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27THE IMPACT OF MACROECONOMIC INDICATORS ON THE INTERNATIONAL LABOR MIGRATION BETWEEN UKRAINE AND POLAND
Dankevych V.
Doctor of Economics, Dean of the Faculty of Law, Public Administration and National Security, Polissia National University, Zhytomyr, Ukraine Pyvovar P.
PhD,
Associate Professor of the Department of International Economic Relations and European Integration
Polissia National University, Zhytomyr, Ukraine Prokopchuk O.
PhD,
Associate Professor of the Department of International Economic Relations and European Integration
Polissia National University, Zhytomyr, Ukraine
Horbachova I.
PhD,
Associate Professor of the Department of International Economic Relations and European Integration
Polissia National University, Zhytomyr, Ukraine
Dankevych Y.
Doctor of Economics, Professor of the Department of Economic Theory, Intellectual Property and Public Administration
Polissia National University, Zhytomyr, Ukraine
Pyvovar A.
PhD,
Senior Lecturer of the Department of Management and Marketing,
Polissia National University, Zhytomyr, Ukraine
Abstract
Given the current trends in migration processes that are now one of the global challenges for the development of the national and world economic systems, it is relevant to identify the key factors that affect the labor migration processes. The trends in the development of migration processes were analyzed in the context of Ukraine and Poland. They indicate a) an increase in the number of migrant workers; b) significant changes in employment, the period of stay of migrants, their age and gender structure. The authors identify macroeconomic factors that affect the processes of international labor migration. Stepwise Regression method was applied to determine the factors that influence the processes of labor migration from Ukraine to Poland, and then the models were tested for mul-ticollinearity and heteroscedasticity. As a result, we obtained 29 economic models. The modeling outcomes show that the following macroeconomic factors of the Ukrainian and Polish economies have the most significant impact on labor migration processes: average salary (euro for Poland), average salary (euro for Ukraine), GDP per capita (current US$ for Ukraine), inflation (annual % for Poland), inflation (annual % for Ukraine), official exchange rate (LCU per euro for Poland), official exchange rate (LCU per euro for Ukraine), unemployment (% of total labor force for Poland), unemployment (% of total labor force for Ukraine). The analysis of the obtained models determined that the level of labor migration from Ukraine to Poland is by 82% affected by Ukrainian macroeconomic indicators and by 18% by Polish ones.
Keywords: international labor migration, macroeconomic indicators, Ukraine, Poland, migration structure, modeling.
JEL Classification: J6, J60, J61, J62.
1. Introduction
Transformation of the traditional system of labor relations, exacerbation of the negative consequences of global redistribution of resources between countries
with different levels of development, economic desta-bilization of many countries in recent years have led to the intensification of interstate migration flows. At the same time, historical experience shows that the effects
of migration can be manifested both today and in the long term. They may be local or national, causing both negative challenges and new opportunities for statebuilding processes.
Migration processes occurring in the context of transformations of the international economy and the global problems that arise in connection with this phenomenon are closely related to the political, economic, demographic and social tensions that arise in society. Despite the numerous studies that underpin the analysis of the current state of these processes, there is currently no general theory of migration.
The first scientist who made an attempt to identify certain patterns in the processes of population movement was the English scientist Ernst-Georg Ravenstein who published articles describing the laws of migration in the late 19th century. Ernst-Georg Ravenstein's study was based on the statistical analysis of London residents and their movement from areas of Wales, Ireland and Scotland, which can be considered internal migration. However, the claim that "the largest migration in the world occurs over short distances" is not confirmed by the current flows of migrants who migrate to European countries (Ravenstein, 1876; Ravenstein, 1885). Nevertheless, Ravenstein's concept was the first attempt in the classical theory to comprehend and systematize the movement and adaptation of significant workforce flows.
The work of Samuel Stouffer, published in 1940 is considered as the next stage in the study of the theories and patterns of development of migration processes (Stouffer, 1940). This refers to factors that impede migration flows, including a number of circumstances. The main are the costs of moving and the imperfection of the laws of the countries (obstacles to migration). Stouffer noted that the number of people who migrate is directly proportional to the number of prospects and inversely proportional to the number of negative and unexpected circumstances of migration.
In 1946-1949, George K. Zipf developed the theory of "least effort", the essence of which was that when there is a choice, people choose a behavior that requires the least resistance and cost. As a result of many years of research, the scientist first published a gravity model of migration (Zipf, 2012).
After World War II, the economic situation in European countries changed significantly. The flow of migrants arriving from peripheral countries to Germany, the United Kingdom, and France increased. This required a rethinking of the factors that affect workforce flows that assimilate in new territories after crossing state borders. The most significant study during this period is the theory of the sociologist Everett S. Lee, who published the article "Migration Theory" in 1966 (Lee, 1966). The author investigated various factors that affect the activity of migration movements and divided them into those that contribute to the intensification of workforce movement (pull) and those that impede these processes (push) ("push / pull").
The English economist William Arthur Lewis received the Nobel Prize in 1979 (in collaboration with T. Schultz) for his study of the movement of workforce
flows, which marked the transition in the study of migration to neoclassical theory. His treatises were based on microeconomic principles of supply and demand in the labor market, excess supply of workforce, etc. (Boyd, 2007).
The globalization processes occurring in the world have shifted the direction of the study of the movement of migrant flows within countries into the international stage and the movement of workforce flows between countries. The approach of V. Zelinsky, who considers migration on a global scale, differs significantly from all previous models. Along with the historical approach, his "concept of mobility transition" includes demographic and socioeconomic factors, which he associates with territorial mobility. In his approach, much attention is paid to the globalization processes (Zel-insky, 1971).
In fact, D. Massey's theory of migration networks is contiguous to Ukraine (Massey, 2002). The theory describes close family, friendly, regional ties between arrivals, which help them reduce the risk of moving and finding a new job. This doctrine indicates that migrant workers maintain a close relationship with their family, relatives, etc. One of the key theories explaining migration in Ukraine is also the theory of world systems by I. Wallerstein (1974, 1989) based on the division of countries into different groups: central, semi-peripheral, peripheral and isolated. Intensification of globalization stimulates the outflow of unemployed people from peripheral countries to central ones, which is encouraged by multinational corporations interested in cheap workforce (Wallerstein, 2011). I. Wallerstein argues that there are two sectors in the economies of developed countries: 1) a sector related to modern industrial production which requires a highly skilled workforce with a high level of wages; 2) a sector of low productive services with low level of salary and low requirements to the qualification of workers (trade, transport, services, etc.). These are the sectors of the economy that attract emigrants from Ukraine, which is beneficial for the entrepreneurs of the recipient country.
