It is widely acknowledged by economists that a households welfare depends
not only on their financial status but also to their vulnerability to risks
and shocks (Jha et al., 2010) and how they cope
with the situation (White and Robinson, 2000). Household
vulnerability to poverty and the related under-development could serve as an
indicator to poverty. It is not only a more satisfactory measure of welfare
but also a part of the factors which determine National Income in particular
and Gross Domestic Product in general. Majority of the poor face the greatest
risks which continues to impact negatively on their welfare due to substantial
losses of their income, high consumption rates and weak wealth creation, when
these shocks occur. Hanjra et al. (2009), Acosta-Michlik
and Espaldon (2008) and Kapoor and Ojha (2006) opined
that rural households are seem to be vulnerable because they are located in
prone areas where there are less developed markets. In many developing countries,
formal mechanisms are poorly developed in the rural areas. In India for instance,
formal credit facilities are more developed in low risk than in high risk areas
(Holden and Bins Wanger, 1998). Furthermore, they experience
lack access to different types of resources such as financial aids (Carter
et al., 2007; Osman-Elasha et al., 2006;
Kamruzzaman and Takeya, 2008).
The lack of formal mechanisms such as financial institutions (credit and insurance)
reduces the capacity of rural households to invest in risk-coping technologies
(Baez, 2006). Therefore, rural households fear to adopt
technological innovations in the presence of risks or future risks associated
with fluctuation and unknown return.
Households have different tools or behaviours to overcome these shocks and
manage the onset and consequences of the risks. Households adopt both long-term
and short-term coping strategies to handle with stressors (Mwangombe
et al., 2011). However, the effectiveness of their performance is
characterized by the availability of significant resources and entitlements
as well as on their ability to cope with and manage the stressors (Alpizar,
2007). Formal strategies are important mechanisms which offer aid and risk-coping
to rural households for dealing with various risks and shocks. When formal credit
institutions are unavailable, rural households depends on the informal mechanisms
as the next best alternative to deal with situation. Although these (informal)
mechanisms are useful to increase the risk bearing capacities of households
to idiosyncratic risks, they do not allow an efficient reallocation of covariate
risks (Baez, 2006). These strategies are believed to
be relatively expensive and do not achieve farm efficiency and in some cases
exacerbate the extent of poverty of rural households (Rosenzweig,
1988; Townsend, 1994; Fafchamps
and Lund, 2003).
The effectiveness of risk management and coping strategies of households in
order to cope with and manage against adverse risks and shocks could be determined
by many factors such as personal, cultural and social (Hinton
and Earnest, 2010; Reid and Vogel, 2006), the nature
(severity and frequency) of risks and shocks and peoples socioeconomic
conditions (Paul and Routray, 2010), the economic liberalization
(Eriksen and Silva, 2009). These studies concluded that
households choice of strategies to manage adverse risks and shocks depended
on the circumstances in which these strategies were employed and the purpose
for which the strategies were intended.
While stressors such as natural disasters cause a serious threat to the wellbeing
of households, only a few studies have quantitatively analysed this aspect (Van
Der Berg, 2010). To fill this existing vacuum therefore, there is a need
for more empirical analysis on the coping strategies of households, in relation
to risks and shocks such as natural disasters. It would be crucial to investigate
and analyse as to how people handle with risks to formulate a comprehensive
understanding on the complexities and the dynamic of poverty (Liu
et al., 2008). Consequently, there is little known about the link
between households coping strategies, government policies and institutions
such as NGOs (Miller, 2008). The present study adds to
this limited information an insight analysis by investigating the dynamic interactions
between households coping and/or risk-management strategies, communities
and institutions. It tries to answer the following questions: What determines
households and communities resilience? How could institutional capacity (support)
affect households responses to risks and shocks? Do these institutions
lead households to fall into poverty traps?
MATERIALS AND METHODS
To investigate the impact of stressors on the wellbeing of households and their
risk-management and coping strategies, the present study utilizes a quantitative
research method. Data was collected using of a structured socio-economic questionnaire
containing both open and close-ended items. The questionnaire administration
was cross-sectional in nature. Before administering the questionnaires, a pilot
test was carried out to test the validity and reliability of the instrument
and to ensure that the questionnaire can be understood and accepted by farmers.
