Uncertainty, Financial Frictions, and Investment Dynamics
10 Apr 2014-Social Science Research Network (Board of Governors of the Federal Reserve System)-Vol. 2014, Iss: 69, pp 1-58
TL;DR: In this paper, the authors analyzed the economic significance of the traditional "wait-and-see" effect of uncertainty shocks and pointed to financial distortions as the main mechanism through which fluctuations in uncertainty affect macroeconomic outcomes.
Abstract: Micro- and macro-level evidence indicates that fluctuations in idiosyncratic uncertainty have a large effect on investment; the impact of uncertainty on investment occurs primarily through changes in credit spreads; and innovations in credit spreads have a strong effect on investment, irrespective of the level of uncertainty. These findings raise a question regarding the economic significance of the traditional "wait-and-see" effect of uncertainty shocks and point to financial distortions as the main mechanism through which fluctuations in uncertainty affect macroeconomic outcomes. The relative importance of these two mechanisms is analyzed within a quantitative general equilibrium model, featuring heterogeneous firms that face time-varying idiosyncratic uncertainty, irreversibility, nonconvex capital adjustment costs, and financial frictions. The model successfully replicates the stylized facts concerning the macroeconomic implications of uncertainty and financial shocks. By influencing the effective supply of credit, both types of shocks exert a powerful effect on investment and generate countercyclical credit spreads and procyclical leverage, dynamics consistent with the data and counter to those implied by the technology-driven real business cycle models.
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TL;DR: In this paper, a strong negative relationship between firm-level capital investment and the aggregate level of uncertainty associated with future policy and regulatory outcomes is found, and the relation between policy uncertainty and capital investment is not uniform in the cross section, being significantly stronger for firms with a higher degree of investment irreversibility and for firms more dependent on government spending.
Abstract: Using the policy uncertainty index of Baker, Bloom, and Davis (2013), we document a strong negative relationship between firm-level capital investment and the aggregate level of uncertainty associated with future policy and regulatory outcomes. More importantly, we find evidence that the relation between policy uncertainty and capital investment is not uniform in the cross section, being significantly stronger for firms with a higher degree of investment irreversibility and for firms which are more dependent on government spending. Our results lend empirical support to the notion that policy uncertainty can depress corporate investment by inducing precautionary delays due to investment irreversibility.
1,164 citations
Cites background or result from "Uncertainty, Financial Frictions, a..."
...Uncertainty has been argued to increase the risk of default (e.g. Greenwald and Stiglitz (1990), Gilchrist, Sim, and Zakrajsek (2011)) and the equity risk premium (Pastor and Veronesi (2011)), which would result in higher costs of external financing....
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...Gilchrist, Sim, and Zakrajsek (2011) also investigate the possibility that financial frictions are an important mechanism through which overall uncertainty affects capital investment and find evidence consistent with the results in this study....
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...Second, uncertainty can increase the costs of external financing by increasing the risk of default (e.g. Gilchrist, Sim, and Zakrajsek (2011)) or the equity risk premium (Pastor and Veronesi (2011)) which can result in lower investment rates....
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TL;DR: This article found that both macro and micro uncertainty appears to rise sharply in recessions and the types of exogenous shocks like wars, financial panics and oil price jumps that cause recessions appear to directly increase uncertainty, and uncertainty also appears to endogenously rise further during recessions.
Abstract: This review article tries to answer four questions: (i) what are the stylized facts about uncertainty over time; (ii) why does uncertainty vary; (iii) do fluctuations in uncertainty matter; and (iv) did higher uncertainty worsen the Great Recession of 2007-2009? On the first question both macro and micro uncertainty appears to rise sharply in recessions. On the second question the types of exogenous shocks like wars, financial panics and oil price jumps that cause recessions appear to directly increase uncertainty, and uncertainty also appears to endogenously rise further during recessions. On the third question, the evidence suggests uncertainty is damaging for short-run investment and hiring, but there is some evidence it may stimulate longer-run innovation. Finally, in terms of the Great Recession, the large jump in uncertainty in 2008 potentially accounted for about one third of the drop in GDP.
