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Economic Determinants of Birth Rate in Romania. A Spatial Analysis

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  • Cimpoeru Smaranda

    (The Bucharest University of Economic Studies, Romania)

  • Pisică Andrei

    (The Bucharest University of Economic Studies, Romania)

Abstract

The purpose of this article is to determine the factors influencing the birth rate in Romania, by incorporating explicitly the spatial factor in the proposed models. The study is justified by the dramatic fall of the birth rate over the past three decades. With a negative natural population growth and an increasing number of emigrants, the population will become older and there will be a few million less in the next decades. To achieve the objective, various spatial modelling methods were used, such as Spatial AutoRegressive Model (SAR), Spatial Error Model (SEM), Geographically Weighted Regression (GWR) and a spatial panel data model. The data granularity is at the county level for the year 2020. Results show that GDP per capita and the amount of financial support received by families for raising a child have a significant effect on the birth rate. Using a spatial approach for modelling the birth rate, we reveal demographic problems that may exist in certain areas and identify the regions that would require a policy to stimulate birth rates.

Suggested Citation

  • Cimpoeru Smaranda & Pisică Andrei, 2023. "Economic Determinants of Birth Rate in Romania. A Spatial Analysis," Journal of Social and Economic Statistics, Sciendo, vol. 12(1), pages 25-45, July.
    • Handle: RePEc:vrs:jsesro:v:12:y:2023:i:1:p:25-45:n:5
    DOI: 10.2478/jses-2023-0002
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    References listed on IDEAS

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    1. J. Paul Elhorst, 2014. "Spatial Panel Data Models," SpringerBriefs in Regional Science, in: Spatial Econometrics, edition 127, chapter 0, pages 37-93, Springer.
    2. Laura Barbieri, 2013. "Causality and interdependence analysis in linear econometric models with an application to fertility," Journal of Applied Statistics, Taylor & Francis Journals, vol. 40(8), pages 1701-1716, August.
    3. Ion Stancu & Dragoş Haşeganu & Alexandra Darmaz-Guzun, 2019. "Proiecții privind sustenabilitatea sistemului de pensii în România," Journal of Financial Studies, Institute of Financial Studies, vol. 6(4), pages 50-67, June.
    4. LeSage, James P., 1997. "Regression Analysis of Spatial Data," Journal of Regional Analysis and Policy, Mid-Continent Regional Science Association, vol. 27(2), pages 1-12.
    5. Gregory, Paul R & Campbell, John M & Cheng, Benjamin S, 1972. "A Simultaneous Equation Model of Birth Rates in the United States," The Review of Economics and Statistics, MIT Press, vol. 54(4), pages 374-380, November.
    6. Beunen, Raoul & Meijer, Marlies & de Vries, Jasper, 2020. "Planning strategies for dealing with population decline: Experiences from the Netherlands," Land Use Policy, Elsevier, vol. 93(C).
    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    birth rate; population decline; spatial regression models; spatial panel models; geographically weighted regression;
    All these keywords.

    JEL classification:

    • J11 - Labor and Demographic Economics - - Demographic Economics - - - Demographic Trends, Macroeconomic Effects, and Forecasts
    • J19 - Labor and Demographic Economics - - Demographic Economics - - - Other
    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models

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