Chapter 5. How do sectoral policies affect migration in Cambodia?

Sectoral policies in key areas for development, such as the labour market, agriculture, education, and financial services and investment can still affect migration decisions. The IPPMD household and community surveys incorporated a wide set of policy programmes in the four sectors to identify some clear links between sectoral policies and migration. This chapter reports on analysis of the ways in which policy programmes in these sectors in Cambodia influence people’s decision to emigrate and to send remittances.

  

Migration is inevitably influenced by policies in the country of origin. Most countries have a set of policies which directly target migration, such as those controlling who can enter the territory and under which conditions, and those aiming to facilitate the sending and receiving of remittances. However, policies not specifically targeted at migration can also have an influence on migration. The IPPMD project in Cambodia focuses on the policies in the sectors that are key to development and explored in Chapter 4: the labour market, agriculture, education, and investment and financial services.

Chapter 4 showed that the migration impacts on these four sectors vary. The policy context for each of these sectors in turn influences migration outcomes, such as the decision to emigrate and how remittances are used. To date, the impact of sectoral policies on migration remains largely unresearched. This chapter attempts to disentangle the link between sectoral policies and migration in Cambodia by examining a wide set of policy programmes in the four sectors (Table 5.1). This chapter is organised according to the four sectors under study. It first discusses how migration outcomes are affected by labour market policies, followed by policies governing agriculture, education and investment and financial services.

Table 5.1. Sectoral policies and programmes covered in the IPPMD project

Sectors

Policies / programmes

Labour market

  • Government employment agencies

  • Vocational training programmes

  • Public employment programmes

Agriculture

  • Subsidy-type programmes

  • Agricultural training programmes

  • Insurance-based programmes

Education

  • In-kind distribution programmes

  • Cash-based programmes

  • Other types of education programmes

Investment and financial services

  • Policies related to businesses investments

  • Policies related to financial inclusion and education

Labour market policies and migration

Cambodia’s growing international migration – mainly to Thailand, Malaysia and South Korea through both formal and informal channels (Chapter 2) – indicates that the increase in the number of domestic jobs is not keeping pace with demand. Furthermore, wages at home are not comparable to those offered in the receiving countries. Both these issues have been acknowledged by the government and responsible ministries and measures have been put in place to increase job growth so as to keep pace with new entrants and to improve working conditions.

IPPMD data confirm that the search for jobs is the main driver of migration. Nearly two-thirds of current emigrants reported that they left the country to take or search for jobs abroad. About 30% of them migrated to help members of their household. Policy instruments that improve the domestic labour market may therefore reduce the incentive to migrate. Such policies can seek to enhance labour market efficiency through government employment agencies, improve the skills set of labour supply through vocational training programmes, and expand labour demand by increasing public employment programmes. To what extent are these policies present in Cambodia, and are they having an influence on migration?

Government employment agencies can reduce the incentives to migrate

The Ministry of Labour and Vocational Training (MOLVT) disseminates labour market information and attempts to match job seekers with potential employers. One of the main public institutions responsible is the National Employment Agency (NEA). The NEA offers guidance to job seekers, provides them with labour market information, and ensures that the information is widely available through mechanisms such as job fairs. Such mechanisms can have an indirect impact on households’ migration decisions. If people can find jobs in the local labour market through government employment agencies, they may choose to stay rather than move abroad to seek work.

Only about 4% of Cambodians (employed in public and private sectors) in the IPPMD sample had found jobs through government employment agencies (6% for men and 2% for women). Most people found their job by approaching potential employers directly or through friends and family (Figure 5.1). Together these two methods account for 80% of all surveyed adults with paid jobs in both the public and private sector. While the share of people who benefited from government employment agencies is low, there are certain patterns related to migration. Of those found their jobs through a government employment agency, only 6% have plans to emigrate, while a much bigger share of those who did not use these agencies plan to emigrate (17%). Individual characteristics of government employment agency beneficiaries explain this pattern. Beneficiaries are more likely than non-beneficiaries to have higher education levels and to hold jobs in the public sector, which are seen as secure occupations.

