Search Results
Working Paper
News and Uncertainty Shocks
We provide novel evidence that technological news and uncertainty shocks, identified one at a time using VAR models as in the literature, are correlated; that is, they are not truly structural. We then proceed by proposing an identification scheme to disentangle the effects of news and financial uncertainty shocks. We find that by removing uncertainty effects from news shocks, the positive responses of economic activity to news shocks are strengthened in the short term; and that the negative responses of activity to financial uncertainty shocks are deepened in the medium term as ?good ...
Working Paper
IDENTIFICATION THROUGH HETEROGENEITY
We analyze set identification in Bayesian vector autoregressions (VARs). Because set identification can be challenging, we propose to include micro data on heterogeneous entities to sharpen inference. First, we provide conditions when imposing a simple ranking of impulse-responses sharpens inference in bivariate and trivariate VARs. Importantly; we show that this set reduction also applies to variables not subject to ranking restrictions. Second, we develop two types of inference to address recent criticism: (1) an efficient fully Bayesian algorithm based on an agnostic prior that directly ...
Working Paper
The Financial Market Effects of Unwinding the Federal Reserve’s Balance Sheet
For the second time in the brief 12-year period between 2008 and 2020, central banks have once again turned to asset purchase programs to combat a global economic downturn. While balance sheet expansions have become familiar, balance sheet normalization has proven more elusive. Nevertheless, an understanding of the consequences of unwinding asset purchases is necessary for well-informed decisions over the deployment of these unconventional policy tools. This paper provides a first analysis of the financial market effects of balance sheet normalization based on the U.S. experience between 2017 ...
Working Paper
Estimating Macroeconomic News and Surprise Shocks
The importance of understanding the economic effects of TFP news and surprise shocks is widely recognized in the literature. A common VAR approach is to identify responses to TFP news shocks by maximizing the variance share of TFP over a long horizon. Under suitable conditions, this approach also implies an estimate of the surprise shock. We find that these TFP max share estimators tend to be strongly biased when applied to data generated from DSGE models with shock processes that match the TFP moments in the data, both in the presence of TFP measurement error and in its absence. ...
Working Paper
Comment on Giacomini, Kitagawa and Read's 'Narrative Restrictions and Proxies'
In a series of recent studies, Raffaella Giacomini and Toru Kitagawa have developed an innovative new methodological approach to estimating sign-identified structural VAR models that seeks to build a bridge between Bayesian and frequentist approaches in the literature. Their latest paper with Matthew Read contains thought-provoking new insights about modeling narrative restrictions in sign-identified structural VAR models. My discussion puts their contribution into the context of Giacomini and Kitagawa’s broader research agenda and relates it to the larger literature on estimating ...
Working Paper
What Drives Inventory Accumulation? News on Rates of Return and Marginal Costs
We study the effects of news shocks on inventory accumulation in a structural VAR framework. We establish that inventories react strongly and positively to news about future increases in total factor productivity. Theory suggests that the transmission channel of news shocks to inventories works through movements in marginal costs, through movements in sales, or through interest rates. We provide evidence that changes in external and internal rates of return are central to the transmission for such news shocks. We do not find evidence of a strong substitution effect that shifts production from ...
Working Paper
Nonparametric Time Varying IV-SVARs: Estimation and Inference
This paper studies the estimation and inference of time-varying impulse response functions in structural vector autoregressions (SVARs) identified with external instruments. Building on kernel estimators that allow for nonparametric time variation, we derive the asymptotic distributions of the relevant quantities. Our estimators are simple and computationally trivial and allow for potentially weak instruments. Simulations suggest satisfactory empirical coverage even in relatively small samples as long as the underlying parameter instabilities are sufficiently smooth. We illustrate the methods ...
Working Paper
Jointly Estimating Macroeconomic News and Surprise Shocks
This paper clarifies the conditions under which the state-of-the-art approach to identifying TFP news shocks in Kurmann and Sims (2021, KS) identifies not only news shocks but also surprise shocks. We examine the ability of the KS procedure to recover responses to these shocks from data generated by a conventional New Keynesian DSGE model. Our analysis shows that the KS response estimator tends to be strongly biased even in the absence of measurement error. This bias worsens in realistically small samples, and the estimator becomes highly variable. Incorporating a direct measure of TFP news ...
Working Paper
The Hard Road to a Soft Landing: Evidence from a (Modestly) Nonlinear Structural Model
What drove inflation so high in 2022? Can it drop rapidly without a recession? The Phillips curve is central to the answers; its proper (nonlinear) specification reveals that the relationship is strong and frequency dependent, and inflation is very persistent. We embed this empirically successful Phillips curve – incorporating a supply-shocks variable – into a structural model. Identification is achieved using an underutilized data-dependent method. Despite imposing anchored inflation expectations and a rapid relaxation of supply-chain problems, we find that absent a recession, inflation ...