Chapter 3. Understanding the methodological framework used in Cambodia
In order to provide an empirical foundation to the analysis of the links between migration and policy, the Interrelations between Public Policies, Migration and Development (IPPMD) project used three evidence-gathering tools: household survey, community survey, and qualitative interviews with representatives of public, international and local organisations. This chapter explains how the sampling for the surveys was designed, as well as the statistical approaches used in the chapters that follow to analyse the links between migration and key policy sectors. The chapter includes a brief overview of the survey data, including differences across regions and between migrant and non-migrant households. It outlines some of the gender differences that emerged among migrants, and the reasons for leaving and returning.
The Interrelations between Public Policies, Migration and Development (IPPMD) project is empirically based. In order to provide evidence-based analysis on the interrelationship between migration and the various sectors under study, the project carried out data collection in Cambodia from April to May 2014. The fieldwork introduced three primary tools developed by the OECD Development Centre: a household survey, a community survey and stakeholder interviews. The generic version of each tool was tailored to the Cambodian context in collaboration with the Cambodian Development Resource Institute (CDRI), which conducted the fieldwork.
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The household survey involved a questionnaire administered to 2 000 households. The household questionnaire included policy questions to gather information on whether households and individuals benefited from certain policies which may affect their migration patterns and return on investment made through migration. It also gathered information about individual and household characteristics related to various key development sectors such as labour market, agriculture, education, and investment and financial services. Although the survey was not nationally representative, the sample provinces represent top migrant sending provinces (see below), and provided accurate and reliable data on migration. It collected information from both migrant and non-migrant households, providing a comparative basis for analysis.
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The community survey was designed to complement the household survey. It was carried out in each of the 100 villages where the household survey took place. Respondents were district and locality leaders. The questionnaire documented community-level demographic, social and economic information, policies and development programmes.
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The 28 stakeholder interviews were conducted to collect qualitative information on trends, policies, opinions and predictions related to the various aspects of migration in the country. The information enriched and helped interpret the quantitative household and community surveys by including additional details about the specific context in Cambodia. The interviews were conducted with representatives of governmental ministries, public institutions, non-governmental organisations, religious organisations, trade unions, private sector institutions and international organisations.
This chapter describes the sampling process for collecting both quantitative and qualitative data. It also illustrates the analytical approaches used to explore the interrelations between the various dimensions of migration and sectoral public policies. Finally, it presents basic descriptive statistics of the data collected.
How were the communities and households sampled?
A multi-stage stratified cluster sampling was used to select the households and communities to be interviewed. In the first stage, eight provinces were chosen for their high rate of international emigration using the Cambodia Rural Urban Migration Project (CRUMP) database (MoP, 2012). These provinces were Banteay Meanchey, Battambang, Koh Kong, Kompong Cham, Kompong Thom, Oddar Meanchey, Prey Veng and Siem Reap. Migrants from these provinces represent about 75% of all Cambodia’s international emigrants. The provinces of Banteay Meanchey, Battambang and Oddar Meanchey in the north west, and Koh Kong in the south west, share a border with Thailand, the largest migrant-receiving country in the region (Figure 3.1). The rate of emigration for these provinces, calculated as the total number of international emigrants over the total population, is 21%, 19%, 5% and 8%, respectively. The province of Siem Reap is in the north region of Cambodia, near the Thai border. The emigration rate for Siem Reap is 13%. Two other selected provinces, Kompong Thom and Kompong Cham, are in the central region and both have an emigration rate of 7%. Most of the emigrants from Kompong Thom are residing in Thailand; while for the province of Kompong Cham the majority of migrants went to Malaysia. The last province, Prey Veng, is in the southeast region and has a migration rate of 5%.
The second stage involved selecting a total of 100 villages – from both rural and urban areas – across the sampled provinces. Following the National Institute of Statistics definition, urban areas are districts containing provincial headquarter towns, while all the remaining areas are rural. Among villages from which migrants left to work abroad, 81% were rural and 19% were urban villages (NIS, 2009). The same rural/urban split was chosen for the sampling of the IPPMD project, resulting in a sample of 81 rural villages, and 19 villages in an urban setting.
