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                                                                                    Conference Paper
                                                                                
                                            Financial innovations and macroeconomic volatility - comments
                                        
                                        
                                        
                                        
                                                                                
                                    
                                                                                    Working Paper
                                                                                
                                            Inferences from parametric and non-parametric covariance matrix estimation procedures
                                        
                                        
                                        
                                        
                                                                                    
                                                                                                    We propose a parametric spectral estimation procedure for contructing heteroskedasticity and autocorrelation consistent (HAC) covariance matrices. We establish the consistency of this procedure under very general conditions similar to those considered in previous research. We also perform Monte Carlo simulations to evaluate the performance of this procedure in drawing reliable inferences from linear regression estimates. These simulations indicate that the parametric estimator matches, and in some cases greatly exceeds, the performance of the prewhitened kernel estimator proposed by Andrews ...
                                                                                                
                                            
                                                                                
                                    
                                                                                    Report
                                                                                
                                            Small sample properties of GMM for business cycle analysis
                                        
                                        
                                        
                                        
                                                                                    
                                                                                                    We investigate, by Monte Carlo methods, the finite sample properties of GMM procedures for conducting inference about statistics that are of interest in the business cycle literature. These statistics include the second moments of data filtered using the first difference and Hodrick-Prescott filters, and they include statistics for evaluating model fit. Our results indicate that, for the procedures considered, the existing asymptotic theory is not a good guide in a sample the size of quarterly postwar U.S. data.
                                                                                                
                                            
                                                                                
                                    
                                                                                    Journal Article
                                                                                
                                            Contract-theoretic approaches to wages and displacement