Health reform in Colombia: more insurance and more segmentation?
CARLOS SOTO-IGUARAN
csoto@univ-paris1.fr
Comments and suggestions are welcomed
Laboratoire MATISSE- CES
Université Panthéon - Sorbonne
Maison de Sciences Economiques
Bureau 201 - 0144078184
106 -112 Boulevard de l’Hôpital
75013 – Paris
Abstract
In this paper, we intend to evaluate the Colombian health reform through an analysis of the
labour market. As the reform establishes, via the contributive regime, a link between
employment and insurance, we will look at the possibilities of accessing the health system
depending on the type of employment status. Therefore, our point of interest is at the
crossroad of labour market and welfare institutions.
Based on the theory of equalizing differences, we used a discrete choice model for calculating
affiliation probabilities. The same framework is found on neo-classic studies about individual
utility maximization related to welfare insurance. The particularity of our approach is that we
consider affiliation regime (used as the dependent variable) as a proxy of labour demand. This
enables to introduce the role played by employers on the decision of affiliating their
employees.
Introduction
Labour market segmentation theories were considered as a “challenge” for neoclassic theory
(Cain, 1976). (For instance it addressed) Criticisms challenged the link between productivity
and remuneration established by the human capital theory; but more generally, it was the
whole neo-classic methodology which was refuted. For Berger and Piore (1980),
discontinuities create differentiated working conditions within several markets, drawing aside
the idea of a unique and competitive market.
Many authors (Hodson and Kaufman 1982, McNabb and Psacharopoulos 1981, Cain 1976)
argued, however, that studies on segmentation did not constitute a coherent theoretical corpus.
Moreover, they suffered from an excess of empiricism reflected by the multiplicity of case
studies not always conclusive and considered too descriptive1. Furthermore, neoclassic
economists have succeeded, to a certain extent, to overcome this “challenge”. They integrated
segmentation hypothesis into their models by endogenising market structures, institutions and
which were not considered in their initial analyses.
The demonstration of a segmented labour market lies on an inoperative effect of human
capital on wages in a secondary market. In other words, this means that two different wage
equations are necessary for representing each segment. Based on the assumptions of human
capital theory, which links investment in education, labour productivity and remuneration
level, it is possible to find factors affecting wage determination. This type of exercise was
1
Usually, empirical papers base their analysis on factor analysis and classification methods have been widely
used. See, for example, Oster (1979), Tolbert et al. (1980) and Eymard-Duvernay (1981) and Cunninghan and
Maloney (2001). The advantage of these two methods is that there is no a priori allocation of individuals or
productive units in a particular segment. Though, these are exclusively descriptive techniques.
carried out in several studies on the Colombian labour market. Bourguignon (1979, 1983),
Fields (1990), Magnac (1991) and Uribe and Ortiz (2007) drew mitigated conclusions on the
existence of segmentation within the labour job market. They all assumed the existence of a
slightly competitive market.
In this paper we will look for an alternative empirical approach to highlight the structures
within the job market. By showing some limits of econometric techniques, as an appropriate
empirical tool, we will look propose an alternative, based on the theory of equalising
differences, for studying individual labour market status, related to social security
contributions. By this way we can explore the links between labour market segmentation and
the access to the health insurance in Colombia. The interest of studying these connections lies
in the fact that the labour legislation and the health system underwent various reforms since
the years 1990 with joint effects in the two spheres.
1.
Some issues on econometric techniques
The neo-classic approach to labour market segmentation is based on individual rationality and
maximization hypothesis. Mincer equations, that draw the productivity-wage link, are used
for explaining the labour market functioning. The logic that dominates is the efficient
allocation of workers, paid according to their productivity. Faced with alternative theories
challenges, neo-classics appropriated segmentation assumptions, in part, by the sophistication
of their own analytical instruments. These have, however, some limitations that we mention
briefly here2.
First of all, neoclassical models are subject to the dictates of the econometric technique. The
latter imposes some constraints which prevent from considering larger real facts. This can be
illustrated by considering the importance of econometric models assumptions. For instance,
according to Fields (1990), one need two conditions for defining what a segment is through an
endogenous variable (vis-à-vis wage determination). Labour must be homogenous in relation
to variables not considered; also, there cannot be any kind of mobility across sectors.
