Dynamics and determinants of emigration: the case of Croatia and the experience of new EU member states

Draženović, Ivana; Kunovac, Marina; Pripužić, Dominik

doi:10.3326/pse.42.4.3.

7901
Views

2219
Downloads

Dynamics and determinants of emigration: the case of Croatia and the experience of new EU member states

Ivana Draženović*

Marina Kunovac*

Dominik Pripužić*

Download citation

https://doi.org/10.3326/pse.42.4.3

FULL ARTICLE

FIGURES & DATA

REFERENCES

CROSSMARK POLICY

METRICS

LICENCING

PDF

Table 2
Determinants of emigration flows from new EU Member States to the core EU countries between 2000 and 2016, Fixed effects estimator (FE) and Poisson pseudo maximum likelihood estimator (PPML)

	Model 1 (Baseline) FE	Model 1 (Baseline) PPML	Model 2 FE	Model 2 PPML
Distance	-	-1.48***	-	-1.54***
Distance	-	(0.00)	-	(0.00)
Population	0.59	1.41	0.99**	5.85***
Population	(0.17)	(0.35)	(0.02)	(0.00)
GDP PC in PPS (origin)	0.11	0.27
GDP PC in PPS (origin)	(0.59)	(0.46)
GDP PC in PPS (destination)	1.55	2.15**
GDP PC in PPS (destination)	(0.00)	(0.01)
Transitional provisions	0.54	0.34***	0.46***	0.46***
Transitional provisions	(0.00)	(0.00)	(0.00)	(0.00)
Employment rate (origin)			-1.45***	-5.04***
Employment rate (origin)			(0.00)	(0.00)
Employment rate (destination)			1.2*	8.15***
Employment rate (destination)			(0.06)	(0.00)
Output gap (origin)			-2.27***	3.07
Output gap (origin)			(0.00)	(0.2)
Output gap (destination)			3.74***	2.03**
Output gap (destination)			(0.00)	(0.04)
Corruption index (origin)			0.03	-1.66***
Corruption index (origin)			(0.89)	(0.00)
Corruption index (destination)			3.78***	2.46*
Corruption index (destination)			(0.00)	(0.09)
Share of youth (20-34) origin			1.5***	0.19
Share of youth (20-34) origin			(0.00)	(0.8)
Share of tertiary educated (origin)			0.25	0.58*
Share of tertiary educated (origin)			(0.14)	(0.07)
Cons	-11.91	0.23	-13.65	5.51
Number of observations	1958	1972	1958	1972
R2	0.46	0.78	0.53	0.82

Note: *, ** and *** refer to 10%, 5% and 1% statistical significance levels, respectively. P-values are in parenthesis. All specifications include origin and destination fixed effects dummies. Parameters associated to output gap for origin and destination country are multiplied by 100 since the output gap enters the model specification in levels instead of being transformed into logarithms, due to negative values.

Source: Authors’ elaboration based on national statistical offices of the core EU countries immigration data and on the data presented appendix 1.

