Migration among Farmers in Delta State, Nigeria: Is it a Climate Change Adaptation Strategy?

Objective: The study has the purpose of evaluating the nexus between climate change and migration of farmers in Delta State, Nigeria. The inuence exerted by cognitive situations and climate – driven stress on farmers’ decisions to migrate and the socioeconomic attributes of migrating and non-migrating farm families are examined. The emphasis is the function of migration in accessing climate and agricultural extension services as well as the contribution made by migration to promote farmers’ climate change coping capacity. Methodology: Survey was articulated using farming households in three agricultural zones of Delta State, Nigeria. Perceptions of farmers about alterations in climate were examined with the use of mental map technique. Binary logistic regression model was applied to assess the function of socioeconomic attributes of farm families while descriptive statistics was employed in evaluating the adaptive capacities of the migrating farming households. Findings: Climate – driven livelihood variables form part of the main propellers of migration among farmers. Migration as well as the socioeconomic attributes are inuenced by perception of farmers about climate change. These appears signicant difference between migrating and non-migrating farm families with respect to utilization of information, technology and knowledge emanating from agricultural and climate extension services. The gains from remittances, knowledge and social networks from host communities or zones raises migrating farm families capacity to adapt to climate change. Theoretical Implications: This paper contributes to the progressively dynamic body of knowledge by pointing out migration as an alternative climate change adaptation strategy to promote agriculture food security in any part of the world. Originality/Value: Micro – evidence is offered by this study with respect to contribution made by migration to adaptive capacity of farmers and their ability to have access to agricultural and climate extension services. This will be useful in the analysis of climate – driven migration in other nations that are agricultural economies. Insight is also offered regarding policy needs for the scaling down of farmers’ vulnerability to climate change. is not all of failure of an individual farmer to adapt effectively to climate change”. It examines the perception of farmers on climate/weather changes and in accordance unveils various cognitive situations that induce farmer’s migration decision during rainy or dry season. Also, the socioeconomic situations of migrating and non-migrating farming households were assessed. The emphasis of this study is to assess the role played by migration in accessing climate and agricultural extension services. It went further to evaluate the contribution made by migration to enhancement of farmer’s coping capacity.

Introduction
Movement of people prompted by environmental threats is an age long phenomenon. Livingstone (2000) suggests that Hippocrates and Aristotle were of the belief that the attributes of natural environment are determinants of human habitability of a location, as well as the qualities of the humans that inhabit it.
Increase in the rate of rural-urban migration is a consequence of wide differences in income levels and standards of living in developing nations like Nigeria. Harris and Todaro (1970), Lucas (1997), and Stark (1984) have offered theoretical support for this hypothesis of internal migration. Internal migration is vertically and horizontally articulated by Fei and Ranis (1964) as a process that is desirable, through which surplus labour is taken from agricultural occupations and moved to offer cheap labour or manpower for modern industrial state. According to Kohli et al (2011), a nation is most likely to remain in middle income trap, should such a nation fail to create transition from labour -intensive to capitalintensive production.
Agriculture is highly dependent on climate factors as it is a climate -sensitive sector that harbours increased labour surplus and it has become one of the contributory factors of internal migration to sectors that are non-climate -sensitive. The model of economic development of Harris and Todaro (1970) articulates some propellers of rural-urban migration. The fundamental postulation is that migration is prompted by the differential income of rural and urban settlements that is expected as well as wage difference. Lucas (1997) supports this model, however, he went further to opine that comprehension of the pull factors which determine the urban side apart from wage differential continues to be poor. To buttress this, De Haas (2020) notes that occurrence of migration is signi cantly dependent on the skill and knowledge level of the migrants as well as the prevailing conditions in the particular economic sectors where they hope to secure employment at home and at the destination.
In concept, the new economics of labour migration (NELM) models are different from other models because they incorporate rural risk factor as a determinant of decisions to migrate (Jha et al., 2018). This approach implies that decision to migrate an affairs of families and households instead of that of the lone individual (Jha et al., 2018); Stark and Lucas, 1988;Stark and Bloom, 1985). The NELM model likewise considers migration as a strategy created by a family or household to maximize expected incomes and reduce risk of failure in consumption by engaging in diversi ed sources of income by crossing sectors or agricultural zones.
Migration of humans is not only necessitated by poverty and social deprivation, but it is as well prompted by climate change Ofuoku and Chukwuji, 2012). Unfriendly weather conditions, rise in sea level and environmental degradation constitute the important outcome climate change. The alterations are the main causes of long -or short -term migration as a result of loss of occupations that are sensitive to climate and poor capacity to adapt to the situation in South Asia (Bhatta and Aggarwa 2016;Kumar and Viswanathan, 2012) and in sub-Sahara Africa, including Nigeria (Ofuoku et al., 2011). As also suggested by Ahmed et al., (2016); Barnett and Webber (2009) suggest that households capacity to adapt to climate change depends on diverse factors, which include nancial base, social resources, infrastructure, human capital and access to information. To be resilient or be able to adapt, Gray and Mueller (2012) opine that farming households will probably cut down expenditures on goods that are non-essential, access formal and informal credit or depend on assistance from governments. On the alternative, or in combination with one or more of the earlier suggestions, farming household may decide to allow a member of the household to move to other locations to engage in alternative sources of income, which is remitted to the household or origin (McLeman and Smith, 2006;Ofuoku, 2017). When or where group -based mitigation activities and spatial coping methods are not on ground, migration becomes a very important climate change adaptation strategy for farming households against the shocks that accompany it (JTha et al., 2018). Shatta et al., (2015) explain that owing to uncertainty surrounding climate -sensitive livelihood activities, farming households embark on diversi cation of livelihood, which is an important strategy for several economic and environmental constrains. Banerjee et al., (2011) emphasize that remittances are the most glaring factor that enhance farming households' capacities to adapt to conditions of stress. Enhanced income from diversi cation of sources of livelihood creates room for farming household to increase their capacity to adapt in order to cope with the risk accompanying climate change (Patnaik and Das, 2017;Tripathi 2017;, Tacoli (2009), Larzko andAghazarm (2009) and Ofuoku (2019) states that in order to avoid the disastrous consequences of climate change adaptations has been made a very signi cant policy option and that one of the adaptation strategies of potent is migration. Since agriculture is the most climate -centered economic activity, it is faced with the highest risk and uncertainties that lead to loss of livelihood. At the national level, farmers rst identify or observe alteration in climatic parameters and take to migration as a coping strategy (Stojanov et al, 2016a(Stojanov et al, , 2016b. At the farm level, farmers constitute the major stakeholders and actors, thus their perceptions about climate change and their socioeconomic attributes, especially of their households, form the major factors propelling their migration. The socioeconomic situations are determinants of the level of vulnerability of farming households to climate -induced economic challenges and social deprivation in spite of the fact that their perception of climate change constitutes a prerequisite for the individual farmer's adaptation reaction (Jha et al, 2018). Farmers tend to choose to migrate to seek alternative means of livelihood in a situation of risk of crop failure or poor yield owing to the effect of erratic climate outcomes. Migration offers the farmers opportunities to gain knowledge on new technologies and techniques and farm practices to increase their agricultural income as well as enable them to generate de ned expected income. Apart from that, the remittances made from hose community or zone lowers credit related challenges adaptation strategies adaptation (Patnaik and Narayanan, 2015), thereby enhancing the adaptive and resilience capacities of the home zone.
Having articulated this theoretical background, it is worthwhile to carry out a study on the nexus between migration and climate change in a close context speci c way through integration of diverse socioeconomic, cultural, political and developmental variables. There is also the need to unveil the way farmers household qualities exert in uences on decision to migrate in order to create better informal zonal or regional policies (Upadhyay et al., 2015). This study develops a comprehension of the role played by migration as a strategy for adaptation for coping with climate alteration as well as attempt to change the course of the argument that "migration is not at all times the consequence of failure of an individual farmer to adapt effectively to climate change". It examines the perception of farmers on climate/weather changes and in accordance unveils various cognitive situations that induce farmer's migration decision during rainy or dry season. Also, the socioeconomic situations of migrating and nonmigrating farming households were assessed. The emphasis of this study is to assess the role played by migration in accessing climate and agricultural extension services. It went further to evaluate the contribution made by migration to enhancement of farmer's coping capacity.

