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Research Article
The effect of creating a single EAEU labor market on the level of financial well-being of migrant households (exemplified by the Republic of Armenia)
expand article infoValeriia G. Oksinenko
‡ Lomonosov Moscow State University, Moscow, Russia
Open Access

Abstract

The article analyzes the effect of creating a single EAEU labor market on the financial well-being of households in countries that mainly send migrants, exemplified by the Republic of Armenia. Based on data of the Integrated Living Conditions Survey (ILCS) 2012-2017 and using the difference-in-differences method, the study has identified a significant causal relationship between the country’s accession to the EAEU and reduced income gap between households with migrants in Russia and households with migrants in other countries and regions or without migrants at all. Thus, after Armenia’s accession to the EAEU, income of the households sending migrants to Russia became 6-11% higher than the one of the households sending migrants to other countries, despite the fact that until 2015 there was hardly any difference in income; the income gap with the households without migrants decreased from 6% in 2012-2014 to 2% in 2015-2016. The confirmed positive impact of Armenia’s accession to the EAEU makes it possible to consider it a tool for reducing poverty in the Republic of Armenia as well as recommend to continue development and harmonization of the labor migration policy of the EAUE member states.

Keywords

Eurasian Economic Union (EAEU), labor migration, Republic of Armenia, single labor market, household income

JEL codes: J1, J2, J4, J6

Introduction

International migration is a powerful mechanism for smoothing effects of the short- and long-term economic shocks and imbalances in both hosting and sending countries, not only in terms of the economy in general, but at the level of individual households as well. The effect on individual households is particularly interesting for countries that send migrants. Researchers have identified the following two channels of this compensatory effect. The first one is remittances of migrant workers from abroad to their homeland, which positively affects the growth of the household financial well—being (and not only households with migrants, but also those without them) (Etowa 2016) and contributes (along with the economic governance system) to the increase in human capital in migrant households (Azam and Raza 2016) in developing countries. The second channel of influence is non–monetary. In particular, participation of mothers in international migration contributes to better health of their children through increased health knowledge among mothers (Hildebrandt et al. 2005).

For Russia and other countries of the former USSR, the issue of migration is also relevant: the countries are historically interconnected by intense migration flows, with Russia being the main center of attraction (Chudinovskikh and Denisenko 2014). In 2015, the Republic of Belarus, the Republic of Kazakhstan, the Russian Federation, the Republic of Armenia, and the Republic of Kyrgyzstan established the Eurasian Economic Union (EAEU), which implies a coordinated, harmonized or unified policy in various sectors of the economy. Among other things, the policy of the EAEU member states includes liberalization of the labor migration regulation within the union and a step towards developing a single labor market through easing the labor migration rules in combination with harmonizing the legislation regarding migrant rights in the member states. In this context, the EAEU creation can have a significant impact on both labor migration between countries, and migrant households remaining at home.

The purpose of this study is to assess the impact of a single labor market within the EAEU on the financial well-being of migrant households in the Republic of Armenia. The study is a further continuation of the study (Denisova et al. 2022), which also analyzed the effect of this mechanism on indicators of subjective well-being of migrant households. In this paper, the effect found will be tested against household income data. The decision to continue the above-mentioned study was guided by the fact that subjective and objective assessments of household well-being in the Republic of Armenia do not coincide, furthermore, they even sometimes correlate in different directions with the same indicators (for example, the nutrition quality index (Oksinenko 2021)).

Choosing to study one market and one country allows us to analyze results of the EAEU creation at the micro level and identify emerging trends and evaluate its effects on individual citizens rather than the economy in general.

The Republic of Armenia was also selected for several reasons. On the one hand, it is one of the countries that most intensively sends labor migrants to Russia (Denisova et al. 2022), and the income of the Armenian migrant households is largely formed by workers’ remittances to their homeland (World Bank 2019). On the other hand, the Republic of Armenia is a country with an ambiguous position in relation to the membership in the Union. Even at the time of signing the agreement, the President of the Republic announced his intention to continue the dialogue with European countries and institutions (Entina 2014). At the end of 2017, the Comprehensive and Enhanced Partnership Agreement was signed between the EU and the Republic of Armenia. From June 1, 2018, it was applied temporarily, and at the beginning of 2021 – after ratification by all EU countries – it entered into full force (Perezagruzka otnoshenij…2021). Obtaining evidence of effective functioning of the EAEU can help maintain its integrity.

