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REMITTANCES EFFECT ON HOUSEHOLD WELFARE AND POVERTY
REDUCTION: A STUDY OF SOUTH WESTERN NIGERIA
Ephraim Ugwu (Corresponding author), Christopher Ehinomen (Ph.D)
Department of Economics and Development Studies
Federal University, Oye – Ekiti, Ekiti State, Nigeria
[email protected] ;[email protected]
ABSTRACT
While global attention focused on remittances effect on overall growth of the economy, its
effects on welfare and households poverty received little attention. This study examines the
effects of remittances on household welfare and poverty reduction in South Western Nigeria.
Employing a survey and Logistic regression techniques, the empirical results show that the
household’s relationship with the remitter increases the probability of households’ being non-
poor by 24.0%. A unit increase of the remitter’s employment status increases the probability of
the household being non-poor by 21.7%. The Federal Government should incorporate migration
and remittances into development policies.
KEYWORDS: Migration, Remittances, Households, Welfare, Poverty, Logistic regression,
South-Western Nigeria.
JEL CLASSIFICATION: C10, C21, D10, F22, F24, I32
ACKNOWLEDGMENT
This research is sponsored by the Tertiary Education Trust Fund (TETfund) Nigeria, Abuja,
under the grant (TETFUND/DESS/UNI/OYE/2016/RP/VOL.1.RE.YEAR 2016. TETFund
RESEARCH PROJECTS).
INTRODUCTION
The mobility of labour across the globe has been
one of the most contemporary issues in
economics. Accordingly, it is expected that the
host country’s economy benefits as influx of
labour force stimulates consumption and
investment activities and thus leads to increased
production. The labour exporting country may
equally benefit as migrant workers’ remittances
enhance households’ income level, improve
household living conditions, and enhance their
consumption level as well as poverty reduction
(Abdelhadil and Bashayreh, 2018, p.3). In the
literature of migration, there are direct and
indirect effects of remittances on a country’s
economy. The direct effect results when the
remittances are directed towards investment
expenditure, while indirect effect results when it
is directed towards education, increasing
income of the households, health care expenses
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and poverty reduction. (Abdelhadi1 and
Bashayreh, 2018, p.3).
One of the most important factors affecting
economic relations between developed and
emerging economies is international migration
(The United Nation, 2002). According to the
World Bank report (2007), migration is a way
out of poverty for rural households in
developing countries because it gives them
opportunities to have a source of income apart
from agriculture and it reduces pressure on
consumption. Remittance is the most important
outcome of migration. Remittances have been
argued to have great potential to generate a
positive impact on the welfare of households
and of course the recipients. This is due to the
fact that families receive the monies directly
without going through middle men or
intermediaries (Keiru, 2010, Fonta, Onyukwu
and Nwosu, 2011, p.3).
The migration and remittances fact book report
(2016) noted that a total of $144 billion United
State (US) dollars was received by developing
economies from a global total of $601 billion
US dollars that were sent back home by
migrants in the year 2016. The World Bank
(2011) report on
Nigeria noted that international remittances flow
in to the country in 2010 from official
channel were estimated to have reached a total
of $10 billion. This figure by the World Bank
ranked Nigeria among the top ten destination
countries for international remittances. Equally,
the International Monetary Fund (IMF) report
(2001) noted that international remittances are
becoming a common source of income for most
developing countries. Solimano (2003, p. 4)
noted that the developing countries benefiting
most from the international remittance flow are
countries in the Latin America and the
Caribbean with a total sum of $25 billion in
2002; also in the league of highest receiving
countries are countries in South Asia, $16
billion inflow and countries from Middle East
and North Africa received $4biilion, which
amounted to an annual growth rate of 5.2%.
Haas (2007,p.567) noted that international
remittances that flowed back to developing
countries rose from a total sum of $31.1 billion
in the 1990s to $76.8 billion in 2000 thus
reaching all time higher to $167 billion in 2005.
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It is noted that the international remittances into
Nigeria was estimated to have exceeded
amounts coming into the country through
Official Development Assistance (ODA) and
that of Foreign Direct Investment (FDI). The
evidence of much remittances flow could be
seen in the over expansion of both informal and
formal money transfer institutions in the country
(Fonta, et al., 2011, p.3). Also, Sander (2003)
noted that remittances have proved to be most
stable flow compared with ODA and private
capital flows. Globalization and other factors
such as greater connectivity and more open
policies have resulted in the international
mobility of production factors. This is
evidenced in the greater number of people
moving out from their countries of origin in
search of greener pastures overseas (Ahmed,
Sugiyarto and Jha, 2010,p. 8).When people who
are educated move out from their countries
especially those from emerging economies,
there is huge loss of human capital which results
to what is termed brain drain. Developing
countries
have witnessed outflow of skilled men and
women especially those in the medical and
engineering professions (Ahmed et al., 2010,
p.8).
