Statistical analysis of international labour migration strategy from India to the Gulf countries

2.1 Review of literature

The migration theories emphasize the significance of conducting a comprehensive cost-benefit analysis that takes both monetary and non-monetary factors into consideration. In addition to short-term economic gains, migration is motivated by the accumulation of human capital through the acquisition of skills and experience in new environments (Sjaastad, 1962). Migrant networks establish links between prospective migrants residing in their home communities and individuals residing in host countries, which plays a crucial role in reducing the financial and logistical burdens associated with international migration (Massey and España, 1987). The decision to migrate is complex and would be seen as the outcome of a balancing of the benefits of migration against the costs of migration (Bogue, 1977). The inclination to engage in migration is also influenced by various factors that indicate the costs associated with migration, such as the level of education attained by the father and the presence of extended family members in the destination area (Mills and Hazarika, 2001). Workers will relocate to different locations solely if they anticipate receiving greater salaries, as well as considering disparities in amenities. Research confirms that the elimination of all barriers leads to an improvement in labour productivity (Bryan and Morten, 2019). In order to incentivize individuals to migrate from their home nation, a substantial salary disparity would be required to offset the associated expenditures and encourage relocation (Hodge, 1985). Migration entails not only financial strain but also psychological distress, particularly in the case of undocumented migration (Campbell-Staton et al., 2021). Due to the significant expense of moving to the city, a recent empirical study found that rural workers would rather stay in the village and earn a considerably lower income (Imbert and Papp, 2020). A study examining labour mobility confirms that the average expense associated with migrating falls within a range of 0.8–1.2 times the mean income earned by migrant workers (Morten and Oliveira, 2016). Another significant study, utilizing the KNOMAD data set, examines the returnee migrants from Saudi Arabia. The findings indicate that the average migration cost for these migrants in India was equivalent to at least nine months' worth of typical earnings, whereas in Saudi Arabia it was equivalent to 4.5 months' worth of earnings. The analysis additionally confirms that the majority of the variation in overall cost may be attributed to significant variability in recruitment cost. The only expenditure on recruitment constituted almost 75 % of the overall expenditure (Sasikumar, 2019).

2.2 Research gap

The previous research has focused on examining the causes of migration, specifically in terms of push and pull forces, as well as the effects of migration on both families and society. There is a dearth of research on the monetary expenditures and fund-raising strategies associated with migration. The scope of the proposed study is to investigate the financial expenditures related to migration and the tactics employed for fundraising.

2.3 Objective

1. To explore the demographic profile of the sample migrant labourers from Bihar to Gulf countries.

2. To analyze the demographic determinants of the cost of migration from Bihar to Gulf countries.

3. To investigate the various sources of fundraising employed by migrant labourers in Gulf migration

2.4 Hypothesis

1. “ Age, visa sources, technical education, presence of friends and relatives, level of education and prior work experience of the migrant labourers are not significant determinants of the cost of migration”.

4.1 Demographic profile of the respondent migrant labourers

Demographic information is a powerful tool that can be used to gain a deeper understanding of the targeted population. It can be used to compare different groups of people, different age groups, occupations and income levels. Table 1 illustrates the demographic information of the sample migrant labourers. The data shows the distribution of religion, age, income, occupation, and educational background of the migrant labourers. The data reveals that the majority of persons in the sample (90 %) adhere to the Muslim faith, However, it is worth highlighting that the home state of the migrant labourers is primarily populated by individuals practicing the Hindu religion (Alam, 2012). Approximately 64 % of sample migrant labourers in Gulf countries were employed as blue-collar workers, such as labourers, electricians, plumbers, carpenters, welders, mechanics, construction workers, factory workers, and drivers and 29 % were engaged in white-collar occupations, while the remaining 6 % were self-employed, operating their businesses within the Gulf region. Blue-collar workers primarily engage in hands-on activities or physical labour, while white-collar workers typically handle administrative, professional, or managerial tasks (Toppinen-Tanner et al., 2002). The sample consists of 75 individuals, representing 18 % of the total, who are below the age of 30. Additionally, there are 191 persons, accounting for 47 %, who fall within the age range of 30–40. The age group between 40 and 50 consists of 100 individuals, accounting for 25 % of the overall sample. Additionally, 8 % of the sample data corresponds to persons above the age of 50. The majority of the sample population (66 %) falls in the younger age group of below 40 years. The educational background helps us to understand the composition of the sample in terms of the level of education attained. The data on the income distribution of sample migrant labourers that the majority of migrant labourers (67.25 %) earn less than 50,000 rupees per month. Only 32 % of migrant labourers earn more than 50,000 rupees per month in the Gulf countries. This information is crucial for creating a comprehensive profile of the participants and ensuring that the sample is representative of the larger population being studied. There are 90 participants within the sample who lack formal education, constituting 22 % of the overall population. Conversely, 29 % of the sample possess a 10th-grade education. A total of 60 individuals, accounting for 15 % of the overall population, have completed their 12th-grade education. Additionally, it is observed that 23 % of the population are graduates. A mere 9 % of the migrant labourers in the sample possess a master's degree level of education.