Finally, the fight against poverty is an acute social issue in the Republic: at the beginning of 2022, 30% of the population lived below the poverty line (COFACE). It has been shown (Oksinenko 2022) that it is predominantly poor households that send migrants to Russia (Table 1), and in literature we find ample evidence that participation in labor migration increases household incomes (Cantore and Calì 2015; Etowa 2016).

Table 1.

Logarithm of the average per capita household income in the Republic of Armenia, expressed in drams, depending on the presence or absence of migrants and the direction of migration, 2013-2017

2013 2014 2015 2016 2017
Migrant in Russia 10.6908 10.8485 10.8252 10.7597 10.6208
Migrant outside Russia 10.6605 10.9186 10.8851* 10.9380** 10.8588**
(0.335) (0.148) (0.064) (0.000) (0.000)
No migrants 10.6933 10.8011* 10.8838* 10.8598** 10.8350**
(0.934) (0.087) (0.059) (0.001) (0.000)

An upward trend in the income of the poorest households as a result of the simplified labor migration from Armenia to Russia is a perfect proof of a positive impact of the single labor market on countries that send migrants, substantiating the need for its further liberalization.

The article consists of the following sections:

  • Data and methodology
  • Results
  • Conclusions and further discussion

Data and methodology

The empirical basis of the study is data of the Integrated Living Conditions Survey in the Republic of Armenia (hereinafter referred to as the Survey), which has been conducted annually since 2001 (the latest full results are available for 2018).

The data uniqueness in comparison with similar surveys in other EAEU countries, including Russia, is the level of detail (the Survey presents questions that comprehensively cover the household well-being, including participation in migration), continuity of methodology and significant coverage of households in terms of their socio-economic characteristics. The sample size of the Survey varies from 5,000 to 8,000 households living in both urban and rural areas, which is about 20,000 respondents annually, the data are cross-sectional (the sample is formed annually according to the same methodology). The proportional data collection throughout the year makes it possible to level out seasonal shifts, including migration ones.

Since the Republic of Armenia joined the EAEU in 2015, which could potentially affect the household income, we take data for the period 2012-2017, including 2015, to identify the expected effects. We choose 2012 as the initial year due to a change in the methodology: before 2012, the sample size was about 8,000 households, while since 2012 it has been reduced to slightly more than 5,000. The sample was expanded again to 8,000 respondents in 2017, therefore we consider it not rather relevant, and in some cases, we limited our study to 2016 only.

To identify the effect of creating a single labor market within the EAEU on the financial well-being of the Armenian migrant households, the difference-in-differences method is used. This method makes it possible to obtain an unbiased estimate of an event or program by considering the non-random selection. A detailed justification of the relevance of the methodology to the data used and its description are presented in the article (Denisova et al. 2022).

The difference-in-differences method allows assessing the effect of an event or program on the target group (intervention) by comparing the indicator that evaluates successes or failures of the program (in our case, average per capita income), before and after the introduction of changes. To adjust for other changes between two points in time, we use data on the group that is outside the program (control). Assuming parallel trends in the selected parameter in the control and intervention groups before the program, the effect of the program is identified by a double difference (formula 1) (Wooldridge 2009).

E[Y1(1) − Y1(0)|X] =

= {E(Y1|X, W = 1) − E(Y1|X, W = 0)} − {E(Y0|X, W = 1) − E(Y0|X, W = 0)},(1)

where W is an indicative variable of affiliation with the intervention (W = 1) or control (W = 0) groups, Y1 is a measurement of the result after and Y0 is a measurement of the result before, X – covariates, controlling which allows to ensure the condition of parallel trends.

Following the methodology (Denisova et al. 2022), we define the control group in two ways: 1) broad definition – households without migrants; 2) narrow definition – households with migrants outside Russia, but in other countries or regions of the Republic of Armenia.

For the purposes of the study, we also defined the intervention group in the following two ways: 1) households with migrants in Russia at the time of the Survey; 2) households with migrants only in Russia at the time of the Survey (without migrants in other countries or regions of the Republic of Armenia). Table 2 shows the distribution of households by group.

Table 2.

Number of Armenian households with and without migrants in their composition, with due regard to the country of residence of the migrant, 2012-2017

Households with migrants currently outside Russia ONLY Households with migrants currently in Russia ONLY Households with migrants currently in Russia Households without migrants
2012 370 535 624 2 352
2013 279 568 652 3929
2014 293 529 606 3 846
2015 203 512 571 3960
2016 224 557 619 3837
2017 303 678 786 5 951

To adjust for differences between the intervention and control groups regarding characteristics under study, we included a set of covariates: sex, age (in the form of five-year groups for ages 16 to 80, a 15-year interval for ages 0-15, and an open interval for ages older than 80), marital status, health status, the share of females in the household, a household member with higher education, the share of working household members among working-age citizens, the share of children and the elderly in the household, type of settlement (Yerevan, urban or rural area). In addition, to consider the cross-sectional nature of the data, the main specifications include a set of year dummy variables.