Literature And Theory
Climate change according to Warner (2014) is a stress variable that has a major under -tone for migration in regions that are vulnerable to climate alterations. Klaiber (2014) suggests that migration offers farmers the opportunity to carry out non-margin shifts in arrangement of adapting to alteration in climate, while Warner (2010) states that the effects of climate variation on migration have for many years been a subject matter of great interest among policy makers and academics.
The fundamental postulation that inundates literature is that farmers migrate to other communities because they could not succeed to adapt to climate change in an effective manner (Warner, 2010).
Environmental factors, Porter et al., (2014) states has indirect effect on farmer's decision to migrate through its impact on livelihood activity, for instance agricultural productivity los and hiked expenditure as a result of rising prices of food. Lybbert and Sumner (2012) are of the view that sources of credit may not be enough for adaption of modern technologies needed for adaptation and change mitigation of climate change. In most sub-Sahara, (Ofuoku et al., 2012) and South Asian countries, the likelihood of migrating during adverse environmental situations is more among farming households that have poor socioeconomic background (Bhatta et al., 2015a;Bhattaet al. 2015b;Etzold et al., 2014). Decisions related to migration are rooted in the individual farmers' vulnerability in terms of economic, social, demographic and political factors (Yi Sun et al., 2017;Stojanovet al, 2016a;Stojanov et al., 2016b). Individual members of farm families are probably relocated in order to generate income for the sustenance of the family expenditures, achieve knowledge and enhance capabilities for surmounting shocks and stresses in the future (de Hann et al., 2002).

Rationale for migration
Migration is capable source of transfer of capital to aid traditional or local communities to progress towards elitist knowledge and education (Taylor, 1999). For example, in developing countries, agricultural extension is a crucial mechanism of knowledge, innovation or technology and education for farm families (Rivera and Sulaiman, 2009). Swanson (2006) describes agricultural extension services as the all-encompassing institutional arrangements that are meant to aid farmers organize themselves and create linkages between farmers and markets. Transfer of resources acquired to home location or zone, such as remittances, return of migrant and knowledge make immense contributions to enhance level of awareness of the work of institution and technical sources of agricultural extension services and climate information services (Jha et al., 2018). Income remitted home has direct effect on the resource base, economic welfare and resilience of the migrant source community (Adger, et al. 2002). Capabilities of the source community to achieve development and sustained livelihood is enhanced or propped up by individual migrants from the community. In most developing countries, high rate of migration has prompted substantial increase in income emanating from remittances. There is the need to give strength to the linkages between host and source communities in other to reactively strengthen home community resilience (Conway and Cohen, 1998), enhance its economic well -being (Adger et al, 2002) and offer access to needed resources required to enrich its human, cultural and social capital (Woodrugg and Zenteno, 2007). Social relationships in the host community have likewise been indicated as a crucial factor to employment and opportunities to shelter (Ofuoku, 2019).

Migration caused by climate change
Since in the prehistoric era there have been linkages between human migration and settlements as indicated by a wide range of literature (Jyson et al., 2002). While responding to loss of occupations that are climate sensitive and the ones that are not climate sensitive, citizens of communities decided and actually diversi ed their sources of livelihood through intensi cation of farming and non-farming activities (McDowell and Haan, 1997). More emphasis was put by Tschakert and Tutu (2010) on the value of migration while coping with climatic alterations. Bhatta and Agarwal (2016) observe that an enormous population of marginal and landless farmers in South Asia migrated in the bid to cope with climate change and variability. Climate change impacts on dynamics of human migration vary much of note in rural settlements because the people do not have adaptive capacity (Kates, 2000). The way individuals perceive climate change is a valuable precondition for their adaptation (Gbetibouo, 2009;Bryan et al 2009, Hassan andNhemachena, 2008).  (2004) opine that in the presence of the signi cant variations that exist between individual experience and external information sources, owing to climate variability, farmers are likely to place more value on current climatic occurrences. Indecisiveness may likewise be prompted by broader differences between farmers' expectations on climate variations and actual climate forecasts given by the agency incharge (Below et al, 2010;Roncoliet al., 2002). Alterations in agricultural systems do not entail straight line update of an individual farmer's decision making, thus the way farmers review their climate variation anticipation importantly becomes a determinant of his or her decision regarding adaptation (Bryan et al., 2009;Gbetibouo, 2009).
Aggregate migration ow stands for the consequence of the underlying individual decision -making process. Migration being a human behavior is, thus a complementary approach more than an alternative approach. Right thinking individuals tend to maximize their anticipated utility function, as a result, the decision whether to migrate or not is determined by the cost -bene t analysis. Hicks (1932) argued that maximizing behavior is born out of differences in net economic advantages. The gains of migration are the main causes of migration. Inspite of the catalogue of literature on climate change and variability, adaptation and migration, there are still gaps in unveiling the ongoing heterogeneous in uences in the home of origin that propel migration and the way migration go on to promote the ability of the migrating household member to gain knowledge on management of farm and bene ts of extension services. There are limited studies on climate -induced patterns of migration among various heterogeneous groups (Bhattaet al. 2015b), in Nigeria. It is thus a matter of necessity to comprehend how migration is the main source of resilience of household in climate change situation or scenario. Delta State is located in Southern Nigeria with the River Niger. Delta lies in the coordinate of longitude 5 0 50` and 6 0 45` east of the Greenwich meridian and latitudes 5 0 , 25` and 6 0 30`. The state is predominantly rural with about 80% of the population found in the rural areas. Internal migration is known to occur regularly, however, there is no o cial record of internal migration as such records are not in existence and no agency has been put in place to take care of that issue. Internal migration is highly implicated in the economy of the state and Nigeria at large. Deltans are one of the most mobile people after the Ibo tribe in Eastern Nigeria.

Sampling and Sample Size
Delta North Agricultural Zone is constituted by 9 local government areas. Delta Central Agricultural Zone is made up of 10 local government areas, while Delta South Agricultural Zone houses 6 local government areas. From each zone, 50% of the local governments were selected. Consequently in Delta North 5; Delta Central 5 and Delta South 3 local government areas were randomly selected. Three rural communities were randomly selected from each of the 13 local government areas selected. The heads of the villages were met for identi cation of the full-time farmers. This exercise led to identi cation of 7,226 farming households. Ten percent (10%) of the farmers were randomly selected and 723 respondents were arrived at. At the end the enumerators used to collect data from the farmers were able to return complete data from 698 farming households. The study involved every class of farmers in terms of farm size-small, medium and large.

Design of the Questionnaire
The issues relating to the questionnaire were discussed with the farming household heads (FHHs) to make sure that they are answered as accurate as possible and data were collected. The selected FHHs belonged to various land ownership strategies (that is, either farming on own land or rented land). The questionnaire captured local perception of the farmers as well as their observation about climate change and their experiences with variation in climate and extreme occurrences for the period of over the past two decades. Mental map technique (MMT) was also applied. In the MMT, the farmers were requested to give their local perceptions about alterations in climate based on their experiences and observations of alterations/variations in climate parameters. Ethnographic studies have the con rmation that persons are capable of identifying change in climate a decade or more on the basis of his or her own experience (Ofuoku and Albert, 2014;Marin, 2010). A previous study by Ofuoke et al (2012) saw through the lenses of the farmers and found that the farmers identi ed alterations in climate parameters such as rainfall and temperature for over a period of 30 years. The questionnaire also had questions on the FHHs socioeconomic situations, as well as the choices of information on climatic issues and new agricultural innovations (agricultural extension and climate). Their access to these information and the innovations were also captured. Their adaptation strategies choices among a list of diverse adaptation options for the rainy and dry seasons separately. The adaptation alternatives included capital -intensive, labourintensive and knowledge -intensive innovations for the facilitation of the assessment of contribution status of migration to adaptation measures adopted.

Analysis of Data
While assessing the role played by socioeconomic attributes of the FHHs, binary logistic regression model was applied. The study was rooted majorly on an assumption that decisions by farmers to migrate are strategies of the family hence, if the farmers does not embark on migration one or more members of the farm family is made to migrate to a location that is close or a distant urban settlement. In the study behavioural qualities of migrating and non-migrating farm families were utilized. No psychological factor apart from perceptions about climate -induced stress as a propeller or pushing force of migration of farmers. Descriptive statistics were useful in unveiling the variations in adaptation behavior, choice of climate extension and agricultural services and the pattern followed in adoption of various adaptation methods between migrating and non-migrating farming households.