The interaction between international
remittances and inequality especially on income
level has continued to dominate the focus of
consideration among scholars. There is also an
exploration of the linkages between
international migration, remittances and poverty
ignored for a long time in the literature of
economic development (Fonta, et al., 2011,
p.3).However, recent global financial crisis has
slowed down growth in the countries importing
labour from developing countries. Reducing
their hiring and leading to job projection for
local workers over imported labour (Raihan,
Khondker, Sugiyarto and Jha. 2009, p. 9). It is
equally important to note that recent upsurge in
mass movement of people especially from war
turn areas of the Middle East to central and
Western Europe have hampered movement of
economic migrants
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from Sub-Saharan African countries, thereby
increasing the rate of poverty among
households.
While attention has been focused on the effect
of international remittances on the overall
growth of the economy, little attention has been
paid on its impact on poverty reduction among
households; and also, the effect of local
remittances or domestic transfers taking place
mainly through informal channels have received
little attention in development research. It
therefore becomes necessary to evaluate the
effect of both international and national
remittances on households’ welfare and poverty
reduction in Nigeria. This study therefore seeks
to answer the following questions: What is the
effect of remittances on households’ welfare and
poverty reduction in Nigeria? How does
remittances affect household income and
expenditure patterns? This study, therefore,
evaluates the effect of remittances on
households’ welfare and poverty reduction in
Nigeria.
LITERATURE REVIEW
There are various theories explaining migration
with varying implications for remittances (Pfua
and Long, 2008, p.4). Remittances according to
Addison (2005) are financial flows into
households that do not require an exchange in
economic value. It also serves as important
source of both income and consumption
smoothing strategies for vulnerable poor and
non-poor households. Quartey (2006) noted that
the literature analysing the impact of remittance
flows indicates that it has been of benefit at
every segment of the economy which include
the households, local communities and the
national level. Buch and Kuchulenz. (2002)
stated that the worker remittances constituted an
increasingly important mechanism for the
transfer of funds from advanced economies to
emerging economies than that of FDI and other
sources of external funding and assistance. Pfua
and Long (2008,p. 4 ) in their study, explained
that Lucas and Stark (1985) developed many
potential explanations on why people send and
receive remittances. One basic factor noted as a
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motivation is selfless desire of the sender to help
alleviate the living conditions of the recipients.
Other factors explored include that the recipient
is helping the sender to take care of properties
or loan payment for expenditures incurred
through education or health and migration
expenditures (Pfua and Long, 2008,p.4).
On the impact of remittances on inequality,
World Bank (2006) report stated that research
must make a decision between considering
remittances as exogenous transfers or as a
substitute for home earnings. Adams (2007)
suggested that the counterfactual situation is no
remittances, and in the latter case, it is necessary
to impute earnings in the counterfactual
situation that the migrant remitter had stayed
and worked at home. Pfua and Long (2008, p.4)
argued that poverty and income equality,
remittances can be compared to the preferred
alternate scenario. Ahmed et al. (2010, p.8)
were of the view that migration can lead to
higher standards of living and improve
educational and health standards. On the other
hand, there is always a significant loss of human
capital as educated elites from developing
countries relocate to advanced economies.
Empirical literature
Abdelhadi1 and Bashayreh (2018, p.3)
investigate remittances effect on poverty
reduction in Jordan using a time series data from
1972 to 2015. Apllying cointegration and error
correction model approaches, the study results
shows that remittances for the country increases
households income percapita.
Tsaurai (2018, p.1) explores remittances effect
on households’ poverty in selected emerging
economies using Ordinary Least Square (OLS)
regression model. The findings result indicate
that remittances increase poverty levels in
emerging economies.
Anderson (2014) investigates the effect of
international remittances and migration on
household welfare in Ethiopia. Using both
subjective and objective approach, the study
show that remittances have a significant effect
on welfare. The equally indicate a positive
effect of remittances on consumer asset
accumulation in rural Ethiopia.
Markram and Mortassar(2014) investigates the
causal relationship between remittances and
poverty reduction for 14 emerging and
developing countries from 1980 to 2012. The
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study apply non –stationary dynamic panel data
method. Empirical evidence show a two ways
causality existing from poverty to remittances
and vice versa.