The pilot study was conducted with 50 farmers in both Kelantan and Terengganu
on November 2010. In this study, a multistage sampling technique was used for
a representative number of households. The first stage was the selection of
two local government states which are Terengganu and Kelantan. The reasons for
choice is because the two states have been noted to have the highest poverty
rate within peninsular Malaysia and are the areas with the most vulnerability
and exposure to natural disasters such as flood (Ahmad, 2007).
The second stage was the selection of three rural districts (strata). The areas
selected include: Pasir Putih in Kelantan and Besut and Setiu in Terengganu.
In the third stage, households of farmers were then randomly selected and surveyed
as representatives of the two states. In order to obtain an accurate data and
minimize bias, the questionnaire was distributed to the respondents face to
face and in the local language (i.e., Bahassa Malaysia), where the researchers
explained all the part of the questionnaire to the respondent properly. Between
January and February 2011, 400 questionnaires were distributed to the respondents
but only 302 were completed in the three communities as follows; 100 questionnaires
were received in Pasir Putih, 102 in Besut and 100 in Setiu.
Measurement of variables: To measure the research variables a wide range
of measuring scale and strategies are used. The items were adapted and adopted
from previous studies, while some items were developed by the researchers. In
this study, the dependent variable is the households monthly income1.
The independent variables are exposure to risks and shocks2;
institutional capacity3 and the households
ability to cope4 with them.
Statistical analysis: Data obtained was analysed using Statistical Package for Social Sciences (SSPS) for windows, version 17. A simultaneous model (Multiple regressions) was carried out to investigate and examine the impact of various types of risks and shocks, households strategies and institutions on households monthly income. Pearson correlation coefficients were calculated to determine the relationship between households strategies and institutions support, poverty, age and educational level, respectively.
Demographic profile: Descriptive statistics (frequencies and percentages)
were calculated and revealed the following (Appendix, Table A);
98.3% of the respondents were married, 96.7% were male. A large percentage of
the subjects were less educated as 29.8% of the respondents reported to have
no formal education, 24.5% finished their primary school, 15.6% completed secondary
school while only 29.5% finished high school and 0.7% of the respondents continued
studying to the university level. The data also indicated that poverty is widespread
among farmers in these communities, as 9.9% of the respondents were found to
live in hard-core poverty, 60.3% are poor and only 29.8% are non-poor (Appendix,
Risks, institutions and households strategies: Households found
to be prone to several covariate and idiosyncratic stressors (Appendix, Table
B). The results showed that floods, economic recession and illness which
prevented respondents from work were the most severe stressors which affected
households income. Idiosyncratic stressors were also present among these
communities but in low percentages, compared to covariate stressors. Although
the results indicates that households use a variety of ex-ante and ex-post strategies
to manage against and cope with unexpected stressors (Appendix, Table
C), only few of these households in the communities evaluated were able
to adopt these strategies. Access to assets and entitlements was another problem
identified in these communities. Most of the respondents did not have access
to facilities and programs provided by various institutions as the results (Appendix,
Table E); indicated that over 46% of the respondents were
not aware about the programs, 11.92% were not selected and 10.26% reported that
no programs of such description existed in the area. Only 29.1% of the respondents
had access to health care facilities, 11.9% had accesses to disaster risk-management
training, 14.2% accessed climate change information and only 9.3% received food
aids (Appendix, Table E). Access to other programs such as
financial aids, market employment information and employment opportunities were
very limited (less than 5%), nevertheless, a high percentage (66.55%) of those
who attended these programs indicated to have benefited from these programs.
