Chapter 3. Understanding the methodological framework used in Armenia
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: a household survey, a community survey, and interviews with representatives of public, international and local organisations to provide additional qualitative information about the migration context in Armenia. This chapter explains how the sampling for the survey was designed, as well as the statistical approaches used in the chapters that follow to analyse the impact of emigration, return and remittances on key policy sectors. The chapter includes a brief overview of the survey findings, including differences across regions and between migrant and non-migrant households. It outlines some of the gender differences that emerged among migrants, and their 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 (Chapter 1), data collection was carried out in Armenia from March to April 2015. The OECD Development Centre developed three analytical tools for the fieldwork, each tailored to the Armenian context in collaboration with the Caucasus Research Resource Center (CRRC) - Armenia. They consisted of the following:
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Household survey, which were carried out in 2 000 households (see Box 3.1 for definitions). The household questionnaire gathered information about individual and household characteristics related to four key development sectors, including the labour market, agriculture, education, and investment and financial services, as well as household members’ experience with emigration, remittances and return migration. It also introduced questions on whether households and individuals benefited from specific public policies which may affect their migration and remittance patterns.
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Community survey, which were carried out in each of the 79 communities in which the household survey was conducted. Respondents were district and local leaders. The questionnaire documented information on the community’s demographic, social and economic background as well as policies and development programmes that have taken place in the community.
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Stakeholder interviews, which were carried out with 47 representatives from government ministries, public institutions, non-governmental organisations, religious organisations, trade unions, private sector institutions and international organisations based in Armenia. They were used to collect qualitative information on trends, policies, opinions and predictions related to the various aspects of migration in the country. The information they provide helped enrich and interpret the quantitative surveys by including additional details on the context specific to Armenia.
A household consists of one or several people, 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 needs of the household, 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, return migrant or immigrant.a
A non-migrant household is a household without any current international emigrant, return migrant or immigrant.
An international emigrant is an ex-member of the household who left to live in another country, and has been away for at least three consecutive months without returning.
An international return migrant is a current member of the household, who was born in Armenia, had previously been living in another country for at least three consecutive months and returned to the country.
An international immigrant is a current member of the household who was born in another country, and has lived at least 3 months in Armenia. Those who are born before 1991 in the former USSR and moved to Armenia before 1991 are not considered international immigrants.
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 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 that have never been part of the household.
← a. The number of immigrants in the final sample was too low to allow for separate analysis of immigration, therefore this report focuses only on emigration, remittances, and return migration.
This chapter describes how these tools were implemented, and provides a descriptive overview of the data collected. It presents the sampling design for the household and community surveys and stakeholder interviews, and outlines the analytical approach adopted in this report. It ends with an overview of the general migration patterns emerging from the data gathered for this project, to set the scene for the more in-depth sector-by-sector analysis of the chapters which follow.
How were the households and communities sampled?
Households and communities were sampled using multistage cluster sampling with initial stratification by urban/rural areas and by administrative provinces (marzes). The sampling frame was built from the database of electricity users provided by the Electricity Networks of Armenia Company. Because nearly 100% of Armenian households have electric power, and electricity is provided by a single company, the electricity user database is among the most comprehensive and up-to-date lists of households available for the country. This electricity network database includes about 770 000 households, divided into 5 052 clusters, ranging in size from 100 to 200 households (see Table 3.A1.1 in Annex 3.A1 for a summary of the sampling design).
The sampling frame was divided into eleven strata; 10 marzes and Yerevan, the capital. Each marz was divided into urban and rural, as defined by the law of the Republic of Armenia on Local Self-Government. Yerevan was stratified by city administrative subdivisions. This sample frame stratification helped ensure that the range of social, economic and cultural backgrounds found in the country was represented. Within each stratum, primary sampling units (PSUs) were randomly selected from the list of clusters provided by the Electricity Networks of Armenia Company. The target sample of PSUs was set at 100: 50 urban and 50 rural. The distribution of PSUs over the provinces is proportionate to the size of the population in each province. Figure 3.1 shows the geographic location of the communities where the sampled PSUs are located.
