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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

Ephraim Ugwu, Christopher Ehinomen, Int. Eco. Res, 2019, V10 i1, 48 – 68 ISSN:2229-6158

IJER – JANUARY – FEBRUARY 2019 available online @ www.ijeronline.com

48

mailto:[email protected]

mailto:[email protected]

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.



49

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



50

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



51

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



52

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



53

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



54

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.



55

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



56

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




57

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




58

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.



59

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




60

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



61

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



62

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


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


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%.



63

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.



64

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.



65

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