Farmers' Perception about Climate and Migration
The shape of migration (temporary or permanent) is determined by the farmers' perception and experiences of climate extremities and variability. A farmer has more likelihood of migrating permanently as a consequence of continued loss of losses, livelihood and wealth when he or she faced high level of vulnerability to climate extremities and continual experience of alterations in patterns of climate. Then the farmers who experience the effects of seasonal variations in climate and temporary climate alterations will likely have the decisions to create temporary income generation to meet up with livelihood needs. The climate parameters put into consideration in this study included temperature and rainfall. The perceptions of the farmers about climate change were assessed on the basis of dichotomous responses (yes or no) to the question of whether they observed long term variations or alterations in average levels of temperature and rainfall since the past 20years or more. The farmers' decision to migrate was evaluated for the two existing farming seasons -early farming and late farming seasons owing to climatic conditions that are ideal for crop yield level and consequently, farm cost of production and management practices vary according to farming season. Rooted in the farmers' responses to questions perception of alteration in temperature and rainfall as well as their options to embark on migration because of sensitivity of crops, Jha et al (2018) four cognitive situations of farmers were put into consideration. These included: i. Perceived changes in climate and migrate; ii. Perceived changes in climate but do not migrate; iii. Do not perceive changes in climate and hence do not migrate; and iv. Do not perceive changes in climate, but choose to migrate. Going further, with respect to crops sensitivity to alterations in rainfall patterns, 63% and 37% chose to migrate and not migrate, respectively during the early farming season. During the late cropping season, about 70% chose to embark on migration, while 29% opted out of migration. During the two seasons, the number of farmers who opted to embark on migration as a consequence of perceived climatic alterations was much higher than the ones who chose to migrateinspiteof the fact that they did not perceive climate change and variability. However, a good percentage (20 -35%) of them perceived alterations in climate pattern, but refuse to migrate. These differences in option decision are attributable to qualities of the farming households farm families. These ndings are in consonance with those of Jha (2018).
Migration was seen as a pro table coping strategy by most of the farmers used for the survey. Perception of climate change and migration formed the dominating cognition situation for early cropping and late cropping seasons in Delta State. Did not perceived but migrated 6 7 7 9 Perceived but not migrated 31 31 28 25 Did not perceive and not migrated 4 6 4 3 NB: The gures are in percentages, but some may not round upt to 100 as a result of rounding off.
This situation is majorly rural risk factors have association with climate alterations and variations in their home community or zone. The decision to embark on migration is one of the farm household coping mechanisms and not the decision taken by an individual. Farmers who fell under the second cognitive situation (migrating when they did not perceive climate change), did so mostly because they purpose to embark on diversi cation and maximization on their sources of income. A few of the farmers opted not to migrate, though they perceived climate alterations (the third cognitive situation), majorly as a result of the risk of uncertainties in the host zone or community (for example, cost of migration, employment guarantee) and favoruable socioeconomic situations in the home community or zone (for instance, education household size, land size). They were risk averse because of these conditions. The number four cognitive situation indicates that farmers were not aware and were still not aware of any alterations in climatic situations and may be satis ed with their economic situations, hence do not consider migration as choice that is pro table or they may be lacking the knowledge and skill required to migrate.

Function of Socioeconomic Qualities in Migration as an adaptation measure
A good comprehension of the socioeconomic attributes of farmers is crucial to recognition the major factors encouraging migrations. The decision taken by farmers to migrate constitutes strategies of the farm households which are mainly articulated for the purpose of overcoming the income loss and social deprivation risks and ensuring smoothing of consumption. For assessment of the function of socioeconomic situations or background as an adaptation strategy, a dichotomous (binary) logistic regression model was utilized with the migration option of farmers (migration = 1 and non -migration = 0) being a single categorical predictor. Socioeconomic qualities of the farm families including age of household head (HH), formal education level of the farming HH; proportion of males in the farm households to sum of household size; proportions of other members of the household (proportion of females and children below the age of 10years); farm land size; land ownership status (own farm land = 1; rent = 0); and livestock ownership formed the independent variables. Table 2 indicates that age and educational status of HH head; proportion of male proportion of other members of the family, farm size and land ownership signi cantly drove decision to migrate during early and late farming seasons. The age of farming HH head positively contributed to choice of migration during both farming seasons. The age of the farming household head implies farming experience, which is a determinant of farmers' perception, adaptation decision and propensity to adapt. Older farmers have a high sense of felt need and responsibility to ensure that their families/households achieve sustained sources of livelihood, thus decide to migrate or advice other members of their households to migrate. The migration project is aimed at reducing dependence level and ensuring ow of remittances to the folks at home. Level of formal education positively in uenced migration of farming HH heads through which enhancement of their capacity to access and articulate information relating to conditions of climate and give response. Farmers who have reasonable level of education have higher level of awareness with regards to available opportunities in their host communities or zone. There is also the ripple effect of education which encourages other members of the household to also embark on movement from the home zone or community. A higher proportion of males in the farm families positively affected the decision and plan to migrate. This is attributed to the fact that more male members of the households gives assurance of more hand in easing of income and more e cient in taking advantage of social networks in their host communities or zones. The proportion of women and children below the age of 10years implies dependence; hence, a higher proportion positively in uences decisions to migrate in order to meet up with their income need for improved consumption desires. Land ownership pattern was signi cant, but the coe cient bore a negative sign, implying that farmers who rent farm land have more likelihood of migrating due to poor net income. The net income is what accrues to them after rent payment. This becomes insu cient while trying to meet up with consumption desires or needs, as well as other needed expenditures of the household in the home community. Farm size signi cantly, but negatively in uence migration in both farming seasons. Thaet al., (2018) found that farm size only in uenced decision to migrate in one of the farming seasons (Rubi) in India; that farm land is negatively signi cant implies that larger farm size requires greater family labour for farm operations; as a result, farming households may not have the intention to embark on migration or encourage any member to migrate.

Function of migration in agricultural extension services
The current context of climate change and its associated risks calls for frequent obtainance of new knowledge via adequate and time-precision extension services. Two institutional arrangements that enhance adaptation most include agricultural extension services and credit facilities (Jha et al., 2018). disseminates information using television, radio, mobile phone and internet. Agricultural extension sources include eld o cers, television, mobile phone and radio. Differences are indicated between the adoption behavior of migrated and non -migrated farmers during the two farming seasons studied (Figures 1 and 2). educational level. This is more so as mobile phone is one of the knowledge-based innovations. As a result of their level of formal education, migrating farmers have become more pro cient in the usage of these information resources for farm or agricultural management. Likewise, remittances received from host communities or zone create improvement in their economic well -being. This empowers them to procure and utilize mobile phones, computers, newspapers, televisions and radios in their home communities or zones. The information need of non -migrating farmers is capable of being met when migrating farmers share information, technology, knowledge and skills with them, thereby enhancing "social learning" and the capacity to adapt to climate change in the home communities or zones.

