Search Results
Working Paper
Dynamic Identification Using System Projections and Instrumental Variables
We propose System Projections on Instrumental Variables (SP-IV) to estimate dynamic structural relationships using impulse responses obtained from local projections or vector autoregressions. SP-IV replaces lag sequences of instruments in traditional IV with lead sequences of endogenous variables. By allowing the inclusion of lagged variables as controls, SP-IV weakens exogeneity requirements and can improve efficiency and effective instrument strength relative to 2SLS. We provide inference procedures under strong and weak identification, and show that SP-IV outperforms conventional IV ...
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
Dynamic Identification Using System Projections on Instrumental Variables
We propose System Projections on Instrumental Variables (SP-IV) to estimate structural relationships using regressions of structural impulse responses obtained from local projections or vector autoregressions. Relative to IV with distributed lags of shocks as instruments, SP-IV imposes weaker exogeneity requirements and can improve efficiency and increase effective instrument strength relative to the typical 2SLS estimator. We describe inference under strong and weak identification. The SP-IV estimator outperforms other estimators of Phillips Curve parameters in simulations. We estimate the ...
Report
Robust inference in models identified via heteroskedasticity
Identification via heteroskedasticity exploits differences in variances across regimes to identify parameters in simultaneous equations. I study weak identification in such models, which arises when variances change very little or the variances of multiple shocks change close to proportionally. I show that this causes standard inference to become unreliable, outline two tests to detect weak identification, and establish conditions for the validity of nonconservative methods for robust inference on an empirically relevant subset of the parameter vector. I apply these tools to monetary policy ...
Working Paper
Reconsidering the Fed's Inflation Forecasting Advantage
Previous studies show the Fed has a forecast advantage over the private sector for inflation, either because it devotes more resources to forecasting or because it has an informational advantage. We evaluate the Fed's forecast advantage to determine how much of it results from the Fed's knowledge of future monetary policy. We develop two tests -- an instrumental variable encompassing test and a path-dependent encompassing test -- to equalize the Fed's information set with the private sector's. We find that Fed forecasts do not encompass those of the private sector when the latter has ...
Working Paper
Lags, Leave-Outs and Fixed Effects
To avoid endogeneity, financial economists often construct regressors and/or instruments using values from other observations, with lagged and leave-out variables being common examples. We examine the use of such variables in common settings with fixed effects and show that it can induce bias and distort inference. We illustrate the severity of this problem via simulations and with patent examiner data. Even when scrambling the patent examiners, thus removing any instrument validity, the bias leads to a first-stage F-statistic over 1,000. General and case-specific solutions are provided.
Working Paper
Local Projections, Autocorrelation, and Efficiency
It is well known that Local Projections (LP) residuals are autocorrelated. Conventional wisdom says that LP have to be estimated by OLS with Newey-West (or some type of Heteroskedastic and Autocorrelation Consistent (HAC)) standard errors and that GLS is not possible because the autocorrelation process is unknown and/or because the GLS estimator would be inconsistent. I derive the autocorrelation process of LP and show that it can be corrected for using a consistent GLS estimator. Estimating LP with GLS has three major implications: 1) LP GLS can be less biased, more efficient, and generally ...
Working Paper
Reconsidering the Fed’s Forecasting Advantage
Previous studies show the Fed has a forecast advantage over the private sector, either because it devotes more resources to forecasting or because it has an informational advantage in knowing the path of future monetary policy. We evaluate the Fed’s forecast advantage to determine how much of it results from the Fed’s knowledge of the conditioning path. We develop two tests—an instrumental variable encompassing test and a path-dependent encompassing test—to equalize the Fed’s information set with the private sector’s. We find that, generally, the Fed does not encompass the private ...
Working Paper
Interest Rate Surprises: A Tale of Two Shocks
Interest rate surprises around FOMC announcements reveal both the surprise in the monetary policy stance (the pure policy shock) and interest rate movements driven by exogenous information about the economy from the central bank (the information shock). In order to disentangle the effects of these two shocks, we use interest rate changes on days of macroeconomic data releases. On these release dates, there are no pure policy shocks, which allows us to identify the impact of information shocks and thereby distill pure policy shocks from interest rate surprises around FOMC announcements. Our ...
Working Paper
A Robust Test for Weak Instruments with Multiple Endogenous Regressors
We extend the popular bias-based test of Stock and Yogo (2005) for instrument strength in linear instrumental variables regressions with multiple endogenous regressors to be robust to heteroskedasticity and autocorrelation. Equivalently, we extend the robust test of Montiel Olea and Pflueger (2013) for one endogenous regressor to the general case with multiple endogenous regressors. We describe a simple procedure for applied researchers to conduct our generalized first-stage test of instrument strength and provide efficient and easy-to-use Matlab code for its implementation. We demonstrate ...