3 resultados para Data mining models
em Scottish Institute for Research in Economics (SIRE) (SIRE), United Kingdom
Resumo:
This paper investigates the role of institutions in determining per capita income levels and growth. It contributes to the empirical literature by using different variables as proxies for institutions and by developing a deeper analysis of the issues arising from the use of weak and too many instruments in per capita income and growth regressions. The cross-section estimation suggests that institutions seem to matter, regardless if they are the only explanatory variable or are combined with geographical and integration variables, although most models suffer from the issue of weak instruments. The results from the growth models provides some interesting results: there is mixed evidence on the role of institutions and such evidence is more likely to be associated with law and order and investment profile; government spending is an important policy variable; collapsing the number of instruments results in fewer significant coefficients for institutions.
Resumo:
Until recently, much effort has been devoted to the estimation of panel data regression models without adequate attention being paid to the drivers of diffusion and interaction across cross section and spatial units. We discuss some new methodologies in this emerging area and demonstrate their use in measurement and inferences on cross section and spatial interactions. Specifically, we highlight the important distinction between spatial dependence driven by unobserved common factors and those based on a spatial weights matrix. We argue that, purely factor driven models of spatial dependence may be somewhat inadequate because of their connection with the exchangeability assumption. Limitations and potential enhancements of the existing methods are discussed, and several directions for new research are highlighted.
Resumo:
The disconnect between rising short and low long interest rates has been a distinctive feature of the 2000s. Both research and policy circles have argued that international forces, such as global monetary policy (e.g. Rogoff, 2006); international business cycles (e.g. Borio and Filardo, 2007); or a global savings glut (e.g Bernanke, 2005) may be responsible. In this paper, we employ recent advances in panel data econometrics to document the disconnect and link it explicitly to the existence of a global latent factor that dominates the long end of the term spread for the recent period; the saving glut story emerges as the most likely contender for the global factor.