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Working Paper
Are Fiscal Transfers Inflationary?
We assess the inflationary effects of fiscal transfers by leveraging advances in the identification of fiscal policy shocks within the recently proposed rotation-invariant time-varying structural vector autoregression. Our analysis suggests that fiscal transfer shocks account for a sizable share of the early post-pandemic increase in the price level through mid-2021. Thereafter, the rise in the price level is dominated by adverse supply shocks (especially supply-chain disruptions), while demand shocks mainly matter later for the lift-off in short-term interest rates. In addition, we find that ...
Working Paper
Assessing the macroeconomic impact of bank intermediation shocks: a structural approach
We take a structural approach to assessing the empirical importance of shocks to the supply of bank-intermediated credit in affecting macroeconomic fluctuations. First, we develop a theoretical model to show how credit supply shocks can be transmitted into disruptions in the production economy. Second, we use the unique micro-banking data to identify and support the model's key mechanism. Third, we find that the output effect of credit supply shocks is not only economically and statistically significant but also consistent with the vector autogression evidence. Our mode estimation indicates ...
Working Paper
Inference Based on Time-Varying SVARs Identified with Sign Restrictions
We propose an approach for Bayesian inference in time-varying SVARs identified with sign restrictions. The linchpin of our approach is a class of rotation-invariant time-varying SVARs in which the prior and posterior densities of any sequence of structural parameters belonging to the class are invariant to orthogonal transformations of the sequence. Our methodology is new to the literature. In contrast to existing algorithms for inference based on sign restrictions, our algorithm is the first to draw from a uniform distribution over the sequences of orthogonal matrices given the reduced-form ...
Working Paper
Heterogeneity in the Pass-Through from Oil to Gasoline Prices: A New Instrument for Estimating the Price Elasticity of Gasoline Demand
We propose a new instrument for estimating the price elasticity of gasoline demand that exploits systematic differences across U.S. states in the pass-through of oil price shocks to retail gasoline prices. We show that these differences are primarily driven by the cost of producing and distributing gasoline, which varies with states’ access to oil and gasoline transportation infrastructure, refinery technology and environmental regulations, creating cross-sectional gasoline price shocks in response to an aggregate oil price shock. Time-varying estimates do not support the view that the ...
Working Paper
Identification Through Sparsity in Factor Models
Factor models are generally subject to a rotational indeterminacy, meaning that individual factors are only identified up to a rotation. In the presence of local factors, which only affect a subset of the outcomes, we show that the implied sparsity of the loading matrix can be used to solve this rotational indeterminacy. We further prove that a rotation criterion based on the 1-norm of the loading matrix can be used to achieve identification even under approximate sparsity in the loading matrix. This enables us to consistently estimate individual factors, and to interpret them as structural ...
Working Paper
Inference Based On Time-Varying SVARs Identified with Time Restrictions
We propose an approach for Bayesian inference in time-varying structural vector autoregressions (SVARs) identified with sign restrictions. The linchpin of our approach is a class of rotation-invariant time-varying SVARs in which the prior and posterior densities of any sequence of structural parameters belonging to the class are invariant to orthogonal transformations of the sequence. Our methodology is new to the literature. In contrast to existing algorithms for inference based on sign restrictions, our algorithm is the first to draw from a uniform distribution over the sequences of ...
Working Paper
Sample Selection Models Without Exclusion Restrictions: Parameter Heterogeneity and Partial Identification
This paper studies semiparametric versions of the classical sample selection model (Heckman (1976, 1979)) without exclusion restrictions. We extend the analysis in Honoré and Hu (2020) by allowing for parameter heterogeneity and derive implications of this model. We also consider models that allow for heteroskedasticity and briefly discuss other extensions. The key ideas are illustrated in a simple wage regression for females. We find that the derived implications of a semiparametric version of Heckman's classical sample selection model are consistent with the data for women with no college ...
Working Paper
How to Construct Monthly VAR Proxies Based on Daily Futures Market Surprises
It is common in applied work to estimate responses of macroeconomic aggregates to news shocks derived from surprise changes in daily futures prices around the date of policy announcements. This requires mapping the daily surprises into a monthly shock that may be used as an external instrument in a monthly VAR model or local projection. The standard approach has been to sum these daily surprises over the course of a given month when constructing the monthly proxy variable, ignoring the accounting relationship between daily and average monthly price data. In this paper, I provide a new ...
Working Paper
Inference Based on Time-Varying SVARs Identified with Sign Restrictions
We propose an approach for Bayesian inference in time-varying structural vector autoregressions (SVARs) identified with sign restrictions. The linchpin of our approach is a class of rotation-invariant time-varying SVARs in which the prior and posterior densities of any sequence of structural parameters belonging to the class are invariant to orthogonal transformations of the sequence. Our methodology is new to the literature. In contrast to existing algorithms for inference based on sign restrictions, our algorithm is the first to draw from a uniform distribution over the sequences of ...
Working Paper
When Do State-Dependent Local Projections Work?
Many empirical studies estimate impulse response functions that depend on the state of the economy. Most of these studies rely on a variant of the local projection (LP) approach to estimate the state-dependent impulse response functions. Despite its widespread application, the asymptotic validity of the LP approach to estimating state-dependent impulse responses has not been established to date. We formally derive this result for a structural state-dependent vector autoregressive process. The model only requires the structural shock of interest to be identified. A sufficient condition for the ...