Migration Governance: Between Skills Needs and Social Constraints

This article has been shortlisted for the 2019 E-IR Article Award

As communication and travel have become easier and faster, international migration has increased to meet the demand and supply of migrant labour. Consequently, while the global population doubled in the last 50 years, international migration tripled over the same period (UN, 2015). More specifically, as of 2015, the global migration stock, or people living in a country not of their birth, was approximately 247 million, which represents a 200 percent increase in the past 50 years (UN, 2015). This development makes the debate over a migration governance framework a key challenge for public policy, especially for Gulf Cooperation Council (GCC) states, and the UAE in particular.

The key challenge for the migration governance debate is how to strike a balance between the benefits and costs of migration. Against this background, the search for and implementation of migration governance frameworks has become a defining aspect of the policies aimed at achieving a sustainable migration path in the UAE. Alongside this debate, there is now a growing consensus that measures of an effective migration governance system should go beyond the creation of a migrant-friendly environment, to consider the socio-economic and demographic needs of the receiving states, such as the UAE (IOM, 2016). This argument is informed by growing youth unemployment amongst Emiratis, and an increasing skills and demographic imbalance in the UAE (Low, 2012).

At the heart of the growing migration debate in UAE is how the current migration system affects the economic, social and demographic outcomes. For example, the UAE’s Ministry of Labour, now the Ministry of Human Resources and Emiratisation, argues that reform of migration policies is central to addressing unemployment and the participation of nationals in the labour market (Ministry of Labour, 2011). This argument is based on two statistical estimates in the Labour Force Survey of 2009 by the UAE’s National Bureau of Statistics. First, the Survey’s estimates suggest that unemployment among UAE Nationals is about 14 percent, increasing to about 25 percent for youth unemployment (Ministry of Labour, 2011). Second, the Ministry of Labour’s analysis of skills distribution of 3.8 million foreign workers, shows that 50 percent of migrant labour is unskilled and a further 29 percent low-skilled (Ministry of Labour, 2011).

In addition, there is also a growing debate about the social cost of the high level of foreign labour, given that the business-friendly fiscal policies in UAE means that the government, not the private companies through taxes, bears the cost of social provision. Aggregating the cost on energy subsidies, use of public services and infrastructure, security and social risk, the available estimate puts the social cost per migrant worker at AED11,559 (USD3,147.06) per year (Al Awad, 2010). The social cost can also be demographic; the increasing number of male migrants, who are unable to qualify to bring their spouses to the country because of the minimum salary requirement, is leading to a growing demographic imbalance.

Furthermore, the potential impact of migrant labour on labour market outcomes and government expenditure raises the question of productivity of the migrant labour. The argument is based on the economic theory that increasing the demand for low-skilled migrant labour may have a negative impact on labour productivity and, therefore, economic growth. For example, Al Awad (2010) argues that while cost low-skilled labour reduces the overall labour cost for the economy, it may also affect the productivity of the aggregate economy, leading to a lower average output per worker.

Consequently, the importance and nature of the debates on the potential impact of migration on economic, social and demographic outcomes require empirical analysis to provide answers. However, systematic and objective research on the evaluation of the social and economic impacts of migration does not exist (Fargues and Shah, 2014). The key social data, including population figures and demographic characteristics of the resident population, is limited in the case of the UAE. For example, a federal census originally due to be carried out in April 2010 by NBS was eventually cancelled. As a result, key statistics are often based on estimates by different national and international statistical agencies, with international agencies questioning the reliability and accessibility of UAE key data (IMF, 2014; De Bel-Air, 2015). For example, while the World Bank estimates the population of UAE for 2008 and 2009 to be 6,894,278 and 7,666,393 respectively. The UAE’s National Bureau of Statistics estimates the corresponding figures to be 8,073,626 and 8,199,996, a difference of 17.1 and 6.9 percent, respectively (NBS, 2015; World Bank, 2017). This empirical analysis is, therefore, an attempt to fill the gap in the literature, by providing statistical analysis using available country-level data to examine the potential impact of migration on key social economic outcomes: unemployment rates; demographic distribution; and economic output or productivity.

The Association Between Migration and Socioeconomic Outcomes

The statistical analysis starts by exploring possible connections between trends in migration and each of youth unemployment, demographic imbalance and economic growth. The Pearson correlation coefficient, which only indicates the direction and strength of association, is estimated as a first step towards establishing the relationship, if any, between migration and the socio-economic outcomes including GDP per capita, demographic distribution, and youth unemployment.