In modern science, the problem of interstate migration is also quite relevant. A significant number of scholars focus on the specifics of labor migration in their publications. Thus, M. Benson and K. O'Reilly explain labor migration with the specifics of modern lifestyle (Benson & O'Reilly, 2016). P. Zuk, P. Zuk explore the most common models of labor migration through the example of Eastern European countries (Zuk & Zuk, 2018). L. Mugge, M. van der Haar investigate trends in labor migration and identify problems of integrating migrant workers into the social life of the recipient country (Mugge & van der Haar, 2016). W. Strielkowski, Y. Tumanyan and S. Kalyugina evaluate the impact of labor market regulators on the process of attracting migrant workers (Strielkowski, Tumanyan, & Kalyugina, 2016). At the same time, a large number of issues related to factors that affect migration flows remain underinvestigated.
The purpose of the study is to identify the macro-economic factors that influence the processes of international labor migration using the case study of Ukraine and Poland.
The question of the study is the following: "Is the impact of macroeconomic indicators of a donor country or a recipient country a major (determining) catalyst for the processes of interstate labor migration?"
We will try to find an answer to this question by examining the case of Ukraine and Poland, namely the factors that affect the trends and structure of interstate migration processes.
The hypotheses of this study are the following:
1. Macroeconomic indicators of the socioeconomic development of a donor country have a determining influence on the processes of interstate labor migration.
2. Macroeconomic indicators of the socioeconomic development of a recipient country have a determining influence on the processes of interstate labor migration.
In the course of the study, it is planned to verify or disprove the hypotheses using the statistical data of Poland and Ukraine and applying the methods of economic and mathematical modeling.
This study is important because labor migration processes have a significant impact on the development of the economy, both of donor and recipient countries; and the changes in the social and cultural spheres occur.
Scoping Review and Research
In recent years, the problem of migration has gone beyond national borders and is of a global nature. Furthermore, it is multidirectional, which is determined by the goals of national migration policies and the impact of global trends in world processes. Today, the main trends are:
The migration policy in the developed countries, in particular members of the European Union, is shaped by two priority directions: a) deterring the illegal migration activity of refugees from Muslim countries; b) liberalization of the regime for migrants from the countries of Eastern Europe in order to minimize national manifestations of the demographic crisis (reduction in the size of population and its aging) and solve problems in the labor market.
At present, the efforts of the scientific and political community are focused mainly on the implementation of measures within the first strategic direction, since the problem of illegal migration has become geopolitical. As a result, there is an active securitization of countries that is primarily focused on national security rather than population security (Estevens, 2018). However, there are supporters of a more liberal approach to migration barriers in the scientific and governmental circles; they stand for the need to lobby for the rights of refugees and to consider the causes of their activity (Frelak, 2017). This is based on findings of the studies which show that the main factors of active migrant movement to Europe is the ability to solve urgent life problems by rapidly obtaining citizenship, expanding social and economic opportunities. Instead, the opportunity to get education plays only a minor role in decision making (Tucker, 2018).
In countries with lower levels of development, there is a rapid increase in migration activity of the population. For example, in Ukraine the movement of peo-
ple of working age with different educational and qualification levels is becoming large-scale. The scientific community emphasizes that international migration is one of the greatest challenges for Ukraine's future, since its intensification presents a steady decline in the human capital of the country. Scientists point out that Ukraine is one of the major suppliers of cheap labor for European countries, where liberalization of migration policies combined with the lack of regulatory restraining measures by the national government could lead to catastrophic consequences (Olga Gulina, 2018). Instead, the activities of national authorities are aimed at liberalizing relations with other countries, in particular in regard to population movement. This is confirmed by the introduction of a visa-free regime between Ukraine and the EU.
Given the trends outlined above, it can be argued that the current migration problem is global in nature and can be solved provided that national efforts are consistent, which will make it possible to alleviate the impact of global externalities and take into account the specifics of individual countries. An important step in reaching the consensus of national migration policies was the adoption of the Global Compact for Migration. The Global Compact for Safe, Orderly and Regular Migration was endorsed by the UN General Assembly in 2018; it is a treaty that defines a comprehensive approach to addressing the problem of migration on a global scale. It sets the framework for international cooperation in the field of migration and is based on the preservation of national and universal human values. The Treaty contains 23 goals and a number of practical measures for regulating international migration based on focusing the efforts of global community on the causes of migration and creating a favorable environment for migrants ("Global Compact for Migration", 2018).
Particularly important in addressing migration problems are the so-called "buffer countries", which have a transit geographical position between highly developed and developing countries. Ukraine and Poland fall into this category.
In recent decades, Poland has had a negative migration balance; and it is a country of emigration (Ag-nieszka Chlon-Dominczak, 2015). The lower level of economic development in comparison with other countries of the European Union encourages the Poles to move abroad in the western direction, both for temporary and permanent residence. This exacerbates the problems of demographic decline and labor shortages in the domestic labor market. Therefore, migration policy in Poland is aimed at the gradual liberalization of the conditions for the arrival of migrants from Eastern countries, in particular Ukraine. The Ukrainians are close to the Poles in cultural and linguistic terms and do not pose a significant challenge in terms of integration. Particular priority is given to people of Polish ancestry who live abroad. However, according to some scholars, Poland's migration policy is not consistent, so migrants face numerous obstacles to active participation in the labor market, including lack of language skills, legal complications and unequal treatment from employers (Frelak, 2017).
Another special feature of Polish migration policy is that it is under constant observation and pressure from the European Union, in the light of the fact that the country is a central European buffer zone between the EU and the countries of the East (Iglicka, 2001).
In terms of migration, Ukraine also belongs to the so-called "buffer countries". This gradually made the issues related to migration from Ukraine to EU countries relevant for both Ukrainian and European scientists (Danzer & Dietz, 2014). The relevance of this problem for European scholars is determined by two main factors: 1. Ukraine is one of the leading countries of origin of migrants arriving to the EU (van Mol, Snel, Hemmerechts, & Timmerman, 2018) (van Mol & Valk, 2016); 2. Migration flows from Ukraine to the EU are the largest among all post-Soviet countries (Fedyuk & Kindler, 2016).
The study of the scientists is mainly focused on the methodological aspects of the analysis of migration processes and on determining the factors that influence the active migration from Ukraine to the EU (van Mol et al., 2018). However, measures in regard to addressing the migration problem remain underinvestigated. Given the urgency of this issue for Ukraine and the potential importance and role of the country in solving the migration problem on a global scale, it is relevant to substantiate the system model of migration processes based on the current trends in their development and the factors that identify them.
