The Effects of Migration on Unemployment: New Evidence from the Asian Countries

Abstract

Asian countries have emerged as a new force in the global economy for the past three decades. However, these Asian countries have experienced fundamental problems arising from migration and unemployment. While the effects of migration on unemployment have been extensively investigated for the EU and OECD countries, these effects in the context of the Asian nations have largely been under-examined. This paper investigates the impacts of migration on unemployment in 47 Asian countries for the 1990–2020 period. Various estimation techniques are used in this study, including fixed-effects and random-effects models, as well as generalized least squares and generalized method of moments (GMM). The empirical findings show that migration reduces unemployment in Asian countries when all 47 countries are jointly considered. However, when countries are separated into different groups based on income levels, migration increases unemployment in low-income and low-middle-income countries such as India, Indonesia, the Philippines, and Vietnam. Economic growth is also shown to reduce unemployment in Asian countries, regardless of the estimation techniques. Policy implications have emerged based on our analysis, including a major reform in education for low-income and low–middle-income countries to ensure that workers in these countries are ready for jobs when facing a flow of migration workers who migrate for a better economic outcome.

1. Introduction

Asian countries have achieved miraculous economic growth and development in the past three decades. The region has become the world’s most dynamic region [1]. Asia has been recognized as a region receiving many immigrants each year. According to the UN [2], the number of remittances transferred to this region increased from 183 billion USD in 2009 to 330 billion USD in 2019. However, the figure decreased due to the COVID-19 outbreak, leaving many migrant households with no source of income. Through the combination of these figures, Asia’s intra-regional migration has significantly increased, rising from 35 million in 1990. Most people who migrate to Asia are international students, temporary skilled workers, and working holidaymakers. In addition, a wave of skilled migrants is seeking better job opportunities. The migration trends have impacted socioeconomic conditions, especially employment, in the Asian economies [3].

The total number of international migrants in 2020 was 281 million. Among these migrants, the international migrant stock accounted for 3.5% of the total population in 2019 [2]. An increased rate of globalization is associated with unemployment due to its social and economic effects [4]. While the impact of migration on the economy has been addressed extensively in economics and politics [5,6], there is still no consensus on the impact of immigration on the labor market [7,8].

Previous studies have focused on the effects of migration on economic growth and employment. The focus of recent empirical studies is diverse, including the EU [9,10], OECD [11,12], a group of countries [13,14], or just a single country [8,15]. The literature on migration and unemployment has been examined generally, and different empirical results have emerged. In a study on the labor market performance of immigrants in Germany, Beyer R.C. [16] stated that migrant workers earn 20% less than domestic workers, and the labor market participation rate is also lower. The unemployment rate is also higher. However, the situation has changed over time. One study [17] concluded that migration does not strongly impact unemployment. The research [18] noted that there is no causal relationship between external migration and unemployment. On the other hand, Çelik R, Arslan I. [19] revealed that migration and emigration positively impact unemployment, especially youth unemployment. Our literature review indicates that this important relationship has largely been ignored in the current literature for the Asia region [7,20].

The contributions of this study to the existing literature are two-fold. First, we examine the linkage between migration and unemployment in 47 Asian economies over the past three decades. This linkage has largely been ignored in the Asian region. Second, different estimation techniques are used to ensure the robustness of the empirical results. The study is extended to examine this relationship between two groups of countries with varying levels of income.

This paper is structured as follows. Following this introduction, Section 2 reviews the relevant literature. Section 3 presents and discusses the methodology and data. Empirical results are discussed in Section 4. Section 5 discusses the robustness analysis, and the concluding remarks and policy implications are provided in Section 6.

2. The Impact of Migration on Unemployment

The effects of migration on unemployment have been extensively investigated in the existing literature. Ravenstein [21], in the discussions of the “laws of migration”, explained that migration represents the movements for opportunities and constraints. The author also contends that the primary drivers of migration are mainly economic factors. Lewis [22] showed that workers move from the traditional sector to the modern sector, and labor shortages in the traditional sector have led to rising wages in the sectors, which have in turn increased the incentives for capital accumulation and productivity gains. This cycle will continue until the traditional sector is depleted and the economy has fully transitioned to the modern sector. The research of [23] investigated the relationship between immigration and unemployment in Canada. The authors concluded that the increase in unemployment decreased migration before 1978. One study [24] examined the migration between provinces in Canada using panel logit models for the 1982–1995 period. Migration in rural areas was found to be lower than in urban areas. Urban unemployment is associated with an increase in migration.