Figure 5.1. Government agencies play a minor role in job seeking among Cambodian IPPMD respondents
Methods for finding a current job in both public and private sectors
picture

Source: Authors’ own work based on IPPMD data.

 http://dx.doi.org/10.1787/888933470340

Vocational training programmes have little influence on migration

Technical and vocational education and training (TVET) is seen in Cambodia as one key tool to reinforce the labour force and address the skills mismatch. The importance of TVET in improving skills provision has recently been emphasised further in the 2015-2025 National Employment Policy. The IPPMD survey found that 5% of the labour force surveyed had participated in a vocational training programme in the five years prior to the survey. Members of rural households were more likely to have participated than urban households: 11% versus 5%. Survey findings indicate the most common training programmes to be agriculture related (60% of the 265 surveyed individuals who participated in vocational training), followed by languages (10%) and computers/IT (8%).

Vocational training programmes can affect migration in two different ways. While they might help people secure better jobs in the domestic labour market, they can also make would-be migrants more employable overseas. A comparative study of the ten IPPMD partner countries shows that in most countries the share of people planning to migrate is higher among those who had participated in a vocational training programme than among those who did not (OECD, 2017). This suggests that people participate in vocational training programmes in order to find a job abroad. Cambodia, however, is an exception to this pattern. A slightly lower share of people who took part in training plan to emigrate compared to non-participants. As seen in Chapter 4, the propensity to emigrate is higher among low-skilled occupational groups than high-skilled groups in Cambodia. In this context, vocational training programmes could be promoting upward labour mobility and reducing incentives to look for jobs abroad.

This effect is explored in a regression analysis (Box 5.1).1 It examines the links between participating in vocational training programmes and plans to emigrate while controlling for other factors, such as unemployment. The results show no evidence of links between vocational training programmes and plans to emigrate (Table 5.2). Being unemployed however, appears to push people to emigrate.

Box 5.1. The links between vocational training programmes and plans to emigrate

To investigate the link between participation in vocational training programmes and having plans to emigrate, the following probit model was used:

Prob(picture (1)

where picture represents whether individual i has a plan to emigrate in the future. It is a binary variable and takes a value of 1 if the person is planning to leave the country. picture is the variable of interest and represents a binary variable indicating if the individual participated in a vocational training programmes in the five years prior to the survey. picture stands for a set of control variables at the individual level and picture for household level controls.a picture implies regional fixed effects and picture is the randomly distributed error term. The model has been tested for two different groups: men and women. The coefficients of variables of interest are shown in Table 5.2.

Table 5.2. Vocational training programmes are not associated with plans to emigrate

Dependent variable: Individual has a plan to emigrate

Main variables of interest: Individual participated in a vocational training programme

Type of model: Probit

Sample: Labour force in working age (15-64)

Variables of interest

Sample

All

Men

Women

Individual participated in a vocational training programme

0.018

(0.023)

0.048

(0.038)

0.002

(0.029)

Household has at least one emigrant

0.001

(0.010)

-0.000

(0.016)

0.001(0.013)

Individual is unemployed

0.191

(0.044)

0.240

(0.065)

0.139

(0.061)

Number of observations

4 230

2 035

2 195

Note: Results that are statistically significant are indicated as follows: ***: 99%, **: 95%, *: 90%. Standard errors in parentheses.

a. Control variables include age, sex, education level of individuals and whether the individual is unemployed or not. At the household level, the household’s size and its squared value, the dependency ratio, its wealth indicator and its squared value are controlled. Whether the household has an emigrant or not is also controlled.

Public employment programmes may be associated with higher emigration

The National Social Protection Strategy for the Poor and Vulnerable (NSPS) is one of Cambodia’s main policies aiming to give the poor and vulnerable access to food, sanitation, water, shelter and employment (CARD, 2011). Various public employment programmes (PEPs) – e.g food-for-work and cash-for-work schemes – have been implemented to provide work opportunities for the poor and vulnerable, while also helping to improve physical infrastructure and human capital in communities. These programmes are funded by the government and its development partners.

