MIGRATION AND REMITTANCES: MAPPING THE SENDING CHANNELS AND THE MANAGEMENT OF REMITTANCES IN CAMBODIA: THE CASE OF THREE PROVINCES
Hing Vutha, Sry Bopharath and Roth Vathana
With the support of:
Massimo Chiaregato (2050), Stefania Pirani (GVC), Margherita Romanelli (GVC)
Cambodia Development Resource Institute (CDRI) CDRI – Cambodia’s leading independent development policy research institute
Phnom Penh, May 2016
Page ii of 43 Contents
FIGURES AND TABLES ...... IV APPENDIX ...... IV ABSTRACT ...... V 1. INTRODUCTION ...... 1 2. LITERATURE REVIEW ...... 2 2.1 PUSH-PULL MODELS AND NEOCLASSICAL THEORY ...... 2 2.2 NEOCLASSICAL AND HUMAN CAPITAL THEORIES ...... 2 2.3 EMPIRICAL STUDIES ...... 2 3. RESEARCH DESIGN AND DATA COLLECTION ...... 4 3.1 DATA ...... 4 3.2 METHODOLOGY ...... 4 3.3 DEFINITION OF MIGRATION AND REMITTANCE USE ...... 6 4. KEY FINDINGS ...... 6 4.1 HOUSEHOLD PROFILE ...... 6 4.2 EXPENDITURE ...... 7 4.3 MIGRATION PROFILE ...... 8 4.3.1 Migration trends ...... 8 4.3.2 Demographic characteristics of migrant workers ...... 9 4.3.3 Education and marital status of migrant workers ...... 10 4.3.4 Motivation for migration ...... 11 4.3.5 Legal status of migrants ...... 11 4.3.6 Sources of financing for migration ...... 13 4.3.7 Occupation and earning ...... 14 4.4 REMITTANCE SENDING PATTERN ...... 15 4.4.1 Percentage, frequency and amount ...... 15 4.4.2 Amount, channels and cost of remittance transfer ...... 17 4.5 REMITTANCE USE ...... 19 4.5.1 Migration, remittance and consumption smoothing ...... 19 4.5.2 Migration, remittances and children’s education ...... 19 4.5.3 Migration, remittances and health ...... 20 4.5.4 Migration and borrowing and saving ...... 21 4.6 IMPACTS OF MIGRATION AND REMITTANCES ...... 22 4.6.1 Household assets ...... 22 4.6.2 Household perception of remittances ...... 25 4.6.3 Migration and community development ...... 28 5. SUMMARY AND CONCLUSION ...... 28 REFERENCES ...... 30
Page iii of 43 Figures and Tables Figure 1: Map of sample provinces and villages ...... 5 Figure 2: Reasons for migrating to Thailand...... 11 Figure 3: Main occupations of migrant workers ...... 14 Figure 4: Income of migrant workers by education level (USD) ...... 15 Figure 5: Percentage of migrants sending remittances home (percent) ...... 16 Figure 6: Average amount of remittance per sending (USD) ...... 17 Figure 7: Average cost per transaction (USD) ...... 18
Table 1: Educational attainment of household members by province ...... 6 Table 2: Income of household members by educational attainment ...... 7 Table 3: Household monthly income ...... 7 Table 4: Main household expenses and the number of households that had those expenses ...... 8 Table 5: Household expenditure in the last month ...... 8 Table 6: Cambodia’s migrant stock and main destination countries, 2010 and 2015 ...... 9 Table 7:Number of legal Cambodian migrant workers in Thailand, 2006-15 ...... 9 Table 8: Percentage age/sex distribution of migrants and non-migrants ...... 10 Table 9: Education, marital status and relation of migrants to household head (percent) ...... 10 Table 10: Types of migration by sex ...... 12 Table 11: Reasons for documented migration ...... 12 Table 12: Types of migration ...... 13 Table 13: Sources of financing for migration ...... 13 Table 14: Average monthly income of migrants ...... 14 Table 15: Frequency of remittance sending (percent) ...... 16 Table 16: Average remittance by migrants’ characteristics (USD) ...... 17 Table 17: Remittance channels by type of migration ...... 18 Table 18: Distribution of remittances spent on major items ...... 19 Table 19: Yearly expenditure on education ...... 20 Table 20: Channels through which remittances improve health ...... 21 Table 21: Sources of loan finance before and after migration ...... 21 Table 22: Extent to which remittances are used to repay debt ...... 21 Table 23: Remittance and savings ...... 22 Table 24: Durable assets before and after migration ...... 23 Table 25: Housing conditions before and after migration ...... 24 Table 26: Livestock holdings before and after migration ...... 24 Table 27: Land ownership before and after migration (number of plots) ...... 25 Table 28: Perception of the contribution of remittances to livelihood improvement ...... 25 Table 29: Comparison of livelihoods before and after migration by remittance quintiles ...... 26 Table 30: Socioeconomic status before and after migration ...... 26 Table 31: Perception of the importance of remittances ...... 27 Table 32: Food sufficiency before and after migration ...... 27 Table 33: Magnitude of changes in food sufficiency after migration ...... 28 Table 34: Cash contributions for community development ...... 28
Appendix Figure A 1: Steps for selected communes ...... 33 Figure A 2: Gender distribution by occupation ...... 34 Table A 2: The person migrants travelled with on their last trip to Thailand ...... 35 Table A 3: Perception of the importance of remittances (percent)...... 35 Table A 4: Channels through which remittances improve livelihoods...... 35 Table A 5: Use of loan before and after migration ...... 36 Table A 6: Transfer agents ...... 36
Page iv of 43 Acronyms and Abbreviations
CDRI Cambodia Development Resource Institute CWCC Cambodian Women’s Crisis Centre GVC Civil Volunteer Group ILO International Labour Organization KHR Khmer riel MOLVT Ministry of Labour and Vocational Training NGO nongovernmental organisation RS random start USD United States dollar
Page v of 43 Acknowledgements
This research paper would not have been possible without the kind assistance of several individuals and institutions. The technical support and constructive comments of Dr Massimo Chieregato, expert of 2050, and Ms Margherita Romanelli, GVC policy advisor and Asia desk officer both members of the Research Scientific Committee, are gratefully acknowledged. The authors would also like to thank Ms Stefania Pirani, Project Manager of MIGRA SAFE and GVC Country Representative in Cambodia for her constructive insights and communication throughout the research process. The authors are grateful to Mr Soung Sopheap, Banteay Meanchey province manager, Cambodia Women’s Crisis Centre (CWCC), for his valuable ideas on questionnaires design and data collection. We are also thankful to the staff from GVC, CWCC and Phare Ponleau Selpak (PPS) who took the time to collect household data for us. Finally, the authors and CDRI would like to express their genuine gratitude to GVC Cambodia Country Office for its generous support to this project.
Page iv of 43 Abstract This study is a component of a three-year project titled “Safe Labour Migration for Vulnerable Cambodian Migrant Workers”, known as MIGRA SAFE, coordinated by the Civil Volunteer Group (GVC) in cooperation with the Cambodia Women’s Crisis Centre (CWCC) and Phare Ponleau Selpak (PPS). The research is committed to understand the remittance behaviour of Cambodian migrant workers and the effects of remittances on the livelihoods of their families. The primary data for analysis were collected from a household survey of 500 migrant households conducted in the three provinces of Banteay Meanchy, Siem Reap and Battambang in September 2015.
In Thailand most of migration journeys are driven by job and higher income earning opportunities. Despite certain variation among migrants with different age and gender, most of them are used to remit some money back home. The most common channel for 72 percent of migrants is informal money transfer operator; followed by bank transfer using another person’s account and bank as money transfer agent.
Remittances are found to increase the likelihood of spending on basic consumption goods. Migration and remittances have positive effects on livelihoods by enabling households to meet basic consumption needs, improving housing conditions and affording a better health care. Migration is found to be associated with positive changes in borrowing and saving behaviour, with a shift from the overwhelming reliance on moneylenders to formal bank, microfinance, NGO or community loans, as well as renewed interest in savings groups. Despite positive effects on households, migration seems to have a disruptive impact on community development as the absence of productive labour reduces community participation and civic engagement.
The study, through comparative analysis targeting before and after migration periods, demonstrates the immediate positive effects of migration flows on household living conditions. On the other hand, the long-term effects of massive migration are difficult to forecast and a concern emerges regarding the social changes family members left behind are forced to face. Indeed, the development of a working education system and new forms of social and economic participation in community life appear to be key factors for the future sustainability of a new virtuous cycle set into motion when people in the sample villages started to move to other countries in search for better opportunities. Local initiatives are increasingly seen as a precondition for socioeconomic development strategies, but such initiatives seldom emerge of their own accord. Therefore, carefully designed social animation programs may be necessary to both preserve the short-term benefits of the new capital flow and transform it into something which can be useful for the development of new investments and new civil society organisations, in turn guaranteeing new employment opportunities for young people.
Page v of 43 1. Introduction A component of the three-year research program “Safe Labour Migration for Vulnerable Cambodian Migrant Workers”, or MIGRA SAFE, coordinated by the Civil Volunteer Group (GVC) in cooperation with the Cambodia Women’s Crisis Centre (CWCC) and Phare Ponleau Selpak (PPS), this project aims to achieve three main objectives: To develop community networks to share and disseminate information about safe migration and the risks of irregular migration, and to support civil society organisation networks to monitor the role of brokers and intermediaries in the recruitment process; To encourage community action aimed at preventing irregular migration and promote safe migration practices; To mainstream the prevention of irregular migration into commune and village planning to strengthen coordination between provincial and national levels.
