Mixed-frequency VAR: a new approach to forecasting migration in Europe using macroeconomic data
Forecasting international migration is a challenge that, despite its political and policy salience, has seen a limited success so far. In this proof-of-concept paper, we employ a range of macroeconomic data to represent different drivers of migration. We also take into account the relatively consist...
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Cambridge University Press
2025-01-01
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| Series: | Data & Policy |
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| Online Access: | https://www.cambridge.org/core/product/identifier/S2632324924000828/type/journal_article |
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| author | Emily R. Barker Jakub Bijak |
| author_facet | Emily R. Barker Jakub Bijak |
| author_sort | Emily R. Barker |
| collection | DOAJ |
| description | Forecasting international migration is a challenge that, despite its political and policy salience, has seen a limited success so far. In this proof-of-concept paper, we employ a range of macroeconomic data to represent different drivers of migration. We also take into account the relatively consistent set of migration policies within the European Common Market, with its constituent freedom of movement of labour. Using panel vector autoregressive (VAR) models for mixed-frequency data, we forecast migration in the short- and long-term horizons for 26 of the 32 countries within the Common Market. We demonstrate how the methodology can be used to assess the possible responses of other macroeconomic variables to unforeseen migration events—and vice versa. Our results indicate reasonable in-sample performance of migration forecasts, especially in the short term, although with varying levels of accuracy. They also underline the need for taking country-specific factors into account when constructing forecasting models, with different variables being important across the regions of Europe. For the longer term, the proposed methods, despite high prediction errors, can still be useful as tools for setting coherent migration scenarios and analysing responses to exogenous shocks. |
| format | Article |
| id | doaj-art-05ec757712744480b029f09eba40379c |
| institution | Kabale University |
| issn | 2632-3249 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Cambridge University Press |
| record_format | Article |
| series | Data & Policy |
| spelling | doaj-art-05ec757712744480b029f09eba40379c2025-01-16T21:51:32ZengCambridge University PressData & Policy2632-32492025-01-01710.1017/dap.2024.82Mixed-frequency VAR: a new approach to forecasting migration in Europe using macroeconomic dataEmily R. Barker0https://orcid.org/0000-0003-3368-9169Jakub Bijak1https://orcid.org/0000-0002-2563-5040Department of Social Statistics and Demography, University of Southampton, Southampton, UKDepartment of Social Statistics and Demography, University of Southampton, Southampton, UKForecasting international migration is a challenge that, despite its political and policy salience, has seen a limited success so far. In this proof-of-concept paper, we employ a range of macroeconomic data to represent different drivers of migration. We also take into account the relatively consistent set of migration policies within the European Common Market, with its constituent freedom of movement of labour. Using panel vector autoregressive (VAR) models for mixed-frequency data, we forecast migration in the short- and long-term horizons for 26 of the 32 countries within the Common Market. We demonstrate how the methodology can be used to assess the possible responses of other macroeconomic variables to unforeseen migration events—and vice versa. Our results indicate reasonable in-sample performance of migration forecasts, especially in the short term, although with varying levels of accuracy. They also underline the need for taking country-specific factors into account when constructing forecasting models, with different variables being important across the regions of Europe. For the longer term, the proposed methods, despite high prediction errors, can still be useful as tools for setting coherent migration scenarios and analysing responses to exogenous shocks.https://www.cambridge.org/core/product/identifier/S2632324924000828/type/journal_articleBayesian forecastingmigrationmixed-frequency modelspanel VAR |
| spellingShingle | Emily R. Barker Jakub Bijak Mixed-frequency VAR: a new approach to forecasting migration in Europe using macroeconomic data Data & Policy Bayesian forecasting migration mixed-frequency models panel VAR |
| title | Mixed-frequency VAR: a new approach to forecasting migration in Europe using macroeconomic data |
| title_full | Mixed-frequency VAR: a new approach to forecasting migration in Europe using macroeconomic data |
| title_fullStr | Mixed-frequency VAR: a new approach to forecasting migration in Europe using macroeconomic data |
| title_full_unstemmed | Mixed-frequency VAR: a new approach to forecasting migration in Europe using macroeconomic data |
| title_short | Mixed-frequency VAR: a new approach to forecasting migration in Europe using macroeconomic data |
| title_sort | mixed frequency var a new approach to forecasting migration in europe using macroeconomic data |
| topic | Bayesian forecasting migration mixed-frequency models panel VAR |
| url | https://www.cambridge.org/core/product/identifier/S2632324924000828/type/journal_article |
| work_keys_str_mv | AT emilyrbarker mixedfrequencyvaranewapproachtoforecastingmigrationineuropeusingmacroeconomicdata AT jakubbijak mixedfrequencyvaranewapproachtoforecastingmigrationineuropeusingmacroeconomicdata |