This paper constructs coincident indices of Australian economic activity using techniques for estimating approximate factor models with many series, using data that begin in the early 1960s. The resulting monthly and quarterly indices both provide plausible measures of the Australian business...

This paper discusses a factor model for estimating monthly GDP using a large number of monthly and quarterly time series in real-time. To take into account the different periodicities of the data and missing observations at the end of the sample, the factors are estimated by applying an EM...

We look at how large international datasets can improve forecasts of national activity. We use the case of New Zealand, an archetypal small open economy. We apply "data-rich" factor and shrinkage methods to tackle the problem of efficiently handling hundreds of predictor data series from many...

Following Bai (2004) and Bai and Ng (2004) we estimate a common factor representation of a panel of output series for India, disaggregated by 15 states and 14 broad industry groups. We find that a single common V-Factor accounts for a large part of the significant shift in the cross-sectional...

We compare a number of data-rich prediction methods that are widely used in macroeconomic forecasting with a lesser known alternative: partial least squares (PLS) regression. In this method, linear, orthogonal combinations of a large number of predictor variables are constructed such that the...

We investigate the factor structure of the term structure of interest rates and argue that characterizing the minimal dimension of the data-generating process is more challenging than currently appreciated. To circumvent these difficulties, we introduce a novel nonparametric bootstrap that is...