Household survey
Since data were not available on which to base a sample of households with either an emigrated household member or a returned one, all households in each of the 100 PSUs were block listed prior to data collection according to whether the household had a migrant or not. After block listing, three PSUs were replaced (one in Gyumri marz, one in Syunik marz, and one in Yerevan) because the number of migrant households was not sufficient or because most of the households were not accessible. These new PSUs, sampled from the same provinces, were also block listed. Overall, 20 main and 20 reserve households were selected in each PSU to meet the target of 2 000 households. During the fieldwork, if a chosen household could not participate, the reserve list was used to randomly select a replacement household. Replacement was allowed if the household refused to participate, or enumerators were unable to reach the household after three attempts.
The survey was conducted in 100 PSUs in 79 communities. In total, 2 000 households were interviewed, 1 004 with migrants and 996 without. The sample was evenly split between urban and rural areas. Within the urban segment, 541 households were surveyed in the capital city of Yerevan and 460 households in other urban areas (Table 3.1). The overall response rate was 58%, though response rates varied by area type, ranging from 47% in the capital to 65% in rural areas. In order to reach the targeted number of 2 000 households, 3 464 households were visited. The most common reason for non-response was that the main respondent (Box 3.1) was not available at the time of the interview and neither was another household member. The second most common reason was refusal to be interviewed. Some households with an international migrant refused to participate out of concern that the interview might harm the emigrant household member.
The survey was conducted by 38 interviewers and 9 supervisors. It took place between 14 March and 2 April 2015, following a week-long training seminar and pilot by the OECD and CRRC-Armenia. All interviews were conducted in Armenian, face to face, using paper questionnaires. A short description of the modules included in the household survey is given in Table Table 3.A1.2 in Annex 3.A1.
A quality check was conducted by CRRC-Armenia staff members during the fieldwork, involving examining a random selection of field teams. Teams were not informed in advance about the quality check. In addition, selected quality control was done via telephone after the completion of the interviews. No major problems were observed during the fieldwork.
Community survey
The community survey was conducted in each community where the household survey was carried out. Some of the sampled PSUs were in the same community, and therefore there are fewer communities (79) than PSUs (100). The community questionnaires were completed by fieldwork supervisors mostly on the same day as the household survey, with assistance from municipal officials.
The questionnaire included around 75 questions to gather demographic, social and economic information on the communities, as well as specific questions on policies and programmes implemented in the localities. It also 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 occupational activities of those living in the community.
In the capital city and other urban areas, because of lack of official data, responses were sometimes based on respondents’ estimations. In two urban communities, Vagharshapat (Armavir marz) and Hrazdan (Kotayk marz), municipal officials refused to participate in the survey. All the data for these two communities were collected using online and other publicly available sources.
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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co-ordination with other stakeholders on migration.
Three versions of the discussion guide were developed, targeting three types of respondents: representatives of 1) public institutions; 2) international organisations; and 3) local non-government organisations (NGOs) and other types of organisations (Table 3.2). Questions for each topic were modified according to whether the institution was working on migration issues directly or indirectly, and its role vis-à-vis migration policy.
In total, interviews were carried out with 47 stakeholders. The interviews were conducted in a semi-structured format. While the main topics of the interviews were determined by the thematic foci listed above, most of the questions were formulated by the interviewer depending on the context and flow of the interview, including follow-up and probing questions.
The participants were selected based on their position, activities and responsibilities, and their knowledge and understanding of the issues to be discussed in the interview, specifically the connections between migration and the labour market, agriculture, education, health, social protection and investment (i.e. the primary areas of interest for the project). Each interview lasted about 1 to 1.5 hours. The interviews were conducted in Armenian by trained interviewers and all but one interview were audio recorded. The recordings were transcribed in Armenian, and then translated into English. The OECD prepared a joint codebook based on preliminary analysis of the data 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 transcripts were then coded according to the codebook and analysed. The results were used in the analysis 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. The analyses in this report incorporate both statistical tests and regression analysis. Statistical tests determine the likelihood that the relationship between two variables is not caused by chance:
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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 agricultural households with emigrants and those without.
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A chi-squared test is used to investigate the relationship between two categorical variables, such as private school attendance (which only has two categories, yes or no) by children from two types of households: those receiving remittances and those not.
These types of statistical tests do not control for other factors. Regression analysis, on the other hand, 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 were 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, such as the household’s business investments or an individual’s plans to emigrate.
