Public Support for Emigration Post-EU Accession: An LM Model Analysis

• Authors: Ewa Genge

Title variants

PL

Poparcie społeczne dla emigracji po przystąpieniu do UE: analiza z wykorzystaniem ukrytych modeli LM

Abstracts

PL

Cel: Celem badania jest określenie wpływu zmiennych socjodemograficznych (tj. wiek, wykształcenie, stan cywilny, status społeczno-zawodowy) na nastawienie do emigracji po wejściu Polski do UE. Metodyka: Zastosowano ukryty model Markowa z wykorzystaniem zmiennych towarzyszących, mających wpływ nie na ukrytą, lecz na obserwowaną część modelu LM. Model ten, uwzględniający zmienne w czasie efekty losowe, został wykorzystany w celu analizy zbioru panelowego dotyczącego gotowości Polaków do pracy zagranicą w latach 2005–2015. Wyniki: Opierając się na polskim panelowym badaniu społecznym, tj. Diagnozie Społecznej, pokazano, że analizowany zbiór można wyjaśnić za pomocą dwóch stanów ukrytych, charakteryzujących się podobną skłonnością do emigracji. Zaobserwowano, że w latach 2011–2015 (następujących po pierwszej fazie akcesyjnej) Polacy wykazali większą stabilność w poglądach dotyczących emigracji. Na podstawie dostępnych (stałych i zmiennych w czasie) zmiennych towarzyszących pokazano, że osoby o pewnych cechach są bardziej skłonne do migracji niż inne. Implikacje i rekomendacje: Przedstawione podejście może być zastosowane w celu ukazania zmieniających się zachowań społecznych również w innych krajach, które doświadczyły masowego odpływu ludności. Ponadto analiza uzyskanych wyników może posłużyć rozwiązywaniu wyzwań politycznych i skutecznemu zarządzaniu migracją, także w przypadku przyszłych danych, dotyczących nastawienia do ukraińskich uchodźców przybywających obecnie do Polski. Oryginalność/wartość: Główną zaletą zastosowanego modelu, w porównaniu z standardowym modelem z efektami losowymi lub modelem klas ukrytych ze zmiennymi towarzyszącymi, jest to, że nieobserwowalna heterogeniczność może być zmienna w badanym czasie. Inaczej niż w badaniach poprzednich założono tu, że udzielane odpowiedzi respondentów mogą różnić się z powodu nieobserwowalnej, zmiennej w czasie współzmiennej, takiej jak „uczucia patriotyczne”. Zastosowany model, uwzględniający również wagi badania panelowego, pozwala także na uzyskanie lepszego dopasowania w porównaniu ze standardowym modelem efektów losowych, zaś parametry modelu LM umożliwiają dodatkowo ocenę dynamiki badanej zmiennej ukrytej.

EN

Aim: Since 2004 European countries, such as Germany and the United Kingdom, have noted an unusual upward trend of migrants from Central and Eastern Europe. The author aimed to examine the popular perception of emigration from Poland in the years following EU accession. Moreover, the study presents the effect of the observed socio-economic features (i.e. age, education, marital status, socio-professional status) affecting the conditional probabilities of the response variable, considering also the unobserved heterogeneity between the respondents representing Polish society. Methodology: The study was based on the Latent Markov (LM) models which allowed finding homogenous groups of respondents on the basis of their definite responses measured at different points in time. The author compared the respondents behaviour in the groups arriving just after EU accession, in relation to the other surveyed surges in migration using the Latent Markov models with different types of constraints. Then, to show the effect of observable socio-economic characteristics, taking into account the unobserved heterogeneity between the subjects, the study employed the version including the covariates in the measurement part of the model. Results: Based on the Polish longitudinal social survey, i.e. Social Diagnosis, the study shows that the analysed data can be explained by two latent states of Poles sharing the same propensity towards emigration. It was observed that Poles were more stable in their feelings concerning their approach to the emigration in the period 2011–2015 (following the first post-accession phase). Based on the available (time-constant and time-varying) covariates, the author demonstrated that certain types of people are more prone to migrate than others. Implications and recommendations: The presented approach could be applied to data from other economies – both within the EU and outside it – which have also seen massive outflows of people, to show the changing behaviour of society. This methodology might also be helpful with policy challenges and the effective management of migration, as well as for future data concerning the attitudes towards refugees from Ukraine coming to Poland at present. Originality/value: Unlike previous studies, the author assumed that the attitudes toward emigration can vary on the response variable, i.e. because of the unobserved covariate such as ‘patriotic behaviour’ (unobserved heterogeneity), which may change over time. The study applied the appropriate LM techniques extended to include the covariates in the measurement part of the LM model and the longitudinal weights of the survey. Note that the applied model also allowed achieving a better measure-of-fit compared to the standard random-effect model, and the parameters of the LM model additionally enabled to evaluate the dynamic of the latent trait.

Keywords

EN

constrained Latent Markov (LM) model; covariates; emigration; unobserved heterogeneity; longitudinal data

PL

emigracja; heterogeniczny oraz częściowo-heterogeniczny ukryty model Markowa; niejednorodność; zmienne towarzyszące

• Publisher: Uniwersytet Ekonomiczny we Wrocławiu. Wydawnictwo Uniwersytetu Ekonomicznego we Wrocławiu
• Journal: Econometrics. Ekonometria. Advances in Applied Data Analytics
• Year: 2024
• Volume: 28
• Issue: 3
• Pages: 9-23

Dates

published

2024

Contributors

author

Ewa Genge

• University of Economics in Katowice

• https://orcid.org/0000000288993697

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Identifiers

DOI

10.15611/eada.2024.3.02

Biblioteka Nauki

59125031