This study proposes a method to identify factor-augmented vector autoregression models without imposing uncorrelatedness or any timing restrictions among observed and unobserved factors in the system. To this end, we utilize changes unconditional shock variances following Rigobon (2003). The proposed can incorporate both structural system allows contemporaneous matrix be fully unrestricted. We ...

System of panel models are popular models in applied sciences and the question of spatial errors has created the recent demand for spatial system estimation of panel models. Therefore we propose new diagnostic methods to explore if the spatial component will change significantly the outcome of non-spatial estimates of seemingly unrelated regression (SUR) systems. We apply a local sensitivity ap...

This paper analyzes the relationship between financial development and economic growth in Latin America with a Granger causality test and impulse response functions in a panel vector autoregression model. Using annual observations from a sample of 18 countries from 1962 to 2005, it is shown that while economic growth causes financial development, financial development does not cause economic gr...

We provide an accessible introduction to graph-theoretic methods for causal analysis. Building on the work of Swanson and Granger (Journal of the American Statistical Association, Vol. 92, pp. 357–367, 1997), and generalizing to a larger class of models, we show how to apply graph-theoretic methods to selecting the causal order for a structural vector autoregression (SVAR). We evaluate the PC (...

This paper proposes a fully nonparametric test for cointegrating rank which does not require estimation of a vector autoregressive model. The test exploits the fact that the degeneracy in the moment matrix of the variables with mixed integration order corresponds to the notion of cointegration. With an appropriate standardization, the test statistics are shown to have a nuisance parameter free ...

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