The impact of health insurance on out of pocket payments in the mekong river delta

UNIVERSITY OF ECONOMICS

ERASMUS UNVERSITY ROTTERDAM

HO CHI MINH CITY

INSTITUTE OF SOCIAL STUDIES

VIETNAM

THE NETHERLANDS

VIETNAM - NETHERLANDS
PROGRAMME FOR M.A IN DEVELOPMENT ECONOMICS

THE IMPACT OF HEALTH INSURANCE ON
OUT-OF-POCKET PAYMENTS IN THE
MEKONG RIVER DELTA

BY

TA THI HONG NGOC

MASTER OF ARTS IN DEVELOPMENT ECONOMICS

HO CHI MINH CITY - DECEMBER, 2017


UNIVERSITY OF ECONOMICS

INSTITUTE OF SOCIAL STUDIES

HO CHI MINH CITY

THE HAGUE

VIETNAM

THE NETHERLANDS

VIETNAM - NETHERLANDS
PROGRAMME FOR M.A IN DEVELOPMENT ECONOMICS

THE IMPACT OF HEALTH INSURANCE ON
OUT-OF-POCKET PAYMENTS IN
THE MEKONG RIVER DELTA
A thesis submitted in partial fulfilment of the requirements for the degree of
MASTER OF ARTS IN DEVELOPMENT ECONOMICS

By

TA THI HONG NGOC
Academic Supervisor:

DR. TU VAN BINH

HO CHI MINH CITY - DECEMBER, 2017


DECLARATION
“I certify that this material is my own work, containing my independent research

results, have not been published. I assure that all sources of information in the thesis,
including data sets, are clearly acknowledged.
I pledge to take responsibility for my research.”

Signature

Ta Thi Hong Ngoc
Date: December, 2017


ACKNOWLEDGEMENT
Firstly, I would like to express my appreciation to my supervisor Dr. Tu Van Binh
who provided me motivation, patience, and knowledge to complete my thesis. I am very
grateful for his sympathy and his kind encouragement to me last year when my mother was
deeply sick. His friendly guidance in all the time of research helped me overcome a hard time
of writing this thesis.
Besides my supervisor, I am grateful to Dr. Truong Dang Thuy and Dr. Pham Khanh
Nam who have provided the theoretical background and econometrics methodology, which
strongly supported my thesis.
My sincere thanks to tutor Nguyen Van Dung who support me data and kindly
encourage me during my thesis.
I would thank all lecturers, administrators and my VNP 22 classmate in the Vietnam –
The Netherlands Program for giving me a loyal sympathy, for the memorable moments we
were working together before deadlines of assignments and exams during the course.
Finally, I would like to give a special thanks to my family who has encouraged me not
only in thesis period but also in my life.


ABSTRACT
The study uses the Vietnam Household Living Standard Survey in the year of 2012

and 2014 in 13 provinces in the Mekong River Delta (MRD) to evaluate the impact of health
insurance on out-of-pocket payments in the MRD. Three models including Pool OLS,
Random Effects and Fixed Effects are applied and the regression result shows that health
insurance is statistically significant and has the negative relationship with out-of-pocket
expenses per visit to outpatient service and inpatient service. The study indicates that health
insurance has a positive impact on reducing out-of-pocket expenses, meaning that people who
have health insurance spend less than those who do not have health insurance. Heath
insurance benefits the society by reducing the monetary cost of using the health services and
therefore is potentially advantageous for poor and underprivileged people in approaching
healthcare resources. The policy implication insists that it is essential to increase health
insurance coverage, especially for the poor and near poor. In addition, policy makers could
consider reducing or eliminating co-payments for the poor and policy beneficiaries such as
ethnic minorities in the MRD. Moreover, the authority needs to concern about awareness
raising in the health insurance of people living in this area.
Key words: Health Insurance, Out-of-pocket expenses, Mekong River Delta.
JEL Classification: I13.


TABLE OF CONTENTS
DECLARATION

i

ACKNOWLEDGEMENT

ii

ABSTRACT

iii

TABLE OF CONTENTS

iv

LIST OF TABLES

vi

LIST OF FIGURES

vii

LIST OF ACRONYMS

viii

CHAPTER 1: INTRODUCTION

1

1.1 The practical problem

1

1.2 The research problem

1

1.3 Research Objectives

2

1.4 Contribution of the Study

2

1.5 Organization of the Study

2

CHAPTER 2: LITERATURE REVIEW

3

2.1 Core concepts

3

2.1.1 Health insurance

3

2.1.2 Out-of-pocket payments

4

2.2 Theoretical background

4

2.3 Empirical studies about the impact of health insurance on out-of-pocket payments 8
2.3.1 Out-of-pocket payments definition and measurements