Olowa,Awoyemi,Shittu and Olowa(2013)
analyse the impact of national and international
remittances on poverty in Nigeria using Foster-
Greer- Thorbecke (FGT) (1984) poverty index.
Their finding show that remittances reduce the
level of depth and severity of poverty in rural
areas.
Anyanwu (2011) investigates the impact of
migrant remittances on income inequality in
panel study of some countries in Africa for
period from 1969 to 2006. The study also
0.013% increase in income inequality in Africa.
The study notes that remittances inflows to
North Africa largely reduced inequality but
inequality continued to increase in the Sub-
Saharan African countries.
Fonta, Onyukwu and Nwosu (2011, p.3)
evaluate the interaction between remittances,
inequality and poverty reduction in Nigeria
using poverty and Gini decomposable
techniques. The result shows that with
remittances, households’ level of poverty falls
from 0.35 to 0.30 in the South-South region and
from 0.67 declined to 0.60 in the North central;
and from 0.72 to 66 in the North-East as well as
from 0.71 to 0.66 in the North-West regions.
RESEARCH METHODOLOGY
The study area for this research includes the
South-west geopolitical zone in Nigeria, while
the target population is the households in the
area. The region comprises six states but three
states which include, Ekiti, Ondo and Osun
states are selected for the study. Of the three
states under study, Ekiti comprises sixteen local
government areas with a population of 2.38
million; Ondo state comprises eighteen local
government areas with a population of 3.44
million; and Osun State has an estimated
population of 3.42 million with thirty local
government areas. The study utilizes a survey
method using a structured and semi –structured
questionnaires as well as focused group
discussion. The focus of the survey are the
households characteristics which include,
gender, age, marital status, education, health,
remittances of the households. The survey
equally generated data on household income
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sources, agricultural and business activities, a
detailed expenditures on food and non-food
items, as well as ownership of tangible items.
The survey data also include household poverty
incidence and household shelter, and access to
basic amenities. The total sample population
used for this study was 1473 households.
To evaluate factors affecting household’s
poverty level and to explore whether
remittances (international and national),
influences a reduction of poverty among
households, we adopted a Logistic regression
model. The logistic regression equations for the
first and second models on remittances effect on
households’ poverty reduction are stated as
follows:
0 1 2 3 4Nonrelative Remitter Channel Remittanceusepoor ...............(1)
:where
poor = Poverty level (dependent variable) (1 = Poor, 0 = Nonpoor)
Nonrelative = if the household receive remittance from non-relative
Remitter = relationship with the remitter
Channel = the channel through which remittance is received
Remittanceuse = what do you use remittance for
= Stochastic variable
The second model on remittances effect on households’ poverty reduction
0 1 2 3 4 5 6Poor= Remittance+ Howlong+ Inthelast+ Fromwhere+ Age+ Employstatus+ ..(2)
:where
Remittance = In the past one year how many times did you receive remittance from relatives?
Howlong = How long have you been receiving remittance?
Inthelast = How many times have you received remittance from non-relatives over the past one
year?
Fromwhere = Is your remittance coming from within the country (local) or abroad?
Age = Age as at last birthday?
Employstatus = What is your principal economic and employment status?
= Stochastic variable
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RESULTS ANALYSIS
Data presentation
Demographic characteristics of the
respondents
The table ( see table 1 below ), shows that
among the 1473 respondents, 572 which
represents 38.8% are residing in Ekiti state,
468 respondents which represents 31.8% of
the total population under study are residing
in Ondo ,while 433 respondents
representing 29.4% of the population reside
in Osun state.The table1 equally reveals that
in our sample of 1473 members, 823 or
55.9% are the heads of their households
while 650 or 44.1% are not heads in their
respective homes.Further analysis of the
households from which the members of our
sample were drawn( see table 1 below ),
shows that 754 respondents or 51.2% of the
1473 members of the sample come from
households with 1-5 members, 714
representing 48.5% of the entire sample
come from households with 6-10 members
and 5 respondents that is 0.3% of the sample
come from households with 11 or more
people as shown in the table above.
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Table 1 : Demographic characteristics of the respondents
Respondent’s state of resident
Frequency Percent Valid Percent Cumulative Percent
Ekiti 572 38.8 38.8 38.8
Ondo 468 31.8 31.8 70.6
Osun 433 29.4 29.4 100.0
Total 1473 100.0 100.0
Are you a household head?
