This paper evaluates the hypothesis that during the 2008–2009 collapse in international trade, imports of higher quality goods experienced larger reductions compared to low-quality imports, using data on US imports disaggregated by HS-10 product category and source country. We find little, if any, robust econometric evidence in support of this hypothesis.

There appears to be a consensus that the recent instability in global financial markets may be attributable in part to the failure of financial modeling. More specifically, it is alleged that current risk models have failed to properly assess the risks associated with large adverse stock price behavior. In this paper, we first discuss the limitations of classical time series models for forecasting financial market meltdowns. Then we set forth a framework capable of forecasting both extreme events and highly volatile markets. Based on the empirical evidence presented in this paper, our framework offers an improvement over prevailing models for evaluating stock market risk exposure during distressed market periods.

Using factor methods, we decompose industrial production (IP) into components arising from aggregate and sector-specific shocks. An approximate factor model finds that nearly all of IP variability is associated with common factors. We then use a multisector growth model to adjust for the effects of input-output linkages in the factor analysis. Thus, a structural factor analysis indicates that the Great Moderation was characterized by a fall in the importance of aggregate shocks while the volatility of sectoral shocks was essentially unchanged. Consequently, the role of idiosyncratic shocks increased considerably after the mid-1980s, explaining half of the quarterly variation in IP.