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ECONOMIES: Social Security and Fighting Poverty in Tunisia
ECONOMIES: Social Security and Fighting Poverty in Tunisia
ECONOMIES
Article
Social Security and Fighting Poverty in Tunisia
Hasna Khemili 1 and Mounir Belloumi 1,2,* ID
1 Faculty of Economics and Management of Sousse, LAMIDED, University of Sousse, Sousse 4023, Tunisia;
akermi_hasna@yahoo.fr
2 College of Administrative Sciences, Najran University, Najran 1998, Saudi Arabia
* Correspondence: mounir.balloumi@gmail.com or mrbelloumi@nu.edu.sa; Tel.: +966-530-948-710
Received: 21 October 2017; Accepted: 30 January 2018; Published: 19 February 2018
Abstract: The objective of this study was to examine the role of social security in fighting poverty in
Metlaoui, Tunisia, using survey data collected between July 2012 and January 2014, covering 200 poor
households. We used questionnaire data, which gave a thorough analysis of the reactions, behavior,
and strategies adopted by poor households as a result of various forms of risk. Social security has an
effect on a number of different areas, including health, education, housing, and income. Our
methodology explored both complete and partial risk-sharing, to investigate the impact of social security
schemes on the strategies adopted by households to cope with economic shocks. The estimation
results of different models showed that social security could help social security-covered households
choose less costly strategies to cope with risks. However, the role of social security remains insufficient,
given that covered households had less confidence in its services and they adopted strategies of self-
insurance or income smoothing. Overall, the results showed that social security plays an important role
in Metlaoui, but it remains insufficient, especially for households that are not covered by social security
and are suffering from heavy health expenditures.
Keywords: poverty; social security; inequality; shocks; economic growth; Tunisia
JEL Classification: C01; D31; I14; I32
1. Introduction
Vulnerability to risk is one of the main causes of poverty. There is broad agreement that social
programs reduce poverty and, subsequently, improve the welfare of households in the short term,
as well as the long term (Holzmann and Jorgensen 2000).
The Tunisian social security system includes three main categories of interventions against
poverty, exclusion, and inequality, and seeks to improve the welfare of households and reduce the
consequences of market risks. The Tunisian social security system covers salaried workers against
a range of risks, including unemployment. Social schemes can provide assistance and help protect
individuals and families from certain contingencies, like being unable to provide for their needs. The
level of contribution is not a fixed rate or amount, but varies according to the salary or wage level of
each individual. Social schemes come under the umbrella of the Ministry for Social Affairs and
Solidarity.
Social security institutions are organized in a network of national, regional, and local bodies. There
are two funds under State supervision, in Tunisia, that manage the statutory social security schemes: the
National Social Security Fund (CNSS) and the National Pension and Social Contingency Fund (CNRPS).
The National Health Insurance Fund (CNAM) manages curative and preventive medical care and
supplements both other funds. The National Social Security Fund provides social security for employees
and self-employed workers in the private sector, such as agricultural workers, farmers, anglers, domestic
workers, and some categories of low-income earners, artists, and
Economies 2018, 6, 12; doi:10.3390/economies6010012
Economies 2018, 6, 12
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intellectuals. It covers people against old age, invalidity, death, and unemployment. The National
Health Insurance Fund provides cover for social security affiliates in the public and private sectors. It
covers medical treatment for sickness, maternity, invalidity, employment accidents, and
occupational diseases. The National Pension and Social Contingency Fund provides coverage to
civil servants and public sector employees.
The applicable social security schemes differ according to their occupational category. The
contribution rate that is paid is not the same for all schemes, but is fixed according to the salary level
of each employee. There are two kinds of social security: voluntary and obligatory. Self-employed
persons may voluntarily insure themselves against the risks of occupational accidents and
occupational diseases. Alternatively, employers may be required to join the CNSS and must declare
the employees covered by this fund within a period not exceeding one month from the date of
engagement. The scheme is funded by salary contributions. It is levied based on the guaranteed
minimum wage, of which two thirds are paid by the employer (between 16.97% and 20.57%) and
one third by the employee (9.18%). It entitles the covered person to various social services, like
health care and a retirement pension.