The interval 2012–2014 was taken as the period before the program, and the interval 2015–2017 (2015-2016) was taken as the period after. Also, to test the sensitivity of the results to the assumption of parallel trends in the intervention and control groups, we weakened the assumption and assumed that (linear) trends before joining the EAEU differ across the intervention and control group. The corresponding cross term is statistically significant in all specifications, results of replacing the year dummy variables with the time trend are presented in Table 5.

We also conducted placebo tests. In one of them, we took a placebo period – 2013 instead of 2015 (specifications 7-10, table 6), and in the other – a placebo group: we replaced the intervention group with households that currently have labor migrants in other countries or regions of Armenia (outside Russia), while households that do not include labor migrants were taken as the control group (specifications 11-12, table 6).

The problem of isolating the effect asssociated with joining the EAEU is complicated by the fact that during the same period the Russian ruble (RR) devaluated against the U.S. dollar (USD) and the Armenian dram (AMD) (the national currency of the Republic of Armenia) (Fig. 1).

Figure 1.

RR to AMD and USD Exchange rates, 2012-2017. Source: Central Bank of the Russian Federation

The monetary nature of the well-being indicator and the availability of detailed information about the constituent parts of this indicator make it easier to separate one effect from another. Thus, we adjust the amounts of incomes received by households from Russia to the changes in RR to AMD exchange rate, so that all income received from Russia are considered at the 2013 ruble-dram exchange rate. The remaining household income received within the country (that is, in drams) or from other countries (in foreign currencies, mainly in USD and EUR) remained unchanged, calculated at the exchange rate of the year in question. As a result, we get the income values as they would be if the dram-ruble exchange rate were stable throughout the period considered in the study.

As a measure of a single labor market creation effect on the level of the migrant household financial well-being, the logarithm of the average per capita income of the present household members was taken. Since all household incomes were indicated in current prices with due regard to the level of average annual inflation of the Armenian dram, all incomes were brought to the price level of 2013.

Results

Results of the difference-in-differences evaluation for the 2012-2017 interval (Table 3) were significant only for the combination of “Households with migrants currently in Russia only” – “Households with migrants currently outside Russia only”, while for the remaining combinations of the control and intervention groups, the result was significant at the 11% interval. As mentioned earlier, the sample increased in 2017, which could potentially affect the results’ significance, so we decided to limit the interval under study to 2012-2016 (Table 4). For this time interval, the results were significant for all considered combinations of the control and intervention groups. The incomes of the households sending migrants to Russia in 2012-2014 were the same as the incomes of the households sending migrants to other countries, and 6% lower than those of the households without migrants. After Armenia’s accession to the EAEU, the incomes of the households sending migrants to Russia became 6-11% higher than the ones of the households sending migrants to other countries, and the income gap with the households without migrants decreased to 2%. We observe that the growth of incomes of the households sending migrants to Russia was registered precisely in 2015, following Armenia’s accession to the EAEU, which is confirmed by a positive and statistically significant assessment of the difference-in-differences (Table 4). According to our estimates, the size of the effect of Armenia’s accession to the EAEU on the well-being of the households sending migrant workers to Russia varies in the range of 7-10% (depending on specification), if the control group is the households sending migrants to other countries (except Russia), and is 5% if the control group is the households without migrants (Table 4).

Table 3.

Estimation by the difference-in-differences method, changes in the logarithms of the average per capita household income in the Republic of Armenia, expressed in drams, depending on the presence or absence of migrants and the direction of migration, 2012-2017

Intervention Households with migrants currently in Russia Households with migrants currently in Russia ONLY Households with migrants currently in Russia ONLY
Control Households with migrants currently outside Russia ONLY Households without migrants
(1) (2) (3) (4) (5) (6)
Before 2012-2014
Control 10.247 10.124 10.247 10.031 10.403 10.018
Intervention 10.151 10.109 10.160 10.043 10.160 9.950
Diff (T-C) -0.0959 -0.0153 -0.0875 0.0125 -0.243 -0.0680
After 2015-2017
Control 10.415 10.193 10.415 10.251 10.572 10.133
Intervention 10.454 10.218 10.485 10.317 10.485 10.094
Diff (T-C) 0.0400 0.0252 0.0708 0.0662 -0.0866 -0.0396
Diff-in-diff 0.136** 0.0405 0.158** 0.0537* 0.156** 0.0284
(0.0217) (0.0250) (0.0222) (0.0256) (0.0144) (0.0175)
Covariates no yes no yes no yes
Year dummy variables yes yes yes yes yes yes
Observations 25629 14455 23215 13116 97337 73010
Control 7182 4574 7182 4574 81304 64468
Intervention 18447 9881 16033 8542 16033 8542
R-squared 0.027 0.204 0.030 0.206 0.023 0.325
Means and standard errors were estimated using linear regression. Robustness of Standard Errors: Significance: ** p<0.01; * p<0.05.
Table 4.

