Mosca, I.

Schut-Welkzijn, A.

English

Research Papers in Economics

ORIGINAL PAPER
Choice determinants of the mobility in the Dutch health insurance
market
Ilaria Mosca Æ Anoushka Schut-Welkzijn
Received: 17 February 2007/Accepted: 17 August 2007
 Springer-Verlag 2007
Abstract We estimate a Logit model for the choice
determinants of the mobility in the Dutch market for health
insurance in 2006. The results highlight that socio-eco-
nomic, geographical, and health-related factors matter in
the decision to switch health care insurer. Moreover, pre-
vious contact with the insurer and the former type of health
policy are also of inﬂuence.
Keywords Health care insurer  Switching 
Choice determinants  Logit model  Marginal effects
JEL Classiﬁcation I10  I11  C25
Introduction
As of 1 January 2006, the new Health Insurance Act (HIA)
has been put into effect in the Netherlands. The new act
uniﬁes the old sickness fund scheme and private health
insurance into one mandatory scheme for all residents. This
single health insurance scheme covers essential care. There
is a basic package, which is mandatory and deﬁned by law.
Moreover, there is additional insurance covering all health
services not included in the basic package that can be
purchased on a free basis. Insurers are legally obliged to
accept everybody applying for the mandatory package,
regardless of age, gender, or health status. A reﬁned risk
adjustment system is in place to compensate insurance
companies for cost differences induced by socio-economic
factors such as age, gender, income, location, and prior
healthcare consumption. Such a system levels the playing
ﬁeld for health insurers by enabling price competition on
the premium rate [7]. The HIA aims to guarantee universal
access to the healthcare system.
Consumers could decide to switch to a new healthcare
insurer, alternatively, to stay with the current health
insurer, until 1 March 2006. During this period a ques-
tionnaire was issued by Center Data (Tilburg)
1 examining
the switching behaviour of the Dutch population. The
dataset used contains 2,172 observations; 26% (n = 568)
switched insurer. Through a Logit estimation we describe
the choice determinants of the mobility in the Dutch
market for health insurance for the year 2006.
The new Dutch health insurance system
As of January 2006, a new insurance system for curative
healthcare came into force in the Netherlands. Under the
new HIA all residents of the Netherlands are obliged to
take out health insurance. The HIA consists of a basic and
mandatory package of services deﬁned by law, and of an
additional insurance that is taken out on a free basis (93%
of the population purchased it [3]). Competition between
health insurance ﬁrms is a central pillar of this recent
The views expressed herein are those of the authors and no ofﬁcial
endorsement by the Dutch Healthcare Authority is intended or should
be inferred.
I. Mosca (&)
TILEC, Tilburg Law and Economics Centre, Tilburg University,
P.O. Box 90153, 5000 LE Tilburg, The Netherlands
e-mail: i.mosca@uvt.nl
A. Schut-Welkzijn
Dutch Healthcare Authority, Utrecht, The Netherlands
1 The questionnaire was assigned by the Institute of Health Policy
and Management (iBMG), The Netherlands Competition Authority
(NMA) and the Supervisory Board for Healthcare Insurance (CTZ).
123
Eur J Health Econ
DOI 10.1007/s10198-007-0073-2market-based reform. The use of the selective contracting
clause, which enables insurers to enter into participation
agreements only with certain care providers, stimulates
more competition between them. The other main goals of
this reform are to guarantee an equitable and cost-efﬁcient
healthcare system in the long run, preserve individuals’
freedom of choice, and enhance room for contracting
between providers and insurers.
The new system is a private health insurance with social
conditions. It is operated by private health insurance
companies (both for proﬁt and not for proﬁt); the insurers
are obliged to accept every resident in their area of activity
and must guarantee that their enrolees will get the neces-
sary medical treatments within a certain time and
geographic area; in other words, they should contract suf-
ﬁcient care to cover the demand of their enrolees; a system
of risk equalisation that contains parameters correcting for
health status differences related to age, gender, and other
objectively measurable client health characteristics enables
the acceptance obligation and thus prevents direct or
indirect risk selection. Universal access to the healthcare
system is hence guaranteed.
The premium for the new insurance consists of two
components: a community-rated nominal premium of
around Euro 1,000 paid by insured as from the age of 18.
The size of this premium varies among insurers and is
unrelated to age, gender, income, or health status. How-
ever, everyone with the same policy will pay the same
insurance premium. The second premium component is an
income-related contribution that equals 6.5% of the income
