  We develop a new VAR model for structural analysis with mixed-frequency data.
The MIDAS-SVAR model allows to identify structural dynamic links exploiting the
information contained in variables sampled at different frequencies. It also
provides a general framework to test homogeneous frequency-based
representations versus mixed-frequency data models. A set of Monte Carlo
experiments suggests that the test performs well both in terms of size and
power. The MIDAS-SVAR is then used to study how monetary policy and financial
market volatility impact on the dynamics of gross capital inflows to the US.
While no relation is found when using standard quarterly data, exploiting the
variability present in the series within the quarter shows that the effect of
an interest rate shock is greater the longer the time lag between the month of
the shock and the end of the quarter
