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Migration, Health and Development in India, South Asia and China: Perspectives in the COVID-19 Era

Migración, salud y desarrollo en India, Asia del Sur y China: Perspectivas en la era COVID-19
Migration, santé et développement en Inde, en Asie du Sud et en Chine : perspectives à l'ère de la COVID-19
Binod Khadria, Narender Thakur and Ratnam Mishra

Abstracts

This chapter revisits the relationship between migration, health and development in the context of Global Compact for Safe, Orderly and Regular Migration (GCM) objectives interrupted by the external shock of the COVID-19 pandemic. By using recent and emerging data from global sources like the United Nations (UN), World Health Organization (WHO) and World Bank, it looks at health indicators, migration stocks and economic development parameters in select South Asian countries, including India, over the last three decades—1990–2020. These are compared against both the world totals and those for China—the East Asian country at the epicentre of COVID-19. The chapter provides background on comparative indicators of economic development in India, other major South Asian countries and China, and critically examines three issues: (a) lessons from the challenges COVID-19 posed to the GCM objective of making migration ‘safe, orderly and regular’ (SOR); (b) indicators of the relationship between migration, health and development in the context of the GCM and COVID-19; and (c) challenges emerging from the dynamic relationship between migration, health and development in the COVID-19 era.

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The authors are grateful to the anonymous reviewers for their comments and observations that helped in revising the final draft.

1. Introduction

1Following the conclusion of the Millennium Development Goals (MDGs) period in 2015, the United Nations (UN) member states embarked upon a wider and disaggregated global agenda of development under the Sustainable Development Goals (SDGs) 2015–2030. Although there was a certain happiness about migration being included in Target 10.7 under the catch-phrase ‘no one to be left behind’, strictly speaking migration had once again missed the bus on account of it not being designated on its own as a major goal among the other SDGs. In fact, disappointment at this exclusion was voiced during the plenary session of the Metropolis International Conference held in Mexico City in September 2015 (Khadria, 2015). As the Syrian refugee crisis also engulfed parts of Europe around the same time, what followed was an initiative aimed to convince the UN member states to agree upon two compacts, both of which came into effect in 2018: the Global Compact for Safe, Orderly and Regular Migration (GCM) and the Global Compact on Refugees (GCR). The GCM thus finally came out of a long process of multilateral negotiations over international migration initiated by the UN Secretary General Kofi Annan in 2002. It took the UN 16 years to bring some member states on board to negotiate and deliberate upon the sensitive subject of international migration, which countries considered to be their exclusive sovereign territory. Although a few countries later withdrew from the GCM, 152 countries out of 193 voted in favour of the agreement and its 23 objectives. Not every objective among these 23 is relevant to all countries and regions of the world. For the nine countries of South Asia, nine objectives seem to be of higher priority. These nine objectives are related to fair and ethical recruitment of nurses, global shortage of human capital etc. (objective 9), smuggling/trafficking of women and children, including fake and fraudulent marriages from India (objectives 9 and 10), more certain and predictable pathways for regular migration (objectives 5 and 12), basic services for migrants like health, education, water, sanitation etc. (objective 15), skills development and mutual recognition of qualifications, including for learning-by-doing and on-the-job training (objective 18), faster, cheaper and safer remittances (objective 20), and totalisation and portability of social security contributions and earned benefits (objective 22).

2The pathways to implementing these objectives are subject to the country positions spelled out in their respective statements made at the concluding multilateral forum preceding the agreement (Khadria et al., 2019). These are reflected in the statements that each of the South Asian countries and China made at the time of ratifying the GCM, presented later in this chapter. The GCM derives its mission from SDG 10, which is to ‘reduce inequality within and among the countries’, and more specifically its Target 10.7—to ‘facilitate orderly, safe, regular and responsible migration and mobility of people, including through the implementation of planned and well-managed migration policies’.

3This chapter analyses the relationship between migration, health and development during the period immediately prior to the COVID-19 outbreak and throughout the pandemic up to early 2021 in South Asian countries and China with a view to recommending comprehensive policy initiatives for the post-COVID-19 period. The chapter is divided into seven sections. Following this introduction, the second section covers the background on global inequalities and migration and the third addresses the chapter’s objectives and sources of data. Section four looks at the country statements on the GCM in light of the different situations prior to the COVID-19 outbreak and following it during the pandemic. Section five highlights the economic condition of South Asian countries and China by comparing various economic indicators. Section six examines the relationship between migration status, health and economic indicators in the context of the COVID-19 pandemic. The final section includes a summary and considers policy implications.

2. Background

4The income inequalities and development gaps between developing economies, like those of India and China, and developed economies, like those of the United States (US) contribute greatly to human mobility across borders as a result of wage differentials (Li, Bedford and Khadria, 2019). At the global level, gross domestic product (GDP) per capita is an important indicator of economic development in the countries of origin and the countries of destination of migrants. Dependency theory (Singer, 1950; Prebisch, 1959) and world-systems theory during the 1950s, 1960s and 1970s talked about the factors of underdevelopment among Asian, African and Latin American countries. According to dependency theory (Toye and Toye, 2003), developed countries are rich because of the profit they gained at the expense of developing countries through the exploitation of cheap labour and resources available in the latter (i.e., periphery countries) in exchange for obsolete technologies from the former (i.e., core countries). Similarly, world-systems theory explains that underdevelopment in developing economies is the result of globalisation and the economic imperialism of developed economies. This theory emphasises that the world system is based on the classifications of core, semi-periphery and periphery countries. The core countries utilise high-skill and capital-intensive production techniques, whereas the rest of the world (comprising semi-periphery and periphery countries) are dependent on low-skill and labour-intensive production techniques.

5Since the early 1990s, with economic globalisation, mobility of people has increased from the global South to the global North countries, resulting in more remittances (in the current account of balance of payments (BOP)) from the destination countries to the sending countries of migrants. For example, migration of high-skilled people from India and China to the US in this phase of globalisation contributed to a rise in remittances that has been counted as an economic gain compensating for the brain-drain for these two major countries of origin. In contrast, the growth of foreign trade in goods and services led to a rise in the flow of foreign capital from the global North to the global South, and thereby of profit in the reverse direction. This resulted in lower net foreign exchange earnings for the global South countries in the periphery. For instance, India experienced an adverse BOP in comparison to the US . At a macro level, remittances could not redress poverty and income inequalities resulting from underdevelopment in the peripheral origin countries such as India and other South Asian countries and there was hardly any transfer of technology worth its name.

6According to world-systems theory and dependency theory, the income inequality and development gaps between the centre and periphery economies cannot be bridged with the ongoing market economic structure, as reflected in the divergence of GDP per capita between the US and India as well as other South Asian countries. Whatever increase India and China experienced in their GDP per capita due to globalisation could not bridge the gap between them and the US. This was mainly because of multinational companies having the US as the source of their foreign capital, which facilitated a positive BOP account for the US and other developed destination countries.