8

2.3.2 Estimation method

9

2.3.3 Control variables

10

2.3.4 Results

10

CHAPTER 3: RESEARCH METHODOLOGY AND DATA

13

3.1 Analytical framework

13

3.2 Research Methodology

13

3.2.1 Fixed Effects Estimation

14

3.2.2 Fixed Effects with Unbalanced Panels

15

3.2.3 Random Effects Models

15

3.2.4 Random Effects or Fixed Effects

16
iv


3.3 Model specification

17

3.4 Data

19

CHAPTER 4: FINDINGS AND DISCUSSION

21

4.1 Overview of the research topic

21

4.1.1 Background of health insurance in Vietnam and the MRD

21

4.1.2 Overview of out-of-pocket health expenditure in Vietnam

24

4.2 Descriptive statistics

26

4.3 Estimation results

33

CHAPTER 5: CONCLUSION AND POLICY IMPLICATIONS

40

5.1 Conclusion

40

5.2 Policy Implications

40

5.3 Limitation

41

REFERENCES

42

v


LIST OF TABLES
Table 3. 1: Variable description and sources ............................................................................ 18

Table 4. 1: Descriptive statistics .................................................................................... 26
Table 4. 2: The correlation coefficient between the variables ...................................... 27
Table 4. 3: Number of observations and proportion of people having health insurance28
Table 4. 4: Proportion of people having health insurance in 13 provinces in the MRD29
Table 4. 5: Statistical coverage of health insurance by age........................................... 30
Table 4. 6: Statistics on the share of health insurance participation by gender ............ 30
Table 4. 7: Statistics on the share of health insurance participation by marital status .. 31
Table 4. 8: Statistics on health insurance participation by ethnics ................................ 31
Table 4. 9: Statistics on health insurance coverage by level of education .................... 32
Table 4. 10: Statistics on health insurance coverage by rural, urban area .................... 33
Table 4. 11: The panel data regression result with Out-of-pocket expenses per visit to
outpatient service (OOV) .............................................................................................. 34
Table 4. 12: The panel data regression result with Out-of-pocket expenses per visit to
inpatient service (OIV) .................................................................................................. 37

vi


LIST OF FIGURES
Figure 1. Analytical framework ................................................................... 13

vii


LIST OF ACRONYMS

2SLS

Two-Stage Least Squares

DID

Difference-in-Difference

FE

Fixed Effects

GLS

Generalized Least Squares

GSO

General Statistics Office

HI

Health Insurance

IV

Instrumental Variables

MRD

Mekong River Delta

OIV

Out-of-pocket expenses per visit to inpatient service

OLS

Ordinary Least Squares

OOP

Out-of-pocket payments

OOV

Out-of-pocket expenses per visit to outpatient

POLS

Pooled Ordinary Least Squares

PSM

Propensity Score Matching

RE

Random Effects

VHLSS

Vietnam Household Living Standard Survey

WHO

World Health Organization

viii


CHAPTER 1: INTRODUCTION
1.1 The practical problem
Out-of-pocket expenses are popular in health care study. According to WHO (2005),
results of 108 surveys conducting in 86 countries showed that catastrophic expenses for health
care services lead 5% of households into poverty. To address the problem of reducing out-ofpocket payments due to illnesses, health insurance is expected as a good measure for its
important role in health care and financial protection. It facilitates insured people to approach
health care services better and protects them from financial burdens resulting from health

problems. As people in the Mekong River Delta (MRD) do not have a long tradition of using
health insurance, an interesting question is “to what extent does health insurance affect out-ofpocket expenses in this region?”.
There are currently several problems with the health care system in Vietnam, where
using health insurance is normally linked with a poor service. In spite of the fact that there is
an improvement in the coverage of health insurance, it is reported that only 52% of annual
outpatient contacts use health insurance and up to 40% of the insured people did not use
health insurances when having health care treatments in 2006 (Nguyen, 2012). It is also the
case of in the MRD. Therefore, understanding the impact of health insurance on out-of-pocket
payments can contribute some ideas to the government so that health insurance scheme may
increase its effectiveness.
1.2 The research problem
Within the context of Vietnam, there have been some researches on the impact of
health insurance on out-of-pocket expenses. Nevertheless, the effects of health insurance on
out-of-pocket expenses are not homogeneous.
Some studies confirm the positive effects of health insurance on reducing out-ofpocket expenses (Jowett et al., 2003, Wagstaff & Pradhan, 2005, Sepehri et al., 2006).
However, Wagstaff (2010) and Nguyen (2012) found that voluntary health insurance does not
have an impact on out-of-pocket expenditures. Moreover, to the best of my knowledge, there
has not been any studies on this issue in the context of the MRD.
Therefore, this research may contribute to filling the literature gap in the context of the
MRD, which is still considered a poor region in Vietnam. Moreover, this study reexamines
the impact of health insurance on out-of-pocket payments with updated data.