The rationale and purpose for incorporating these research components into project activities are clearly stated in the project document. First, migration has increasingly become an important source of employment and therefore income, as well as a way of life, for many rural Cambodian households, whether they live near or far from the border. Remittances from family members working abroad contribute to poverty reduction, improved health and well-being, qualitative change in children’s education, improved housing and living conditions, all of which serve to enhance rural livelihoods. Second, a better understanding of remittance management and remittance uses can further improve livelihood opportunities for migrant households, as well as local socioeconomic conditions, and reduce the push factors behind irregular migration to Thailand. In addition, the household members left behind often have limited capacity to realise the full benefits of remittances due to their insufficient knowledge of basic banking, savings and credit services. Although the communities in which MIGRA SAFE program works (referred to as intervention communities) have a long history of migration with many households benefitting from it, the project team still lacks comprehensive understanding about the use, management and impact of remittances. This study will provide evidence-based information to support project implementation.
The study attempts to answer the following research questions: . What are the migration profiles of the study sites (mode of migration, selection of migration channel, characteristics of migrants, type of work)? . What is the most common remittance-sending behaviour (channel, amount and frequency)? . Are remittances used for consumption or investment, and in what proportion? . Do migration episodes (i.e. seasonal, short, medium and long-term) have any effect on the frequency and channel used for international remittances? If so, how? . Which are the perceived impacts of migration and remittances on household livelihoods and communities?
This study can usefully contribute to the migration literature in a number of ways. First, using survey data, it compiles an up-to-date migration profile for three provinces bordering Thailand (i.e. Battambang, Banteay Meanchey and Siem Reap). Second, the study sheds light on the previously less well understood areas of remittance behaviours, both of migrant workers (remittance sending) and the family members left behind (remittance use and management). Third, because the survey sample is representative of the total population, the evidence-based research findings can support nationwide monitoring and evaluation of MIGRA SAFE interventions.
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The rest of the paper is structured as follows. Section 2 reviews the literature, summarising migration theories and empirical findings. Section 3 describes the research design and data collection methods. Section 4 discusses key findings by looking at the migration profile, remittance behaviours and the impact of remittances on recipient communities. Section 5 concludes.
2. Literature review This section first reviews migration theory and then draws on empirical studies on the impacts of migration on migrant households and how they spend received remittances. The pros and cons of migration and remittances is a topic of much debate. Empirical studies focus on the impacts of remittances on consumption, education, agriculture, landholdings, livestock investment, health status, income inequality, moral hazard problem, household livelihood and community participation.
2.1 Push-pull models and neoclassical theory Two early studies on migration by Ravenstein (1885, 1889) viewed migration as an opportunity that could give an important contribution to economic development. Gravity models, developed in the early twentieth century by geographers, were obtained from Newton’s Laws and predict the volume of migration between places and countries based on distance, population size and economic opportunities. However, Lee (1966) argued that the migration decision is determined by ‘plus’ and ‘minus’ factors later known as push-pull models (Passaris 1989). Lee (1966) contended that environmental economic and demographic factors push people out of places of origin and pull them to destination places. Push factors are lack of economic opportunities, political repression, population growth and population density, while pull factors are demand for labour, economic opportunities, availability of land and political freedom.
2.2 Neoclassical and human capital theories Neoclassical migration theory is based on the assumption of equilibrium (balance) which is influenced by social forces. Neoclassical theorists believe that migration is a factor caused by geographical differences in labour supply and labour demand. Surplus labour in rural areas contributes to urban industrial economy. Neoclassical theory also views migration as movement from low-wage, surplus labour regions to high-wage, labour-scarce regions. Hence, since individuals are supposed to be take their decisions on a rational basis, they seek a better income. Migration is also viewed as a process which maximises the allocation of production resources. Labour capital is expected to move from areas with low demand for labour to areas with high demand for labour, and these flows result in wage convergence (Harris and Todaro 1970; Lewis 1954; Ranis and Fei 1961; Schiff 1994; Todaro and Maruszko 1987).
2.3 Empirical studies In the early literature, there is a mixed view on remittances. For instance, an ethnographic study in Mexico (Airola 2007) asserts that remittances are clearly used for consumption and increased leisure. Indeed, Kapur (2004) posited that the use of remittances for consumption can lead to a culture of dependency among the vast majority of migrant households. Other scholars take the opposite view, noting how at the macro level remittances are used for investment and ultimately lead to sustainable economic growth (Harris and Todaro 1970; Lewis 1954; Ranis and Fei 1961; Schiff 1994; Todaro and Maruszko 1987).
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There is some evidence of a causal relationship between remittances and investment and entrepreneurial activity (Arif 2009; Airola 2007). There is no consensus on the use of remittances for production which boosts local economies and non-productive investments. Empirical evidence supports the view that migration represents a benefit for household members that are left behind and that migrant households somehow use remittances for productive investments. In fact, a survey in Guatemala has found that migrant households spend remittances more at the margin on education and housing (Adams and Cuecuecha 2010). This is supported by Adams, Cuecuecha and Page’s (2009) finding demonstrating that households in Ghana spend less at the margin on food consumption. Arif’s (2009) study of migrant and non- migrant households in Pakistan reveals that large proportions of remittances are destind to buy real estate and agricultural machinery, followed by food, marriage and savings. Migrant households use remittances also for repairing or building their houses, and their propensity to spend is greater than that of non-migrant households. Arif (2009) also found that migrant households invest more than their counterparts and that they mainly invest in land— which is considered the best type of investment for rural migrants. Airola (2007) uses household income and expenditure models inin Mexico, with notable results: by controlling household characteristics such as size, location and demographics, his regression results show that remittances increase the share of spending on durable goods by 56 percent, healthcare 44 percent, and housing 17 percent, while the share of spending on food dropped 8 percent. However, the World Bank (2008) study on Ghana found no differences in the marginal spending of remittances between recipient and non-recipient households. The study concludes that migrant households treat remittances in the same way as other sources of income. Thus, accoring to these studies, we might assume there is no change in the marginal spending of remittance receiving households.
Remittances can be used for smoothing income shocks, especially for low-income households. Drawing on panel data from many different countries, Chami, Fullenkamp and Jahjah (2003) postulate that a significant proportion of remittances is spent on status-oriented consumption and argue that this is not productive for the economy. Using panel data from the Indonesian Family Life Surveys, Adams and Cuecuecha (2010) find that migrant households in Indonesia spend more on consumption than on investment goods because the majority of them are poor. Maltoni (2006) assesses the impact of remittances on local communities in Prey Veng and reports that remittances were used mainly to satisfy basic needs or repay debts. Similarly, Chan (2009) asserts that about 87 percent of total remittances is destined to daily consumption, including food, debt repayment, health care and durable household assets, with the remaining 13 percent used to buy farm inputs, set up a new business, expand an existing business, and other productive assets or businesses. A study conducted by Deelen and Vasuprasat (2010) in Cambodia, Myanmar and Laos found that in Cambodia around 32 percent of remittances are used on daily needs, 14 percent on health care and 10 percent on debt, with only 4 percent channelled into agriculture and livestock investment and 2 percent into business and income generating activities. An interesting result from Coon (2014) shows that remittances made through bank transfers are likely to be used for productive investments or for purchasing assets and less likely to be used for general consumption.
Despite these overall positive developmental outcomes, the magnitude of the impacts of remittances on households varies considerably depending on several factors, including mode of migration, family structure, management of remittances by family left behind and frequency of sending. In a large-scale study of household inclusive of 10 Latin American and Caribbean countries, Calderon et al. (2008) discovered that remittances resulted in inequality and increased social gaps. This finding supports evidence from an earlier cross-sectional household
Page 3 of 43 survey in Bluefields, Nicaragua, which revealed that remittances increased income inequality (Barham and Boucher 1998). In addition, remittance-recipient households might choose more leisure over labour, which could be disadvantageous to economic growth (Ratha 2006). Similarly, a study by Chami, Fullenkamp and Jahjah (2003) to explore the effect of remittance on economic activities also highlights the moral hazard problem. For instance, recipients may depend on remitters and treat remittances as a substitute for labour income and lower their work efforts. Their finding suggests that this moral hazard problem can affect the whole economy.
An empirical study by Namsuk (2007) conceived to examine the impact of remittances on labour supply in Jamaica, found that they resulted in higher real wages and higher unemployment. The reason unemployment persisted even though labour supply was reduced is due to the fact that the real wage rate was less than the reservation wage. Iwasawa, Inada and Fukui (2014) look at migration and its effect on the education of children left behind in Cambodia. Using data from the Cambodia Socio-Economic Surveys, they find that more children from migrant households than from non-migrant households participated in the labour market, indicating a negative effect on education decision-making for children whose parents work away.