7During economic crises, mainstream economics has both neglected the theories and stayed ignorant of the gaps in economic development and income inequalities. Therefore, there is a need to address these issues within mainstream economics and work on the causes and effects behind the underdevelopment that ultimately leads to migration pressures. Uneven development and income inequalities are instrumental to the migration decisions of migrants from the global South to the global North for their better living and working conditions. These issues have in some instances been addressed more actively during times of crisis by multilateral institutions like the UN. However, the gaps and inequalities could not be reduced at a greater scale even though migration did lead to improvements in the living standards of migrants and their families in the global South via higher wages in the destination countries and remittances to migrants’ countries of origin, such as India, which is the highest global recipient of remittances sent by migrants. Migrants also contributed to a greater scale in economic growth and development in their destination countries in the global North.

8The UN has been instrumental in bridging the challenges of migration with approaches to development. In 1990, the United Nations Development Programme (UNDP) came up with the Human Development Index (HDI) to comprehensively estimate human development at the country level based on three prominent indicators: income, health and education. The HDI shows the limitations of economic growth and development for human lives, sustainability of material production and neglect of income inequalities at the country and global levels. To address development gaps, the UN launched eight MDGs for 2000 to 2015 and seventeen SDGs for 2015 to 2030. The rise in economic inequality between and within countries was witnessed during the global financial crisis of 2007, which revealed the fault lines of development pathways across different nations. However, migration, which had not been among the first eight goals also did not get included among the second set of seventeen. It was only through the back door of the GCM and the GCR, finalised in 2018 to support the safe, orderly and regular migration of migrants and refugees that the UN finally succeeded in upholding migration as an independent global agenda without piggybacking on that of global development (IOM, 2019). The GCM and GCR were thus acknowledged to address the reduction of income inequalities specified under SDG 10.

9With this background, the ongoing COVID-19 pandemic has led to further uncertainties resulting from the stricter immigration policies intended to contain fatalities and rising unemployment among the local population in countries of destination, particularly the US, as well as countries of origin such as India, other South Asian countries and China. Due to the COVID-19 pandemic and the global recession, the inflows of remittances were also expected to decline in India by 9 per cent from USD 83.3 billion in 2019 to USD 76 billion in 2020 and in South Asian countries by 4 per cent from 2019 to 2020 (World Bank, 2020). Along with the decline in remittances to global South countries, immigration restrictions and travel bans were initiated by the US to protect life and the livelihood challenges arising from the COVID-19 pandemic. It is expected that migration pressures will increase with stricter immigration policies in destination countries, creating more challenges of development gaps and income inequalities in the post-COVID-19 era. It has been argued by economists and scientists that the neglect of the sustainable development indicators and early warning signals of the communicable disease at the global level have made the situation grimmer (Seshaiyer and McNeely, 2020). Prior to the COVID-19 pandemic, the challenges of underdevelopment already existed as income inequalities along with emigration pressures in South Asian countries as well as China. It is now being observed that the COVID-19 pandemic has made the situation even more challenging.

3. Objectives and Data Sources

10This article has three main objectives in examining the dynamic relationship between migration, health and development in the context of the COVID-19 pandemic: (i) to highlight and assess the critical statements of India on the GCM objectives as compared to those of the other South Asian countries and China during the COVID-19 period, particularly in the light of slower economic development and greater income inequalities during this time; (ii) to establish the relationship of migration and health with economic development in these countries in the pre-COVID-19 period; and (iii) to highlight the challenges of migration, health and development in these countries during the COVID-19 period. The sources of data used to examine these objectives are the World Bank, the UNDP, the International Monetary Fund (IMF), the WHO, and the UN. On the basis of an analysis of these dynamic relationships, we suggest a number of policy implications to enhance the positive relationship between inclusive migration, sustainable development and the public health system.

4. Looking Back at the Country Statements on the GCM

11This section analyses the statements on the GCM made by a select few signatory South Asian member states (India, Pakistan, Iran and Sri Lanka) and China. The statements of other countries (Bangladesh, Nepal, Maldives, Afghanistan and Bhutan) are also briefly commented upon.1

4.1. India

12In 2017, India stated that with regard to the GCM it

[…] may like to flag that in certain cases stringent and lopsided policies of the receiving States make the migrants vulnerable, make it difficult for the migrants to comply with obligations of retaining legal migratory status and in quite a number of cases migrants were forced to face criminal proceedings even for minor violations.

  • 2 See also, GCM: India calls for protecting Human Rights of migrants, libralising [sic] norms for ec (...)

PMI Geneva, 2017, 12

13In 2018 it declared, ‘[The GCM] recognizes the sovereign right of each state in determining its migration policy. Individual states can distinguish between regular and irregular migrants and determine the conditions of entry and stay of non-nationals in their jurisdiction and need not follow a prescriptive approach’ (UN, 2018b, 2).

14India further stated:

International migrants are said to contribute nearly 10% of the global GDP even as they formed only 3% of global population [. . .] There is a legitimate purpose to legal migration as the means of global economic development as opposed to illegal migration. [. . .] India looks forward to continuing our engagement with partners to facilitate safe, orderly and regular migration.

UN, 2018b, 2, 4

15Of the above three statements made by India, the second and third, made in 2018, seem to be inconsistent with the first statement, made in 2017. The first raised concerns regarding the vulnerability of Indian overseas migrants to the discretion used by destination countries and employers through conflating minor and major violations of the legality of their status. The second concerns the definition of illegal or irregular immigration of ‘non-nationals’ in India, purporting it to be the sovereign jurisdiction of the country and not to be prescribed by the GCM. The third statement raises a doubt as to how 10 per cent of the global GDP could all be attributed to be the contribution of legal migrants alone who comprise just 3 per cent of the global population, assuming thereby that the contribution made by irregular migrants has not been recognised.

4.2. Pakistan

16Pakistan gave three different statements on the GCM in 2018. It said, ‘While States retain the sovereign right to strengthen their border security, this right should be consistent with international law. Migrants regardless of their migration status, are entitled to the universal human rights and fundamental freedoms, which must be respected, protected and fulfilled across all stages of the migration cycle’ (UN, 2018d, 4). Further, it added another statement: ‘The tendencies of xenophobia, racial profiling and Islamophobia in the countries of destination against migrants must be countered. All States must foster inclusive and cohesive societies by empowering migrants to become active members of society’ (UN, 2018d, 4). Third it stated: ‘As we move towards implementing the GCM provisions, we look forward to enhanced bilateral engagements, energized regional dialogues and global cooperation that are responsive to the GCM commitments’ (UN, 2018d, 4).

