Jess Benhabib, Xuewen Liu, Pengfei Wang,
Based on: Journal of Finance, 2019, 74 (3), 1503-1557 DOI: https//doi.org/10.1111/jofi.12764
Uncertainty in both financial markets and the real economy rises sharply during recessions. The Federal Open Market Committee minutes repeatedly emphasize uncertainty as a key factor in the 2001 and 2007–2009 recessions. The financial crisis of 2007-2009 presented one of the most striking episodes of such heightened uncertainty. Financial market uncertainty, measured by the VIX index, jumped by an astonishing 313% in the Great Recession. The increase in measured real economic uncertainty was equally astounding. For instance, macroeconomic uncertainty measured by the forecast error of industrial production growth almost doubled, and micro-level real uncertainty as measured by the firm-level dispersion of output increased by 152%.
Why does uncertainty rise sharply in recessions? And why do financial uncertainty and real uncertainty move together?
One important reason behind high uncertainty is lack of information --- a reduction in the production of information by economic agents. In particular, information production and acquisition in the economy is interdependent across economic agents and procyclical, as incentives to acquire and produce information are higher in booms. Higher levels of information production and acquisition by firms and traders improve market efficiency and provide incentives to other market participants to seek and produce information, improving overall resource allocation in the economy. What can emerge is a coordination problem in information production, especially between the production of financial information in markets and the conditions of production at the level of firms and industries. So, there is a possibility of stagnant equilibria where markets operate at less than full efficiency as information production remains low in busts. A two-way causality exists between low levels of production, which discourage expenditures for information production and acquisition, and the paucity of information about production conditions.
What is central to our analysis is the compound feedback loops of information amplification and acceleration in the macroeconomic context, as illustrated by the following figure.
First, there exists mutual learning between financial markets and the real economy. As an example, oil companies typically have more information about the supply side of the oil market, while financial future market investors, in aggregate, have more information about the demand side. Hence oil-producing companies scrutinize oil futures prices when making their production decisions, because future prices contain information about the demand side while such information is important for them to make the production decisions. On the other hand, financial market participants obviously want to have more information about the supply side in order to profit in trading, so they study the financial reports of the oil-producing companies to obtain information when trading on oil futures.
Second, the mutual learning creates a strategic complementarity between information production in the financial sector and that in the real sector. Their joint information production decisions reinforce each other and determine both allocative efficiency in the real sector and market efficiency in the financial sector. If one side anticipates that the other side will produce more information, it also has an incentive to do so. Intuitively, when information about the oil supply becomes more precise, acquiring information about the oil demand becomes more valuable for traders in trading oil futures to profit. Conversely, when uncertainty about oil demand is lower, it becomes more valuable for oil-producing firms to reduce uncertainty associated with oil production conditions. Self-fulfilling changes in financial uncertainty and real uncertainty naturally arise when both sides produce little information in anticipation that the other side will produce little information.
Third, information production on the firm side as well as the financial sector is affected by --- and in turn affects --- the aggregate economy. Specifically, the benefit to a firm of acquiring information depends on aggregate demand/output (GDP) in addition to the level of information it obtains from the financial market. That is, the incentives of firm managers to acquire information depend, in part, on their expectation about the performance of the aggregate economy. Conversely, the performance of the aggregate economy depends on the allocative efficiency in the real sector or equivalently the investment efficiency of individual firms, which in turn depends on the level of information about production conditions for firms. Therefore, overall, an increase in uncertainty (a decrease in the level of information across the economy) is accompanied by a reduction in investment efficiency and a decline in aggregate output.
Among others, three key implications arise from the theory. First, if information becomes harder to collect in either the real or the financial sector, this has a large impact on the aggregate economy due to the compound feedback loops. Indeed, both aggregate investment and aggregate total-factor-productivity (TFP) are decreasing when information precision becomes lower. Hence, a small shock in information acquisition cost has a large impact on aggregate investment, endogenous aggregate TFP, and aggregate output in the same direction, particularly when it triggers a self-fulfilling "bad" equilibrium. This also implies an information contagion channel whereby a shock that directly affects only a small portion of the economy (e.g., some sectors) propagates a global recession on all parts of the economy through the information mechanism. Second, financial uncertainty, real uncertainty, and aggregate economic activity move together, and uncertainty is countercyclical, as observed in the data. Third, the theory sheds light on several puzzling empirical facts about asset price co-movement. For instance, empirical evidence shows that correlations between U.S. stocks and the aggregate U.S. market are much higher for downside moves than for upside moves, and industries with larger firm-specific variation in stock returns have higher economic efficiency of corporate investment. When firms have access to more information about the idiosyncratic shocks to their individual demands or to their production conditions that they face, they will align their production decisions to these shocks to maximize profits, and in doing so their investment efficiency improves. Since these shocks are firm-specific as opposed to shocks that affect the whole economy, the profitability of firms as well asset prices will exhibit lower co-movements across firms when firms have access to more information, and at the same time the investment efficiency of firms will be higher. Therefore, at the macroeconomic level, a lower degree of co-movement of asset prices, as well as a higher efficiency of resource allocation, is accompanied by a higher GDP.
As John Maynard Keynes argued, the macroeconomy is a coordination game and economic agents’ expectations matter a lot. Because information is a productive factor like capital and labor and the incentives of the private sector to invest in that factor partially depend on expectations about the aggregate economy, the externality in information production among economic agents should be an important consideration for policy makers. An important policy implication of the theory is that government’s timely intervention such as bailouts and fiscal expansions not only serves the purpose of increasing the aggregate demand, but can also coordinate and stimulate the private sector’s investment in information. This helps prevent the economy from falling into “uncertainty traps” --- the vicious cycle of higher uncertainty and poorer performance of the aggregate economy. Disclosure requirements for corporations and governmental dissemination of information would also be useful policies.
Paulette Goddard Professor of Political Economy
Department of Economics. New York University
Professor of Finance
Department of Finance, HKU Business School. The University of Hong Kong (HKU)
Chair Professor of Economics and Associate Dean
HSBC Business School. Peking University