The aim of this study is to investigate whether migration affects Austrian economic growth. Migration is seperated into total and foreign migration. The framework of this analysis is the Neoclassical Solow-Swan model. Analogous to the main results of this model, the two types of – convergence and an augmented version of the model regarding the two migration variables will be tested.
The empirical work is based on a data set especially created for Austria, which covers the time period from 1961 to 2002. This data set provides a clear tendency towards absolute convergence. The test of conditional convergence verifies that the Austrian federal states started at different technological status and converge at a speed of 3, 54% per year. Furthermore, this test points out that the Solow-Swan models findings are not asserted, but some of the variables help to improve the results of the test.
The augmented model, which includes the migration variables, leads to the conclusion, that total migration in Austria has a positive and highly significant influence on the growth of GDP per capita, while foreign migration also suggests the positive relationship but only at a 10% level of significance.
Contents
Abstract
1. Introduction
2. The Solow-Swan model of economic growth
2.1. β-Convergence in the Solow-Swan model
2.1.1. The theory of absolute and conditional β-convergence
2.1.2. The speed of convergence
3. Data
3.1. Gross Domestic Product
3.2. Savings Rate
3.3. Labor Force
3.4. Migration
4. Results
4.1. Absolute β-convergence
4.2. Conditional convergence
4.3. Migration and convergence
5. Conclusions
A. Appendix
A.1. Characteristics of panel data
A.2. Panel data models
A.2.1. The model with fixed effects
A.2.2. The model with random effects
A.3. Instrumental variables and Two-Stage Least Squares(TSLS)
A.4. Nonlinear regression models
List of Figures
List of Tables
Bibliography
- Citation du texte
- Clemens Buchinger (Auteur), 2006, Growth, Convergence and Migration in Austria, Munich, GRIN Verlag, https://www.grin.com/document/288616
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