17Pakistan emphasised that the human rights of migrants should be taken care of irrespective of their legal or so-called illegal status in destination countries. It called for countering the increasing tendencies of xenophobia, racial profiling and Islamophobia against migrants in countries of destination.

4.3. Iran

18In 2018, Iran stated that

the GCM could enhance the positive impact of cross-border migration for all through effective management and international cooperation. The validity of these notions depends on taking the various and unequal capacities of member states into account as well as the implementation of the compact by all members of the international community in good faith.

UN, 2018c, 1

19It further entreated:

Let’s not forget that the impact of migrants on their host countries is a function of the specific circumstances such as level of development and demographic situation of any given host country. We should also keep it [in] mind that [a] majority of developed countries have been well equipped with normative tools and natural and man-made barriers to shield themselves from negative impacts of migration and to tailor migratory flows in a way to maintain or even enhance their level of development.

UN, 2018c, 1

20Iran also expressed concerns about the withdrawal from the GCM by developed countries, specifically the US.

4.4. Sri Lanka

21In 2018, Sri Lanka gave its statement:

The adoption of the Migration compact in our view marks a beginning of a new journey, a collective journey-consciously departing from the path of negative and toxic narrative of migration and migrants, aiming at safe, regular and orderly migration, and adding real value and dignity to human mobility. [. . .] Sri Lanka places high importance on inclusivity, particularly the active engagement with the business and private sector involved in labour migration.

UN, 2018e, 1

4.5. Other South Asian Countries

22The statements made by the other five South Asian countries, specifically Bangladesh, Nepal, Maldives, Afghanistan and Bhutan, are in support of the GCM and offer assurance of the countries’ implementation of their commitments. The five countries made statements more or less similar to the statements made by Pakistan and Iran to work for positive relationships between international migration and sustainable development.

4.6. China

23The statement made by China was more generic than those of the South Asian countries, especially that of India. It appears more sensitive and balanced toward making migration safe, orderly and regular for both immigrants in China and emigrants from China. The second paragraph of China’s statement reads as follows:

In today’s era of globalization, orderly migration flows help stimulate vitality for innovation, promote economic development and global inclusive growth, and enhance mutual understanding and cultural integration among nations. Meanwhile, one should also realize that irregular migration flows without effective governance may breed organized transnational crime and increase pressure on and challenges to countries in border control and societal governance. The protection of migrants’ own rights and interests is also often under threat. We need to strengthen global governance in the field of migration to bring about safe, orderly and regular migration.

UN, 2018a, 1

24On the governance of global migration, China advocated four points: the first was related to upholding the principle of respect for national sovereignty; the second focused on the regularity, safety and orderliness of global migration flows; the third addressed resolving the main issues of migration, such as underdevelopment and unbalanced development; and the last point considered cooperation among member states to implement the GCM. In the last paragraph of the statement, China recognised the positive role migration plays in development.

25Just around the time when stock-taking was due for the indicators of the GCM objectives being achieved at the end of the year, in December 2019, the world was struck by the COVID-19 pandemic, which ‘left no one behind’ and created a ripple of disruption in people’s lives, livelihoods and migration. It remains to be seen how consistent the South Asian countries will be with respect to the GCM’s objectives, particularly in and after the extraordinary circumstances created by the COVID-19 pandemic. The next part of this chapter examines the consistencies and contradictions in the relationship between migration and development by looking at the precariousness of the health risks let loose by the extraordinary circumstances in South Asia and China, which was the epicentre of the contagious infection.

5. Comparative Economic Indicators in India, South Asia and China

26During times of recession, economic theory suggests increasing government expenditure so as to expand aggregate demand to counter the economic slowdown and to contain rising unemployment. It is therefore pertinent to examine the share of government expenditure in GDP. Table 8.1 shows that, at the world level, government expenditure in GDP was 16 per cent in 1990 and 1995 and increased to 17 per cent in 2015 and 2018.

Table 8.1 General government final consumption expenditure in India, other South Asian countries and China (% of GDP)

Country/Region

1990

1995

2015

2018

Afghanistan

NA

NA

12

NA

Bangladesh

4

5

5

6

Bhutan

15

12

18

NA

China

14

13

14

15

India

11

11

10

11

Iran

11

14

13

NA

Maldives

NA

NA

NA

NA

Nepal

9

9

11

12

Pakistan

15

12

11

12

Sri Lanka

10

11

9

9

South Asia

11

10

10

11

World

16

16

17

17

Source: World Bank (2020).

Note: NA denotes data not available.

27 However, the government expenditure in India remained stagnant at 11 per cent in 1990 and 1995, thereafter declining to 10 per cent in 2015, and catching up again to 11 per cent in 2018. China’s government expenditure was relatively higher at 14 per cent in 1990, 13 per cent in 1995 and 2015, and 15 per cent in 2018. Both India and China were, however, lower than the world indicators for these years (World Bank, 2020).

28The shares of government expenditure, especially in times of recession, are interlinked with the economic growth of GDP. The lower government expenditure in India was accompanied by higher economic slowdown as opposed to China’s higher government expenditure and lower economic slowdown. The world GDP growth rate also increased in 2018 along with higher government expenditure. Thus, it is clear from this analysis that there is a need to increase government expenditure to improve the demand conditions and employment generation in times of recessionary pressures.

29 Table 8.2 depicts the score values of the HDI from 1990 to 2018. The level of human development in China improved over these years, which is reflected in the improved HDI scores surpassing even the world HDI trend in 2010. The HDI values for China were 0.50 in 1990, 0.70 in 2010 and 0.76 in 2018 as compared to the world’s scores of 0.60, 0.69 and 0.73 respectively. The values of Indian HDI scores in 1990, 2010 and 2018 were 0.43, 0.58 and 0.65 respectively, showing lower values than those of both China and the world. The lower Indian HDI scores pulled down the overall South Asian HDI values over the years, which also remained lower than the HDI values for both China and the world. The respective HDI values for South Asia were 0.44, 0.59 and 0.64 in the three years. In comparison to China and the world, lower economic development in India, as reflected in lower HDI scores, is linked with low growth rates of GDP and GDP per capita.

Table 8.2 Human development in India, other South Asian countries, China, South Asia and the world, 1990–2018

HDI Rank

Country

1990

2010

2015

2018

65

Iran

0.577

0.756

0.789

0.797

71

Sri Lanka

0.625

0.75

0.772

0.78

85

China

0.501

0.702

0.742

0.758

104

Maldives

NA

0.669

0.709

0.719

129

India

0.431

0.581

0.627

0.647

134

Bhutan

NA

0.571

0.606

0.617

135

Bangladesh

0.388

0.549

0.588

0.614

147

Nepal

0.38

0.527

0.568

0.579

152

Pakistan

0.404

0.524

0.55

0.56

170

Afghanistan

0.298

0.464

0.49

0.496

South Asia

0.441

0.585

0.624

0.642

World

0.598

0.697

0.722

0.731

Source: Authors, using UNDP (2020).

