned companies withless than 10 employees. Therefore, these two decrees stipulate all the workers of non-state owned
companies, particularly the domestic private firms being in the compulsory group.
One of the notable characteristics of the health insurance system for workers at non-state
owned enterprises is that its registration system is individual-based. This means that only theworkers are covered by the health insurance provided by the firms, but their family members arenot. During the studied period, until 2009, the contribution rate to health insurance was 3% of thegross income: 2% by the employer and 1% by the employee.
The insurance is effective when the insured are provided with medical care at the healthfacility whose name appears on his/her health insurance card and at higher-level health facilities
to which he/she is referred. Patients can choose to register at a health facility of their choice,within the given options by the government (Ministry of Health 2009). In 2009, the co-payments
were 20% for a wage earner when he/she was treated at the medical facility where registered.
Many drugs are covered by health insurance, and patients can obtain these drugs at the healthfacilities at which they are registered. Since health insurance only applies to the purchase ofdrugs in the hospital where the insured are registered, in many cases, patients cannot obtain the
drugs that they need. When patients purchase drugs from a private pharmacy, the costs must becovered out-of-pocket (OOP).
If the insured prefer to be treated at other health facilities, they must pay the hospital
directly, and the OOP costs will be reimbursed later at their place of residence, except inemergency cases. In the case of an emergency, treatment will be given free of charge.

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3. Empirical strategies
In this section, we estimate the impact of firms’ complying with the health insurance
related laws on firm performance and productivity, using PSM methods. We estimate averagetreatment effect on the treated (ATT) and average treatment effect on untreated (ATU). ATT
computes the average difference in the outcomes of the firms complying with the healthinsurance related laws with and without health insurance provision. ATU computes the average
difference in outcomes of the firms not complying with the health insurance related laws withand without health insurance provision.
The formula for ATT is given by:
ATT = E(𝑦1𝑖 − 𝑦𝑖 |𝐷𝑖 = 1)
= E(𝑦1𝑖 |𝐷𝑖 = 1) − E(𝑦0𝑖 |𝐷𝑖 = 1),(1)where E(∙) denotes an expectation operator, 𝑦1𝑖 is an outcome of interest for a firm i with healthinsurance provision to the employees, 𝑦0𝑖 is the outcome of the same firm without healthinsurance provision to the employees, and 𝐷𝑖 is a treatment indicator equal to 1 if the firmcomplies with the health insurance related laws (contributes to health insurance premiums for theemployees) and 0 otherwise. The fundamental problem with estimating equation (1) is that it is
impossible to observe the outcome of firms with health insurance provision for the employees
had they not provide health insurance, that is, E(𝑦0𝑖 |𝐷𝑖 = 1). Therefore, with observational data,
one may be inclined to simply compare outcomes between firms with health insurance provisionand those without. However, such an analysis will likely result in biased estimates if thefollowing does not hold:7

E(𝑦0𝑖 |𝐷𝑖 = 1) = E(𝑦0𝑖 |𝐷𝑖 = 0).

(2)

For our primary estimator, we use PSM, introduced by Rosenbaum and Rubin (1983),
with added controls to eliminate the bias because equation (2) does not hold. PSM relies on anassumption of conditional independence, where, conditional on the probability of firmcomplying with the health insurance related laws given observable covariates, an outcome ofinterest in the absence of treatment, 𝑦0𝑖 , and complying with the health insurance related laws, 𝐷𝑖 ,are statistically independent. This leads to:E(𝑦0𝑖 |𝐷𝑖 = 1, 𝑝(𝑥𝑖 )) = E(𝑦0𝑖 |𝐷𝑖 = 0, 𝑝(𝑥𝑖 )),(3)

where 𝑝(𝑥𝑖 ) denotes the probability of the firm contributing to health insurance premiums for theemployees given characteristic x, which is defined as:
Pr(𝐷𝑖 = 1|𝑥𝑖 ) = 𝑝(𝑥𝑖 ).

