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10
Пространственная Экономика 2022. Том 18. № 3. С. 42-62
JEL: C33, F22, О15 https://dx.doi.Org/10.14530/se.2022.3.042-062
УДК 314.7+330.4
Does Institutional Quality Matter
for International Migrants in Their Home
and Host Country? A Case of Russian Federation
A. Valei, S.O. Mamman
Azamat Valei PhD in Economics
1 Center for Economic Research and Graduate Education - Economics Institute (CERGE-EI), Charles University, 7 Politickych Veznu St., Prague, 111 21, Czech Republic
Senior Researcher, Associate Professor
2 Ural Federal University, 19 Mira St., Yekaterinburg, 620002, Russian Federation E-mail: azamat.valey@urfu.ru
ORCID: 0000-0002-9583-6542
Suleiman OnimisiMamman Researcher
Laboratory for International and Regional Economics, Graduate School of Economics and Management, Ural Federal University, 19 Mira St., Yekaterinburg, 620002, Russian Federation E-mail: onimisism@gmail.com ORCID: 0000-0003-3204-0595
Abstract. Poor institutions have been identified to hinder economic growth and development, with negative social and economic effects such as skilled human resource emigration. In a resource-rich economy, a poor institutional framework has been stated to be a key cause of resource curse. The current study used the CIS and other bordering countries to investigate the impact of both home and destination country institutional quality on migration flows to the Russian Federation. Is the Quality of Institutions (Origin and Host Countries) Important in Migration? The study demonstrated that institutional quality matters for migration from surrounding countries using a gravity-based model estimated using the Poisson Pseudo Maximum Likelihood (PPML). Population, unemployment, and GDP per capita were identified as push factors. In addition, the study discovered a correlation between the institutional quality of the host country and the inward migration flow. Therefore, the study recommends enhancing the institutional quality of the host country to increase the positive effects of inward migration flow.
Keyword: migration, Institutional quality, economic growth, Panel model, Augmented Mean Group technique, Income, regulatory quality, rule of law, corruption, CIS countries, Russia
Acknowledgements. The research funding from the Ministry of Science and Higher Education of the Russian Federation (Ural Federal University project within the Priority-2030 Program) is gratefully acknowledged.
© Valei A., Mamman S.O., 2022
For citation: Valei A., Mamman S.O. Does Institutional Quality Matter for International Migrants in Their Home and Host Country? A Case of Russian Federation. Prostranstvennaya Ekonomika = Spatial Economics, 2022, vol. 18, no. 3, pp. 42-62. https://dx.doi.org/10.14530/ se.2022.3.042-062
Имеет ли значение качество институтов для международной миграции в стране происхождения и в стране назначения? Случай Российской Федерации
А. Валей, С.О. Мамман
Валей Азамат PhD in Economics
1 Center for Economic Research and Graduate Education - Economics Institute (CERGE-EI), Charles University, 7 Politickych Veznu St., Prague, 111 21, Czech Republic
старший научный сотрудник, доцент
2 Уральский федеральный университет, ул. Мира, 19, Екатеринбург, 620002, Российская Федерация
E-mail: azamat.valey@urfu.ru ORCID: 0000-0002-9583-6542
Мамман Сулейман Онимиси научный сотрудник
Лаборатория международной и региональной экономики, Высшая школа экономики и менеджмента, Уральский федеральный университет, ул. Мира, 19, Екатеринбург, 620002, Российская Федерация E-mail: onimisism@gmail.com ORCID: 0000-0003-3204-0595
Аннотация. Целью настоящего исследования являлось определение влияние качества институтов как в странах происхождения, так и в принимающих странах. В данном исследовании анализ производился на основе панельных данных, сформированных на массиве за 1997-2019 гг. по 11 странам, с использованием гравитационной модели, оцененной с помощью псевдомаксимального правдоподобия Пуассона (PPML) для учета социально-экономических характеристик, которые являются важным фактором, определяющим миграцию. Были получены доказательства тесной взаимосвязи между социально-экономическими факторами, такими как ВВП на душу населения, безработица, численность населения и миграционный поток в общей выборке, что может подтвердить широко распространенное мнение о том, что экономический прогресс является важным фактором, привлекающим мигрантов. Исследование показало, что институциональные факторы в принимающей стране (Россия) более эффективны, чем качество институтов в стране происхождения. Во многих случаях регулятивный контроль и эффективность правительства оказывают положительное влияние, в то время как такие факторы, как право голоса и подотчетность, верховенство закона и борьба с коррупцией оказывают негативное влияние. Также было установлено, что региональная близость является важным фактором, определяющим миграционный поток. Таким образом, результаты показывают, что для максимизации выгод от приема международных мигрантов повышение качества институтов должно стать приоритетом.
ПЭ A. Valei' S-°- Mamman
№ 3 2022
Ключевые слова: миграция, качество институтов, экономический рост, гравитационная модель на панельных данных, методика дополненной средней группы, доход, качество регулирования, верховенство права, коррупция, страны СНГ, Россия
Благодарности. Выражаем благодарность за финансирование исследования Министерством науки и высшего образования Российской Федерации (проект Уральского федерального университета в рамках программы «Приоритет-2030»).
