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Keywords:GMM 

Working Paper
A Local-Spillover Decomposition of the Causal Effect of U.S. Defense Spending Shocks

This paper decomposes the causal effect of government defense spending into: (i) a local (or direct) effect, and (ii) a spillover (or indirect) effect. Using state-level defense spending data, we show that a negative cross-state spillover effect explains the existing simultaneous findings of a low aggregate multiplier and a high local multiplier. We show that enlisting disaggregate data improves the precision of aggregate effect estimates, relative to using aggregate time series alone. Moreover, we compare two-step efficient GMM with two alternative moment weighting approaches used in ...
Working Papers , Paper 2020-014

Working Paper
Real Rates and Consumption Smoothing in a Low Interest Rate Environment: The Case of Japan

We study the dynamics of consumption, the real interest rate, and measures of labor input in Japan over the period from 1985-2014. We identify structural breaks in macroeconomic aggregates during the 1990s and associate them with the zero interest rate policy pursued by the Bank of Japan and the surprise increase in the consumption tax rate in April 1997. Formal estimation using the Generalized Methods of Moments shows that the mid-1990s are characterized by breaks in the structural parameters governing household consumption and labor supply decisions. Specifically, following the tax hike and ...
Working Paper , Paper 17-8

Working Paper
Small Sample Properties of Bayesian Estimators of Labor Income Processes

There exists an extensive literature estimating idiosyncratic labor income processes. While a wide variety of models are estimated, GMM estimators are almost always used. We examine the validity of using likelihood based estimation in this context by comparing the small sample properties of a Bayesian estimator to those of GMM. Our baseline studies estimators of a commonly used simple earnings process. We extend our analysis to more complex environments, allowing for real world phenomena such as time varying and heterogeneous parameters, missing data, unbalanced panels, and non-normal errors. ...
Finance and Economics Discussion Series , Paper 2014-25

Working Paper
Minimum distance estimation of possibly non-invertible moving average models

This paper considers estimation of moving average (MA) models with non-Gaussian errors. Information in higher-order cumulants allows identification of the parameters without imposing invertibility. By allowing for an unbounded parameter space, the generalized method of moments estimator of the MA(1) model has classical (root-T and asymptotic normal) properties when the moving average root is inside, outside, and on the unit circle. For more general models where the dependence of the cumulants on the model parameters is analytically intractable, we consider simulation-based estimators with two ...
FRB Atlanta Working Paper , Paper 2013-11

Report
Regression-based estimation of dynamic asset pricing models

We propose regression-based estimators for beta representations of dynamic asset pricing models with an affine pricing kernel specification. We allow for state variables that are cross-sectional pricing factors, forecasting variables for the price of risk, and factors that are both. The estimators explicitly allow for time-varying prices of risk, time-varying betas, and serially dependent pricing factors. Our approach nests the Fama-MacBeth two-pass estimator as a special case. We provide asymptotic multistage standard errors necessary to conduct inference for asset pricing test. We ...
Staff Reports , Paper 493

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