(4)

Therefore, PSM eliminates the bias that might otherwise result from the selection of observed
characteristics.
Another important assumption of PSM is the common support condition, which requires
substantial overlap in covariates between firms complying with the health insurance related laws
and those not, so that firms being compared have a common probability of being both complying
or not.
If these two assumptions are fulfilled, the PSM estimator for ATT can be specified as themean difference of the firms contributing to health insurance premiums for the employees,
matched with those not who are balanced on the propensity scores and fall within the region ofcommon support, expressed as follows:8

𝐴𝑇𝑇𝑃𝑆𝑀 = E{𝑦1𝑖 |𝐷𝑖 = 1, 𝑝(𝑥𝑖 )} − E{𝑦0𝑖 |𝐷𝑖 = 0, 𝑝(𝑥𝑖 )}. (5)This PSM estimator yields consistent estimators of the ATT if covariate x properly characterizes
the firms providing health insurance. Therefore, selection of x is important. It is recommended
that all factors affecting the decision on providing health insurance and outcomes be included(Heckman et. al. 1997, Caliendo and Kopeinig 2008). With similar analogies, we can estimate
𝐴𝑇𝑈𝑃𝑆𝑀 .
A key limitation of the PSM method is that if unobservable factors affect the decision ofcontributing to health insurance premiums for employees, estimated PSM estimators may bebiased by the selection of those unobservables (Smith and Todd 2005). CEO’s characteristics,
which are not available in the data, may play an important role in decision on health insurance
provision. Alternatively, it is virtually impossible to control for all relevant unobservables. We
therefore test whether unobservables affect estimated results using the sensitivity tests proposedby Rosenbaum (2002).
4. Data
We use the data provided by the Vietnamese Enterprise Survey (VES). Since 2001, theGeneral Statistics Office of Vietnam (GSO) has collected information on the economic activitiesof the preceding year of each business identity countrywide annually. Although the sampling
methods are different for each year for private firms, GSO has continued to conduct a census of
all private firms with more than 30 employees between 2000 and 2009. There are several
complex sampling criteria in 2009 data if the number of employees is less than 30. First, given
the rapid increase and the large number of firms, 15% random sampling was conducted for
private firms with less than 30 employees in Hanoi and Ho Chi Minh provinces. Second, 15%

9

random sampling was conducted for private firms with less than 10 employees. Third, in 18
provinces with less than 1,000 firms, a census was conducted regardless of firm size. Fourth, acensus was conducted for the following sectors: agriculture, forestry, aquaculture, transportation,
hotel, tourism, finance, credit, and insurance. We attempted constructing the corresponding
weights, but it was impossible to come up with a convincing set of weights. Therefore, we
decided to use only the census of firms having more than 30 employees. By using this sample,
our focus is the effects of health insurance on medium and large-scale firms’ performance andproductivity.
The data set contains information on the total annual contribution amounts to pension, healthinsurance, and trade-unions. However, the breakdown of these categories is only available in2009 data. That is, only 2009 data includes the information on whether a firm really contributed
to health insurance premiums for its employees. Therefore, we exclusively use the 2009 data. If a
firm reports a positive amount contributed to health insurance premiums for employees on thebalance sheet, that firm is included in the treatment group. On the other hand, if a firm reports nocontribution, the firm is included in the control group.5
We define a domestic private firm as a firm not having partial capital from the state or
foreign affiliates. We also exclude collective business firms. Additionally, VES contains general
information about domestic private firms, such as type of economic activities, profit, output,
employment, assets, and liabilities. This information comes directly from the balance sheet. After
deleting outliers and observations with missing crucial information, the total sample size of the5

The problem regarding grouping is tackled in the conclusion section.