Indeed, social security in Tunisia should play a key role in protecting employees against the
risks of unemployment, sickness, and aging, and contribute to strengthening the human capital and
productivity that is necessary for economic growth. Coverage must touch all social categories and
groups, including the employed, the unemployed, artists, and intellectuals.
The objective of this study is to investigate and quantify the impact of social security on the
vulnerability to risk and poverty in Tunisia. We will attempt to clarify and better understand the
impact of social schemes to reduce poverty in Tunisia, using the Metlaoui region as an example.
Our contribution is twofold. Firstly, we will apply the econometric model of Skoufias (2007) to
social security schemes in Tunisia, based on health care expenditure as a factor of poverty.
Secondly, we will differentiate the effect of income or health expenditure shocks on the risk coping
strategies used to finance economic shocks.
This paper is organized as follows. After a brief literature review, the empirical analysis will be
described. This analysis will employ data from household surveys, to evaluate the impact of social
security schemes on the strategies adopted by households to support themselves during sickness,
death, and old age shocks in Tunisia. A considerable portion of the analysis will compare whether
there are any differences in the correlation between household income and health care expenditure,
between those who are covered by social security schemes and those who are not. We will also
investigate how coverage might result in fundamental changes to how households cope with
economic shocks. Following an examination of the sensitivity of the results, the last section of this
paper will summarize the key findings.
2. A Brief Literature Review
In this literature review, we present a selection of studies that have investigated the relationship
between poverty and social insurance, the impact of economic, social, and natural shocks on the welfare
of households, and the degree of intervention of social schemes after these shocks.
Cochrane (1991) was one of the first to highlight the relationship between social insurance and
shocks. This was the first empirical study to address the impact of shocks on household consumption
and, subsequently, the social protection effect on the welfare of households. The author sought to find an
answer to the following problem: Are households actually insured against idiosyncratic income shocks by
formal or informal mechanisms? The results showed that, with perfect insurance, marginal utility should
grow at the same rate for all consumers, and that the distribution of the growth rate of consumption must
be independent of the shock’s variables. The data used in this study covered the period 1981 to 1984,
with a sample size of 2000 to 4000 people. The study concluded that the shock’s variables were
significantly correlated with the growth rate of consumption.
Economies 2018, 6, 12
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Dekker (2004) and Leliveld (2006) showed that illness is a significant risk for people in
developing countries. Illness is likely to reduce household income if people are not able to work and
cover the costs of treatment. Households often try to pay for medical care by selling productive
assets (e.g., land or cattle) or borrowing money. Such strategies increase the risk of becoming
trapped in poverty (Scheil-Adlung et al. 2006). Poverty is a topical subject and should, therefore, be
a central focus of social programs and future development. Employment is one of the key channels
by which economic growth is translated into a reduction in poverty and income inequality (Perry et
al. 2006). It is recognized that job creation is one of the most sustainable ways to reduce poverty.
Poverty is a multidimensional phenomenon. The vision of poverty that emerges has so many facets.
To highlight this multidimensionality, Handa et al. (2000) tried to combat against relative poverty in rural
Mexico by using the national poverty program ‘PROGRESA’. They investigated the impact of a social
transfer program on the welfare of households. Based on a survey of approximately 24,000 households
in 506 villages, Handa et al. (2000) showed that relative poverty increased between March and October
(the investigation period), but that this increase was less severe in treatment villages that were eligible for
‘PROGRESA’ benefits. This was also true for extreme poverty. A decline in poverty leads to a reduction
in inequality. This study showed the positive role of a cash transfer program in the reduction of household
vulnerability to risk and relative poverty.