3. Research design and data collection 3.1 Data This study draws on data collected through household survey interviewsin 25 villages across Banteay Meanchy, Siem Reap and Battambang provinces. The questionnaire was administered to the heads of 500 left behind households with at least one adult member migrating to Thailand. The questionnaire was conceived to collect information on comprehensive socioeconomic indicators such as household characteristics, members of households, income, food and non-food consumption, durable assets, land ownership, credit, migration, remittances, household perception of remittances, and migrant households’ community participation. 3.2 Methodology The sampling design for the survey is based on multi-stage stratified cluster sampling. First, the research team purposively selected three provinces subject to interventions from MIGRA SAFE; i.e. Siem Reap, Banteay Meanchey and Battambang. The second stage involved the selection of nine communes from a total of 45 targeted communes (15 for each province). Commune selection was made using a “probability proportionate to size” methodology mainly because the communes vary considerably in population size and migrant numbers. This method ensured that households in larger study sites had the same probability of being included in the sample as those in smaller sites, and vice versa (see Table A1 for more detail). Figure 1 illustrates the locations of the sample provinces and villages.
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Figure 1: Map of sample provinces and villages
Source: Author’s illustration
The last stage of sampling involved the selection of households for interview. To capture the spending behaviour of remittance-receiving households, we selected only households having at least one member working in Thailand (referred to as a migrant household). Twenty households were selected from each village using village household lists and systematic sampling. In this technique, the team leader randomly picked a bill from a wallet to acquire the last digit of the serial number on the bill. Then, that number was used to select the first household from the village household list, and the second, third and following households were selected based on the sum of the last number of the note and the interval number, acquired by dividing the households in the village by 20 (the total number of households selected in each village). The survey sampling frame consists of 500 households.
A structured questionnaire was the sole data collection instrument used for the survey. Pre- coded questions were designed to capture quantitative information. The questionnaire was drafted based on the research team’s knowledge and experience of conducting migration surveys, a comprehensive literature review, and consultation with the manager and grassroots coordinator of MIGRA SAFE. The questions focused on the following primary variables: household characteristics, expenditure and income, agricultural activities, basic migration information, remittances, and household perception of remittances.
Training and pre-testing was conducted from 19 to 21 October 2015 in Battambang province. The main purpose was to familiarise enumerators (interviewers) with the concept of the research project and with all survey questions, and to fine-tune the questionnaire. Training was divided into three components. First was an introduction to the project and contextual issues. Second was a detailed presentation and discussion of the questionnaire to familiarise enumerators with all questions. Third was a pre-test of the questionnaire in one village. After the pre-testing, the research team collected feedback on issues arising from administering the questionnaire as input for its revision. The questionnaire was finalised and translated into Khmer for use in the field. Data collection took place from 22 October to 1 November 2015.
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The field team comprised three supervisors and six enumerators from CDRI and six enumerators from the MIGRA SAFE project team.
3.3 Definition of migration and remittance use Defining migration remains controversial. Differences mainly lie in components such as distance, time, place and purpose of migration. For the purpose of this study, migration is defined as the movement of people over some distance and from one usual place of residence to another (NIS 2009). Remittance use can be classified into two groups: productive and unproductive. Investing in human capital, buying land, building or repairing houses and buying durable goods are classified as productive use, and spending remittance on consumption goods is treated as unproductive use.
4. Key Findings 4.1 Household profile The average sample household size is around six members, and approximately four people living under the same roof, meaning that on average two of the household members migrated. As shown in Table 1, disaggregation of household members’ educational attainment by province reveals that the majority have primary education, followed by no schooling. This possibly reflects poverty incidence, which in 2012 stood at 24.8 percent in Battambang, 25.5 percent in Banteay Meanchey and 28.8 percent in Siem Reap (Commune Database 2012 cited in Asian Development Bank 2014)
Table 1: Educational attainment of household members by province
Banteay Meanchey Battambang Siem Reap Education N % N % N % No schooling 271.0 29.0 138.0 29.5 220.0 39.3 Kindergarten 30.0 3.2 9.0 1.9 22.0 3.9 Primary 442.0 47.3 236.0 50.4 236.0 42.1 Lower secondary 104.0 11.1 54.0 11.5 43.0 7.7 Secondary 50.0 5.4 18.0 3.9 18.0 3.2 Post-secondary 5.0 0.5 0.0 0.0 0.0 0.0 Vocational training 0.0 0.0 1.0 0.2 1.0 0.2 Informal schooling 19.0 2.0 7.0 1.5 12.0 2.1 Don’t know 14.0 1.5 5.0 1.1 8.0 1.4 Total 935.0 100.0 468.0 100.0 560.0 100.0
Table 2 disaggregates household income by the educational attainment of household members. Higher educational attainment is clearly associated with higher earning. In our survey the income of household members with post-secondary education is double than that of those with secondary education. Vocational training resulted in zero income because people are still on the training course.
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Table 2: Income of household members by educational attainment
Education of household members Income ‘0000 riels US dollars No schooling 9.2 23.0 Kindergarten 0.0 0.0 Primary 13.5 33.7 Lower secondary 20.2 50.6 Secondary 28.9 72.2 Post-secondary 58.8 147.0 Vocational training 0.0 0.0 Informal schooling 14.1 35.2 Don’t know 19.2 48.0
Table 3 shows the different types of work and household members’ average earnings for a month. Farm jobs pay the least; for example, livestock keeper (USD41.7), farmers (USD48.6), and on-farm labourers (USD60). This suggests that farming generates the lowest income.
Table 3: Household monthly income
Main occupation ‘0000 riels US dollars Farm labourer 24.0 60.0 Small trader 45.0 112.4 Fisher 47.8 119.5 House worker 41.7 104.2 Moto taxi driver 60.0 150.0 Government officer 52.3 130.8 Taxi/tuk tuk driver 23.0 57.5 Migrant broker 48.0 120.0 Soldier 82.0 205.0 Livestock keeper 16.7 41.7 Construction worker 46.6 116.5 Hairdresser 47.5 118.8 Farmer 19.5 48.6 Factory worker 62.7 156.7 Other 57.8 144.5 Total 19.4 48.5
4.2 Expenditures Table 4 illustrates by category the main household expenses and the number of households that had those expenses. The recall period varies, from the last 7 days for food, 30 days for utilities and 6 months for the other items. All of the households bought food and 93.4 percent paid for utilities. An interesting finding is that only 10.0 percent of the households reported buying
Page 7 of 43 assets in the previous 6 months; however, in the previous month’s household expenditure, shown in Table 5, spending on assets accounts for 50.6 percent of the total. Assets such as machines or land are more expensive than general household items or durable assets. The findings reveal that about 41.0 percent of household income goes on basic consumption goods such as food, utilities, clothes, shoes, healthcare, weddings and funerals, while only 5.5 percent is spent in education.
Table 4: Main household expenses and the number of households that had those expenses
Items N % Food (last 7 days) 500 100.0 Utilities, e.g. electricity, gas, water (last 30 days) 467 93.4 Family expenses, e.g. clothes, shoes (last 6 months) 422 84.4 Health care (last 6 months) 480 96.0 Education (last 6 months) 314 62.8 Individual expenses, e.g. cigarettes, cosmetics (last 6 months) 415 83.0 Wedding/funeral (last 6 months) 492 98.4 Assets, e.g. machines, land (last 6 months) 50 10.0
Table 5: Household expenditure in the last month
Items 0000 riels US dollars % Food 29.8 74.5 21.98 Utilities 3.7 9.2 2.73 Family expenses (clothes, shoes…) 3.3 8.3 2.44 Health care 11.8 29.5 8.70 Education 7.4 18.5 5.45 Individual expenses (cigarettes, cosmetics) 2.1 5.3 1.55 Wedding/funeral 8.9 22.2 6.55 Assets (machines, land) 68.6 171.5 50.59 Total 135.6 339.0 100.00
4.3 Migration profile 4.3.1 Migration trends
In 2015, Cambodia’s working age population (15-64) was estimated being 9.96 million or 64 percent of the total population (UN 2015a). This demographic trend suggests that the country has a large number of young people entering the labour market. While the majority of them work inside the country, more and more Cambodians are emigrating to find jobs abroad, driven by considerable wage differences and limited employment opportunities in the domestic labour market. An estimated 1, 118, 878 Cambodians (both with and without official documents) emigrated for employment, around 7.2 percent of the total population (UN 2015b). Thailand is the most common destination country, attracting 68 percent of Cambodian migrants. Other destination countries in order of emigrant stock (highest to lowest) include the USA, France, Australia, South Korea Canada and Malaysia.
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Table 6: Cambodia’s migrant stock and main destination countries, 2010 and 2015
2010 2015 Total population 14 364 000 15 578 000 Stock of migrants 492 385 1 187 142 % of migrants to total population 3.4 7.6 Destination countries (%) Thailand 66 68 USA 17 14 France 6 5 Australia 3 3 South Korea 1 3 Canada 3 2 Malaysia 1 1 Source: UN (2015a), UN (2015b)
Despite the signing of a memorandum of understanding in 2003 between the two countries that has allowed Cambodian workers to legally work in Thailand since 2006, the vast majority continue to opt for irregular migration. Their migration journey is usually helped by pioneer migrants or a broker (known locally as me kchal). Also, irregular migration is less costly,1 less complicated and more flexible, especially for seasonal migrant workers. The main destination for irregular migrants is Thailand. The total number of Cambodian migrant workers (both regular and irregular) working in Thailand was estimated at 750, 109 (WB 2016). The number of Cambodian workers officially sent to work in Thailand has increased since 2006 making a total of 115.420 as of 2015, the majority of whom were men employed in manufacturing and enterprises.
