مقایسه ذخایر فدرال، بلو چیپ و پیش بینی های سری زمانی رشد تولید آمریکا  Comparing Federal Reserve, Blue Chip, and time series forecasts of US output growth

1. Introduction Despite the inherent difficulty, both public and private forecasters are regularly engaged in predicting output growth. Market participants seek accurate forecasts of growth for making a variety of economic and financial decisions including investment. Such forecasts are also key inputs for both fiscal and monetary authorities in formulating economic policies (Chauvet and Potter, 2013). In evaluating the accuracy of output growth, inflation, and unemployment forecasts, studies have often tested the asymmetric information hypothesis that the Federal Reserve has useful information about the state of the economy that is not known by the private sector. Romer and Romer (2000), Gavin and Mandal (2001), and Sims (2002) convincingly support this hypothesis for inflation forecasts. However, as noted by Gavin and Mandal (2001), the findings are rather weak for output growth forecasts. In addition, Baghestani (2008) shows that the private forecasts of unemployment are more informative than the Federal Reserve forecasts.1 In this study, we evaluate the predictive information content of the Federal Reserve and private (Blue Chip) forecasts of output growth by employing two sets of comparable forecasts as benchmarks. The first setis from a univariate autoregressive (AR) model, and the second one is from a vector autoregressive (VAR) model. The AR forecasts contain past information in output growth, and the VAR forecasts contain past information on output growth, growth in residential investment, and consumers’ assessments of business conditions. There are two noteworthy aspects to this study. First, we utilize real time data to provide out-of-sample evidence on the usefulness of growth in residential investment for predicting output growth. This complements existing studies which have provided in-sample evidence. For instance, Green (1997) utilizes the Granger-causality approach to demonstrate that, unlike non-residential investment, residential investment Granger-causes GDP. As demonstrated by Coulson and Kim (2000), the reason behind such evidence is that, unlike non-residential investment, residential investment has a significant impact on consumption. Leamer (2007) shows that “It is residential investment that contributes most to weakness before recessions.” Toward a more effective monetary policy, Leamer argues for a new Taylor Rule in which GDP is replaced by housing leading indicators.2