Table A1
Data sources and details, independent variables

Data Sources and details for set of independent variables
Variable	Description	Source	Estimation details
GDP PC in PPS	Gross domestic product at market prices, current prices, PPS per capita	Eurostat online statistical database	Destination and origin country, in log
Unemployment rate	Yearly unemployment rates, from 15 to 64 years, percentage	Eurostat online statistical database	Destination and origin country, in log
Population	Population on 1 January, total	Eurostat online statistical database	Relative values between destination and origin country, in log
Distance	Distance between two countries is calculated based on latitudes and longitudes of the most important cities/agglomerations (in terms of population). Mayer and Zignago (2011)	CEPII database	In log
Youth population number	Population on 1 January, from 20 to 34 years	Eurostat online statistical database	Origin country, as a share in total population, in log
Tertiary educated	Population by educational attainment level, from 15 to 64 years, tertiary education (levels 5-8)	Eurostat online statistical database	Origin country, as a share in total population, *1000, in log
Corruption index	Control of corruption captures perceptions of the extent to which public power is exercised for private gain, including both petty and grand forms of corruption, as well as "capture" of the state by elites and private interests link	Worldwide Governance Indicators (WGI), The World Bank	Destination and origin country, in log
Governance index	Government effectiveness captures perceptions of the quality of public services, the quality of the civil service and the degree of its independence from political pressures, the quality of policy formulation and implementation, and the credibility of the government's commitment to such policies link	Worldwide Governance Indicators (WGI), The World Bank	Destination and origin country, in log
Output gap	Output Gaps (% of potential output), HP filter	European Commission CIRCAB, II. autum forecast	Destination and origin country
Employment rates	Yearly employment rates, from 15 to 64 years, percentage	Eurostat online statistical database	Destination and origin country, in log
Transitional Provisions	Variable representing the access to common free EU market for BG and RO takes value 1 for FI, SE from 2007, for DK from 2009, for IT and IE from 2012 and for all other countries from 2014. Variable representing the access to common free EU market for HR takes value 1 for DK, FI, IR, SE from 2013, for BE, IT, DE, LU from 2015, while NL, AT and UK apply transitional provisions for HR during the entire sample period (sample is ending in 2016, while transitional provisions applied by NL, AT and UK should be lifted by June 2018). Variable representing the access to common free EU market for CZ, SK, SI, PL, HU, LV, LT, EE takes value 1 for UK, SE, IE from 2004, for IT, FI from 2006, for NL, LU from 2007, for BE, DK from 2009 and for AT, DE from 2011	European Commission	Set of dummy variables

Table A3
Total migration flow in Croatia – approximation based on discretional combination of different data sources

Emigration from and to Croatia following the EU accession	2013	2014	2015	2016	2013-2016
(1) Emigration to core EU countries from national statistical offices of core EU countries	31,655	53,666	72,528	71,314	229,163
(2) Emigration to "rest of the world" according to CBS	11,220	9,049	11,116	9,238	40,623
(3) Total emigration = (1) + (2)	42,875	62,715	83,644	80,552	269,786
(4) CNB total emigration	15,262	20,858	29,651	36,436	102,207
(5) Emigration coefficient	2.8	3.0	2.8	2.2	2.6
(6) Immigration from core EU countries according to national statistical offices of core EU countries	14,164	19,346	23,261	23,422	80,193
(7) Immigration from "rest of the world" according to CBS	8,676	8,540	8,512	9,705	35,433
(8) Total immigration = (6) + (7)	22,840	27,886	31,773	33,127	115,626
(9) CBS total immigration	10,378	10,638	11,706	13,985	46,707
(10) Immigration coefficient	2.2	2.6	2.7	2.4	2.5
(11) Net emigration = (3) - (8)	20,035	34,829	51,871	47,425	154,160
(12) CNB net emigration	4,884	10,220	17,945	22,451	55,500
(13) Net emigration coefficient	4.1	3.4	2.9	2.1	2.8

Note: UK and Ireland not included in immigration numbers.

Source: CBS and national statistical offices of the core EU countries.

Table A5
Determinants of emigration flows from new EU Member States to the core EU countries between 2000 and 2016, Poisson pseudo maximum likelihood estimator, extended specification Model 4

	Model 4 FE	Model 4 PPML
Distance	-	-1.52***
Distance	-	(0.00)
Population	1.69***	6.63***
Population	(0.00)	(0.00)
Transitional provisions	0.47***	0.42***
Transitional provisions	(0.00)	(0.00)
Unemployment rate (origin)	0.19**	0.69***
Unemployment rate (origin)	(0.03)	(0.00)
Unemployment rate (destination)	-0.03	-1.09***
Unemployment rate (destination)	(0.66)	(0.00)
Output gap (origin)	2.18**	1.53
Output gap (origin)	(0.01)	(0.34)
Output gap (destination)	4.64***	2.52*
Output gap (destination)	(0.00)	(0.09)
Governance index (origin)	-0.22	-2.29***
Governance index (origin)	(0.52)	(0.00)
Governance index (destination)	0.89	-2.71
Governance index (destination)	(0.11)	(0.40)
Share of youth (20-34) origin	1.71***	1.34
Share of youth (20-34) origin	(0.00)	(0.11)
Share of tertiary educated (origin)	0.41**	0.69**
Share of tertiary educated (origin)	(0.02)	(0.01)
Cons	-1.04	42.2**
Number of observations	1958	1972
R²	0.51	0.82