Dekker and Wilms (2010) studied the impact of the health insurance program ‘Micro Care
Insurance’, particularly on out-of-pocket (OOP) expenditures. The authors explored the relationship
between health insurance and other strategies used to finance medical expenditures and,
subsequently, the influence of health insurance on household poverty in Uganda. Survey data were
collected from five rural and two urban communities in Uganda in June/July 2006. Insured and
uninsured people were chosen randomly to participate, with 259 total observations. To test the
relationship between health insurance and OOP health care expenditure, Dekker and Wilms (2010)
used ordinary least squares (OLS) regression and a Probit model. They concluded that health
insurance was an appropriate instrument to reduce the impact of health risks and an effective
poverty reduction strategy in developing countries. Moreover, insured households sold assets less
frequently and borrowed less money for the illness than uninsured households. Therefore, the
authors adopted the same conclusion as Young et al. (2006), who also found that health insurance
helped reduce work incapacity and increase productivity. When households were covered against
serious and costly diseases, they had lower OOP health expenditures and were less obliged to use
other risk-coping strategies. This resulted in overall improvements to welfare.
Social security is based on the idea of risk-sharing, where many people pay to cover the losses
of a few. This idea only works because losses are unpredictable, which means that households,
organizations, and governments commonly share risk through transfers and emergency loans.
However, most empirical research rejects the predictions of models where insurance is perfect and,
instead, show that risk-sharing does not provide full consumption smoothing (Cochrane 1991; Mace
1991; Townsend 1994). Kruse and Ståhlberg (2013) present various welfare programs that alleviate
the kind of risks households can encounter, such as not being able to support themselves due to
sickness, unemployment, or old age. Residual risk tends to be important. This is especially so in the
presence of aggregate shocks, because actors who share idiosyncratic losses are typically
simultaneously affected. Therefore, households cannot continue to make transfers between
themselves perfectly (Samphantharak and Townsend 2017). Imperfect risk-sharing may arise for
different reasons, such as the inability to insure aggregate shocks and limited commitment or
information asymmetry (Coate and Ravallion 1993; Attanasio and Pavoni 2011). Anti-selection, as a
result of hidden risk information limiting household access to insurance, can also be another reason
for insurance market malfunctions. The problems described are the main cause of systematic
failures in the complete insurance of affiliates.
Economies 2018, 6, 12
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3. Methodology
We chose to apply the model established in Skoufias (2007), which is based on a questionnaire and
gives a thorough analysis of the reactions, behavior, and strategies adopted by poor households in
response to risk. In addition, we chose the Metlaoui region in Tunisia, given that the specialty of this rural
region is mining and it is facing very serious shocks following the Tunisian revolution of 2011.
3.1. Data Sources and Description of Variables
3.1.1. Data
This study used four rounds of panel data from 200 poor households, surveyed to evaluate the
impact of Tunisian social security schemes on basic indicators of welfare in Metlaoui. Poor households
were classified as those with social security coverage (i.e., CNAM, CNSS, or CNRPS) and those without.
Our choice was not arbitrary, as we chose 200 poor families who needed government help. In
Metlaoui, there were almost 600 families receiving government subsidies in 2012. Among these
families, some had members who were recruited to the CPG1 in 2013. We selected 100 of these
families and 100 other families who were not employed, in order to obtain a credible evaluation of
the potential impact of these schemes. We obtained a list of those persons recruited to the CPG
from the Human Resource Management Service.
Furthermore, recent years have been characterized by the violent events that have occurred in
Metlaoui between tribal factions. This is likely to have affected household behavior in the region and
had a direct impact on the concepts of ‘complete’ and ‘partial’ risk-sharing. In this work, we attempt
to highlight the effect of these events and their influence on household strategies to mitigate
economic shocks.
3.1.2. Research Survey
The research survey included 35 questions collecting the socio-economic information required
to evaluate the social security schemes. A number of core questions, concerning the demographic
composition of households, were asked in each round of the survey. The questions assessed
education level, household size, the age, income, and occupation of the head of the household, the
total value of household, food, and non-food consumption, and variables characterizing the coping
strategies of households to income shocks.
The survey was carried out across four six-monthly periods between July 2012 and January
2014. Descriptive statistics of the main study variables for the poor households covered and not yet
covered, are shown in the Table 1.