Rural villages were selected from a list of villages included in the CRUMP survey. This survey included a random sample of 151 villages from the 8 selected provinces. From this list, 81 villages were selected based on systematic sampling with a probability proportionate to the number of migrants from the village. This method ensures that all migrants have the same probability of being included, regardless of whether they live in a village with many or few migrants. Urban villages were deliberately sampled because the prevalence of migration in urban villages is unlikely to be high enough for a random sample to capture a sufficiently large number of migrant households. Instead, a list of urban villages was derived from the Cambodian Socio-Economic Survey (CSES) 2009 (NIS, 2009) based on migration rates, from which villages with a high proportion of migration were selected. Figure 3.1 marks the location of the enumeration areas, including rural and urban villages. A summary of the sample strategy can be found in Table 3.A1.1 in Annex 3.A1.
Household survey
The last stage of the sampling design involved selecting households. First, for each village the field team created the sampling frame: two separate lists of households, one for households with, and one for households without migrants (see Box 3.1 for key definitions). The research team prepared these lists through communication with village chiefs. Four villages were replaced, two because the village chief could not be reached or was not willing to participate, and two because the number of households with migrants was too low.
A household consists of one or several persons, irrespective of whether they are related or not, who normally live together in the same housing unit or group of housing units and have common cooking and eating arrangements.
A household head is the most respected/responsible member of the household, who provides most of the household needs, makes key decisions and whose authority is recognised by all members of the household.
The main respondent is the person who is most knowledgeable about the household and its members. He or she may be the head, or any other member (aged 18 or over). The main respondent answers the majority of the modules in the questionnaire, with the exception of the immigrant and return migrant modules which were administered directly to the immigrants and returnees themselves. As it was not possible to interview migrants who were abroad at the time of the survey, questions in the emigrant module were asked of the main respondent.
A migrant household is a household with at least one current international emigrant or return migrant (Table 3.1).
A non-migrant household is a household without any current international emigrant or return migrant.
An international emigrant is an ex-member of the household who has left to live in another country, and has been away for at least three consecutive months without returning.1
An international return migrant is a current member of the household who had previously been living in another country for at least three consecutive months and who returned to the country.
International remittances are cash or in-kind transfers from international emigrants. In the case of in-kind remittances, the respondent is asked to estimate the value of the goods the household received.
A remittance-receiving household is a household that has received international remittances in the past 12 months prior to the survey. Remittances can be sent by former members of the household as well as by migrants who have never been part of the household.
← 1. Migration surveys often consider individuals to be migrants only after they have been away for either 6 or 12 months. Including shorter migration spells ensures that seasonal migrants are included in the sample (however temporary trips such as holidays are not considered in this definition). The survey also captures migration experiences that date back in time as the definitions do not put any restrictions on the amount of time that has elapsed since emigration, immigration or return migration. However, it is likely that more recent migration experiences are better captured in the survey as emigrants who left long ago are less likely to be reported by the household.
Systematic sampling was then used to select households from each group. The target ratio for migrant and non-migrant households was 50:50. Twenty households were selected from each village, 10 migrant and 10 non-migrant households. In case of a non-response, the household was replaced by a household from a reserve list. The total percentage of non-responses was around 5%. The main reason for not responding was that no household member was available. In these cases, the village chief was asked whether the household head was present in the village. For the majority of the households this was not the case and therefore the households were not revisited but replaced instead. Other reasons for non-response were that available household members were too old, or that the household member present refused to participate.
The household survey took place between 19 April and 17 May 2014, following a week-long training seminar and pilot survey led by the OECD and CDRI. The interviews were conducted in Khmer, using paper questionnaires. A short description of the modules included in the survey is included in Table 3.A1.2 in Annex 3.A1. Overall, 2 000 households were interviewed across the country (Table 3.2). Of these, 999 households had international migrants and 1 001 did not.