Table 7: Number of legal Cambodian migrant workers in Thailand, 2006-15
Year 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 Female 894 1597 1175 1575 4920 6213 9839 4626 6338 6537 Male 3222 3249 1816 1968 6304 10624 16551 8845 9501 9626 Total 4116 4846 2991 3543 11224 16837 26390 13471 15839 16163 Source: MOVLT (2015)
4.3.2 Demographic characteristics of migrant workers
Table 8 provides age/sex distribution of migrants and non-migrants living in rural areas. Overall, migrants are younger than non-migrants with an average age of 28 versus 46 years old. The average age does not differ profoundly between male and female migrants or male and female non-migrants. Almost 65 percent of migrants are under 30 years of age. Disaggregation
1 A comparison of the costs and time involved in regular and irregular migration concludes that regular routes (to Thailand) cost migrants around USD700 and take three to six months to arrange, whereas irregular routes cost around USD100 and take just a few days (CDRI 2009).
Page 9 of 43 by age shows that about half of migrants fall in the 20-29 age group and 15 percent in the 30-34 age group. In stark contrast, less than 3 percent of migrants and 42 percent of non-migrants are in the 50 plus age group. Gender distribution among migrants and non-migrants in each age group does not vary notably. These statistics confirm researchers’ observations during fieldwork: villages with a high proportion of migrants are short of productive labour but full of children and elder people.
Table 8: Percentage age/sex distribution of migrants and non-migrants
Migrants Non-migrants Age Male Female Total Male Female Total 15-19 10.62 15.40 12.71 13.32 9.85 11.36 20-24 29.14 27.10 28.24 10.17 10.62 10.42 25-29 23.67 24.37 23.98 9.03 8.19 8.55 30-34 15.33 14.62 15.02 6.30 5.86 6.05 35-39 10.47 10.53 10.49 5.44 5.53 5.49 40-44 4.55 4.29 4.44 4.87 7.96 6.62 45-49 3.19 2.34 2.82 9.60 9.40 9.49 50+ 3.03 1.36 2.30 41.26 42.59 42.01 Total 56.23 43.77 100.00 43.57 56.43 100.00 Mean age 28.43 27.27 27.9 44.75 46.16 45.56
4.3.3 Education and marital status of migrant workers
The overall educational level of migrants is usually quite low. About half of them completed primary school and about 14 percent did not attend formal school. A moderate high proportion of migrants completed lower secondary school but the ratio is very low for higher secondary school completion. We can note a slight difference between the educational attainment of female and male migrants. The majority (56 percent) of migrants are married while around 39 percent are single. There are more single male migrants than single female migrants; the distribution is the opposite for married migrants. The distribution of migrants in terms of relationship to the household head suggests that a large proportion of migrants are sons/daughters or sons-in-law/daughters-in-law. Only 9 percent are family heads and 7.6 percent are spouses.
Table 9: Education, marital status and relation of migrants to household head (percent)
Educational attainment Migrants Male Female Total Education No schooling 14.75 14.08 14.44 Primary 49.06 50.91 49.91 Lower secondary 27.79 29.58 28.61 Higher secondary 7.89 4.83 6.48 Post-secondary 0.51 0.60 0.56 Marital status
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Single 44.43 33.60 39.44 Married 53.86 58.75 56.11 Windowed 0.69 3.02 1.76 Divorce/separated 1.03 4.63 2.69 Relation to household head Head 7.47 11.08 9.31 Spouse/partner 9.20 6.09 7.62 Son/daughter 68.68 37.67 52.89 Son-in-law/daughter-in-law 12.07 41.83 27.22 Brother/sister 1.44 1.94 1.69 Grandchild 0.57 0.83 1.00 Other relative 0.57 0.55 0.56
4.3.4 Motivation for migration
When the respondents were asked what motivates them to migrate to Thailand, the predominant reason given was employment. Lack of jobs in Cambodia was the primary factor pushing them to migrate, and opportunities to earn higher wages in Thailand the second. Less than 1 percent of them decided to migrate for the experience of living abroad. A consistent percentage anyway responded that their migration decisionwas mainly due to the fact they had to repay debts (usually to moneylenders).
Figure 2: Reasons for migrating to Thailand
For the Others experience of 3% living abroad Repay debt 0.4% 10%
Help relatives in bad health 0.3%
Lack of jobs in Higher Cambodia earnings/wages in 60% Thailand 27%
4.3.5 Legal status of migrants
Table 10 shows the distribution of migrants’ legal status by sex. Migrants are broadly classified into four categories—undocumented, temporary documented, legal and passport. Undocumented migrants are those who moved to work to Thailand without the documents required by the Thai law. Temporary documented migrants refer to those working without a legal employment contract but have a temporary employment certificate from Thailand. Legal
Page 11 of 43 migrants are those who work legally under employment contract which usually lasts two years. Passport migrants refer to those who enter Thailand on a tourist visa but then work without a legal employment contract. From the survey, 41 percent of migrants hold a temporary employment document, 28 percent have a legal employment contract and 29 percent have no proper documentation. There is a slight difference between the legal status of female and male migrant workers.
The fact that a large proportion of migrants have temporary documentation is largely the result of recent collaborative efforts by the governments of Cambodia and Thailand to legalise Cambodian migrant workers. Stringent implementation of immigration policy by the new Thai government in early 2014 led to the repatriation of approximately 250,000 Cambodian migrant workers—almost all of them were undocumented—and some voluntarily returned home because of fear of arrest. Such massive deportation and return represents a big blow for both Cambodian migrants and the Thai businesses and enterprises that rely on foreign labour. In response, the Thai government has introduced a program to provide temporary legal status to undocumented migrants already working in Thailand.
Table 10: Types of migration by sex
Male Female Total N (%) N (%) N (%) Undocumented migration 172 29.50 132 26.76 304 28.24 Temporary documented migration 239 40.99 207 41.65 446 41.30 Legal migration 164 28.13 153 30.78 317 29.35 Tourist visa and passport migration 7 1.20 3 0.60 10 0.93 Don’t know 1 0.17 1 0.20 2 0.19 Total 583 100 496 100 1079 100
Approximately 54.5 percent of undocumented migrants think that the cost of legal migration is too high, which is why they opt for informal or undocumented routes; around 30 percent do so because informal migration is cheaper and quicker than legal migration. Those who opt to migrate through legal channels do so for reasons related to job safety and full protection from abuse.
Table 11: Reasons for documented migration
N % R easons for choosing legal migration Safe from abuse, cheating, human trafficking 160 46.0 Fully protected under law 112 32.2 Benefit from labour protection 59 17.0 Benefit from social security 17 4.9 348 100 Reasons for choosing undocumented migration Know little about documented migration 97 11.77 Cheap and quick 246 29.85 Cost of legal migration too high 449 54.49 Want freedom and flexibility to change 20 2.43
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Feel safe and satisfied with undocumented migration 10 1.21 Don't know 2 0.24 Total 824 100
According to our survey, migrants are classified into five types depending on the nature of their journey: daily, seasonal, and frequent (every one or two months), medium stay (six months to two years), and long stay (two years or more). Slightly more than half of migrants stay in Thailand for more than two years, and about 39 percent stay away for six months to two years. Seasonal migrants represent just 5.38 percent of the total migrant population.
Table 12: Types of migration
N % Daily 2 0.19 Seasonal 58 5.38 Frequent 44 4.08 6 months to 2 years 422 39.11 2 plus years 553 51.25 Total 1079 100
4.3.6 Sources of financing for migration
The main sources of funding for migration are savings and loans from moneylenders. About 10 percent of migration trips are funded by money borrowed from relatives or friends and 2.6 percent by microfinance or bank loan. The distribution of migration financing by type of migrant varies notably. For example, the majority of legal migrants rely more on savings to finance their migration journey than loans. The opposite trend seems to hold for temporary documented migrants, more than half of whom obtain a loan from a moneylender to pay for migration costs. The primary source of finance for undocumented migrants is savings, followed by loan and borrowing from relatives/friends. Overall, the migration financing landscape looks somehow positive as a reasonably high proportion of migrants use savings to finance their journey.
Table 13: Sources of financing for migration
Temporary Undocumen Legal N % documented ted (%) (%) (%) Household savings 495 42.24 41.45 34.08 54.89 Borrow from relative or 118 10.07 13.49 8.30 8.83 friend Loan from moneylender 475 40.53 37.17 52.02 27.44 Loan from MFI/bank 31 2.65 4.28 1.35 3.15 Sell land/house 1 0.09 0.33 0.00 0.00 Other (specify) 52 4.44 3.29 4.26 5.68 Total N 1172 100 100 100 100
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4.3.7 Occupation and earning
Figure 3 presents the distribution of occupations among migrants. About 43 percent of them are construction workers, 16 percent are agricultural workers, 13 percent are luggage loaders and 10 percent are factory workers. Fishing boat workers and domestic workers represent just 1 percent each of the total number of migrants. Figure A2 shows gender distribution by occupation. Only male migrants work as taxi drivers and fishing boat workers, while 59 percent of construction workers are male. Most of the female migrants are domestic workers, cleaners, street sellers and restaurant/bar waiters.