1


1.3 Research Objectives
The study has the following objectives:
(i)

to estimate the impacts of health insurance on out-of-pocket payments

(ii)

to propose feasible policies to better manage health insurance program

This study employs the Vietnam Household Living Standard Survey (VHLSS) in the
year of 2012 and 2014 are used in the research to approach the research objectives. The data
set covers 13 provinces/city (Long An, Tien Giang, Ben Tre, Tra Vinh, Vinh Long, Dongs
Thap, An Giang, Kien Giang, Can Tho, Hau Giang, Soc Trang, Bac Lieu, Ca Mau) with
approximately 7,000 observations/wave. This thesis utilized Pool OLS, Fixed Effect, Random
Effect regressions to test the impact of health insurance on out – of – pocket payments.
1.4 Contribution of the Study
This study makes a major contribution in two aspects as follows. First, there have been
many empirical studies on the impact of health insurance on out-of-pocket expenses.
However, most of these studies mainly focus on the case of developed countries. There are
still few studies about this issue for developing countries where using health insurance is
normally linked with a poor service. In the case of the MRD, the rural area of Vietnam, there
is still no published studies on this topic. Therefore, this paper contributes to the literature as
one of the first comprehensive analysis of this issue in the Vietnamese case. Second, the
research results are an important and reliable source of information for policy makers to better
manage the health insurance service in the MRD in particular and in Vietnam in general.
1.5 Organization of the Study
The organization of the study is structured as follows.
Chapter 1 introduce the practical problem, the research problem as well as research
objectives.
Chapter 2 gives a review of the definition, core concepts of health insurance and out-ofpocket payments. In addition, theories and empirical studies are also presented.
Chapter 3 presents the analytical framework, the research methodology, model specification
and data.
Chapter 4 gives a general review of background of health insurance in Vietnam and the MRD,
an overview of out-of-pocket health expenditure in Vietnam, the descriptive statistics of

variables used in the study and the findings and discussion.
Chapter 5 presents the conclusion, suggests some practical policy implications, and discusses
the limitation and direction for further studies.

2


CHAPTER 2: LITERATURE REVIEW
2.1 Core concepts
2.1.1 Health insurance
It is important to understand clearly the concept “health insurance” before going
further with the study. The concept of “health insurance” is popular in health economics.
Health insurance is defined as “coverage that provides for the payments of benefits as a result
of sickness or injury. It includes insurance for losses from accident, medical expense,
disability, or accidental death and dismemberment” (Health Insurance Association of
America, 2010).
According to the Vietnamese Health Insurance Law No. 25/2008/QH12, “Health
insurance is a form of services that is applied in the field of health care, not for profit
purposes, organized by the State and those who are responsible for participating in
provisions of law.” The health insurance fund is made up of contributions from the insured's
income, managed centrally and transparently, ensuring a balance between revenue and state
protection. Thus, although health insurance is a service, the activity must be based on risksharing, shared financial burdens on sickness and illness, and health insurance is not for the
purpose of profit, but for the purpose of providing health care for people participating in the
purchase of health insurance is regulated by the state. Health insurance is also a form of
undertaking socialization of the health sector as it helps to mobilize the contribution of the
society. When the budget for health is limited, the health insurance fund is also a way to share
the medical burden for many patients, especially those with limited income and dependents.
Assistance between healthy people and the sick, between the young and the elderly, between
the rich and the poor has contributed to the reduction of injustice.
Under the Vietnamese Health Insurance Law No. 25/2008/QH12, there are 25 groups

including policy beneficiaries and target groups. The law stipulates that workers with a
contract of 3 months or more, indefinite labor, the staff at agencies, public service units,
pensioners, etc. belong to the group of buyers of compulsory health insurance. Health
insurance premiums will also be set for each beneficiary under which certain policy
beneficiaries will be paid by third parties, while employees and employers pay premiums
according to the income level of workers. Voluntary health insurance applies to those who
wish to volunteer to participate in health insurance, including those who have participated in
compulsory health insurance but who wish to participate in voluntary health insurance in
order to qualify for higher health insurance services. This type of insurance is not for profit
but only for the purpose of encouraging all people to participate in health insurance. In the

3


context that Vietnam has not yet implemented the form of universal health insurance, in order
to avoid moral hazard and budget deficit, voluntary health insurance sets a number of rules to
limit the status of people who have high risk buy new health insurance. According to the
Circular 06/2007/TTLT-BYT-BTC, the rules for the issuance of voluntary health insurance
cards are as follows:
For household members, they will buy voluntary health insurance according to the
place of their residence and must ensure that 100% of their members participate in each
issuance, at least 10% in the area. For students, voluntary school-based health insurance is
compulsory for at least 10% of the participating students.
Thus, the voluntary insurance scheme to expand the coverage of health insurance
coverage and to implement this group of people requires deep and broad dissemination to help
people understand the meaning of health insurance operation.

2.1.2 Out-of-pocket payments
The concept of “out-of-pocket payments” is a widely used concept in health
economics. It is defined as: “cost-sharing, self-medication and other expenditure paid

directly by private households, irrespective of whether the contact with the health care system
was established on referral or on the patient’s own initiative” (OECD, 2003). According to
World Bank (2016), “out-of-pocket payments” is “any direct outlay by households, including
gratuities and in-kind payments, to health practitioners and suppliers of pharmaceuticals,
therapeutic appliances, and other goods and services whose primary intent is to contribute to
the restoration or enhancement of the health status of individuals or population groups. It is a
part of private health expenditure.” According to Hoang et al. (2013), “out-of-pocket
payments” refer to “the payments made by households at the point they receive health
services. Typically these include doctor’s consultation fees, purchases of medication and
hospital bills. Although spending on alternative and/or traditional medicine is included in out
of pocket payments, expenditure on health-related transportation and special nutrition are
excluded. Out-of-pocket payments are net of insurance reimbursement.”