For various decades in the 1970s and 1980s, studies have found a negative relationship between immigration and the out-migration of resident workers [25,26], or an insignificant relationship [27,28,29,30]. The authors of [30] argued that mixed results from the literature are due to differences in model specifications, samples, regions, and periods selected in these analyses.

The impacts of migration on unemployment have been divided in the existing literature. The first stream has analyzed how migration impacts unemployment, employment, and the labor market [8,9,12,13,31,32,33]. The second stream has focused on the effects of unemployment, employment, and the labor market on migration [34,35,36].

In the first stream of papers, Nica E [9] showed a low proportion of high-skilled workers who used to or who currently work in another country. In addition, living expenses are the main driver of labor mobility, followed by chances for income improvement and the unemployment rate. The freedom of movement of employees plays a fundamental pillar of economic incorporation in Europe. The study of [37] suggests that immigration positively impacts unemployment. In addition, the findings confirm the unidirectional causality from immigration to unemployment in the short term but not in the long term. One study [38] considered that foreign labor, wage rate, and female participation are associated with increased unemployment in a country. The research of [5] found that owing to the characteristics of the migration policy in Spain, immigration and unemployment are co-integrated, and unemployment is derived from immigration. Such causality presents a positive relationship that the more significant extent of immigration, the larger the extent of unemployment.

Moreover, a positive relationship between GDP and flows of immigration is also found in the long term. One study [12] examined the relationship between migration and unemployment in OECD countries from 2000 to 2015. They concluded that migration negatively affects 23 OECD countries. The authors of [8] suggested a negative relationship between unemployment and net overseas migration, and unemployment and per capita GDP were found in the long term. Another study [13] discussed labor migration between a sending country (Indonesia) and a receiving country (Malaysia), both of which are members of the Association of Southeast Asian Nations (ASEAN). The findings from their study confirm a weakness in protecting migrant workers in Johor Bahru, Malaysia. Most employers kept the documents of their Indonesian migrant employees in Johor. The fisheries sector displayed the largest proportion of employees whose documents were held by their employers. Meanwhile, domestic workers were found to not have sufficient days off every week. Interestingly, the authors of [10] validated the causal connections between net migrants and countries’ economic, social, political, and ecological development. The author argued that international migration has evolved into a multifaceted phenomenon, resulting in population redistribution across nations and significant social and economic transformations regarding the economic growth and development of EU countries. The results from a previous study [39] indicate that returnees in Slovakia had a higher unemployment rate compared with those who stayed, and they were less likely to be self-employed after returning. In addition, another study [40] found that immigration positively affects the GDP of the host nation, and other control factors are also statistically significant in relation to immigration in both the short and long term. The employment opportunities of local residents are not affected by the arrival of newcomers. Moreover, immigrants with high skill levels contribute to the economic growth of the host country.

International migrants cross borders for the economic opportunities in the destination country. Labor market studies have examined the relationship between migrants and resident workers, including case studies, economic studies, and economic mobility studies. Mixed results result in different implications for policy. Governments at the individual and joint country levels seek ways to improve the productivity of the manufacturing and services sectors. They also aim to promote higher value-added activities within their territories and the firms operating in their countries. Doing so relies on creating and fostering a high-quality Asia labor market. However, more attention should be paid to integrating education and industrial sectors to educate and train workers who can work within international-standard companies and develop within them. Additional areas of concern include the role of migrant labor in the region and the degree to which freedom of association and unionization impacts productivity and the promotion of social and economic development.

Our literature reviews indicate that previous studies focused greatly on the EU or OECD countries. Emerging regions such as the Sub-Sahara and Asia have largely been neglected. In particular, the Asian region has recently emerged as an important economic force in the global economy. Urbanization and migration have caused social and economic problems for the countries in the region. As such, this study is warranted to be conducted. In this study, we investigate the link between immigration flows and unemployment in Asian countries using the most updated data and appropriate estimation techniques. In this paper, we use the net migration rate, which compares the difference between the number of persons entering and leaving a country during the year per 1000 persons (based on midyear population) from the international migration in Asia [41].

3. Data, Research Hypothesis, Methodology, and Tests

3.1. Variables: Measurements and the Descriptive Statistics

Table 1. List of variables.

