Search Results
Working Paper
How Much Should We Trust Regional-Exposure Designs?
Many prominent studies in macroeconomics, labor, and trade use panel data on regions to identify the local effects of aggregate shocks. These studies construct regional-exposure instruments as an observed aggregate shock times an observed regional exposure to that shock. We argue that the most economically plausible source of identification in these settings is uncorrelatedness of observed and unobserved aggregate shocks. Even when the regression estimator is consistent, we show that inference is complicated by cross-regional residual correlations induced by unobserved aggregate shocks. We ...
Working Paper
Significance Bands for Local Projections
An impulse response function describes the dynamic evolution of an outcome variable following a stimulus or treatment. A common hypothesis of interest is whether the treatment affects the outcome. We show that this hypothesis is best assessed using significance bands rather than relying on commonly displayed confidence bands. Under the null hypothesis, we show that significance bands are trivial to construct with standard statistical software using the LM principle, and should be reported as a matter of routine when displaying impulse responses graphically.
Working Paper
Identifying Structural VARs with a Proxy Variable and a Test for a Weak Proxy
This paper develops a simple estimator to identify structural shocks in vector autoregressions (VARs) by using a proxy variable that is correlated with the structural shock of interest but uncorrelated with other structural shocks. When the proxy variable is weak, modeled as local to zero, the estimator is inconsistent and converges to a distribution. This limiting distribution is characterized, and the estimator is shown to be asymptotically biased when the proxy variable is weak. The F statistic from the projection of the proxy variable onto the VAR errors can be used to test for a weak ...
Working Paper
On the Real-Time Predictive Content of Financial Conditions Indices for Growth
We provide evidence on the real-time predictive content of the National Financial Conditions Index (NFCI), for conditional quantiles of U.S. real GDP growth. Our work is distinct from the literature in two specific ways. First, we construct (unofficial) real-time vintages of the NFCI. This allows us to conduct out-of-sample analysis without introducing the kind of look-ahead biases that are naturally introduced when using a single current vintage. We then develop methods for conducting asymptotic inference on tests of equal tick loss between nested quantile regression models when the data are ...
Working Paper
Detecting Periods of Exuberance: A Look at the Role of Aggregation with an Application to House Prices
The recently developed SADF and GSADF unit root tests of Phillips et al. (2011) and Phillips et al. (2015) have become popular in the literature for detecting exuberance in asset prices. In this paper, we examine through simulation experiments the effect of cross-sectional aggregation on the power properties of these tests. The simulation design considered is based on actual housing data for both U.S. metropolitan and international housing markets and thus allows us to draw conclusions for different levels of aggregation. Our findings suggest that aggregation lowers the power of both the SADF ...
Working Paper
A Dummy Test of Identification in Models with Bunching
We propose a simple test of the main identification assumption in models where the treatment variable takes multiple values and has bunching. The test consists of adding an indicator of the bunching point to the estimation model and testing whether the coefficient of this indicator is zero. Although similar in spirit to the test in Caetano (2015), the dummy test has important practical advantages: it is more powerful at detecting endogeneity, and it also detects violations of the functional form assumption. The test does not require exclusion restrictions and can be implemented in many ...
Working Paper
Monetary Policy with Judgment
We consider two approaches to incorporate judgment into DSGE models. First, Bayesian estimation indirectly imposes judgment via priors on model parameters, which are then mapped into a judgmental interest rate decision. Standard priors are shown to be associated with highly unrealistic judgmental decisions. Second, judgmental interest rate decisions are directly provided by the decision maker and incorporated into a formal statistical decision rule using frequentist procedures. When the observed interest rates are interpreted as judgmental decisions, they are found to be consistent with DSGE ...
Working Paper
Bootstrapping out-of-sample predictability tests with real-time data
In this paper we develop a block bootstrap approach to out-of-sample inference when real-time data are used to produce forecasts. In particular, we establish its first-order asymptotic validity for West-type (1996) tests of predictive ability in the presence of regular data revisions. This allows the user to conduct asymptotically valid inference without having to estimate the asymptotic variances derived in Clark and McCracken’s (2009) extension of West (1996) when data are subject to revision. Monte Carlo experiments indicate that the bootstrap can provide satisfactory finite sample size ...
Working Paper
The Effect of the Conservation Reserve Program on Rural Economies: Deriving a Statistical Verdict from a Null Finding
This article suggests two methods for deriving a statistical verdict from a null finding,allowing economists to more confidently conclude when ?not significant" can in fact be interpreted as ?no substantive effect." The proposed methodology can be extended to a variety of empirical contexts where size and power matter. The example used to demonstrate the method is the Economic Research Service's 2004 Report to Congress that was charged with statistically identifying any unintended negative employment consequences of the Conservation Reserve Program (the Program). The report failed to ...
Report
On the Validity of Classical and Bayesian DSGE-Based Inference
This paper studies large sample classical and Bayesian inference in a prototypical linear DSGE model and demonstrates that inference on the structural parameters based on a Gaussian likelihood is unaffected by departures from Gaussianity of the structural shocks. This surprising result is due to a cancellation in the asymptotic variance resulting into a generalized information equality for the block corresponding to the structural parameters. The underlying reason for the cancellation is the certainty equivalence property of the linear rational expectation model.The main implication of this ...