4.2 Sources of visa and cost of migration

Migrant labourers often obtain visas via diverse channels to engage in employment opportunities within Gulf countries. The sorts of visas acquired by individuals can exhibit variability contingent upon factors such as the nature of their employment, period of stay, and specific agreements in place. The predominant sources utilized are agents or agencies, Family, friends or relatives, and government agencies. Table 2 illustrates the responses of the sample migrant labourers revealing the various sources through which they obtained their visas. A significant portion of migrant labourers, comprising 76 % of the respondents, obtained their visas through agents or private agencies. These agents or agencies might act as intermediaries between the workers and the employers. Family members, friends and relatives already working in Gulf countries are another important source for the migrant labourers to obtain the visas which account for approximately 21 % of the total sample migrants. A smaller percentage of respondents, approximately 2 %, indicated that they obtained their visas through a government agency. The researcher has also asked the respondents about the total money expenditure on Gulf migration. The response from migrant labourers is shown in Table 2 which sheds light on the range of money expenditure in Indian Rupees for Gulf migration. A significant proportion of sample migrant labourers, constituting 46 % of the respondents, reported spending below 60,000 INR for their migration to the Gulf countries, however, a notable number of respondents, accounting for 36 %, mentioned spending between 60,000 and 80,000 INR. A relatively smaller but significant percentage of respondents, approximately 17 %, stated that they spent above 80,000 INR for their migration to the Gulf. The distribution across these expenditure categories suggests that there is diversity in the financial commitments made by migrant labourers for their migration endeavours (Agbor, 2021).

4.3 Bivariate analysis of cost of migration with prior work experience, sources of visa obtained and type of education of the migrant labourers

Labour Migration from one country to another countries often comes with a range of costs that individuals and families need to consider. These costs, collectively known as the “cost of migration,” encompass various financial, social, and emotional expenditures associated with the process of moving from one place to another. The cost of migration can vary widely based on factors such as the destination country, mode of transportation, legal requirements, and personal circumstances. The researcher has tried to explore the monetary cost of migration of labour from India to the Gulf countries, aiming to establish an association between the cost of migration and prior work experiences of migrant labourers, the type of education migrant labourers possess and the various sources they received their visas. The chi-square test is used to test the null hypothesis that “there is no significant difference in the cost of migration with prior work experience of the migrant labourers”. Table 3 illustrates the result of the Chi-square test. The null is rejected as the Chi-square value is estimated as 19.2096 and significant at a 5 % level of significance. It means that the higher the prior work experience with migrant labourers lower the cost of migration. It is because, with prior work experience, migrant labourers are likely to have acquired a specialized skill set and valuable job-related knowledge. Employers' investment in training curricula might be minimized due to the pre-existing possession of requisite skills by individuals. This reduces the initial financial obligation for both the company and the migrant labourers. The researcher has also tried to find out the association between the cost of migration and various sources from which migrant labourers received their visas. The study confirms that the majority of the migrant labourers obtained their visas with the help agent or private agency. Based on this finding the researcher has formulated another null hypothesis that “there is no significant difference in the cost of migration with various sources that migrant labourers received their visas”. The chi-square test result rejects the null hypothesis as the Chi-square value is 16.1673 and significant at a 5 % level of significance. It means that the cost of labour migration is higher for those who obtained their visas through an agent. This is because recruitment agencies and agents frequently charge fees for their services, which can include visa processing, job placement, and documentation assistance. These fees can substantially increase the total cost of migration for an individual. The educational background of the migrant labourers may also affect the cost of migration. The researcher has classified the education of the labourer as technical education and non-technical education. Based on this classification, the researcher has formulated the null hypothesis that “there is no significant difference in the cost of migration with different types of education. The result of the Chi-square test rejects the null hypothesis as the Chi-square value is 12.408 and significant at a 5 % level of significance. It means that the cost of migration is less for the migrant labourer with technical education. This is because migrant labour possessing technical education frequently exhibits reduced training or onboarding needs when entering their new employment positions. The reduction in expenses for businesses associated with this phenomenon has the potential to facilitate expedited integration of individuals into the labour market.