2.2 Theoretical background
Assuming that health is a productive asset, creating health can be considered as an
investment to compensate for the capital spent on age and lifestyle. Creating health is an
increase in “health capital”. This investment is achieved through the use of medical treatments
and personal efforts in preventing illness. The benefit from health capital is the reduction of

4


time spent in a “sick” health state. Over time, the increase in the utility towards health
services is linked to the increase in income and consumption. Therefore, the maximization of
utility among rational individuals is in line with the optimal amount of money they invest in
health services. Grossman's study (1972) analyzes this optimization problem with optimal
control theory.
Consider an individual with a two-stage plan. In each period, he or she has to spend a
lot of time sick 𝑡 𝑠 , if the health capital is larger, this time less. In other words, healthy times
are the health benefits (non-exchangeable) of health capital. The individual receives a positive

level of enjoyment from consumer goods X and negative levels of utility from time of illness
𝑡 𝑠 (𝐻). Such conditions create the independence of the utility function overtime, that is, the
marginal rate between time and consumption is unchanged. The utility then is discounted by
an element, β≤1, in the future. As a result, this individual maximizes the discounted µ.
𝜇 = 𝑈(𝑡 𝑠 (𝐻0 ), 𝑋0 ) + 𝐵𝑈(𝑡 𝑠 (𝐻1 ), 𝑋1 )

(2.1)

𝜕𝑈
𝜕 2𝑈
𝜕𝑈
𝜕 2𝑈
𝜕𝑡 2
<
0,
>
0,
>
0,
<
0,
< 0.
𝜕𝑡 𝑠
𝜕(𝑡 2 )2
𝜕𝑋
𝜕𝑋 2
𝜕𝐻
The above function, commonly called Grossman model, represents the change in the
amount of money for health services over time. That the wearing rate of this equation is not
constant and is at the δ rate proves that health capital will reduce when time passes by.

Therefore, to heighten the capital, individuals need to make I investment. This investment
includes consumption for health services and time spent 𝑡 𝐼 for prevention sick efforts. Taken
together we have:
𝐻1 = 𝐻0 (1 − 𝛿) + 𝐼(𝑀0 , 𝑡 𝐼 )

(2.2)

𝜕𝐼
𝜕 2𝐼
𝜕𝐼
𝜕 2𝐼
> 0,
<
0,
>
0,
<0
𝜕𝑀
𝜕𝑀2
𝜕𝑡𝐼
𝜕(𝑡𝐼 )2
Following the equation 2.2, I is considered as investment for health in which I
includes M (health care services). M includes cost of health care services. This cost refers to
many expenses, and out-of-pocket payments are one of the cost.
The constraint is set in this equation for the optimal utility of individuals. This
equation shows that individuals’ health, wealth, and knowledge varies across time. The
savings of individual in the first stage will be used in the second stage. The interest rate is R =
1 + r. The equation indicates that individuals just invest in health services at the first stage.
As for health insurance, the individual property and income are considered as a source
for healthcare expenditures. p is the price of healthcare services, and 𝑤0 is the salary in the

5


first stage. In this case, both the first and the second stage must have positive consumption,
and the sum of time is 1. Establish those things together, we have the budget constraints after
the discount as follows:
𝐴0 + 𝑤0 (1 − 𝑡 𝑠 (𝐻0 ) − 𝑡 𝐼 ) +

𝑤1 (1− 𝑡1𝑠 (𝐻1 ))
𝑅

= 𝑝𝑀 + 𝑐𝑋0 +

𝑐𝑋1

(2.3)

𝑅

To interpret this optimization problem, we write the Lagrange function as follows:
𝐿(𝐻1 , 𝑡 𝐼 , 𝑀, 𝑋0 , 𝑋0 ) = 𝑈(𝑡 𝑠 (𝐻0 ), 𝑋0 ) + 𝛽𝑈(𝑡 𝑠 (𝐻1 ), 𝑋1 ) + 𝜇(𝐻0 (1 − 𝛿) + 𝐼(𝑀, 𝑡 𝐼 ) −
𝐻1 ) + 𝜆 (𝐴0 + 𝑤0 (1 − 𝑡 𝑠 (𝐻0 ) − 𝑡 𝐼 ) +

𝑤1 (1−𝑡1𝑠 (𝐻1 ))
𝑅

− 𝑝𝑀 − 𝑐𝑋0 −

𝑐𝑋1

𝑅

) (2.4)

μ is the Lagrange multipliers, in which the positive λ means that when the constraints
are loosened, the goal of optimization can be improved. This improvement can be calculated
through the discount utility.

