We calculate global inflation as the first principal component of inflation in a sample of emerging market and advanced economies and find that it may account for an important fraction of headline and core inflation variance across countries. We then show that global inflation is correlated with...

This paper discusses whether differences in the data structure of observational and experimental studies should lead to different strategies for variable selection. On the one hand, it is argued that outliers in the predictor variables have to be treated differently in the two kinds of studies....

The ratio of Indian to US per capita output over the past 45 years has displayed a distinctive V-shaped pattern. We show that a strikingly similar V-shaped pattern is visible not just in aggregate output .figures, but also as the primary determinant of long-term movements in the cross-sectional...

Principal components are a well established tool in dimension reduction. The extension to principal curves allows for general smooth curves which pass through the middle of a p-dimensional data cloud. In this paper local principal curves are introduced, which are based on the localization of...

In this study we forecast the term structure of FIBOR/EURIBOR swap rates by means of recursive vector autoregressive (VAR) models. In advance, a principal components analysis (PCA) is adopted to reduce the dimensionality of the term structure. To evaluate ex-ante forecasting performance for...

The paper proposes a data driven adaptive model selection strategy. The selection crite- rion measures economic exante forecasting content by means of trading implied cash flows. Empirical evidence suggests that the proposed strategy is neither exposed to selection bias nor to the risk of...

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...

In this paper we adopt a principal components analysis (PCA) to reduce the dimensionality of the term structure and employ autoregressive models (AR) to forecast principal components which, in turn, are used to forecast swap rates. Arguing in favor of structural variation, we propose data...