<b>svars</b>: An <i>R</i> Package for Data-Driven Identification in Multivariate Time Series Analysis

Structural vector autoregressive (SVAR) models are frequently applied to trace the contemporaneous linkages among (macroeconomic) variables back an interplay of orthogonal structural shocks. Under Gaussianity parameters unidentified without additional (often external and not data-based) information. In contrast, often reasonable assumption heteroskedastic and/or non-Gaussian model disturbances offers possibility identify unique We describe R package svars which implements statistical identification techniques that can be both heteroskedasticity-based or independence-based. Moreover, it includes a rich variety analysis tools well known in SVAR literature. Next comprehensive review theoretical background, we provide detailed description associated functions. Furthermore, macroeconomic application serves as step-by-step guide on how apply these functions interpretation VAR models.