It is found that the best conditions for a solution of this

optimization problem by taking the first derivative of each decision variable and for this
derivative to zero.
Taking the derivative with the variables μ and λ is to ensure that the constraints in the
above equations occur, we do not present them here. Considering 𝐻0 is a given constant
value, we have:
𝜕𝑈 𝜕𝑡 2

𝜕𝐿
𝜕𝐻1
𝜕𝐿
𝜕𝑡 𝐼

𝜆

𝜕𝑡 2

= 𝛽 𝜕𝑡 2 𝜕𝐻 − 𝑅 𝑤1 𝜕𝐻 − 𝜇 = 0
1

𝜕𝐼

= 𝜇 𝜕𝑡 𝐼 − 𝜆𝑤0 = 0
𝜕𝐿
𝜕𝑀

𝜕𝐼

𝜕𝐿

𝜕𝐿

(2.6)

= 𝜇 𝜕𝑀 − 𝜆𝑝 = 0
𝜕𝑈

= 𝜕𝑋 − 𝜆𝑐 = 0

𝜕𝑋0

0

𝜕𝑈

𝜕𝑋1

(2.5)

1

𝜆

= 𝛽 𝜕𝑋 − 𝑅 𝑐 = 0
1

(2.7)
(2.8)
(2.9)

Dividing the equation (2.6) by (2.7) we have
𝜕𝐼/𝜕𝑡 𝐼
𝜕𝐼/𝜕𝑀

=

𝑤0

(2.10)

𝑃

Dividing the equation (2.8) by (2.9) we have
𝜕𝑈/𝜕𝑋0
𝜕𝑈/𝜕𝑋1

= 𝛽𝑅

Solve the equation (2.9), find

𝜆

𝑅

(2.11)

then substituting into equation (2.5) we obtain:

𝜕𝑡 𝑠 𝑤 𝜕𝑈

𝜕𝑈

−𝛽 𝜕𝐻 [ 𝑐1 𝜕𝑋 − 𝜕𝑡 𝑠 ] = 𝜇
1

1

(2.12)

From equations (2.7), (2.8) we have
𝜇=

𝜕𝑈/𝜕𝑋0 𝑝
𝜕𝐼/𝜕𝑀 𝑐

(2.13)

6


Substitute μ in equation (2.13) into equation (2.12) we have
𝜕𝑡 𝑠 𝑤 𝜕𝑈

𝜕𝑈

−𝛽 𝜕𝐻 [ 𝑐1 𝜕𝑋 − 𝜕𝑡 𝑠 ] =
1

1

𝜕𝑈/𝜕𝑋0 𝑝

(2.14)

𝜕𝐼/𝜕𝑀 𝑐

Or
𝛽

𝜕𝑡 𝑠 𝜕𝑈
𝜕𝑡 𝑠 𝑤1 𝜕𝑈 𝜕𝑈/𝜕𝑋0 𝑝
+
(−𝛽
)
=
𝜕𝐻1 𝜕𝑡 𝑠
𝜕𝐻1 𝑐 𝜕𝑋1
𝜕𝐼/𝜕𝑀 𝑐
Under the above condition, there is the equality between the marginal utility and the

marginal cost for healthcare services.
The effectiveness of the investment is measured through prerequisites. The reduction

in the illness time of an individual will result in the positive investment. The combination of
𝜕𝑡 𝑠

both the negative derivative of 𝜕𝐻 and the positive value of the function causes the left side of
1

condition (2.14) to be positive, for example, the margin of positive right-hand margin.
Consider health as consumer goods. The decrease in the duration of sickness (as well
as the increased health benefit) increases the utility directly because
benefit from the utility level is 𝛽

𝜕
𝜕𝑡 𝑠

𝜕𝑈
𝜕𝑡 𝑠

<0. If discounted, the

. If condition (14) is only the first factor in the investment

and well-being state’s marginal utility, the consumption model is pure.
When health investment is considered as investing in a certain item, the decrease in
𝜕𝑡 𝑠

sickness has an immediate impact on an individual's well-being through −𝛽 𝜕𝐻 and real wage
1

𝑤1
𝑐

𝜕𝑈

. This value depends on 𝜕𝑋 (marginal margin of consumption of an additional commodity).
1

So, even if the sickness time is not denied because of the discomfort itself, health investment
brings benefits to the increase in labor income and individual wealth. In this situation when
health is considered as goods, its assessment should be examined together with its influence
on wealth. The condition (2.14) is an individual’s pure investment.
The marginal cost of an additional health investment is on the right-hand side of the
equation (2.14).
Marginal utility level

𝜕𝑈
𝜕𝑋0

represents what is lost from skipping a part of consumption

to health.
However, this loss is reduced to a significant extent if the consumption of health
𝜕𝐼

services is effective (𝜕𝑀 large).
At last, the adjustment of the productivity through the adjustment of the price of
healthcare services must be carried out when the investment in health capital is not

7

beneficiary when p is at a high rate. Similarly, the level of utility actually lost from
abandoning a particular consumption needs to be adjusted by the consumer price because if 𝑐
is high, only a few units of 𝑋0 are abandoned.
To sum up, the Grossman model shows the interrelation between healthcare
investment and the health status of individuals. The value is adjusted to reach the optimal
level across time for each individual. The increase in consumption and investment is
explained by the increase in the marginal utility of an additional health unit. The total
marginal utility has to be the same as the marginal cost of health investment.

