Dynamics Modeling And The Study Of Birth Rate Determinants In Russian Regions

Shubat, Oksana; Bagirova, Anna

doi:10.7148/2019-0065

Cited by 1 publication

(1 citation statement)

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“…Spatial autocorrelation and spatial convergence regimes models are used by Salvati et al (2020) to argue the spatially-varying response of fertility rate to economic expansion. By including the spatial effects in the modelling approach, it becomes possible to develop targeted and efficient demographic policies suited to different types of regions (Shubat and Bagirova, 2019).…”

Section: Literature Reviewmentioning

confidence: 99%

Economic Determinants of Birth Rate in Romania. A Spatial Analysis

Cimpoeru,

Pisică

2023

Journal of Social and Economic Statistics

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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.

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Section: Literature Reviewmentioning

confidence: 99%