Abstract
Structural vector-autoregressive models are potentially very useful tools for guiding both macro- and microeconomic policy. In this study, we present a recently developed method for estimating such models, which uses non-normality to recover the causal structure underlying the observations. We show how the method can be applied to both microeconomic data (to study the processes of firm growth and firm performance) and macroeconomic data (to analyse the effects of monetary policy).
Original language | English |
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Pages (from-to) | 705-730 |
Number of pages | 26 |
Journal | Oxford Bulletin of Economics and Statistics |
Volume | 75 |
Issue number | 5 |
DOIs | |
Publication status | Published - 2013 Oct |
Externally published | Yes |
Keywords
- C32
- C52
- D21
- E52
- L21
ASJC Scopus subject areas
- Statistics and Probability
- Social Sciences (miscellaneous)
- Economics and Econometrics
- Statistics, Probability and Uncertainty