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) | 1-21 |
| Number of pages | 21 |
| Journal | Spatial Economic Analysis |
| Early online date | 7 Dec 2017 |
| DOIs | |
| Publication status | E-pub ahead of print - 7 Dec 2017 |
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)
Access to Document
- Cross Country Convergence in a General Lotka-Volterra Model
This is an Accepted Manuscript of an article published by Taylor & Francis