2. Methodological approach
Study phases:
Data collection. In order to achieve the goals, we have formed three data sets for the period 2011-2018:
Macroeconomic indicators as factor indicators that affect labor migration processes: Inflation, consumer prices (annual %) - Inflation as measured by the consumer price index reflects the annual percentage change in the cost to the average consumer of acquiring a basket of goods and services that may be fixed or changed at specified intervals, such as yearly (X11 -for Ukraine, X21 - for Poland); Unemployment, total (% of total labor force) - Unemployment refers to the proportion of the labor force that is without work but available for and seeking employment. Definitions of labor force and unemployment differ by country (X12
- for Ukraine, X22 - for Poland); GDP per capita (current US$) - GDP per capita is a gross domestic product divided by the midyear population. GDP is the sum of gross value added by all resident producers in the economy plus any product taxes and minus any subsidies not included in the value of the products. It is calculated without making deductions for the depreciation of fabricated assets or for the depletion and degradation of natural resources. Data are in current U.S. dollars (X13
- for Ukraine, X23 - for Poland); Average salary, LCU (local currency unite) - Wages and salaries of those workers who hold the type of jobs defined as "paid employment jobs", where the incumbents hold explicit (written or oral) or implicit employment contracts that give them basic remuneration that is not directly dependent upon the revenue of the unit for which they work (X14 - for Ukraine, X24 - for Poland); Average
salary, euro (X15 - for Ukraine, X25 - for Poland); Official exchange rate (LCU per Euro) - Official exchange rate refers to the exchange rate determined by the national authorities or the rate determined in the legally sanctioned exchange market. It is calculated as the annual average based on monthly averages (local currency units relative to the Euro) (X16 - for Ukraine, X26 - for Poland) (Worldbank, 2020).
Microeconomic indicators, as outcome indicators that characterize the labor migration processes of the Ukrainians to Poland: Number of applications for work permits (Y1 - for men, Y3 - for women, Y5 - total) and issued work permits (Y2 - for men, Y4 - for women, Y6
- total) Share of approved work permits, % (Y7 - for men, Y8 - for women); Number of work permits issued by type (Type A - Y9, B- Y10, C- Y11, D- Y12, E-Y13) (Type A permit is issued for a foreigner working in Poland, based on a contract with an entity whose registered office, place of residence, branch, plant or other form of organized activity is located in Poland. A type B permit applies to a foreigner who: performs a function on the management board of a legal entity entered in the register, undertakes entrepreneurial activity, performs the function on the management board of a legal entity which is a limited company in the organization, conducts cases of a limited partnership or a limited joint-stock partnership as a general partner or proxy - if in subsequent 12 months he served this function for over 6 months. In addition to A and B type permits, you can still apply. Type C permit - applies to a foreigner working in a foreign company and delegated to work in Poland for more than 30 days a year. Type D permit applies to a foreigner temporarily posted to work in Poland and employed in a foreign company that has no branch or branch in Poland. Type E permit - applies to a foreigner delegated to work in Poland for more than 30 days within the next 6 months (MRPiPS, 2020). Number of issued work permits, respectively, by industry (building - Y16, industry - Y15, transport and logistics - Y18, wholesale and retail - Y17, households
- Y25, activities related to accommodation and catering services Y19, scientific and technical activities - Y22, agriculture and related industries - Y14, information and telecommunications Y20, health social sector -Y24, financial Activities And Insurance - Y21, education - Y23). Terms for which work permits are issued (up to 3 months - Y26, from 3 months to 1 year - Y27, from 1 year to 2 years- Y28, more than 2 years - Y29).
Analysis of the sample
A cross-sectional dataset will be built in our case. Cross-sectional data analysis is when you analyze a data set at a fixed point in time (one year). Surveys and government records are some common sources of cross-sectional data. The datasets record observations of multiple variables at a particular point of time.
Analysis of outliers
For the analysis of outliers, 4 techniques were used, using which no outliers and other anomalies were detected: Outlier detection using Robust Kernal-based Outlier Factor (RKOF) algorithm (Ester, Kriegel, Sander, & Xu, 1996), Outlier detection using depth based method (Johnson, Kwok, & Ng, 1998)(Johnson, Kwok, & Ng)(Johnson, Kwok, & Ng)(Johnson, Kwok,
& Ng), Outlier detection using k Nearest Neighbours Distance method (Hautamaki, Karkkainen, & Franti), Outlier detection using kth Nearest Neighbour Distance method (Ram, Jalal, Jalal, & Kumar, 2010).
Correlation analysis
Correlation analysis is used in this work to quantify the extent to which two variables are related. Using correlation analysis, we estimated a correlation coefficient that shows how much one variable changes when another changes. Correlation analysis shows a linear relationship between two variables.
Selection of factors for regression
In statistics, stepwise regression is a method of fitting regression models in which the choice of predictive variables is carried out by an automatic procedure. In each step, a variable is considered for addition to or subtraction from the set of explanatory variables based on some prespecified criterion. Usually, this takes the form of a sequence of F-tests or t-tests, but other techniques are possible, such as adjusted R2, Akaike information criterion, Bayesian information criterion, Mal-lows's Cp, PRESS, or false discovery rate (SAS Institute Inc., 1989).
The frequent practice of fitting the final selected model followed by reporting estimates and confidence intervals without adjusting them to take the model building process into account has led to calls to stop using stepwise model building altogether or to at least make sure model uncertainty is correctly reflected (Efron & Tibshirani, 1998).
The main approaches are:
Forward selection, which involves starting with no variables in the model, testing the addition of each variable using a chosen model fit criterion, adding the variable (if any) whose inclusion gives the most statistically significant improvement of the fit, and repeating this process until none improves the model to a statistically significant extent.
Backward elimination, which involves starting with all candidate variables, testing the deletion of each variable using a chosen model fit criterion, deleting the variable (if any) whose loss gives the most statistically insignificant deterioration of the model fit, and repeating this process until no further variables can be deleted without a statistically significant loss of fit.
Bidirectional elimination, a combination of the above, testing at each step for variables to be included or excluded.
Test:
Multicollinearity
Determining the level of multicollinearity is also important when constructing regression equations, the higher it is, the greater is the probability of statistically insignificant regression parameters. There is an indicator that can be used to determine the level of multicol-linearity. It is called the variance inflationary factor (VIF). For its calculation it is necessary to construct a series of regression equations - dependences of the corresponding factor xi on other factors of the model. Researchers use the value VIFi = 10 as critical. If VIFi <
10, then the relationship between the ith factor and all others may be insufficient. If VIFi > 10, this indicates multicollinearity.
