Although the RNase H-dependent mechanism of inhibition of gene expression by chemically modified antisense oligonucleotides (ASOs) has been well characterized, little is known about the interactions between ASOs and intracellular proteins that may alter cellular localization and/or potency of ASOs. Here, we report the identification of 56 intracellular ASO-binding proteins using multi-step affi...

Vector Autoregressive Moving Average (VARMA) models have many theoretical properties which should make them popular among empirical macroeconomists. However, they are rarely used in practice due to over-parameterization concerns, difficulties in ensuring identification and computational challenges. With the growing interest in multivariate time series models of high dimension, these problems wi...

Suppose that a dataset with N time series is available. N1 < N of those are the variables of interest. You want to estimate a vector autoregression (VAR) with the variables of interest. Which of the remaining N−N1 variables, if any, should you include in the VAR with the variables of interest? We develop a Bayesian methodology to answer this question. This question arises in most applications o...

We prove that local projections (LPs) and Vector Autoregressions (VARs) estimate the same impulse responses. This nonparametric result only requires unrestricted lag structures. discuss several implications: (i) LP VAR estimators are not conceptually separate procedures; instead, they simply two dimension reduction techniques with common estimand but different finite?sample properties. (ii) VAR...

This paper investigates the effects of government spending in the Euro area where the fixed exchange rate regimes have been maintained. I employ the Bayesian pooling method which has been used to analyze the effect of monetary policy. By applying the Bayesian estimation procedure to the panel of VARs in the Euro area, I explore whether there exists heterogeneity in country dynamics or not, i.e....

Large aggregation interval asymptotics are used to investigate the relation between Granger causality in disaggregated vector autoregressions (VARs) and associated contemporaneous correlation among innovations of the aggregated system. Our approach allows us to better understand the informational content in non-diagonal error covariance matrices, which play an important role in structural VAR a...