Stock Market Firm-Level Information and Real Economic Activity
Filippo di Mauro, Fabio Fornari, Dario Mannucci
ECB Working Paper,
Nr. 1366,
2011
Abstract
We provide evidence that changes in the equity price and volatility of individual firms (measures that approximate the definition of 'granular shock' given in Gabaix, 2010) are key to improve the predictability of aggregate business cycle fluctuations in a number of countries. Specifically, adding the return and the volatility of firm-level equity prices to aggregate financial information leads to a significant improvement in forecasting business cycle developments in four economic areas, at various horizons. Importantly, not only domestic firms but also foreign firms improve business cycle predictability for a given economic area. This is not immediately visible when one takes an unconditional standpoint (i.e. an average across the sample). However, conditioning on the business cycle position of the domestic economy, the relative importance of the two sets of firms - foreign and domestic - exhibits noticeable swings across time. Analogously, the sectoral classification of the firms that in a given month retain the highest predictive power for future IP changes also varies significantly over time as a function of the business cycle position of the domestic economy. Limited to the United States, predictive ability is found to be related to selected balance sheet items, suggesting that structural features differentiate the firms that can anticipate aggregate fluctuations from those that do not help to this aim. Beyond the purely forecasting application, this finding may enhance our understanding of the underlying origins of aggregate fluctuations. We also propose to use the cross sectional stock market information to macro-prudential aims through an economic Value at Risk.
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Business Volatility, Job Destruction, and Unemployment
Steven J. Davis, R. Jason Faberman, John Haltiwanger, Ron S. Jarmin, Javier Miranda
American Economic Journal: Macroeconomics,
Nr. 2,
2010
Abstract
Unemployment inflows fell from 4 percent of employment per month in the early 1980s to 2 percent by the mid 1990s. Using low frequency movements in industry-level data, we estimate that a 1 percentage point drop in the quarterly job destruction rate lowers the monthly unemployment inflow rate by 0.28 points. By our estimates, declines in job destruction intensity account for 28 (55) percent of the fall in unemployment inflows from 1982 (1990) to 2005. Slower job destruction accounts for similar fractions of long-term declines in the rate of unemployment.
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