Only 24.5% of these programs were provided by government institutions, 20.7%
by Community-Based Organisations (CBOs) and 20.6% from Non-Government Organisations
(NGOs) (Appendix, Table E). Households were found to be recovering,
although slowly, from the shocks which they have experienced, where 82.4% indicated
that they were able to recover (completely or partially) from experiencing threats
and 48% of them took between 3 to 6 months to recover (Appendix, Table
The effects of stressors on households income: Table
1 summaries the results of the impact of stressors, households strategies
and institutional supports on households monthly income.
|| The effects of stressors, households strategies and
institutions on households income
|r2: 0.772, Adjusted r2; 0.595, F: 8.791,
Sig.: p<0.01*, **, *** -indicate the significance level at 1, 5 and 10%,
respectively. 1USD = 3RM, Dependent Variable: Households monthly income
Floods, low economic level and illness were found to significantly reduce households
monthly income at 1% significance level. The statistical results indicated that
these three stressors are the major threats which households suffer from. The
results of Table 1 showed that if a household experienced
flood, low economic level and illness, then its monthly income reduces by RM81,
RM102 and RM52, respectively. Surprisingly however, harvest failure and heavy
rain positively affected households monthly income at 1% significance
level. The results of Table 1 showed that if a household experienced
heavy rain or harvest failure threats, its monthly income increased by as much
as RM67 and RM192, respectively. Other stressors such as droughts, strong winds,
pest and diseases, increase food prices and loss of job or reduce salary found
not to have any effect on farmers income.
The majority of households recovered from the stressors which they experienced. Data showed that when a household recovers from stressors, its monthly income increased by RM102. The time of recovery is an important factor which could enhance households living. The longer the recovery time, the higher the reduction in monthly income occur. The results showed that when a household took one more period longer to recover, then its monthly income decreased by RM72.
The impact of households strategies on their income: Although
households implemented a variety of risk-management and coping strategies in
their daily lives in order to manage against and cope with unexpected threats,
only few of these strategies were significantly effective and efficient. Some
of the strategies were found to have negative impact on their income. The results
of the survey on this aspect indicated that risk reduction strategies (less
risky production activities) and coping strategies (spending saving and out-migration
looking for job) threaten households income, as the results showed that
by implementing these strategies, households monthly income decreased
by as high as RM123, RM139 and RM166, respectively.
Collection and selling of natural resources (from the forest) and selling of non-productive assets have positive effects on households monthly income (Table 1). The results indicated that these variables have the positive sign at 1 and 10% significance level, respectively. Collection and selling of natural resources lead to an increase in households monthly income by RM119, while the selling of non-productive assets increase the monthly income by RM76 (Table 1).
Other strategies that farmers had implemented such as adopting new technologies in production, doing multiple jobs, investing in assets, getting insurance, reducing diet, decreasing expenditure, getting loans, working in relief programs, getting assistance and selling productive assets found not to have any impact on farmers income.
The impact of institutional support on households income: The
role of government and non-governmental institutions did not significantly contribute
to the enhancement of households wellbeing in the communities studied.
Data showed that households were able to participate in only 7 of the 13 types
of programs which were listed to them. Only one type of these programs (Financial
Aids) recorded a significant impact on households monthly income. Households
monthly income increases by RM155 when it benefits from financial aids (Table
|| Pearson correlation test
|r denote Pearson correlation, *, ** -indicate the significance
level at 1 and 5%, respectively
The benefits from the programs which households attended were found to be limited.
Households increased their production by investing the financial aids which
they accessed from these programs. The results (Table 1) reveal
that those households which benefited from financial aids and as such, increasing
their production are able to boost their monthly income by RM197.
The relationship between institutions supports, age, education, gender, poverty and households strategies: In order to investigate the relationship between households strategies and the institutions support, Pearson correlation coefficient was calculated. Table 2 show, that there exists a positive relationship between households coping strategies and institutions supports.
The more supports households obtained from institutions, the more their coping strategies are (r = 0.31, p = 0.000). In contrast, no relationship was found between programs received by institutions and households risk management strategies (r = 0.087, p = 0.067). Benefits from the programs were found to have positive relationship with coping strategies (r = 0.298, p = 0.000), while no relationship was found with risk management strategies (r = 0.0.95, p = 0.055). The Pearson correlation coefficients test also indicated that there exists a negative relationship between poverty and households coping strategies (r = -0.125, p = 0.015) and between poverty and households risk management strategies (r = -0.272, p = 0.000). Those who are poor are unable to use the strategies efficiently.
There exists a positive relationship between age and coping strategies (r =
0.117, p = 0.021) and no relationship between age and risk management strategies
(r = 0.006, p = 0.458). Older household have better experience and skills to
deal with risks and shocks. However, older households are skillful and can only
significantly deal with stressors after the shocks occur.