Although these restrictions can validate the test from an econometric point of view, we
believe that there lie many problems. According to these restrictions, in the presence of
mobile workers, it is not correct to “prove” the existence of segmentation from variables such
as the type of firm, the type of occupation or the employment sector. For Fields, these are
“income-determining factors which result from choices made by and opportunities open to
workers in their quest for an improved economic position”3. The existence of inter-sectoral
mobility increases the level of wages due to a higher level of education, ignoring this leads to
biased results of wage regressions.
This means that constraints of econometric tests fail to explore the impact of labour demand
factors on the structure of the labour market. We assume that the latter plays on the
determination of the forms of employment and occupation. However, regressions are
supposed to include both factors supply and labour demand. In this regard, Fine (1998) asks:
“What exactly is the equation being estimated, even from an orthodox, neoclassical point of
view? Is it the supply of labour or is it the demand for labour? Or is it some reduced form of
the two?”4.
Fine criticises human capital econometric models for interpreting variables coefficients’ on
the bases of their initial assumption. In the case of competitive markets, it may be the proxies
of human capital that explain a possible wage differential. But assuming the existence of
2
For more details see Soto-Iguarán (Forthcoming)
Fields (1990), p. 74. Types of firm, occupation and employment sector are endogenous variables in regard to
labour income.
4
Fine (1998), p. 66.
3
imperfections, these same variables are used to justify these imperfections. For instance, in
the case of competitive markets, a positive sign of the gender coefficient may be reflecting
individual innate skills. In the second case – where there are market imperfections, the sign of
the coefficient may be interpreted as the existence of discrimination against men or women.
In the eyes of Fine, this approach reflects two weaknesses. First, it fails to identify a structure
within the labour market due to the lack of distinction between supply and demand. Hence,
the question about what exactly is being modelled5. Lang and Dickens (1987) argue that both,
supply and demand, are included in these equations, but everything depends on a semantics
choice. This means that no total distinction is possible: “it is not evident whether education
should be considered as a characteristic of the worker or of the job”6.
Secondly, and more importantly, Fine states that the theory is validated mainly from a test of
significance, and not through an alternative hypothesis. This alternative hypothesis in the case
of human capital, for example, lies in a competitive market which is used as a point of
reference. However, as variables are included in the equation in order to reflect reality and its
non-competitive functioning, the point of reference becomes unstable and depends on factors
that one decides to take into account. This seems a common practice: to "accommodate" wage
regressions, thus, all variables supposed to have an impact on earnings, especially those
reflecting market imperfections, are included.
A second series of problems concern the wages functions which empirically validate the
human capital theory. Heckman and Hotz (1986) observe that using a linear wage functions is
a “central defect” of dualism tests. This criticism is also valid in the case of human capital:
“We have no a priori knowledge of the relationship between income and education”7. There
is no indication that the function that links education years to productivity follows that
direction. There is no evidence that someone with twice as much education in years than
another person is twice as productive. In this sense, “after correction of the selection bias, the
findings supporting the dual hypothesis could just be a misinterpretation of a specification
error”8.
Moreover, there may also be a bad specification as a consequence of the assumptions made
vis-à-vis the model’s variables. Considering the independence between variables in the
regression cannot highlight the underlying structures of the labour market9. This is a
theoretical mistake that implies that results of the empirical model are neither correct as “are
left out “mutually determining relation between variables such as gender, occupation, capitalintensive and sector employment”10. Considering those relations means recognizing that there
are underlying structures in the labour market.
Thirdly, another problem is related to the assumption of employment forms used in basic
models. The simplest form of segmentation is used in these regressions, that is, a dual
structure of labour is considered. On the other hand, employment forms are seen as
homogeneous ensembles. If neoclassic authors criticize the ex ante allocation of workers in a
particular segment, their assumption of the existence of an a priori formal sector separated
5
Fine illustrates this point with variables coefficients signs. For example, a positive sign for the part-time work
variable may suggest that the employers seek cheap and flexible labour, a negative coefficient may suggest, in
the contrary, the desire of a full-time job by workers.
6
Lang and Dickens (1987), p.6. According to these authors this lack of determination lies on the fact that the
education variable is a characteristic of the worker/job match.
7
Heckam and Hotz (1986), p.528.
8
Hanchane et Nohara (2003), p.57.
9
Independence is necessary in order to avoid multicollinearity that would lead to biased results.
10
Fine (1998), p.67.
from an informal sector is also questionable11. The empirical observation of the labour market
reflects a very different reality. Labour demand, ranging from the type of firms and industries,
jobs and occupations, is proving to take different forms. Thus, the division into two segments
results unlikely.
