ACTA GEOGRAPHICA 
GEOGRAFSKI ZBORNIK 


SLOVENICA 

2020 
60 
1 
ACTA GEOGRAPHICA SLOVENICA GEOGRAFSKI ZBORNIK 60-1 • 2020 
Contents 
Mojca POKLAR
Comparison of the sonar recording method and the aerial photography methodfor mapping seagrass meadows 7 

Vanja PAVLUKOVIĆ, Uglješa STANKOV, Daniela ARSENOVIĆ 
Social impacts of music festivals: A comparative study of Sziget (Hungary) and Exit (Serbia) 21 
Péter János KISS, Csaba TÖLGYESI, Imola BÓNI, László ERDŐS, András VOJTKÓ,István Elek MAÁK, Zoltán BÁTORI 
The effects of intensive logging on the capacity of karst dolines to provide potential microrefugia for cool-adapted plants 37 

Radu SĂGEATĂ 
Commercial services and urban space reconversion in Romania (1990–2017) 49 

Kristina IVANČIČ, Jernej JEŽ, Blaž MILANIČ, Špela KUMELJ, Andrej ŠMUC
Application of a mass movement susceptibility model in the heterogeneous Miocene clastic successions of the Slovenj Gradec Basin, northeast Slovenia  1 

Andrej GOSAR 
Measurements of tectonic micro-displacements within the Idrija fault zone in the Učjavalley (W Slovenia) 79 

Piotr RAŹNIAK, Sławomir DOROCKI, Anna WINIARCZYK-RAŹNIAK 
Economic resilienceofthe command andcontrolfunctionof citiesin Centraland EasternEurope 95 

Mateja FERK, Rok CIGLIČ, Blaž KOMAC, Dénes LÓCZY 
Management of small retention ponds and their impact on flood hazard prevention in the Slovenske Gorice Hills 107 
Gregor KOVAČIČ
Sediment production in flysch badlands: A case study from Slovenian Istria 127 

Vesna LUKIĆ, Aleksandar TOMAŠEVIĆ 
Immigrant integration regimes in Europe: Incorporating the Western Balkan countries 143 

Mitja DURNIK 
Community development: LocalImmigrationPartnershipsin Canadaand implications forSlovenia 155 
ISSN 1581-6613 
9 771581 661010 


IMMIGRANT INTEGRATION REGIMES IN EUROPE: INCORPORATING THE WESTERN BALkAN COUNTRIES 
Vesna Lukić, Aleksandar Tomašević 

Ensuring timely policy responses to integration is important. 
DOI: https://doi.org/10.3986/AGS.7286 UDC: 316.4.063.3-054.72(497) COBISS: 1.01 
Vesna Lukić1, Aleksandar Tomašević2 

ImmigrantintegrationregimesinEurope:IncorporatingtheWesternBalkancountries 
ABSTRACT: This article discusses immigrant integration policies in Europe. We analyzed data from the 2015MigrationIntegrationPolicyIndextoidentifysimilarimmigrantintegrationregimesinEuropeaccord­ing to policy priorities related to immigrants’ socioeconomic rights. The results of a latent class analysis demonstrated that there are two immigrant integration policy regimes among the EU 28, Albania, Bosnia and Herzegovina, Montenegro, Macedonia, and Serbia, with variation between the old EU member states since 1995 (without Greece) and Estonia versus the new EU member states since 2004 (without Estonia), Greece, and the Western Balkan countries. Based on our classification, we conclude that there is a trend of convergence in integration policy regimes in Europe, in which the effects of spatial/geographical and temporal dimensions are manifested. 
KEYWORDS:immigration,integrationpolicy,MigrantIntegrationPolicyIndex,latentclassanalysis,Europe 