Analysis of Pearson correlation coefficient conducted between migration and the socio-economic outcomes. The result showed that there is a relationship between migration and GDP per capita growth implies a strong, negative correlation (-0.996). This result suggests that there is a negative association between migration and economic growth, i.e. the higher the migration level, the lower the rate of growth of GDP per capita, and vice versa. Looking at the association between net migration and demographic distribution (the ratio of female-to-male population), the result suggests a strong, positive correlation (0.906) between net migration and demographic distribution, which means that the higher the net migration, the higher the differential between the male population and female population in the UAE, and vice versa. The relationship between net migration and youth unemployment indicate a weak positive association, but it is statistically insignificant; i.e. the higher the net migration level, the higher the youth unemployment, although the association is not meaningful. Consequently, the correlation coefficient of 0.05, which is close to zero, suggests a potentially zero relationship between net migration and youth unemployment.

The Effects of Migration on Socioeconomic Outcomes

Regression model is used to estimate the effect, if any, of changes in migration level on the socio-economic outcomes. The estimate for the coefficient on net migration with respect to GDP per capita growth is -1.036, and the p-value of 0.004 suggests that the estimated coefficient is statistically significant. The negative, significant coefficient on net migration suggests that migration has a negative impact on the economic growth of UAE. There is a growing debate about how migrants entering the UAE impact on aggregate productivity. However, the estimated negative impact of migration on economic growth is not surprising, because of the lower productivity associated with unskilled labour. The lower productivity is a potential channel through which migration affects the level of economic growth. The recent evidence suggests that productivity levels in the UAE have been in decline over the years, especially in the non-oil sector of the economy, with the lowest level of productivity observed in the construction sector and large decreases also observed in the service sectors, such as restaurants and hotels, and business services (Al Awad, 2010). Comparatively, the UAE lags behind other small countries with a higher ratio of unskilled-to-skilled labour migration. For example, while the UAE’s labour productivity for 2008 was about AED212,000 (USD58,000), it was around AED392,000 (USD107,000) and AED435,000 (USD118,000) in Norway and Luxembourg, respectively (Al Awad, 2010).

The coefficient on net migration with respect to ratio of female-to- male population is -0.00 with a correspondent p-value of 0.0004, which suggests the estimated coefficient is statistically significant. The negative, significant coefficient on net migration suggests that migration has a negative impact on the demographic distribution of UAE. Specifically, an additional one thousand net migrants will lead to a decrease in 3 females for every 100 males in the population. The channel through which migration leads to demographic imbalance in the UAE can be easily explained. For example, almost 70 percent of migrant workers in the UAE are male, dominating most private sector jobs, apart from domestic jobs, which are dominated by a much smaller female population (Malit and Al-Youha, 2013). Furthermore, the existing migration policy places limitations on family reunion, which is determined by income levels. According to UAE government migration policy, males who are employed in the UAE can sponsor their immediate family members, such as their wife, subject to conditions which include minimum salary of AED4,000 (USD1,089) or AED3,000 (USD817) plus accommodation, making it difficult for a significant number of male migrants to qualify for bringing in their spouses (UAE government, 2017). The estimated regression coefficient on net migration with respect to demographic distribution clearly shows that migration is the significant driver of demographic imbalance, measured as the ratio between female and male workers, which has worsened by about 35 percent from 2011 to 2016.

The coefficient on net migration with respect to youth unemployment rate is 0.004 but the p-value of 0.950 (greater than 0.05) means that the estimated coefficient is statistically insignificant at conventional levels. The result suggests a potential positive relationship between higher migration levels and higher youth unemployment. However, the associated p-value also suggests that this relationship is not meaningful or statistically significant. This result contrasts with the UAE Ministry of Human Resources and Emiratisation, which argues that the growing youth unemployment rate may be driven by the increase in the net migration, especially low-skilled migration, which the Ministry argues may be driving down wages and discouraging nationals, especially the youth, from seeking employment in the private sector (Ministry of Labour, 2011). To further examine this claim, the ratio of unskilled-to-skilled labour is added to the regression model. The results reported in shows that the estimate for the coefficient on skills ratio with respect to net migration is 0.001 and is again statistically insignificant at conventional levels. These results imply that although higher net migration may potentially lead to higher youth unemployment, the estimated p-value indicates that any change in unemployment rate as a result of increase in migration rate is insignificant.