and will be payable up to the income ceiling of Euro
30,015 [6]. The income-related premiums are collected
through payroll and income taxes and are redistributed
through the risk-adjustment system.
A healthcare allowance has been introduced in order to
keep insurance premiums affordable. This allowance is
paid via the tax authorities and has been designed to make
the system ﬁnancially accessible to all income groups, so
that a tax credit is given to people before they have to pay
the insurance premium [6].
2
Data and switching model
In order to understand the main determinants contributing
to the decision to switch health insurer, we use a Logit
speciﬁcation. The Logit model (or binary choice model)
allows to design the choice between two discrete
alternatives, in our case between switching and not
switching health insurer. The Logit model describes the
probability that yi = 1 directly, although they are often
derived from an underlying latent variable model [8]. In
our analysis the probability that an individual changes
insurer depends on a set of covariates that consists of socio-
economic variables (age, gender, education and income
level), health status, geographical and insurance-related
factors. A brief description of these regressors is given in
Table 1.
Regression results are shown in Table 2. Almost all
variables are signiﬁcant and hold the expected sign.
Moreover our results are in line with the ones of [2] and of
[3]. In the report of [2] there is an analysis of the switching
behaviour of the Dutch population and the determining
factors. The authors estimate a multivariate model and
conclude that the main causes of changing insurer are age
(old people change less), the knowledge of the new
healthcare system organisation (more knowledge, more
switching), the length of the contract with the insurer (the
longer an individual has a contract the lower the switching
rate), families with teenagers (they switch more), and the
level of satisfaction of insured (the more satisﬁed the less
the switch). The study of [3] conﬁrms that the most
important factors inﬂuencing the choice of switching
insurer are: age (old people change less), education level
(highly educated people switch more often), health status (a
better health favours switching), living in a urban area (it
inﬂuences switching positively), and being part of a family
with children (they change insurer more often).
Our results lend support to the following: the probability
of switching from one insurer to another decreases with
age. Young individuals are therefore expected to switch
more often, while the elderly might avoid switching
because they are afraid of being rejected by the health
insurer. The probability of changing insurer augments if the
education level is high. Highly educated people were likely
more informed about the changes taking place in the
healthcare system.
Those households with a monthly gross income higher
than Euro 4,552 have a greater probability of switching.
3
Individuals with a partner and more than one child (below
18 years) also switched more, probably due to the fact that
children below 18 years must pay no nominal premium.
The regression results also depict that healthy people
have a higher probability of switching. This result is quite
intuitive; these individuals do not face any risk of being
cream-skimmed by the insurer. Moreover, the fact of living
in the three major cities (Amsterdam, Rotterdam, The
2 The size of the allowance depends on the income: a single person is
entitled to the allowance if his yearly income is below Euro 25,000,
while the threshold of a household with a joint income is set at Euro
40,000.
3 This amount is set by the Ministry of Social Affairs each year and it
refers to two times the gross monthly maximum income on which
health insurance premiums are being paid by employers.
I. Mosca, A. Schut-Welkzijn
123Hague) increases the chance to switch, being the presence
of different health insurers that compete for the same local
market much higher than in other parts of the country (e.g.
the South).
Finally, those people who did not have any contact in
the previous 12 months with the health insurer switched
less. The individuals with a private health insurance in
2005 had a higher probability of switching.
4
We subsequently test the goodness-of-ﬁt of the esti-
mated model. Both the Pearson chi-square [1] and the
Hosmer–Lemeshow chi-square test [5] do not reject the
hypothesis that the outcome probabilities estimated by the
model agree with the empirical outcome probabilities.
In Table 3 we report the marginal effects [4]: The
probabilities of switching increase by 0.15 for people with
an excellent health status, and decrease by 0.09 for those
individuals who did not have any contact in the previous
12 months with the health insurer. Furthermore, the
probability of switching for the elderly decreases by
0.003.
Discussion
Our econometric analysis shows that the most important