4.4 Determinants of cost of migration: A multivariate ordinal logistic regression analysis

An ordinal, logistic regression was conducted to examine the association between the dependent variable (Cost of Migration) and independent variables (age, technical education, level of education, presence of relatives and friends and prior work experience). The null hypothesis is “there is no association between cost of migration and age, level of education, technical education, presence of relatives and friends and prior work experience of the migrant labourers “. The regression result is shown in Table 4; the pseudo-R-square value is = 0.178 (Nagelkerke), and McFadden. = 0.086, which measures that 8.6 % change in the dependent variable accounted by the independent variable in the model. The Chi-square test (65.610) is significant at a 1 % level of significance which indicates the estimated model adequately fits the data and these predictors had a significant impact on the cost of migration. The regression result showed that the age of the migrant labourers has a statistically significant and negative impact on the cost of migration ( $\widehat{\mathrm{\beta }}$ ₁ = −0.065, P = 0.000). This is because younger migrants are frequently more prepared to accept the risks and challenges of migration despite having fewer financial resources to cover the costs of migration. Similarly, a visa obtained through an agent has also a significant and negative impact on the cost of migration ( $\widehat{\mathrm{\beta }}$ ₂ = −0.953, P = 0.000). Those who obtained the visa through an agent will have to bear the high cost of migration. It is because migration agents charge fees for their assistance with visa applications, documentation, and navigating the migration process. Migrant labourers with technical education are another significant predictor ( $\widehat{\mathrm{\beta }}$ ₃ = −0.647, P = 0.009) in the model. The migrant labourers without a technical education will have to bear the higher cost of migration. This is primarily due to the willingness of some employers in destination countries to sponsor migrants with technical education. The presence of relatives or friends of migrant labourers is also an important significant predictor ( $\widehat{\mathrm{\beta }}$ ₄ = 0.393, P = 0.043) of the cost of migration. The presence of relatives or friends will lower the cost of migration. The network effect can provide information, assistance, and guidance on how to navigate the migration process, thereby decreasing the perceived costs and risks. The educational attainment of the migrant labourers is a statistically insignificant predictor in the model however school level of education is significant. Similarly, prior work experience has an insignificant and negative impact on the cost of migration, however, those who have 3–6 years of work experience have a significant impact on the cost of migration. This is because migrants with prior work experience are more likely to find employment in their destination countries that match their skills and qualifications and are also able to access networks of other migrants with similar skills (Mintchev et al., 2017). Human capital theory suggests that investments in human capital, such as expenditure on education and training, can lead to increased productivity and efficiency (Nafukho et al., 2004). The findings of this study suggest that technical education and prior job experience can reduce the cost of migration, which could lead to increased human capital in Gulf countries.

4.5 Sources of fund raising

Migration from India to Gulf countries is expensive, and employees and their families frequently rely on a variety of funding sources. Loans from banks (Personal loans or loans against gold) or other financial institutions are common sources of capital; these loans may require collateral or a guarantor. At present there is no migration finance by financial institutions and hence they take either gold loans or personal loans to finance their migration. Friends and family are also provided financial assistance through loans or by pooling their resources. For some migrants, the sale of assets such as land or jewellery can also be a source of funds. In addition, some workers may save for years to finance their migration, while others may work multiple jobs or undertake additional work to save enough money to cover the migration costs. As a method for migrant labourers to raise funds for their migration, online crowdfunding platforms are gaining popularity in some parts of the country (Bai et al., 2023). Overall, raising funds for the migration of Indians to the Gulf requires meticulous planning and consideration of a variety of financial options and sources of support. Because it is also possible that migrant labourers had used more than one source to raise the funds, The researcher asked the respondents open-ended questions about the various sources of fundraising they had used at the time of migration. Table 5 displays the results of the analysis performed on the sample data. The results of the multiple responses show that the majority of migrant labourers (around 40 %) rely on their parents' savings to cover the cost of migration, but friends and relatives also play a significant role in financing migration. More than 30 % of those who responded to the survey said they had borrowed money from friends or family to fund their migration. According to the study, approximately 40 % of migrant labourers were not working before migration; thus, approximately 18 % of migrant labourers used their savings to cover the cost of migration; however, approximately 4 % of respondents either sold or mortgaged their assets to cover the cost of migration. Based on the study, borrowing from moneylenders is higher (2.6 %) than borrowing from commercial banks (2 %). Employers contribute to the cost of relocating migrant labourers in less than 1 % of cases.