Variables	Description	Source
Unemployment rate	Unemployment, total (percent of the total labour force) (modelled ILO estimate) in destination and origin country	International Labor Organization
International migration rate	The number of immigrants minus the number of emigrants over a period, divided by the person-years lived by the population of the receiving country over that period	United Nations
Economic growth	Gross domestic product growth (percent)	World Development Indicators
GDP per capita	GDP per capita, PPP (constant 2017 international USD)	World Development Indicators
Inflation rate	Inflation, consumer price index (annual percent)	World Development Indicators
Trade openness	Trade openness (Exports and Imports as a share of GDP, percent)	World Development Indicators

presents the measurement of the variables and data sources used in this paper. A sample of 47 Asian countries are included in Appendix A. These Asian countries are also grouped into two groups depending on their income level, including (i) the upper-income Asian countries (25 countries) and (ii) the lower-income Asian countries (22 countries). All details are included in Appendix A. The variables used in our empirical analysis were drawn from previous studies [8,10,11,12,17,32,33].

Table 2. Descriptive statistics.

Variable	Observations	Mean	Std. Dev.	Min	Max
UNEMPL	329	5.6684	4.3138	0.1700	21.2060
MIGRATION	329	2.2815	15.8831	−70.7870	134.4140
GDPPC	328	7.8812	1.5918	3.8972	11.1185
GROW	329	4.2197	8.5747	−33.4999	58.1000
INF	265	11.0736	39.6561	−3.8462	411.7596
TRADE	281	87.9692	58.8893	0.0209	420.4305

Notes: UNEMPL denotes the unemployment rate; MIGRATION stands for the net migration rate; GDPPC denotes the logarithm of GDP per capita; GROW represents economic growth rate; INF is inflation; TRADE stands for trade openness.

presents the descriptive statistics. The highest and lowest values of migration were 134.414 and −70.787, respectively. The average value of migration in Asian countries was about 2.281. The mean value of unemployment, proxied by UNEMPL, was 5.668, with a standard deviation of 4.313, a minimum of 0.170, and a maximum of 21.206.

3.2. Research Hypothesis

On the basis of our literature review and our research objectives, the following research hypotheses were developed and tested in our empirical analysis.

• How does migration affect unemployment in these Asian countries?
• If the above effect is established, are there any differences between countries with different levels of income per capita?

3.3. The Collinearity, Autocorrelation, and Heteroscedasticity Tests

We performed the collinearity diagnostics to examine the multicollinearity. The findings from

Table 3. Collinearity matrix.

	TRADE	MIGRATION	GDPPC	GROW	INF
TRADE	1.0000
MIGRATION	0.2173	1.0000
GDPPC	0.3070	0.4450	1.0000
GROW	0.0891	0.1252	−0.1202	1.0000
INF	0.0927	−0.1237	−0.1830	−0.1696	1.0000

Notes: MIGRATION stands for the net migration rate; GDPPC denotes the logarithm of GDP per capita; GROW represents economic growth rate; INF is inflation; TRADE stands for trade openness.

indicate that multicollinearity did not appear to exist in our study (Tran and Vo, 2022) [1].

In the next step, we examined autocorrelation and heterogeneity using the Wooldridge test and Breusch–Pagan Lagrangian multiplier test.

Table 4. Autocorrelation and heteroscedasticity test.

	Wooldridge Test			Breusch–Pagan Lagrangian Multiplier Test
	F-Test	p-Value	Present Autocorrelation	chi2(1)	p-Value	Present Heteroskedasticity
Model	14.891	0.0004	✓	0.95	0.3301	x

presents the results. These findings indicate that autocorrelation existed in our model. Meanwhile, the results from the Breusch–Pagan Lagrangian multiplier test confirm that the heterogeneity problem did not exist in this model.

In response to the results from the various tests discussed above, various regression methods were used to examine the impacts of migration on unemployment in Asian countries. These estimation techniques include the random-effects and fixed-effects models and the generalized least squares (GLS). The random-effects and fixed-effects models are used in panel data analysis to control unobserved heterogeneity and obtain unbiased estimates of the effects of explanatory variables on the outcome variable. Furthermore, generalized least squares (GLS) regression is used when the assumptions of ordinary least squares (OLS) regression are violated, particularly in the presence of heteroscedasticity and/or serial correlation in the error terms. GLS is a method that allows for efficient estimation by considering the structure of the error terms and providing more accurate standard errors. Aitken A.C. [42] first introduced GLS in 1936, and it is considered a generalization of the ordinary least squares (OLS) estimator for linear regression coefficients. GLS is employed when the OLS estimator is not the best linear unbiased estimator due to the violation of one of the primary assumptions of the Gauss–Markov theorem, namely homoskedasticity and the absence of serial correlation. However, Wooldridge J.M. [43] considers the generalized method of moments (GMM) estimation technique a more appropriate approach, even with weak assumptions. GMM regression offers advantages in addressing endogeneity, providing efficient estimates, accommodating flexible model specifications, and being robust to misspecification. Its versatility and ability to handle various empirical challenges make it a valuable tool in econometric analysis according to Hansen L.P [44]. Additionally, the GMM estimation technique produces robust empirical findings, particularly in models characterized by serial correlation and heteroscedasticity [45]. Hence, we utilized all four techniques to enhance the robustness of the empirical results.