Migration as an adaptation strategy
The way migration promotes farmers' capacity to adapt and make possible adoption of other strategies is examined in this section. A total of 11 adaptation strategies, inclusive of migration were identi ed as  Their options of adaptation measures were considered to be propelled by climate parameters, though they were aimed to generate pro t as pointed out by the farming family heads (Jha et al., 2018;Nhemachena and Hassan, 2007;Maddison, 2006). While assessing the farmers' options of adaptation strategies, the level of adaptation was developed on the basis of the number of adaptation methods adopted by the farmers (Bhattaet. al. 2016;Jha et al, 2018). The number of adaptation indicated by the farm family heads ranged a minimum of 0 (no adaptation) to 11 (maximum number of adaptation methods used by any of the farmers) (Jha et al., 2018). The mean number of adaptation strategies adopted by the farmers during the early farming season for perceived alterations in climate parameterstemperature and rainfall was above 4 for both of the parameters. In the late farming season, the mean was about 5 for perceived alterations in temperature and precipitation. This is congruent with the ndings of Jha et al., (2018).
Adaptive capacity according to Brooks and Adger (2005) is system -controlled and can modify its qualities or behavior to widen its range of coping under extant climate alteration or later climate situations. In accordance, this study is of the assumption that farmers who have higher adaptation level (range of coping) possess higher adaptive capacity (Jha et al., 2018). The capacity to adapt likewise represent the capacity index of the individual farmer to control the impacts of climate change at the farm level which is dependent on the skill, formal education status and the ability of the farm family head (Tarleton and Rainsey, 2008). Table 3 shows that among the 698 farmers used for the survey study, 19% and 28% failed to adapt to alterations in temperature and precipitation during the early farming season respectively. In the late farming season, 11% and 19% did not carry adaptive effort to change in temperature and rainfall, respectively.
Most (63 -71% and 68 -71%) adopted migration as an adaptation strategy in early farming and late farming seasons, respectively. Slightly, more farm families opted to migrate during late farming season than in early farming season. This is because early farming season is highly labour intensive than late farming season and it involves a lot of farm operations, while late farming season is not labour intensive.
Since there is no adequate amount of operations for all the household members, some of them opted to migrate during late farming season. Out -migration from a state to another align very much with alterations in the yield of rice (a crop favoured in the rain season) (Viswanathan and Kumar, 2015). The variation between the result of this study and that of Viswanathan and Kumar (2015) is attributed to the fact that while the data used by them was based on state level migration, this study is based on microlevel assessment of migration as an adaptation method and majorly utilized behavioural qualities of farmers that wrought with uncertainty and unpredictability. However, the results of this study are in consonance with those of Jha et al. (2018) who also based their study on micro -level assessment of migrations. During the early farming season, for alterations in temperature, 26% had low level adaptation and for precipitation, 29% had low level adaptation. In the same period, 44% had medium level adaptation to temperature and 40% had medium level adaptation to alterations in precipitation, while 11% had high level adaptation to changes in temperature and 3% to changes in precipitation. Likewise, in late farming season, for alterations in temperature, 4% had low level adaptation and 26% had low level adaptation for alterations in precipitation. In this same season, 44% had medium level adaptation for alterations in temperature and another 44% for changes in rainfall, while 21% had high level adaptation to changes in temperature and 11% for changes in rainfall. Therefore, medium level adaptation was dominant in the study area. This implies that farmers adopted 4 -6 distinct adaptations measures every season in reaction to alterations in temperature and precipitation.
During the early farming season, 71% migrated because of changes in temperature, while 63% embarked on migration because of changes in rainfall. In late early farming season, 68% migrated due to alterations in temperature, as 71% migrated as a result of alteration in precipitation. To evaluate the signi cance of migration in promotion of farmers' capacity to adapt to alterations in climate, by farming season, the proportion of migrating farmers to total households adopting climate change adaptation strategies at each level of adaptation was examined. In early cropping season, about 79 -81% of farm families with high level of adaptation and about 92% of farmers that had medium level of adaptation were migrating farm families. Also, in late cropping season, 88 -93% who had high level adaptation, 81 -83% that had medium level adaptation were migrating farm families. These results are indicative of the fact that migrating farm families have a greater capacity to adapt to climate change since they have the ability and capability to adopt more adaptation strategies because of the support from host communities in the shape of remittances, social networks, knowledge and resources.

4.5
Adaptation strategies adopted by migrating farm families by season in the study area In order to evaluate the signi cance of migration in adoption of other adaptation methods, separate analysis were done for migrating household and non -migrating households with respect to changes perceived in temperature and precipitation for early farming and late farming seasons. For both early and late farming season, their adaptation responses for alteration in temperature and rainfall were of the same trend (Figures 3a,b,c,d). Migrating farm families chose more adaptation strategies than nonmigrating families. For temperature and precipitation in early farming season 94 -95% adopted irrigation; 43 -70% chose to adopt changing land under cultivation, 51 -58% adopted improved crop varieties that are bred to be resilient to prevailing climate in the scenario of climate change, 58 -66% of the migrant farm families adopted crop insurance to avert risk of loss of crops, 24 -28% chose to adopt water conservation, 14 -18% adopted soil conservation practices; 19 -24% decided to move onto nonfarm livelihood activities by way of diversi cation, 38 -44% planted vegetables and 15 -20% opted for horticultural production. Likewise, in late farming season, 98 -99% opted for irrigation, 91% chose to plant improved varieties of crops, about 71% change their farmland, 58 -59% opted for crop insurance, 44 -46% chose to practice soil conservation, 39 -40% decided to cultivate vegetables, 23 -25% practiced water conservation and about 19% diversi ed to non -farm livelihood activities among the migrating farm families for both temperature and precipitation. In comparison, both migrating families, the adoption score of non -migrating farm families that opted for these adaptation strategies was glaringly low. However, the common choice of adaptation strategies between migrating farmers and non -migrating farmers is planting of improved crop varieties, irrigation, crop insurance and soil conservation practices, water conservation and vegetable cultivation. The adaptation strategies are known to be intensive in nature in terms of resources, capital and knowledge. This makes the migrating households to a comparative advantage over non -migrating farm households. Migrating farm families had the bene t of remittances and knowledge acquired from host community or zone. Migrant farmers acquired knowledge of crops and soil and water conservation technology, the social network of the migrant in the host community.
Migrant farmers were quick to access and better informed about any new government agricultural development initiative, hence accessed the facilities in the schemes successfully. Remittances from migrants in host zones were utilized to buy farm inputs, especially seeds of improved varieties of crops. The remittances also helped them to procure and adopt modern or improved farm mechanization technologies. The study results imply that remittances social networks and knowledge acquired from host communities has direct positive in uence on the progression and improvement migrating farm families' economic situation. However, to limited extent, non -migrating farm families also tap from the migrating households to promote their ability to adapt the innovations for adaptation to climate change.
It is therefore, convenient to assert that the micro level, migration of farmers is capable of having bene cial outcomes for improvement of adaptation, sustainability of livelihood and resilience to climate change.

Conclusion
Climate -driven migration is considered as an adaptation strategy for the mitigation of adverse and extreme weather situations born out of alterations in climatic conditions. Farmers tend to often embark on migration to diversify their sources of income, as well as create smooth consumption. However, migration has a far broader function as a strategy for adaptation to climate change. This study assessed the effect farmers' perception of climate has on farm family migration. It also evaluated the contribution made by migration to promotion of farmers' capacity to adapt through scale up of their nancial capabilities and acquisition of knowledge relative to improved agricultural technologies. As well, the in uence wielded by migration in creation of access to climate and agricultural extension services was examined. In addition, variations in adaptation methods for early and late cropping seasons were explored to unveil the advanced cultivation practices that were better resilience to climate alteration. This study reveals that climate -driven livelihood risk is the main propeller of farm family migration during both farming seasons. Migration also offered economic incentives through employment opportunities and enhanced value placed crops in the home zone. The socioeconomic qualities of the farm family, such as household head's age, male proportion in the household and the ratio of dependency promotes sense of responsibility in favour of livelihood sources sustenance of the house, thus making positive contributions to migration of farmers. Formally educated farmers have a higher propensity to migrate as they are well abreast with opportunities and gains that are available outside their communities. However, land size negatively in uenced migration of farmers. Land ownership is as well a crucial consideration in migration. Large farm size and land ownership promotes farm income, which consequently helps to achieve smooth consumption and other necessities.
Comparatively, marginal and smallholder farmers and tenant farmers possess a higher sense of insecurity, this higher propensity to migrate. While comparing migrant and non -migrant farmers, migrant farm families better accept to utilize instruction -based, knowledge -based, and technology -based climate and agricultural extension services from sources such as agricultural extension, eld o cers, meteorological agency, newspapers, television and radio. Migrating farm families most times have a higher adaptation score. They are also of superior capability for adoption of adaptation strategies that are intensive in terms of knowledge, capital and resources because of remittances coming from migrating members of the household. Non -migrating farm families only receive encouraging resources and knowledge from outside the communities through spillover from migrating families. In all, migrating farming households have advantage over non -migrating farming households with respect to adaptive capacity. For further study, not revenues of migrating farm families and that of non -migrating farm families should be examined by way of comparison, to further comprehend migration as an adaptation strategy against climate alterations.
As for policy perspectives, emphasis should be placed on creating a relationship between reduction of risk, human capacity building and development in rural communities. Efforts should be made by government to livelihood options that are not climate -driven to enable farm families diversify. In order to reach non -migrating farm families, training and workshops should be organized for this set of farmers so that they can handle knowledge -intensive adaptation strategies. This will help them to develop adaptive capacity. The policy of empowerment through farmers' groups should be sustained as this will enhance formation of social networks that will enhance adaptive capacities on non -migrant and migrant farmers.