2.3 Empirical studies about the impact of health insurance on out-of-pocket payments
2.3.1 Out-of-pocket payments definition and measurements
Out-of-pocket payments have been used as the main variable in a number of studies by
many researchers around the world. Based on such a huge amount of research, a variety of
definitions and measurements for this variable is drawn. In the study with the sample of three
provinces in Vietnam in 1999, Jowett et al. (2003) suggest that this variable can be measured
by adding up both official and unofficial payments to achieve the total expenditure on
healthcare. Sephri et al. (2006) did not mention official or unofficial payments but just
consider out-of-pocket payments as the household expenditure on health during the past 12
months. Ekman (2007) has a quite different point of view that the difference between the
income of a patient and the expense of the household on heath is the out-of-pocket payments.
Fan et al. (2012) divide healthcare services into two elements, inpatient and outpatient
services. Each element is also the combination of different indicators at the household level.
Out-of-pocket payments are the sum of these two elements. This variable is adjusted to the
monthly scale and is divided by the household size to have the spending per capita. Using the
Indonesia’s Family Life Survey in four years, Aji et al. (2013) show that out-of-pocket
payments include all medical costs such as hospitalization, clinic, physicians, traditional
cures, and medicines except transportation costs due to the unavailability of the data. The
effects of inflation on household expenditures on health are eliminated by instilling the
Consumer Price Index (CPI) in 2007. Similar to Fan et al. (2012), the adjustment of the
variable based on the household size is added to get payments per capita. Van Minh et al.

(2013) also hold that payments on health services should take into account consultation,
medication, hospitalization, and medicine costs but not costs related to transportation and
nutrition.

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2.3.2 Estimation method
A wide range of methods has been used by different authors to test the relationship
between out-of-pocket payments and a certain factor. To estimate the effects of health
insurance on health expenditures, Jowett et al. (2003) use Ordinary Least Squares (OLS) for
the regression models. However, this method is limited due to the assumption that there is no
relationship between health expenditures and unobservable factors. Ekman (2007) also
analyzes the impact of health insurance on health expenditures in Zambia, a low-income
country, in 1998 only by multivariate regressions. Compared with these two cross-sectional
studies, Sepehri et al. (2011) expand the study scope to the panel data of VHLSS 2004-2006
with the use of Fixed Effects (FE) and Random Effects (RE) for the insured and uninsured
group. With a variety of methods for panel data regression like Pooled Ordinary Least
Squares (POLS) and Fixed Effects (FE) for models without endogeneity as well as Two-stage
Least Squares (2SLS) for models with instrumental variables (IV), Aji et al. (2013) discover a
significantly negative relation between out-of-pocket payments and health insurance
programs. According to the paper, household participation in the communal gatherings,
women’s groups, and co-operation are considered as the three instrumental variables in the
research.
Besides, some other studies provide researchers with different kinds of regression
methods. Sepehri et al. (2006) apply Tobit and truncated regression models to interpret the
relationship between health insurance and health expenditures. In these two models, Fixed
Effects and Random Effects for the panel data of VLSS are included in the regression. Van
Minh et al. (2013) approach the research with the logistic model to examine whether the
catastrophe and poverty will decide the probability of having an out-of-pocket expenditure of

a household.
Other methods commonly used by several researchers is Propensity Score Matching
(PSM) and Difference-in-Difference (DID). While Wagstaff and Pradhan (2005) just apply
double difference for their research, Wagstaff (2010) later extend this method, ranging from
single difference, double difference, and triple difference, together with the matching method.
Nguyen (2012) combines OLS, IV, PSM, and DID in his research to measure the impact of
voluntary insurance on health expenditures for VHLSS 2004 – 2006. Fan et al. (2012) also
use DID analysis for their study in Southern India with the clear division of data into the
treated and control group. Recently, the paper of Alkenbrack and Lindelow (2015) employs
propensity score matching for 3000 households in Laos and then double treatment effects to
examine the influence of out-of-pocket payments.

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2.3.3 Control variables
A great number of control variables have been defined and listed in some studies
related to out-of-pocket expenditures. In general, control variables are composed of two types,
demographic and attitude variables.
Demographic variables include the characteristics of the household head (gender, age,
education, marital status, occupation, ethnicity, health status), the characteristics of the
household (size, income, expenditure, distance to healthcare providers, location, the elderly,
children), and the feature of healthcare services (insurance types, health facilities, outpatient
visits, outpatient contacts) (Jowett et al, 2003; Sepehri et al, 2006; Ekman, 2007; Sepehri et al,
2011; Fan et al, 2012; Nguyen, 2012; Aji et al, 2013; Van Minh et al, 2013).
Attitude variables are mention recently in the research of Alkenbrack and Lindelow
(2015). In this paper, aside from the demographic variables presented in the previous papers,
they take into account risk preferences of the household head and attitudes of households
toward insurance.