Для цитирования: Valei A., Mamman S.O. Does Institutional Quality Matter for International Migrants in Their Home and Host Country? A Case of Russian Federation. Prostranstvennaya Ekonomika = Spatial Economics, 2022, vol. 18, no. 3, pp. 42-62. https://dx.doi.org/10.14530/ se.2022.3.042-062
INTRODUCTION
International migration has played a critical role in labor mobility and the transfer of funds from host countries to migrants' home countries over the years. As a result, both the host and origin countries are expected to benefit. However, because of the availability of a cheap workforce (skilled and unskilled), especially in countries with less stringent labor movement rules, the question of who profits most from migration remains debatable. On the other side, the home countries of migrants, who are all from developing countries, have reaped the benefits of massive financial transfers (remittances). Remittances to countries in East Asia and the Pacific climbed to almost $147 billion in 2019, according to a World Bank estimate published in 2020. Remittances to countries in Europe and Central Asia, Latin America and the Caribbean, and South Asia grew steadily in 2019, with only Sub-Saharan Africa seeing a modest dip to around $48 billion.
The drivers of migration are an important topic in this discussion, with existing work highlighting social and economic reasons such as income, job possibilities, and better living conditions, among others. Environmental and climatic elements, such as extreme weather, floods, and drought, have also been identified as predictors of people's mobility in several studies (Beine, Parsons, 2015; Reuveny, 2007; Martin, 2013). Although Borjas (2001) stated that traditional migration theory tends to link movement mainly to differences in economic possibilities such as income across nations.
However, other research has attempted to link institution as another important factor of migration, emphasizing the importance of institutional quality in migration. The feedback of the relationships is more obvious in this nexus, as institutional quality is thought to have a beneficial effect on migrants' movements and vice versa. On the one hand, research by (Ariu et al., 2016; Bergh et al., 2015; Bertocchi, Strozzi, 2008; Docquier et al., 2014) has found that institutional quality has a favorable impact on migration from countries with low institutional quality
to countries with high institutional quality. More importantly, countries with high institutional quality expand quicker than those with low institutional quality.
Acemoglu et al. (2001) link the levels of economic growth to the influence of colonial migration on institutions in a similar study. It is often said that resource-rich countries suffer from the resource curse due to inadequate institutional quality and governance. On the other hand, research such as (Batista, Vicente, 2011; Beine, Sekkat, 2013; Li et al., 2017; Tran et al., 2017; Tran et al., 2019) have claimed that migration has a favorable impact on institutional quality, especially in migrants' home countries. The investigations also identify the influence transmission pathways, which include diaspora and return channels.
Despite EU and US sanctions, the Russian Federation has enjoyed considerable political and economic stability in recent decades. Despite this retaliation, a casual examination at the World Bank's governance measure, World Governance Index, suggests a good governance and institutional outlook (Fig.). Government effectiveness and political stability, both key characteristics that could attract migration, particularly from neighboring nations, have improved significantly over the years.
0,40 0,20 0,00 -0,20 -0,40 -0,60 -0,80 j--1,00 -1,20
IH
101
un
B 1
■ L
I
m
ÏH
HI
ffl
2010 2011 2012
□ Voice & Accountability
□ Regulatory Quality
2013
2014 2015
□ Political Stability
□ Rule of law
2016 2017 2018 2019
□ Government Effectiveness
□ Control of Corruption
Fig. Institutional indicators for Russia Source: Worldwide..2020.
However, the assessment also revealed that the country has struggled in areas like rule of law and corruption control. More importantly, various doubts have been raised about the governing system, with some analysts labeling it an authoritarian state. Despite this, the Federation continues to be a popular destination for migrants from Asia and Europe. The study attempts to evaluate if institutional quality matters for migrants' movement in both their home and host countries, taking into consideration the migrants' socioeconomic variables.
A. Valei' S-°- Mamman
A BRIEF OVERVIEW OF MIGRATION AND INSTITUTIONAL QUALITY IN RUSSIA
Russian Federation borders a host of European and Asian countries which also comprises of countries of the former Soviet Union some of which are now members of the Commonwealth of Independent States1 (founded in 1991 after the dissolution of the Soviet Union). The Federation is characterized by a multidimensional political and economic ideology which may have accounted for the steady inflow of migrants within and outside the region with a report from Migration Policy Institute (MPI) (Top 25..., 2019) revealing Russia to be one top country in Eastern Europe for the destination for international migrants.
As of 2019, Russia had over 11.6 million international migrants, the majority of whom were from neighboring countries, including members of the Commonwealth of Independent States (CIS), such as Ukraine, Kazakhstan, and Uzbekistan, which ranked first, second, and third, respectively, in terms of foreign-born populations (World., 2020). Also, Chudinovskikh and Denisenko (2017) stated that, with the fall of the Soviet Union, the majority of migration into and out of Russia took place within the region, with citizens from the former Union accounting for about 90% of all arrivals in Russia between 1991 and 2015. During this time, the region has welcomed around 11.8 million immigrants and expelled approximately 5.3 million emigrants, resulting in a net migration flow of 6.5 million (Chudinovskikh, Denisenko, 2017). Most of these migrants are classified as labor migrants because they travel to Russia in quest of better job prospects and living conditions.