Community survey
In each of the 100 villages sampled, a community questionnaire was administered to a local government representative knowledgeable about the community and migration issues. The community surveys took place simultaneously with the household survey. Team leaders conducted the interviews after village chiefs had finished the listing exercise for the household sampling.
The community survey included questions about the share of households that currently have a family member living in another country and their most common country of residence, as well as the most common occupations of those living in the community.
Stakeholder interviews
In order to capture a wide range of information and opinion on the topic of migration and sectoral policies, semi-structured interviews were conducted using a guide developed by the OECD.
The guide was divided into five topics:
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general awareness of migration
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actions, programmes and policies directly related to migration
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main actions, programmes and policies likely to have a link with migration
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perceptions of migration-related issues
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coordination with other stakeholders on migration.
Three versions of the discussion guide were developed, targeting representatives of three types of respondents: representatives of 1) state institutions, 2) international organisations and 3) local NGOs and academic institutions. Questions were modified according to whether the institution was working on migration issues directly or indirectly. All versions of the discussion guide were available both in Khmer and in English and were sent to respondents on request in advance of the interviews. The final 28 interviewees consisted of 9 representatives of public institutions, 6 from international organisations, and 13 from local NGOs or academic institutions (Table 3.3).
The OECD prepared a joint codebook based on preliminary analysis of the data from the ten IPPMD countries which was then used as a conceptual framework. The codebook includes general themes (main themes and subthemes) which are common to all countries taking part in the project, but left room for adding new themes specific to a country. All interview transcripts were coded according to the codebook and analysed. The results were then used in the analytical chapters to make sense of and complement the findings.
How were the data analysed?
Having described the tools used to collect data for the project, this section provides an overview of how the data were analysed. Statistical analysis assesses the statistical significance of an estimated relationship – the likelihood that a relationship between two variables is not random. The analysis for this project involved both statistical tests and regression analysis. Statistical tests, such as t-tests and chi-squared tests, calculate the correlation between two variables without controlling for other factors. A t-test compares the means of a dependent variable for two independent groups. For example, it is used to test if there is a difference between the average number of workers hired by an agricultural household with emigrants and one without. A chi-squared test is applied when investigating the relationship between two categorical variables, such as private school attendance (which only has two categories, yes or no) by the children living in two types of households: those receiving remittances and those not. Statistical tests determine the likelihood that the relationship between two variables is not caused by chance.
In addition, regression analysis is useful to ascertain the quantitative effect of one variable upon another, while controlling for other factors that may also influence the outcome. The household and community surveys included rich information about households, their members, and the communities in which they live. This information was used to create control variables that included in the regression models in order to single out the effect of a variable of interest from other characteristics of the individuals, households and communities that may affect the outcome.
Two basic regression models were used in the analysis: ordinary least square (OLS), and probit models. The choice of which one to use depends on the nature of the outcome variable. OLS regressions are applied when the outcome variable is continuous. Probit models are used when the outcome variable can only take two values, such as owning a business or not.
The analysis of the interrelations between public policies and migration is performed at both household and individual level, depending on the topic and hypothesis investigated. The analysis for each sector is divided into two sections:
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The impact of a migration dimension on a sector-specific outcome
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The impact of a sectoral development policy on a migration outcome
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The regression analysis rests on four sets of variables:
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A) Migration, comprising: (1) migration dimensions including emigration (sometimes using the proxy of an intention to emigrate in the future), remittances and return migration; and (2) migration outcomes, which cover the decision to emigrate, the sending and use of remittances, and the decision and sustainability of return migration.
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B) Sectoral development policies: a set of variables representing whether an individual or household took part or benefited from a specific public policy or programme in four key sectors: the labour market, agriculture, education, and investment and financial services.
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C) Sector-specific outcomes: a set of variables measuring outcomes in the project’s sectors of interest, such as labour force participation, investment in livestock rearing, school attendance and business ownership.