PEPs can either increase or decrease the incentives to migrate. Programmes which improve local employment opportunities may encourage people to stay. In rural areas in particular, public works programmes for agricultural workers during the farming off-season can provide an alternative to seasonal migration. On the other hand, the increased income received from cash-for-work programmes can help people afford to migrate. Overall, the impact of PEPs on migration is likely to depend on their duration, coverage and income level.

Results of the IPPMD household survey in Cambodia indicate low participation in these cash-for-work and food-for-work programmes among employed and unemployed people (3%). They are more popular among people in rural areas (4%). People from emigrant households are slightly more likely to have benefited from these programmes than those from non-migrant households (4% vs. 3%). While further analysis cannot be made due to the small sample size, this pattern also reflects the findings of the community survey. Of the surveyed communities, 21% offered public employment programmes. The average share of households with emigrants is higher in the communities with public employment programmes (25%) than those without (21%).

Agricultural policies and migration

Agricultural policies may also influence migration and remitting decisions. The Cambodian government has been active in enacting policies to boost the agricultural sector and reduce poverty for those working in it. Given agriculture’s important share in the country’s GDP and labour force (Chapter 4), the agricultural sector is highlighted as one of six key pillars in its 2014-2018 National Strategic Development Plan (MOP, 2014). Specifically, the government’s goals for agriculture include:

  1. improving productivity, diversification and commercialisation

  2. promoting livestock farming and aquaculture

  3. enacting land reform

  4. sustainably managing natural resources.

The largest and most dominant agricultural programme is the Rice Export Policy, enacted in 2010, which aimed to promote rice as a major export commodity from an export base of near to zero in 2010 (OECD and WTO, 2011). This ambitious five-year plan specifically aimed at increasing production and post-harvest processing by attracting foreign direct investment, using better and more efficient inputs, expanding irrigation, modernising farming techniques and improving land titling. In the end, Cambodia fell short of its objective of exporting one million tons of rice by 2015, but the programme served as an important boost to the sector. For instance, the national rice milling capacity rose from 95 tons of paddy per hour in 2009 to 854 tons of paddy per hour in 2015 (Thath, 2016; World Bank, 2016a). Many of Cambodia’s programmes involve agricultural subsidies, which typically target subsistence or vulnerable farmers. For instance, the Emergency Food Assistance Project (EFAP), which began in 2008, offers productivity enhancement support by distributing subsidised quality seeds (among other things). The government has also provided subsidised rice seeds during crises, such as the massive flood that occurred in 2011 (FAO, 2014).

The survey collected data on whether households had benefitted from a variety of agricultural programmes, as well as recording each year in which they had benefited between 2010 and 2014. The question on participation in agricultural-related programmes was stated as the following: “In each of the listed years, did anyone in the household participate in the following programme?” In terms of subsidies, the questionnaire asked households whether they benefited from (1) subsidies for seeds, (2) subsidies for agricultural labour and (c) subsidies for other inputs. The results presented here relate to households that answered yes to any of the above types of subsidies.

Overall, 136 of the 1 671 agricultural households in the IPPMD sample (8%) had benefited from agricultural subsidies at least once between 2010 and 2014 – mostly for seeds. In addition, 322 households (19%) had a member participate in agricultural training. Very few households (less than 1%) had participated in an insurance-based programme. However, data on other types of insurance mechanisms were also collected. Among these, 137 households (10%) had received financial aid following crop loss, 423 arable farming households (32%) had the certificate of their agricultural land title and 31 (2%) were members of an agricultural cooperative.

Because of their pertinence to current policy in Cambodia, the analysis focuses on agricultural subsidies. It is not always clear whether agricultural subsidies have a net positive or negative effect on migration and remittance flows. By increasing the household’s income, they reduce financial constraints. In doing so, they may reduce the household’s need to seek income elsewhere, and thus reduce emigration pressure. On the other hand, they may provide enough additional income to cover the costs of emigration. Or they may provide the incentive for households to invest and channel funds towards agricultural activities, thus increasing the need for remittances, or they may make them less necessary, thereby reducing their flow. What does the IPPMD data analysis tell us about these effects of subsidies on migration?

