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Outmigration and Remittances as Facilitating Conditions for Economic Transition in Romania

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Labor Markets, Migration, and Mobility

Part of the book series: New Frontiers in Regional Science: Asian Perspectives ((NFRSASIPER,volume 45))

Abstract

Cross-border migration is a phenomenon of all times, because people seek to improve their economic fortune—and that of their relatives or community—through labour mobility. There is an extant literature on the backgrounds and rationality of migration decisions. Research has extensively addressed both the specific and the wider impacts of a migration influx into a destination or host country. The impacts of outmigration and remittances on the source country have received less attention. The present paper examines whether outmigration from (national or regional) labour markets—and the related remittances—have exerted an impact on the Romanian political-economic transition in the post-communist period, especially after the country’s access to the EU. Thus, the system-wide migration impacts transmitted through both remittances and labour market mechanisms are analysed for Romania, using a long-term time series (1991–2015), while accounting for endogeneity of migration and remittances. The post-communist period is split up into three characteristic stages, while the difference in the magnitude of these effects for each stage is tested. Our findings show that migration has exerted an overall net positive effect on economic growth, except for the second stage when the Romanian economy moved from a shortage of jobs to a shortage of labour. The positive effects were due to a reduction in the social security burden, given the prevailing high unemployment rate. Remittances from migration were also shown to enhance growth, with a stronger effect during the second stage, which may have offset the negative effects of outmigration. The lesson for Romanian policy-making is that migration is not sufficient for economic development, as home country conditions need to continuously improve for unleashing the full development potential of outmigration.

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Notes

  1. 1.

    The statistics refers to working age of movers (20–64 year) from EU and European Free Trade Area (EFTA) countries who are residing in other than their country of citizenship. In 2018 the Romanian outflows accounted for 158 from a total of 971 thousands at EU28 level.

  2. 2.

    The largest stocks of Romanian working-age population were shown to be in Italy (931 thousands), Spain (559 thousands), Germany (370 thousands) and United Kingdom (345 thousands).

  3. 3.

    According to the Land Fund Law no. 18/1991 available at: http: //www.cdep.ro/pls/legis/legis_pck.htp_act_text?idt=7996.

  4. 4.

    See the Emergency Ordinance no. 55 in 20 June 2007 for the establishment of the Romanian Immigration Office through the reorganization of the Authority for Aliens and the National Office for Refugees, but also for amending and supplementing certain normative acts, available at: http://www.mmuncii.ro/pub/imagemanager/images/file/Legislatie/ORDONANTE-DE-GUVERN/OUG55-2007_act.pdf.

  5. 5.

    See the Emergency Ordinance no. 187 of 20 February 2008 concerning the approval of the Action plan for encouraging the return of Romanian citizens working abroad, available at http://www.mmuncii.ro/pub/imagemanager/images/file/Legislatie/HOTARARI-DE-GUVERN/HG187-2008.pdf.

  6. 6.

    See Law 157/11 July 2011, available at: http://www.mmuncii.ro/j33/images/Documente/Legislatie/LEGE157din11iul2011.pdf. However, given the labour shortage, this measure was cancelled by the Law 247/2018 which reduced the required salary for migrant workers from the average gross wage to the minimum gross wage: https://ec.europa.eu/migrant-integration/?action=media.download&uuid=F40D5BCD-A311-1522-B3B4AAAB27705D70.

  7. 7.

    More details about instruments used are given as a note to every estimation table. Lags of endogenous regressors were used as internal instruments, which are commonly used for instrumental variables. External instruments were also included, namely lags in wages for the migration models and lags in migration for the remittance models.

  8. 8.

    It is interesting to note that, while models (1a)–(1d) display better the AIC and BIC scores with the series in levels (Table 7.7), models (2a)–(2d) display better scores with a detrended series.

  9. 9.

    Estimations with detrended series display better the AIC and BIC scores. However, this result is not confirmed by the models using the series in levels [Eqs. (2b)–(2c) in Table 7.7].

  10. 10.

    However, the result is not confirmed by the models using detrended series which report better AIC and BIC scores [Eq. (4b) in Table 7.6].

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Acknowledgments

This work was supported by a grant of Ministry of Research and Innovation, CNCS–UEFISCDI, project number PN-III-P4-ID-PCCF-2016-0166, within PNCDI III project ‘ReGrowEU—Advancing ground-breaking research in regional growth and development theories, through a resilience approach: towards a convergent, balanced and sustainable European Union’.

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Authors and Affiliations

  1. Centre for European Studies, Alexandru Ioan Cuza University of Iasi, Iasi, Romania

    Cristian Incaltarau, Karima Kourtit & Peter Nijkamp

  2. Faculty of Economics and Business Administration, Alexandru Ioan Cuza University of Iasi, Iasi, Romania

    Liviu George Maha

  3. Open University, Heerlen, The Netherlands

    Karima Kourtit & Peter Nijkamp

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  2. Liviu George Maha
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  3. Karima Kourtit
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  4. Peter Nijkamp
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Corresponding author

Correspondence to Cristian Incaltarau .

Editor information

Editors and Affiliations

  1. School of Social Science, University of Waikato, Hamilton, Waikato, New Zealand

    William Cochrane

  2. School of Accounting, Finance and Economics, University of Waikato, Hamilton, Waikato, New Zealand

    Michael P. Cameron

  3. School of Accounting, Finance and Economics, University of Waikato, Hamilton, Waikato, New Zealand

    Omoniyi Alimi

Appendices

Appendix 1: Data

Table 7.1 Variable definitions and sources
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Table 7.2 Descriptive statistics
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Appendix 2: Stationarity and Cointegration Tests

Table 7.3 Unit root and stationarity tests on detrended series
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Table 7.4 Unit root and stationarity tests on model residuals
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Appendix 3: Estimation Results

Table 7.5 Estimation results of the long-term impact of migration on GDP per capita and unemployment in Romania (1991–2015, detrended series)
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Table 7.6 Estimation results of the long-term impact of remittances on GDP per capita and unemployment in Romania (1991–2015, detrended series)
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Table 7.7 Estimation results of the long-term impact of migration on GDP per capita and unemployment in Romania (1991–2015)
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Table 7.8 Estimation results of the long-term impact of remittances on GDP per capita and unemployment in Romania (1991–2015)
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Incaltarau, C., Maha, L.G., Kourtit, K., Nijkamp, P. (2021). Outmigration and Remittances as Facilitating Conditions for Economic Transition in Romania. In: Cochrane, W., Cameron, M.P., Alimi, O. (eds) Labor Markets, Migration, and Mobility. New Frontiers in Regional Science: Asian Perspectives, vol 45. Springer, Singapore. https://doi.org/10.1007/978-981-15-9275-1_7

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