Source: Authors’ elaboration based on national statistical offices of the core EU countries immigration data and on the data presented in appendix 1.

Table A6
Number of emigrants from Croatia by region (as % of total population of the region) between 2001 and 2016. Central Bureau of Statistics data, gross emigration flows

	2001	2002	2003	2004	2005	2006	2007	2008	2009	2010	2011	2012	2013	2014	2015	2016
Eastern Croatia	0.2	0.2	0.2	0.3	0.2	0.3	0.3	0.2	0.4	0.3	0.3	0.3	0.4	0.6	1.0	1.4
Central Croatia	0.2	0.2	0.2	0.2	0.2	0.2	0.3	0.3	0.3	0.3	0.4	0.3	0.5	0.6	0.8	1.0
Lika and Gorski kotar	0.2	0.2	0.2	0.1	0.1	0.2	0.2	0.2	0.2	0.2	0.3	0.3	0.4	0.6	0.9	1.0
Central and Southern Adriatic	0.1	0.2	0.1	0.1	0.1	0.1	0.2	0.2	0.2	0.3	0.4	0.4	0.5	0.5	0.6	0.7
Northen Adriatic	0.2	0.2	0.1	0.1	0.1	0.1	0.1	0.1	0.1	0.2	0.5	0.4	0.3	0.4	0.6	0.7
Northwestern Croatia	0.1	0.1	0.1	0.1	0.0	0.1	0.1	0.0	0.0	0.0	0.1	0.1	0.1	0.3	0.4	0.6
City of Zagreb	0.2	0.6	0.2	0.1	0.1	0.1	0.1	0.1	0.1	0.2	0.3	0.3	0.3	0.4	0.6	0.6

Notes: Eastern Croatia encompasses Virovitičko-podravska, Požeško-slavonska, Brodsko-posavska, Osječko-baranjska and Vukovarsko-srijemska counties. Central Croatia encompasses Zagrebačka, Sisačko-moslavačka, Karlovačka and Bjelovarsko-bilogorska counties. Lika and Gorski kotar encompass Primorsko-goranska and Ličko-senjska counties. Central and Southern Adriatic encompass Zadarska, Šibensko-kninska, Splitsko-dalmatinska and Dubrovačko-neretvanska counties. Northen Adriatic refers to Istarska County. Northwestern Croatia encompass Krapinsko-zagorska, Varaždinska, Međimurska and Koprivničko-križevačka counties.

Source: CBS.

Crossmark is a multi-publisher initiative from Crossref to provide a standard way for readers to locate the current version of a piece of content. By applying the Crossmark logo, the Institute of Public Finance is committing to maintaining the content it publishes and to alerting readers to changes if and when they occur.

Clicking on the Crossmark logo will tell you the current status of a document and may also give you additional publication record information about the document.

For more details see IPF Crossmark policy page.

December, 2018
IV/2018

Vladimir Arčabić
Fiscal convergence and sustainability in the European Union

Ozana Nadoveza Jelić, Margareta Gardijan Kedžo
Efficiency vs effectiveness: an analysis of tertiary education across Europe

Ivana Draženović, Marina Kunovac, Dominik Pripužić
Dynamics and determinants of emigration: the case of Croatia and the experience of new EU member states

Branko Stanić
Determinants of subnational budget/fiscal transparency: a review of empirical evidence

Predrag Bejaković
Working Together: Integration, Institutions and the Sustainable Development Goals, World Public Sector Report 2018