Agricultural subsidies are linked to emigration

The descriptive statistics suggest that households benefiting from agricultural subsidies were more likely to have a member plan to emigrate within the next 12 months than non-benefitting households (18% vs. 12%, Figure 5.2).2 They were also more likely to have had a member emigrate in the past five years (49% vs. 40%, Figure 5.2) (The difference becomes 45% vs. 37% if households with emigrants that left prior to those five years are included in the sample). Regression analysis was used to determine whether these subsidies were linked to migration-related decisions in a more robust way (Box 5.2). The regression results, which control for household wealth, suggest that the subsidies may enable households to afford to send a member overseas, as the coefficient for the variable of interest (benefiting from agricultural subsidies in the past five years) is positive and statistically significant.

Figure 5.2. Agricultural subsidies are linked to emigration
Share of households benefiting from an agricultural subsidy (%), by migration outcome
picture

Note: Results that are statistically significant are indicated as follows: ***: 99%, **: 95%, *: 90%. Only members planning to emigrate within the next 12 months are considered in the furthest left panel.

Source: Authors’ own work based on IPPMD data.

 http://dx.doi.org/10.1787/888933470359

Box 5.2. The links between agricultural subsidies and migration

To explore the links between agricultural subsidies and migration, the following probit regression model was estimated:

picture (2)

where the unit of observation is the household hh and the dependent binary variable mighh takes on a value of 1 if the household has had a migration-related outcome take place and 0 otherwise. picture represents a dummy variable taking the value of 1 if the household benefited from an agricultural subsidy. picture stands for a set of household-level regressorsa and picture represents a regional fixed effect. Standard errors, picture, are robust to heteroskedasticity.

A second ordinary least squares (OLS) model was also estimated to measure whether agricultural subsidies affect the amount of remittances sent:

picture (3)

where the dependent variable is continuous and equal to the logged amount of remittances sent by former household members, but the rest of the variables remain the same.

Table 5.3. The link between subsidies and remittances is positive and significant

Dependent variable: Migration outcomes

Main variables of interest: Household benefited from an agricultural subsidy

Type of model: Probit

Sample: Agricultural households

Variables of interest

Dependent variables

(1) Household has a member planning to emigrate (equation 2)

(2) Household has a member leave within 5 years (equation 2)

(3) Household received remittances in the past 12 months (equation 2)

(4) Logged amount of remittances sent in the past 12 months (equation 3)

Benefited from an agricultural subsidy in the past 5 years

0.060

(0.035)

0.103

(0.050)

0.094

(0.046)

-0.037

(0.133)

Number of observations

1 671

1 446

1 671

598

Note: Statistical significance is indicated as follows: ***: 99%, **: 95%, *: 90%. Coefficients from probit model estimations reflect marginal effects. Standard errors are in parentheses and robust to heteroskedasticity.

a. Control variables for the model estimation presented here include the household’s size, its dependency ratio (number of children 0-15 and elderly 65+ divided by the total of other members), the male-to-female adult ratio, its wealth estimated by an indicator (Chapter 3) and whether it is in a rural or urban region.

The descriptive results also show that households receiving agricultural subsidies were more likely to receive remittances than those without subsidies (49% vs. 39%, Figure 5.2). This is also confirmed by regression analysis in Table 5.3. By providing households with the means to produce and invest in their land through, for example, quality seeds, subsidies may be providing the incentive for emigrants to send remittances home to enable households to capitalise on this investment. However, pushing the analysis deeper by controling for whether households also have an emigrant suggests that the link between agricultural subsidies and migration is driven by emigration, and not by remittances. This is not surprising given that most emigrant households also receive remittances in Cambodia. Agricultural subsidies do not, however, have any impact on the amount of remittances sent.

Because the amount and decision to remit depends highly on the host country,3 the two regression models were also applied to the subsample of households receiving remittances from former members where at least one former member is living in Thailand, a neighbouring country. The results are similar, but the link is even stronger (not shown). On the other hand, there is no such link for the households with an emigrant living in a country other than Thailand (not shown). Overall, these findings show that efforts to boost the agricultural sector may be undermined, as they also enable emigration from the sector.