10

domestic private firms whose number of employees is more than 30 is 18,215.6 The number ofcomplying firms is 10,827 and that of non-complying firms is 7,388.
As outcome variables, we use profit after tax deduction and profit after tax deduction per
employee. Since the profit could take a negative value, we did not log the profit variables. The
unit of measurement is million Vietnamese dong (VND).
As regressors for the first stage probit, we include the debt-asset ratio, log of capital, log of
the number of employees, as well as 23 industry dummies and 63 province dummies.7
The descriptive statistics of outcome variables and regressors in the first stage probit are
shown in Table 1. The average profit after tax deduction is VND 746.5 million (i.e., USD
43,748.5 in 2009 nominal terms).8 The average profit after tax deduction per employee is VND
6.3 million (USD 369.5). These values appear small because there are numerous firms withnegative profit after tax deduction. Indeed, more than 10% of the firms run accounting deficits.
In the sample, 59.4% of the firms contribute to health insurance premiums for their employees.
In other words, more than 40% of the firms do not comply with the health insurance related laws.
The average number of employees is approximately 74 (= exp(4.3)), while the average capitalstock is VND 13,696 million (= exp(9.525)). The average debt-asset ratio is 5.568, with a medianjust below 2.
Table 2 reports the unconditional differences in outcome variables and regressors in the firststage probit. Note that outcome variables and firm characteristics are significantly different at themean between the group of complying firms and that of non-complying firms. In all the variables,
6

The original census of private domestic firms with more than 30 employees is approximately 25,000.
The list of the 23 industries and the sample size for each are shown in Appendix 1.
8The official exchange rate in 2009 (annual average based on monthly averages) was VND 17,065.1 per USD(World Bank 2015).
7

11

the former group has higher values than the latter, and the differences are large. However, it isunclear in Table 2 whether this reflects favorable profit impacts of health insurance or the exante attributes of complying firms that make them better off than non-complying firms,
irrespective of health insurance.
Table 3 reports the estimation results of the first stage probit estimation. The binary
dependent variable is equal to 1 if a firm contributes to health insurance premiums and 0
otherwise. We emphasize that the objective of this first stage probit is to balance the important
observable covariates underlying health insurance provision between firms complying withhealth insurance related laws and those not complying, not to establish causal relationships
between covariates and contribution to health insurance premiums. We therefore caution against
causal interpretation of the results presented in Table 3. For example, subtle forms ofendogeneity may affect some covariates. In other words, any endogenous component of these
regressors generates a correlation between covariates and the error term akin to the selection-onunobservables problem. Therefore, tests for the robustness of results in the face of prospective
selection-on-unobservables provide an effective check on the qualitative impact findings, even if
some of the first stage regressors are endogenous. All three main regressors (debt-asset ratio, log
of capital, and log of the number of employees) included are statistically significant. Although
not shown, many of the province and industry dummies are statistically significant.9
Subsequently, the propensity score for each observation is constructed using the parameters
obtained by the probit estimation.

9

The full results of the first stage probit are available upon request.

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5. Results
5.1 Overall results
Table 4 reports the PSM estimation results for total profit after tax deduction. As
matching algorithms, we use (1) nearest five, (2) radius of 0.01, and (3) a kernel (Epanechnikov
kernel, bandwidth is 0.06) matching. This is to check whether the results are robust to various
matching algorithms. Standard errors are obtained by bootstrapping with 500 replications. For
ATT and ATU, we show the results using the mentioned matching algorithms. For each result,
we show the result of the balancing and sensitivity tests, the latter of which is proposed by
Rosenbaum (2002).
There are several findings. First, looking at the results of ATT, the firms complying withthe health insurance related laws become better off rather than those not complying. Specifically,
profit increases by VND 293–395 million, depending on the matching algorithm. Subsequently,
looking at ATU, we find the positive effect of a firm’s contributing to health insurance premiums
for the employees on profit for the firms not currently complying with health insurance related
laws. As such, profit increases by VND 125–146 million, depending on the matching algorithm.
Consequently, the magnitude of ATU is much smaller than that of ATT. However, given that
non-complying firms are, on average, small in terms of total profit after tax deduction (VND
278.7 million as per Table 2), the profit gain could be 44.8% to 52.4%. This implies that thesefirms could substantially improve their performance if they contribute to health insurance
premium for the employees. Combining the results of ATT and ATU, we claim that contributing
to health insurance premiums for the employees makes the medium and large-scale firms in
Vietnam better off.

