Many time series are sampled at different frequencies. When we study co-movements
between such series we usually analyze the joint process sampled at a common low …

We examine the relationship between Mi (xed) Da (ta) S (ampling)(MIDAS) regressions and
the Kalman filter when forecasting with mixed frequency data. In general, state space …

Economic data are collected at various frequencies but econometric estimation typically
uses the coarsest frequency. This article develops a Gibbs sampler for estimating vector …

This paper evaluates the effects of high‐frequency uncertainty shocks on a set of low‐
frequency macroeconomic variables representative of the US economy. Rather than …

Macroeconomic forecasting has recently started embracing techniques that can deal with
large-scale datasets and series with unequal release periods. Mixed-data sampling (MIDAS) …

This paper introduces regime switching parameters to the Mixed-Frequency VAR model. We
begin by discussing estimation and inference for Markov-switching Mixed-Frequency VAR …

Mxenes can be used in a variety of applications due to their multifunctional chemical
properties. It has received increasing attention as a piezoresistive sensor. However, the …

Parsimoniously specified distributed lag models have enjoyed a resurgence under the
MIDAS moniker (Mixed Data Sampling) as a feasible way to model time series observed at …

Counter to the credit channel of monetary transmission, monetary policy tightening induces
a rise in lending by two different types of non-bank financial institutions (NBFI): shadow …

Focusing on the MI (xed) DA (ta) S (ampling) regressions for handling different sampling
frequencies and asynchronous releases of information, alternative techniques for the …