Although econometric instrument is useful to quantify relationships between different
variables and to highlight correlations, they do not necessarily lead to causalities. More
importantly, this tool seems insufficient to reflect the fact that labour relations are essentially
a social relationship. This relationship reflects the configurations of social and productive
organization, and is distinguished by power asymmetries between the participants in the
labour market. The limits of econometric tool can be illustrated with an example. If wage
regression coefficients indicate that two identical individuals have the same salary, the
assumption of segmentation is excluded. However, the conclusion is different if there are
different forms of subordination despite equal pay. In other words, if there are separate
working relationship in terms of contract type, stability, mobility, access to social security or
any other labour protection, we might speak of a segmented labour market, even if there are
identical workers paid at the same rate.
Having said this, we propose next an econometric model based on the theory of differential
compensation in which we will try to consider the impact of both labour supply and demand
2. Equalising differences model
In their study on labour segmentation, Dickens and Lang (1985) propose a model with a wage
equation for each employment sector and a third equation determining individual probability
of belonging to one employment segment. Their results, based on United States data, favour
the hypothesis of labour market segmentation. According to Heckman and Hotz (1986), the
rejection of the non-dualistic assumption is due to the fact that workers seek utility rather than
income maximisation. Regarding this point Magnac (1991) adds that if the sectoral choice is a
matter of individual utility, then segmentation is not a testable hypothesis: “if utility depends
on nonwage-related characteristics of jobs, the true model is no longer a Roy model but a
compensating wage differentials models”12.
Indeed, when testing the rationing of primary jobs, Dickens and Lang assume that workers
maximize their utility depending on income level but also on non-monetary jobs
characteristics, such as employment quality (schedule, risks, experience required, etc.) or
benefits regarding social security.
From our point of view, this is a crucial issue that binds employment to social insurance.
Note, however, that the mentioned correlations concern individual preferences -risk aversion,
for instance- and the type of employment chosen. We consider that this is one dimension, but
not the only one, which must be taken into account in the analysis of the relation between
employment and social insurance; we propose below a model of sectoral choice based on
utility maximisation.
However, the peculiarity of our model lies in the nature of the variable to explain. Our
hypothesis is that workers maximize their utility when they get access to social security. The
dependent variable used is the type of contributions to health insurance. A brief presentation
on the functioning of the Colombian social security system is thus necessary.
In 1993, a new health system was set up. The reform has altered resource flows: from then on,
health providers ought to sell their services to finance themselves, and system users chose
11
In the same way, it is possible to question the distinction of sectors according to a monetary threshold, when
jobs have more qualitative characteristics that distinguish them.
12
Magnac (1991), p.181.
among different health insurance companies (Graphic 1)13. Two separate systems were
created. Access to the Contributory regime (CR) is done through payroll taxes paid jointly by
employees and employers; self-employed persons can also pay the full amount by their own.
By this way they have right to a set of health services, called POS (Compulsory health plan).
People can also access the CR as beneficiaries of their spouse. The Subsidised regime (SR) is
a means-tested system; those who qualify to the subsidy (depending on their socio-economic
characteristics) get access to a set of health services14. Coverage increase is mainly explained
by the increase of the number of subsidies, which means that the system relies less on wage
insurance (Table 1). Hence the assumption that insurance increases together with higher
labour market segmentation, as different insurance modalities enrol workers in different
career paths15. We will try to highlight through our econometric model this double movement
which may seem paradoxical.
The originality of the variable chosen, which takes into account these different ways of
affiliation, is that it reflects individual labour market status. Belonging to the CR supposes
being engaged in a formal labour relation in which employers declare their employees and
contribute to their social security affiliation. In other cases, labour status may be more or less
formal, depending on the type of independent work considered16. Though occupying a
salaried employment does not guarantee the contributions to insurance schemes. This can be
explained by a combination of strategies deployed by mutual agreement, by households and
employers that lead to elusion and/or contribution evasion. Furthermore, this is only one
dimension defining informality which comprises evasion of labour legislation, not only
concerning health contributions, but also pensions, minimum wage, employment risks
legislation, etc.
The type of access to health insurance can be interpreted, on the one hand, as the type of job
offered, i.e. labour demand: employers choose the type of insurance given to employees.