Despite the region's enormous economic success, there have been concerns about the country's institutional and governance quality. According to Barabashev and Klimenko (2017), the country went through an unrestrained period of modifications of its public governance system following the collapse of the USSR in 1991, which he inherited from the previous administration. Though some studies have found a significant improvement in institution quality, others have claimed that the quality is not temporary and has had no major positive influence on the economy.
According to Azarhoushang and Rukavina (2014), Russia is suffering from a resource curse as a result of poor institutional quality, which could provide a severe barrier to attaining long-term economic growth. According to Burakov (2015), the quality of Russia's legal institutions has been weakened by corruption, bribery schemes, and other factors, all of which have a negative impact on the country's economic progress. According to Puffer and McCarthy (2007), the
1 The Commonwealth of Independent States (CIS) is an association that coordinates the facilitation of free movement of goods, services, labor force, and capital between member states. It also promotes cooperation on security matters.
weak legitimacy of formal institutions and low level of generalized trust in Russia are the outcome of a failure to properly introduce property rights throughout the privatization process. As a result, long-term economic and governance issues have arisen.
According to the UNCTAD (World..., 2013) assessment, the Kremlin has significant investment potential due to its vast natural resources and unique geographical location between the East and the West. However, its position as a beneficiary of FDI has not been complemented. The institutional quality in terms of formal business norms is one of the possible causes for this phenomenon. Although, according to Seyoum (2009), weak institutions may still be able to attract FDIs due to geographical advantages such as the presence of natural resources, big ravenous markets, and inexpensive labor. Gel'man and Zavadskaya (2020) point out some advantages, noting that Russia employs a variety of governing structures. There were countless examples of better-than-expected governance in a variety of policy areas and geographic places. Some of the early 2000s policy improvements, on the other hand, have generated beneficial consequences. This progress is mirrored in Russia's position and score in Transparency International's Corruption Perception Index, where it scored 30/100 and was ranked 129/180 in 2020, up from 21/100 and 154/180 in 2010 (Corruption., 2020). Gel'man and Zavadskaya (2020) argued that certain post-2000s policy in Russia has resulted in beneficial consequences. However, there hasn't been the same level of success in the areas of voice and accountability, as well as regulatory control, with estimates indicating a declining trend in corruption control and regulatory quality. This is an issue that was also brought up by (Burakov, 2015; Puffer, McCarthy, 2007).
THEORETICAL FRAMEWORK
Existing theories attempt to explain migration dynamics and determinants. These include, but are not limited to, the old classical migration theory, the Pull-Push theory, and the new economics labor migration theory. Despite their strong foundations, none of these theories were able to explain the causal link between institutions and international migration. More attention has been paid to the role of governance quality in economic development in the literature on institutions. Regardless, migration plays a critical role in a country's growth, particularly in the labor market, by providing skilled and unskilled human resources. As a result, the institution's contribution in the migration process may not be deemed insignificant.
North's seminal work from 1990 suggested that institutions help to shape the collection of incentives and motives that influence human behavior and decisions.
A. Valei, S.O. Mamman
These options may include deciding to stay in or change the environment to achieve a better institutional structure in the former case, but a depraved structure in the latter case. Furthermore, the framework of the New Economics of Migration theory in analyzing the nexus between the two component factors indicates that migration decisions are made collectively by the entire household, rather than solely by individual choice. In most cases, migrants' actions are impacted by a complex combination of influences forged within their home country. Given that the Pull-Push theory has explained socioeconomic determinants of migration such as income disparities, unemployment, population, and better living conditions, incorporating the institutional concept into the study could be crucial, as it also indicates the political dimension to international migration that influences migrants' decision to leave or stay.
There are two threads in the existing literature on the institution's relationship with international migration. The first explains how migration affects the institution. These findings are in line with those of (Barsbai et al., 2017; Batista, Vicente, 2011; Beine, Sekkat, 2013; Edo, Rapoport, 2019; Li et al., 2017; Pfutze, 2012; Piper, Rother, 2015; Tran et al., 2017; Tran et al., 2019), who found that international migration has a positive and significant impact on the institutional quality of the home country through return emigrants. The positive role of migration in promoting institutional quality development in home countries is largely predetermined by the spillover effects of migrants from less developed countries transmitting and dispersing attitudes and behaviors back home that were engrossed in the developed host countries, according to Tran et al. (2017). More importantly, they have encouraged democratization (Barsbai et al., 2017; Piper, Rother, 2015) and the political system of their home country in the majority of cases, whether through diaspora or return channels. In addition to the diaspora and return channels of transmission, (Cooper et al., 2006; Kapur, 2010) have highlighted the prospect and absence channels as alternative ways in which migration influences the institutional quality of the home nation. Though it is considered that the diaspora and return channels have a favorable impact on institutional quality, the prospect and absence channels have a detrimental impact.