927 citations
TL;DR: The authors found that both macro and micro uncertainty appears to rise sharply in recessions and the types of exogenous shocks like wars, financial panics and oil price jumps that cause recessions appear to directly increase uncertainty, and uncertainty also appears to endogenously rise further during recessions.
Abstract: This review article tries to answer four questions: (i) what are the stylized facts about uncertainty over time; (ii) why does uncertainty vary; (iii) do fluctuations in uncertainty matter; and (iv) did higher uncertainty worsen the Great Recession of 2007-2009? On the first question both macro and micro uncertainty appears to rise sharply in recessions. On the second question the types of exogenous shocks like wars, financial panics and oil price jumps that cause recessions appear to directly increase uncertainty, and uncertainty also appears to endogenously rise further during recessions. On the third question, the evidence suggests uncertainty is damaging for short-run investment and hiring, but there is some evidence it may stimulate longer-run innovation. Finally, in terms of the Great Recession, the large jump in uncertainty in 2008 potentially accounted for about one third of the drop in GDP.
781 citations
TL;DR: In this paper, a new empirical measure of uncertainty based on the Michigan survey and a VAR model is proposed, which is consistent with US data, and combining search frictions and nominal rigidities can match the qualitative VAR pattern and account for about 70 percent of the empirical increase in unemployment following an uncertainty shock.
630 citations
Cites background from "Uncertainty, Financial Frictions, a..."
...Overall, both theory and evidence suggest that uncertainty shocks are aggregate demand shocks....
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...Uncertainty shocks can have important interactions with financial factors (Gilchrist, Sim, and Zakrajsek, 2010; Arellano, Bai, and Kehoe, 2011)....
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TL;DR: The authors showed that deterioration in household balance sheets, what they refer to as the housing net worth channel, played a significant role in the sharp decline in U.S. employment between 2007 and 2009.
Abstract: We show that deterioration in household balance sheets, what we refer to as the housing net worth channel, played a significant role in the sharp decline in U.S. employment between 2007 and 2009. Using geographical variation across U.S. counties, we show that counties with a larger decline in housing net worth experience a larger decline in non-tradable employment. This result is not driven by industry-specific supply-side shocks, exposure to the construction sector, policy-induced business uncertainty, or contemporaneous credit supply tightening. We find little evidence of labor market adjustment in response to the housing net worth shock. There is no expansion in the tradable sector in affected counties, and the correlation between the housing net worth decline and job losses in the tradable sector is zero. There is no evidence of wage adjustment, or of net labor emigration out of affected counties either.
434 citations
References
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TL;DR: In this paper, a framework for efficient IV estimators of random effects models with information in levels which can accommodate predetermined variables is presented. But the authors do not consider models with predetermined variables that have constant correlation with the effects.
16,245 citations
Journal Article•
TL;DR: In this article, the effect of financial structure on market valuations has been investigated and a theory of investment of the firm under conditions of uncertainty has been developed for the cost-of-capital problem.
Abstract: The potential advantages of the market-value approach have long been appreciated; yet analytical results have been meager. What appears to be keeping this line of development from achieving its promise is largely the lack of an adequate theory of the effect of financial structure on market valuations, and of how these effects can be inferred from objective market data. It is with the development of such a theory and of its implications for the cost-of-capital problem that we shall be concerned in this paper. Our procedure will be to develop in Section I the basic theory itself and to give some brief account of its empirical relevance. In Section II we show how the theory can be used to answer the cost-of-capital questions and how it permits us to develop a theory of investment of the firm under conditions of uncertainty. Throughout these sections the approach is essentially a partial-equilibrium one focusing on the firm and "industry". Accordingly, the "prices" of certain income streams will be treated as constant and given from outside the model, just as in the standard Marshallian analysis of the firm and industry the prices of all inputs and of all other products are taken as given. We have chosen to focus at this level rather than on the economy as a whole because it is at firm and the industry that the interests of the various specialists concerned with the cost-of-capital problem come most closely together. Although the emphasis has thus been placed on partial-equilibrium analysis, the results obtained also provide the essential building block for a general equilibrium model which shows how those prices which are here taken as given, are themselves determined. For reasons of space, however, and because the material is of interest in its own right, the presentation of the general equilibrium model which rounds out the analysis must be deferred to a subsequent paper.