Režimi integracije priseljencev v Evropi: vključevanje držav Zahodnega Balkana 
POVZETEK:Včlankuavtorjaobravnavataevropskopolitikovključevanjapriseljencevvvečinskodružbo. NapodlagianalizepodatkovIndeksapolitikevključevanjamigrantov(MIPEX)zaleto2015inobhkratnem upoštevanju prednostnih nalog, ki se nanašajo na družbenogospodarske pravice priseljencev, ugotavljata, katerirežimivključevanjapriseljencevvEvropisosimedsebojpodobni.Rezultatianalizelatentnihrazre­dovsopokazali,dasev28državahčlanicahEU,Albaniji,BosniinHercegovini,Črnigori,SeverniMakedoniji inSrbijiuporabljatadvarežimapolitikevključevanjapriseljencev,pričemersoopaznerazlikemedstarejši­midržavami EU (članicami od leta 1995, a brez Grčije) in Estonijo ter novejšimi članicami (od leta 2004, brez Estonije),GrčijoindržavamiZahodnegaBalkana. Na podlagi izdelane klasifikacijeavtorja ugotavljata, dapostajajoevropskirežimiintegracijskepolitikemedsebojčedaljeboljpodobni,navedenopaimaopazne prostorske oziroma geografske in časovne posledice. 
KLJUČNE BESEDE: priseljevanje, integracijska politika, indeks politike vključevanja migrantov, analiza latentnih razredov, Evropa 
The paper was submitted for publication on March 4th, 2019. Uredništvo je prejelo prispevek 4. marca 2019. 
1 Institute of Social Sciences, Belgrade, Serbia lukicbodirogav@gmail.com 2 University of Novi Sad, Faculty of Philosophy, Department of Sociology, Novi Sad, Serbia atomashevic@ff.uns.ac.rs 

