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Commuting in the Baltic States: Patterns, determinants and gains

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  • Hazans, Mihails

Abstract

To what extent does commuting reduce urban – rural and regional wage disparities? This question is addressed by estimating two sets of earnings functions (based on 2000 LFS data for Estonia, Latvia and Lithuania): with location variables (like capital city, rural etc.) measured at the workplace and at the place of residence. The main finding is that in Estonia and Latvia commuting has significantly narrowed the ceteris paribus wage gap between capital city and rural areas, as well as between capital and other cities. In Lithuania only residents of urban areas in the capital county manage to catch up significantly with the capital, while overall urban-rural gap remains almost unchanged. So different outcomes are explained by country-specific skills composition of rural – urban commuting flows and wage discrimination against rural residents in Lithuanian urban markets. Individual gains to rural – urban or inter-city commuting (both with and without correcting to selectivity) are uniformly big in Latvia but on average negligible in Lithuanian urban areas.

Suggested Citation

  • Hazans, Mihails, 2003. "Commuting in the Baltic States: Patterns, determinants and gains," ZEI Working Papers B 02-2003, University of Bonn, ZEI - Center for European Integration Studies.
  • Handle: RePEc:zbw:zeiwps:b022003
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    References listed on IDEAS

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    Citations

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    Cited by:

    1. Peter Huber, 2011. "Educational Attainment and Education-job Mismatch of Cross-border Commuters in the EU," WIFO Working Papers 388, WIFO.
    2. Napolitano, Oreste & Bonasia, Mariangela, 2010. "Determinants of different internal migration trends: the Italian experience," MPRA Paper 21734, University Library of Munich, Germany.
    3. Peter Huber, 2014. "Are Commuters in the EU Better Educated than Non-commuters but Worse than Migrants?," Urban Studies, Urban Studies Journal Limited, vol. 51(3), pages 509-525, February.
    4. Mihails Hazans, 2004. "Does Commuting Reduce Wage Disparities?," Growth and Change, Wiley Blackwell, vol. 35(3), pages 360-390, September.
    5. Silaghi, Monica Ioana & Ghatak, Subrata, 2011. "Why do not They Move from Rural to Urban Areas? Inter-Regional Migration in Romania," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(1), pages 143-158, March.
    6. repec:dgr:uvatin:20110114 is not listed on IDEAS
    7. Georg Gottholmseder & Engelbert Theurl, 2006. "Nicht-PendlerInnen, Binnen- und GrenzpendlerInnen - Eine sozioökonomische Charakterisierung am Beispiel der Pendlerregion Bodenseeraum," Wirtschaft und Gesellschaft - WuG, Kammer für Arbeiter und Angestellte für Wien, Abteilung Wirtschaftswissenschaft und Statistik, vol. 32(2), pages 209-243.
    8. Olga Kupets, 2012. "Characteristics and Determinants of Internal Labor Mobility in Ukraine," World Bank Publications - Reports 26804, The World Bank Group.
    9. Giovanni Russo & Federico Tedeschi & Aura Reggiani & Peter Nijkamp, 2014. "Commuter Effects on Local Labour Markets: A German Modelling Study," Urban Studies, Urban Studies Journal Limited, vol. 51(3), pages 493-508, February.
    10. Mihails Hazans, 2003. "Potential emigration of Latvian labour force after joining the EU and its impact on Latvian labour market," SSE Riga/BICEPS Research Papers 2003-2, Baltic International Centre for Economic Policy Studies (BICEPS);Stockholm School of Economics in Riga (SSE Riga).
    11. World Bank, 2012. "In Search of Opportunities : How a More Mobile Workforce Can Propel Ukraine’s Prosperity (Vol. 2 of 2) : Technical Report," World Bank Publications - Reports 12287, The World Bank Group.
    12. Anna Zasova & Aleksejs Melihovs, 2005. "Assessment of Labour Market Elasticity in Latvia," Working Papers 2005/03, Latvijas Banka.
    13. Hazans, Mihails, 2003. "Determinants of inter-regional migration in the Baltic countries," ZEI Working Papers B 17-2003, University of Bonn, ZEI - Center for European Integration Studies.
    14. Hazans, Mihails, 2005. "Unemployment and the earnings structure in Latvia," Policy Research Working Paper Series 3504, The World Bank.

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    More about this item

    Keywords

    commuting; earnings functions; treatment effects model; wage disparities; Baltic States; ethnic minority;
    All these keywords.

    JEL classification:

    • J31 - Labor and Demographic Economics - - Wages, Compensation, and Labor Costs - - - Wage Level and Structure; Wage Differentials
    • J61 - Labor and Demographic Economics - - Mobility, Unemployment, Vacancies, and Immigrant Workers - - - Geographic Labor Mobility; Immigrant Workers
    • R23 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Household Analysis - - - Regional Migration; Regional Labor Markets; Population
    • D63 - Microeconomics - - Welfare Economics - - - Equity, Justice, Inequality, and Other Normative Criteria and Measurement
    • C31 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions; Social Interaction Models
    • C35 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions

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