On the one hand, (Ariu et al., 2016; Bergh et al., 2015; Bertocchi, Strozzi, 2008; Gignarta et al., 2020; Nga Ndjobo, Certo Simoes, 2020; Nifo, Vecchione, 2014; Poprawe, 2015) identified the impact of institution on international migration. The quality of institutions, according to Ariu et al. (2016), has a beneficial impact on the net inflow of college-educated migrants. According to the study, college graduates are more willing to relocate to nations with high institutional quality regardless of cost, whereas those who are less educated and competent are not. Conversely, Bertocchi and Strozzi (2008) explained that migration decisions are
made over a long time horizon, and democratic countries with greater economic freedom are more appealing destinations than others. Also, rather than academic pressure, the quality of an institution is a more distinguishing reason why people migrate from poor to rich countries. According to Bergh et al. (2015), absolute poverty and poor institutions operate as a push-factor for emigration; however, while migration may be impossible for absolute poverty owing to financial constraints (as it confines it), a weak institution may be the primary reason individuals leave. Poor institutional quality, according to Poprawe (2015), leads to corruption, which pushes people to migrate.
Because the majority of migration flows occur from developing to developed countries, which the conventional literature has attributed to income disparities, studies such as (Gignarta et al., 2020; Nga Ndjobo, Certo Simoes, 2020) have discovered evidence of weak institutions as a determinant of emigration from developing countries. Gignarta et al. (2020) discovered that economic freedom and institutional quality are important drivers of migratory flow in a study of 44 African nations. The study considered socioeconomic and demographic aspects such as the size of the population, income levels, culture, and the physical distance between the migrants' home and destination nations.
METHODOLOGY
Panel data analysis was used in the study to investigate the role of institutional quality in international migration in a regional context. Given the assumption of migration pull to Russia, the gravity-based model was chosen. The gravity-based model was estimated using Santos Silva and Tenreyro (2010) Poisson Pseudo Maximum Likelihood (PPML) technique, which follows the conventional literature that has investigated the relationship between institutions and migratory movements. Also, this is based on the notion that larger economies have more influence over smaller economies and that states in close proximity are more intimately linked than states further apart as highlighted by Bergh et al. (2015). This might be applied to Russia's situation in East Europe and several Asian neighbors. As a result of the foregoing, the study introduced two models, which are as follows:
Imgu = + y0Soci°1,t(host) + 7iInstiQual(Host)i:t + 72geoit + yMP°lu + eu. (1)
Equation 1 tries to determine the role of institutional quality on immigrants in the host country as equation 2 determines the role of institutional quality on immigrants in their home country.
Img,,t = + P0S°Ci°U(home) + filInStiQual(Home)i t + ft2ge°it + PMP°l,t + . (2)
Img.t is the number of immigrants into Russia across i countries at time t, Socio. tvector of socioeconomic factors such as the GDP per capita of the host country, unemployment rate, and population size, InstiQual.t vector of institutional qualities of the host countries, Mpol.t is a dummy introduced to capture the various migration regime policy categorized into periods of restrictive and less restrictive labor migration laws, a to capture the proximity (physical distance in kilometres) between the home and host country and is the error term.
DATA
Annual data on migration flows to Russia from the CIS plus was used from 1997 to 2019. There are 11 countries in the Commonwealth of Independent States (CIS) (with exception of Russia). Armenia, Azerbaijan, Belarus, Georgia, Kazakhstan, Kyrgyzstan, Moldova, Tajikistan, Turkmenistan, Ukraine, and Uzbekistan are among these countries. Norway, Finland, Estonia, Latvia, Lithuania, Poland, Mongolia, China, and North Korea are among the neighboring countries with Russian borders. The data on migration came from the Rosstat database of the Russian Federal State Statistics Service. The working population, unemployment, and GDP per capita, on the other hand, were taken from the World Bank's World Development Indicator. While the World Bank produces institutional quality measures, the World Governance Indicator is developed by the World Bank (Kaufmann et al., 2011). Voice and Accountability, Political Stability and Violence Absence, Government Effectiveness, Regulatory Quality, Rule of Law, and Corruption Control are some of the institutional indicators. Table 1 provides a brief overview of the data.
Table 1
Indicators of Institutional quality
Variable Description Measurement
1 2 3
Control of Corruption (corruption) Reflects perceptions of the extent to which public power is exercised for private gain, including both petty and grand forms of corruption, as well as 'capture' of the state by elites and private interests Ranges from approximately -2.5 (weak) to 2.5 (strong)
Rule of Law (rule) Reflects perceptions of the extent to which agents have confidence in and abide by the rules of society, and in particular the quality of contract enforcement, property rights, the police, and the courts, as well as the likelihood of crime and violence Ranges from approximately -2.5 (weak) to 2.5 (strong)
Regulatory quality (regulatory) Reflects perceptions of the ability of the government to formulate and implement sound policies and regulations that permit and promote private sector development Ranges from approximately -2.5 (weak) to 2.5 (strong)
1 2 3
Government Effectiveness (effectiveness) Reflects perceptions of the quality of public services, the quality of the civil service and the degree of its independence from political pressures, the quality of policy formulation and implementation, and the credibility of the government's commitment to such policies Ranges from approximately -2.5 (weak) to 2.5 (strong)
Political Stability and Absence of Violence / Terrorism (stability) Political Stability and Absence of Violence / Terrorism measures perceptions of the likelihood of political instability and/or politically motivated violence, including terrorism Ranges from approximately -2.5 (weak) to 2.5 (strong)
Voice and Accountability (voice) Reflects perceptions of the extent to which a country's citizens are able to participate in selecting their government, as well as freedom of expression, freedom of association, and a free media Ranges from approximately -2.5 (weak) to 2.5 (strong)
Source: Worldwide..., 2020.