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D) Household and individual-level characteristics: a set of socio-economic and geographical explanatory variables that tend to influence migration and sector-specific outcomes.
What do the surveys tell us about migration in Cambodia?
The migration dimensions of emigration and return were left to chance when sampling migrant households; therefore their numbers reflect their relative importance. Figure 3.2 shows the prevalence of emigrant and return migrants by province, based on the household data. It shows differences across provinces. The province of Kampong Thom, for instance, has a relatively larger sample of return migrants, whereas their share in Oddar Meanchey is much smaller.
Source: Authors’ own work based on IPPMD data.
Overall, the 2 000 household surveys collected data on 9 020 individuals, as well as on another 1 483 former household members who had emigrated. A total of 816 households had former members who had emigrated: 41% of all households in the sample (Figure 3.3, left-hand pie chart). Among the individuals currently living in the country, 409 were return migrants, and specific data about their migration experience were also collected. The 282 households with return migrants formed 14% of all households in the sample (Figure 3.3, right-hand pie chart). Ninety-nine households (5% of the sample) have both emigrants (one or more) and return migrants (one or more).
Source: Authors’ own work based on IPPMD data.
Table 3.4 shows how household characteristics differ depending on their migration experience. About 81% of all households are in rural areas, and this rural share is reflected across all migrant households except for a slightly lower share of those with return migrants. Households with emigrants have typically fewer members than other households, which is not surprising given that they have lost at least one member. Households with return migrants are the largest households, due to the migrant who has returned but also because they have the highest share of households with children. The share of households with a female household head is highest among households with emigrants, which, at 42%, is more than double the percentage found in households without migrants. This is not surprising given that 60% of emigrants are men. Among households with return migrants, the percentage of households with a female household head is 32%. Households without migration experience are more likely to have a member who has completed at least lower secondary education.
For the purpose of this project, a household-level wealth indicator was constructed based on questions in the household survey on the number of assets owned by the household. Assets include a range of items, from cell phones to real estate. The wealth indicator was created using principal component analysis. It suggests that households without migration experience tend to be wealthier.
The household survey also asked whether individual household members aged 15 or over planned to emigrate. The data show that plans to emigrate are more prevalent in migrant households, and are highest among households with return migrants (45%; Table 3.4). A large part of this share can be attributed to return migrants themselves, 34% of whom planned to emigrate again within the next 12 months compared to 5% among non-migrants.
Table 3.5 summarises the characteristics of individuals from the sampled households, broken down by whether they are emigrants, return migrants or individuals without migration experience. The non-migrants are the oldest group, with an average age of 40, compared to return migrants (32) and emigrants (27). Women made up 53% of the overall sample. While emigration seems to be a male-dominated phenomenon (60% are men), return migration is more gender-balanced with an equal share of men and women.
Among individuals without migration experience, 18% have finished at least lower secondary education. The share is similar for emigrants (17%), while only 12% of returned migrants have completed at least lower secondary education.
Most emigrants choose Thailand as their country of destination
Data collected on emigrants included their current country of residence, the time since they emigrated and the reason they left. Thailand is the main destination country, hosting 88% of the emigrants from the households sampled (Figure 3.4). While women, who account for 40% of the emigrants captured by the IPPMD data, are very similar to men in terms of choice of destination, Malaysia is slightly more prominent as a destination for female emigration, and South Korea for male emigration. Less than 5% migrate to high-income countries.
The main reasons given for emigrating were to help the family in Cambodia, to take a job, to search for work abroad, or because of unemployment (Figure 3.5). Together these four reasons accounted for more than 90% of the responses. The reasons for emigrating are very similar among emigrants from rural and urban households, although a larger share of urban emigrants left to help family members.
Source: Authors’ own work based on IPPMD data.
Note: Respondents were given the chance to provide two reasons for emigrating, but only the first reason was taken into account.
Source: Authors’ own work based on IPPMD data.