Education policies and migration

The relationship between education policies and migration is multidimensional. As shown in Chapter 4, migration has both positive and negative effects on education outcomes: remittances tend to be invested in children’s schooling, while the prospect of future emigration is linked to early school dropouts. Simultaneously, education policies may have both positive and negative influences on migration decisions. Policies to improve access to quality education can decrease emigration motivated by the desire to finance children’s education. In particular, cash-based education programmes such as conditional cash transfers and scholarships could ease the pressure to earn extra income to pay for children’s schooling and thus reduce incentives to emigrate. On the other hand, they might have the opposite effect by giving the household the financial means to allow a member to emigrate. Receiving financial support for children’s education could also affect the amount and frequency of remittances sent home. This section analyses these effects for a range of education polices on migration and remittance patterns in Cambodia.

Education programmes do not appear to be linked to emigration decisions

One of the strategic goals of Cambodia’s educational policy 2014-18 is to ensure equitable access to education. Programmes such as scholarships and school meal programmes, distribution of textbooks and Take-Home Ration programmes4 aim to increase school enrolment rates, especially by poor and vulnerable children. The provision of textbooks aims to provide students with textbooks for all subjects from grades 1 to 12. Scholarships, school meal programmes and Take-Home Rations contribute to Cambodia’s educational policies as well as to the National Social Protection Strategy for the Poor and Vulnerable. The aim is to provide cash and in-kind (food) assistance to poor students to enable them to attend school. However, achieving wide coverage of scholarship and school feeding programmes remains a challenge. For example, a shortfall of funds for the Take-Home Ration programme has meant that not all poor areas are covered.

The IPPMD household survey included questions on both in-kind and cash-based programmes targeting primary and secondary schooling (Figure 5.3). Households were asked if any members had benefited from any of the specified programmes in the five years prior to the survey.

Figure 5.3. Households with emigrants are more likely to have benefited from an education programme
Share of households benefiting from an education policy (%), by having an emigrant or not
picture

Source: Authors’ own work based on IPPMD data.

 http://dx.doi.org/10.1787/888933470360

Overall, 29% of the surveyed households had benefited from an education support programme of some kind. The most common support was the distribution of school textbooks (23% of households), while 11% of households benefited from school meal programmes. Very few households benefited from scholarships, which is the only cash-based programme in the survey. Descriptive statistics also suggest that households with at least one emigrant were more likely to have benefitted from an education programme (Figure 5.3). In other words, households not benefiting from education programmes are less likely to have a member abroad. This could suggest that households use the financial support from education programmes to finance emigration. To investigate this further it is necessary to control for other factors, such as household wealth, size and number of dependent children, which might influence the decision to emigrate. This was done using a regression analysis summarised in Box 5.3.

Box 5.3. The links between education policies and migration

To estimate the impact of education support programmes on the decision to emigrate, the following probit equation was applied:

picture (4)

where picture represents household migration status, being a binary variable for the household either having at least one member planning to emigrate in the future (specification 1), having at least one emigrant who left in the five years prior to the survey (specification 2), or receiving remittances (specification 3 and 4). picture is the variable of interest and represents a binary variable indicating if the household benefited from an education policy in the five years prior to the study (results presented in the upper part of the table). It takes on a value of “1” if the household has benefited from an education policy programme and “0” otherwise. Cash-based programmes (scholarships for primary and secondary education) are also analysed separately (results presented in the lower part of the table). picture is the variable of interest and represents a binary variable indicating if the household benefited from any education policy in the five years prior to the study. It takes on a value of “1” if the household had benefited from an education support programme and “0” if not. picture are a set of observed individual and household characteristics influencing the outcome.a picture represents regional fixed effects and picture is the randomly distributed error term.