The educational level also seem to have a positive relationship with risk management strategies (r = 0.151, p = 0.004) but no relationship was found to exist between educational level and coping strategies (r = -0.053, p = 0.177). In a similar manner, no relationship is found to exist between gender and coping strategies (r = -0.025, p = 0.336) and between gender and risk management strategies (r = 0.019, p = 0.371).
In summary, this study investigated the impact of stressors, households strategies and institutions support on the wellbeing (income) of households in rural communities in Kelantan and Terengganu states of Malaysia.
The results of this study confirmed the findings of Chan
(1995) where stressors such as floods were noted to ruin rural households
income, making them vulnerable to poverty in Malaysia. The present study confirmed
that floods, low economic level and illness have disastrous impacts on households
livelihoods. It is observed that farmers livelihood (productive and non-productive
assets) is drastically destroyed by floods and this caused a steady decline
in their monthly income. The lost of livestock and damages in mechanical tractors,
fertilizers and pesticides resulted in under production. Consequently, farmers
are unable to produce surpluses that can be marketed domestically. Moreover,
low economic level led to decrease peoples purchasing power. As a result,
farmers found difficulties in marketing their agricultural products locally.
Marketable surplus lead to higher income generation thereby makes farmers refraining
away from vulnerability (Omolehin et al., 2007).
It is evident that idiosyncratic shocks do not significantly affect the wellbeing
of households in rural communities of Kelantan and Terengganu. Only illness
was found to be disastrous to the welfare of these communities. These results
substantiate to Wie (2001) and Mia
et al. (2011) findings. The co-relation between number of times households
fall as ill or receive medical attention and their monthly income is significant
and negative. The healthy situation of households contributed to increase their
monthly income directly and indirectly. Directly impacted to increase households
working hours and mounts their productivity and production in both in-farm and
off-farm activities. Indirectly, resulted in reducing the cost bared for medical
purposes and also reduced the opportunity cost that is occurred as households
are being jobless during the period of being sick.
On the other hand, heavy rainfall and harvest failure were found to encourage households to increase their monthly income. Households adopted and implemented various strategies to cope with and manage against stressors. While some of the coping strategies were effective in reducing the impact of the threats experienced; risk management strategies were found not to be effective but rather, to be destructive to the wellbeing of households.
Households who experienced harvest failure succeeded in gaining from this experience. By collecting natural resources and selling them in the market, they increased their monthly incomes. Heavy rain was found to be a useful resource for the communities, as they use the water made available during droughts. However, these strategies were not effective to those households which experienced floods, economic recession and illness. The reason is could be that households who got sick were unable to do extra work to enhance the family welfare. Households are also, not able to collect and sell natural resources from the forest when the economic level is down, as many of them suffer from shortage of money, therefore making the purchasing power of the communities to decrease. In the case of floods, households were even not able to enter into the forest and collect these natural resources due to the climatic situation and also due to the damage which occurs while experiencing the flooding.
Doing multiple jobs (off-farms), investing in assets, getting insurance and
work in relief (off-farm) programs have no significant impact on farmers
income. This is due the fact that majority of farmers in these communities only
depend on farming activities and seldom involved in off-farm activities. Many
studies such as Babatunde (2008), Onduru
et al. (2007) and Owuor et al. (2007)
confirmed that farmers derive income from both in-farm and off-farm activities.
While selling non productive assets found to be beneficial for farmers, selling
productive assets is neither increasing nor decreasing farmers monthly
income. These findings are not similar to Hoddinott (2006)
results which indicated households who sold their productive assets dramatically
reduced their capabilities and are being vulnerable to chronic poverty. Also
Bokosi (2007) and Owuor et al.
(2007) stated that productive assets such as livestock significantly contribute
to the reduction of the probability of being chronically poor.
