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
Rethinking Central Bank LSAPs: The Power of Market Functioning Purchases
We show that operationally similar central bank asset purchases can have markedly different effects. Combining security-level data on the Federal Reserve’s duration-adjusted asset holdings with narrative event-based identification reveals that purchases made for accommodation strongly affect yields, while purchases made for market functioning primarily enhance liquidity. We advance a partial equilibrium model of an intermediated bond market that can reconcile these findings. When trading flow is orderly, large-scale asset purchases (LSAPs) operate through the expected supply of duration ...
Working Paper
Facts and Fiction in Oil Market Modeling
A series of recent articles has called into question the validity of VAR models of the global market for crude oil. These studies seek to replace existing oil market models by structural VAR models of their own based on different data, different identifying assumptions, and a different econometric approach. Their main aim has been to revise the consensus in the literature that oil demand shocks are a more important determinant of oil price fluctuations than oil supply shocks. Substantial progress has been made in recent years in sorting out the pros and cons of the underlying econometric ...
Working Paper
A Flexible Finite-Horizon Identification of Technology Shocks
Recent empirical studies using in finite horizon long-run restrictions question the validity of the technology-driven real business cycle hypothesis. These results have met with their own controversy, stemming from their sensitivity to changes in model specification and the general poor performance of long-run restrictions in Monte Carlo experiments. We propose an alternative identification that maximizes the contribution of technology shocks to the forecast-error variance of labor productivity at a long, but finite horizon. In small samples, our identification outperforms its in finite ...
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
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. This paper examines the ability of the state-of-the-art VAR approach in Kurmann and Sims (2021) to identify responses to TFP news shocks and possibly surprise shocks in theory and practice. When applied to data generated from conventional New Keynesian DSGE models with shock processes that match key TFP moments, this estimator tends to be strongly biased, both in the presence of TFP measurement error and in its absence. This bias worsens in realistically small samples, ...
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
Macroeconomic Effects of Large-Scale Asset Purchases: New Evidence
We examine the macroeconomic effect of large-scale asset purchases (LSAPs) and forward guidance (FG) using a proxy structural VAR estimated on data through 2015, where the stance of the LSAP policy is measured using primary dealer expectations of the Federal Reserve's asset holdings. Monetary policy shocks are identified using instruments constructed from event study yield changes, and additional assumptions are employed to separately identify LSAP and FG shocks. We find that unexpected expansions in the Federal Reserve's asset holdings during the ZLB period between 2008 and 2015 had ...
Working Paper
Refining the Workhorse Oil Market Model
The Kilian and Murphy (2014) structural vector autoregressive model has become the workhorse model for the analysis of oil markets. I explore various refinements and extensions of this model, including the effects of (1) correcting an error in the measure of global real economic activity, (2) explicitly incorporating narrative sign restrictions into the estimation, (3) relaxing the upper bound on the impact price elasticity of oil supply, (4) evaluating the implied posterior distribution of the structural models, and (5) extending the sample. I demonstrate that the substantive conclusions of ...