Figure 3: Main occupations of migrant workers
Construction worker 43% Agricultural worker 16% Luggage loader 13% Factory worker 10% Street sale/ shop assistant 4% Agri-Industry workers 3% Food sellers 2% Cleaner 2% Domestic worker 1% Restaurant/bar waiter 1% Taxi driver 1% Fish boat worker 1% 0% 5% 10% 15% 20% 25% 30% 35% 40% 45% 50%
Table 14 presents a breakdown of migrants’ average monthly income by gender and type of work. Among female workers, food sellers make the highest income, earning USD285.7, followed by factory workers (USD282.0) and luggage loaders (USD273.4). Among male workers, taxi drivers earn the most at USD346.0, followed by street sellers/shop assistants (USD310.0) and luggage loaders (USD289.8). Overall, male workers’ average income of USD248.8 is 9.2 percent higher than that of female workers. In seven of the 11 categories, men earn more than women; for example, female street vendors/shop assistants earn 26.5 percent less than their male counterparts and luggage loaders get 6.0 percent less. However, there are instances where women earn more than men; female domestic workers earn 34.5 percent more than their male counterparts, restaurant/bartenders 18.6 percent more, and food sellers 16.1 percent more. A simple t-test shows the statistical power of the difference in earnings between men and women by type of work. The differences between the earnings of female and male construction workers and male and female food sellers are statistically significant at the 1 percent and 5 percent levels, respectively. However it is also important to notice that the differences between the earnings of males and females for other types of job are not statistically significant,.
Table 14: Average monthly income of migrants
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Type of work Thai baht US dollars Female Male Female Male Difference Agricultural worker 5,777 5,981 180.5 186.9 -6.4 Factory worker 9,025 8,762 282.0 273.8 8.2 Cleaner 6,829 7,833 213.4 244.8 -31.4 Domestic worker 6,870 4,500 214.7 140.6 74.1 Fishing boat worker 0.0 8,667 0.0 270.8 -270.8 Construction worker 6,909 7,916 215.9 247.4 -31.5*** Agro-industry worker 7,824 8,461 244.5 264.4 -19.9 Restaurant/bartender 8,400 6,840 262.5 213.8 48.7 Street vendor/ shop assistant 7,841 9,921 245.0 310.0 -65 Luggage loader 8,750 9,273 273.4 289.8 -16.4 Taxi driver 0.0 11,071 0.0 346.0 -346 Food seller 9,143 7,667 285.7 239.6 46.1** Other (specify) 5,645 7,772 176.4 242.9 -66.5** Total 7,295 7,963 228.0 248.8 -20.8*** Note: 1 dollar=32 baht; statistically significant at the ***1%, **5% and *10% levels. 푝 < 0.01, ** 푝 < 0.05, * 푝 < 0.10
Disaggregation of migrants’ income by educational attainment in Figure 4 indicates that migrants with higher educational attainment earn more than those with little or no education. For instance, migrants who complete primary education make USD236, lower secondary school USD260 and post-secondary school USD315, while those who have no schooling at all earn the least at USD197. This indicates a positive correlation between education and earnings.
Figure 4: Income of migrant workers by education level (USD)
350 315 300 260 261 236 250 197 200 150 100 50 0 No schooling Primary Lower Higher Post-secondary secondary secondary
4.4 Remittance sending pattern 4.4.1 Percentage, frequency and amount
This section examines the patterns of remittance sending by sex, age group and relationship to the household head. It also explores the channels for sending remittances, amount, cost and frequency of sending. As seen in Figure 5, the majority (89.6 percent) of migrant workers remit money back home on a constant basis. The ratio is even higher among female migrants (93.2
Page 15 of 43 percent) and highest among household heads (97.1 percent). Comparison of remittance-sending behaviour across age groups shows that young migrants are less likely to send money home than older migrants. Specifically, 87 percent of migrants aged 15-24 remit some money; this ratio is 5 percent lower than the 35-44 age group and 9 percent lower than the 44 plus age group. In sum, the overall percentage of migrants sending remittances home is quite high but varies according to sex, age group and relationship to household head.
Figure 5: Percentage of migrants sending remittances home (percent)
97% 98% 96% 96% 93% 94% 92% 92% 90% 90% 90% 89%
88% 87% 87%
86%
84%
82%
Sending remittances home once a month is the most common practice for 65 percent of migrants. The percentages are a lot lower for those sending remittance every two months (14.37 percent) and every three months (8.07 percent). Interestingly, the frequency of remittance sending varies according to the nature of migration. The longer migrants stay in the destination country, the more often they send remittances home. For example, 76.8 percent of migrants remitting once a month stay away for more than two years, about 21 percentage points higher than those who stay away for less than two years. The statistics also suggest that the majority of seasonal migrants prefer to send remittance every three months.
Table 15: Frequency of remittance sending (percent)
Frequency of migration Every 1-2 6 months to 2 years or Seasonal Remittance sending frequency months 2 years more Once a week 0.62 - - 1.48 - Once in two weeks 1.45 - 7.89 1.48 1.10 Once a month 65.25 28.26 42.11 56.05 76.80 Once in two months 14.37 17.39 21.05 17.53 11.60 Once in three months 8.07 45.65 18.42 8.15 4.24
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Once in four months 2.38 - 5.26 4.20 0.92 Once in five months 2.38 2.17 - 2.96 1.84 Once in six months 3.41 2.17 5.26 5.93 1.47 Once during a year 1.65 4.35 - 1.48 1.84 Once in two years 0.41 - - 0.74 0.18 Total 100 100% 100 100 100
4.4.2 Amount, channels and cost of remittance transfer
On average, migrants remit USD124/transaction. Figure 6 shows a negative association between the amount of remittance and the frequency of sending. For example, the average amount of remittance sent once a month is USD103, about USD30 less than the amount sent every two months and USD92 less than that sent every 3-6 months.
Figure 6: Average amount of remittance per sending (USD)
250 229 195 200
150 134 124 103 100
50
0 Average amount Once a month Once in 2 Once in 3-6 Once a year of remittance per months months sending
Disaggregation of average monthly remittance by migrant characteristics gives a picture of the remittance-sending pattern (Table 16). While there is a slight difference in the average remittances sent by male and female migrants, the variation is modest between household heads and sons/daughters (USD126 versus USD110). A similar pattern is observed among migrants with different statuses and types: legal migrants remit more than undocumented and temporary documented migrants, while seasonal migrants remit the highest amount at USD129. These findings imply that gender and length of stay is not associated with the amount of remittance. What matters is whether migrants are household heads and/or seasonal workers.
Table 16: Average remittance by migrants’ characteristics (USD)
Migrant characteristics Average monthly remittance (USD) Gender
Male 105 Female 101 Relation to household head
Head of household 126
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Son/daughter of household head 110 Migration status
Undocumented 100 Temporary documented 91 Legal 118 Type of migration
Seasonal 129 Frequent i.e. every 1-2 months 106 6 months to 2 years 97 2 years or more 106 Note: 1 dollar=32 baht
Table 17 indicates how remittances are transferred. The most common channel inclusive of 72 percent of sample migrants is th informal money transfer operator; this costs around USD2.78/transaction. The other channels are bank transfer using another person’s account (12 percent) and bank as money transfer agent, such as Western Union (6.9 percent). The former is safer but costs more at USD3/transaction while the latter is cheaper at around USD1.3/transaction but requires an access to a bank account. Despite no transfer fee, sending remittance via friends or relatives has become less common among migrant workers. Interestingly, regardless of migrant legal status, sending via informal money transfer operator is the most preferred channel. The notable difference is the transfer through bank account which is quite high among legal migrants compared to undocumented ones. The trend towards using formal money transfer seems promising and is consistent with Cambodia’s labour migration policy, which instructs private recruitment agencies to help migrant workers open foreign- currency bank accounts in Cambodia and access financial services in labour-receiving countries. The challenge, though, is how to make formal transfer services more widely available and accessible among undocumented migrant workers.
Table 17: Remittance channels by type of migration
All Type of migration Temporary N % Undocumented documented Legal Bank as money transfer agent (i.e. Western Union) 67 6.93 3.92 7.13 8.87 Informal money transfer operator 699 72.29 73.73 76.41 65.19 Friends or relatives 37 3.83 7.45 3.93 0.68 Himself/herself when visiting the house 35 3.62 8.24 1.72 2.05 Bank own account transfer 2 0.21 0.00 0.25 0.34 Bank transfer using others' account 118 12.2 0.00 9.58 21.16 Broker 6 0.62 6.67 0.74 1.02
Figure 7: Average cost per transaction (USD)
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3.5 3.01 3.02 3 2.78
2.5 2.4
2
1.41 1.5 1.28
1
0.5
0 Average Bank as money Informal money Bank own Bank transfer Broker transfer agent transfer operatoraccount transfer using others' (i.e. Western account Union)
4.5 Remittance use 4.5.1 Migration, remittance and consumption smoothing
There has been a growing evidence from case studies that consumption is the major use of remittances. In other words, migrant households greatly rely on remittances to stabilise family consumption. Similarly, evidence from our survey suggests that much basic consumption is financed by remittances without which migrant households would be vulnerable to food insecurity (Table 18). When asked about the major items remittances are spent on, 92.2 percent of respondents said consumption. Other items include health care (61 percent), debt repayment (39.8 percent) and children’s education (30 percent).