RESULT AND DISCUSSION
Table 2 provides an overview or descriptive information for both the migrants' home countries and their destination or host country (Russia). In terms of migration data, we found that the largest number of entrants to Russia in a year was roughly 235,903 persons, with a minimum of 11 people. The mean value, on the other hand, was utilized as a benchmark for later categorization of Russian migrants.
Table 2
Descriptive statistics
Variable Obs Mean Std. Dev. Min Max
Immigration 394 19156.66 31799.02 11.00 235903.00
GDPpc (host) 437 9527.81 2222.97 5505.70 12011.53
Unemploy (host) 437 7.48 2.49 4.59 13.26
Popul (host) 437 144000000.00 1574316.00 143000000.00 148000000.00
Inst. variables
Voice (host) 437 -0.78 0.28 -1.13 -0.31
Stability (host) 437 -0.97 0.25 -1.51 -0.53
Effectiveness (host) 437 -0.38 0.22 -0.73 0.15
Regulatory (host) 437 -0.38 0.13 -0.58 -0.12
Rule (host) 437 -0.86 0.10 -1.10 -0.72
Corruption (host) 437 -0.95 0.10 -1.13 -0.76
Table 3's estimates show that the host country has struggled with some institutional variables. For example, political stability, voice and accountability, and corruption control all had negative values of -1.51, -1.13, and -1.13, respectively, whereas government effectiveness had a high and positive score
of 0.15. Table 3 reveals that several of the origin countries scored worse than the host country (Russia) on all measures, with political stability and regulatory quality being the most important given their minimal values.
Table 3
Descriptive statistics
Variable Obs Mean Std. Dev. Min Max
GDPpc 436 11795.26 20364.02 367.63 92556.32
Unemploy 437 8.89 4.12 2.49 20.71
Popul 437 79800000.00 293000000.00 1314545.00 1400000000.00
Inst. variables
Voice (home) 437 -0.28 1.17 -2.26 1.78
Stability (home) 437 0.04 0.81 -2.02 1.76
Effectiveness (home) 437 -0.03 0.96 -1.64 2.26
Regulatory (home) 437 -0.02 1.06 -2.13 1.88
Rule (home) 437 -0.17 1.04 -1.64 2.10
Corruption (home) 437 -0.21 1.08 -1.54 2.46
Table 4
Unit root test
Variable 1st Gen. IPS First Diff. 2nd Gen. Pesaran First Diff.
Immigrants -0.44 -5 84*** 2.12 -0.98
GDPpc 0.91 -5 53*** -2 59***
Unemployment -1.08 -8 23*** 4 37***
Population 9.26 -0.39 5.98 -3.26***
Voice & Accountability 0.59 -8.68*** -2.56***
Political stability -1.56* -1.51*
Government Effectectiveness 0.68 -10.64*** -1.85**
Regulatory Quality 0.39 -10.16*** -1.63*
Rule of Law 0.2 -9 35*** -1 9**
Control of Corruption 1.44 -10.0*** -0.32 -3.67***
The maximum figures, on the other hand, demonstrate that certain countries outperformed Russia across the board. This study further carried out a panel unit root test of (Pesaran, 2007) which takes account of cross-sectional dependence and that of (Im et al., 2003) followed by N (the cross sectional dimension. The result reveals a different level of stationarity (see Table 4).
ESTIMATES
Table 5 shows the full sample estimate of the effect of institutional quality on migratory flow in the host country. The socioeconomic aspects, on the other hand, are consistent with the theoretical underpinning. For example, Russia's
GDP per capita indicates that an increase in GDP per capita may result in an increase in migrant flow. The same result was reported for the migrants' host country, indicating that as GDP per capita rises, so does migration flow. The result also demonstrates the inelasticity of economic progress to migration. That is, migration is less sensitive to changes in GDP per capita. This, however, suggests that living standards have a significant impact on migration flows. Furthermore, Russia is one of the region's largest economies and a diverse range of natural resources. Unemployment and the population of the migrant's origin also play a significant role in the migration flow. They suggest that rising unemployment and population may act as a catalyst for migration.