Note: The Human Development Index (HDI) ranking in column 1 pertains to the 2018 index. NA denotes data not available.

Table 8.3 GDP growth of a selection of Asian countries (1990–2020, annual %)

Country Name

1990

2015

2018

2020

Afghanistan

NA

1.5

1.0

NA

Bangladesh

5.6

6.6

7.9

NA

Bhutan

10.9

6.6

2.3

NA

China

3.9

6.9

6.6

1.0

India

5.5

8.0

6.8

4.5

Iran

13.8

-1.3

NA

NA

Maldives

NA

2.9

6.9

NA

Nepal

4.6

3.3

6.7

NA

Pakistan

4.5

4.7

5.8

NA

Sri Lanka

6.4

5.0

3.2

NA

South Asia

5.4

7.5

6.7

NA

World

2.9

2.8

3.0

-4.9

Source: Authors, using World Bank (2020) and IMF (2020).

Note: NA denotes data not available.

30 Table 8.3 shows that India’s GDP growth rate experienced a sharper decline of 1.2 percentage point from 8 per cent in 2015 to 6.8 per cent in 2018 whereas China’s GDP growth rate experienced a slower decline of 0.3 percentage points from 6.9 per cent in 2015 to 6.6 per cent in 2018. For improving human and economic development conditions, there is a need for higher government expenditure via expansionary fiscal policy in times of recession and the COVID-19 pandemic to universalise the public healthcare system, increase employment opportunities and ensure safe, regular and orderly emigration and immigration.

Table 8.4 GDP per person employed in a selection of Asian countries (1995–2019, constant 2011 PPP USD)

Country Name

1995

2015

2018

2019

Afghanistan

3,572

5,082

4,897

4,916

Bangladesh

4,311

8,222

9,216

9,691

Bhutan

8,092

16,419

19,524

20,436

China

4,497

24,267

29,499

31,380

India

5,645

15,898

18,565

19,589

Iran

54,727

56,766

66,427

68,776

Maldives

28,809

28,551

33,072

34,036

Nepal

2,729

4,189

4,393

4,468

Pakistan

11,997

14,095

15,430

15,906

Sri Lanka

12,970

29,137

32,673

34,134

South Asia

6,032

14,687

16,890

17,747

World

21,975

34,290

36,750

37,739

Source: Authors, using World Bank (2020).

31The level of economic development is examined by using World Bank data on GDP per person employed at the constant prices of 2011 at purchasing power parity (PPP) for the four years, specifically 1995, 2015, 2018 and 2019 (see Table 8.4 and Figure 8.1). The level of Indian GDP per person employed increased in each of these years. However, the difference between the world GDP per person employed and that in India also continuously increased through these years. The GDP per person employed in South Asian countries as a whole is slightly lower than that in India, even if only by a slight margin. The GDP per person employed in China was lower than that in India in 1995, but it surpassed the Indian GDP per person employed in the subsequent years of 2015, 2018 and 2019. The gap between the world GDP per person employed and that of China also reduced in the latter three years (see trends shown in Figure 8.2).

Figure 8.1 GDP per employed person in a selection of Asian countries (1995–2019, constant 2011 PPP USD)

Figure 8.1 GDP per employed person in a selection of Asian countries (1995–2019, constant 2011 PPP USD)

Source: Constructed by the authors using data from World Bank (2020).

32Thus, China experienced higher economic development in comparison to India as reflected in the two indicators. These indicators reflect a lower rate of economic development in India as compared to that in China, which can be linked to the migration trends in these countries as discussed in the next section.

Table 8.5 Youth unemployment among 15–24-year-olds in a selection of Asian countries (1995–2019, % of labour force)— International Labour Organization (ILO) modelled estimate

Country Name

1995

2000

2005

2010

2015

2018

2019

Afghanistan

6

5

5

4

3

3

3

Bangladesh

6

10

9

6

11

12

12

Bhutan

5

6

9

9

10

10

10

China

6

7

10

10

11

11

11

India

7

8

9

9

11

10

11

Iran

20

23

24

28

26

28

29

Maldives

2

4

6

9

15

17

18

Nepal

3

3

3

3

2

2

2

Pakistan

1

1

1

1

7

6

6

Sri Lanka

35

24

27

19

21

23

23

South Asia

7

7

8

8

10

10

10

World

11

12

13

12

13

13

13

Source: Authors, using World Bank (2020).

33 Table 8.5 shows the percentage of youth unemployment in the labour force in South Asian countries, including India, as well as China, South Asia as a whole and the world at five-yearly intervals from 1995 to 2015 and then for 2018 and 2019. There is an increasing trend of youth unemployment at the world level, reflecting recessionary pressures in times of economic slowdown as it fluctuated between 11 per cent in 1995 and 13 per cent in 2019. The percentage share of youth unemployment in China increased from 6 per cent in 1995 to 11 per cent in 2019. Over the same years, the share of youth unemployment in India increased from 7 per cent to 11 per cent.

Figure 8.2 Youth unemployment in a selection of Asian countries (1995–2019, % of total labour force aged 15–24)modelled ILO estimate

Figure 8.2 Youth unemployment in a selection of Asian countries (1995–2019, % of total labour force aged 15–24)—modelled ILO estimate

Source: Constructed by the authors using data from World Bank (2020).

34 Figure 8.2 drawn for just three years – 1995, 2015 and 2019 - from amongst those in Table 8.5, shows that in other South Asian countries a similar trend was observed with an unemployment rate of 7 per cent in 1995 rising to 10 per cent by 2019. The latter double-digit figures of youth unemployment reflect recessionary pressures arising from economic slowdown, particularly after 2008. Before any effective recovery measures could come into force to uplift employment, there were a number of uncertainties that continued to destabilise the employment scenario, such as the Syrian refugee problem since 2015 followed by the COVID-19 pandemic beginning in December 2019. Whereas the GCM signed in 2018 was an effort to make migration safe, orderly and regular through better governance, what followed in India was widespread public unrest triggered by the inaccurate results of the National Register of Citizens (NRC) in 2018–19, on the one hand, and the confusion around the effects of the Citizenship Amendment Act (CAA) in 2019–20 on the other. This could be seen as part of a global trend for selectivity in immigration as reflected, for example, in China’s preference to welcome the talented and the highly skilled in its recent immigration policy.

6. Migration, Economic Development and Health in the Context of COVID-19

35In times of ongoing global health crisis due to the COVID-19 pandemic and economic slowdown at the global level, the most populous countries, such as India and China, are also affected adversely with declining growth rates of GDP, which eventually affect the growth rates of the GDP per capita, and more importantly GDP per employed worker (as explained in the previous section). Figures 8.3 and 8.4 both show lower economic growth rates of GDP and GDP per capita respectively in 2020, i.e., the year of the pandemic and consequent recession. However, the same figures show an expected recovery being forecasted for 2021.