Discussion of the Effects of Migration in the UAE

The findings suggest a statistically significant negative impact, whereby an increase of one thousand in net migration into the UAE, on average, will result in a reduction in the GDP per capita growth by about one percentage point, after controlling for the potential impact of low-skilled migration. The fact that the results suggest a negative impact even after discounting for the effects of the skills’ composition of migrants is particularly interesting. As such, it is important to understand the channels through which migration may impact on economic performance. According to Orefice (2010), the main transmission mechanism is the human capital distribution of the migrant population; the higher the low-skilled levels in the migrant population, the worse the labour productivity level and, therefore, the lower GDP per capita growth.

The concept that explains the relationship between migration and productivity is the capital-labour ratio, which, when the optimal ratio is identified, gives the most efficient combination of capital and labour in the economy. The illustration of how migration affects the economic performance, can be achieved by assuming that the capital accumulation is constant, which implies that an increase in net migration, leads to an increase in labour inputs and, therefore, a reduction in capital per labour and output per labour. However, this negative impact can be minimised, or partially offset, if the migrants are primarily high-skilled. But where the migrants are primarily low-skilled, as in the case of the UAE, the negative impact of migration on labour productivity holds.

What this explanation demonstrates is that the economy of a migrant-receiving country will potentially gain—have a higher per capita GDP—if the migrant inflow is mainly skilled labour, as this increases the productivity of the available capital. However, the reverse is the case if the migrant workers are mainly low-skilled, and hence are less productive, which not only reduces capital-labour ratio but also reduces the efficiency of capital.

The implication of low-skilled migration can be further illustrated by the findings of Kangasniemi et al. (2012). The study considers data over the period 1996 to 2005 in order to analyse the impact of skilled and low-skilled migration on productivity in the UK and Spain at the industry level. The evidence for Spain from the study suggests that migration may have a negative impact on productivity. The study finds that productivity deceases as more migrants join the sectors examined, especially where the migrants are, on average, less-skilled than Spanish workers. For the UK, the study finds that the negative impact of low-skilled migrants offsets the positive impact of skilled migrants on labour productivity.

Furthermore, Orefice (2010) examines the productivity effects of migration in 24 Organisation for Economic Co-operation and Development (OECD) countries from 1998 to 2007. The study finds that inward migration has a significant impact on the productivity of the host countries, with estimates of the relative impact achieved by differentiating between the impacts of high-skilled migrants and low-skilled migrants. The findings from the study suggest that high-skilled migrant labour has a positive impact on the productivity, or per capita GDP, of the host country. In contrast, the findings suggest an increase in low-skilled migrant labour, on average, leads to a decrease in per capita income, which results in the production process shifting towards less productive, more labour-intensive production ones. Overall, the study finds that increasing inward migration by one percent, in the short run, leads to 0.69 percent decrease in per capita GDP. The study also concludes that the higher proportion of skilled migrants relative to low-skilled migrates may minimise the negative impact of migration, highlighting the strong impact of low-skilled migration on productivity.

This finding clearly highlights the potential negative impact of low-skilled migration on economic performance. With about 80 percent of migrant labour in the UAE low-skilled or unskilled, the implication is straightforward: effective migration governance should be designed to attract skilled migrants who will improve the productivity of the UAE’s economy. However, transiting from a low-skilled to a high-skilled economy is liable to pose a major challenge; for example, the on-going infrastructural development requires significant labour inputs, many of which will be undertaken by low-skilled, migrant labour. Furthermore, as Al Awad (2010) shows, the construction sector has the lowest level of productivity in the UAE’s economy, which highlights the potential policy challenges for balancing the primary needs of economy and boosting its productivity.

Regarding demographic imbalance, the imbalance is the significant difference between the male and female population. The findings suggest that migration has a significant negative impact on the demographic distribution of UAE population. More specifically, the estimated regression coefficient, suggests that the share of females in the population will decrease by three for every 100 males in the population, if the net migration increases by one thousand.