Table 18: Distribution of remittances spent on major items
N % General consumption/expenditure 461 92.2 Debt repayment 199 39.8 Health treatment 305 61.0 Children’s education and training 150 30.0 Buy household appliances 69 13.8 Marriage and other ceremonies 79 15.8 Fertiliser 81 16.2 Total 1344 100
4.5.2 Migration, remittances and children’s education
In theory, the relationship between migration and children’s education is ambiguous. On the one hand, remittances from migration can increase household income and thus investment in education; as a result, children’s education improves. On the other, migration may disrupt family life and therefore have a negative impact on children’s school performance. Migration also means losing adult working members which may force older children to drop out of school to earn income to help meet labour and/or cash shortages. In order to examine this correlation,
Page 19 of 43 we could focus on a number of indicators including education expenditure, both in absolute and relative terms, and school attendance.
The survey results show that households spend on average around KHR887,600 (USD222) a year on their children’s education. This amount is equivalent to 10.09 percent of total average household yearly expenditure. Those receiving a larger amount of remittances tend to spend more on education, both in absolute value and as a percentage share. This finding is consistent with the results shown in Table 18: migrant households use some of their remittances to invest in children’s education and training. This also confirms Roth et al. (2014) empirical estimation that migrant remittances receipt increases the share of household expenditure on education.
The study also finds positive associations between remittance receipt and children’s school attendance. For example, children aged 6-14 living in households receiving a large amount of remittances are more likely to attend school than those living in households receiving a small amount. The difference is even bigger for children aged 15-17. About 69 percent of children in households receiving the least remittance attend school, 13 percentage points lower than children in the same age group in families that receive the bigger remittances. Also, respondents perceived that remittances contribute positively to improving access to education for children left behind.
Table 19: Yearly expenditure on education
1st 2nd 3rd 4th All quintile quintile quintile quintile Education expenditure 118.57 88.76 65.32 92.27 77.15 (10, 000 riels) 2 Share of education expenditure in total household 10.09% 8.75% 10.36% 9.99% 11.24% expenditure (%) School participation of children aged 6-14 92.45% 85.48% 91.52% 94.87% 97.94%
School participation of children aged 15-17 68.91% 50.98% 67.30% 75.00% 82.35% Note: Households in the 1st quintile receive the smallest remittances and those in the 4th quintile receive the largest; 1 dollar=4000 riels
4.5.3 Migration, remittances and health
Migration can have both positive and negative effects on the health of family members left behind. They may be positive in the meaning that family members can afford medical services when needed and can improve their health status. But, if remittances are insufficient, the absence of key family members may have adverse health outcomes. A comparison of the health outcomes of different types of households would be an appropriate methodology to gain insight into the migration-health nexus. However, the survey questionnaire did not include questions about the health of family members. Instead, the survey captured household heads’ perceptions about the use and impacts of remittances on the health and well-being of their families. Their responses shown in Table 20 suggest that remittances have positive direct and indirect effects on health. Around 61 percent perceive that remittances enable their family members to afford better health care, though this finding is not surprising given that health expenditure is the second most common use of remittances.
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Table 20: Channels through which remittances improve health
N % Better consumption of basic items as food, clothes 393 78.6 Better health care 303 60.6 Better housing conditions 138 27.6 Better access to education for children 132 26.4 Better opportunity to pay off debt 101 20.2
4.5.4 Migration and borrowing and saving
In principle, the relationship between remittance, credit and savings is ambiguous. Remittances may increase access to capital and in return enable households to save more. Households may take on more loans to finance migration but then later use remittances to repay that debt. We assess this relationship by looking at a number of indicators such as loan sources and purpose, remittance use and savings group participation. In general, remittances seem to be associated with certain positive changes in borrowing and saving behaviours. Table 21 shows positive shifts in sources of loan finance after migration. People are now less likely to borrow from a moneylender, with the percentage share of such loans decreasing from 58.86 percent to 40.14 percent. At the same time there is a significant increase in the share of households taking out a bank or microfinance loan, along with smaller increases in the use of loans from an NGO or community organisation. Although other factors such as rapid expansion of financial institutions and financial products may have affected the result, the evidence is sufficient to conclude that remittances have the effect of decreasing dependency on moneylenders and increasing borrowing from formal channels.
Table 21: Sources of loan finance before and after migration
Before migration After migration Loan source N % N % Moneylender 259 58.86 175 40.14 Relative in Cambodia 70 15.91 64 14.68 Bank or microfinance 71 16.14 129 29.59 Friend/neighbour 15 3.41 21 4.82 NGO 11 2.50 18 4.13 Community organisation 3 0.68 11 2.52 Others 11 2.50 18 4.12 Total 440 100 436 100
The data in Table 22 indicates that remittances can help ease debt. Some 62 percent of migrant households allocates some of their remittances to repay debt: about 36 percent use less than one fourth of their remittances, 14 percent use about half, 8 percent more than three fourths and 4 percent use almost all of their remittance. Disaggregation by the amount of annual remittances received indicates that the larger the remittance, the greater the use of it to repay debts.
Table 22: Extent to which remittances are used to repay debt
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st All 1 quintile 2nd quintile 3rd quintile 4th quintile N % % % % % None at all 164 37.88 56.45 38.53 37.11 15.53 Some (<25%) 155 35.80 23.39 36.70 36.08 49.51 About half (around 50%) 61 14.09 14.52 11.93 16.49 13.50 A big part (>75%) 35 8.08 4.03 3.67 9.28 16.50 Almost all 18 4.16 1.61 9.17 1.03 4.85 Total 433 100 100 100 100 100 Note: Households in the 1st quintile receive the smallest remittances and those in the 4th quintile the largest.
The patterns of loan use before and after migration are quite similar (Table A5). There are no significant differences in the distribution of household loans to finance agricultural investment, health care, housing improvement, basic consumption and assets before and after migration. The only big change is showed in loans to finance the migration journey, meaning households depend more on loans to cover initial migration costs. Table 23 shows a positive correlation between remittances and savings. First, a modest but significant proportion (16.6 percent) of households belong to a savings group. Of these, 60.24 percent save less than one fourth of remittances received and just 3.61 percent save about half of it. If savings groups function to serve the best interests of their members, it is fair to say that remittances can have a positive spill-over effect on development outcomes. Table 23: Remittance and savings
N % Has anyone in your family joined a savings group? Yes 83 16.6 No 417 83.4 How much of your remittances do you save? None at all 30 36.14 Less than one fourth 50 60.24 About half 3 3.61
4.6 Impacts of migration and remittances Although no consensus has been reached yet, there is an increasing evidence that migration is an important means of livelihood generation and diversification. Poor households use migration to offset poor harvests and food insecurity, while better-off households access wage employment to diversify income sources and maximise earnings. Descriptive statistics extracted from our survey firmly support this trend. More specifically, migration has become a livelihood strategy for many rural households, improving housing conditions, increasing the quantity and quality of food consumed, serving as safety net in response to shocks, and enhancing access to education and health services. To identify the impacts, this section examines household characteristics before and after migration such as household assets, durable assets, housing condition, livestock holdings and land ownership.
4.6.1 Household assets
Three households were not available to respond to the household asset section of the questionnaire, leaving a total sample of 497 households. Table 24 presents the survey data on
Page 22 of 43 household ownership of durable assets before and after migration. Each household may have more than one of the items listed. The numbers of durable assets increase significantly after migration; for instance, the share of households with a motorbike rose from 33.8 percent to 58.56 percent, those owning a television from 40.0 percent to 69.0 percent, while the proportion of households using batteries decreased of 9.1 percentage points. Ownership of other household items has also risen such as video/VCD/DVD player or recorder (13.5 percentage points), satellite dish (10.1 percentage points), electric kitchen/gas stove (6.8 percentage points), electric fan (48.0 percentage points), dining set (35.2 percentage points) and wardrobe and cabinets (22.7 percentage points). There are also increases in households owning agricultural equipment such as hand tractors (15.1 percentage points), generators (1.2 percentage points) and water pumps (6.0 percentage points). However, some categories of farm assets have decreased dramatically, notably ploughs, harrows and ox carts.