Health insurance contributes to individual utility maximization; this depends on individual
characteristics that we may consider, on the other hand, as the labour supply. An interaction
between labour supply and labour demand is thus implicitly assumed in the partial
equilibrium model that we present now.
We suppose an economy where workers maximize their utility based on their wage (W) and
on a basket of consumer goods attached to their employment (S)17.
ui = ui (W, S)
In our case, S corresponds to the consumption of social benefits and takes the value 0 if the
workers have access to social security and 1 if access is denied.
ui = ui (W, 0) ou ui = ui (W, 1)
S takes a dichotomous form (insurance, non-insurance) but, as indicated, there are different
modalities of access to the system (see below).
13
Insurance companies (public or private), called EPS (Empresas promotoras de salud) or ARS (Aseguradores
del regimen subsidiado), contract with health providers (IPS – Instituciones prestadores de salud) to take charge
of their clients.
14
An annual survey (the SISBEN) identifies beneficiaries of the SR. It right to a set of health services (POS-S)
that corresponds to half of the services offered by the POS.
15
A labour reform was adopted in 1990 that introduced less restrictive forms of employment and made more
flexible employment contracts and less costly severance pay.
16
Micro-enterprises owners cannot be considered at the same level of street vendors..
17
We suppose that the all income is consumed and savings are thus inexistent.
The theory of equalizing differences, which is at the basis of our model, constitutes an
explanation of wage determination. Rosen (1986) explains that some type of compensation
should balance advantages and disadvantages between different types of employment. It is
therefore an alternative for explaining wage hierarchy, in opposition to segmentation theories
that study the existence of a pay scale and career paths across internal and external labour
markets.
In this sense, a worker would accept a job of lesser quality (in our case without access to
social security), if a premium compensates their opportunity cost. If W0 is the wage without
social insurance, W1 is the wage of protected jobs that equals to:
W1 = W0+Z
Z corresponds to the minimum compensation income required so that a risky job can be
accepted. Those who accept an unprotected job receive a higher salary. The additional income
will allow the equalization of the value corresponding to each type of work. Thus, they can
indiscriminately choose to work with or without insurance:
ui (W0, 0) = ui (W0+Z,1)
~
In terms of utility, the cost W of access to social security for each individual, i.e. the
sacrificed income W or lost utility, due to insurance benefit, is equal to:
~
W = ui (W0) - ui (W0- W )
~
By comparing the utility of being affiliated u(S), to the cost W , it is possible to determine for
each individual the choice concerning the payment of contribution to social insurance.
~
~
If u(S)> W , then the individual will seek affiliation. If u(S)< W , then affiliation will not be
~
considered, and finally, if u(S)= W , he will be completely indifferent.
The reasoning is similar in the case of firms, which are expected to maximize their profit. The
latter will compare the costs to the benefits of providing insurance to their employees. The
cost is associated to the wage percentage that employers must pay on behalf of their workers.
On the other hand, the profits of paying employee contribution, V, can be deducted from gains
in productivity, as a worker covered against social risks is supposed to be more productive.
The utility of profits, ui(V), represents a productivity differential between insured and
uninsured workers:
ui (V) = (va - vna)
The costs borne by firms Ŵ include both wages and the amount of employer contribution CP:
Ŵ = u(W0) - ui (W0- CP)
In the same way we saw for individuals, firms have three different possibilities to consider. If
u(V) is higher than Ŵ , then the firm will opt for the affiliation of workers to social insurance.
If, however, u(V) is less than Ŵ then any contribution will be done. Finally, if u(V) and Ŵ
are equal then the firm is indifferent towards workers insurance.
We try next to estimate the probability of affiliation to social security for workers in
Colombia. The explanatory variables combine individual characteristics as well as firms and
employment sector types. Affiliation probability is calculated by using discrete choice models
that can simultaneously integrate different modalities related to the dependent variable18.
These models can indeed explain discrete variables, i.e. qualitative variables taking
multinomial or dichotomous terms. In our particular case, we will assume the existence of two
mutually exclusive choices, which are based on the utility expected.
As linear probability models present some problems (estimated values outside the limits 0-1,
heteroscedasticity problems, residues not following a normal distribution), we will use nonlinear models: a logit model is estimated using the maximum likelihood method.