Therefore selling these assets might ruin households capacities. The reason that selling productive assets found not to have negative impact on farmers income (in the present study) is that, in these communities majority of the farmers do not have access to such type of assets. Therefore, the impact of selling these assets is marginal. Nevertheless, adopting such type of strategy could severely affect the welfare of household members who need to increase their working hours in order to generate more income to fulfil the needs of their families for better nutrition. Poor households who sell their productive assets (such as cattle, land) as an intervention to face adverse risks may solve an immediate problem but this would lead to severe poverty in future as the only sources of income has been diminished.
Engaging in less risky production activities, spend saving and out migration
looking for jobs are disparaging strategies adopted by these communities towards
reducing the effects of shocks. Households were responsible for the reduction
in their monthly incomes. Due to the lack of access to assets and entitlements
provided by various institutions, households are left with little options other
than to engage in less risky production activities which, in most cases, are
less profitable. Farmers loose the opportunity to venture into high return and
more profitable but also more risky activities.. Furthermore, poor households
are discouraged from taking high return on investment opportunities due to the
fear of the consequences of failure (Dercon, 2000).
Farmers with saving in banks or with cash kept at homes were periodically able
to help themselves when experiencing negative events and are therefore, less
vulnerable to income fluctuations. However, instead of using the savings in
adopting new technologies in their production, households spend these savings
to compensate for the decrease in their monthly income. Although such action
could solve an immediate problem, it severely ruin their welfare in the short
term, as the last resort is demolished. Getting loans from institutions was
found not to have any significant impact on the farmers revenues as majority
of farmers do not access these resources as they lack of properties and possessions
that can be used a mortgages. Other studies such as Jehangir
et al. (2002) and Owuor et al. (2007)
found that there exist a significant and positive relationship between agricultural
credit and farmers income.
Those farmers which could not find any means to cope with risks and shocks
but had to migrate (temporarily) to another area looking for jobs exacerbate
their vulnerability to poverty. These results are similar to Gandhi
et al. (2009) findings which demonstrated that in India, households
which chose migration as a favored strategy to mitigate drought, actually exposed
migrants to a higher risk of contracting HIV which deepened the households
vulnerability to poverty. By out migrating to another area, households prone
to another risk as they had to liquidate their very few assets and savings in
order to survive while looking for new jobs. Furthermore, since they have no
formal education or are less educated, members of poor households find difficulties
to access employment opportunities. Even when offered the chance to access employment;
their salaries are very low, usually below the income poverty line. This makes
them more vulnerable to income fluctuations. Fluctuations in income imply relatively
high levels of transient poverty. Rural households could run into transient
poverty when they are exposed to adverse shocks and may fall into chronic poverty
if exposed to adverse shocks and having limited long term income generating
In the communities studied, institutions do not play significant roles in strengthening households capacities. In spite of the fact that there exist a number of programs provided by these institutions, only few households have access to these facilities (Appendix, Table E). Except for financial aids which significantly increase households revenues, all other programs did not contribute in building up capacities of the rural communities. Households used the financial aids to invest in productive assets. Results of the study indicated that by investing these financial aids in productive assets, households increase their productions and this led to an increase in their monthly income. The provision of material and non-material assistance and supports which could enhance the productivity of rural communities such as access to new technologies and training on how to use these technologies; are vital and a priority. Adoption of new technologies is low as farmers lack adequate knowledge on how to use it.
Relying on their own resources and attending limited programs were most commonly
reported among the rural households. Therefore, households implemented coping
strategies rather than preparatory ones which could enhance farmers to manage
better against next unexpected threats. Poor and less educated households therefore
are unable to utilise facilities provided by the relevant institutions. This
is evidenced by the negative relationship between households coping strategies
and poverty. The study also confirmed the existence of positive relationship
between the level of education and risk management strategies. This could be
a reliable reason to explain why households risk management and coping
strategies are disparaging to their livelihoods. The poorer the households,
the more vulnerable they are. The more educated households, the less vulnerable
they are. Where as institutions in these communities did not lead rural households
to fall into poverty trap, their support also made no difference. Human capital
in terms of better health of the households was demonstrated to contribute as
the key factor for recovering from threats. The time taken to partial or complete
recovery from the threat was found to be a vital factor in speeding the recovery
process. In this case, external supports and assistance such as financial aids
at the proper time, plays an essential role in determining the effectiveness
and the efficiency of households strategies, thus leading to swift recovery
from the stressors.