Figure 8.3 Country-wise growth rates of gross domestic product at constant prices in 2020 and 2021 (estimates in April 2020)

Figure 8.3 Country-wise growth rates of gross domestic product at constant prices in 2020 and 2021 (estimates in April 2020)

Source: Constructed by the authors using data from IMF (2020).

Figure 8.4 Country-wise growth rates of gross domestic product per capita, constant prices in 2020 and 2021 (estimates in April 2020)

Figure 8.4 Country-wise growth rates of gross domestic product per capita, constant prices in 2020 and 2021 (estimates in April 2020)

Source: Constructed by the authors using data from IMF (2020).

36The COVID-19 pandemic also affected the Current Account Balance (CAB) adversely, reflected in the negative shares of CAB in GDP in all the South Asian countries except Afghanistan in both 2020 and 2021 (Figure 8.5). However, it has been projected that the share of CAB in GDP would be positive in both years in the case of China.

Figure 8.5 Country-wise Current Account Balance (CAB) as percentage of GDP in 2020 and 2021

Figure 8.5 Country-wise Current Account Balance (CAB) as percentage of GDP in 2020 and 2021

Source: Constructed by the authors using data from IMF (2020).

37These indicators of economic growth and development are dynamically linked with migration flows and health indicators across different countries. As India and China are main sending countries of migrants to the US, in the global North, the GDP per worker and the growth rate of GDP per capita are important determinants of migration from the sending to the destination countries. Skilled migrants and students are the main categories of migrants from India and China to the US. The low growth rate of GDP per capita and the trends of GDP per employed person in India, other South Asian countries and China, as mentioned earlier, are reflective of the development gaps highlighted in dependency theory and world-systems theory vis-à-vis the US (Li, Bedford and Khadria, 2019).

Figure 8.6a Remittance inflows (% of GDP), 2018

Figure 8.6a Remittance inflows (% of GDP), 2018

Source: Constructed by the authors using data from UNDP (2020).

38The higher shares of South Asian migrants in other countries had a positive impact on the inflow of remittances measured using the receiving country’s GDP. For example, in 2018, these shares ranged between a high of 28 per cent and low of 2 per cent as follows: Nepal (28 per cent), Sri Lanka (8.4 per cent), Pakistan (6.7 per cent), Bangladesh (5.7 per cent), India (2.9 per cent), Bhutan (2.3 per cent) and Afghanistan (2.0 per cent). The other South Asian countries and China had lower shares of remittances in their GDPs (Figure 8.6a).

Figure 8.6b Migrant remittance inflows (USD millions) in India, South Asian countries and China, 200020

Figure 8.6b Migrant remittance inflows (USD millions) in India, South Asian countries and China, 2000–20

Source: Constructed by the authors using data from World Bank (2020).

39The COVID-19 pandemic and global recession have adversely affected the inflows of migrant remittances in India and China. Figure 8.6b shows the level of remittances in India declining from USD 83.3 billion in 2019 to USD 76 billion in 2020 and in China from USD 68.4 billion in 2019 to USD 59.5 billion in 2020. These declines are expected to continue to have detrimental effects on development in the global South countries in the COVID-19 period.

40The COVID-19 pandemic exacerbated the recessionary trend, leading to deep and widespread adverse effects on world economies. It dampened economic growth and development by causing large-scale loss of precious human capital, preventing the stabilisation of migration and remittances. Neither India nor the US, among the foremost sources and destinations of migration respectively, could flatten the curve on their COVID-19 cases between March and August 2020 (see Figures 8.7 and 8.8); instead, both experienced exponential growth of infections during this time. Indeed, except for Cuba, a small communist island country, and Norway, a democratic Nordic country with the highest HDI ranking, no country in the global North or global South, with or without a highly developed healthcare system, was successful in flattening the curve of COVID-19 fatalities until August 2020. While smaller countries in South Asia like Bhutan, Sri Lanka, Maldives and Nepal reported lower numbers of cases and rates of deaths, other larger South Asian countries like Iran, Pakistan and Bangladesh experienced significant losses.

Figure 8.7 Cumulative cases of COVID-19 from 24 March 2020 to 1 August 2020 in India and the United States of America

Figure 8.7 Cumulative cases of COVID-19 from 24 March 2020 to 1 August 2020 in India and the United States of America

Source: Constructed by the authors using data from WHO (2020).

Figure 8.8 Cumulative cases of COVID-19 from 24 March 2020 to 1 August 2020 in South Asian countries (except India), China, Cuba and Norway

Figure 8.8 Cumulative cases of COVID-19 from 24 March 2020 to 1 August 2020 in South Asian countries (except India), China, Cuba and Norway

Source: Constructed by the authors using data from WHO (2020).

41While the impact of COVID-19 was thus significant across countries with diverse states of development and widely varying healthcare systems, we still expected that a high-quality healthcare system as a driver of high human development indicators would turn out to be instrumental in containing the pandemic. Thus, we strongly believe that government expenditure would continue to be a significant factor to ensure good health as well as the other indicators of human development in future as they have been in the past.

Figure 8.9 Quality of health indicators in India, China, other countries and the world (various years)

Figure 8.9 Quality of health indicators in India, China, other countries and the world (various years)

Source: Constructed by the authors using data from UNDP (2020).

Note: Data not available for Maldives, China, Bhutan, High human development, East Asia and the Pacific.

42The three important health indicators related to a country’s ability to contain the pandemic are the lost health expectancy (in %), the number of physicians per 10,000 people and the number of hospital beds per 10,000 people. In the case of India, the three indicators are 14, 8 and 7 and for China 12, 18 and 42 respectively, reflecting poor health infrastructure in terms of numbers of doctors and hospital beds in India in comparison to China. In contrast to Norway and Cuba, ranked first and seventieth in the HDI respectively and having highly developed healthcare indicators of 15, 46 and 39 for Norway and 12, 82 and 52 for Cuba, these health indicators in South Asian countries are 14, 8 and 8, respectively (see Figure 8.9).

Figure 8.10 Expenditure on education and health as a percentage of military expenditure (various years)

Figure 8.10 Expenditure on education and health as a percentage of military expenditure (various years)

Source: Constructed by the authors using data from UNDP (2020).

43The poor health infrastructure indicators are also dynamically related to the health and education priorities of governments in comparison to their military expenditure. Figure 8.10 shows that expenditure on education and health as a percentage of military expenditure is lower for India at 3.1 per cent in comparison with that of the world at 6.7 per cent. The share in South Asian countries is only 3 per cent, reflecting their poor health expenditure.