Table 24: Durable assets before and after migration
Before After Percentage Assets N % N % change Motorbike 168 33.8 291 58.6 24.8 Bicycle 270 54.3 331 66.6 12.3 Television 199 40.0 343 69.0 29.0 Cassette player 29 5.8 17 3.4 -2.4 Radio 106 21.3 161 32.4 11.1 Sewing machine 29 5.8 31 6.2 0.4 Boat (with engine) 64 12.9 65 13.1 0.2 Remorque 3 0.6 3 0.6 0.0 Generator 3 0.6 9 1.8 1.2 Water pump 15 3.0 45 9.1 6.0 Threshing machine 1 0.2 1 0.2 0.0 Rice mill 10 2.0 7 1.4 -0.6 Oxcart (traditional or modern) 139 28.0 56 11.3 -16.7 Horse cart 4 0.8 1 0.2 -0.6 Plough and harrow 151 30.4 50 10.1 -20.3 Tractor 1 0.2 1 0.2 0.0 Hand tractor 70 14.1 145 29.2 15.1 Vehicle/car 0 0.0 7 1.4 1.4 Battery 225 45.3 180 36.2 -9.1 Telephone, Icom or cell phone 188 37.8 424 85.3 47.5 Mechanically powered saw (Trancinor) 3 0.6 6 1.2 0.6 Video/VCD/DVD player/recorder 65 13.1 132 26.6 13.5 Camera (picture/video) 1 0.2 3 0.6 0.4 Satellite dish 9 1.8 59 11.9 10.1 Refrigerator 1 0.2 4 0.8 0.6 Electric kitchen/gas stove 6 1.2 40 8.1 6.8 Washing machine 0 0.0 1 0.2 0.2
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Electric iron 4 0.8 22 4.4 3.6 Electric fan 61 12.2 304 61.2 48.9 Air conditioner 1 0.2 2 0.4 0.2 Suitcases/box for store/travelling 44 8.9 88 17.7 8.9 Sofa set 11 2.2 22 4.4 2.2 Dining set (table, chairs) 84 16.9 259 52.1 35.2 Bed set (bed, mattress ...) 116 23.3 208 41.9 18.5 Wardrobe, cabinet 88 17.7 201 40.4 22.7 Computer (desktop, laptop) 1 0.2 6 1.2 1.0
Table 25 describes the housing conditions of the sample households, before and after household member(s) migrated to Thailand. The share of remittance-receiving families living in thatch houses dropped 21.6 percentage points, while the shares of those with a tin-roofed wooden house grew 14.4 percentage points and with a tile-and-fibre-roofed wooden house 4.2 percentage points. Thus, having a household member working in Thailand means households can have a better quality home.
Table 25: Housing conditions before and after migration
Before After Percentage Types of house N % N % change Thatch house 123 24.6 15 3.0 -21.6 Wooden house roofed with tin sheets 296 59.2 368 73.6 14.4 Wooden house roofed with tiles and fibre 72 14.4 93 18.6 4.2 Concrete/brick house 1 0.2 20 4.0 3.8 Stay at parents/others house 8 1.6 3 0.6 -1.0 Other 0 0.0 1 0.2 0.2 Total 500 100 500 100 -
Table 26 shows the numbers of farm animals commonly raised by villagers and which the 500 sample households own between them. A household can have multiple types of animal and more than one of each type. The numbers of farm animals have declined since migration: the number of cows dropped by 37 percentage points, pigs 33 percentage points and chickens 6 percentage points, while the number of ducks increased by 2.4 percentage points.
Table 26: Livestock holdings before and after migration
Before After Percentage change Type of livestock N N % Cow 248 156 -37.1 Buffalo 10 4 -60.0 Pig 135 91 -32.6 Horse 2 6 200.0 Chicken 392 368 -6.1 Duck 82 89 8.5
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Fish 300 200 -33.3 Other 1 1 0.0 Total 427 412 -3.5
Each household usually has one residential plot and land for growing rice or crops. The share of residential plots increased very slightly by 0.4 percentage points to 51.7 percent (Table 27). By contrast, the proportion of wet-season rice plots dropped from 40.8 percent to 38.4 percent. Like the majority of Cambodians, the sample households in the three provinces grow rainfed rice and therefore own only wet-season rice land. Other types of land such as chamkar, land leased out, idle land and land used for growing more than one crop a year account for 7.8 percent of the total before and 9.9 percent after migration.
Table 27: Land ownership before and after migration (number of plots)
Before After Percentage Land use point change N % N % % Residential 481 51.4 492 51.7 0.4 Wet-season rice 382 40.8 365 38.4 -2.4 Chamkar 12 1.3 12 1.3 -0.0 Leased out 24 2.6 37 3.9 1.3 Left idle 16 1.7 20 2.1 0.4 More than one crop/year 20 2.1 23 2.4 0.3 Other 1 0.1 2 0.2 0.1 Total 936 100 951 100 -
4.6.2 Household perception of remittances
In this section we focus on households’ perceptions of remittance use and how remittances may affect their livelihoods. Overall, family members left behind perceive that remittances make an important contribution to livelihood improvements (Table 28). Just 4.42 percent of respondents said remittances do not contribute to better living standards, but the vast majority reported otherwise: about 34 percent perceived remittances as “extremely helpful” and 43.89 percent “moderately helpful”. Perceptions vary according to household characteristics. Families with male and female migrants share similar perceptions. However, perceptions differ widely between households with a migrant family head and those with another migrant adult. The former are more likely to rely on remittances for their day-to-day living than the latter. Comparison of recipient and non-recipient households clearly shows the role of remittances in livelihood improvement. The channels through which remittances help raise living standards are better basic consumption, better access to health care, better housing conditions, better access to education and better ability to repay debt (for further detail see Table A4).
Table 28: Perception of the contribution of remittances to livelihood improvement
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HHs HHs HHs HHs with Non- with with with non- Recipient All recipient male female migrant migrant HHs HHs migrant migrant HH head HH head N % % % % % % % Extremely helpful 171 34.34 39.71 32.90 61.72 34.79 36.79 50.00 Moderately 44.69 0.00 helpful 219 43.98 41.99 47.83 26.56 45.91 Slightly helpful 86 17.27 14.68 15.80 9.38 15.63 15.06 30.00 Not helpful at all 22 4.42 3.62 3.48 2.34 3.66 3.46 20.00 Note: 1 percent of sample households did not receive remittances.
To verify the survey results, respondents were asked to compare their living standards before and after migration (Table 29). Similarly to previous indicators, their responses firmly suggest a positive association between remittances and livelihood improvements. Specifically, more than half of the migrant households asserted that their standard of living is better now than it was before migration. When disaggregated by the annual amount of remittances received, it is evident that remittances helped to enhance livelihoods. In other words, households receiving larger remittances benefit from the largest livelihood improvements.
Table 29: Comparison of livelihoods before and after migration by remittance quintiles
All 1st quintile 2nd quintile 3rd quintile 4th quintile N % % % % % Better than before 279 55.8 40.6 53.3 60.3 73.6 The same 162 32.4 42.8 32.5 31.9 20.7 Worse than before 59 11.8 16.8 14.2 7.8 5.8 Total 500 100 100 100 100 100 Note: Households in the 1st quintile receive the smallest remittances and those in the 4th quintile the largest
Migration has enabled many families to move out of poverty. Table 30 describes respondents’ socioeconomic status before and after migration. There are significant declines in the proportions of “very poor” and “poor” migrant households and concomitant increases in the proportions of those in the “average” and “rich” categories. This implies that migration and remittances have a poverty-reducing effect. Although this finding is based on perceptions and recall, it is consistent with several previous CDRI studies including Tong (2012) and Roth et al. (2014).
Table 30: Socioeconomic status before and after migration
Before migration After migration N % N % Very poor 81 16.2 24 4.8 Poor 195 39.0 120 24.0 Average 220 44.0 298 59.6 Rich 4 0.8 56 11.2
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Very rich 0 0.0 2 0.4 Total 500 100 500 100
The data presented in Table 31 provide similar evidence. Remittances are “very important” for supporting the consumption needs of about 65 percent of respondents and “moderately important” for 32 percent. Without remittances, 80 percent of migrant households would not have enough income to cover their consumption needs, and 83 percent of households need remittances to support basic consumption all year round. These results point to migrant households’ heavy reliance on remittances. The degree of reliance among households varies slightly by migrant gender but significantly depending on whether the migrant is the family head or other adult family member (Table A3). Households with migrant family heads rely more on remittances, though the opposite is true for seasonal migration.
Table 31: Perception of the importance of remittances
N % Perception of the importance of remittances Very important 326 65.33 Moderately important 160 32.06 Not important 13 2.61 When remittances are helpful All year round 397 83.09 During wet season 60 12.07 During dry season 29 4.84 Consumption sufficiency without remittance Enough 97 19.40 Not enough 403 80.60
The indicator that compares food sufficiency before and after migration also proves a similar association between remittance and consumption smoothing. As seen in Table 32, food security improves notably after migration. The proportion of households reporting “not enough at all” decreased sharply from 34.6 percent before migration to 7.6 percent after migration, and those reporting “enough” increased from 26 percent to 57 percent.
Table 32: Food sufficiency before and after migration
Before migration After migration N % N % Not enough at all 173 34.6 38 7.6 Not quite enough 193 38.6 151 30.2 Enough 130 26.0 285 57.0 More than enough 4 0.8 26 5.2
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Table 33: Magnitude of changes in food sufficiency after migration
N % From not enough at all --> slightly not enough 73 15.37 From not enough at all --> enough 68 14.32 From not enough at all --> more than enough 5 1.05 From not quite enough --> enough 116 24.42 From not quite enough --> more than enough 4 0.84 Enough --> more than enough 14 2.95 No change (not enough) 92 19.37 No change (enough) 103 21.68
4.6.3 Migration and community development
The relationship between migration and community development is not straightforward. Although migration can contribute to community development through improved living standards, the absence of productive labour may lead to lower participation in community programs. When asked if they used any of their remittances to help others in the community, 26.4 percent of respondents said that they did but only gave small amounts (Table 34). When disaggregated by the amount of remittances received, statistics do not show a clear pattern of the relationship between remittances and contribution to community development. Although migration has contributed little to community development, the survey findings prove that migration and remittances help enhance the livelihoods of migrant households.