Two basic regression models are used in the report: 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 used when the outcome variable is continuous (i.e. can take on an infinite number of values). 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 was performed at both household and individual level, though this depended on the topic and hypothesis investigated. The analysis for each sector looks at two relationships:
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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
The regression analysis rests on four sets of variables:
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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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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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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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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 Armenia?
In total, the 2 000 households interviewed included 8 902 individuals. Of these, only 131 were immigrants, which meant there were not sufficient data to analyse immigration. A total of 550 households had emigrants – 28% of all households in the sample (Figure 3.2, left-hand pie chart), from which 819 former household members had emigrated. Among current members of the sampled households, 707 were return migrants: specific data about their migration experience were collected. The 509 households with return migrants formed 25% of all households in the sample (Figure 3.2, right-hand pie chart), while 106 households (5% of the sample) had both emigrants (one or more) and return migrants (one or more). Overall, 48% of households had an emigrant, a return migrant or both, while the other 52% did not.
Source: Authors’ own work based on IPPMD data.
The migration dimensions of emigration and return were left to chance in the sampling of migrant households, therefore their numbers reflect their relative importance in each marz. Figure 3.3 shows the prevalence of emigrants and return migrants in each marz, based on the household data. It ranges from a relative share of 25% of households with at least one return migrant in Aragatsotn to 75% of households in Shirak.
Source: Authors’ own work based on IPPMD data.
Table 3.3 shows how household characteristics differ depending on their migration experience. Households with emigrants are more likely to be located in rural areas, while households with return migrants are more often found in urban areas. Households with emigrants are only marginally smaller than those without, which, given that at least one of their members has left the household, suggests that these households were slightly larger than average before migration. Similarly, the dependency ratio is higher for households with emigrants, even though they are less likely to include children. Overall, 36% of households are headed by women, but there are large differences between the groups. About half of the households with emigrants have a female head, whereas this is the case for only one third of the households without migrants, and a bit less for the households with return migrants. This comes as no surprise given that the large majority of emigrants (77%) and return migrants (72%) are men, who often re-assume the position of household head on their return (44% of return migrants are head of the household). Households with an emigrant had a lower likelihood of having at least one member having completed post-secondary education than households without migration experience, while households with return migrants seem to be the most educated.
For the purposes 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 with migration experience tend to be wealthier.
The household survey also included a question on whether individual household members aged 15 or over had plans to emigrate. The data show that plans to emigrate are more prevalent for migrant households, especially those with return migrants. A large share of this can be attributed to return migrants themselves, as 28% of them plan to emigrate again, compared to 7% of their household members.
Table 3.4 summarises the characteristics of adults from the sampled households, broken down by whether they are non-migrants, returned migrants or current emigrants. Emigrants are the youngest group, with an average age of 38, compared to non-migrants (44) and return migrants (43). Overall, women account for 52% of the adults in the sample. The share of women among emigrants and return migrants is much lower, at 23% and 28% respectively.
Among individuals without migration experience, 44% have completed post-secondary education. This share is slightly lower for return migrants, and significantly lower for emigrants. Among those planning to emigrate in the future (not shown), 56% has completed post-secondary education.
Emigration patterns differ for men and women
Data collected on emigrants included their current country of residence, the time since they emigrated and the reason they left. Emigrants’ destination countries vary by gender (Figure 3.4). Whilst Russia is the most common destination for both women and men (68% and 87% respectively), women are relatively more likely than men to migrate to the European Union (EU) and North America.
Note: One individual migrated to Latvia, which is included in the category “EU-28”, rather than “Former USSR”.
Source: Authors’ own work based on IPPMD data.
The main reasons given for emigrating were to search for work or to take up a job, overall accounting for 80% of the responses (Figure 3.5). About one-third of women migrated for family reasons (marriage or to reunite the family), while this share is marginal (3%) among men. For both men and women, the share migrating to study abroad is around 3%, but this differs depending on the country of destination. Among emigrants who migrated to the European Union and the United States, around 10% gave studying abroad as their reason for migrating.
Source: Authors’ own work based on IPPMD data.