44Because they are simultaneously countries of origin, transit and destination, these countries can also be referred to as overlapping ‘hubs’ and ‘hinterlands’ of migration (Khadria, 2011 and 2020). This means that a country at various points in time or in its development trajectory may be exclusively a country of origin or a destination, but at a later time may take on the characteristics of a country of transit, destination and/or origin all at the same time. India and three other South Asian countries, specifically Bangladesh, Pakistan and Sri Lanka, are characterised by large-scale migration of highly skilled individuals to developed countries and of low- to medium-skilled individuals to the Middle East, Southeast Asia and East Asia. Nepal also sends large numbers of low- to medium-skilled individuals to India and the rest of the world. Afghanistan and Pakistan have cross-border refugee migration from the former to the latter where safety of the migrants has been an issue. There is ‘dis-orderly’ migration from Nepal to India and from Bhutan to Nepal and vice-versa, whereas there has been substantial ‘irregular’ migration from Bangladesh to India. Meanwhile, Bhutan and Maldives are more preoccupied with the alternatives of a happiness index and environment index respectively, and are less bothered about international migration.

45The number of immigrants in South Asia declined from 19.54 million in 1990 to 15.28 million in 2000. It declined further to 14.05 million in 2015 and remained at a lower level, 14.08 million in 2019 (see Table 8.6). India, the most populous country in South Asia, also experienced a sharp decline from 7.59 million in 1990 to 6.41 million in 2000 to 5.24 million in 2015, and it declined further to 5.15 million in 2019. However, China has experienced an increase in immigrants from 0.38 million in 1990 to 0.51 million in 2000 to 0.98 million in 2015 to 1.03 million in 2019 crossing the million mark, reflecting higher economic progress of China in the last 30 years.

Table 8.6 Immigrants in South Asian countries, India, China and the world, 1990–2019 (in millions)

Major area, region, country or area of destination

1990

1995

2000

2005

2010

2015

2019

World

153.01

161.32

173.59

191.62

220.78

248.86

271.64

South Asia

19.54

15.34

15.28

13.72

14.31

14.05

14.08

Afghanistan

0.06

0.07

0.08

0.09

0.10

0.49

0.15

Bangladesh

0.88

0.93

0.99

1.17

1.35

1.42

2.19

Bhutan

0.02

0.03

0.03

0.04

0.05

0.05

0.05

India

7.59

6.95

6.41

5.92

5.44

5.24

5.15

Iran

4.29

2.94

2.80

2.57

2.76

2.73

2.68

Maldives

0.01

0.02

0.03

0.05

0.05

0.06

0.07

Nepal

0.43

0.69

0.72

0.68

0.58

0.51

0.49

Pakistan

6.21

3.67

4.18

3.17

3.94

3.51

3.26

Sri Lanka

0.04

0.04

0.04

0.04

0.04

0.04

0.04

China

0.38

0.44

0.51

0.68

0.85

0.98

1.03

Source: Authors, using UN (2020).

Figure 8.11 Percentage of world immigrants in South Asia and China, 1990‒2019

Figure 8.11 Percentage of world immigrants in South Asia and China, 1990‒2019

Source: Constructed by the authors using data from UN (2020).

46The share of India’s stocks of immigrants in the world shows a declining trend in the three decades, during the late twentieth and early twenty-first centuries—from 4.96 per cent in 1990 to 3.69 per cent in 2000, to 2.46 per cent in 2010, to 2.11 per cent in 2015 and 1.90 per cent in 2019. This determined the declining trend of South Asia’s share in world immigrants from 12.77 per cent in 1990, to 8.80 per cent in 2000, to 6.48 per cent in 2010, to 5.65 per cent in 2015 and 5.18 per cent in 2019. China’s share of world immigrants has remained lower at 0.25 per cent in 1990, increasing slightly to 0.38 per cent in 2019 (see Figure 8.11).

47The total number of emigrants from South Asian countries was 24.53 million in 1990, which slightly declined to 24.29 million in 2000, then sharply increased to 33.95 million in 2010. Furthermore, it increased to 38.86 million in 2015 and 42.19 million in 2019, showing an increasing trend of emigration from South Asian countries during the last 20 years (see Table 8.7 and Figure 8.12). The first and second decades of the twenty-first century witnessed sharply increasing trends of emigration. The number of emigrants has been increasing since 1990 because the economic policy of 1991, implemented to liberalise, globalise and privatise the Indian economy, caused an increase in the global mobility of Indians. The number of emigrants from India was 6.62 million in 1990, which increased to 7.93 million in 2000, increased further to 13.23 million in 2010 and 15.93 million in 2015 and finally increased to 17.51 million in 2019.

Table 8.7 Emigrants from South Asian countries, China and the world, 1990–2019 (in millions)

Table 8.7 Emigrants from South Asian countries, China and the world, 1990–2019 (in millions)

Source: Authors, using UN (2020).

48The dominance of Indian emigrants in world migration can also be analysed with the help of Figure 8.12. The percentage share of Indian emigrants in world migration increased from 4.33 per cent in 1990 to 4.57 per cent in 2000 and then from 5.99 per cent in 2010 to 6.40 per cent in 2015, reaching 6.45 per cent in 2019, reflecting a slowdown in the rate of increase in 2019. However, the share of South Asian emigrants in world migration declined in the last decade of the twentieth century from 16.03 per cent in 1990 to 13.99 per cent in 2000 but increased thereafter to 15.38 per cent in 2010 to 15.62 per cent in 2015 and remained at 15.53 per cent in 2019, which was still lower than in 1990. The share of Chinese emigrants in world migration has followed the same trend as India’s, increasing from 2.76 per cent in 1990 to 3.39 per cent in 2000, then 3.95 per cent in 2010 to 4.08 per cent in 2015, showing a slight decline thereafter in 2019.

Figure 8.12 Percentage of world emigrants from South Asia and China, 1990–2019

Figure 8.12 Percentage of world emigrants from South Asia and China, 1990–2019

Source: Constructed by the authors using data from World Bank (2020).

49Thus, the South Asian countries experienced increasing trends in the aggregate stocks of emigrants, dominated by Indian emigrants in comparison to other South Asian countries in the three decades of globalisation. China also experienced an increasing trend of stocks of emigrants in the same decades, although the rate of growth has been higher for India. The dominance of Indian emigrants has been the result of pull factors such as English language knowledge and push factors such as adverse exchange rates, lower employment opportunities, lower real wages and other working and living conditions. Since 1995 and until 2019, even among major countries of origin throughout Asia, India thus continued to be the largest contributor of emigrants in the world, with its share being far higher than the shares of other major countries of origin like China and Bangladesh. The UN data, however, do not provide the overall number of emigrants originating from Asia as a whole, which keeps the intercontinental comparison immigration-focused and therefore one-sided (Khadria and Mishra, 2021, 16).