Table 5.4. The links between education programmes and migration dimensions are weak

Dependent variable: Household with emigrant/member planning to emigrate

Main variables of interest: Household benefited from education programme

Type of model: Probit

Sample: All households

Variables of interest

Dependent variable

(1) Plan to emigrate

(2) Household has an emigrant

(3) Household receives remittances

(4) Household receives remittances (controlling for migration)

Household benefited from any education programme in the past 5 years

0.016

(0.025)

0.043

(0.026)

0.053

(0.026)

0.018

(0.015)

Number of observations

1 398

1 880

1 940

1 940

Cash-based programmes

Household benefited from scholarship programme

-0.028

(0.042)

0.043

(0.026)

-0.015

(0.049)

-0.016

(0.027)

Number of observations

1 940

1 880

1 940

1 940

Note: Statistical significance is indicated as follows: ***: 99%, **: 95%, *: 90. Standard errors are in parentheses and robust to heteroskedasticity. The sample is restricted to emigrant households with a member who emigrated abroad in the past five years in order to capture the timing of the migration decision and the policy intervention. Analysis was also performed on a sub-sample of households with children in school age (6-20 years), which did not affect the results.

a. The control variables include household size, household dependency ratio (defined as the number of children and elderly in the household as a share of members in working age), the mean education level of adults in the household, the number of young children (aged 6-14) and the number of youth (aged 15-17) in the household, a binary variable for urban location, and an asset index aiming to capture household wealth.

The regression results show only a weak link between education programmes and emigration decisions. Although there is a positive relationship between benefitting from an education programme and receiving remittances (column 3), the relationship is no longer significant when including a control for having an emigrant (column 4). The results do not show any statistically significant association between benefiting from an education programme and intentions to emigrate. The weak link between education policies and emigration decisions may be explained by the nature of the programmes. The education policies in Cambodia are to a large extent distribution programmes – for example school textbooks and school meals – rather than cash-based. As discussed, cash-based programmes may have a stronger effect on migration decisions as they decrease the incentives to emigrate to finance education. However, there was no significant link between cash-based scholarship programmes and migration outcomes. This is potentially partly explained by the low coverage of such programmes (Figure 5.3) as few households benefited from scholarship programmes.

Investment and financial services policies and migration

Cambodia has undergone significant change in its investment and financial regime over the last three decades, from a regime controlled by the state to a more open policy. This transition has brought major shifts in favour of international trade, investment and private sector development, as well as in building solid economic foundations, such as macroeconomic stability, economic openness and a more favourable investment climate.

In parallel, the financial sector has seen substantial change, including structural reforms and the development of a financial service sector. Structural reforms were initiated in 1989 through a government decree establishing a two-tier banking system which separated out the function of commercial banks from the National Bank. Foreign banks have been permitted since 1991, and significant progress has been made in transforming financial institutions to create a market-based, private sector-dominated sector. The banking sector has grown rapidly in terms of the number of banks and services provided. In the same vein, microfinance institutions have expanded to fulfil the greater demand for financial services, especially in rural areas. In 2014, the number of commercial and specialised banks was 44, with 556 local offices nationwide. There were 36 microfinance institutions, with more than 100 000 village-level offices and a consequent wider geographical coverage than banks (National Bank of Cambodia, 2016).

Despite the rapidly expanding financial sector, the shares of individuals with a bank account and savings in a financial institution are still lower in Cambodia than in other Association of Southeast Asian Nations (ASEAN) countries. Only about 22% of adults (people over 15 years old) have a bank account and only 4% reported having savings in a financial institution, considerably lower than most other countries in the region (World Bank, 2016b).

Access to the formal financial sector translates into higher and more formal remittances

A favourable investment climate and inclusive financial institutions stimulate savings and investments. Access to the formal financial sector may facilitate the sending and receiving of higher volumes of remittances, and especially through formal channels. Remittances sent through formal channels are not only more secure for the sender and the receiver, they can also contribute to developing the financial sector and create multiplier effects by making resources available for financing economic activities, which in turn can encourage more productive investments.

To establish households’ access to finance, the survey asked whether any member of the household has a bank account. This found that only 6% of surveyed households had a bank account – much lower than the World Bank rate quoted above. This may in part be explained by the sampling strategy, which focused mainly on rural households (81% of the IPPMD sample) and areas with high migration rates, while the capital city – Phnom Penh – was excluded (Chapter 3).