1 Introduction 
In Europe today, there has been an increasing focus on immigration-related issues by both scholars and policymakers. A literature review suggests that in the academic world much attention has been given to thediscussionofimmigrationandintegrationpoliciesacrosscountries(Bjerreetal.2014;deHaas,Natter and Vezzoli 2015). However, most studies have focused on northwestern Europe, with its long immigra­tion and integration experience, the EU, or OECD countries (Joppke 2007; Garibay and Cuyper 2013;Gregurović and Župarić-Iljić 2018), whereas this topic remains under-researched in the non-EU coun­tries and particularly in the Western Balkans. Therefore, tackling migration and developing immigration and integration policies in European countries that are not immigrant destinations is challenging. 
Migrationcutsacrossdisciplines,whereasmigrantscrossgeographicallyandsociallyconstructedbor­dersandboundaries.AsHardwick(2008)andJosipovičandRepolusk(2003)emphasize,itisimportantto consider the spatial perspective of migration when theorizing about assimilation. The social and political challenges of immigration make immigrant integration a very important policy domain for governments. European countries formulated national immigrant integration policies in the past primarily in countries in northwestern Europe, whereas the institutional framework for migration is relatively new in eastern Europe.SeveralnationalmodelsofintegrationforthecountriesofnorthwesternEuropeweredistinguished inmigrationliteratureaccordingtogovernmentpolicyprinciplesandresponsestoimmigrationandinte­gration: the assimilationist model, the multicultural model, and the differential exclusionist model (Brubaker 1992; Castles 1995). 
Thesemodelshavebeenquestionedandcriticizedbyresearchersforvariousreasons.Criticaldiscussions suggestthatthetypologyofnationalimmigrantintegrationmodelsdoesnotrecognizethedynamicchar­acterofintegrationpolicies.It,therefore,under-recognizesthetemporalityofcategoriesofintegrationregimes (Meuleman and Reeskens 2008; Finotelli and Michalowski 2012). Entzinger and Biezefeld (2003) empha­sizethelimitationsoffocusingonalimitednumberofdimensionsinthemostcommonlyusedtypologies. Other shortcomings of the typologies refer to the validity of indicators as well as to ignoring the poten­tial immigration-integration policy nexus (Boucher and Gest 2014). 
Contemporary Europeanization, as Knill and Lehmkuhl (2002) define it, and globalization process-esinfluencemigrationmanagement(AppaveandLaczko2011).Therefore,effortstowardtheEuropeanization ofintegrationpolicieshavebeenevidentinthelastdecade(Parkes2008).Since2004,theEuropeanUnion has been developing the legal framework and principles of a coherent policy for integrating immigrants (Council…2004,2008). Thedocumentscreateacommonunderstandingofintegrationasaprecondition forharmonization ofimmigrant integration legislation(Martiniello 2006; Lozano etal. 2014). Integration is defined as a »dynamic, two-way process of mutual accommodation by all immigrants and residents of Member States« (Council…2004). Although the EU supports national policies with policy funds, coor­dination and exchange of knowledge among the integration policies is a responsibility of EU countries. Previousresearchhasidentifiedthetransformationofnationalintegrationmodelsandconvergenceininte­gration policies and practices across the EU (Joppke 2007; Penninx and Garcés-Mascarenas 2015), as well as convergence in integration models (Doomernik and Bruquetas-Callejo 2015). 
Researchers, policymakers, and decision-makers are increasingly preoccupied with immigration and integrationpoliciesacrosscountries.Variousdatabasesofmigrationpoliciesandadoptedlegislationhave been created that cover a number of policy fields, countries, and timespans. These databases offer many opportunities to researchers and policymakers for comparative analysis or evaluation of integration poli­cies across countries. The immigrant integration indicators are part of the International Migration Policy andLawAnalysis(IMPALA)database(Beineetal.2016)trackingimmigrationpolicies.Theyarealsopart oftheDeterminantsofInternationalMigration(DEMIG)databasetrackingmigrationpolicychanges(de Haas,NatterandVezzoli2018).TheBarcelonaCentreforInternationalAffairs(CIDOB)andtheMigration Policy Group (MPG) have produced the Migrant Integration Policy Index (MIPEX). This index covers thirty-eight countries and eight policy areas (labor market, family reunion, education, political participa­tion, long term residence, access to nationality, anti-discrimination, and health) relevant for immigrant integrationfor2004–2014(Huddlestonetal.2015).ThedataarelimitedtoEUcountries,Australia,Canada, Iceland, Japan, South Korea, New Zealand, Norway, Switzerland, Turkey, and the United States. Data for the Western Balkans are not included. The MIPEX data are available for Bosnia and Herzegovina, North Macedonia, and Serbia (2013 and 2015), whereas Albania and Montenegro were assessed only in 2015. In the Western Balkan countries, immigration and integration issues are relatively new. 
Scholars interested in comparing policies for integrating immigrants across countries and classifica­tion of integration regimes (Meuleman and Reeskens 2008; Zamfir et al. 2014) frequently refer to MIPEXdata.Someresearcherscombinethesedatawithotherindicators;GregurovićandŽuparić-Iljić(2018)used the MIPEX overall index together with the OECD indicators of integration. Recently scholars have linked integration policy models with other social phenomena such as the political participation of immigrants (Helblingetal.2016)orperceptionsofeconomicandculturalthreats(CallensandMeuleman2016).However, only the EU countries were studied. 
Considering the diversity of European societies, there is a need to study and analyze integration mod-elsofcountriesthathavenotbeenstudiedsofar.Thisisparticularlyimportantforcountriesthataccording toMelegh et al. (2014) are stillcharacterized by major emigration flows and could transform into »coun­triesofimmigration.«Thereisalsoaneedtoenhancetheunderstandingofdifferenttypologiesofintegration regimes that represent the integration of immigrants. 
Understanding the concept of integration of immigrants is very important given its complex nature involving multiple processes. There is an increasing number of thoughts about alternative approaches to the concept of integration (Grzymala-Kazlowska and Phillmore 2018) due to the era of super-diversity as a new demographic reality (Vertovec 2007). However, regarding the data referred to in this article, immi­grant integration is understood as an opportunity for gaining equal socio-economic rights. 
This article identifies similar clusters of immigrant integration regimes in Europe according to poli­cyprioritiesrelatedtoimmigrants’socioeconomicrights.Basedontheresearchgapidentifiedinprevious literature, this article answers two main research questions. First, it examines how many different types of integration regimes can be distinguished in Europe when the Western Balkan countries are taken into account. Second, it looks at what the differences are between clusters of immigrant integration regimes and which ones do better in integrating migrants based on the policy areas discussed. 