13

We perform a series of balancing tests on the differences in means to investigate whether
the matched non-complying firms have characteristics similar to the matched complying firms in
the case of ATT, and whether the matched complying firms have characteristics similar to thematched non-complying firms in the case of ATU. As Table 4 shows, no main variables are
statistically different at the 10% level after matching. The p-values of the likelihood-ratio test of
the joint insignificance of all the regressors from the probit estimation of the propensity scoreshow the matching procedures are successful in generating comparison groups to infer the causal
impact of health insurance, controlling for observable characteristics.
Table 4 also shows the Rosenbaum bounds test of critical values for each matching
estimate to be statistically significant and different from 0. For instance, the lowest critical value
producing a 95% confidence interval encompassing 0 is 1.2 for all the ATT estimates. Although
there is no clear-cut critical threshold that distinguishes the existence and non-existence ofhidden bias, the larger the critical value, the less sensitive are the findings based on observables
to hidden bias (Rosenbaum 2002). Based on the estimated critical values, we consider our ATU
results relatively less sensitive to bias, based on selection-on-unobservables. These facts are very
encouraging because they provide relatively solid evidence that currently non-complying firms
could become better off by providing health insurance to their employees. However, our ATT
results should be interpreted with greater caution because those findings may be sensitive toestimator choice and to the omission of relevant unobserved characteristics of firms.
PSM estimation results for profit after tax deduction per employee are also shown in
Table 4. We interpret this as one measure of (labor) productivity. As the results clearly show, theproductivity gain is statistically significant for both ATT and ATU. In terms of magnitude, theproductivity gain is VND 2.6–3.0 million for the firms complying with health insurance related14

laws and VND 1.6–1.9 million for those not complying. This implies that average laborproductivity of medium and large-scale firms increases by contributing to health insurance
premiums for the employees. Although the magnitude of ATU (VND 1.6–1.9 million, whichcorresponds to USD 93.7–111.3) looks small, this gain implies that labor productivity of noncomplying firms increases by 45% to 54%, since the labor productivity of non-complying firms
is much lower than that of complying firms. As for the critical values of the Rosenbaum bounds
tests, our ATU results are relatively less sensitive to bias based on selection-on-unobservables,
while our ATT results should be interpreted with greater caution because those findings may besensitive to estimator choice and to the omission of relevant unobserved characteristics of firms.
In summary, although we require caution in interpreting the ATT results due to their
sensitivity to selection-on-unobservables, we find positive health insurance effects for bothaggregate profit and profit per worker for complying and non-complying medium and large-scale
firms. These results are robust in terms of statistical significance, with several matchingalgorithms under sufficiently balanced samples.
5.2 Results by industry
Hitherto, we pool all the industries for estimations. However, impacts of health insurance
could be industry specific. Appendix 1 shows the general industrial structure of medium andlarge-scale firms in terms of the number of firms in Vietnam. Manufacturing, construction, andwholesale/retail are three representative sectors.10 Here, we estimate the PSM specifications for

10

The sample of the manufacturing sector consists of industry code 3-10 in Appendix 1.

15

each of these three groups.11 Tables 5, 6, and 7 report the estimation results for the
manufacturing, construction, and wholesale/retail sectors, respectively.
In Table 5, we do not find any positive health insurance effect for aggregate profit on
both complying and non-complying firms in the manufacturing sector. The estimated effect is
not significantly different from 0 either. The effect on the profit per worker is again not different
from 0 for complying firms (i.e., ATT), while we find marginal statistically significant positiveeffects on profit per worker for those not complying with health insurance related laws. However,
the estimated effect (ATU) is economically small. One plausible reason on why the results aredifferent for this sector is that the manufacturing sector in Vietnam might be using intensively
manual workers who can be easily trained within a few days or weeks. Therefore, the additional
profit gain by contributing to health insurance premium is negligible. Alternatively, employers
can also replace workers easily because such workers are abundant.
Meanwhile, in both construction (Table 6) and wholesale/retail sectors (Table 7), thepositive health insurance effects are statistically significant for both aggregate profit and profit
per worker, for complying and non-complying firms. The magnitude of the positive healthinsurance effects is particularly large for both complying and non-complying firms in thewholesale/retail sector. Therefore, in this sector, complying with the health insurance related
laws is profit and productivity enhancing. However, we require caution in interpreting the ATT
results due to their sensitivity to selection-on-unobservables. On the other hand, it is encouraging
that our ATU results are relatively less sensitive to bias based on selection-on-unobservables,
which implies that currently non-complying firms could become better off by contributing tohealth insurance premiums for their employees.
11

The descriptive statistics for each of the three groups are presented in Appendix 2.