2.3.4 Results
The results on the impacts of health insurance on out-of-pocket payments show a
distinct polarization, making this relationship interesting for researchers across the globe to
pay their attention to. Health insurance may have no, positive, or negative effects on out-ofpocket payments.
King et al. (2009) indicate the insignificant impact of health insurance on healthcare
service expenditures for the case of households in Mexico. However, he says that this
insignificance may be due to the fact that the health insurance program is only distributed to
the poor and it lasts just for a short period of ten months. Nguyen (2012) points out the similar
finding that the voluntary health insurance has no impact on out-of-pocket expenditures. His
explanation is that health insurance only pays for the costs of healthcare and drugs, while he
defines this variable as the total of treatment and other related treatment costs. Another
problem may be due to measurement errors in measuring out-of-pocket expenditures for the
research data.
Ekman (2007) researches households in Zambia and shows that health insurance has
no role to play in the protection of household members from the catastrophe. He finds that this
influence of health insurance is mainly guided by the quality and the provision of the
insurance. The research suggests that the higher income a household has, the lower risks of
disasters it incurs, and the further a house is, compared to the healthcare service providers, the

10


higher spending on catastrophe a household suffers. In addition, those who are employed or
are farmers confront smaller risks of disasters than other groups.
On the contrary, Fan et al. (2012) found the negative relationship between health
insurance and out-of-pocket payments. The research shows that during the first nine months
after the introduction of health insurance, both inpatient and outpatient expenses reduce at the
state of Andhra Pradesh in Southern India. This result is proved to be robust after the use of
quantile regression and the matching method. Aji et al. (2013) give the same results when
doing research in Indonesia. They suggest that the two largest health insurance programs are

the main cause leading to the decrease in households’ out-of-pocket payments. Van Minh et
al. (2013) identifying the determinants of health spending on catastrophe show that the
enrollment of households in health insurance helps them lower the expenditures on
catastrophe and impoverishment. Alkenbrack and Lindelow (2015) say that those who are
insured have more opportunities to lower their out-of-pocket payments and disaster rates than
those who are not. They show a surprising result that the health insurance program protects
the rich better than the poor since the poor are unlikely to pay out-of-pocket costs.
The context of Vietnam rises some highlighted studies on the impacts of health
insurance on out-of-pocket payments. Jowett et al. (2003) indicate that both voluntary health
and student insurance make out-of-pocket payments decrease. Especially, health insurance
helps reduce out-of-pocket payments for Vietnamese households up to 200%. This effect is
clearly observed through the expenditures of the poor rather than the rich. Using the VLSS in
1993 and 1998, Wagstaff and Pradhan (2005) find that health insurance is positively linked to
the adoption of healthcare services and is the reason for the increase in the households’ visits
to hospitals. Finally, their study holds that health insurance is proved to cause out-of-pocket
expenditures to fall. In the further study, Wagstaff (2010) discovers that although Vietnam’s
Health Care Fund for the poor truly does not have any effect on the use of healthcare services,
it has, in effect, reduced out-of-pocket expenditures. Sepehri et al. (2006), like Wagstaff and
Pradhan (2005), use the panel data of VLSS in 1993 and 1998 to measure the effects of health
insurance. They then come to the same conclusion that health insurance decreases out-ofpocket payments after controlling unobserved heterogeneity. They show that health insurance
lowers out-of-pocket expenditures from 16% to 18% and that the decrease in expenditure is
larger for the high than the low-income households. Later research of Sepehri et al. (2011)
again supports the decrease in out-of-pocket expenditures by 24% if patients have either
compulsory or voluntary health insurance. As for the poor, the use of health insurance helps
them reduce their out-of-pocket payments by approximately 15%. The study proves that if

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patients visit healthcare centers at the district or higher level instead of the communal level,

they can lower their expenditures on health services. Both the compulsory and voluntary
health insurance have no effects at the commune health facilitates. In addition, compared with
those who are uninsured, those who are insured can decrease their out-of-pocket payments by
32% to 40%.

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CHAPTER 3: RESEARCH METHODOLOGY
AND DATA
3.1 Analytical framework
Based on empirical studies on the impacts of health insurance on out-of-pocket
payments mentioned above, the analytical framework analyzes the factors that affect out-ofpocket payments for this study include three groups of factors: (i) Socio-Economic and
Demographic Characteristics, (ii) Health insurance participation and medical service usage,
and (iii) Living Environment characteristics.

Figure 1. Analytical framework

Socio-Economic
and Demographic
Characteristics
Age
Gender
Education

Health insurance

Income
Marital status
Ethnics

Inpatient

participation and
medical service usage
Health insurance

Outpatient

Out-of-pocket
expenses per visit

Living Environment characteristics
Urban area
Rural area

3.2 Research Methodology
This study employs Pool OLS, Fixed Effect, Random Effect regressions to test the
impact of health insurance on out – of – pocket payments.

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3.2.1 Fixed Effects Estimation
In the fixed effects estimation, the unobserved effects 𝛼𝑖 is eliminated by using the
transformation. So do the time constant explanatory variables together with 𝛼𝑖 .
The transformation of the function by using the first difference is one of the methods
that help to put away the fixed effects (Woolridge, 2003). Another effective way is the
transformation of fixed effects. The method can be explained through the consideration of
these below functions.

For each 𝑖,
𝑦𝑖𝑡 = 𝛽1 𝑥𝑖𝑡 + 𝛼𝑖 + 𝜇𝑖𝑡 , 𝑡 = 1,2, … . 𝑇.