Institutions are found to be active and to provide their services to the rural households in these communities but only after disasters occur. This is confirmed by the existence of a positive relationship between institutions supports and households coping strategies, while this relationship was found not to exist between the programs provided by institutions and households risk management strategies. It is very important to guarantee assistance and supports from governments institutions, NGOs, CBOs and international partners before, during and after unexpected events occur, in order to curtail the negative impacts which affect rural households, particularly the poor.
CONCLUSION AND IMPLICATIONS
The results of the present study highlights some important implications for policy makers, donors and professionals involved in poverty eradication in Malaysia. Based on the results of this study, interventions should be focused on two different levels: first at community level and secondly, at the household level. At the community level, there is the need to establish an effective supportive centres and agencies which can provide training, advice and guidance on agricultural matters, market information and flood awareness. Support services from centres and agencies must be made available all the time and not only after the households experience stressors.
Second, there is the need to develop a financial system in these communities which allows poor people to be able to access loans, financial resources and aids without paying high interest rates or any unaffordable charges. The analysis of this study confirmed that financial aids has a positive impact on households livelihoods as those who had access to it invest the financial resources to increase their production, thereby increasing their monthly incomes.
Thirdly, the results of the study has indicated that the most serious threats
which the rural households experience are covariate shocks such as floods and
low economic level, where households were unable to manage against and cope
with these stressors. Therefore, there is a need to develop an effective and
practical frameworks, policies and programs which could help to enhance the
capacities of rural communities, in order to reduce the negative outcomes of
floods and economic recession. These frameworks and policies should be planned
to be proactive before the threats occurs.
At the level of the households, government institutions, NGOs, CBOs and any other institution involved in poverty alleviation should facilitate the access of rural households to assets and entitlements, particularly the poor and most vulnerable people to threats. Although the results indicate that most of the programs provided by the institutions made no difference in enhancing households livelihoods, the study confirmed the existence of positive relationship between the programs provided by the institutions and households strategies. The higher the supports from institutions towards the households, the more their strategies are and therefore, the less vulnerable to threats they are.
The authors acknowledge that the present research work was aided with funds from USM Postgraduate Research Grant Scheme (USM-RU-PRGS) Account Number 1001/PSOCIAL/843069. The usual disclaimer applies. Any remaining errors or omissions rest solely with the researchers of this work. The main author acknowledges the financial supports of USM fellowship Scheme.
Appendix: Frequencies and percentage of stressors, households
strategies and institutions supports.
||Exposure to shocks and risks
||Recovery from shocks and risks
|| Programs received
1Households’ poverty is measured on the basis
of people who do not have the minimum level of income that is deemed necessary
to achieve the adequate standard of living in peninsular Malaysia. Household
is considered poor if its income is less than RM194 per capita per month.
2This study defines risk (shock) as uncertain events
which can damage the households’ wellbeing. The uncertain event could
be natural, health, social, economic and/or environmental. Furthermore, the
present study measured risks and shocks first according to its nature; ranging
from risks affecting individuals (i.e. idiosyncratic) to those affecting communities,
regions or nations (i.e. covariate). Secondly, risks were measured according
to the severity (i.e., whether the risk affecting households’ wellbeing
3The role of these institutions is to provide
a variety of support to disadvantaged individuals, households and groups such
as health, education, training, etc. and to provide resources which would strengthen
the capacities of those individuals, households and groups such as assets (human,
physical, natural, financial and social). For example, households were asked
to indicate from a given list, the programs which they attended, as well as
answer from a given list of questions how the programs benefited their households
if they attended it, or to state reasons why, if they did not attend.
4Households’ ability to cope is measured
as the social risk management which the households implements both before and
after the risks occurs. Households’ strategies were summarized in two
categories; strategies which households implement before negative events occur
or what is referred to as ex-ante or risk management strategies (risk reduction,
risk mitigation) and strategies which households mplement after the event had
occurred, or ex-post or coping strategies. For example households were asked
to indicate from a given list, the strategies they used and implemented in order
to compensate or resolve the decrease or loss of their income and assets. In
addition, households were also asked if they recovered from these losses in
income and assets caused by stressors they had experienced.