About one-third of the sample had left Cambodia less than one year before the survey, 29% between one and two years, 27% between two and five years, and the remaining 10% had left more than five years before the survey (Figure 3.6). Emigration from rural areas tends to be more recent, as 37% of emigrants from rural areas had left Cambodia less than one year before the survey, compared to only 21% of emigrants from urban areas. While women and men present very similar patterns in terms of duration of stay in the destination country, seasonal migrants are slightly more likely to be men than women (6% versus 5%).
Source: Authors’ own work based on IPPMD data.
Remittance patterns differ across rural and urban households
Although emigration and remittances are closely linked, one does not necessarily imply the other. Four in ten households in the sample received international remittances, partly reflecting the oversampling of migrant households (Figure 3.7). Most – but not all – of these households received them from a former household member who has emigrated, though 11% of them received them from someone else. Among households with an emigrant, 90% received remittances, compared to 7% of households without an emigrant member.
Note: The category “households receiving remittances from former member” does not imply that they solely receive remittances from a former member. It includes households that receive additional remittances from other emigrants.
Source: Authors’ own work based on IPPMD data.
Information was collected on the financial decisions of households receiving remittances from a former household member. The most common action taken by both rural and urban households was to repay a loan (Figure 3.8). This was more likely for rural households (42%) than urban households (35%). Urban households were more likely than households in rural areas to pay for health treatment or schooling and accumulate savings.
Note: The sample includes only households that receive remittances from a former household member. The figure displays the top seven most common activities reported by households. Households could specify whether they had undertaken each activity from the following list: taking a loan from a bank, paying for health treatment or schooling of a household member, accumulating savings, repaying a debt/loan, building or buying a home, investing in agricultural activities, taking out a loan from informal sources, accumulating debt, setting up a business, building a dwelling to sell to others and buying land.
Source: Authors’ own work based on IPPMD data.
The survey also collected information on the frequency and amount of remittances received from former household members. The average amount sent home by emigrants is KHR 3 597 000 (Cambodian Riel; equivalent to USD 889) over the last year, taking into account both cash and in-kind remittances. The average amount remitted is slightly higher for male (USD 919) than for female emigrants (USD 843). Both sexes remit equally, at 83%. About 8% of remittance-sending emigrants had sent in-kind remittances in the past 12 months. Around 40% of the remittances were sent through informal channels (informal agent, friends or family) to households in both rural and urban areas. (Figure 3.9). On average, remittance senders have send money home every other month.
Source: Authors’ own work based on IPPMD data.
Most return migrants are satisfied to have returned
Most return migrants (85%) were previously residing in Thailand, reflecting Thailand’s predominance as a destination country. A slightly higher share of migrants are returning from Malaysia (14%) than emigrating there (6%), a difference especially marked for women (22% vs 8%). About 33% of return migrants came home because they experienced difficulties integrating in the host country or lacked legal papers, whereas 48% returned because they preferred to be in Cambodia for a range of reasons (family, marriage, health) (Figure 3.10).
Notes: The category “individual preference” includes returning for family, marriage and health reasons.
Source: Authors’ own work based on IPPMD data.
Return migrants were also asked about the challenges they faced after returning. Even though more than half of the return migrants report facing labour-related difficulties on their return to Cambodia, 89% of all returnees are satisfied to be back in the country. Among those satisfied, 31% plan to migrate again in the next 12 months. Among return migrants whom are not satisfied to be back in Cambodia, 52% plan to migrate again.
This chapter has presented the three tools – household and community surveys and the qualitative stakeholder interviews – used to collect data to analyse the interrelation between migration, public policies and development. The following chapters take a sector-by-sector approach to presenting the results of the data analysis: for the labour market, agriculture, education, and investment and financial services.
References
Ministry of Planning (MoP) (2012). Migration in Cambodia: Report of the Cambodian Rural Urban Migration Project (CRUMP).
NIS (2009), Socio-Economic Survey - CSES 2009, National Institute of Statistics, Phnom Penh, www.ilo.org/surveydata/index.php/catalog/50/study-description.