Heteroscedasticity
Heteroscedasticity - a concept used in applied statistics (most often - in econometrics), meaning heterogeneity of observations, expressed in the unequal (variable) variance of the random error of the regression (econometric) model.
The Breush-Pagan test is one of the statistical tests to check for heteroscedasticity of random errors in the regression model. It is used if there is reason to believe that the variance of random errors may depend on some set of variables. Moreover, in this test, the linear dependence of the variance of random errors on a certain set of variables is checked.
3. Results
3.1. Transformations of Ukraine's external migration
Ukraine has traditionally been characterized by a high level of activity of migration processes and has been an exporter of human capital. According to the UN, in the 1990-s of the 20th century the Ukrainian diaspora in the world amounted to almost 7 million people. In recent years, there has been another increase in the rate of emigration, which causes the need to update the issue in scientific, governmental and social circles. The intensification of migration processes is dual in nature and stimulated by both internal (macroeconomic instability, low quality of life and well-being, high unemployment, etc.) and international factors (liberalization of immigration policy and implementation of motivational programs for attracting migrant workers in the European Union countries).
Assessment of trends in the development of interstate migration in Ukraine is complicated by the significant differences in the information base of various official sources, which is explained by differences in methodological approaches of the study. Thus, according to the State Statistics Service of Ukraine, only about 20,000 people leave every year, of them almost 90% are from urban areas (Tab. 1).
It should be noted that according to this information, the external migration balance is positive. This does not fully reflect the objective situation and is explained by the selective record of the population outflow and the forced registration of the arrivals to Ukraine, which is a prerequisite for them to carry out any kind of activity. At the same time, according to the State Border Guard Service, 6.5 million Ukrainians left and did not return between 2002 and 2018.
Most people who crossed the border are migrant workers. According to the State Statistics Committee of Ukraine, these were 1.3 million people (SSSU, 20082019); according to International Monetary Fund 2.3 million people (International Monetary Fund. European Dept., 2019); according to Center for Economic Strategy 4 million people.
Table 1.
Indicators of external migration processes in Ukraine
Indicator Year 2018 p. go 2011, +/-
2011 2013 2015 2017 2018
Migration movement of the population, individuals
the number of arrivals persons 31684 54100 30659 28360 39307 7623
the number of persons leaving the country 14588 22187 21409 20234 24252 9664
migration increase (+), decrease (-) 17096 31913 9250 8126 15055 -2041
Structure of persons leaving the country by type of settlements,%
urban 83,6 89,6 87,2 89,8 85,1 1,5
rural 16,4 10,4 12,8 10,2 14,9 -1,5
Source: (SSSU, 2008-2019).
According to the Center for Economic Strategy, taking into account the temporal structure of emigration (34 % - pendulous, 20 % - long-term, 20 % - short-term, 14 % - people who did not return, 10 % - illegal) there were 2.6-2.7 million Ukrainian citizens abroad at the same time in 2002-2017 (CES, 2019).
The main recipient countries of Ukrainian emigrants for the period 2015-2017 are Poland (38.9 %), the Russian Federation (26.3 %), Italy (11.3 %) and the Czech Republic (9.4 %). Whereas until 2015, flows to the Russian Federation accounted for the largest share (over 40 %) (SSSU, 2008-2019).
Regarding the structure of migration flows by period, it should be noted that during 2008-2017 the share of long-term trips that lasted more than 6 months gradually decreased from 35 % to 21 %. In recent years, 79 % of migrant workers have been abroad for less than six months (Center for Economic Strategy, 2019). In terms of the gender structure of migrants in 2008-2017, traditionally, men predominate (over 70%) for most countries except Italy and Hungary, but in 2018 women already accounted for 41.4 %. In the age structure, persons aged 25-40 years make up the major part. Most migrant workers have vocational or secondary education. At the same time, there is a high demand for workers that have higher education in the USA, Israel, Germany and Finland.
The main areas of employment for Ukrainian emigrants are construction (39 %), housekeeping (16 %), and agriculture (14 %). At the same time, in the CIS
countries the main sectors of employment are construction and industrial production, in the EU countries household help and agriculture.
Summarizing the above, the main trends in modern emigration processes from Ukraine are as follows: increase in the number of labor and educational migrants; gradual structural change in migration towards young people with higher level of education and qualifications; territorial reorientation of emigrants from CIS, in particular Russia, to EU countries, specifically Poland.
3.2. Trends in migration processes between Ukraine and Poland
Ukrainian people have always been active participants in interstate migration processes, which have become even more dynamic in recent years due to the low level of quality of life and well-being, the events at east of Ukraine. Given the fact that the main recipient country of Ukrainian emigrants for the period 2015-2018 is Poland (38.9 %) and that the Ukrainians account for the major share of labor immigrants in this country, it is relevant to study the migration processes between these countries, identify major factors that affect labor migration flows (SSSU, 2008-2019).
The intensity of migration processes between Ukraine and Poland is dual in nature and is stimulated by the macroeconomic factors of both countries. In particular, Poland has been actively opening its borders to immigrant workers since 2015, as evidenced by the rapid increase in the number of issued work permits (Fig. 1).
400 350 300 250 200 150 100
Other countries,% Ukrainians,%
■Total work permits for foreigners, thousand
367
236
72%
66
Source: (MRPiPS, 2020).
127/
83%
17% 2016
Figure 1. Dynamics of issuing work permits in Poland
82%
41 50 - 39 39 44
♦26% 0 74% 30% 70% 52% 60% 77%
48% 40% 23%
2011 2012 2013 2014 2015
18% 2017
28%
2018
Almost 70 % of permits were issued to the Ukrainians. The main donors of labor migrants are the western regions of Ukraine, including Lviv, Volyn, Ternopil, Ivano-Frankivsk and Rivne regions. The largest flows of labor are directed to Masovian, Greater Poland, Lesser Poland, Lower Silesian, Pomeranian and Lubusz voivodeships. About 60 % of the permits issued in the Masovian Voivodeship are in Warsaw. Taking into account the specifics of the supply in the labor market, men predominate in the structure of issued work permits by sex; their share increased to 71 % in 2017 (MRPiPS, 2020).
It should be noted that the share of the refusal to issue work permits on the Polish part is rather insignificant. At the same time, it tends to increase (from 5.1 % for men, 6.9 % for women in 2011 to 10.5 % and 11.8 % in 2018, respectively) due to the saturation of the labor market in Poland and increasing requirements for employees (MRPiPS, 2020).
A distinctive feature of modern migration flows is the significant changes in the employment structure of Ukrainian migrant workers in Poland. In 2018, the main areas of their employment were construction, industry, transport and logistics, while in 2011, most people worked in construction, households, transport, trade and agriculture (Fig. 2).
