We investigate the role of 12 shocks that drive the business cycles since the end of the 80s in the US and the Euro Area (EA). See the model description for more details.
Following Christiano, Motto and Rostagno (2014) the uncertainty associated to the financial sector plays a crucial role. The estimation and the quatitative analysis are provided by Dynare (Adjemian et al., 2011) and updated databases for the US and the Euro area are available online via DBnomics.
We show here the observed variables used in the estimation of the model.
We build the trajectory each variable would have followed if we feed the model with only one type of shock.
We show the historical decomposition of the observed variables used in the estimation (net of the average growth rate) over the sample period.
The bars represent the historical contribution of each of the shocks to the observed variables, that is the counterfactual values predicted by the model when all other shocks are set to zero.
For each observed variable in row, one column is the variance explained by the considered shock.
Numbers in each row may not add up to 100 as we ignore the correlation between the shocks when we add explained variances. Business cycle frequency is measured with HP filter (lambda = 1600).
We show the dynamic responses of variables in our model to a shock.
The table shows the prior and posterior distributions of estimated economic parameters and shocks.
The model introduces a financial accelerator mechanism and nominal rigidities in the context of a closed economy. The extensive presentation of the model can be found in Christiano, Motto and Rostagno (2014).
This description of the model defines preferences, technologies and market arrangements. It also allows to specify the 12 shocks that perturb the economy.
There is a continuum of households in the economy who have access to capital markets.