Table 5
Estimated result
Variable Mod 1 Mod 2 Mod 3 Mod 4 Mod 5
log(gdppc) -0.169*** (0.00827) -0.165*** (0.00873) -0.167*** (0.00851) -0.212*** (0.00910) -0.0251 (0.0171)
log(gdppc)rUs 0.254*** (0.0442) 0.280*** (0.0422) 0.187*** (0.0470) 0.218*** (0.0435) -0.0365 (0.0352)
log(pop) 0.0158** (0.00781) 0.0215** (0.00887) 0.0216*** (0.00837) 0.0370*** (0.00765) -0.00615 (0.00712)
Unemploy 0.00690** (0.00317) 0.00767** (0.00305) 0.00211 (0.00282) 0.00270 (0.00236)
Migpol 0.123*** (0.0263) 0.124*** (0.0242) 0 114*** (0.0166)
Voice -0.161*** (0.0208)
Stability -0.0706*** (0.0145)
Effectiveness 0.112*** (0.0380)
Regulatory 0.176*** (0.0263)
Rule -0.205*** (0.0473)
Corruption -0.137*** (0.0272)
log(geo) -0.164*** (0.0192) _0 195*** (0.0174)
Constant 0.947** (0.393) 0.519 (0.417) 1 347*** (0.450) 2.466*** (0.410) 4.000*** (0.364)
Observations 393 393 393 393 393
R-squared 0.429 0.436 0.463 0.552 0.796
Notes: Robust standard errors in parentheses. *** p < 0.01, ** p < 0.05, * p < 0.1.
The institutional effect was varied but significant. Institutional indicators such as government effectiveness and regulatory control, for example, have a positive effect on migration inflows. Factors such as voice and accountability, political stability, rule of law, and corruption control, on the other hand, have a negative impact on migration flow. Given this, we can deduce that migrants are more receptive to government macroeconomic policies than to governance structures. However, there is some contextual evidence of poor institutional quality in terms of corruption control and regulatory control; improvements in these areas may encourage migrants to relocate to Russia, as most migrants do (especially investors). This is significant because it demonstrates the government's ability to create and enforce effective rules and regulations that allow and encourage private-sector development. This is significant because it demonstrates the government's ability to create and enforce effective rules and regulations that allow and encourage private-sector development. In line with this, Puffer and McCarthy (2007) ascribed the failure of a proper introduction of property rights to a lack of formal institutions and a low degree of trust.
Migration policy estimates show that it has a positive and significant effect on migrants' inward movement. This implies that the less restrictive the policy, the more migration policy is fostered. Finally, geographical proximity indicates the farther the migrants' location, the less willing they are to move. Again, when combined with CIS migration law, the inflow of migrants from neighboring CIS countries is much easier than the rest of the world.
Estimates in Table 6 show the impact of migrants' home institutions on migration. The outcome is less robust than previous estimates for the migrants' destination. For example, while economic growth and other socioeconomic factors continue to be important push factors for migration, the migrants' institutional quality shows no evidence of influencing migration flow to the host country. This could imply that there is no institutional push effect of migrants to Russia.
Table 6
Estimated result
Variable Mod 1 Mod 2 Mod 3 Mod 4 Mod 5
1 2 3 4 5 6
l°g(gdPPc) _0 174*** (0.00761) -0.172*** (0.00768) -0.172*** (0.00766) -0.214*** (0.00940) -0.215*** (0.00932)
log(gdPPc)ras 0.643*** (0.0732) 0.668*** (0.0739) 0.846*** (0.150) 0.883*** (0.140) 0.581** (0.247)
log(PoP) 10.51*** (1.772) 10.65*** (1.776) 14 10*** (3.157) 14 39*** (2.906) 11.52*** (4.373)
Unemploy 0.00487** (0.00238) 0.00468* (0.00239) -0.00168 (0.00227) -0.00193 (0.00224)
1 2 3 4 5 6
Migpol -0.0659 (0.0466) -0.0691 (0.0437) 0.0157 (0.112)
Volce(0) -0.143 (0.211)
Stability(0) 0.0470 (0.115)
Effectiveness^ -0.108 (0.217)
Regulatory(0) 0.0743 (0.258)
Rule(0) 0.0735 (0.189)
Corruption^ -0.202 (0.234)
lgeo -0.142*** (0.0205) -0.143*** (0.0204)
Constant —1998*** (33.84) -202.6*** (33.93) -269.2*** (60.61) -273 5*** (55.78) -217 1*** (83.56)
Observations 393 393 393 393 393
R-squared 0.469 0.473 0.475 0.547 0.554
Notes: Robust standard errors in parentheses. *** p < 0.01, ** p < 0.05, * p < 0.1.