Based on previous empirical studies [8,10,11,12,17,32,33,37], we examined the impact of migration on unemployment for 47 Asian countries over the period of 1990–2020 using five-year data due to the limited data on migration. The following empirical equation is utilized.

$$UNEMP{L}_{it}={\beta }_0+{\beta }_{1}MIGRATIO{N}_{it}+{\beta }_{2}GDPP{C}_{it}+{\beta }_{3}GRO{W}_{it}+{\beta }_{4}IN{F}_{it}+{\beta }_{5}TRAD{E}_{it}+u_{it}$$

(1)

where i and t represent a country and time, respectively. UNEMPL denotes the unemployment rate, MIGRATION stands for the net migration rate, GDPPC denotes GDP per capita, GROW represents the economic growth rate, INF is inflation, and TRADE stands for trade openness.

4. The Effects of Migration on Unemployment in the Asian Countries

Table 5. The effects of migration on unemployment.

	Random Effects	Fixed Effects	GLS	GMM
UNEMPLt−1				0.9516 ***
MIGRATION	0.0116	−0.0209 *	−0.0419 **	−0.0273 ***
MIGRATIONt−1				−0.0119 **
GDPPC	−0.1665	−0.1839	0.1629	−0.3325 ***
GROW	−0.1022 ***	−0.1182 ***	−0.0822	−0.1573 ***
INF	−0.0084 **	−0.0088 **	0.0076	0.0492 ***
INFt−1				0.0021 **
TRADE	0.0112 *	0.0233 ***	−0.0041	0.0023 ***
_cons	6.6050 ***	5.7910 ***	5.1753 ***	3.3981 ***
AR(2)				0.739
Sargan				0.694
Hansen				0.615
No. of Obs.	239.000	239.000	239.000	201.000

Notes: *, **, and *** significant at 10%, 5%, and 1%, respectively. UNEMPL denotes the unemployment rate; MIGRATION stands for the net migration rate; GDPPC denotes the logarithm of GDP per capita; GROW represents the economic growth rate; INF is inflation, and TRADE stands for trade openness.

presents empirical results regarding the effects of migration on unemployment in Asian countries for the 1990–2020 period. Various estimation techniques, including random-effects and fixed-effects models, GLS, and GMM, are used in our analysis. Our results indicate that increased migration was associated with reduced employment in Asian countries during the 1990–2020 period. These results were generally consistent across estimation techniques. Under a dynamic GMM estimation, we also found that previous migration led to lower unemployment in Asian countries. The findings from our paper align with those of earlier studies [8,9,12,31,32], which present a negative relationship between migration and unemployment. If results from the Hausman test show that chi2 = 7.67 and Prob > chi2 = 0.1754, then we accept the null hypothesis. The random effects model is preferred. Furthermore, the GLS and GMM techniques are well suited for addressing endogeneity, providing efficient estimates, accommodating flexible model specifications, and being robust to misspecification.

These findings can be justified, namely that migrant workers contribute to a sense of competition in Asian countries. A flow of migrant workers into destination countries encourages local workers to obtain jobs. Local workers in destination countries are trained and ready for the job. As such, they can secure local jobs, decreasing unemployment in the destination countries. On this basis, migration is positive and healthy for the labor markets of the destination countries. Migration is also positive for migrant workers because they migrate to another country for a better economic outcome. On balance, migration should be encouraged across Asian countries because the final economic outcomes for both migrant workers and the destination countries are positive.

Our results also confirm that unemployment in the previous year is associated with increased unemployment in the current year in Asian countries. On the other hand, economic growth and increased income per capita lead to a reduction in unemployment. These study results are consistent with the studies of [46,47], which conclude that economic growth contributes to job creation and decreases unemployment. Surprisingly, trade openness leads to increased unemployment in Asian countries. This finding aligns with the study [6], which considers that trade openness increases unemployment in capital-abundant Islamic Cooperation economies.