16

6. Conclusions and policy implications
In this paper, we quantify the effects of complying with the health insurance related laws
on profit and productivity by using a large-scale dataset of private firms in Vietnam, focusing on
medium and large-scale firms. We find positive health insurance effects for both aggregate profit
and profit per worker for complying and non-complying medium and large-scale firms.
Given the full sample results, it is recommended that the government encourage medium
and large-scale firms to contribute to health insurance premiums for their employees because it isprofit and productivity enhancing. Information sharing with non-complying firms (and theiremployees) so that they would comply is perhaps one effective policy. Additionally, the low
compliance rate might be due to weak government monitoring. If this is a case, strengthening thegovernment monitoring could be another policy option.
Although we believe our attempt in this paper is an important initial step toward
understanding of effects of health insurance on firms’ performance and productivity, many issues
remain unsolved. First, we completely ignore small firms in this paper due to the complexity of
the VES sampling scheme. However, given that a large number of firms have less than 30
employees, we need to study the health insurance effect on relatively small firms. Second, in
future studies, we might have to take into account the issue of partial compliance. In this paper,
we classify a firm into the treatment group if the firm has contributed to health insurance
premiums. However, some firms might decide to pay health insurance premiums for only afraction of the employees. Due to data limitations, we could not consider this possibility in thispaper, but this issue is an important future research topic. Third, we believe that health insurance
effect on employment is an important research area. In this paper, we treat the number of17

employees as a covariate rather than an outcome. However, given the idea that health insurance
provision is a type of labor regulation, its employment effect is an important margin to beinvestigated, particularly if one is interested in the general equilibrium effect. Fourth, in thisstudy, we analyze the health insurance effect as if the supply side of the health sector were given,
although provincial dummies are included in the first stage probit. However, the quality of healthservices people can receive could greatly influence both a firm’s decision of contributing tohealth insurance premiums and effects of health insurance on various margins. We believe a
study incorporating the supply side of the health sector would be fruitful. Lastly, we have tomention both internal and external validities. Regarding internal validity, although we examine
whether biases based on selection-on-unobservables exist and whether the samples are
considered sufficiently balanced, biases could still remain, since our study uses non-experimental
data. Regarding external validity, the health insurance system substantially differs acrosscountries. Although we find positive health insurance effects on firm performance andproductivity, it is conceivable that such effects differ depending on circumstances. Similar
studies in other country contexts are definitely informative.
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VSS. Available at: http://vietnamnews.vn/society/237645/health-insurance-for-all-projectapproved.html (Accessed: 24 May 2013)19

Vietnam Social Security (VSS) (2010). Vietnam Social Security Annual Report. Hanoi,
VSS.
Vietnam Social Security (VSS) (2011). Vietnam Social Security Annual Report. Hanoi,
VSS.
Vietnam Social Security (VSS) (2012). Vietnam Social Security Annual Report. Hanoi,
VSS.
World Health Organization (2013). World health report 2013: Research for universal
health coverage. World Health Organization, Luxembourg.
World Bank (2015). World Development Indicators. http://data.worldbank.org/datacatalog/world-development-indicators. Accessed 6 April 6 2016.