In this way, it is assumed that S, which represents individual preferences concerning
affiliation, and that CP, which represents firms’ affiliation costs, can be estimated according
to the following stochastic equality19:
Si   x xi  ui
CPi   z zi  vi
(3)
(4)
From these two equations, we consider that the type of contribution TC is a function of
individual characteristics and employment forms:
TCi   x xi   z zi  vi  ui
(5)
Variables included in the vector xi concern individual preferences like age, sex, family status
and household income. Other variables related to the labour market status are also considered,
as is the case of wage level, years of education completed and professional experience.
Variables included in vector zi, concern employment forms like type of employment contract
(verbal or written), the type of written contract (fixed or permanent) and type of occupation
(worker or employee of the private sector or the public sector, domestic employee, selfemployed, independent professional). On the other hand, there are variables related to firms’
characteristics as the economic sector and the number of employees.
3. Results interpretation
The data we use comes from the Encuesta Calidad de Vida conducted in 2003 among 22,949
households or 85,150 observations. With an error margin of less than 5%, the survey is
representative of nearly 11.2 million households, or nearly 43.7 million people. The sample
we used is restricted to the active population urban area.
The different regressions include individual independent variables and subsequently variables
related to the type of employment. The first modality of our dependent variable includes
contributors to the CR. As already indicated, this variable indicates the labour market status,
and those affiliated to the CR are supposed to work under formal working relationship20. The
results can be seen in Table 2. Coefficients correspond to the odds ratios estimates, which
equals the exponential regression coefficients. In the first regression (Column 1), we have
18
The same type of model is used by De La Rica and Lemieux (2003) in a comparative study of Spain and the
United States and Vargas (2007) in the case of Colombia.
19
We suppose that residues ui and vi are normally distributed.
20
It may be the case, though, that those persons contributing to the CR may not have a pension plan, enlarging
the spectre of informality.
included three economic sectors, and four types of occupation that correspond to salaried
employment: industry, construction and trade employ respectively 2.1 million, 740,000 and
4.2 million people, i.e. more than half of the occupied population (54%). Workers and
employees of the private sector exceed 5 million people, public employees are a total of
nearly 1 million, daily labourers do not exceed 150,000 and domestic workers are around
700,000 people.
According to the odds ratios in the table below, the relative probability of contributing to
health insurance increases 1.57 with an increase of one unit of the wage logarithm and 1.13
with an increase of one unit of the logarithm of hours worked per month. These results are
expected as a higher income increases the possibility of contribution, the same may be said
concerning the number of hours worked.
The effect is lesser in the case of higher education (1.08) or more experience (1.02). These
factors, close to 1, seem to fit real-life situations to the extent that education should not have a
cumulative effect over time on the likelihood of contribution. However, we can consider that
with a certain level of education, access to the CR is more likely, because, for instance a
university degree makes the access to formal employment easier. One might expect, the same
thing concerning experience, but the effect is particularly low. We must note that the
coefficient is even lower in the case of women.
In addition, being married has a positive effect in general, but in the specific case of women it
is significantly negative: being a married woman reduces the relative probability of
contribution by 0.54. This result coincides with a current situation in households where the
man plays the role of bread-winner and his affiliation benefits other members of the family,
while women remain in great part in charge of domestic tasks or work in informal jobs.
The gender variable, on the other hand, is not significant, thus we cannot see how it can affect
the contributing probability. The coefficient is 0.8 in the case of men, which is opposite to the
expected result as women are more frequently victims of discrimination and higher insecurity
on the labour market.
Regarding variables describing employment, several interesting aspects should be
emphasized. Firstly, the group of control concerning labour contracts corresponds to verbal
contract. The link is clear between affiliation to the CR and written contracts. However, there
is a significant differential between fixed-term contracts and those with indefinite duration. In
the first case, the chances of contribution are multiplied by 8, while only twice in the second
case.
Secondly, regarding the forms of employment, there are differences in respect to the control
group formed mainly by independent labour (workers and professionals). The groups included
in our regression have very high odds ratios. Public sector workers have the higher probability
of contribution (6.24) and for private sector workers the likelihood remains high but to a
lesser extent (4.9). The difference between the two types of occupation is understandable as
the state promulgates the law and should be the first to enforce it. Besides, more than half
public officials are unionized and often belong to special regimes. In the private sector the
situation is more unequal and heterogeneous. Although more important for domestic workers
than for day labourers, the probability of belonging to the CR (2.7 against 2) is greater for
these categories than for the control groups. This result may seem surprising, but can be
explained by the fact that those are salaried jobs in which employers choose unilaterally the
affiliation. This is less true in the case of independent labour as affiliation is purely individual
and may be less likely as their activities are more precarious. Again, we must remember the
heterogeneity of independent workers. But still, results remain very surprising as there is a lot
of informality among domestic workers and daily labourers21.