2 Data and methods 
The data used in this paper are from the 2015 Migration Integration Policy Index (MIPEX) database for thirty-threecountries,collectedin2014.Theindexrepresentstheintegrationpolicybytheindicatorsbased on qualitative expert evaluation of existing national laws and policies. The MIPEX database covers eight policy areas relevant to the integration of immigrants. Every policy area presents diverse components and policy dimensions that are related to policy indicators. Thus, the policy area scores are based on the aver­age scores of policy dimensions that favor the integration of immigrants (Huddleston 2016). 
The aim of our analysis was the construction of an exclusive and exhaustive typology of integration policy regimes among the EU 28, Albania, Bosnia and Herzegovina, Montenegro, North Macedonia, and Serbia. Because the integration regime is represented by eight categorical policy indicators, our analysis requires a model that will reveal the latent classification of these regimes into clusters based on similar patternsofvaluesforeachindicator.Inotherwords,thismodelwouldrevealadiscretelatentvariablethat will indicate the membership of each country in one of the regime types in such a manner that countries belonging to different types will exhibit substantial differences in the majority of MIPEX indicators. This model was constructed using polytomous latent class analysis, which estimates the conditionalprobabil­ityofeachcountrybelongingtooneofthedifferentregimes(latentclasses)giventhevaluesofpolytomous categoricalvariablesbasedontheMIPEXindicators.Thisprocedurerequiresthespecificationofthenum­berofclasses,andsotheanalysisproceedsbyestimatingseveralmodels,wherebyeachmodelhasoneclass morethanthepreviousone.Themaximumnumberofestimatedclasses dependsonthenumberofcoun­triesanalyzed(samplesize),thetotalnumberofvariablesobserved,andthenumberoflevelsofcategorical variablesobserved.Themodelwiththebestfittotheempiricaldatawaschosenasthemostsuitabletypol­ogy. This also means that the model output results in a conditional probability distribution in which for eachcountrythereisahighprobabilityofmembershipinoneoftheclassesandalowprobabilityofmem­bershipinanyotherclass,whichsatisfiesourgoalofcreatingatypologythatisstraightforwardandexclusive. 
Our analysis included data that consist of scores for eight policy areas on migrant integration, with thirty-three observations for each policy area. For each policy area score, the minimum value is 0 and the 
maximum is 100, with each value being one categorical level of policy area variable. Therefore, given the sample size, the reduction of categories (data recoding) was necessary in order to perform polytomous latent class analysis. We reduced the number of categories of each policy area to three so that the new val­ues are as follows: 1 if the original value of the score was less than the first tercile, 2 if the original value of the score was between the first and second tercile, and 3 if the original value of the score was higher than the second tercile, as shown in Table 1. TheanalysiswasperformedusingRstatisticalsoftwareandthepoLCApackage(DrewandLewis2011). 

3 Results 
As noted above, the total number of estimated parameters in the latent class model is a function of the 
number of variables, the number of categories for each variable, and the number of latent classes speci­
fied by the model. 
A model that consists of seven policy areas, three categories for each policy area, and two latent classes 
has twenty-nine estimated parameters. Given our sample size of thirty-three, the model with eight poli­
cy areas could handle only one class, which is not suitable for our research goals (for a further reference 
Table 1: Policy area indicator values for thirty-three European countries. 
Country I1 I2 I3 I4 I5 I6 I7 I8 (labor (family (education) (political (permanent (access (anti-(health) market) reunion) participation) residence) to nationality) discrimination) 
Albania 23122 3 23 Austria 31322 1 13 Belgium 33333 3 32 Bosnia and Herzegovina 2 1 1 1 3 2 2 2 Bulgaria 22113 1 32 Croatia 23113 1 23 Cyprus 11221 2 12 Czech Republic 2 22 2 1 2 13 Denmark 31333 2 12 Estonia 33323 1 11 Finland 33333 3 32 France 21231 3 32 Germany 32332 3 22 Greece 21222 1 23 Hungary 12123 1 33 Ireland 11231 3 22 Italy 33233 2 21 Latvia 12112 1 12 Lithuania 2 11 1 1 1 12 Luxembourg 1 23 3 2 3 13 Malta 11121 1 12 Montenegro 2 12 1 2 2 32 Netherlands 3 23 2 2 3 22 North Macedonia 1 2 1 1 1 2 3 2 Poland 12113 2 11 Portugal 33333 3 33 Romania 23112 1 33 Serbia 22211 2 23 Slovakia 12212 1 21 Slovenia 13222 2 21 Spain 33233 2 13 Sweden 33333 3 31 United Kingdom 2 13 2 1 3 33 
regardingtherelationshipbetweenmodelparameters,numberofclasses,samplesize,anddegreesoffree­dom in a latent class model, see Hagenaars and McCutcheon 2002). Therefore, we decided to exclude the data for the policy area health, which was most recently included in the MIPEX database (in 2015). With seven remaining policy areas (I1–I7), the model can be estimated for one or two classes, but not for three or more. We constructed two models: Model A with seven policy areas, three categories per policy area and one class; and Model B with seven policy areas, three categories per policy area, and two classes in order for classes to encompass different integration regimes of countries. 
Given the data restrictions imposed on the estimated models, our analysis focused on the distinction between Model A, which classifies all countries into the same type, therefore disregarding the concept of different integration regime types, and Model B, which classifies countries into two different integration regime types. 
As shown in Table 2, Model B (two classes) has lower values for both AIC (the Akaike Information Criterion) and BIC (the Bayesian Information Criterion), and also higher relative entropy, and so it has 
Table 2: Model comparison. 
Model  Number of classes  Degrees of freedom  Number of estimated parameters  Log-likelihood  Akaike Information Criterion  Bayesian Information Criterion  Relative entropy  
A  1  19  14  -253.33  534.64  555.60  0.8804  
B  2  4  33  -221.8322  501.66  545.06  0.8953  