ROBUSTNESS CHECK
Based on the frequency of flow to Russia, a sub-sample estimate was performed. Armenia, Azerbaijan, Belarus, China, Georgia, Kazakhstan, Kyrgyzstan, Moldova, Tajikistan, Turkmenistan, Ukraine, and Uzbekistan are among the countries with a high frequency, whereas Estonia, Finland, Lithuania, Latvia, Mongolia, Norway, and Poland are among the countries with a low incidence. The same approach was used to investigate the impact of origin and destination institutional quality on migration to Russia. We looked at countries with high-frequency flow in the first scenario. Table 7 depicts the effect of institutional quality on migratory flow in the host country. Where the socioeconomic factors are still consistent in terms of sign and significance, there was similar outcome for the institutional qualities with the estimates in Table 5. But unlike the voice & accountablility of the host country (Russia) which was negative in the previous estimates, this indicator was positive and significant in the current estimate. This could explain why migrants feel safe in countries where they can express themselves. Though Russia is not a democratic country, migrants are given preferential treatment if they follow the country's laws and order. Again, the result of the high incidence sub-sample for migrant origin in Table 8 indicates consistency with the estimates in Table 6, revealing no significant impact of institution on their movement.
The second sub-group assessed the low migration incidence flow using institutional quality from home and destination. Table 9 shows two distinct features of the first case, which was evaluated based on Russia's institutional quality. To begin, only three of the six indicators were significant, with only regulatory quality and corruption control being positively associated with migration flow. Rule of law, on the other hand, was found to be negatively associated with migration. Second, the origin of the migrants' population was discovered to be a strong demographic factor that was negatively associated with migration flow. This means that as the population grows, so does the flow of migrants to Russia. While this may appear counter-intuitive, we can understand it in terms of declining population growth. Also, keep in mind that this is a low-inflow category of migrants to Russia. Another intriguing fact is that, with the exception of Mongolia, virtually all of the low-frequency countries outperform Russia in several categories. As a result, we can deduce that, aside from proximity, they may be sensitive to certain institutional and social factors. Lastly, Table 10 shows the role of migrants home institutional quality on migration flow in the low frequency countries. In this case, the estimates reveal a consistent result with the previous sections of migrants' home institutional quality of no significant effect on migrants' movement.
Table 7
Sub-sample estimates
Variable Mod 1 Mod 2 Mod 3 Mod 4 Mod 5
1 2 3 4 5 6
log(gdppc) -0.00543 (0.00987) -0.00368 (0.0100) -0.00811 (0.00989) -0.0252** (0.0126) 0.00511 (0.0130)
log(gdppc)rus 0.0737** (0.0347) 0.0816** (0.0338) 0.0181 (0.0351) 0.0380 (0.0358) 0.0308 (0.0287)
log(pop) -0.0133* (0.00698) -0.0108 (0.00727) -0.0109 (0.00685) -0.00184 (0.00613) 0.00953* (0.00574)
Unemploy 0.00245 (0.00190) 0.00238 (0.00176) 0.00218 (0.00172) 0.00774*** (0.00154)
Migpol 0.0853*** (0.0170) 0.0873*** (0.0162) 0.107*** (0.0142)
Voice 0.0293** (0.0146)
Stability 0.00615 (0.0128)
Effectiveness 0.0707* (0.0363)
Regulatory 0.0485* (0.0260)
Rule -0.0964*** (0.0366)
1 2 3 4 5 6
Corruption -0.202*** (0.0232)
Igeo -0.0564*** (0.0137) -0.0742*** (0.0138)
Constant 1.862*** (0.289) 1 714*** (0.294) 2.309*** (0.304) 2.540*** (0.301) 2.115*** (0.235)
Observations 250 250 250 250 250
R-squared 0.051 0.056 0.128 0.184 0.468
Notes: Robust standard errors in parentheses. *** p < 0.01, ** p < 0.05, * p < 0.1. Table 8 Sub-sample estimates
Variable Mod 1 Mod 2 Mod 3 Mod 4 Mod 5
l°g(gdppc) -0.0178* (0.00917) -0.0133 (0.00947) -0.0129 (0.00938) -0.0286** (0.0119) -0.0297** (0.0119)
l°g(gdppc)ras 0.372*** (0.0516) 0.381*** (0.0524) 0 547*** (0.101) 0.568*** (0.0980) 0.279* (0.162)
log(pop) 7 875*** (1159) 7.800*** (1.139) 11 04*** (2.065) 11.21*** (1.970) 9 413*** (2.822)
Unemploy 0.00388** (0.00191) 0.00377* (0.00193) 0.00197 (0.00176) 0.00177 (0.00173)
Migpol -0.0616** (0.0298) -0.0618** (0.0283) -0.0108 (0.0740)
Voice(0) -0.183 (0.132)
Stability(0) 0.0149 (0.0763)
Effectiveness^ -0.0171 (0.144)
Regulatory(0) 0.0574 (0.165)
Rule(0) -0.0370 (0.115)
Corruption(0) -0.228 (0.147)
lgeo -0.0594*** (0.0134) -0.0601*** (0.0133)
Constant -148 9*** (22.15) -147 7*** (21.79) -210.0*** (39.67) -212.8*** (37.82) -176.8*** (53.96)
Observations 250 250 250 250 250
R-squared 0.181 0.195 0.206 0.277 0.308
Notes: Robust standard errors in parentheses. *** p < 0.01, ** p < 0.05, * p < 0.1.