Japan-AfCFTA Integration through Economic Impacts of Alternative EPA Scenarios - Examination of the GTAP 10A MRIO Database and Industry -Examination

This paper analyzes the impact on an economic partnership agreement (EPA) between African countries and Japan through trade liberalization and reduction in non-tariff barriers. This study aims to investigate sectoral interconnections and participation in the EPA that would facilitate further possible opportunities for the Japan-African businesses. The methodology employed is the Computable General Equilibrium model integrated with the Global Trade Analysis Project version 10A Multi-Region Input-Output database. We first modified the GTAP’s structure form to develop a long-run closure under steady-state and thereafter examined the African Continental Free Trade Area-Japan Economic Partnership Agreement (AfJEPA) with several EPAs scenarios relying on the quantitative comparison of economic impacts of different technical measurements. As a result, the AfJEPA can provide new possible opportunities for Africa-Japan businesses, such as contributing to the existing African and Japanese mega-regional trade agreements. Specifically, the electronics, petroleum and coal, and chemical, rubber, and plastic industries in Africa would see the highest percent growth. Likewise, the Japanese industries would improve their productivity in the motor vehicles and transport equipment, chemical, rubber, and plastic, and textiles and apparel industries. To sum up, trade facilitation and knowledge transfer, which policymakers can improve concrete action and investment, would considerably stimulate African and Japanese real GDP. Thus, potential growth would rely on deep regulation policy through a degree of openness and initial level of trade barriers to each country. Citation: of Alternative of the

Introduction
The spread of Corona-19 highlights the need for international cooperation and collaboration to address global issues. There is a need to strengthen global governing bodies/mechanisms such as World Health Organization (WHO) and World Trade Organization (WTO) to function effectively. To address global issues and to maintain a coherent and peaceful society, movements such as that of the mega-regional trade agreements (MRTAs) and economic partnership agreements (EPAs) play a key process as platforms that create regional and global cooperation frameworks based on mutual trust and interest among nations with cooperative orientations. Japan and countries in Africa strive to contribute towards regional and global cooperation frameworks despite the anti-globalization and state-capitalism sentiments. Japan is not only shaping and leading the Comprehensive and Progressive Agreement for Trans-Pacific Partnership (CPTPP) but also is promoting the Regional Comprehensive Economic Partnership (RCEP). Likewise, Africa has also started increasing its free trade agreements (FTAs) and finally completed the African Continental Free Trade Area (AfCFTA) agreement. Indeed, Japan and Africa have been strengthening the links between their economies and the world economy in favor of perpetuating sustainable development and inclusive growth such as increasing each economy's welfare, and profit margin in the Global Value Chains (GVCs).
As many economies, Japanese and African industries face various problems and bottlenecks, but their participation in the EPA will facilitate further possible opportunities. Which would stimulate the development of international frameworks for promoting trade of goods and services, direct and indirect investment, and technological transfer. Also, Japan has been a bridge to strengthen the links between Africa and Asia-Pacific and acted as a front-runner in regional cooperation frameworks. Therefore, the purpose of this paper is to analyze the possible challenges and opportunities for Africa-Japan businesses. This paper examines the African Continental Free Trade Area-Japan Economic Partnership Agreement (AfJEPA) through trade liberalization and reduction in non-tariff barriers (NTBs) under the African and Japanese MRTAs. This study focuses on creative sectors and sectoral linkages, such as how much percentage of African production is necessary to meet the Japanese production and to produce African goods that are domestically consumed or exported to other countries. In conclusion, this paper makes some policy recommendations regarding the regional and sectoral integration which could boost the GDP, welfare, and other opportunities of Japan-African businesses.
Past literature reviews have focused on the impact of the CPTPP, RCEP, European Union-Japan Economic Partnership Agreement (EUJEPA), and AfCFTA (Biyik, 2020 As a result of the AfJEPA, NTBs reduction and trade facilitation improvement compared to tariff removals would have a substantial growth in macro variables, which thereby would contribute positive value to the existing African and Japanese MRTAs. Specifically, Japanese industries would improve their productivity in the motor vehicles and transport equipment, chemical, rubber, and plastic, and textiles and apparel industries. In addition, the African electronics, petroleum and coal, and chemical, rubber, and plastic industries would see the highest percent growth. In short, this paper suggests that (i) the EPA including Japan would provide sustainable and promising growth strategies in African macro variables, (ii) trade facilitation and knowledge transfer, which policymakers can improve concrete action and investment, would considerably stimulate African real GDP, and (iii) only tariff liberalization policy would comparatively have less impact across regional real income growth. Thus, potential growth would rely on deep regulation policy through a degree of openness and initial level of trade barriers to each country.
Overall, African output relying on Japanese products is 1.4%; similarly, Japanese dependence on African industrial goods is between 1.1% to 5.5% throughout East Asian countries. Therefore, the EPA would constitute a strategy for Japanese growth, which has been suffering from long-term economic stagnation, allowing Japan to integrate effects of growth outside of Asia. In addition to this, Africa would enhance its economic development strategy by learning from Japanese MRTAs' experiments and integration and would have access to the Japanese high-tech market and capital. This paper is organized as follows: after the introduction and literature review, the third section provides an explanation of the methodology and the data. The fourth section portrays the framework of the aggregation, tariff and NTBs, trade facilitation and technological spillover, and policy scenarios. The fifth section discusses the empirical results of the AfJEPA and AfJE-PA-E. The sixth section then concludes the paper.

Literature Review
This section reviewed recent literature about AfJEPA and considered interpreting the MRTAs, such as AfCFTA, RCEP, and CPTPP (see below, sub-section 4.1) as a base case/condition. Empirically, existing studies have already examined the regional Asia-Pacific integration and landlocked African FTA using the CGE model interacted with the GTAP database and multinational Input-Output database. Kawasaki (2015) and Kawasaki et al. (2019) focused on the analysis of EPAs in Asia-Pacific, such as the trans-pacific partnership (TPP) and RCEP. Other studies by Kawasaki (2017) and Ji et al. (2018) extensively examined the Asia-Pacific integration and alternative regional trade agreements (RTAs). As a result, they reported that NTBs reduction compared to tariff removals would have a strong impact on income gain, so that local market regulation would play a crucial process/role for economic growth from EPAs.
Likewise, Kuwayama (2019) examined CPTPP and alluded to the fact that building a rules-based trading system would help positively to shape the Asia-Pacific region in order to gain benefits from trade for all. Moreover, Biyik (2020), Grübler et al. , and African Development Bank (AfDB) (2020) demonstrated that the AfCFTA would have biggest benefit from reduction in NTBs and would provide many opportunity and potential gain through a degree of openness and initial level of trade barriers to each country. Urata (2016) advocated that mega-free trade agreements (MF-TAs) and the WTO could be complementary and that expanding MFTAs to a global level, will lead to the participation of new members and mergers with other MFTAs. Correspondingly, this paper also justifies that each EPA/FTA is complementary and would help to improve the agreements/relationships. In this sense, we generated our assumptions based on previous literature. Nevertheless, scholars have not comprehensively focused on the impact of the AfJEPA on contribution to MRTAs in terms of Japan and Africa. At the same time, few studies have considered the model of trade cost, the endogenous structure of capital, and exogenous trade balance. Consequently, the objective of this paper analyzed the AfJEPA and implemented the applied general equilibrium (AGE) model regarding the GTAP-MRIO database for the first time.
Methodology and Data Sources This paper used the CGE model and GTAP-MRIO Database through which we investigated a trade integration between Japan and Africa and provided a description of (tariff) trade policy impact on each economy's future. In general, the database allows scholars to broadly evaluate the effect of a reducing tariff shock in trade studies. Therefore, we employed the CGE model as the appropriate approach to examine the effect of AfJEPA on Japanese and African markets. This paper modified closure under alternative long-run closure rules, such as capital accumulation and (perfect) capital mobility2 following Walmslye (1998) and as seen in Appendix I.
As for the limited African countries' international trade integrated database3, the GTAP database is to provide the most available data for African countries. The GTAP-MRIO database, which was launched in 2020 (Carrico, et al., 2020) and accounts for 65 sectors in each of the 141 regions, relies on the linkage model by implementing the GTAP 10A with the 2014 base year. The GTAP-MRIO model extends the standard GTAP, such as introducing agent (end-user as firms, consumers, and investors), and provides time series of input-output tables, bilateral trade flows, transport costs, tax (income and factor) and tariff information, and all other data calculating based on Social Accounting Matrices and elasticity parameters (Aguiar et al., 2019;Carrico et al., 2020;Hertel, 1997). The GTAP Database has denominated in millions of base years (2014) US dollars.