Yes 823 55.9 55.9 55.9
No 650 44.1 44.1 100.0
Total 1473 100.0 100.0
How many persons are in the household?
1-5 754 51.2 51.2 51.2
6-10 714 48.5 48.5 99.7
11- Above 5 .3 .3 100.0
Total 1473 100.0 100.0
Source: Authors Computation from Research Survey 2018
Migrant status of the respondents
An investigation into the number of the
respondents’ relatives who live outside the
State, local government areas (LGA), Town
or country (see table 2 below), indicates
that 454 representing 30.8% of the sampled
population have between 0 and 5 relatives
living outside the respondents’ State, LGA,
Town and country of residence. 394
respondents, which is 26.7% of the sampled
population have between 6 and 10 and 625
respondents, representing 42.4% of the
respondents have between 11 and 15
relatives living outside the respondents’ the
State, LGA, town or country of residence.
Also, an enquiry into the number of
occasions in which the respondents lived
outside their home communities in the last
12 months is presented (see table 2 below).
The result shows that 1286 respondents,
representing 87.3% of the total sampled
population affirmed
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that they had lived outside their home
communities between 1 and 5 times in the
last twelve months, 48 respondents,
representing 3.3% had lived outside between
6 and 10 times and 139 that is 9.4% had
lived outside their home communities
between 11 and 20 times in the last twelve
months. The result on information provided
by the respondents concerning the reasons
for which they lived outside their home
communities (see table 2 below) indicates
that 1036 respondents, representing 70.3%
of the population under study, reported that
they lived outside their host communities for
educational reasons, 99 respondents, which
represents 6.7% of the population lived
outside for job opportunities, 67 respondent,
that is 4.5% of the sampled population lived
outside their town for marital reasons, and
271 respondents, representing 18.4% of the
total population lived outside for trading.
Table 2: Migrant status of the respondents
How many of your relatives live outside the State/ LGA/Town/ country
0-5 454 30.8 30.8 30.8
6-10 394 26.7 26.7 57.6
11-15 625 42.4 42.4 100.0
Total 1473 100.0 100.0
In the last 12 months how many separate occasion have you travelled away
from your home community and stay away?
1-5 times 1286 87.3 87.3 87.3
6-10 times 48 3.3 3.3 90.6
11-20 times 139 9.4 9.4 100.0
Total 1473 100.0 100.0
If you have lived outside your community what are the reasons
Educational 1036 70.3 70.3 70.3
Job Opportunity 99 6.7 6.7 77.1
Marriage 67 4.5 4.5 81.6
Trading 271 18.4 18.4 100.0
Total 1473 100.0 100.0
Source: Authors Computation from Research Survey 2018
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Remittances status of the respondents
An investigation into the number of times
respondents receive remittance from
relatives in the past one year is presented
(see table 3 below). From the results, 136
respondents or 9.2% of the population have
received remittance every month from
relatives. 511 respondents, that is 34.7%
have received once, and 528 or 35.8% of the
respondents have received twice. Equally,
110 respondents or 7.5% of the population
under study have received thrice and 188
respondents, or 2.8% of the population have
received remittance four or more times from
relatives. The table(see table 3 below),
presents results on the respondents’
relationship with the remitter. The result
show that 136 respondents or 9.2% received
remittance from friends, 240 or 16.3%
received remittance from spouses, 72 or
4.9% received remittance from children,
37respondents or 2.5% of the population
received remittance from son in law or
daughter in law and 209 respondents,
representing 14.2% of the population
under study receive remittance from sibling
s. Table 3: Remittances status of the respondents
In the past one year how many times did you receive remittance from relatives?
Frequency Percent Valid Percent
Cumulative Percent
Every month 136 9.2 9.2 9.2
Once 511 34.7 34.7 43.9
Twice 528 35.8 35.8 79.8
Thrice 110 7.5 7.5 87.2
four or more times 188 12.8 12.8 100.0
Total 1473 100.0 100.0
What is your relationship with the remitter?
A friend 136 9.2 9.2 9.2
spouse (husband) 240 16.3 16.3 25.5
Child 72 4.9 4.9 30.4
son/daughter in law 37 2.5 2.5 32.9
niece/nephew 779 52.9 52.9 85.8
sibling 209 14.2 14.2 100.0
Total 1473 100.0 100.0
Source: Authors Computation from Research Survey 2018
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An enquiry into the channel through which
remittance is received (see table 4 below),
finds that 136 which is 9.2% had received
through relatives, 1131 or 76.8% of the
sample had received through formal means,
36 or 2.4% of the sample had received
through informal means and 170 that is
11.5% of the sample had received through
both formal and informal means as
presented in the table above. The above
table presents results on if the respondents
receive any remittance from non-relatives.