There have been significant changes in the structure of Ukrainian labor migration by the period of stay. Particularly, the share of long-term migration lasting from two years and more is increasing, while the frequency of medium-term migration (from 3 months to 2 years) has decreased. However, it should be noted that the share of migrants who stay up to 3 months is quite high, which is not reflected in official donors of information.
Trends in the development of migration processes between Ukraine and Poland indicate their intensification and structural transformation towards the change of sector of employment, an increase in the share of young people and length of period they stay abroad. The share of Ukrainian emigrants who do not plan to return from Poland to Ukraine is increasing. The above necessitates modeling of the impact of macroeconomic indicators on labor migration trends in order to identify the causes of negative processes associated with excessive migration flows and their impact on the economic development of countries.
3.3. Modeling of the impact of macroeconomic indicators on labor migration trends
Application of a stepwise regression and its further testing for multicollinearity and heteroscedasticity for four groups of dependent indicators of labor migration (1 - number of migrant workers, 2 - type of entry and labor permit of Ukrainian migrant workers in Poland, 3 - sector where Ukrainian migrant workers are employed in Poland, 4 - term of employment of Ukrainian migrant workers in Poland) gave the following results.
3.3.1. Intensity of labor migration from Ukraine to Poland
Determinants of the number of Ukrainian migrants in Poland are the average salary in Ukraine, inflation in both countries, exchange rate of UAH to Euro (Tab. 2).
Modeling results indicate:
• When annual inflation in Ukraine, average salary in national currency in Ukraine, average salary in euro in Ukraine change by 1%, the number of applications for work permits for men will change by -13909, 70148, -20293 persons respectively, provided that all other factors remain unchanged.
• When annual inflation in Ukraine, average salary in national currency in Ukraine, average salary in
euro in Ukraine change by 1%, the number of issued work permits for men will change by -12245, 63557, -17783 persons respectively, provided that all other factors remain unchanged.
• When average salary in national currency in Ukraine changes by 1%, the number of applications for work permits for women will change by 25009 persons.
• When average salary in national currency in Ukraine changes by 1%, the number of issued work permits for women will change by 22226 persons respectively, provided that all other factors remain unchanged.
• When average salary in national currency in Ukraine changes by 1%, the total number of applications for work permits will change by 94483 persons.
• When official exchange rate (UAH per Euro), Average salary in euro for Poland change by 1%, the total number of issued work permits will change by 80976, 3331 persons respectively, provided that all other factors remain unchanged.
Figure 2. Main economic spheres of employment of Ukrainian migrants in Poland Source: (MRPiPS, 2020).
• When annual inflation in Poland changes by • When annual inflation in Poland changes by
1%, the share of approved work permits for men (%) 1%, the share of approved work permits for women (%) will increase by 2.4%. will increase by 1.4%.
Table 2.
Dependence of indicators of the number of Ukrainian labor migrants in Poland
De-pen den t vari abl e Selected features with method Step regression Test for multicollinearity (VIF) Test for heterosce-dasticity Result model R2
VIF after removing feature with the highest level VIF Breush-Pagan test
Y1 Xn,X:3, X:4,X:5 Xii=2.59 Xi3=41.8 Xi4=10.2 Xi5=24.7 Xn=2.37 X14=1.10 X15=2.23 p-val.= 0.4006 65239***- Xnx13909* + X14X70148*** - X15X20293** 0.99
Y2 Xn,X:3, X:4,X:5 Xii=2.37 Xi4=i.i0 Xi5=2.23 - p-val.= 0.5983 59153***- Xnx12245** + X14X63557*** - X15X17783** 0.99
Y3 X14 - - p-val.= 0.2i44 27779***+Xj4x25009** * 0.95
Y4 X14 - - p-val.= 0.2284 25004***+XMx22226** * 0.95
Y5 X14 - - p-val.= 0.2943 93019***+X14x94483** * 0.96
Y6 X16, X25, X14 Xi6=i2.3 X25=i2.4 Xi4=i2.7 X16=10.4 X25=10.1 p-val.= 0.i094 84158***+ + X16X80976 + X25X3331 0.94
Y7 X21 - - p-val.= 0.6667 92***+X14X2.43* 0.63
Y8 X21 - - p-val.= 0.0.64 91***+X14X1.36* 0.64
*** p < 0.001; ** p < 0.01; * p < 0.05 Source: result of modeling
Summarizing these results, it can be argued that positive changes in macroeconomic indicators in Ukraine do not lead to a reduction in migration flows that have a steady upward trend. This is due to great differences in salary of workforce in the donor and recipient countries. At the same time, rise in the inflation in Poland causes an increase in the share of rejections to issue work permits for the Ukrainians. 3.3.2. Type of entry and labor permits The type of labor permit for the Ukrainians in Poland is predominantly determined by GDP per capita, unemployment, inflation and salary in both countries (Tab. 3).
Modeling results indicate: • When GDP per capita (current US$) in Ukraine, average salary in euro in Ukraine change by
1%, the Number of work permits issued by type A will change by -44102 persons.
• When total unemployment (% of total labor force) in Ukraine and Poland changes by 1%, the Number of work permits issued by type B will change by 48, 53 persons respectively, provided that all other factors remain unchanged.
• When total unemployment (% of total labor force) in Ukraine, Inflation in Poland, Official exchange rate (PLN per Euro) change by 1%, the Number of work permits issued by type C will change by 709, 564, 368 persons respectively, provided that all other factors remain unchanged.
Table 3.
Dependence of the type of employment permit for Ukrainian migrants in Poland
De- Selected features with method Step regression Test for multicollinearity (VIF) Test for heterosce-dasticity
pendent after removing feature Result model R2
variable VIF with the highest level VIF Breush-Pagan test
Y9 X13 - - p-val.= 0.i43 53236*- Xi3*44102 0.49
Y10 X12 X22 Xi2=1.05 X22=1.06 - p-val.= 0.38i5 112***+ + X12*48* + X22X53* 0.79
Y11 X12 X21 X26 Xi2=4.54 X2i=1.72 X26=4.18 - p-val.= 0.i294 1095***+ + X12*709** - X21 X564** + X26X368 0.98
Y12 X13 X15 Xi3=4.00 Xi5=4.00 - p-val.= 0.2055 253***+ + X16XI66** - X25X257** 0.9i
Y13 X14 X16 Xi4=8.36 Xi6=8.36 - p-val.= 0.3i22 199***- X¡4x102 + X¡6X327*** 0.98
*** p < 0.001; ** p < 0.01; * p < 0.05. Source: result of modeling
• When GDP per capita (current US$) in Ukraine, Average salary in euro for Ukraine change by 1% Number of work permits issued by type D will change by 166 and 257 persons respectively, provided that all other factors remain unchanged.
