This paper proposes an iterative procedure to discriminate between structural breaks in the coefficients and the disturbance covariance matrix of a system of equations, with recursive procedures then identifying individual coefficient shifts and separating volatility from correlation breaks. Structural breaks in short-term cross-country inflation relations are then examined for major G-7 economies and within the euro area. There is evidence that the euro area leads inflation in North America, while changing short-term interactions apply within the euro area. Covariability generally increases from the late 1990s, while euro-area countries move from essentially idiosyncratic contemporaneous variation to comovement in the 1980s.
We propose an iterative decomposition that tests and accounts for multiple structural breaks in the mean, seasonality, dynamics and conditional volatility, while also accounting for outliers. Considering each component separately within each iteration leads to greater flexibility compared with joint procedures. Monte Carlo analysis shows the procedure performs well. Applied to monthly CPI inflation in G7 countries and the Euro area, we uncover mean and seasonality breaks for all countries and, allowing for these, changes in persistence are generally also indicated. Further, volatility reductions are widespread in the early to mid 1980s, with some countries exhibiting increases from 1999 onwards.
The U.S. Energy Information Administration estimates that approximately 52% of total U.S. crude oil was produced from shale oil resources in 2015. We examine whether the recent low crude oil price is attributable to this shale revolution in the U.S., using a SVAR model with structural breaks. Our results reveal that U.S. JEL classification: C32, E32, F43.
Using a new iterative algorithm that tests for possible breaks in the coefficients and residual variances of recursively identified structural equations, we examine changes in the parameters of the oil market model of Kilian (2009). Our analysis reveals breaks in the coefficients of the oil production and price equations, together with volatility shifts in all equations. In particular, the medium term response of production to aggregate demand shocks increases after 1980 and the price response to supply shocks is more persistent from the mid-1990s.All variables evidence changes in the relative contributions of individual shocks to their forecast error variances.JEL classification: E42, Q43.
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