Modeling Trade Taxes and Iceberg Method
In the GCE model, we implemented tax policies and illustrated a simulation of the trade liberalization and reduction in NTBs. This paper draws tax and iceberg-related equations, following Walmsley Strutt (2019) and Kawasaki (2015). As for the demand function, demand for import ( Q s,d ) relies on Armington CES in the GTAP model obtained from maximizing utility function 4 ( , =[Σ( ⋅ ) ] =1−1 ) and budget constrain ( =[Σ , . , ]) =1. Policymakers use the import and export taxes T (1+ , , representing the GTAP model) to estimate trade liberalization. Thus, import demand with trade taxes represents in Armington (1969): , is the prices of import c from s for use by region d, inclusive of import tax price.
Where: c is the community, s is the source country, and d is the destination country. Equation 1 is formalized in the GTAP-MRIO model: Equation (2) shows that when tariff, , , , ( , , ), start imposing or eliminating, import price change depends on the import of c from s (exporter) for use by agent (a) in region d (importer).
(or , in the GTAP-MRIO) is the commodity price of import in region d; (or in GTAP-MRIO) is the elasticity of substitution between goods from different countries s; , (or , , in GTAP-MRIO) is the demand for goods from the county s by country d; and (or , in GTAP-MRIO) is the demand for imported goods by d.
In the concept of import and export linkages, the free on board (FOB) price and the cost, insurance, and freight (CIF) prices link for export and import prices for each commodity.
In percent changes as a shown lowercase letter in the GTAP-MRIO model: , , = , , + , , Where: , . . is the basic price of import c from s for use by an agent an in d; , , is the FOB price of commodity c from source s to destination d; , , is the PCIF price of commodity c from source s to destination d; , , is the price of commodity c from source s; , , is the import tax rate applied on commodity c; and , , is the export tax rate applied c.
Tariff elimination leads to a reduction of the cost of input and subsequently has a positive impact on the flow of commercial products. Also, trade facilitation agreements and NTBs improving the quality of commercial goods maximize the FTAs' potential benefits. Accordingly, it is the most common approach to model the trade facilitation in trade liberalization and NTBs, we use the iceberg cost variable, , or , , which presents "value melt away". Therefore, the demand for import ( , , ) changes so that utility function becomes;  , is the prices of import c from s for use by region d, inclusive of import tax price.
Where: c is the community, s is the source country, and d is the destination country. (1) , is the prices of import c from s for use by region d, inclusive of iceberg cost.
In the GTAP model, In percent changes as a shown lowercase letter in the GTAP-MRIO model: Where: , , is the percent change in augmenting iceberg cost of commodity c from s to d; and , is the percent change of aggregate imports of commodity c in each region.
Hertel et al. and Walmsley and Strutt expressed that the iceberg cost variable ( , or , , ), which substitutes quantity demand by reducing the input price of an imported commodity through Armington CES, reduces the amount of imported goods because of the productivity effect from technological change. These two opposite directions have a positive impact on reducing the price and increasing demand due to the different multiplier elasticity on domestic and import goods. Nevertheless, note that , , shock5 directly creates productivity shock and thereby boosts real GDP growth considerably.

Policy Simulation Scenarios
Scholars extensively use the GTAP model to document economic integration and FTAs, applying reductions in trade costs, liberalization of agriculture and industry, and the cross-border flow of people, capital, and technology. In this section, we summarized the information on the implication of regional and sectoral aggregation and tariff liberalization and reduction in NTBs, as well as trade facilitation and technological spillover impact on FTAs.

Regional and Sectoral Aggregation
Firstly, Japan has a high FTAs coverage ratio of export and import, more than 80% (Table A4) As for regional and sectoral aggregation, we aggregated the data depending on Japanese and African FTAs and past literature contributions. Thus, this study used the 2014-year base as the last reference year and aggregated 12 regions and 18 sectors (Table 1), as shown in the GTAP concordance in Appendix II. Specifically, we first eliminetd tariff levels of the AfCFTA and the Japanese MRTAs to be a baseline condition and right after started examining the AfJEPA. Which would present potential gain from each agreement and would demonstrate the contribution of the new EPA to Japan and Africa.

CY SIMULATION SCENARIOS
ely use the GTAP model to document economic integration and FTAs, applying e costs, liberalization of agriculture and industry, and the cross-border flow of people, logy (Hertel, 2013;van Meijl & van Tongeren, 1999). In this section, we summarized the e implication of regional and sectoral aggregation and tariff liberalization and reduction s trade facilitation and technological spillover impact on FTAs.

nal and Sectoral Aggregation
a high FTAs coverage ratio of export and import, more than 80% (Table A4)

CY SIMULATION SCENARIOS
ely use the GTAP model to document economic integration and FTAs, applying e costs, liberalization of agriculture and industry, and the cross-border flow of people, logy (Hertel, 2013;van Meijl & van Tongeren, 1999). In this section, we summarized the implication of regional and sectoral aggregation and tariff liberalization and reduction s trade facilitation and technological spillover impact on FTAs.
nal and Sectoral Aggregation a high FTAs coverage ratio of export and import, more than 80% (Table A4)  On one hand, each country regarding FTA has a different economic structure following the percentage of expenditure in GDP and population in the world. For example, the export percent in ASEAN countries' GDP is comparatively much higher than the export percent in East Asian countries' GDP. Moreover, while EUJEPA, RCEP, and CPTPP have positive trade balance, AfJE-PA's export is lower than its import (Table A3). Furthermore, RCEP, AfCFTA, EUJEPA, and CPTPP account for 30.3%, 17%, 7.9%, and 6.8% world population, respectively (Table A3). Therefore, enhancing each economic integration, such as AfJE-PA, would provide a possible opportunity for the world population.

Tariff and Nontariff Barriers
Regarding GTAP data version 10A, the reference year 2014, tariff data shows import tax imposed in RCEP countries have higher tariff levels than CPTPP members due to the heavily protected processed food industries (Table A5). Likewise, the African import tariff level is higher than the Japanese. In addition to inter-sector tariff heterogeneity, Africa protects its manufacturing industries in which average tariffs are close to 8%. Conversely, Japanese tariffs on the manufacturing industries are around 0 while Japanese tariffs on agriculture, processed food, and textile industries are comparatively higher than other industries in Japan (Table 2). Regarding sectoral self-sufficiency which presents a domestic share in total use, the Japanese market heavily depends on the import of energy resources and agriculture goods while electronic and automobile industries are highly self-efficient to export. As for the African economy, it is a rich energy resource landlocked but needs to meet mainly foreign manufacturers to produce its own goods. Thus, Japanese industries import energy resources from Africa whose industries import more motor vehicles and transport equipment from Japan (Table 2). Moreover, trade services function to set up businesses, such as banks, to strengthen the connection between countries which leads to a smooth flow of commercial products. On the other hand, trade-in service is difficult to capture an impact by tariff but is instead affected by behind-the-border regulations and technical measurements such as Technical Barrier to Trade (TBT) and Sanitary and Phytosanitary (SPS) standard, as known NTBs simulating growing concern healthy and quantity and environmental attributes (Herghelegiu, 2018). Accordingly, many studies documented that reduction in NTBs is more beneficial to stimulate trade than the only tariff policy (Kee, et al., 2009;Webb et al., 2020).
Implementing NTBs in GTAP, this paper first translated NTBs to ad valorem equivalents (AVE) to be incorporated into the tariff and export taxes by applying the Altertax procedure (Malcolm, 1998), which modified the original database to minimize disturbances. In other words, this paper designed the model to minimize the changes to the rest of the database while the required change in tax rates is large (Walmsley & Strutt, 2019). The NTB changes were assumed to imply to most-favored-nation (MFN) countries. Moreover, it was assumed that removing tariffs in the NTBs would have 50% with spillover effect (SE) to third countries at 50 %. In other words, GDP gain from NTBs reduction relies on assuming a 50% of NTBs reduction with a 50% spillover effect. If the AVEs of NTBs in the RCEP member of Japan is 10%, we have assumed Japan will reduce the AVEs of NTBs by 5% (50% of NTBs) for the imports from RCEP member countries and by 2.5% (50% spillover effects of 50% NTBs reductions) from non-RCEP member countries. This is due to the reduction of the cost of compliance with foreign standards and regulations. This assumption was based on previous studies on AfCFTA, RCEP, and CPTPP ( In addition, joining the GVCs through FTA, which accounts for strong firm-to-firm relationships and specialization (specializing in specific parts and components) for the long term (WB, 2020b), can boost growth, create more jobs, and importantly reduce poverty. For example, empirical studies documented that international trade stimulated the cross-border flow of technology because knowledge is embodied in goods, so that a country importing commodities and receiving FDI is directly influenced by technology depending on its absorption capacity and its structural similarity. WB (2020b) also reported that multinational firms relocating their productions such as designing, producing, and assembling parts and components due to the most cost-effective location would have to exchange knowledge when their products meet the border restrictions, such as import-related law and regulations. Accordingly, such an emerging imitation or innovation in a country allows firms to reduce their input cost that may trigger an increase in their output under the multi-region and general equilibrium setting. This represents technical change gaining a competitive edge over exporters on the world market. Thus, this paper assumed that the cross-border flow of the knowledge would have the benefit of reducing an average of between 0.1% and 0.5% of input cost in trade commodities (Table 3). Basically, we assumed that the degree of knowledge regarding the percentage of export and import in total bilateral trade (Table A4) were to transfer: (i) from Japan to Africa and from Africa to Japan (whole sectors) (ii) only from Japan to Africa (electronic sector in particular). Note that the technological spillover effect (TSE) relies on strong assumptions through a technical change in the GTAP model. We implemented a simple assumption is to fit the closure. Further, we also address this limitation in sub-section 5.2, below.