• When Average salary, national currency in Ukraine, Official exchange rate (UAH per Euro) for Ukraine change by 1% Number of work permits issued by type E will change by 102 and 327 persons respectively, provided that all other factors remain unchanged.
The results confirm the fact that improvement in macroeconomic indicators in Ukraine leads to a decrease in the level of migration activity of low skilled
workforce (type A). At the same time, a rise in unemployment in both countries leads to an increase in the migration of highly skilled workforce with higher education, in particular in the field of management (type B). It should be emphasized that changes in the economic situation in both countries have not affected the level of international economic cooperation between business entities in recent years, as evidenced by the steady increase in the number of permits of C, D, E type issued to Ukrainian migrants.
3.3.3. Sectors of employment of Ukrainian migrant workers in Poland
During 2011-2018, significant changes occurred in the employment structure of the Ukrainians in Poland, which was due to changes in macroeconomic proportions in the development of countries (Tab. 4).
De- Selected features with method Step regression Test for multicollinearity (VIF) Test for hetero-scedasticity
pendent variable VIF after removing feature with the highest level VIF Breush-Pagan test Result model R2
Yi4 X21 - - p-val.= 0.33ii 2403***- X21X1522** 0.70
Yi5 X15 X22 Xi5=i.ii X22=i.ii - p-val.= 0.5502 10418***+ +X15X5518** - X22X18639*** 0.98
Yi6 X15 X11 X13 X14 Xi5=24.7 Xii=2.59 Xi3=4i.8 Xi4=i0.2 X15=2.23 Xn=2.37 X14=2.23 p-val.= 0.2i52 18101***- X15X4909*** - X11X366O** + X14X19488*** 0.99
Yi7 X16 Xi6=i.43 - p-val.= 0.599 4105***+ 0.98
Table 4.
Dependence of economic spheres of employment of Ukrainian migrants in Poland
X26 X26=1.43 +X16*3001*** - X26x824**
YlB X14 X24 2X 1X 21 44 1 1 k> 2 - p-val.= 0.6395 11329***+ +X14XI88I3*** - X24X4665* 0.99
Yl9 X14 - - p-val.= 0.1613 2261***+ +X14X2480*** 0.93
Y20 Xl6 X22 X16=5.77 X22=5.77 - p-val.= 0.1838 659***+ +X22X409*** +X16X953*** 0.99
Y21 X14 X23 X14=1.4 X23=1.4 - p-val.= 0.341 147***+ +X14X219*** - X23X53* 0.99
Y22 X12 X13 X12=1.07 X13=1.07 - p-val.= 0.1705 4136**- X13X3752* + X12X2219 0.82
Y23 X12 X25 X16 X12=1.41 X16=11.8 X25=11.4 X12=1.41 X25=1.41 p-val.= 0.4505 149*+ +X12X73 +X25X6I 0.51
Y24 X14 - - p-val.= 0.3906 317***+ + X14X294*** 0.95
Y25 X21 - - p-val.= 70.92 6320***- X21X2I88** 0.83
*** p < 0.001; ** p < 0.01; * p < 0.05. Source: result of modeling
The results of economic and mathematical modeling of interstate migration processes between Ukraine and Poland indicate:
• When annual inflation in Poland changes by 1%, the number of Ukrainian migrant workers in agriculture and related industries will change by -1522 persons.
• When Average salary in euro for Ukraine, total unemployment (% of total labor force) in Poland change by 1%, the number of Ukrainian migrant workers in industry will change by 5518, -18639 persons respectively, provided that all other factors remain unchanged.
• When annual inflation in Ukraine, average salary in national currency in Ukraine, average salary in euro in Ukraine change by 1%, the number of Ukrainian migrant workers in industry will change by -4909, -3660, 19488 persons respectively, provided that all other factors remain unchanged.
• When Official exchange rate (UAH per Euro) for Ukraine, Official exchange rate (PLN per Euro) change by 1%, the number of Ukrainian migrant workers in wholesale and retail will change by 3001, -824 persons respectively, provided that all other factors remain unchanged.
• When Average salary, national currency in Ukraine and Poland change by 1%, the number of Ukrainian migrant workers in transport and logistics will change by 18813, -18639 persons respectively, provided that all other factors remain unchanged.
• When Average salary, national currency in Ukraine change by 1%, the number of Ukrainian migrant workers in activities related to accommodation and catering services will change by 2480 persons.
• When Official exchange rate (UAH per Euro) for Ukraine, total unemployment (% of total labor
force) in Poland change by 1%, the number of Ukrainian migrant workers in information and telecommunications will change by 409, 953 persons respectively, provided that all other factors remain unchanged.
• When Average salary, national currency in Ukraine, GDP per capita (current US$) in Poland change by 1%, the number of Ukrainian migrant workers in financial Activities And Insurance will change by 219, 53 persons respectively, provided that all other factors remain unchanged.
• When total unemployment (% of total labor force) in Ukraine, average salary in euro in Ukraine change by 1%, the number of Ukrainian migrant workers in scientific and technical activities will change by 3752, 2219 persons respectively, provided that all other factors remain unchanged.
• When Average salary, national currency in Ukraine change by 1%, the number of Ukrainian migrant workers in health social sector will change by 294 persons.
• When annual inflation in Poland changes by 1%, the number of Ukrainian migrant workers in households will change by -2188 persons.
Summarizing of these results suggests that the positive and negative changes in the microeconomic indicators of the development of both countries do not affect the increase in the employment rate of migrants in the service sector, which is a global trend in the development of migration processes. At the same time, a rise in the inflation rate in Poland stimulates the demand for low-paid workforce, particularly in the household sector.
3.3.4. Period of stay of Ukrainian migrant workers in Poland
The period of stay of Ukrainian migrants in Poland is mainly determined by the factors of the donor country of the workforce (Tab. 5).
The results of modeling of interstate migration processes indicate:
• When total unemployment (% of total labor force) in Ukraine, Official exchange rate (UAH per Euro) for Ukraine change by 1%, the number of Ukrainian migrant workers for a term up to 3 months will change by -440, -173 persons respectively, provided that all other factors remain unchanged.
• When total unemployment (% of total labor force) in Ukraine, GDP per capita (current US$) in Ukraine, Inflation in Poland, total unemployment (% of total labor force) in Poland, Official exchange rate (PLN per Euro) for Poland change by 1%, the number of Ukrainian migrant workers for a term from 1 year to 2 years will change by -20249, -8229, 6075, -2521, -14816 persons respectively, provided that all other factors remain unchanged.