Differences are significant and demonstrate the impact of different forms of subordination,
with different degrees of stability and job quality. Those with a short-term contract undergo a
significant mobility that allows them to contribute to the CR, but not in a stable way. The
frequency of contribution will depend on the economic sector and the type of firm.
There are, indeed, some differences depending on the type of economic activity. We took as
regressors important and dynamic employment sectors such as industry, trade and
construction. In the last sectors there is, to a greater extent than in the first one, more informal
employment. If we define informality according to firms' characteristics, it is higher than 30%
in the case of trade, against 16% and 6% in the case of industry and construction, respectively.
However, if we take a broader definition, there may be greater informality in the case of
construction. In the case of trade, the number of self-employment remains very significant and
so is informality. Industry workers have a greater chance of being employed under formal
conditions, although this does not mean that informal employment is non-existent in this
sector. Differences between these three sectors, compared to other (agriculture, services,
transport) are reflected in the regression results. Affiliation probability to the CR is higher for
industrial workers (1.16), and is less than 1, in the case of construction and trade (about 0.8 in
both cases).
In a second regression (Column 2), we have included the number of employees by firms, as
additional variable, instead of economic sectors. The coefficients of variables described above
vary slightly. The control group is firms with less than 5 employees. The results are consistent
with the definition of informality defined by the size of productive units: the higher the
number of employees, the higher is the probability of affiliation22. Productive techniques,
legislation influence, labour relations, among others, are at opposite extremes in the case of
micro-enterprises (3 or 4 workers) and firms employing 200 or more persons. The latter are
more visible and thus obliged to respect the law to a greater extent. However, they can also
find different strategies so as to develop a more flexible management of their workforce.
In a second step, we sought to estimate probabilities of independent contribution (Column 3).
Firstly, the wage level plays significantly in this kind of affiliation. The coefficient is 1.74 and
shows a stronger relationship than in the last two regressions. Being a woman has a negative
relationship with independent affiliation. In this particular case, it is normal to find that
independent activities have a greater probability compared to others (salaried employees).
However, there are differences depending on the type of independence: small employers have
a greater relative probability than independent professionals, who in turn have a greater
chance of belonging to the regime than self-employed workers (coefficients are respectively
equal to 5.25, 3.18 and 3.06). These results may reflect the link mentioned between salaries
and this type of contribution. The negative coefficients of type of contract variables seem
obvious since, by definition, self-employed workers do not have legal relations with an
employer.
In a final series of regression we took the fact of being beneficiary of another person’s
contribution or from a public subsidy, as independent variables (Columns 4 and 5). We found
that in both cases there is a negative relationship with the salary, which is higher for those
benefiting from SR. These results seem normal in the sense that the public subsidy is awarded
on the basis on socio-economic criteria. Thus, low-income households usually belong to the
21
If the same regression we specify one type of occupation each time, in both cases we have contribution
probabilities inferior to 1 (0,6 in the case of domestic workers and 0,4 in the case of daily labourers).
22
The odds ratios follow the same direction of the former regression.
SISBEN. The reasoning is similar in the case of education years, for which there is also a
coefficient less than 1. Being a woman increases significantly belonging to these two forms of
affiliation. In addition, married women have a higher probability of benefiting from their
spouse, while unmarried women are more likely to receive a subsidy.
Coefficients regarding employment contracts are obviously negative as having a contract
supposes higher incomes and contribution to the CR. Finally, it is mainly independent
workers and those working on the trade sector, which are the most likely to be in this type of
affiliation.
4. Concluding remarks
Preliminary results obtained through the former discrete choice model show that labour
demand is significant in structuring the labour market. Variables concerning the type of firm
or other where employer choices come into play have an active role in determining people’s
affiliation to the health system. The reform adopted in the last years may have helped to
increase affiliation rates because of the existence of subsidies. But the existence of various
health insurance schemes leaded to the enrolment of workers in different forms of
employment and crated inequalities in the access to social protection; belonging to one of
these segments depends on individual characteristics as well as employment sector.