A. Valei' Mamman
Table 9
Sub-sample estimates
Variable Mod 1 Mod 2 Mod 3 Mod 4 Mod 5
l°g(gdppc) -0.0486** (0.0243) -0.0278 (0.0203) -0.0291 (0.0186) -0.152*** (0.0116) -0.134*** (0.0370)
log(gdppc)ras 0.0690 (0.0781) 0.200*** (0.0669) 0.0708 (0.0690) 0.0715 (0.0441) 0.0765 (0.0529)
log(pop) -0.109*** (0.0131) -0.116*** (0.0180) -0.116*** (0.0170) -0.0830*** (0.00883) -0.0782*** (0.0126)
Unemploy 0.0275*** (0.00441) 0.0317*** (0.00436) 0.000892 (0.00297) 0.00172 (0.00278)
Migpol 0.190*** (0.0335) 0.137*** (0.0250) 0.113*** (0.0261)
Voice -0.147 (0.120)
Stability -0.0270 (0.0528)
Effectiveness 0.0159 (0.0901)
Regulatory 0.169** (0.0821)
Rule -0.183* (0.109)
Corruption 0.102* (0.0558)
lgeo -0.348*** (0.0309) -0.287*** (0.0511)
Constant 3 211*** (0.732) 1.665** (0.682) 2.780*** (0.670) 6.202*** (0.546) 5 544*** (0.633)
Observations 143 143 143 143 143
R-squared 0.244 0.436 0.522 0.797 0.810
Notes: Robust standard errors in parentheses. *** p < 0.01, ** p < 0.05, * p < 0.1.
Table 10
Sub-sample estimates
Variable Mod 1 Mod 2 Mod 3 Mod 4 Mod 5
1 2 3 4 5 6
log(gdPPc) _0 174*** (0.00761) -0.172*** (0.00768) -0.172*** (0.00766) -0.214*** (0.00940) -0.215*** (0.00932)
log(gdppc)rus 0.643*** (0.0732) 0.668*** (0.0739) 0.846*** (0.150) 0.883*** (0.140) 0.581** (0.247)
log(PoP) 10.51*** (1.772) 10.65*** (1.776) 14 10*** (3.157) 14 39*** (2.906) 11.52*** (4.373)
Unemploy 0.00487** (0.00238) 0.00468* (0.00239) -0.00168 (0.00227) -0.00193 (0.00224)
Migpol -0.0659 (0.0466) -0.0691 (0.0437) 0.0157 (0.112)
1 2 3 4 5 6
Voice (0) -0.143 (0.211)
Stability (0) 0.0470 (0.115)
Effectiveness (0) -0.108 (0.217)
Regulatory (0) 0.0743 (0.258)
Rule (0) 0.0735 (0.189)
Corruption (0) -0.202 (0.234)
lgeo -0.142*** (0.0205) -0.143*** (0.0204)
Constant —1998*** (33.84) -202.6*** (33.93) -269.2*** (60.61) -273 5*** (55.78) -217 1*** (83.56)
Observations 393 393 393 393 393
R-squared 0.469 0.473 0.475 0.547 0.554
Notes: Robust standard errors in parentheses. *** p < 0.01, ** p < 0.05, * p < 0.1.
CONCLUSION
The aim of the research was to determine the effect of institutional quality on migration in both host and destination countries. Several studies identify a possible feedback nexus between institutional quality and international migration after reviewing current and relevant theoretical and empirical literature. The current study used a panel analysis to account for socioeconomic characteristics, which have been shown to be a significant determinant of migration.
The study also conducted a sub-sample estimation of low and high incidence of migration flow to Russia, and the results show that migrants may react differently to a variety of institutional factors. There was evidence of a strong relationship between socioeconomic factors such as GDP per capita, unemployment, population, and migration flow in the total sample, which may support the widely held belief that economic progress is a significant pull factor for migrants. Furthermore, because Russia has one of the largest economies in the region, economic advancement may be more important to migrants from high-frequency countries. Regardless, there was also some evidence from the migrants' home country. There was also indication that a less restrictive migration policy encourages migration policy as Russia's dynamic policy changes over time. The study found that institutional factors in the host country (Russia) are more effective than institutional quality in the country of origin. In many cases, regulatory control and government effectiveness have a positive effect, whereas
factors such as voice and accountability, rule of law, and corruption control have a negative effect.
Except for the case of the low incidence sample, the sub-sample was also consistent with the estimates from the full sample, indicating that there is a quiet effect and sensitivity to institutional quality given that most of the country has better institutions than the host country. Finally, regional proximity was found to be a significant factor in determining migration flow, revealing that the farther a country is from Russia, the less likely migrants will move. According to the study, institutional quality is critical, particularly in migration-hosting countries. Although migrants may respond differently, it is also important to note that these institutional indicators are related in some way. Thus, the findings indicate that to maximize the gains of international migrants, particularly those with an investment opportunity, tourism and other explorable sectors of the economy the quality of institutions should be prioritized.
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Поступила в редакцию / Submitted: 30.03.2022
Одобрена после рецензирования / Approved after reviewing: 02.06.2022 Принята к публикации / Accepted for publication: 22.07.2022 Доступно онлайн / Available online: 30.09.2022