• When Official exchange rate (UAH per Euro) for Ukraine, total unemployment (% of total labor force) in Poland change by 1%, the number of Ukrainian migrant workers for a term more than 2 years will change by -47368, -58517 persons respectively, provided that all other factors remain unchanged.
Thus, it can be argued that the exacerbation of macroeconomic situation in Ukraine (rising unemployment, inflation, etc.) leads to an increase in the migration period, while the emergence of negative trends in the Polish economy causes a decrease in the period of stay of migrant workers in its territory.
Conclusion
1. The theories of international migration evolved in line with the trends in the development of the world economy and the transformation of forms of
• When total unemployment (% of total labor force) in Ukraine, Official exchange rate (UAH per Euro) for Ukraine, Official exchange rate (PLN per Euro) for Poland change by 1%, the number of Ukrainian migrant workers for a term from 3 months to 1 year will change by -73222, -36873, 15722 persons respectively, provided that all other factors remain unchanged.
international relations. Migration behavior of workforce is based on macroeconomic, microeconomic and globalization paradigms. Macroeconomic theories examine a system of macroeconomic and conjunctural indicators that explain the causes and motivators of migration. Microeconomic theories investigate workforce movement through the migrant's assessment of economic benefits, degree of integration in the country of immigration. Globalization theories consider the movement of population between countries as a regularity related to the intensified processes of transnationaliza-tion, integration, as a factor in the development of the world economy. Migration processes that are characteristic of Ukraine occur in accordance with the theory of world systems. It states that the determining factor of interstate labor migration is the specific features of socioeconomic development of the country of origin and destination of migrants.
2. The analysis of the case study of Ukraine and Poland suggests that the intensity of migration processes between them is dual in nature and is stimulated by the macroeconomic factors of both countries. A distinctive feature of modern migration flows is an increase in their intensity, structural changes in the sector of employment, period of stay, age and gender.
Table 5.
Dependence of working period of Ukrainian migrants in Poland
De- Selected features with method Step regression Test for multicollinearity (VIF) Test for hetero-scedasticity Result model R2
pendent variable VIF after removing feature with the highest level VIF Breush-Pagan test
Y26 X12 X16 Xi2=4.13 Xi6=4.13 - p-val.= 0.8027 334***- X12*440** - X26X173 0.92
Y27 X12 X14 X16 X22 X26 X12=15.6 X14 =50.8 Xi6 =24.2 X22 =58.2 X26=10.0 X12 =4.17 X16 = 1.44 X26=4.38 p-val.= 0.5897 46756**- X:2x73222** - X26X36873 + X16X15722*** 0.90
Y28 X12 X13 X16 X21 X22 X26 X12 =21.8 X13 =10.1 X16 =105 X21 =6.87 X22 =55.1 X26=13.1 X12 =7.28 X13 =6.59 X21 =4.85 X22 =4.20 X26=10.1 p-val.= 0.1967 15040*- X12X20249 - X26X8229 + X13X6O75 - X21X2521 - X22X14816 0.97
Y29 X16 X22 X16=5.77 X22=5.77 - p-val.= 0.1387 17652**- X16X47368** - X22X58517*** 0.91
*** p < 0.001; ** p < 0.01; * p < 0.05. Source: result of modeling
3. The authors have obtained 29 econometric models for a study of the processes of interstate labor migration. The effective features (Yi) were the main indicators of labor migration between Ukraine and Poland, and the factorial features (Xi) were the macroeco-nomic indicators at the level of these countries. The models were divided into 4 groups: 1st group characterizes the number of migrant workers from Ukraine to Poland; 2nd group types of work permits; 3rd group sectors of the economy where Ukrainian labor migrants are involved; 4th group terms of employment.
As a result of the regression analysis, taking into account the tests for multicollinearity and heteroscadic-ity, the following results were obtained:
3.1. the number of Ukrainian migrant workers in Poland is most significantly influenced by the following macroeconomic factors in the Ukrainian and Polish economies: positive impact (Average salary, euro for Ukraine, Official exchange rate, LCU per Euro for Ukraine, Average salary, euro for Poland); negative impact (Inflation, consumer prices (annual %) for Ukraine, Average salary, euro for Ukraine);
3.2. GDP per capita (current US$) for Ukraine is the major negative factor that affects the types of work permit;
3.3. the main factors that determine the choice of the sector of employment are: positive impact (Average salary, euro for Ukraine, average salary, LCU for Ukraine, Official exchange rate (LCU per Euro) for Ukraine); negative impact (Unemployment, total (% of total labor force) for Poland, Average salary, LCU for Poland);
3.4.the main factors that affect the period of employment of Ukrainian migrant workers include: positive impact (GDP per capita (current US$) for Ukraine, Official exchange rate, LCU per Euro for Ukraine); negative impact (Unemployment, total (% of total labor force) for Poland, Unemployment, total (% of total labor force) for Ukraine, (Inflation, consumer prices (annual %) for Poland, Official exchange rate (LCU per Euro) for Poland).
4. Summarizing the results obtained, it can be argued that the state of labor migration from Ukraine to Poland is affected by 82% by Ukrainian macroeconomic indicators and by 18% by Polish ones. Accordingly, socioeconomic reforms in Ukraine have to play a key role in influence these processes (which is more critically important for Ukraine).
5. Some modeling results are questionable and need to be further staded with the inclusion of more factorial features and the extension of the study term, taking into account current globalization trends.
References
1. Agnieszka Chlon-Dominczak (2015). Migration Policies: Poland (2015) | SPLASH DB. Retrieved January 29, 2020, from Institute of Statistics and Demography Warsaw School of Economics SGH: https://splash-db.eu/policydescription/migration-policies-poland-2015/.
2. Benson, M., & O'Reilly, K. (2016). From lifestyle migration to lifestyle in migration: Categories,
concepts and ways of thinking. Migration Studies, 4(1), 20-37.
3. Boyd, D. (2007). W. Arthur Lewis's Theory of Economic Growth: a Review with 50 years of Foresight: South Africa, University of East London.
4. CES (2019). How many Ukrainians have gone abroad and what the state has to do with it: Сшльки украшщв по1хало за кордон i що державi з цим робити, from https://ces.org.ua/migration/.
5. Danzer, A. M., & Dietz, B. (2014). Labour Migration from Eastern Europe and the EU's Quest for Talents. JCMS: Journal of Common Market Studies, 52(2), 183-199.
6. Efron, B., & Tibshirani, R. J. (1998). An introduction to the bootstrap. Boca Raton, London and New York: Washington, DC: Chapman & Hall/CRC Press.