7. Concluding Remarks and Policy Implications

50This article dwells on the GCM objectives as the benchmark for South Asian countries’ desirable SDG targets on migration, health and development in the context of the COVID-19 pandemic. The first among the 23 objectives of the GCM is for signatory member countries to ‘collect and utilize accurate and disaggregated data as a basis for evidence-based policies’ (UN Task Force on Data Integration for Disaggregated Statistics on International Migration, 2020). The greater the quality and quantity of data available, the more accurately the realities of migration and migrants they report on are reflected, which ultimately determines the quality of migration policy for each country at unilateral, bilateral and multilateral levels, and eventually their ability to achieve the objectives of the GCM. For example, the data used for this article on South Asian countries have been drawn from the United Nations and the World Bank, reflecting a whole host of dimensions of immigration and emigration, specifically the numbers of international migrant stocks by country, region, gender, age, population, etc. But there is a need to expand these data sets to more accurately capture other up-to-date dimensions of migrants and migration, such as education, skills and employment, countries of transit, country of earlier stay, year of entry in the destination country, data on family and their stay, wages, social security, health indicators, savings and investment by migrants, amounts and costs of remittances, and data on employers of migrants, etc. Such requirements of better data on education and employment are also highlighted in GCM objectives 3, 6 and 18.

51The second objective of the GCM is to ‘minimize the adverse drivers and structural factors that compel people to leave their country of origin’. Although all nine South Asian countries are in the category of developing economies belonging to the global South, and all have higher rates of emigration than of immigration, leading to a negative net migration rate over the 27 years between 1990 and 2018, they are diverse in their levels of economic growth and development and their consequences. For example, even with higher economic growth in India, the level of inequalities of income and wealth in the country has increased, leading to underdevelopment of large sections of society. These structures of inequalities and underdevelopment are dynamically and significantly driving the outflow levels of migrants, comprising both high-skilled and low-skilled workers, as elaborated in the case of India’s emigration. Other than economic factors, there are also social and political factors that drive such outmigration, like caste-, gender- and religion-based discriminations in India and other neighbouring countries (Thakur and Khadria, 2018; Akhil, 2019; Rejimon, 2018). There is, therefore, a need for the countries to work at all levels to minimise the economic, social and political differences and to ensure peace and harmony among South Asian countries in order to attain sustainable development and reduce the compulsions of migration.

52Objectives 3 to 14 of the GCM are primarily meant for the safety of migrants in the destination countries. The measures suggested in these objectives are more relevant to migration of low-skilled and unskilled workers from the nine South Asian developing countries, like domestic workers, nurses, construction workers, taxi drivers, electricians, plumbers and carpenters, for example, in Middle East countries rather than the highly skilled workers who are less vulnerable to the discrimination and risks in the destination countries due to their occupations and higher level of education. Toward this, India’s attempt to legalise the registration of employers of migrants overseas especially in the Middle East through the ‘eMigrate portal’ is a case in point (Akhil, 2019). The hurdle to its success has been the lower response from employers based overseas who consider it as an interference of foreign governments.

53GCM objective 13 provides a ray of hope to facilitate safety and security for irregular migrants prior to resorting to their detention. This applies to the irregular immigrants from Bangladesh and Rohingya refugees from Myanmar entering India since 2015 and living in fear of detection and deportation (HT, 2019). Objectives 15 to 17 are meant to reduce the chances of scapegoating migrants in destination countries by enhancing their inclusivity. Objectives 18 to 23 are aimed at increasing the link between migration and development through partnerships.

54Based on the study of economic development and health indicators and migration status in South Asian countries and China in the context of the GCM and the current pandemic situation, three prominent and significant issues have emerged. First, there are some gaps in the UN migration data. Therefore, there is a need to address these gaps to facilitate a qualitative study of migration stocks and flows that can clearly guide the migration policies for sustainable development. Secondly, compared to other South Asian countries and China, India’s stand on the GCM’s overall philosophy of reducing inequalities of wealth and income in tandem with the SDGs reflects an inconsistency in its position between emigration and immigration. India’s stand on immigrants ranges from being indifferent to being negative, whereas for emigrants it ranges from being concerned to being proactively positive. This creates a lack of clarity on India’s position with respect to the GCM objective of making migration ‘safe, orderly and regular’. The former approach promotes risks and fear among immigrants in India in contrast to the latter approach building hope and confidence among Indian emigrants in destination countries. This dichotomy acts against arriving at a triple-win situation for migrants, the receiving country and the destination country for sustainable development of all stakeholders. There is thus a need for change in the outlook and understanding on the part of India to create a win-win condition for itself as a country of destination as well as a country of origin. Simultaneously, there is a need for collective understanding on the part of the leading South Asian nation-states like India to have a wider horizon for reinforcing the positive link between migration and development by removing the above kind of inconsistencies from their migration policies. Such a collective understanding would facilitate a win-win-win condition for the three prime stakeholders, namely countries of origin, the destination countries and the migrants that supposedly are at the centre of the GCM objectives. Thirdly, collaboration, partnership and working together, trust-building between countries of origin, countries of destination, and transit states would be essential for achieving the GCM objectives. This can be achieved by pursuing the innovation of ‘Equitable Adversary Analysis’ (EAA) suggested by Khadria (2017a). According to this, the adversaries ought to exchange places, stepping into each other’s shoes so that they can see things from other countries’ perspectives, and then try to solve the problem. This would also facilitate so-called mini-multilateralism for the successful implementation of the GCM, to use the term used by the former UN Special Adviser for International Migration Peter Sutherland. In addition, this would bring similar countries of the global South together through their respective ‘objective functions’ of the GCM, incorporating their ‘wish list’, their ‘strategies to reinvent the wheel’ and their ‘innovative ideas’, as per the statements of Khadria, as the thematic expert, given in the ‘Second Informal Thematic Session’ (Khadria, 2017b).

55 There has been a declining trend in the stock of immigrants and an increasing trend in the stock of emigrants in India between 1990 and 2019 and increasing trends in the stocks of both in China. China has undertaken a positive stance for immigration in its national immigration policy toward the GCM whereas India has undertaken a stringent stance on immigration in its statement on the GCM. These trends have policy implications for suitably adapting the recommendations of the GCM for sustainable migration and development in times of recessionary uncertainties and emergencies like the COVID-19 pandemic.

56 There are two primary lessons drawn in this article: (i) there is a need for expansionary fiscal policy to revive GDP growth which has been forecasted by the IMF to be negative for India and other South Asian countries and lower for China in the post-COVID-19 period. The same is required to protect livelihoods and employment, which were adversely affected due to the crash of demand and supply caused by the nationwide lockdowns initiated by various governments; and (ii) there is an urgent need to universalise the public healthcare system, keeping in view that quality health indicators are instrumental in containing the recurrence of a COVID-19-type pandemic in the future even if the development of vaccines seems to have helped us tide over the present crisis.

