A speech at the Middle Tennessee State University, Annual Economic Outlook Conference, Murfreesboro, Tenn., Sept. 29, 2006

A speech at the Middle Tennessee State University, Annual Economic Outlook Conference, Murfreesboro, Tenn., Sept. 29, 2006

2008 Annual Economic Outlook Conference, Middle Tennessee State University, Murfreesboro, Tenn., Sept. 26, 2008

This paper presents analytical, Monte Carlo, and empirical evidence linking in-sample tests of predictive content and out-of-sample forecast accuracy. Our approach focuses on the negative effect that finite-sample estimation error has on forecast accuracy despite the presence of significant...

This paper develops bootstrap methods for testing whether, in a finite sample, competing out-of-sample forecasts from nested models are equally accurate. Most prior work on forecast tests for nested models has focused on a null hypothesis of equal accuracy in population - basically, whether...

This paper presents empirical evidence on the disagreement among Federal Open Market Committee (FOMC) forecasts. In contrast to earlier studies that analyze the range of FOMC forecasts available in the Monetary Policy Report to the Congress, we analyze the forecasts made by each individual...

This paper develops a novel and effective bootstrap method for simulating asymptotic critical values for tests of equal forecast accuracy and encompassing among many nested models. The bootstrap, which combines elements of fixed regressor and wild bootstrap methods, is simple to use. We first...

This chapter provides an overview of pseudo-out-of-sample tests of unconditional predictive ability. We begin by providing an overview of the literature, including both empirical applications and theoretical contributions. We then delineate two distinct methodologies for conducting inference:...

This paper presents empirical evidence on the efficacy of forecast averaging using the ALFRED real-time database. We consider averages taken over a variety of different bivariate VAR models that are distinguished from one another based upon at least one of the following: which variables are used...

Motivated by the common finding that linear autoregressive models often forecast better than models that incorporate additional information, this paper presents analytical, Monte Carlo, and empirical evidence on the effectiveness of combining forecasts from nested models. In our analytics, the...