Abstract
This paper uses a general Lotka–Volterra model to estimate convergence for 93 countries over the period 1960–2007. It employs an equation with a spatial time lag and common factors. The spatial lag controls for spatial dependence, while the common factors control for strong cross-sectional dependence. As spatial weights matrices, the shares of high-skilled migrants, trade shares and foreign direct investments are used. A simultaneous least squares estimator and a dynamic common correlated effects (DCCE) estimator are employed. The DCCE estimator finds conditional convergence. The paper highlights the importance of controlling for both types of cross-sectional dependence.
| Original language | English |
|---|---|
| Pages (from-to) | 191-211 |
| Number of pages | 21 |
| Journal | Spatial Economic Analysis |
| Volume | 13 |
| Issue number | 2 |
| Early online date | 7 Dec 2017 |
| DOIs | |
| Publication status | Published - 3 Apr 2018 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 8 Decent Work and Economic Growth
Keywords
- convergence
- economic growth
- growth empirics
- Lotka–Volterra
- spatial econometrics
ASJC Scopus subject areas
- Geography, Planning and Development
- Economics, Econometrics and Finance(all)
- Statistics, Probability and Uncertainty
- Earth and Planetary Sciences (miscellaneous)
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