20

Figure 1: Timeline and roadmap of health insurance universal coverage

2013: newly ratified

coverage rate
80% ofpopulations

Remaining
populations

Law on HI

Universal
Coverage

Farmers, workers in the sectors ofagriculture, forestry, fishery, andsalt producers

Decree 63
Decree 58

Students and pupils
Children under six and near poor people
Employees at non-state owned enterprises having less than 10 workers,
cooperatives, and legal entities, the poor, and veterans

Decree 299

Members of the Congress and People's Council, pre-school teachers, meritorious people, socially
protected people; dependents of army officer s and soldiers, and foreign students in Vietnam

Employees and employers in enterprises having more than 10 workers, civil servants, pensioners, sociallyaided people, staff of international representative organizations in Vietnam

1992

1998

2005

2009

2010

2012

2014

2020

Source: Matsushima and Yamada (2014)21

Table 1: Descriptive statistics of (A) outcome variables and (B) a dependent variable andregressors in the first stage probit
Variable
Outcome variables
Aggregate profit after tax deduction (million VND)
Profit after tax deduction per employee (million VND)
Whether a firm pays health insurance premium for the employees(=1 for paying firms and 0 otherwise.)
Regressors in the first stage probitln (the number of employees)ln (capital, million VND)
debt-asset ratio
Sample size
Note: 24 industry and 63 province dummies are omitted.

MeanStd. Dev.

746.573 2,777.870
6.307
21.046
0.594

0.491

4.307
9.525
5.568

0.722
1.296
10.35918,21522

Table 2: Mean difference in outcome variables and regressors in the first stage probit
With healthWithout health
Difference
insurance
insurance
Variable
Outcome variables
Aggregate profit after tax deduction
1,065.790
278.765787.025(million VND)
(3,370.920)(1416.050)(41.512)***
Profit after tax deduction per employee
8.185
3.554
4.630
(million VND)
(24.039)(15.247)(0.315)***Regressors in the first stage probitln (the number of employees)
4.461
4.081
0.381
(0.755)(0.601)(0.010)***ln (capital, million VND)
9.874
9.014
0.860
(1.245)(1.194)(0.018)***debt-asset ratio
5.835
5.175
0.660
(10.219)(10.548)(0.660)***Sample size
10,827
7,388
Notes
1: Standard deviations are in parentheses for means and standard errors are in parentheses for thedifference in mean. *** p < 0.01.
2: 24 industry and 63 province dummies are omitted.

23

Table 3: First stage probit estimation result
Variablesln (the number of employees)

Industry dummy
Province dummy
Prob > chi2

0.323***[0.018]0.284***[0.010]-0.003***[0.001]-4.915***[0.218]
Yes
Yes
0.000

Pseudo R2

0.175

ln (capital, million VND)
debt-asset ratio
Constant

Observations
18,215Notes
1: Dependent variable = 1, if a firm pays health insurance premiums for the employees and 0 otherwise.
2: Robust standard errors in brackets. *** p < 0.01, ** p < 0.05, * p < 0.1.

24

Table 4: Estimated ATT and ATU (Full samples)
ATT

ATU
Nearest 5

Radius of 0.01 Kernela

395.070

124.907138.838

146.126(89.930)***(74.526)***(26.786)***(23.286)***(24.536)***

1.2

1.2

1.2

1.6

3.1

3.4

2.665

2.845

3.013

1.643

1.797

1.904

Standard error(0.585)***(0.498)***(0.466)***(0.406)***(0.336)***(0.370)***Sensitivity test
Rosenbaum bounds critical level

1.2

1.2

1.2

1.5

2.8

3.0

1.59
0.5
-0.82
0.883

1.31
0.66
0.75
0.402

0.84
0.90
0.50
0.793

1.22
1.12
0.56
0.994

Nearest 5

Radius of 0.01 Kernel

292.916

339.820

Standard error(103.550)***Sensitivity test
Rosenbaum bounds critical level
Profit after tax deduction per employee
Estimated ATT/ATU (million VND)

a

Aggregate profit after tax deduction
Estimated ATT/ATU (million VND)bb

Balancing test
t-value on the difference in meansln (the number of employees)
-0.33
0.14
ln (capital)
-1.22
-0.99
debt-asset ratio
-0.71
-0.73
P-values of the likelihood-ratio test
0.572
0.968
Notes
***p < 0.01, **p < 0.05, *p < 0.10
a: We use an Epanechnikov kernel with bandwidth of 0.06.
b: Standard errors are obtained by bootstrapping with 500 replications.