About half of the emigrants in the sample had left Armenia in the year leading up to the survey, around 20% had left between one and five years previously, another 11% between 5 and 10 years previously, and the remaining 21% more than ten years previously. The time since migration also varies by country of destination and gender. More than one-third of the emigrants who migrated to the EU or North America had left Armenia more than ten years ago, compared to 18% of the emigrants who migrated to Russia. About 67% of emigrant women have been abroad for more than two years, compared to only 41% of men. The higher share of seasonal migrants among men (45% compared to 7% among women) partly explains this difference.
Gender plays a role in remittance use and sending
Although migration and remittances are closely linked, one does not necessarily imply the other. Seventy-one percent of households with an emigrant received remittances, compared to 2% of households without an emigrant. Overall, about one in four households had received international remittances in the year prior to the survey. Of these, most (79%) – but not all – received remittances from an emigrant member; 95 (21% of remittance-receiving households) received them from another source (Figure 3.6).
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 remittances also from other emigrants.
Source: Authors’ own work based on IPPMD data.
What financial decisions are made by households receiving remittances from a former household member? The most common activity was to repay a loan (Figure 3.7). Households in rural areas were particularly likely to do so, with 28% of them repaying loans, compared to 22% of households in urban areas. Households undertook similar activities regardless of whether they were headed by men and women (not shown), except that households headed by a woman are more likely to invest in schooling than those headed by men (14% versus 8%).
Note: The sample only includes 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, buying land, and restoring or improving housing.
Source: Authors’ own work based on IPPMD data.
The survey also collected detailed information on the amount of remittances received from former members, the frequency of sending, and the channels used. The average amount sent home by emigrants in the 12 months leading up to the survey was AMD 756 120 (Armenian Dram), equivalent to USD 1 854. This includes both monetary remittances and the cash equivalent value of in-kind remittances. Only about 3% of emigrants had sent in-kind remittances over the year leading up to the survey, with an average estimated value of AMD 214 000 (USD 525). About 39% of remitting emigrants sent remittances at least once a month, another 42% did so on a quarterly or yearly basis, while the rest did not send funds regularly. More than 90% of monetary remittances were sent using the formal bank system.
Women were less likely to send remittances than men, as only 20% of emigrated women sent remittances compared to 66% of men. This difference holds across different destination countries and levels of education. However, the average amount sent by women was higher, as women remitted AMD 837 607 (USD 2 053) on average, while men remitted AMD 729 160 (USD 1 788).
About half of the return migrants are satisfied to be back
Most of the 707 returnees had come back from Russia, though the share for women is lower than for men (Figure 3.8). Among female return migrants, the share returning from Russia is higher than the share of female emigrants currently live there. Men returnees have mainly come home from Russia, and again the share is slightly higher than the share of current emigrants in Russia. The reverse is true for North America and the European Union, indicating that emigrants who moved there are more likely to stay than return.
Note: One individual returned from Latvia, which is included in the category “EU-28”, not in “Former USSR”.
Source: Authors’ own work based on IPPMD data.
The reasons why return migrants initially emigrated are similar to those mentioned by current emigrants, especially for men. Most male return migrants reported labour related or financial reasons as their motivation for emigrating. Among female returnees, the share that initially migrated for family reasons (44%) is higher than the share of female current emigrants who reported migrating for this reason (32%).
About 72% of the return migrants had spent less than one year abroad. The three most common reasons returnees gave for coming back to Armenia were that they preferred their own country (54%), a lack of legal status (19%) or difficulties integrating (13%; Figure 3.9). Men are more likely than women to return because of a lack of legal status (23% versus 9%), and women because of their preference for Armenia (64% versus 51%).
Note: The category “individual preference” includes returning for family, retirement, marriage, and health reasons.
Source: Authors’ own work based on IPPMD data.
Return migrants were also asked whether they were satisfied to be back in Armenia. More than half were satisfied or very satisfied to be back in the country, with the share higher for migrants who have returned to rural areas (56%) than to urban ones (49%). Among those satisfied to be back, 17% plan to re-migrate in the next 12 months, compared to 34% of those who are unsatisfied. More than 60% of the returnees faced challenges on their return, mostly difficulties finding a job in the first five years upon return.
This chapter has presented the three tools used to collect data – household and community surveys and the qualitative stakeholder interviews – and the analysis techniques for exploring the links between migration, public policies and development. The following chapter takes a sector-by-sector approach to presenting the results of the data analysis: the labour market, agriculture, education, and finance and investment.