After computing the sample autocovariance matrices, PROC STATESPACE fits a sequence of vector autoregressive models. These preliminary autoregressive models are used to estimate the autoregressive ...
We estimate the low-frequency relationship between fiscal deficits and inflation and pay special attention to its potential time variation by estimating a time-varying vector autoregression model for ...
This paper investigates spillovers between electricity supply shocks and US growth, using monthly data from forty-eight US states from January 2001 to September 2016, and employs a novel strategy for ...
This is a preview. Log in through your library . Abstract An expression for the likelihood function of a stationary vector autoregressive-moving average process is developed. The expression is very ...
A mixture vector autoregressive framework to capture extreme events in macro-prudential stress tests
Severe financial turbulence is driven by high impact and low probability events that are the hallmarks of systemic financial stress. These unlikely adverse events arise from the extreme tail of a ...
A model with first-order autoregressive errors, AR(1), has the form while an AR(2) error process has the form and so forth for higher-order processes. Note that the ...
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