Consumption, income, and health care expenditure are all expressed as growth rates, while the
variables representing shocks and household characteristics are all categorical variables codified as
zero or one.
The food consumption value consists of the sum of the value of consumption of fruit and
vegetables, cereals and grains, meats and animal products, and other foods. Expenditure on
durable goods and other luxury items are included in the calculation of non-food expenditures.
In economics, household income is the income that a household derives from their contribution
to economic activity, either directly (e.g., income from work or self-employment) or indirectly (e.g.,
furniture or real estate investment income). Therefore, we included declared income from work, self-
employment, pension, interest, rents, community profits, and government transfers.
Health expenditure, as defined by the World Bank, represent the total of public and private health
expenditure. This includes the delivery of health services (preventive and curative), family planning
1 CPG is a Tunisian phosphate company based in the governorate of Gafsa in Tunisia.
Economies 2018, 6, 12
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activities, activities related to nutrition, and health emergency services. In this study, household
health expenditure included expenditure on health care and services (hospital care, outpatient care,
medical transportation, and medical goods), as well as preventive medicine.
The variables identifying the various shocks experienced by households were acquired by direct
questions. In each survey, households were asked if, during the last six months, they had experienced a
drought, fire, flood, serious illness, or accident, and if, because of these shocks, they had lost their land,
crops, animals, houses, or other items. Finally, they were asked how they responded to these shocks, for
example, by selling land, selling household items, selling animals, receiving money from the government,
borrowing money, getting additional work, and/or receiving help from family members.2
Table 1. Descriptive Statistics.
Variables
Description of Variables
Covered Households
Non-Covered Households
Mean
SD
Mean
SD
TC
Total consumption per month (TND) 1
366.703
141.993
282.778
65.557
FC
Food consumption per month (TND)
229.929
81.468
176.631
52.549
NFC
Non-food consumption per month (TND)
136.773
82.681
106.147
44.067
R
Income per month (TND)
464.432
184.093
325.691
76.482
HC
Health care expenditure per month (TND)
74.361
111.038
142.251
123.194
LH
Loss of harvest
0.093
0.29
0.096
0.295
DLH
Death, or loss of house
0.07
0.26
0.083
0.276
IM
Injury of a household member
0.166
0.37
0.156
0.364
LO
Loss of articles or other items
0.116
0.32
0.11
0.313
HH
Gender of the head of household
0.086
0.281
0.07
0.255
AH
Age of the head of household > 50 (years)
0.246
0.431
0.173
0.379
ED
Education < primary
0.11
0.313
0.22
0.414
LOD
Lodgment
0.583
0.493
0.073
0.261
How they responded to these shocks?
BM
Borrowed money
0.2
0.4
0.12
0.68
SA
Sold animals
0.13
0.34
0.09
0.29
SH
Sold house or other item(s)
0.15
0.36
0.13
0.34
RF
Received help from family
0.19
0.39
0.2
0.4
RG
Received help from the government
0.093
0.28
0.22
0.41
WM
Worked more
0.22
0.41
0.176
0.382
1 TND: Tunisian Dinar.
3.2. Method
There are diverse strategies to insure against idiosyncratic risks. Rosenzweig and Wolpin (1993)
reported that households might be forced to sell assets when they face shocks. For example, livestock
transactions can smooth income fluctuations (Fafchamps and Pender 1997; Fafchamps et al. 1998). Self-
insurance is one of the most effective approaches to risk-coping (Lim and Townsend 1998).
3.2.1. Complete Risk-Sharing
Mace (1991) and Hayashi et al. (1996) assumed that, within a complete market, there is
complete risk-sharing. This means that income fluctuations should not have a significant impact on
the consumption of households.
We begin our empirical analysis by investigating the impact of social security schemes on the
strategies adopted by households to cope with shocks in Tunisia. According to the standard theory
of complete risk-sharing, Townsend (1995), Mace (1991), and Cochrane (1991), showed that GDP
fluctuations should not play an important role in explaining country-level changes in consumption. In
poor countries, social security is weak or non-existent and risks are frequently present, particularly
2 Some variables (such as family size and head of family) were not included in the analysis due to their strong collinearity
with the other variables.