5. A Robustness Analysis: Upper-Income Asian Countries versus Lower-Income Asian Countries

This section examines the impacts of migration on unemployment in Asian countries during the 1990–2020 period based on the income level of these countries. The World Bank classifies countries globally into four distinct groups. The first group includes countries with an income per capita of USD 12,535 per year or higher, namely the high-income countries. The second group includes countries with an income per capita of USD 4046 per year up to USD 12,534 per year, namely the high-middle-income countries. Finally, the remaining two groups have countries with a per capita income level lower than USD 4046 (the low-middle-income countries) up to USD 4045 and USD 1035 (the low-income countries) and below.

In this study, the entire sample of 47 Asian countries was then divided into two sub-samples using the benchmark per capita income level. The first sub-sample, called the upper-income countries group, covered 25 Asian countries, including high-income and high-middle-income per capita countries such as Japan, Singapore, Malaysia, and Thailand, whose income level is above USD 4046 per person per year based on the classification of the World Bank. The lower-income countries group covered the remaining 22 Asian countries, including low-income and lower-middle-income countries such as Bangladesh, India, Indonesia, the Philippines, and Vietnam. The results from a Hausman test show that chi2 = 1.61 and Prob > chi2 = 0.8998 for the upper-income group of countries and chi2 = 4.24 and Prob > chi2 = 0.5150. As such, we accepted the null hypothesis. The preferred model is also the random-effects model in this case.

The empirical results are presented in

Table 6. The effects of migration on unemployment for different income levels.

	Random Effects	Fixed Effects	GLS	GMM
The upper-income countries group
UNEMPLt−1				0.8202 ***
MIGRATION	0.0086	0.0160	−0.0175	0.0061
MIGRATIONt−1				−0.0160 ***
GDPPC	−0.2582	0.1210	−1.6259 ***	−0.4979
GROW	−0.1149 ***	−0.1246 ***	−0.1572 **	−0.1235 ***
INF	−0.0101 **	−0.0073	−0.0139 *	0.0157
INFt−1				−0.0006
TRADE	0.0040	0.0224 *	−0.0030	0.0004
_cons	8.6967 **	36.9010	22.3933 ***	6.2115 *
AR(2)				0.608
Sargan				0.562
Hansen				0.999
No. of Obs.	135.000	135.000	135.000	114.000
The lower-income countries group
UNEMPLt−1				0.3237 **
MIGRATION	0.0873 *	0.0821 *	0.0692	0.0560 **
MIGRATIONt−1				0.0254 ***
GDPPC	−0.2995	−0.4730 *	−0.8107 **	−0.7995 *
GROW	−0.0768 *	−0.0888 **	−0.0903	−0.0583 **
INF	−0.0041	−0.0279	0.1818 ***	−0.1357 **
INFt−1				−0.0382
TRADE	0.0224 **	0.0283 ***	−0.0014	0.0297 **
_cons	6.2537 ***	6.8746 ***	−1.1940
AR(2)				0.417
Sargan				0.715
Hansen				0.961
No. of Obs.	104.000	104.000	104.000	68.000

Notes: *, **, and *** significant at 10%, 5%, and 1%, respectively. UNEMPL denotes the unemployment rate; MIGRATION stands for the net migration rate; GDPPC denotes the logarithm of GDP per capita; GROW represents the economic growth rate; INF is inflation; TRADE stands for trade openness.

. Migration positively contributes to increased unemployment in lower-income Asian countries, whereas this effect disappears in upper-income countries. These findings imply that workers in lower-income countries of the Asian region are not skillful. When migrant workers arrive, these foreign migrants are well prepared to take the jobs, leading to local workers losing their jobs in their country. This finding aligns with the studies of [5,33], which conclude that migration increases unemployment in labor-abundant countries. Lower-income countries are relatively labor-abundant. As such, migration will increase unemployment.

The story is different in upper-income Asian countries, where migration does not affect unemployment when workers in these countries are ready for jobs. In addition, the previous year’s migration also positively affects unemployment in lower-income Asian countries, with the same reasoning as above. We found that previous migration reduces unemployment in the upper-income countries of the Asian region. Migrant workers appear to contribute a sense of competition in the destination countries, causing workers, including migrants and local workers, to actively look for jobs. This sense of competition is suitable for the labor market and the economy. The main findings are illustrated in Figure 1, Figure 2 and Figure 3 below.