The table reports that 53 respondents or
3.6% can’t remember if they receive
remittance non-relatives 364 or 24.7%
received remittance from non-relatives while
1056 or 71.7% of the total sample did not
receive any remittance from non-relatives.
Further investigation (see Table 4 below),
revealed that in the past one year, 1106 that
is 75.1% received remittance every month
from non-relatives, 240 or 16.3% received
once, 61 or 4.1% received remittance twice
and 66 or 4.5% received remittance from
non-relatives thrice in the past one year as
shown in the table above. Table 4 below
further show the results on whether
respondent’s remittance comes from within
the country (local) or abroad. The table
reports that 118 respondents or 8.0% receive
remittance from within the states, 916 or
62.2% from within the country while 376 or
25.5% of the total sample receive remittance
from both within and outside the country.
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Table 4: Remittances status of the respondents
What is the channel through which remittance is received?
Frequency Percent Valid Percent Cumulative Percent
Through a relative 136 9.2 9.2 9.2
formal means (western union,
money grams, others)
1131 76.8 76.8 86.0
2.informal means (sent you a
motor vehicle, phone, watch,
jewelleries)
36 2.4 2.4 88.5
both formal and informal 170 11.5 11.5 100.0
Total 1473 100.0 100.0
Do you receive remittance from non-relative?
Can't remember 53 3.6 3.6 3.6
Yes 364 24.7 24.7 28.3
No 1056 71.7 71.7 100.0
Total 1473 100.0 100.0
How many times have you received remittance from non-relatives over the past one
year?
Every month 1106 75.1 75.1 75.1
Once 240 16.3 16.3 91.4
Twice 61 4.1 4.1 95.5
Thrice 66 4.5 4.5 100.0
Total 1473 100.0 100.0
Is your remittance coming from within the country (local) or abroad?
Wiithin the states 118 8.0 8.0 8.0
Within the country 916 62.2 62.2 70.2
Abroad 63 4.3 4.3 74.5
c.Both within and
abroad
376 25.5 25.5 100.0
Total 1473 100.0 100.0
Source: Authors Computation from Research Survey 2018
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The Logistic regression on remittances effect on poverty level of the households
The model summary and the predicted classification for the first model
The model summary result (see Table 5
below ), on the remittances effect on poverty
level of the households indicates a Pseudo
R2 from the Cox and Snell result of 0.217
and Nagelkerke result of 0.291. The result
shows that the explained variations in the
dependent variable of the model ranges from
21% to 29% respectively. The classification
results (see Table 5 below ), shows that the
cut value is .500, it indicates if the
probability of case is being classified into
“No ” is greater than .500 then that case is
classified into “No” otherwise the case is
classified into “Yes” category. The
implication of this is that it provides
important logistic regression information
which includes, the percentage accuracy in
classification, sensitivity, specificity,
the positive predictive value and
the negative predictive values.
Table 5: The Model summary and the predicted classification for the first model
Model Summary
Step -2 Log likelihood Cox & Snell R Square Nagelkerke R Square
1 1661.286a .217 .291
a. Estimation terminated at iteration number 5 because parameter estimates changed by less than .001.
The predicted classification
Observed Predicted
Do you think you could genuinely
say you are poor now?
Percentage
Correct
Yes No
Do you think you could genuinely say you
are poor now?
Yes 651 172 79.1
No 219 431 66.3
Overall Percentage 73.5
a. The cut value is .500 Source: Authors Computation from the SPSS Statistics
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The logistic regression results for the first model
From the logistic regression results (see
Table 6 below ), on the remittances effect on
poverty reduction among the households
under study, the question do you receive
remittance from non-relative indicates that a
unit increase in the remittances from non-
relative ,increases the probability of the
household being non-poor to 21.8% and it is
significant statistically. The dummy variable
remitter shows that the relationship with the
remitter increases the probability of
households’ being non-poor by 24.0%. A
unit increase in the relationship of the
remitter increases the probability of the
household non-poor to 24%. On the other
hand, a unit increases in the channel of the
remitter reduces the probability of the
household becoming poor by 5.5%. In the
case of the dummy variable remittance use,
a unit increase in the uses of remittances
decreases the probability of the household
being poor to -46.2%.