factors determining the mobility in the Dutch health
insurance market in the ﬁrst year of the reform (2006) are
age, education level and health status, income, geographic
area of residence, and having a partner and at least one
child. It turns out that young and well-educated people are
more likely to switch insurer. As some insurance compa-
nies are based in speciﬁc regions, one might expect that—
given that young and highly educated people may change
jobs more frequently—they also move more often than
other people to other regions in the country. This reasoning
Table 1 Description of the regressors
Variable Description
Age The dataset ranges from the minimum age
of 18 to the maximum age of 91
Gender Female/male
Middle education An individual is middle educated if (s)he
has a secondary education diploma
High education An individual is highly educated if (s)he
has at least a university degree
Good health The individual reported that her/his health
status was good
Excellent health The individual reported that her/his health
status was very good or excellent
Three cities The individual lives in one of the three
major cities in the Netherlands
(Amsterdam, Rotterdam, or
The Hague)
South The individual lives in the Southern
provinces of the Netherlands
Couple The individual has one partner and at least
one child
Income The gross household income is equal to,
or higher than € 4,552. This amount is
set yearly by the Ministry of Social
Affairs and refers to two times the
gross monthly maximum income on
which health insurance premiums are
being paid by employers
Contact insurer The individual did not have any phone or
written contact with the health insurer
in the last 12 months
Insurance The individual was privately insured
in 2005
Table 2 Regression results
Variable Logit coefﬁcient estimates
Age –0.017*
(0.004)
Gender –0.048
(0.104)
Middle education 0.200
(0.134)
High education 0.372*
(0.134)
Good health 0.395**
(0.166)
Excellent health 0.750*
(0.180)
Three cities 0.301**
(0.137)
South –0.258**
(0.127)
Couple 0.238**
(0.114)
Income 0.288**
(0.122)
Contact insurer –0.446*
(0.104)
Insurance 0.323*
(0.109)
Constant –0.946*
(0.316)
Standard errors in parenthesis
*, ** Signiﬁcantly different from zero at the 99 and 95% conﬁdence
interval
4 In the Netherlands it is also possible to take out a group health
insurance, for example via the employer. Group health insurances
normally offer a discount on the monthly premium.
Choice determinants of the mobility in the Dutch health insurance market
123can partly explain the higher rate of switching of young
individuals, in addition to other factors such as good health
status.
It is also likely that the impact of higher income is partly
related to the above-mentioned mechanism. If young and
educated people effectively change jobs more often, and
therefore their area of residence, then they can affect
switching positively.
Young and educated people live in big cities, especially
when starting up their careers, and this might also inﬂuence
the probability of switching insurer.
Conclusions
The recent change in the Dutch healthcare insurance sys-
tem has caused a massive switch between insurance
companies. About 18% of the whole Dutch population
changed insurer in the ﬁrst months of 2006 [3]. It thus
seems that people were spurred to shop around and look for
better insurance policies. In this paper we investigate the
main choice determinants of the mobility. Based on data
collected through a questionnaire we can afﬁrm that health
status, socio-economic, geographical, and previous insur-
ance-related factors have inﬂuenced the decision to switch.
References
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Table 3 Marginal effects
Variable Marginal effects estimates
Age –0.003*
(0.001)
Gender –0.009
(0.019)
Middle education 0.038
(0.026)
High education 0.071*
(0.026)
Good health 0.072**
(0.030)
Excellent health 0.150*
(0.038)
Three cities 0.059**
(0.028)
South –0.046**
(0.022)
Couple 0.045**
(0.022)
Income 0.055**
(0.024)
Contact insurer –0.085*
(0.020)
Insurance 0.059*
(0.019)
Standard errors in parenthesis
*, ** Signiﬁcantly different from zero at the 99 and 95% conﬁdence
interval
I. Mosca, A. Schut-Welkzijn
123

A Guide To Modern Econometrics.

Applied Logistic Regression.

Authority: De tussenstand op de zorgverzeke Ringsmarkt,

Changes and Challenges of the New Healthcare Reform in The Netherlands: What Should the Dutch Be Aware Of? SSRN Working Paper No.

Chi-square diagnostic tests for econometric models: theory.

Econometric Analysis. Upper Saddle River:

Het overstapgedrag van de Nederlandse bevolking binnen het nieuwe zorgstelsel en de achterliggende factoren die hierop van invloed zijn. Amsterdam: Vrije Universiteit

W.P.M.M.: Rationing and competition in the Dutch Health Care System.

Choice determinants of the mobility in the Dutch health insurance market.

Choice determinants of the mobility in the Dutch health insurance market.

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