Figure 1: Conditional probabilities of outcomes given class membership (Model B). Note: I1 = labor market, I2 = family reunion, I3 = education, I4 =political participation, I5=permanent residence, I6=access to nationality, I7=anti-discrimination 
a better fit to empirical data and the distribution of policy area score values compared to the model with oneclass(Nylund,AsparouhovandMuthén2007).Inotherwords,theclassificationofcountriesintotwo classes has a higher fit than the classification of all countries into one class. 
Theresultsofthelatentclassanalysis(Figure1)showthatforModelB45.8%ofthecountriesanalyzed belongtoClass1,and54.2%ofcountriesbelongtoClass2.InModelB,Class2includescountriesforwhich the distribution of the outcomes of the variables (policy areas) has a high probability of each of the seven variables (policy areas) having the lowest or median score (1 or 2), and a very small probability of them having the highest score (3). There are higher probabilities for the countries grouped in Class 2 to have the highest value for variables I2, I5, and I7 (family reunion, permanent residence, and anti-discrimina-tion),whereasfortheothersthecountriesfromthisclassdonothavethehighestvalue.Ontheotherhand, countries belonging to Class 1 have high probabilities of each variable’s value being the highest one. In summary, Class 2 consists of the countries where one can expectlow or medium levels of integration pol-icyinthemajorityofareas,whereasClass1containscountriesforwhichonecanexpectthehighestscores for integration policy. The most striking differences between the two classes are in regard to areas I1, I3, I4,andI6(labormarket,education,politicalparticipation,andaccesstonationality),andthesepolicyareas may serve as clear demarcation lines between countries belonging to the highest tier of integration stan­dards and others. 

Figure 2: Integration regimes according to latent class prevalence membership for the EU 28 and Western Balkan countries. 
Table 3: The latent class membership for EU 28 and Western Balkan countries. 
Class 1  Class 2  
Austria, Belgium, Denmark, Estonia, Finland, France, Germany, Ireland, Italy, Luxembourg, Netherland, Portugal, Spain, Sweden, United Kingdom  Albania, Bosnia and Hercegovina, Bulgaria, Croatia, Cyprus, Czech Republic, Greece, Hungary, Latvia, Lithuania, North Macedonia, Malta, Montenegro, Poland, Romania, Serbia, Slovakia, Slovenia  