25

Table 5: Estimated ATT and ATU (Manufacturing sector)
ATT

ATU
Nearest 5

Radius of 0.01 Kernela

56.43874.45967.93271.392(231.243)(178.320)(60.210)(49.267)(49.030)

-

-

-

-

-

-

0.151

0.274

0.96

0.947

0.829

0.877

Standard error(1.291)(1.136)(0.965)(0.514)*(0.449)*(0.439)**Sensitivity test
Rosenbaum bounds critical level

-

-

-

1.4

1.9

2.2

1.76*
-1.26
-0.57
0.941

1.63
-1.09
0.18
0.995

1.51
-0.59
-0.15
1.000

Nearest 5

Radius of 0.01 Kernel-146.499-138.793

Standard error(260.029)

Sensitivity test
Rosenbaum bounds critical levela

Aggregate profit after tax deduction
Estimated ATT/ATU (million VND)bProfit after tax deduction per employee
Estimated ATT/ATU (million VND)bBalancing test
t-value on the difference in meansln (the number of employees)
-1.52
1.33
-0.34
ln (capital)
-0.27
-0.25
0.67
debt-asset ratio
0.25
0.32
-0.03
P-values of the likelihood-ratio test
0.683
0.973
0.989
Notes
The sample size is 5,892 (3,725 complying and 2,167 non-complying firms).
***p < 0.01, **p < 0.05, *p < 0.10
a: We use an Epanechnikov kernel with bandwidth of 0.06.
b: Standard errors are obtained by bootstrapping with 500 replications.

26

Table 6: Estimated ATT and ATU (Construction sector)
ATT

ATU
Nearest 5

Radius of 0.01 Kernela

341.966

113.607127.16121.454(71.161)***(75.140)***(38.580)***(30.266)***(28.215)***

1.2

1.2

1.2

2.0

3.2

3.7

2.446

2.521

2.282

1.643

1.736

1.649

Standard error(0.782)***(0.658)***(0.703)***(0.685)**(0.578)***(0.518)***Sensitivity test
Rosenbaum bounds critical level

1.2

1.2

1.2

1.9

3.1

3.8

0.25
1.08
-0.54
1.000

0.09
0.31
-0.16
1.000

0.35
0.81
-0.24
1.000

Nearest 5

Radius of 0.01 Kernel

355.822372.562

Standard error(79.613)***

Sensitivity test
Rosenbaum bounds critical level
Profit after tax deduction per employee
Estimated ATT/ATU (million VND)

a

Aggregate profit after tax deduction
Estimated ATT/ATU (million VND)bb

Balancing test
t-value on the difference in meansln (the number of employees)
1.01
1.52
1.09
ln (capital)
0.06
-0.21
0.09
debt-asset ratio
0.96
0.46
0.35
P-values of the likelihood-ratio test
0.98
0.997
1.000
Notes
The sample size is 4,810 (2,517 complying and 2,293 non-complying firms).
***p < 0.01, **p < 0.05, *p < 0.10
a: We use an Epanechnikov kernel with bandwidth of 0.06.
b: Standard errors are obtained by bootstrapping with 500 replications.

27

Table 7: Estimated ATT and ATU (Wholesale/retail sector)
ATT
Nearest 5
Radius of 0.01 Kernela

ATU
Nearest 5

Radius of 0.01 Kernela

619.060

308.694311.683288.621(157.819)*** (140.954)***(134.940)***(93.808)***(77.536)***(72.753)***

1.3

1.2

1.2

1.6

2.5

2.6

5.703

5.446

4.311

4.818

4.223

(1.814)***(1.634)***(1.549)***(1.526)***(1.399)***(1.178)***

1.3

1.2

1.2

1.6

2.5

2.6

0.48
0.24
-0.34
1.000

0.14
0.53
0.05
1.000

0.50
0.07
-0.16
1.000

Aggregate profit after tax deduction
Estimated ATT/ATU (million VND) 668.749
Standard errorbSensitivity test
Rosenbaum bounds critical level

Profit after tax deduction per employee
Estimated ATT/ATU (million VND) 6.341
Standard errorbSensitivity test
Rosenbaum bounds critical level