(3.1)

Now, for each 𝑖, average this equation over time. We get
𝑦̅𝑖 = 𝛽1 𝑥̅𝑖 + 𝛼𝑖 + 𝜇̅𝑖 ,

(3.2)

Where 𝑦̅𝑖 = 𝑇 −1 ∑𝑇𝑡=1 𝑦𝑖𝑡 , and so on. 𝛼𝑖 is unchanged over time; therefore, it is the
same in these two above functions. Then, the two are subjected from each other to gain this
following function
𝑦𝑖𝑡 − 𝑦̅𝑖 = 𝛽1 (𝑥𝑖𝑡 − 𝑥̅𝑖 ) + 𝜇𝑖𝑡 − 𝜇̅𝑖 , 𝑡 = 1,2, … 𝑇,
Or
𝑦̈ 𝑖𝑡 = 𝛽1 𝑥̈ 𝑖𝑡 + 𝜇̈ 𝑖𝑡 , 𝑡 = 1,2, … 𝑇,

(3.3)

Where 𝑦̈ 𝑖𝑡 = 𝑦𝑖𝑡 − 𝑦̅𝑖 is the difference between the real value and the average value of
the dependent variable. It is similar to the case of 𝑥̈ 𝑖𝑡 , the independent variables, and 𝜇̈ 𝑖𝑡 , the
error terms. Besides the name of fixed effects transformation, this method is also named the
within transformation. In the equation (3.3), the unobserved effects 𝛼𝑖 is removed, proposing
the use of Pooled OLS estimation for this equation. When Pooled OLS estimation is used
under this transformation, this estimator has the name of fixed effects or within estimator.
According to this estimator, y and x variate in time within cross-sectional observations.
After the addition of explanatory variables to the equation (3.3), we gain the model for
unobserved effects at first
𝑦𝑖𝑡 = 𝛽1 𝑥𝑖𝑡1 + 𝛽2 𝑥𝑖𝑡2 + ⋯ + 𝛽𝑘 𝑥𝑖𝑡𝑘 + 𝛼𝑖 + 𝜇𝑖𝑡 , 𝑡 = 1,2, … 𝑇.

(3.4)

Then, the application of the fixed effects method with time dummies and Pooled OLS
estimation as what is explained in advance is included to get the general equation demeaning
in time for each 𝑖
𝑦̈ 𝑖𝑡 = 𝛽1 𝑥̈ 𝑖𝑡1 + 𝛽2 𝑥̈ 𝑖𝑡2 + 𝛽𝑘 𝑥̈ 𝑖𝑡𝑘 + 𝜇̈ 𝑖𝑡 , 𝑡 = 1,2, … 𝑇.

(3.5)

This equation is estimated with Pooled OLS regression.
The fixed effects method will be biased if the strict assumption of the exogenous
problem is broken. The assumption is that the error term 𝜇𝑖𝑡 is not allowed to correlate with

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independent variables across time, but the cross sectional difference can have the correlation
with the explanatory variables. The transformation helps eliminate any explanatory variable
unchanged through time: 𝑥̈ 𝑖𝑡 = 0 for all 𝑖 and 𝑡, if 𝑥𝑖𝑡 is constant across 𝑡.
The degrees of freedom for this estimation is easy to incorrectly identify. In the
equation (3.5) calculated through Pooled OLS, NT is the total observations and k is the
number of independent variables. Therefore, the degrees of freedom can be inferred by taking
subjection of k from NT. However, this calculation creates a misleading result because,
through each cross-sectional observation, the degrees of freedom will reduce by one due to
the demeaning of time. In short, the true degrees of freedom should be 𝑑𝑓 = 𝑁𝑇 − 𝑁 − 𝑘 =
𝑁(𝑇 − 1) − 𝑘. Fortunately, the regression in the fixed effects package of statistics software
compute the degrees of freedom correctly. However, there is still work to be done, that is, the
correction of the standard errors and the statistical tests after the estimation of Pooled OLS.

3.2.2 Fixed Effects with Unbalanced Panels

When the data have missing values for individuals across years, the data set is called
unbalanced panel data. Different kinds of panels will have different estimations. Compared
with balanced panel data, the method of fixed effects estimation for unbalanced panel data is
far more difficult. In the equation, 𝑇𝑖 is denoted as the number of time periods for each
individual 𝑖. Based on this, 𝑇1 + 𝑇2 + ⋯ + 𝑇𝑁 is considered as the total number of
observations. As mentioned above, in the balanced panel data, the demeaning of time reduces
the degrees of freedom by one for each cross sectional individual. The package for this
regression method always shows the result of the degrees of freedom at the end of the
regression to adjust the degrees of freedom. The degrees of freedom are similarly calculated
as for the case of dummy variable regression.
When the observed individual has only a single time period, it has no effect on the
fixed effects estimation. Such kind of individual has zero time demeaning and is not included
in the estimation. What is considered difficult here is how to determine the panel data is
unbalanced. If the independent variables in the unbalanced panel data with missing value have
no correlation with the error terms 𝜇𝑖𝑡 , the unbalanced panel does not matter at all.
3.2.3 Random Effects Models
Similar to fixed effects method, the random effects method starts with the unobserved
effects equation,
𝑦𝑖𝑡 = 𝛽0 + 𝛽1 𝑥𝑖𝑡1 + ⋯ + 𝛽𝑘 𝑥𝑖𝑡𝑘 + 𝛼𝑖 + 𝜇𝑖𝑡

(3.7)

15