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Notes

1 All country statements are available at https://www.un.org/en/conf/migration/statements.shtml (accessed on 22 May 2021).

2 See also, GCM: India calls for protecting Human Rights of migrants, libralising [sic] norms for economic migration, no to any additional barriers to migration, official tweet of the Permanent Mission of India in Geneva at the UN on its representation at the first informal thematic session on Human rights of all migrants, social inclusion, cohesion, and all forms of discrimination, including racism, xenophobia and intolerance’, 10 May 2017, https://twitter.com/indiaungeneva/status/862309983400206337?lang=en (accessed on 22 May 2021).

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List of illustrations

Title Figure 8.1 GDP per employed person in a selection of Asian countries (1995–2019, constant 2011 PPP USD)
Credits Source: Constructed by the authors using data from World Bank (2020).
URL http://journals.openedition.org/poldev/docannexe/image/4833/img-1.png
File image/png, 122k
Title Figure 8.2 Youth unemployment in a selection of Asian countries (1995–2019, % of total labour force aged 15–24)—modelled ILO estimate
Credits Source: Constructed by the authors using data from World Bank (2020).
URL http://journals.openedition.org/poldev/docannexe/image/4833/img-2.png
File image/png, 114k
Title Figure 8.3 Country-wise growth rates of gross domestic product at constant prices in 2020 and 2021 (estimates in April 2020)
Credits Source: Constructed by the authors using data from IMF (2020).
URL http://journals.openedition.org/poldev/docannexe/image/4833/img-3.png
File image/png, 89k
Title Figure 8.4 Country-wise growth rates of gross domestic product per capita, constant prices in 2020 and 2021 (estimates in April 2020)
Credits Source: Constructed by the authors using data from IMF (2020).
URL http://journals.openedition.org/poldev/docannexe/image/4833/img-4.png
File image/png, 93k
Title Figure 8.5 Country-wise Current Account Balance (CAB) as percentage of GDP in 2020 and 2021
Credits Source: Constructed by the authors using data from IMF (2020).
URL http://journals.openedition.org/poldev/docannexe/image/4833/img-5.png
File image/png, 91k
Title Figure 8.6a Remittance inflows (% of GDP), 2018
Credits Source: Constructed by the authors using data from UNDP (2020).
URL http://journals.openedition.org/poldev/docannexe/image/4833/img-6.png
File image/png, 97k
Title Figure 8.6b Migrant remittance inflows (USD millions) in India, South Asian countries and China, 2000–20
Credits Source: Constructed by the authors using data from World Bank (2020).
URL http://journals.openedition.org/poldev/docannexe/image/4833/img-7.png
File image/png, 125k
Title Figure 8.7 Cumulative cases of COVID-19 from 24 March 2020 to 1 August 2020 in India and the United States of America
Credits Source: Constructed by the authors using data from WHO (2020).
URL http://journals.openedition.org/poldev/docannexe/image/4833/img-8.png
File image/png, 61k
Title Figure 8.8 Cumulative cases of COVID-19 from 24 March 2020 to 1 August 2020 in South Asian countries (except India), China, Cuba and Norway
Credits Source: Constructed by the authors using data from WHO (2020).
URL http://journals.openedition.org/poldev/docannexe/image/4833/img-9.png
File image/png, 138k
Title Figure 8.9 Quality of health indicators in India, China, other countries and the world (various years)
Credits Source: Constructed by the authors using data from UNDP (2020).
URL http://journals.openedition.org/poldev/docannexe/image/4833/img-10.png
File image/png, 196k
Title Figure 8.10 Expenditure on education and health as a percentage of military expenditure (various years)
Credits Source: Constructed by the authors using data from UNDP (2020).
URL http://journals.openedition.org/poldev/docannexe/image/4833/img-11.png
File image/png, 151k
Title Figure 8.11 Percentage of world immigrants in South Asia and China, 1990‒2019
Credits Source: Constructed by the authors using data from UN (2020).
URL http://journals.openedition.org/poldev/docannexe/image/4833/img-12.png
File image/png, 63k
Title Table 8.7 Emigrants from South Asian countries, China and the world, 1990–2019 (in millions)
Credits Source: Authors, using UN (2020).
URL http://journals.openedition.org/poldev/docannexe/image/4833/img-13.png
File image/png, 388k
Title Figure 8.12 Percentage of world emigrants from South Asia and China, 1990–2019
Credits Source: Constructed by the authors using data from World Bank (2020).
URL http://journals.openedition.org/poldev/docannexe/image/4833/img-14.png
File image/png, 67k
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Cite this article

Electronic reference

Binod Khadria, Narender Thakur and Ratnam Mishra, Migration, Health and Development in India, South Asia and China: Perspectives in the COVID-19 EraInternational Development Policy | Revue internationale de politique de développement [Online], 14 | 2022, Online since 25 April 2022, connection on 01 July 2022. URL: http://journals.openedition.org/poldev/4833; DOI: https://doi.org/10.4000/poldev.4833

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About the authors

Binod Khadria

Binod Khadria is a Former Professor of Economics, Education and International Migration and former Chairperson of the Zakir Husain Centre for Educational Studies, School of Social Sciences, Jawaharlal Nehru University (JNU). In 2017‒18, he held the inaugural Indian Council for Cultural Relations (ICCR) Chair in Contemporary Indian Studies at Rutgers University and was a key commentator in the processes that led to the United Nations Global Compact for Migration (GCM) in 2018. He was also co-editor of the World Migration Report 2020. Presently, he is President of the Global Research Forum on Diaspora and Transnationalism (GRFDT), and co-convener of Metropolis Asia, a regional chapter of Metropolis International. His fields of expertise are international migration, education, economics, governance, law and policy.

Narender Thakur

Narender Thakur is an Associate Professor in the Department of Economics at Dr Bhim Rao Ambedkar College, University of Delhi. He completed a post-doctoral fellowship of the Indian Council for Social Science Research at the Zakir Husain Centre for Educational Studies and the Centre for Economic Studies and Planning, Jawaharlal Nehru University (JNU), New Delhi. He holds a Master of Science in Econometrics from the University of Nottingham, UK. His teaching and research areas of specialisation are political economy, macroeconomics, the economics of education and migration, and econometrics.

Ratnam Mishra

Ratnam Mishra is an Assistant Professor of Economics at the University School of Management and Entrepreneurship (USME), Delhi Technological University (DTU). She holds a PhD from Jawaharlal Nehru University (JNU), New Delhi, with specialisation in the Economics of Education. Her areas of interest are the economics of migration, entrepreneurship, vocational education and skill development, and issues in the Indian economy.

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International Development Policy is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

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