7. Ester, M., Kriegel, H.-P., Sander, J., & Xu, X. (1996). A density-based algorithm for discovering clusters in large spatial databases with noise. In Proc. of the 2nd Int'l Conference on Knowledge Discovery in Databases and.
8. Estevens, J. (2018). Migration crisis in the EU: developing a framework for analysis of national security and defence strategies. Comparative migration studies, 6(1), 28.
9. Fedyuk, O., & Kindler, M. (2016). Migration of Ukrainians to the European Union: Background and key issues. In Ukrainian Migration to the European Union (pp. 1-14). Springer, Cham.
10. Frelak, J. S. (2017). Solidarity in European Migration Policy: The Perspective of the Visegrad States. In A. Grimmel & S. M. Giang (Eds.), Solidarity in the European Union. A fundamental value in crisis / Andreas Grimmel, Susanne My Giang, editors (pp. 8195). Cham, Switzerland: Springer.
11. Global Compact for Migration (2018), from https://www.un.org/pga/72/wp-content/uploads/sites/51/2018/07/migration.pdf.
12. Hautamaki, V., Karkkainen, I., & Franti, P. Outlier detection using k-nearest neighbour graph. In Proceedings of the 17th International Conference on Pattern Recognition, 2004. ICPR 2004 (pp. 430-433). IEEE.
13. Iglicka, K. (2001). Migration movements from and into Poland in the light of east-west European migration. International migration (Geneva, Switzerland), 39(1), 3-32.
14. Johnson, T., Kwok, I., & Ng, R. T. (1998). Fast Computation of 2-Dimensional Depth Contours. In KDD, 224-228.
15. Lee, E. S. (1966). A theory of migration. Demography, 3(1), 47-57.
16. Massey, D. A. (2002). Synthetic theory of international migration. World in the mirror of international migration, 10, 143-153.
17. MRPiPS (2020). Poland Ministry of Family, Labor and Social Policy: Statistics: Work permits for foreigners. Retrieved February 21, 2020, from Departament Rynku Pracy: https://psz.praca.gov.pl/statystyka//-/asset_publisher/MDNO4TyL2uZj/content/8180075-zezwolenia-na-prace-cudzoziemcow.
18. Mugge, L., & van der Haar, M. (2016). Who is an immigrant and who requires integration? Categorizing in European policies. In Integration processes and policies in Europe (pp. 77-90). Springer, Cham.
19. Olga Gulina, O. P. (2018). Migration flows from Ukraine: changing trends, from https://en.zois-berlin.de/publications/zois-spotlight-2018/migration-flows-from-ukraine-changing-trends/.
20. Ram, A., Jalal, S., Jalal, A. S., & Kumar, M. (2010). A Density Based Algorithm for Discovering Density Varied Clusters in Large Spatial Databases. International Journal of Computer Applications, 3(6), 1-4.
21. Ravenstein, E. G. (1876). The birthplaces of the people and the laws of migration: Trubner.
22. Ravenstein, E. G. (1885). The laws of migration. Journal of the statistical society of London, 48(2), 167-235.
23. SAS Institute Inc. (1989). SAS/STAT User's Guide Version 6 Fourth Edition.
24. SSSU (2008-2019). Stat Statistics Service of Ukraine, from http://www.ukrstat.gov.ua/.
25. Stouffer, S. A. (1940). Intervening opportunities: a theory relating mobility and distance. American sociological review, 5(6), 845-867.
26. Strielkowski, W., Tumanyan, Y., & Kalyugina, S. (2016). Labour market inclusion of international protection applicants and beneficiaries. Economics & Sociology, 9(2), 293.
27. Tucker, J. (2018). Why here? Factors influencing Palestinian refugees from Syria in choosing Germany or Sweden as asylum destinations. Comparative migration studies, 6(1), 29.
28. van Mol, C., Snel, E., Hemmerechts, K., & Timmerman, C. (2018). Migration aspirations and migration cultures: A case study of Ukrainian migration towards the European Union. Population, space and place, 24(5), e2131.
29. van Mol, C., & Valk, H. de (2016). Migration and immigrants in Europe: A historical and demographic perspective. In Integration processes and policies in Europe (pp. 31-55). Springer, Cham.
30. Wallerstein, I. (2011). The modern world-system III: The second era of great expansion of the capitalist world-economy, 1730s-1840s (Vol. 3): Univ of California Press.
31. Worldbank (2020). Indicators - Data. Retrieved January 29, 2020, from The World Bank: https://data.worldbank.org/indicator.
32. Zelinsky, W. (1971). The hypothesis of the mobility transition. Geographical review, 219-249.
33. Zipf, G. K. (2012). Human behavior and the principle of least effort: An introduction to human ecology. Mansfield Centre, Conn.: Martino Publishing.
34. Zuk, P., & Zuk, P. (2018). Offshoring, labour migration and neo-liberalisation: nationalist responses and alternatives in Eastern Europe. The Economic and Labour Relations Review, 29(1), 97-117.
ОСОБЕННОСТИ РЕАЛИЗАЦИИ ТАМОЖЕННОЙ ПОЛИТИКИ КАЛИНИНГРАДСКОЙ ОБЛАСТИ КАК ОСОБОЙ ЭКОНОМИЧЕСКОЙ ЗОНЫ
Коноплева И.А.
Западный филиал ФГБОУ ВО РАНХиГС доцент кафедры таможенного дела, доцент, к.т.н.
Коноплева В. С.
Западный филиал ФГБОУ ВО РАНХиГС доцент кафедры региональной экономики и менеджмента, к.э.н.
FEATURES OF THE IMPLEMENTATION OF THE CUSTOMS POLICY OF THE KALININGRAD
REGION AS A SPECIAL ECONOMIC ZONE
Konopleva I.
Western Branch of RANEPA Associate Professor of the Department of Customs Affairs, Associate Professor, Candidate of Technical Sciences
Konopleva V.
Western Branch of the RANEPA Associate Professor of the Department of Customs Affairs, Associate Professor, Ph. D. in Economics
Аннотация
В статье рассмотрена таможенная политика в условиях организации особой экономической зоны (ОЭЗ) в Калининградской области. В процессе исследований авторы выявили негативные моменты, связанные со спецификой внешнеэкономической деятельности ОЭЗ. Это, прежде всего, провоз в страну санк-ционных товаров, формирование черного рынка и др., которые в большинстве своем пресекаются таможенными и внутренними органами рассматриваемого региона. Авторы указали на позитивные аспекты организации ОЭЗ, выявили особенности таможенной политики в Калининградской области и указали на перспективы ее развития.
Abstract
The article considers the customs policy in the conditions of the organization of a special economic zone