In a forthcoming paper, we sought to improve this initial hypothesis by interviewing
employers and employees of different sectors. To sum it up briefly, we noted that the labor
factor constitutes a mechanism of flexibility for firms, and in particular throughout the
different insurance modalities. To cope with different constraints (such as competition from
formal and/or informal firms, access and costs of financial credit, expensive laws, etc),
Colombian firms set up, among other strategies, a particular management of their human
resources. As a result, employment forms with hybrid characteristics (between formality and
informality) emerge, which are deployed inside or outside productive units and vary
according to workers characteristics.
Due to the limitations of econometric techniques presented in this paper and to the high level
of aggregation of available data, interviews with labor market actor seem as an ideal
complement for a deeper analysis of underlying labor market structures.
Graphic 1
The Colombian Health Stystem
Source: Gonzalez-Rossetti, A., Ramirez, P, (2000), p 34
TABLE 1
Health insurance affiliation (2000-2006)
Contributive
Regime (%)
Subsidised
Regime (%)
Contributive
Regime
(thousands)
Subsidised
Regime
(thousands)
Total affiliation
Total
population
Affiliation (%)
2000
2001
2002
2003
2004
2005
2006
33.5
31
30.1
31
33.8
33.7
36.28
25.5
25.7
26.1
26.6
34
40.4
42.99
9 510
11 069
11 444
11 867
15 553
16 581
20 107
14 193
13 336
13 165
13 805
14 857
15 533
16 971
23 703
24 405
24 609
25 673
30 410
34 114
37 078
42 321
43 010
43 834
44 583
45 325
46 039
46 772
56.01
56.66
56.14
57.58
67.09
74.01
79.27
Source: Ministerio de la Proteccion Social - DANE
TABLE 2
Probabilities of contribution/affiliation to the social security regimes
Contribution to the
Contibutive
Regime
(1)
Contribution to the
Contibutive
Regime
(2)
Independent
contribution
Labour contract
(Fixed term)
1.57
(0.000)
1.13
(0.002)
1.07
(0.000)
1.02
(0.000)
0.89
(0.147)
0.54
(0.000)
1.00
(0.003)
8.38
(0.000)
1.45
(0.000)
1.16
(0.000)
1.07
(0.000)
1.02
(0.000)
0.88
(0.099)
0.55
(0.000)
1.01
(0.003)
5.77
(0.000)
Labour contract
(Permanent)
15.68
(0.000)
11.18
(0.000)
Private employee
4.97
(0.000)
6.24
(0.000)
2.04
(0.002)
2.70
(0.000)
1.16
(0.005)
0.83
(0.068)
0.87
(0.005)
3.49
(0.000)
3.05
(0.000)
1.31
(0.257)
3.24
(0.000)
Log wage
Log hours worked
Education
Work experience
Man
Married women
Women experience
Public employee
Daily labourers
Domestic workers
Industry
Construction
Trade
(3)
Contribution
regime
beneficiaries
(4)
Subsidised
regime
beneficiaries
(5)
1.74
(0.000)
1.10
(0.033)
1.12
(0.000)
1.011
(0.000)
0.93
(0.504)
0.74
(0.008)
1.005
(0.127)
0.59
(0.000)
0.95
(0.027)
0.78
(0.000)
1.09
(0.000)
1.005
(0.010)
0.089
(0.209)
1.97
(0.000)
1.00
(0.946)
0.34
(0.000)
0.71
(0.000)
1.11
(0.000)
0.84
(0.000)
0.98
(0.000)
0.65
(0.000)
0.65
(0.000)
0.99
(0.240)
0.25
(0.000)
0.17
(0.000)
0.15
(0.000)
0.13
(0.000)
0.79
(0.005)
0.51
(0.000)
0.99
(0.942)
1.05
(0.359)
0.87
(0.185)
1.18
(0.000)
0.91
(0.149)
1.71
(0.000)
1.02
(0.665)
3.18
(0.000)
1.11
(0.281)
0.227
(0.000)
1.37
(0.000)
1.04
(0.840)
25745
-9034.29
1.08
(0.069)
0.62
25745
-8776.64
3.06
(0.000)
5.25
(0.000)
25745
-5517.50
25745
-8145.8
0.4804
0.177
0.1255
0.1984
Less than 10
employees
Less than 50
employees
Less than 250
employees
1.62
(0.000)
2.62
(0.000)
3.44
(0.000)
More than 250
employees
3.70
(0.000)
Independent
Professionals
Independent workers
Small Employers
Observations
Log likelihood
Pseudo R2
25745
-9010.09
0.4803
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