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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
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
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 ...
Report
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 ...
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
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
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 for 2SLS with Multiple Endogenous Regressors
We develop a test for instrument strength based on the bias of two-stage least squares (2SLS) that (1) generalizes the tests of Stock and Yogo (2005) and Sanderson and Windmeijer (2016) to be robust to heteroskedasticity and autocorrelation, and (2) extends the Montiel Olea and Pflueger (2013) robust test for models with a single endogenous regressor to multiple endogenous regressors. Our test can be based either on Stock and Yogo’s (2005) absolute bias criterion or on the 2SLS bias relative to Montiel Olea and Pflueger’s (2013) worst-case benchmark. We also develop extensions to test ...
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
Weak Instrument Bias in Impulse Response Estimators
We approximate the finite-sample distribution of impulse response function (IRF) estimators that are just-identified with a weak instrument using the conventional local-to-zero asymptotic framework. Since the distribution lacks a mean, we assess bias using the mode and conclude that researchers prioritizing robustness against weak instrument bias should favor vector autoregressions (VARs) over local projections (LPs). Existing testing procedures are ill-suited for assessing weak instrument bias in IRF estimates, and we propose a novel simple test based on the usual first-stage F-statistic. We ...