There are other potential explanations for the low rate of bank use. Past upheavals mean that most people have little or no trust in the banking system and do not use formal financial services. The National Bank of Cambodia and other financial institutions are striving to regain people’s trust, but progress is slow. There are also culture and knowledge barriers to formal financial services; for example financial literacy is very low. When it comes to credit, many people, especially in rural areas, turn to informal sources of finance at substantially higher interest rates. In many communities non-government organisations (NGOs) act as financial co-operatives and operate saving funds. The IPPMD community survey also shows low coverage by financial service institutions (microcredit organisations, money transfer operators and banks) in the surveyed communities, particularly in rural areas (Figure 5.4). None of the sampled rural communities has a bank branch, and less than 10% have money transfer operators or microcredit organisations.

Figure 5.4. Financial service institution coverage is low in rural areas
Share of communities with financial institutions (%)
picture

Note: No rural community in the sample has a bank.

Source: Authors’ own work based on IPPMD data.

 http://dx.doi.org/10.1787/888933470378

Descriptive statistics show that households without access to a bank account are more likely to receive remittances through an informal channel (38%) than households with access to a bank account (17%) (not shown here). Households that have a bank account are also more likely to have participated in financial training in the past five years (23% compared to 4% for households without a bank account). These patterns indicate the importance of access to formal financial institutions for allowing remittances to be sent through formal channels.

Regression results presented in Box 5.4 support the hypothesis that wider access to financial institutions translates into positive effects on the mode of remittance sending and the amount of remittances sent. Having access to a bank account is positively and significantly associated with a higher amount of remittances received by the household and lowers the likelihood of receiving remittances through informal channels (Table 5.5). Thus, expanding financial inclusion could stimulate higher amounts of remittances, and channel more remittances into the formal financial sector.

Box 5.4. The links between bank accounts and remittance-sending behaviour

Regression analyses were applied to estimate the link between bank accounts on remittance patterns, using the following two models:

picture (5)

picture (6)

where the dependent variable in model (1) represents the probability of receiving informal remittances, and In model (2) the amount of remittances the household receives. picture represents a binary variable indicating if the household has a bank account, where “1” denotes a household with a bank account and “0” if not. picture are a set of observed household and individual characteristics influencing the outcome.a picture represents regional fixed effects and picture is the randomly distributed error term.

Table 5.5. Access to a bank account channels more remittances into the formal financial sector

Dependent variable: Amount of remittances received/household receives formal remittances

Main variables of interest: Household has a bank account

Type of model: Probit/OLS

Sample: All households receiving remittances

Variables of interest

Dependent variables

(1) Amount of remittances received

(2) Household receives informal remittances

Household has a bank account

1 642

(291)

-0.135

(0.066)

Number of observations

691

773

Note: Statistical significance is indicated as follows: ***: 99%, **: 95%, *: 90%. Standard errors are in parenthesis and robust to heteroskedasticity.

a. The control variables include household size, household dependency ratio (defined as the number of children and elderly in the household as a share of members in working age), the mean education level of adults in the household, the number of young children (aged 6-14), a binary variable for urban location and female household head, and an asset index aiming to capture household wealth.

Migrant households are less likely to have participated in financial literacy programmes

Financial literacy is still relatively weak in Cambodia. The country’s Financial Sector Development Strategy 2011-2020 highlights the low financial literacy of current clients of financial institutions, as well as the population in general (ADB, 2012). It has proposed a programme for promoting financial literacy. Financial constraints mean, however, that government-provided financial literacy programmes are not widespread. There are also several basic financial literacy and saving group programmes co-ordinated and financed by NGOs in the country. Their coverage is not nationwide either. The data show that the share of surveyed households benefiting from financial training programmes varied between 1-11% depending on the province. The overall participation rate among all households in the survey was less than 5% (4.6%). The share of households benefiting from this type of training was higher among households without emigrants (6%) than households with an emigrant (4%). The same pattern is, naturally, observed across households with and without remittances, with remittance-receiving households slightly less likely to have benefited from financial training.

Better knowledge about savings and investment possibilities can encourage people to channel remittances into productive investments such as real estate and businesses.

Conclusions

This chapter identifies some clear links between sectoral policies and migration in Cambodia. The investigation into the influence of labour market policies on migration decisions finds that government employment agencies tend to curb emigration by providing people with better information on the Cambodian labour market. Public employment programmes (PEPs) on the other hand, are found to be associated with higher emigration. Increased income received through PEPs may be financing emigration. Vocational training programmes however are found to have no link with migration.

