REMITTANCES EFFECT ON HOUSEHOLD WELFARE AND POVERTY REDUCTION: A STUDY OF SOUTH WESTERN NIGERIA

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 ephraim.ugwu@fuoye.edu.ng;chris_ehinomen@yahoo.com 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 nonpoor 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 48

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: poor Nonrelative Remitter Channel Remittanceuse...(1) where : poor 0 1 2 3 4 = Poverty level (dependent variable) (1 = Poor, 0 = Nonpoor) Nonrelative = if the household receive remittance from non-relative Remitter Channel = relationship with the remitter = 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 Poor= Remittance+ Howlong+ Inthelast+ Fromwhere+ Age+ Employstatus+..(2) where : 0 1 2 3 4 5 6 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 Employstatus = Age as at last birthday? = 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 Are you a household head? Yes 823 55.9 55.9 55.9 No 650 44.1 44.1 100.0 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 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 Table 2: Migrant status of the respondents 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. 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 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 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 Source: Authors Computation from Research Survey 2018 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 s. Table 3: Remittances status of the respondents 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 In the past one year how many times did you receive remittance from relatives? Frequency Percent Valid 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 Cumulative Percent four or more times 188 12.8 12.8 100.0 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 Source: Authors Computation from Research Survey 2018 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, 1131 76.8 76.8 86.0 money grams, others) 2.informal means (sent you a 36 2.4 2.4 88.5 motor vehicle, phone, watch, jewelleries) both formal and informal 170 11.5 11.5 100.0 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 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 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 376 25.5 25.5 100.0 abroad Source: Authors Computation from Research Survey 2018 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 R 2 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 1661.286 a.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 Do you think you could genuinely say you are poor now? Yes No 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 nonrelative,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) 21.868 5104.515 3.141E9 Step Nonrelative(1).000 1.997 1 a Remitter(1) 24.032 8617.672.000 1.998 2.736E10 Channel(2) 5.579 1.970 8.023 1.005 264.753-46.297 10016.004.000 Remittanceuse(1).000 1.996 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 R 2 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 1 937.162 a.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%. 63

The logistic regression results for the second model Dependent variable :poor B S.E. Wald df Sig. Exp(B) -36.292 56832.535.000 Step Remittance(1).000 1.999 1 a 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 4.136-3.000.584.050 Age(1) 26.421 1.000 Employstatus(1) 21.787 8685.67 Constant 38.287 40658.2 1 81.000 1.998 2898184941.624.000 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 nonpoor 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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