Economies 2018, 6, 12
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the risk of unemployment, sickness, death, and adverse weather. For these reasons, social
assistance between households is crucial for poor households. Alderman and Paxson (1992)
distinguish that two of the strategies that are often adopted to cope with risks are self-insurance and
risk-sharing. This model is based on a consumer optimization problem, within the context of a
complete market (Deaton 1992). This concept allows households to protect themselves against
risks. The assumption of this model is that the growth rate of household consumption between t and
t 1 will be a function of the growth rate of shocks affecting the community. Therefore, Equation (1) is
the more commonly encountered equation in the literature. The formal tests for risk-sharing,
presented in Townsend (1994, 1995), Cochrane (1991), and Mace (1991), exploit the fact that the
growth rate of household consumption within an insured community, between periods t 1 and t, will
only be a function of the growth rate in aggregate shocks affecting the community. Equation (1)
summarizes the full risk-sharing hypothesis:
D Ln Cht = a + b D ln Rht + f Xht + D #ht
(1)
where DLnCht is the growth rate of total consumption per capita of household h, at period t; DlnRht
is the growth rate of income; X is a vector of the characteristics of the head of the household (i.e.,
whether the head of the household is a female, has a low level of education, has a lodgment, and is
more than 50 years old); a, b, and f are the parameters to be estimated; and #ht represents a
household-specific error term.
Equation (1) represents the relationship between the consumption growth rate, C, and the
income growth rate, R. The parameter, b, provides an estimate of the extent to which income
changes play a significant role in explaining the household consumption growth rate. It indicates the
partial correlation between income and consumption for non-covered households. If b = 0, there is
complete risk-sharing (Townsend 1994; Mace 1991; Jacoby and Skoufias 1998), while if b = 1, this
implies a total absence of any risk-sharing. For a low income coefficient that is close to 0, the full
risk-sharing hypothesis is rejected, which implies that the growth rate of consumption is related to
the growth rate of income. Therefore, we test the hypothesis of partial risk-sharing.
According to Amin et al. (2003), a high (low) estimated value of b means that as the degree of
consumption insurance decreases (increases) and there is a higher (lower) vulnerability of consumption
to income risk. In order to verify the complete risk-sharing hypothesis in a country, Skoufias (2007)
estimated a modified version of Equation (1), by which he tried to estimate risk-sharing for the poor who
were covered and not yet covered by transfer programs (Equation (2)). Skoufias (2007) investigated the
impact of social insurance schemes on vulnerability to risk for covered households. For this, the growth
rate of consumption was set as a function of the growth rate of income for covered and non-covered
households by including the binary variable, cot, as follows:
D Ln Cht = a + bDLn ( Rht) + cot (gp + bpD ln (Rht))+f Xht + D #ht
(2)
where cot is a binary variable taking the value of 1 for a covered household or 0 for a non-covered
household; a, b, bp, and f are the parameters to be estimated; and #ht represents a household
specific error term.
According to Heckman et al. (1999), the coefficient bp is the difference in vulnerability to risk
between covered and non-covered households. If bp is negative, this implies that social security is
associated with a decreased vulnerability to risk for the covered households.
Therefore, there would be complete risk-sharing for non-covered households if b is positive and
significant; whereas, if bp is significantly negative this would suggest that Tunisian social security
reduces the impact of income risks faced by households. We have documented that health care
expenditure has dramatic implications for household welfare. The aim of our analysis is to highlight the
impact of social health insurance on the welfare of households. To focus on our contribution, which
ECONOMIES: Social Security and Fighting Poverty in Tunisia
Social Security and Fighting Poverty in Tunisia
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ECONOMIES: Social Security and Fighting Poverty in Tunisia ( An sinh xã hội và Cuộc đấu tranh Sự nghèo khổ ở Tunisia )
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