Table 6: The logistic regression results for the first model
Dependent variable: Poor B S.E. Wald df Sig. Exp(B)
Step
1a
Nonrelative(1) 21.868 5104.515 .000 1 .997 3.141E9
Remitter(1) 24.032 8617.672 .000 1 .998 2.736E10
Channel(2) 5.579 1.970 8.023 1 .005 264.753
Remittanceuse(1) -46.297 10016.004 .000 1 .996 .000
Constant 1.062 1.339 .629 1 .428 2.893
Variable(s) entered on step 1: Nonrelative, Remitter, Channel, Remittanceuse. Source: Authors Computation from the SPSS Statistics
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The logistic regression results for the
second model
The model summary result for second model
(see table 7 below), on the remittances effect
on poverty level of the households indicate a
Pseudo R2 from the Cox and Snell result of
0.521 and Nagelkerke result of 0.698. The
result shows that the explained variations in
the dependent variable of the model range
from 52% to 69% respectively.
Table 7: the Model Summary for the second model
Step -2 Log likelihood Cox & Snell R Square Nagelkerke R Square
1 937.162a .521 .698 Source: Authors Computation from the SPSS Statistics
From the logistic regression results the
variable remittance shows that a unit
increase on whether the household receives
remittances, decreases the probability of the
household being poor to -36.3% and it is
insignificant statistically. For the variable
“How long” a unit increase in the in the
period of receiving the remittances
decreases the probability of the household
being poor to -5%. In the case of how many
times the household receives remittances in
the last one year, a unit increase in number
of times remittances are received, the log
odds of the households being non- poor
increases by 8.3%. The variables “Age of the
household head” indicates that a unit
increase in the age as at the last birthday
decreases the probability of the household
becoming poor by -3%. On the other hand,
for the variable of employment status, a unit
increases in the employment status of the
remitter increases the probability of the
household becoming non-poor by 21.7%.
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The logistic regression results for the second model
Dependent variable :poor B S.E. Wald df Sig. Exp(B)
Step
1a
Remittance(1) -36.292 56832.535 .000 1 .999 .000
Howlong(1) -5.341 .986 29.335 1 .000 .005
Inthelast(1) 8.375 .950 77.728 1 .000 4337.109
Fromwhere(1) 1.420 .531 7.146 1 .008 4.136
Age(1) -3.000 .584 26.421 1 .000 .050
Employstatus(1) 21.787 8685.67
1
.000 1 .998 2898184941.624
Constant 38.287 40658.2
81
.000 1 .999 42457963267033
712.000 Variable(s) entered on step 1: Remittance, Howlong, Inthelast, Fromwhere, Age, employstatus
Source: Authors Computation from the SPSS Statistics
Discussion
One of the most important outcomes of
migration and the factor affecting economic
relations most, between developed and
emerging economies, is remittance. It is
regarded as one of the best ways out of
poverty for rural households in developing
countries. It is noted that among the
developing countries benefiting most from
the remittance flow are countries from the
Latin America and the Caribbean countries,
as well as countries in South Asia, Middle
East and North Africa. As one of the
common source of income for most
developing countries, international
remittances into Nigeria is estimated to have
exceeded amounts coming into the country
through ODA and FDI.
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The Logistic regression on remittances
effect on poverty level of the households
shows that the relationship with the remitter
increases the probability of households’
being non-poor by 24.0%; and a unit
increase in the channel of the remitter
reduces the probability of the household
becoming poor by 5.5%. The result equally
shows that a unit increase in the remittances
from non-relative, increases the probability
of the household being non-poor to 21.8%
and it is significant statistically. The
variables Age of the household head
indicates that a unit increase in the age as at
the last birthday decreases the probability of
the household becoming poor by -3%.On the
other hand, for the variable of employment
status, a unit increases in the employment
status of the remitter increases the
probability of the household becoming non-
poor by 21.7%.
Conclusion
The study adopted a survey and the
Logistic regression model as a technique.
The study finds that major remittances
variables affecting household’s poverty level
include, educational attainment of the
household, age of the household head,
relationship with the remitter and
remittances from non-relative. Other
variables include, sex of the households’
head and employment status of the remitter.
Since remittances are important for food
security, efforts should be made by the
Federal Government to incorporate
migration and remittances into development
policies, so that remittances can have a more
favourable effect on household’s nutrition.
Policy makers should put in place social
protection measures for households not
having access to national or international
remittances in order to cushion effect from
economic shocks.
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