Scenarios
In the policy experiment, this paper used the full version of model structure and parameter values regarding the aggregated data to represent economic reality in trade liberalization function as accurately as possible. This paper also examined selected FTAs/ EPAs by estimating the quantification of the NTBs (Table 3). In literature, common sense is that policymakers should consider underpinning trade facilitation, NTBs, and connectivity measurements that demonstrate a potential fruit of FTAs. To evaluate the quantitative impacts of selected FTAs, this paper implemented series of trade-related shocks: (1) up to full tariff elimination; (2) 50% of reduction in NTBs with 50% of a spillover effect to third countries; (3) up to 2.1% (roughly 7% for AfCFTA) of reduction of time in customs due to the TFA and up to 0.5% of the cross-border flow of technological spillover effect (Table 3).

Results of the Analysis
This section presents the result of this paper's questions. We first modified the GTAP's structure form to develop a long-run closure (long-term macroenvironment) under steady-state, as shown in Appendix I. The long-term macroenvironment, through which capital can be mobile across regions, causes capital shock depending on a rate of return across regions and across time. We comparatively examined the two different approaches, EX-PAND7 and RORC8, impact on real GDP growth and welfare9, which will be discussed results in subsection 5.2, below. The difference is that in the case of 'expand' closure, 'rorc' remains endogenous, but is equalized across regions, while a change in investment relative to endowment stock is fixed/exogenous. When 'rorc' became closure works, such as everything is captured by the expansion/change in quantities. Moreover, 'rorc' has a positive correlation with a rental price of capital through substitution between capital and labor. Two different compensatory effects cause the price of capital goods to change: The first effect is a decrease in the price of capital goods due to the reduction in tariffs on imported inputs into capital goods and the second effect is conversely an increase of the price of capital goods because of increased demand for inputs (Walmsley, 1998).
As for portraying the result, this paper, firstly, eliminated tariffs for the AfCFTA and the Japanese MRTAs which created the base data set so that this paper would present the contribution of AfJEPA to Japan and Africa. Secondly, this paper displayed the AfJEPA, through which this paper revealed the trade facilitation improvement (TFI), NTBs, and TSE. Lastly, the knowledge transfer occurs in mainly electronics-related technology which was implemented and indicated the final scenario (AfJEPA-E) impact on each industrial value-added (Table 3). This section was divided into two subsections, sub-suction 5.1 and 5.2 below, and implemented long-run closure for the scenarios. We did not focus on presenting results with baselines simulation because the AfJEPA is a possible EPA. In other words, we did not consider updated data to run baseline scenarios due to minimizing unnecessary distortion. Nevertheless, we considered the contribution of economic impacts of several EPA scenarios relying on the quantitative comparison of economic impacts of different tech-nical measurements, such as rorc and expand. Therefore, this paper's result came out differently than previous studies. Also, we preferred to demonstrate the equivalent variation (EV) and the real GDP impacts which look more familiar to policymakers.