Table 34: Cash contributions for community development
All 1st quintile 2nd quintile 3rd quintile 4th quintile N % % % % % None at all 363 72.6 79.17 71.32 73.64 64.94 A little 132 26.4 19.44 27.13 25.45 35.04 A moderate sum 5 1.0 1.39 1.55 0.91 0.00 Note: Households in the 1st quintile receive the smallest remittances and those in the 4th quintile the largest.
5. Summary and conclusion
The empirical analysis of migration, remittance behaviour and impact allows us to draw the following summaries and conclusions:
. The survey shows similar results on migrant characteristics. First, migrants are younger than non-migrants living in rural areas. This means migration is the most common livelihood option among adults while elders are more likely to stay and take care the family. Second, lucrative job opportunities in Thailand are the main reason behind migration to Thailand. Third, majority of migrants have low education and thus work in unskilled jobs as construction workers, agricultural workers, bar/restaurant waiters and domestic workers. Yet, they can earn a lot more than working in Cambodia. Fourth, migrants prefer undocumented migration since the cost is lower than documented migration.
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. The results also suggest that remittance sending behaviour is somehow similar to many conducted studies as i.e. MOP (2012). Majority of them do remit some money back home. The ratio is higher among female migrants and highest among household heads. The most common channel is informal money transfer operator; this costs around USD2.78/transaction.
. Finally, the analysis found positive links between remittances and various household outcomes. First, remittances play a critical role in supporting daily consumption and improve the food sufficiency of family members left behind. Another Second, migration also has positive effects on livelihoods. It have the potential to improve well-being, stimulate new/diversified livelihood strategies, and serve as a safety net and income insurance for family left behind. The study finds significant shifts towards higher socioeconomic status: the proportions of migrant households classified as “very poor” and “poor” declined, matched by concomitant increases in those classified as “average” and “rich”. This confirms that migration has poverty-reducing effects.
. Third, remittances increase household spending on children’s education. There is also a positive association between remittances and school attendance. Children living in households getting a large amount of remittances are more likely to attend school than those living in households receiving a small amount. Further, migrants perceive that remittances enable them to provide a better education for their children left behind
. Fourth, health expenditure is the second most common use of remittances. As a result, migrant families left behind can afford better health care and thus improve their general well-being/health status.
. Fifth, migration seems to be associated with certain positive changes in borrowing and saving behaviour. Migrant households have reduced reliance on moneylenders and instead turned to formal bank, microfinance, NGO or community loans. Also, the modest but significant proportion of households joining a savings group signifies a new or renewed interest in savings.
. Finally, the impact of migration on community as a whole is usually modest. Migration can contribute to community development through improved living standards, but the absence of productive labour decreases active participation in community building programs.
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Appendix
The steps for selecting the sample communes are as follows:
. List all the targeted communes (Column A) and the total number of international migrants (Column B) . Calculate the cumulative number of international migrants (Column C). The last number in this column is the total number of migrants. . Determine the number of communes to be selected for survey (9 out of 45). . Calculate the sampling interval (SI) by dividing the cumulative population by the number of communes selected for survey. . Choose a number between 1 and the SI at random; this is the random start (RS). Calculate the following series, RS, RS + SI, RS + 2SI, RS + 3SI … RS + 9SI. . Each of these nine numbers corresponds to a specific site on the list of communes. The selected communes are those for which Column C, the cumulative number of migrants, contains the numbers in the series we calculated.
The next stage involves the selection of villages from the sample communes. The sampling of villages is based on probability proportionate to size; the steps are as follows:
. List all villages from selected communes in Column A, and the total number of international migrants in those villages in Column B. The sampling frame for the nine sample communes consists of 81 villages. . Calculate the cumulative number of international migrants (Column C). The last number in this column is the total number of international migrants. . Determine the number of villages to be selected for survey (25 out of 81) . Calculate the sampling interval (SI) by dividing the cumulative population by the number of villages selected for the survey . Choose a number between one and the SI at random; this is the random start (RS). Calculate the following series: RS, RS + SI, RS + 2SI, RS + 3SI … RS + 25SI, . Each of these 25 numbers corresponds to a site on the list of villages. The selected villages are those for which Column C, the cumulative number of migrants, contains the numbers in the series we calculated.
This sampling procedure allows us to randomly select 25 sample villages in which 11 are from Banteay Meanchey province, six from Battambang province and eight from Siem Reap province.
Figure A 1: Steps for selected communes
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Table A 1: List of sample villages
No. Village ID Province District Commune Village 1 01040502 Banteay Meanchey Preah Netr Preah Preah Netr Preah Cheung Voat 2 01040503 Banteay Meanchey Preah Netr Preah Preah Netr Preah Kandal 3 01040505 Banteay Meanchey Preah Netr Preah Preah Netr Preah Paoy Samraong 4 01040506 Banteay Meanchey Preah Netr Preah Preah Netr Preah Paoy Pring 5 01040509 Banteay Meanchey Preah Netr Preah Preah Netr Preah Sreh Lech 6 01040511 Banteay Meanchey Preah Netr Preah Preah Netr Preah Sramaoch 7 01040513 Banteay Meanchey Preah NetrPreah Preah NetrPreah Doun Chaeng 8 01050601 Banteay Meanchey Ou Chrov Souphi Souphi Cheung 9 01050603 Banteay Meanchey OuChrov Souphi Souphi Tboung 10 01050606 Banteay Meanchey Ou Chrov Souphi Boeung Knhnom 11 01030403 Banteay Meanchey Phnum Srok Spean Sraeng Spean 12 17010703 Siem Reap Angkor Chum Ta Saom Mkak 13 17010707 Siem Reap Angkor Chum Ta Saom Pram Damloeng 14 17010711 Siem Reap Angkor Chum Ta Saom Ta Saom 15 17010713 Siem Reap Angkor Chum Ta Saom Svay Chum 16 17060704 Siem Reap Kralanh Saen Sokh Kouk Phngeas 17 17060707 Siem Reap Kralanh Saen Sokh Angkaol 18 17060713 Siem Reap Kralanh Saen Sokh Treas 19 17140401 Siem Reap Varin Svay Sa Ou 20 02040806 Battambang Bavel Boeung Pram Oureusey 21 02060904 Battambang Moung Ruessei Robas Mongkol Koun K'aekMuoy 22 02060910 Battambang Moung Ruessei Robas Mongkol Anlong Tamok 23 02020902 Battambang Thma Koul Bansay Traeng Ta Kay 24 02020904 Battambang Thma Koul Bansay Traeng Prey Leav 25 02020907 Battambang Thma Koul Bansay Traeng Spean
Figure A 2: Gender distribution by occupation
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Food sellers 36% 64% Taxi driver 100% 0% Luggage loader 57% 43% Street sale/ shop assistant 47% 53% Restaurant/bar waiter 31% 69% Agri-Industry workers 47% 53% Construction worker 59% 41% Fish boat worker 100% Domestic worker 29% 71% Cleaner 26% 74% Factory worker 46% 54% Agricultural worker 50% 50% 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
Male Female
Table A 2: The person migrants travelled with on their last trip to Thailand
N % Relative(s) 343 29.27 Friend 49 4.18 Broker 7 0.60 Recruitment agency 35 2.99 Alone 160 13.65 Broker 578 49.32 Total 1172 100
Table A 3: Perception of the importance of remittances
HHs with HHs with HHs with HHs with migrant HHs with HHs with male female head not head seasonal regular migrant migrant migrating of family migrant migrant (%) (%) (%) (%) (%) (%) Very important 64.98 66.52 82.03 64.25 54.25 66.78 Moderately 33.06 31.01 17.97 33.44 43.14 31.10 important Not important 1.96 2.46 0.00 2.35 2.61 2.13
Table A 4: Channels through which remittances improve livelihoods
N % Better consumption of basic items e.g. food, clothes 393 78.6 Better access to healthcare services 303 60.6 Better dwelling conditions 138 27.6 Better access to education for children 132 26.4 Higher possibility of paying off debt 101 20.2
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Higher possibility of buying durable goods 25 5.0 Better possibility of investing in own business 23 4.6 Higher possibility of saving/buying valuables 20 4.0 More free time for self and family 10 2.0 Other 88 17.6 Total 500 -
Table A 5: Use of loan before and after migration
Before migration After migration
N % N % Agricultural activities 76 17.27 94 21.56 Non-agricultural activities 9 2.05 11 2.52 Household consumption needs 44 10.00 50 11.47 Illness, injury, accident 54 12.27 60 13.76 Rituals (marriage ceremony, funeral etc 16 3.64 21 4.82 Purchase/improvement of dwelling 41 9.32 86 19.72 Purchase of consumer durables 9 2.05 22 5.05 Servicing and existing debts 12 2.73 38 8.72 Finance migration journey 171 38.86 43 9.86 Others (Specify) 8 1.82 11 2.52
Table A 6: Transfer agents
N % Bank as paying agent of money transfer 70 6.78 Informal agent 748 72.41 Friend or relative 37 3.58 Migrants themselves when visiting home 35 3.39 Bank own account transfer 2 0.19 Bank transfer 132 12.78 Broker transfer 6 0.58 Other 3 0.29 Total 1033 100
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