Estimation by the difference-in-differences method, changes in the logarithms of the average per capita household income in the Republic of Armenia, expressed in drams, depending on the presence or absence of migrants and the direction of migration, 2012-2016

Intervention Households with migrants currently in Russia Households with migrants currently in Russia ONLY Households with migrants currently in Russia ONLY
Control Households with migrants currently outside Russia ONLY Households without migrants
(1*) (2*) (3*) (4*) (5*) (6*)
Before 2012-2014
Control 10.247 9.987 10.247 10.061 10.403 10.014
Intervention 10.151 9.976 10.160 10.081 10.160 9.950
Diff (T-C) -0.0959 -0.0116 -0.0875 0.0194 -0.243 -0.0635
After 2015-2016
Control 10.375 10.114 10.375 10.270 10.527 10.097
Intervention 10.455 10.178 10.491 10.387 10.491 10.079
Diff (T-C) 0.0800 0.0637 0.116 0.117 -0.0363 -0.0171
Diff-in-diff 0.176** 0.0753* 0.203** 0.0974** 0.207** 0.0464*
(0.0263) (0.0306) (0.0267) (0.0312) (0.0168) (0.0207)
Covariates no yes no yes no yes
Year dummy variables yes yes yes yes yes yes
Observations 20448 11525 18595 10476 73894 54982
Control 5771 3667 5771 3667 61070 48173
Intervention 14677 7858 12824 6809 12824 6809
R-squared 0.024 0.210 0.028 0.220 0.020 0.318
Means and standard errors were estimated using linear regression. Robustness of Standard Errors: Significance: ** p<0.01; * p<0.05.

To verify the obtained results, we conducted a test for resistance to the time trend: in the specification 1-6, instead of the year dummy variables, we included a linear time trend and the cross term “intervention group * linear trend”. Difference-in-differences estimates retained their sign, although the differences became more significant. Both variables were significant across all specifications (Table 5).

Table 5.

Estimation by the difference-in-differences method, changes in the logarithms of the average per capita household income in the Republic of Armenia, expressed in drams, depending on the presence or absence of migrants and the direction of migration, tests for resistance to the time trend

Intervention Households with migrants currently in Russia Households with migrants currently in Russia ONLY Households with migrants currently in Russia ONLY
Control Households with migrants outside Russia ONLY Households without migrants
(1) (2) (3) (4) (5) (6)
Before 2012-2014
Control 10.031 9.816 10.033 9.875 10.283 9.816
Intervention 9.985 9.946 10.011 10.061 10.011 9.844
Diff (T-C) -0.0455 0.130 -0.0195 0.187 -0.272 0.0276
After 2015-2017
Control 9.862 9.677 9.862 9.734 10.297 9.827
Intervention 10.027 10.082 10.106 10.254 10.106 10.040
Diff (T-C) 0.165 0.406 0.244 0.520 -0.192 0.213
Diff-in-diff 0.211** 0.275** 0.264** 0.333** 0.0803* 0.185**
(0.0473) (0.0547) (0.0484) (0.0560) (0.0314) (0.0381)
Covariates no yes no yes no yes
Year dummy variables instead of year dummy variables, a linear time trend and a cross term “experimental group*linear trend” are included
Observations 25629 14455 23215 13116 97337 73010
Control 7182 4574 7182 4574 81304 64468
Intervention 18447 9881 16033 8542 16033 8542
R-squared 0.035 0.202 0.037 0.211 0.027 0.324
Means and standard errors were estimated using linear regression. Robustness of Standard Errors: Significance: ** p<0.01, * p<0.05.