Intermsoflatentclassprevalencemembership(Table3),weidentifiedtwodifferenttypesofintegration regimes in Europe when the Western Balkan countries are included. Class 1 includes EU countries since 1995 (the EU 15) without Greece and with Estonia, and Class 2 includes EU countries since 2004 (EU 13) withGreeceandwithoutEstoniabutwiththeWesternBalkancountries.AsshowninFigure2,aclearpat-tern of class division across Europe can be seen. 
We find high probabilities for the countries in Class 2 of having achieved high standards regarding immigrants’equalrightsandopportunitiesintheareasoffamilyreunion,permanentresidence,andanti­discrimination(I2,I5,andI7).However,theEU13(withtheexceptionofEstonia)andtheWesternBalkan countries will need to make further efforts in developing integration policies in other areas relevant for integration of immigrants in the host society such as the labor market (I1), education (I3), political par­ticipation (I4), and access to nationality (I6). According to Huddleston (2016), political participation is seen as an area of weakness for integration policy in all Western Balkan countries and most new coun­triesofimmigration,suchastheCzechRepublicandGreece.ThehighestprobabilityfortheEU13(except Estonia) and the Western Balkan countries for achieving standards of integration equivalent to those in the EU 15 countries is in anti-discrimination (I7). The differences between the two classes of immigrant integrationregimespointtoconvergenceinintegrationpoliciesandpracticesinEurope.ThenewEUmem­berstatesandWesternBalkancountriesneedmoretimetocreateandimplementlawsandpolicesinorder toachievecomprehensivehighstandardsdefinedbytheEUregardingimmigrants’equalrightsandoppor­tunities. 

4 Discussion 
The validity of traditional national models of integration is currently being questioned and reviewed due tothetransformationofnationalintegrationpoliciesaffectedbytheprocessofEuropeanizationanddiverse recent migration challenges (Joppke 2007; Choquet 2017). Calling for more international and compara­tive migration research (Bommes and Thränhardt 2010) considers paradigms of migration research to be »national paradigms« shaped with states’ reactions toward international migration and its social effects identifiedinnationalmodels.Inthissense,Pajnik(2007)advocatesthinkingofmigrationfromatransna­tional citizenship perspective. 
Variousimmigrationexperiencesofcountries,theshareofimmigrantsinthenationalpopulation,and diverseinternationalmigrationpatternsarereflectedinpoliciesandmeasuresofimportanceforintegrating immigrants. The comparison and evaluation of different countries’ migration policies make it possible to monitorthebestintegrationpractices.Basedontheoverallscoreonthe2015MIPEXIndexwithouthealth (index value 45) for the Western Balkan countries, immigrant integration policies in those countries are barely halfway favorable for social integration (Huddleston 2016). Although this value is in line with the MIPEXindexvalue(42)forthenewEUmemberstates(2004–2013),thereisroomforimprovementcom­paredtotheEU15countries(61),whichdobetterinprovidingrightsthatmayproducebetterintegration outcomes.OurresultspointtotwoclassesofintegrationregimesfortheEU28andWesternBalkancoun­tries,withacleardistinctionbetweentheEU15countriesononehandandtheEU13andWesternBalkan countries on the other. The exceptions are Greece and Estonia, which, regarding their EU membership group,doworseandbetterinthegovernanceofintegratingimmigrants,respectively.Lowerscoresinsome policy areas in Greece in comparison to Estonia show that targeted support in Greece is missing. Limited fundsforintegrationarenotinlinewithalargenumberofasylumseekersandillegalarrivalsofimmigrants. Lookingattargetedsupportineducationandthelabormarket,thereismoreresponsivenesstoimmigrants’ specificneedsinEstonia,whichhasasmallnumberofimmigrantsperyear(Huddlestonetal.2015).High 
standards in anti-discrimination in Greece (Huddleston et al. 2015) are in line with the probability val­ues of the class it belongs to. 
The Western Balkan countries are continuously harmonizing their legislation relevant to migration with EU standards. However, according to the MIPEX report for the countries of the Western Balkan (Huddleston 2016), indicators of targeted support for immigrants in the labor market and in education express that those measures are completely nonexistent. There are no proper immigrant integration poli­cies for immigrants’ participation in political life, consultative bodies, and implementation policies. Nevertheless,customizingdifferentservicesforasmallnumberofimmigrantsisnoteasilyfeasible.Likewise, the creation of targeted measures to support the integration of immigrants in certain sectors, such as the labormarket,education,orpoliticalparticipation,dependsonthefinancialcapacityofthestateandaddi­tional funds for these purposes. For EU member states, financial resources for integration measures are available through EU funds, whereas other countries face more challenges in this regard. Doomernik and Bruquetas-Callejo(2015)pointoutthatintegrationmeasuresincentralEuropelargelydependonEUfunds. 
Comparing our classification with the results obtained by Meuleman and Reeskens (2008) as well as with the results obtained by Zamfir et al. (2014) for twenty-seven EU countries, based on the 2007 and 2010 MIPEX data, respectively, we find that the outcomes are not consistent when the Western Balkan countries are incorporated into the classification of integration regimes. An important difference is that, based on the same policy areas – except for Meuleman and Reeskens (2008), who did not cover educa-tion–MeulemanandReeskens(2008)andZamfiretal.(2014)classifiedintegrationregimesintooneclass more (i.e., three). Latent Class 2 from our analysis is similar to latent Class 2 of Meuleman and Reeskens (2008),whichencompassedalleasternEuropeancountriesplusAustria,Denmark,Greece,andMalta,which were considered to have exclusionist integration policies, characterized by difficult access to nationality andpoliticalparticipation.Inthisregard,Denmarkhasmadesignificantprogresssince2007,whereasprogress in integration policy in Austria is related to labor market mobility as the major political priority for new integrationpolicies(Huddlestonetal.2015).Inourclassification,basedonthe2014MIPEXdata,Austria andDenmarkareinClass1,pointingtotheimprovedlegalenvironmentofimmigrantintegration.According toourresearch findings,differences andinequalities inthegovernanceofimmigrant integrationbetween the old and the new EU member states are more visible when a broader territory is covered. 
InthecourseoftheanalysisoftheMIPEXdata,asLukić(2018)pointsout,itshouldbeborneinmind that these data point only to the legal and political framework of immigrant integration, and not to more complex integration policy implementation and effectiveness. According to Czaika and de Haas (2013), thecomplexityofperceptionoftheeffectivenessofimmigrationpoliciesmightbetheoutcomeoftheunclear boundarybetweenmigration/integrationpolicyaswellasbetweenmigrationpolicyandotherpublicpoli­cies.Indeed,theintertwiningofdifferentareaswithintheinstitutionalframeworksignificantlyaffectsthe integration of immigrants. Given the diverse integration experience and immigration patterns between countries, the appropriateness of comparing integration policies through MIPEX has recently been ques­tioned(GregurovićandŽuparić-Iljić2018).Nonetheless,MIPEXisthemostcomprehensivedatabaseand the most widely used tool for measuring immigrant integration policies. 