African Continental Free Trade Area-Japan Economic Partnership Agreement
This paper analyzed the AfJEPA because of a sectoral integration, as presented in Appendix III. A sectoral integration between Japan and Africa, the AfCFTA would contribute by 0.004 percent of Japanese GDP, and the Japanese MRTAs would stimulate African GDP to increase between 0.001% to 0.015% throughout East Asian countries (Table A6). To enhance this integration, this paper suggested the EPA between Japan and Africa, called AfJEPA. In other words, not only would the AfJEPA constitute a strategy for growth for Japan suffering from long-term economic stagnation and allow Japan to integrate the effect of growth outside of Asia, but also Africa would enhance its economic development strategy by learning from Japanese MRTAs' experiment and would have accessed the Japanese high-tech market and capital.
Primarily, reducing tariff level leads comparatively to cheaper input, which constitutes competitiveness of local goods. Therefore, the AfJEPA would subsidize the African and Japanese markets and benefits to member countries, lowering the price of import and benefits customers of final (household) and intermediate (firms) goods. Therefore, trade liberalization and reduction in NTBs would deliver more promising gains for member countries. However, while there are countries with a higher level of MFN border protection and trade-to-GDP ratio that would gain more, imposing a low level of prevailing MFN tariff rates countries would have modest benefit through the EPA (Table 4 and  Table A6) In general, we analyzed the AfJEPA by implementing the two different approaches of 'rorc' and 'expand' closure. Technically, 'rorc' closure has a strong impact on real GDP than 'expand' closure; in contrast, the impact of 'rorc' closure on welfare gain compared to 'expand' closure has significantly less effect ( Table  4). This is because 'expand' closure leads (regional) saving to be invested in the home country and thereby is likely to improve (national) household income. In other words, 'rorc' closure with endogenous 'expand' allows the capital shock to spread out across regions and thereafter has a positive impact on other nations' welfare and GDP due to the positive effect of the flow of commercial goods. For instance, the EU with 'rorc' closure which is not the trade deal would have a positive impact on its welfare from the AfJEPA due to EUJEPA and regional integra-tion with Africa (Table 4). In short, while the 'rorc' swap leads to comparatively higher impacts on GDP growth due to the large increase in capital shock, 'expand' swap has a strong effect on raise welfare due to the regional saving and investment correlation. Therefore, to capture the efficient impact of the AfJEPA on macro variables, this paper preferred to present the result of the macro variables by using 'rorc' swap, but only welfare by implementing 'expand' swap because each variable should take into account different approaches regarding their own different condition. As a result of empirical analysis, AfJEPA would boost Japanese GDP by 0.175% in tariff elimination (TE) and 0.319% in NTBs, and African GDP by 0.834% in TE and 1.147% in NTBs (Table  4). This agreement with capital mobility would also stimulate other regions' GDP. For example, the EU could have a positive impact and could increase its GDP by 0.027% in TE and 0.046% in NTBs with capital shock; however, the AfJEPA would harm non-members' GDP in TE in terms of implementing standard closure, without capital shock (Table 4). This paper also investigated each instrument variable's impact, such as a calibrated change by only tariff effect, tariff and trade facilitation agreement (TFA), and tariff and technological spillover effect (TSE), respectively. Accordingly, we can track the most stimulant variable regarding GDP and welfare. It is also obvious that Japanese and African economic structures are dif-ferent from their firms' input cost of land and labor. For example, while the TSE has a comparatively higher impact on Japanese real GDP than trade facilitation improvement (TFI), Africa gaining benefit from TFI would have remarkably a crucial effect of welfare than TSE (Table 5).  To recapitulate the finding of the different instrument experiments, TFI and TSE have a larger impact on GDP than only tariff elimination. This is due to the fact that technological change directly increases the amount of production, but tariff elimination relatively affects saving and allocative effect, and mainly the term of trade effect in Japan and capital effect in Africa ( Figure  1). Empirically, while the African market is quite sensitive to the TFI impact, boosting GDP by 0.733% in TE and 0.939% in NTB, the Japanese economy influences larger effect from TSE, enhancing GDP by 0.158% in TE and 0.286 in NTBs (Table 5), as well as the same impact accrued on their welfare growth (Figure 1). Africa would get a higher total welfare change due to the contribution of capital and allocation effect is positive, but negative in Japan which would cause by factor movement into the distorted each sector. Furthermore, another effect of the AfJEPA would have a negative value in African saving in which the TSE variable would lead to shrinking comparatively more ( Figure 1).
Source: GTAP 10A MRIO Data Base, author's estimation In this subsection, we demonstrated each agreement's contribution to African value-added and Japan's output percent change.
Value-added would increase higher because capital, allocative, and technological improvements positively impact on factors (Figure1) that move out of the subsidized sectors ( Figure 2). The AfJEPA would indeed contribute to AfCFTA and thereby have a positive impact on African value-added, the highest growth in the fossil fuel industry particularly ( Figure 2). Likewise, adding a new EPA to Japanese MRTAs would comparatively have a small impact on Japanese output due to the regional and sectoral integration through export/import percent (Table A4) and therefore could contribute a positive impact on the output of agriculture, processed foods, wood and paper, manufacturing, and service industries mainly (Figure 3).
To summarize the key points here, we documented that GDP is not a useful instrument to present national welfare10 (Table 4).
We also reported that tariffs and TFA have a substantial impact on the Japanese and African economies. However, firms' cost of input relying on TSE analysis would be biased to distribute the possible impact on selected countries because this change should consider a specific technical change in the GTAP model, such as Meijl et al., (1999) did. Therefore, we modified the final scenario of AfJEPA-E to be a proper/simple approach and investigates it in subsection 5.2, below.
Technological Spillover Effect in Electronic Sector, AfJEPA-E This subsection provided information on the final scenario that accounts for the different technological spillover effects from Japan to Africa (Table 3). An empirical study documented that most of the knowledge accrues in mainly consumer electronics industries, such as television, computer, and phone. Also, analytically portrayed the "biased technical change in the agricultural sector" due to the limited experiment capacity of biological and mechanical technology. Moreover, Japan has relatively a higher land and labor share in its costs and, therefore, would receive a larger gain than Africa through TSE (Table 5 and Figure 1). In that sense, we assumed there would be a 0.5% technological spillover effect on only African electronic sectors from the advanced/innovative country, Japan (Table 3). Since we investigated different impacts of each instrument (Tariff and TFA) on real GDP and welfare in the subsection of 5.1, above, we focused on presenting the AfJEPA-E effect on African and Japanese macroeconomic variables in this subsection. Table 6 shows the real GDP growth and welfare change for only Japan and African countries. The AfJEPA would provide many opportunities for Japan-African business, as well as non-members countries (Table 5; 6). African countries would enjoy through not only AfCFTA but also AfJEPA-E (Table 6; Table A7). Specifically, Southern Africa would have a relatively higher real income growth rate and welfare gain (by 1.49% and 6,496 US$ millions, respectively) than other regions. As for each country11, Namibia, Botswana, and Burkina Faso could be the top three highest real GDP growth rate countries, increasing12 by 10.14%, 4.94%, and 4.04%, respectively. Besides, East and North Africa would importantly improve their welfare gain. Similarly, the Japanese economy gaining benefits from AfJFTA-E would improve its real income by 0.03%. More importantly, in-cluding Japan in the EPA compared to AfCFTA would remarkably hike up real GDP in Egypt and Tunisia, increasing from 0.07% to 0.30% and from 0.17% to 0.43%, respectively (Table   A7). In addition to this, TSE-related electronics would have a relatively strong impact on Tunisia and the Rest of South Africa (Table A7). has a productivity impact through reducing the cost of (importer) rent which leads to directly boost value-added growth. The larger you use TFA/TSE the larger productivity is to boost directly sectoral output and value-added. Also, the African tariff rate is higher than the Japanese tariff level ( Table 2). As a result, African industries would have a positive impact from the tariff, tariff plus TFA, tariff plus TSE, and thereupon could considerably improve their value-added. In detail, the electronics, petroleum and coal and chemical, rubber, and plastic industries in Africa would be the highest percent growth while only the African construction industry would have a negative value, shrinking by 3.17% (Table 7). Besides, the Japanese industries would improve their productivity in the motor vehicles and transport equipment, chemical, rubber, and plastic, and textiles and apparel industries; however, the fossil fuel and construction industries in Japan would negatively have an influence on value-added (Table 7). Table 8 shows the result of industrial production and consumption change through AfJEPA-E. That is, we investigated the trade dependence of industrial production and consumption change because of a trade-related policy strategy for policymakers. As a result of the EPA, the Japanese and African industrial export share in total production would increase due to the decreased trade-related input cost and increased trade flow of commercial goods. Specifically, whereas the Japanese mining, fossil fuel, and financial service industries' export percent in total output could shrink, the automobile, construction, and textile and apparel industries in Japan would take leads, increasing by 0.9% 0.5%, and 0.4%, respectively (Table 8). However, Japanese import share in its industrial consumption has a different structure.
The consequences of increased export would forward the energy-intensive manufacturing and automobile industries in Japan to demand more for import products due to the limited Japanese energy resource; however, the Japanese construction, manufacture, and electronics industries would comparatively decrease to consume import-related production ( Table 8). The African manufacturing industries' export share in total production would marginally rise, such as automobile and electronic sectors could shoot up by 14.8% and 13.3%, respectively, whereas services-based sectors would decrease their export percent in total production. The consequences of increased export would trigger the fossil fuel, processed food, and textile and apparel industries to demand more import-related goods, increasing by 12, 23%, 2.07%, and 1.22%, respectively (Table 8).
In contrast, the construction and electronics industries in Africa would reduce consumption of the import goods. In short, the result is to also show a promising signal that Africa would improve the production of the manufacturing-related sectors in total export such as an Asian development relied on export oriented and impoprt substitution growth strategy, increasing export-related manufacturing goods; however, the African service sector has a negative impact from the EPA so that policymakers should consider more TFI and regional regulation policy (Table 8), such as infrastructure investments.

Conclusion Remarks
This paper analyzed the impact of an EPA between Africa and Japan through trade liberalization and reduction in NTBs. This study aimed to investigate sectoral interconnection participation in the EPA. Therefore, this paper made some policy recommendations regarding the regional and sectoral integration which could efficiently boost the GDP, welfare, and other opportunities of Japan-Africa businesses. We used the CGE model integrated with the GTAP-MRIO version 10A database. We first modified default closure to build the long-run closure and thereafter examined the AfJEPA with several possible EPA scenarios relying on the quantitative comparison of economic impacts of different technical measurements. As a result of this analysis, the AfJEPA would provide a new opportunity for Africa and Japan, as well as other regions. First, this agreement would contribute positive value to the existing African and Japanese MRTAs. Specifically, Namibia, Botswana, and Burkina Faso are the top three highest real GDP growth rate countries in Africa where electronics, petroleum and coal, and chemical, rubber, and plastic industries would comparatively have strong effects on their value-added. In addition to this, the EPA including Japan compared AfCFTA would boost remarkably real GDP in Egypt and Tunisia, and TSE-related electronics would have a relatively strong impact on Tunisia and the Rest of South Africa. Therefore, Africa would improve the production of the manufacturing sectors in total export. Likewise, the Japanese industries would improve their productivity in the motor vehicles and transport equipment, chemical, rubber, and plastic, and textiles and apparel industries. Briefly, we in line with previous studies suggested that (i) the AfJEPA would provide sustainable and promising growth strategy in African macro variables, (ii) trade facilitation and knowledge transfer, which policymakers can improve concrete action and investment, would considerably stimulate African real GDP and other macro variables, and (iii) only tariff liberalization policy would comparatively have less impact across regional real income growth. Thus, potential growth would rely on deep regulation policy through a degree of openness and initial level of trade barriers to each country.
To conclude, Japanese dependence on industrial input and output depending on import goods from African is between 1.1% to 5.5% throughout East Asian countries. Similarly, African output relying on Japanese products is 1.4%. Therefore, the EPA would constitute a strategy for growth for Japan, which has been suffering from long-term economic stagnation, allowing Japan to integrate effects of growth outside of Asia. In addition to this, Africa would enhance its economic development strategy by learning from Japanese MRTAs' experiments and would have access to the Japanese high-tech market and capital.