This finding clearly shows that migration has a fundamental implication for the relative composition of females and males in the UAE’s populations. For example, while the UAE national composition is evenly balanced between males and females with males comprising 50.7 percent and females 49.3 percent (Mansour, 2017), the corresponding distribution increases to 70 percent for males, when non-nationals are included in the population (UN, 2017). It is important to highlight the implications of a major demographic imbalance. Large or growing gender gaps tend to have a negative impact on the workforce profile as they create an imbalance in the structure of skills in the labour market, with both economic and social costs. In terms of the economic cost, gender gaps in favour of males skew jobs and skills’ development towards male-dominated job roles, thereby negatively affecting efficiency and diversity in the labour market. Socially, where the gender gap is as a result of male-dominated migration, it may lead to an increase in human trafficking of females and criminal activities (Saltenyte, 2013). Furthermore, the negative effects of migration-driven gender gap may become perpetuated if, as with the UAE, family unification is conditional on the income level of male migrants. Indeed, the migration-driven gender gap may, at least in the short- to medium- run, persist because the economy currently relies on low-skilled skilled, male- dominated roles. Therefore, breaking this vicious circle may require changing the rules on family reunion to bring the income condition into line with average income.

Concerning youth unemployment, which is a key concern of policymakers in the UAE, due the potential social and economic cost implications. The findings suggest a positive relationship between migration and youth unemployment but that it is statistically insignificant. This finding implies that while the trends in youth unemployment and migration tend to move in the same direction, changes in youth unemployment cannot be explained by changes in migration level.

One possible explanation is the ‘nationalisation’ of the labour market by the UAE government (Emiratisation policy), which seeks to increase the proportion of UAE nationals in the private sector labour market. Emiratisation policies are a combination of quotas for national labour and taxation on foreign labour. For example, the banking sector is required by the Emiratisation quota policy to target an increase in the number of Emiratis by four percent per year. Similarly, a five percent target is set for the insurance sector and two percent for all private sector companies with more than 50 employees (UAE Government, 2018).

However, there is a question about the role and effectiveness of Emiratisation policy as a factor that promotes the participation of nationals to counteract the increasing dependence on foreign labour. For example, Al-Ali (2008) studies the effectiveness of the Emiratisation in boosting the prospect of UAE nationals, especially the youth, in the labour market. The findings suggest that Emiratisation has not delivered the expected results, with factors hindering the participation of nationals in the labour market, including low standards of education and skills, inadequate English, and a lack of trust by employers in the work-readiness of UAE nationals.

The study also finds that, compared to the rewards available in the public sector, the relatively low wage in the private sector is a significant factor which discourages nationals participation in the labour market. This result is consistent with Randeree (2012) who finds that private sector wages are lower than wages in the public sector, and that there are better employment benefits and working conditions in the public sector, such as job security and shorter working hours. In addition, there is evidence that differences in the organisational culture between the private and public sectors is a major factor why Emiratisation is not effective in driving up the UAE nationals’ participation in the private sector labour market. For example, regimented working hours, commitment to corporate objectives and diverse working environment are significant in limiting participation, such that even national employers often have strong reservations about employing fellow nationals (Al-Ali, 2008; Randeree, 2012).

Summary & Policy Implications

One key argument for better migration governance is to provide a mechanism for ensuring that migration leads to positive outcomes for the host country. Migration theories, particularly political-economy based models, suggest that higher wages and job prospects provide positive incentives for migrants to move from one country to another. However, the same theory suggests migration may have potential negative impacts on the receiving country, depending on the nature and quality of migrants attracted. To examine the impact of migration on the socio-economic outcomes of the UAE, as part of the aim of developing a balanced migration government framework, the effects of migration on economic growth, youth unemployment and demographic distribution were examined.

The policy implication of the findings is that migration governance should take into account the skills composition of migrants and the UAE’s current policy of strategically shifting the economy towards a high-skilled, knowledge- based economy, which means that migration governance, should be designed to attract migrants who have the desired skills. Thus, there is a need for a more harmonised migration governance framework as the present discrepancy leads to increasing the gap between the current policy of strategically shifting the economy towards a high-skilled and knowledge-based economy and labour market productivity in the UAE to achieve the UAE’s 2020 Vision.

Furthermore, migration governance should go beyond simplistic argument of the migration governance framework for better understanding the reasons why a country such as the UAE is overly dependent on migrant labour; therefore, proposing three-dimensions balanced migration governance approach, which reveals important gaps in developing a migrant- friendly environment for UAE’s policy makers. One dimension is exploring its implications in relation to socio-economic outcomes. Other diminutions, which not included in this research, are legal and institutional capacity that aimed at creating a migrant-friendly environment, and, on the other hand, allows for the evaluation of migration outcomes with respect to the economic, social and demographic objectives of the UAE. The relevant social and demographic objectives, according to UAE Vision 2021 and Abu Dhabi 2030, form part of what is termed “Emiratisation” policies, which target higher growth and productivity, lower youth unemployment, higher women’s participation in the labour market and a reduction in demographic imbalance.


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