6. Conclusions and Policy Implications

The Asian region has emerged as a new economic force in the global economy in the past three decades. The region has become increasingly important in economic cooperation and integration with the world economy. Among other problems, migration to and from these Asian countries has caused various economic and social problems. One hotly debated issue among Asian nations is the effects of migration on unemployment in countries. In addition, managing unemployment has attracted significant attention from policymakers globally, especially in Asian countries. The Asian region has experienced a significant increase in unemployment in the past three decades. Previous studies have focused on the effects of migration on unemployment in EU and OECD countries. However, the existing literature has largely neglected these effects on Asian countries. As such, this paper examined the effects of migration on unemployment in 47 Asian countries from 1990 to 2020. We used various estimation techniques, including the random-effects and fixed-effects models, GLS, and GMM estimation. Our analysis was extended by considering this effect for two subgroups of Asian countries based on different levels of income—the upper-income countries group and the lower-income countries group.

We found that increased migration contributes to decreased unemployment in Asian countries, both short term and long term in Asian countries. This finding confirms that migration to and from Asian nations introduces a sense of competition between migrant workers and local workers competing for jobs in the countries. However, it also helps rebalance the labor market in these countries and can reduce unemployment in these economies. Local workers are keen and ready to apply for jobs in response to a flow of foreign workers. As such, the economy grows in response to decreased unemployment. Migrant workers are also better off in these countries because the key motivation for them to migrate is to achieve a better economic outcome for themselves and their families. For example, most migrants in Qatar are low-skilled workers who come to the country seeking employment opportunities. Another example of migration in Asia is the significant flow of labor migrants from countries such as the Philippines, Indonesia, and Bangladesh to Gulf Cooperation Council (GCC) countries such as Saudi Arabia, the United Arab Emirates, and Qatar. These labor migrants often seek employment opportunities in sectors such as construction, domestic work, and service industries. In 2021, IOM [3] reported the share of labor migration in the total migration from leading countries of origin in Asia. The figures indicate that India accounts for 90%, Afghanistan 69%, Indonesia 65%, Sri Lanka 56%, Nepal 54%, and Vietnam 52%. These statistics highlight the significant scale of labor migration for employment in certain Asian countries, which can have a substantial impact on their respective labor markets. This result reinforces labor-market-related migration policies in Asian countries.

However, the findings change when Asian countries are considered based on income level. While the effects of migration on unemployment in upper-income Asian countries disappear, these effects become negative in lower-income Asian countries. This finding implies that unemployment will increase in countries with the flow of migrant workers. We considered that workers in lower-income Asian countries such as Vietnam are unskilled. As such, they are not educated and trained to be ready for jobs. As such, with a flow of migration workers who migrate for better economic outcomes, local workers become less competitive in job applications and jobs are then offered to migration workers. Therefore, economic growth positively links with lower unemployment across estimation techniques and income levels. This finding supports sustainable economic growth and development in Asian countries. In 2023, ILO provided data that migration to low-income countries can lead to significant pressure on employment. The movement of labor from lower-income countries to higher-income countries is significant for reducing labor costs. These countries faced high unemployment in 2022, including Afghanistan 11.7%, Nepal 11.1%, India 7.3%, and Sri Lanka 6.7% [48].

Policy implications have emerged based on the results of this study. Migration contributes positively to countries because these countries show decreased unemployment. However, the effects are reversed for countries with a lower-income level in the Asian region. Net migration will increase unemployment in lower-income countries in Asia. When immigration is more than emigration in these countries, the resulting consequence can be a considerable burden for job creation in low-income countries in the Asian region. As such, the governments of lower-income countries such as Vietnam should focus on improving the labor force quality. This finding raises important issues of migration that may require tailored solutions in lower-income countries, leading to the significant pressure of unemployment.

Despite the actual findings on the relationships between international migration and social-economic factors on unemployment in Asian countries, this study has limitations. International migration is an increasingly complex process that depends on various demographic, economic, political, military, and environmental factors. In future studies of migration, other important aspects at the macro-level of migration, such as climate change, urbanization, political aspects, human rights, and education, should be considered. In addition, the demographic structure of migrants (religious, gender, education, health, and family) at the micro-level of migration, which requires data from individual Asian countries, may need to be considered as the case study for policy implications.