In placebo tests, we also tested sustainability of the results by replacing the intervention group with a group of the households with migrants who are not in Russia at the time of the Survey (specifications 11-12), as well as replacing the year of the formation of the union (2015 with 2013) (specifications 7-10). The use of the placebo group and placebo period in all specifications with the inclusion of covariates gave results with the opposite sign. However, specifications 7 and 9 (without including covariates) turned out to be significant as well, but in them the difference-in-differences turned out to be positive; in specification 11, the difference remained negative, yet insignificant. The results obtained in all specifications indicate that 2015 was indeed a turning point in changing the indicators of financial well-­being of households in the intervention group, as well as the fact that Armenia’s accession to the EAEU had an effect on the households with migrants in Russia only (Table 6).

Table 6.

Estimation by the difference-in-differences method, changes in the logarithms of the average per capita household income in the Republic of Armenia, expressed in drams, depending on the presence or absence of migrants and the direction of migration, placebo tests

Placebo period Placebo group
Intervention Households with migrants currently in Russia Households with migrants currently in Russia ONLY Households with migrants currently outside Russia
Control Households with migrants currently outside Russia ONLY Households without migrants
Before (7) (8) (9) (10) (11) (12)
2012 2012-2014
Control 10.089 9.874 10.089 9.934 10.403 9.819
Intervention 9.984 9.981 10.007 10.088 10.210 9.702
Diff (T-C) -0.104 0.107 -0.0820 0.154 -0.192 -0.117
After 2013-2017 2015-2017
Control 10.375 10.214 10.375 10.274 10.572 10.122
Intervention 10.368 10.195 10.388 10.286 10.368 9.972
Diff (T-C) -0.00654 -0.0194 0.0131 0.0116 -0.204 -0.150
Diff-in-diff 0.0979** -0.126** 0.0951** -0.143** -0.0116 -0.0325*
(0.0269) (0.0320) (0.0276) (0.0332) (0.0170) (0.0189)
Covariates no yes no yes no yes
Year dummy variables yes yes yes yes yes yes
Observations 25629 12268 23215 13116 90900 70381
Control 7182 4574 7182 4574 81304 64468
Intervention 18447 9881 16033 8542 9596 5913
R-squared 0.026 0.205 0.025 0.214 0.019 0.337
Means and standard errors were estimated using linear regression. Robustness of Standard Errors: Significance: ** p<0.01; * p<0.1.

Conclusions and further discussion

Until 2015, the incomes of the households sending migrants to Russia were on average the same as the incomes of the households sending migrants to other countries, and 6% lower than those of the households without migrants. After Armenia’s accession to the EAEU, the incomes of the households sending migrants to Russia became 6-11% higher compared to the households sending migrants to other countries, and the income gap with the households without migrants decreased to 2%. The methodology of the study suggests that the changes are due to Armenia’s accession to the EAEU in 2015, while this effect failed to spread to other groups of the households.

Since the study considered the period until 2017 only and the effect of creating a single labor market exclusively, we did not touch upon the impact of significant global events on migration flows. Thus, the study neither focused on the impact of the COVID-19 pandemic in 2019 and 2020 and the associated significant restrictions on movements of international migrants nor considered the escalation of the armed conflict in Nagorno-Karabakh (2020-2022). These developments are certainly additional factors that can reduce the effects of the creation of a single labor market on household incomes and are potential areas for future research on this topic.

Since the poorest households mainly send migrants to Russia, the chosen form of migration policy in the EAEU can become one of the tools to reduce poverty in the Republic of Armenia. The confirmed positive impact of the single labor market functioning makes it possible to recommend continuing the process of harmonization of the legislation of the EAEU member states in relation to labor migration, especially against the background of instability arising under the influence of external factors.

References

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Other sources of information

Chudinovskikh O, Denisenko M (2014) Migration Between CIS Countries: Working Paper —WP3. URL: https://www.hse.ru/data/2013/04/15/1233209379/Денисенко-докл.pdf

COFACE. Armenia / Economic Studies. URL: https://www.coface.com/Economic-Studies-and-Country-Risks/Armenia (Accessed on: 13.12.2022)

Perezagruzka otnoshenij ES — Armeniya: Moskva ne protiv? [Reset of EU—Armenia relations: Does Moscow mind?] 1.03.2021. URL: https://www.dw.com/ru/es-armenija-perezagruzka-otnoshenij/a-56718077 (Accessed on: 18.02.2022) (in Russian)

World Bank (2019) Armenia International Outmigration: An Exploration on the Effects on Armenian Households’ Welfare. World Bank, Washington, DC. © World Bank. https://openknowledge.worldbank.org/handle/10986/32537. License: CC BY 3.0 IGO

Information about the authors

Oksinenko Valeria Gennadievna – 1st category engineer of the Laboratory of Population Economics, Lomonosov Moscow State University, Moscow, 119234, Russia. Email: leraoksinenko@gmail.com

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