One of the debates regarding the current financial crisis is whether in fact there is a crisis, or whether in fact the financial system is operating normally. I’ve been skeptical myself of the “times are normal view”, but here is some evidence that the credit crunch is real. The findings also reinforces my view that un-nuanced reliance on highly aggregated volume statistics (e.g., Chari et al. 2008) is likely to result in misleading inferences (See the rejoinder from the Boston Fed’s economists). From the conclusion to Tong and Wei (2008):
In this paper, we propose a methodological framework to study the underlying mechanisms by which a financial-sector crisis may affect the real sector, and apply it to the case of the subprime mortgage crisis. In particular, we are interested in documenting and quantifying the importance of tightening liquidity constraints and the deterioration of consumer confidence on non-financial firms. We ask the question: could an ex ante classification of the firms based on their degrees of liquidity constraint and sensitivity to demand contraction prior to the subprime crisis help to predict their ex post stock price performance during the crisis period? We find the answer to be a resounding yes. Both channels are at work; liquidity constraints appear to be more significant quantitatively in explaining cross firm differences in the magnitude of stock price declines. A conservative estimate is that a tightening liquidity constraint is likely to explain at least half of the actual drop in stock prices for firms that were liquidity constrained to start with.
In order to reach these conclusions, we propose a novel methodology that distinguishes a shock to the supply of finance from an expected contraction of economic demand. We measure a firmâ€™s sensitivity to demand contraction by its stock price reaction to the September 11, 2001 terrorist attack (change in log stock price from September 10, 2001 to September 30, 2001). We measure a firmâ€™s liquidity constraint by the Whited-Wu (2006) index, valued at the end of 2006. We conduct extensive robustness checks to ensure that these indicators are valid and informative. For example, we verify that the 9/11 index is not contaminated by the impact of a liquidity constraint itself. While liquidity constraint and demand sensitivity, as measured by these two indicators, have statistically significant power in predicting stock price movement during the subprime crisis period, placebo tests suggest that they do not predict stock price movement in a period shortly before the subprime crisis broke out. An alternative measure of a firmâ€™s dependence on external finance proposed by Rajan and Zingales (1998) and valued based on information during 1990 â€“ 2006 also has predictive power about stock price movement during the subprime crisis period.
Correctly diagnosing the transmission channels for a financial crisis to affect the real economy has implications for designing appropriate policy responses to the crisis. For the subprime mortgage crisis, our analysis suggests that policies that aim primarily at restoring consumer confidence and increasing demand, such as a tax rebate to households, will probably be insufficient to help the real economy; policies that could relax liquidity constraints faced by non-financial firms are likely to be indispensable. Our methodology should also be useful in other contexts where effects of a financial shock to the real economy need to be measured. We leave these applications for future work.
To illustrate their methodology and key findings, consider the following:
If subprime problems disproportionately harm those non-financial firms that are more liquidity constrained and/or more sensitive to a consumer demand contraction, could financial investors earn excess returns by betting against these stocks (relative to other stocks)? This is essentially another way to gauge the quantitative importance of these two factors. We now turn to a â€œportfolio approach,â€ and track the effects of the two factors over time. Specifically, we follow three steps. First, we classify each non-financial stock (other than airlines, defense and insurance firms) along two dimensions: whether its degree of liquidity constraint at the end of 2006 (per the value of the Whited-Wu index) is above or below the median in the sample, and whether its sensitivity to a consumer demand contraction is above or below the median. Second, we form four portfolios on July 31, 2007 and fix their compositions in the subsequent periods: the HH portfolio is a set of equally weighted stocks that are highly liquidity constrained and highly sensitive to consumer demand contraction; the HL portfolio is a set of stocks that are highly liquidity constrained, but relatively not sensitive to a change in consumer confidence; the LH portfolio consist of stocks that are relatively not liquidity constrained but highly sensitive to consumer confidence; and finally, the LL portfolio consists of stocks that are neither liquidity constrained nor sensitive to consumer confidence. Third, we track the cumulative returns of these four portfolios over time and plot the results in Figure 6.
Here is Figure6:
Figure 6: from Tong and Wei (2008).They conclude that about half of the decline in stock prices is due to the credit crunch, with the other half attributable to the decline in consumer confidence.
Originally published at Econbrowser and reproduced here with the author’s permission.
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