632.029

Balancing test
t-value on the difference in meansln (the number of employees)
0.08
-0.33
0.35
ln (capital)
-0.34
-0.66
-0.07
debt-asset ratio
-0.61
-0.8
-0.34
P-values of the likelihood-ratio test
1.000
1.000
1.000
Notes
The sample size is 2,828 (1,863 complying and 965 non-complying firms).
***p < 0.01, **p < 0.05, *p < 0.10
a: We use an Epanechnikov kernel with bandwidth of 0.06.
b: Standard errors are obtained by bootstrapping with 500 replications.

28

Appendix 1: List of 23 industries
1-Agriculture, forestry, and aquaculture
2-Mining and quarrying
3-Food and drink
4-Textile and garment
5-Shoes and leather
6-Wood, wood products, and printing
7-Chemical, chemical products, and pharmaceutical
8-Rubber, rubber products, and plastic
9-Non-metal
10-Metal
11-Others (electric equip, machinery, repairing, installation)
12-Accommodation and food service
13-Arts, entertainment, and recreation
14-Construction
15-Education
16-Electricity, gas, steam, and air conditioning supply
17-Information and communication
18-Professional, scientific, and technical activities
19-Transportation and storage
20-Water supply, sewerage waste management and remediation
21-Wholesale and retail trade
22-Other service activities
23-Others
Total

Number of firms
324
423
1,121
1,022
190
1,096
290
447
924
802
1,146
602
35
4,810
95
33
117
564
1,160
48
2,828
30
108
18,215Percent
1.78
2.32
6.15
5.61
1.04
6.02
1.59
2.45
5.07
4.4
6.29
3.3
0.19
26.41
0.52
0.18
0.64
3.1
6.37
0.26
15.53
0.16
0.59
100

29

Appendix 2: Mean difference in outcome variables and regressors in the first stage probit
With healthWithout health
Difference
insurance
insurance(1) Manufacturing Sector
Outcome variables
Aggregate profit after tax deduction
1,311.302
348.650962.652(million VND)
(3,927.862)(1,995.621)(90.652)***
Profit after tax deduction per employee
7.604
2.836
4.768
(million VND)
(21.914)(14.238)(0.525)***Regressors in the first stage probitln (the number of employees)
4.627
4.153
0.474
(0.791)(0.662)(0.020)***ln (capital, million VND)
9.889
8.858
1.031
(1.285)(1.284)(0.034)***debt-asset ratio
3.428
3.874
-0.446(6.341)(8.399)(0.193)**Sample size
3,725
2,167
(2) Construction Sector
Outcome variables
Aggregate profit after tax deduction
750.207186.607563.600(million VND)
(2,395.577)(604.172)(51.456)***
Profit after tax deduction per employee
6.010
2.717
3.293
(million VND)
(17.243)(8.196)(0.395)***Regressors in the first stage probitln (the number of employees)
4.552
4.141
0.411
(0.756)(0.604)(0.019)***ln (capital, million VND)
9.924
8.988
0.936
(1.194)(1.082)(0.033)***debt-asset ratio
8.298
6.852
1.446
(12.219)(12.232)(0.352)***
Sample size
2,517
2,293
(3) Wholesale/Retail sector
Outcome variables
Aggregate profit after tax deduction
1,004.737
269.885734.852(million VND)
(3,286.663)(1,573.627)(111.913)***
Profit after tax deduction per employee
11.092
4.264
6.828(million VND)
(32.400)(23.635)(1.178)***Regressors in the first stage probitln (the number of employees)
4.121
3.904
0.217
(0.584)(0.476)(0.021)***ln (capital, million VND)
10.1329.535
0.597(1.094)(1.066)(0.043)***debt-asset ratio
10.1178.847
1.270(13.789)(13.551)(0.543)***Sample size
1,863
965
Notes
1: Standard deviations are in parentheses for means, and standard errors are in parentheses for the difference
in mean.
2: ***p < 0.01, **p < 0.05.
3: 24 industry and 63 province dummies are omitted.

30