Education policies did not seem to have any significant effects on household migration decisions. This result is likely in part explained by the nature of the policy programmes examined in the survey, which were mainly in-kind support and of fairly limited coverage. For education polices to affect emigration decisions they would need to be more significant in their effect, as well as more widespread.

While the use of remittances is a private household decision, public policies can help increase the probability that they are sent in the first place, as well as influence how they are sent. For example, agricultural subsidies, which are an important component of the Cambodian government’s agricultural policy, may encourage emigrants to send remittances to the benefiting household to help maximise the opportunities offered by the subsidies. In addition, access to banking services is linked to greater amounts of remittances and also to their transfer through formal channels, which can help boost their productive use.

Financial inclusion has positive effects on remittance patterns. As well as being linked to greater amounts of remittances, having a bank account reduces the transfer of remittances through informal channels. Yet, bank use is very low in Cambodia, and many current and future remittance receivers lack access to formal bank accounts. Policies to increase access to bank accounts could hence stimulate the sending of remittances and channel remittances into formal financial institutions.

Furthermore, participation in financial training programmes is very low among migrant as well as non-migrant households in the sample, despite NGO and government initiatives to implement them. There is scope to expand the access to bank accounts and financial training programmes among households in order to encourage more remittances sent through formal channels and to enable households to make productive investment.

References

ADB (2012), Cambodia’s Financial Sector Development Strategy 2011-2020, Asian Development Bank, Manila.

CARD (2011), National Social Protection Strategy for the Poor and Vulnerable, Council for Agricultural and Rural Development, Phnom Penh.

FAO (2014), “Cambodia: Country fact sheet on food and agriculture policy trends,” Food and Agriculture Policy Decision Analysis, Food and Agriculture Organization, April 2014, Rome.

MOP (2014), “2014-2018 National Strategic Development Plan,” Cambodian Ministry of Planning, Phnom Penh, http://www.mop.gov.kh/LinkClick.aspx?fileticket=XOvSGmpI4tE%3d&tabid=216&mid=705.

National Bank of Cambodia (2016), MFIs Data, database, accessed 1 March 2016, www.nbc.org.kh/english/economic_research/mfis_reports.php.

OECD (2017), Interrelations between Public Policies, Migration and Development, OECD Publishing, Paris, http://dx.doi.org/10.1787/9789264265615-en.

OECD and WTO (2011), “The expansion and diversification of Cambodia’s exports of milled rice,” Aid-for-Trade Case Story: Cambodia, Reference Number 272, OECD, Paris.

Thath, R. (2016), “Potentials and Constraints of Cambodian Rice Export,” MPRA Paper Number 71490, Royal University of Phnom Penh.

World Bank (2016a), “Leveraging the Rice Value Chain for Poverty Reduction: In Cambodia, Lao PDR, and Myanmar,” Economic and Sector Work Report No. 105285-EAP, Washington DC.

World Bank (2016b), Global Findex Database, http://datatopics.worldbank.org/financialinclusion/ (accessed 20 October, 2016).

Notes

← 1. See Chapter 3 for methodological background on the regression analyses used in this project.

← 2. Note that when it comes to individuals planning to emigrate in general (not only those planning to emigrate within the next 12 months), there is no statistically significant difference between benefitting and non-benefitting households.

← 3. There are many reasons for this. First, incomes in richer countries may be higher and therefore allow migrants to send more money home. Second, the infrastructure in richer countries may also be more developed, and allow a quicker, easier and cheaper transaction than in poorer countries. In fact, remittances from less developed countries may even be underreported since emigrants may choose to carry their remittances over by hand, or choose informal channels, often through a private courier. On the other hand, emigrants in richer countries may be participating in a formal circular migration scheme, which allows them to return home and remit part of their earnings by hand.

← 4. The Take-Home Ration Programme, supported by the World Food Program (WFP), promotes universal access to primary education and increased enrolment, retention and graduation, by providing monthly food rations of rice to children from poor families in selected grades.