5 Conclusion 
This article examined immigrant integration regimes in Europe according to policy priorities related to immigrants’ socioeconomic rights. A latent class analysis showedthat a model with two classes has a bet­ter fit to the MIPEX data than a baseline model in which no distinction between classes is made. Due to the data and method limitations, no further models could be tested. 
The results of the latent class analysis demonstrate that two distinct types of integration regimes can be distinguished across the EU 28 and the Western Balkan countries. There are clear differences between the EU 15 group of countries versus the EU 13 and Western Balkan countries group regarding integra-tionregimes.Thecountriesinthefirstgrouphaveachievedhighstandardsinpolicyareasrelevanttointegrating immigrants. Furthermore,intheWesternEuropeancountriesvariationsinimmigrantintegration-related legislationandpolicyinstrumentsproducedbyhistoricalandnationalcontextsaredecreasing.Thecountries from the more numerous second group are lagging in developing integration policies and targeted mea­suresforsupportingtheintegrationofimmigrants.Thisisinlinewiththelong-termprocessofintegrating 
immigrants into the countries’ societies, whereas creating targeted measures for supporting the integra­tionofimmigrantsisnoteasytoachieveincountrieswithasmallnumberofimmigrantsandlimitedfinancial means. 
Continued comparative analysis of national policies toward the integration of immigrants can shed light on how particular countries manage to incorporate immigrants in various social spheres while mak­ing changes in those policies at the same time. The outcomes provide inputs for policies aiming at best practices in immigrant integration. Monitoring differences within a broader geographical and social set­tingmakesitpossibletobetterunderstandthestrengthsandweaknessesofintegrationregimes.Themain conclusion is that there is convergence in integration regimes where the temporal dimension of migra­tion policy development and the geographical dimension are visible. 
ACKNOWLEDGEMENT: This paper was written as part of the 2020 Research Program of the Institute ofSocialScienceswiththesupportoftheMinistryofEducation,ScienceandTechnologicalDevelopment of the Republic of Serbia. 

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