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Working Paper
Growth-at-Risk is Investment-at-Risk
Amburgey, Aaron; McCracken, Michael W. (2024-08-16)
We investigate the role financial conditions play in the composition of U.S. growth-at-risk. We document that, by a wide margin, growth-at-risk is investment-at-risk. That is, if financial conditions indicate U.S. real GDP growth will be in the lower tail of its conditional distribution, we know that the main contributor is a decline in investment. Consumption contributes under extreme financial stress. Government spending and net exports do not play a role. We show that leverage plays a key role in determining both consumption- and investment-at-risk, which provides support to the financial ...
Working Papers , Paper 2023-020

Report
Robust inference in models identified via heteroskedasticity
Lewis, Daniel J. (2018-12-01)
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 ...
Staff Reports , Paper 876

Working Paper
Pooled Bewley Estimator of Long-Run Relationships in Dynamic Heterogenous Panels
Smith, Ron P.; Chudik, Alexander; Pesaran, M. Hashem (2023-11-08)
Using a transformation of the autoregressive distributed lag model due to Bewley, a novel pooled Bewley (PB) estimator of long-run coefficients for dynamic panels with heterogeneous short-run dynamics is proposed. The PB estimator is directly comparable to the widely used Pooled Mean Group (PMG) estimator, and is shown to be consistent and asymptotically normal. Monte Carlo simulations show good small sample performance of PB compared to the existing estimators in the literature, namely PMG, panel dynamic OLS (PDOLS) and panel fully-modified OLS (FMOLS). Application of two bias-correction ...
Globalization Institute Working Papers , Paper 409

Report
On the Validity of Classical and Bayesian DSGE-Based Inference
Petrova, Katerina (2024-01-01)
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 ...
Staff Reports , Paper 1084

Working Paper
Tests of Conditional Predictive Ability: Some Simulation Evidence
McCracken, Michael W. (2019-03-01)
In this note we provide simulation evidence on the size and power of tests of predictive ability described in Giacomini and White (2006). Our goals are modest but non-trivial. First, we establish that there exist data generating processes that satisfy the null hypotheses of equal finite-sample (un)conditional predictive ability. We then consider various parameterizations of these DGPs as a means of evaluating the size and power properties of the proposed tests. While some of our results reinforce those in Giacomini and White (2006), others do not. We recommend against using the fixed scheme ...
Working Papers , Paper 2019-11

Report
A Jackknife Variance Estimator for Panel Regressions
Lopez Gaffney, Ignacio; Crump, Richard K.; Gospodinov, Nikolay (2024-10-01)
We introduce a new jackknife variance estimator for panel-data regressions. Our variance estimator can be motivated as the conventional leave-one-out jackknife variance estimator on a transformed space of the regressors and residuals using orthonormal trigonometric basis functions. We prove the asymptotic validity of our variance estimator and demonstrate desirable finite-sample properties in a series of simulation experiments. We also illustrate how our method can be used for jackknife bias-correction in a variety of time-series settings.
Staff Reports , Paper 1133

Working Paper
Half-panel jackknife fixed effects estimation of panels with weakly exogenous regressor
Chudik, Alexander; Yang, Jui-Chung; Pesaran, M. Hashem (2016-08-31)
This paper considers estimation and inference in fixed effects (FE) panel regression models with lagged dependent variables and/or other weakly exogenous (or predetermined) regressors when NN (the cross section dimension) is large relative to TT (the time series dimension). The paper first derives a general formula for the bias of the FE estimator which is a generalization of the Nickell type bias derived in the literature for the pure dynamic panel data models. It shows that in the presence of weakly exogenous regressors, inference based on the FE estimator will result in size distortions ...
Globalization Institute Working Papers , Paper 281

Working Paper
Growth-at-Risk is Investment-at-Risk
Amburgey, Aaron; McCracken, Michael W. (2023-08-21)
We investigate the role financial conditions play in the composition of U.S. growth-at-risk. We document that, by a wide margin, growth-at-risk is investment-at-risk. That is, if financial conditions indicate U.S. real GDP growth will be in the lower tail of its conditional distribution, we know that the main contributor is a decline in investment. Consumption contributes under extreme financial stress. Government spending and net exports do not play a role.
Working Papers , Paper 2023-020

Report
The relationship between expected inflation, disagreement, and uncertainty: evidence from matched point and density forecasts
Rich, Robert W.; Tracy, Joseph (2006-07-01)
This paper examines matched point and density forecasts of inflation from the Survey of Professional Forecasters to analyze the relationship between expected inflation, disagreement, and uncertainty. We extend previous studies through our data construction and estimation methodology. Specifically, we derive measures of disagreement and uncertainty by using a decomposition proposed in earlier research by Wallis and by applying the concept of entropy from information theory. We also undertake the empirical analysis within a seemingly unrelated regression framework. Our results offer mixed ...
Staff Reports , Paper 253

Working Paper
On the Real-Time Predictive Content of Financial Conditions Indices for Growth
McCracken, Michael W.; Amburgey, Aaron (2022-06-03)
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 Papers , Paper 2022-003

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