15,342 citations
TL;DR: In this paper, Bhandari et al. found that the relationship between market/3 and average return is flat, even when 3 is the only explanatory variable, and when the tests allow for variation in 3 that is unrelated to size.
Abstract: Two easily measured variables, size and book-to-market equity, combine to capture the cross-sectional variation in average stock returns associated with market 3, size, leverage, book-to-market equity, and earnings-price ratios. Moreover, when the tests allow for variation in 3 that is unrelated to size, the relation between market /3 and average return is flat, even when 3 is the only explanatory variable. THE ASSET-PRICING MODEL OF Sharpe (1964), Lintner (1965), and Black (1972) has long shaped the way academics and practitioners think about average returns and risk. The central prediction of the model is that the market portfolio of invested wealth is mean-variance efficient in the sense of Markowitz (1959). The efficiency of the market portfolio implies that (a) expected returns on securities are a positive linear function of their market O3s (the slope in the regression of a security's return on the market's return), and (b) market O3s suffice to describe the cross-section of expected returns. There are several empirical contradictions of the Sharpe-Lintner-Black (SLB) model. The most prominent is the size effect of Banz (1981). He finds that market equity, ME (a stock's price times shares outstanding), adds to the explanation of the cross-section of average returns provided by market Os. Average returns on small (low ME) stocks are too high given their f estimates, and average returns on large stocks are too low. Another contradiction of the SLB model is the positive relation between leverage and average return documented by Bhandari (1988). It is plausible that leverage is associated with risk and expected return, but in the SLB model, leverage risk should be captured by market S. Bhandari finds, howev er, that leverage helps explain the cross-section of average stock returns in tests that include size (ME) as well as A. Stattman (1980) and Rosenberg, Reid, and Lanstein (1985) find that average returns on U.S. stocks are positively related to the ratio of a firm's book value of common equity, BE, to its market value, ME. Chan, Hamao, and Lakonishok (1991) find that book-to-market equity, BE/ME, also has a strong role in explaining the cross-section of average returns on Japanese stocks.
14,517 citations
TL;DR: Using a sample free of survivor bias, this paper showed that common factors in stock returns and investment expenses almost completely explain persistence in equity mutual fund's mean and risk-adjusted returns.
Abstract: Using a sample free of survivor bias, I demonstrate that common factors in stock returns and investment expenses almost completely explain persistence in equity mutual funds' mean and risk-adjusted returns Hendricks, Patel and Zeckhauser's (1993) "hot hands" result is mostly driven by the one-year momentum effect of Jegadeesh and Titman (1993), but individual funds do not earn higher returns from following the momentum strategy in stocks The only significant persistence not explained is concentrated in strong underperformance by the worst-return mutual funds The results do not support the existence of skilled or informed mutual fund portfolio managers PERSISTENCE IN MUTUAL FUND performance does not reflect superior stock-picking skill Rather, common factors in stock returns and persistent differences in mutual fund expenses and transaction costs explain almost all of the predictability in mutual fund returns Only the strong, persistent underperformance by the worst-return mutual funds remains anomalous Mutual fund persistence is well documented in the finance literature, but not well explained Hendricks, Patel, and Zeckhauser (1993), Goetzmann and Ibbotson (1994), Brown and Goetzmann (1995), and Wermers (1996) find evidence of persistence in mutual fund performance over short-term horizons of one to three years, and attribute the persistence to "hot hands" or common investment strategies Grinblatt and Titman (1992), Elton, Gruber, Das, and Hlavka (1993), and Elton, Gruber, Das, and Blake (1996) document mutual fund return predictability over longer horizons of five to ten years, and attribute this to manager differential information or stock-picking talent Contrary evidence comes from Jensen (1969), who does not find that good subsequent performance follows good past performance Carhart (1992) shows that persistence in expense ratios drives much of the long-term persistence in mutual fund performance My analysis indicates that Jegadeesh and Titman's (1993) one-year momentum in stock returns accounts for Hendricks, Patel, and Zeckhauser's (1993) hot hands effect in mutual fund performance However, funds that earn higher
13,218 citations
"Uncertainty, Financial Frictions, a..." refers methods in this paper
...In implementing the first step, we employ a 4-factor model—namely, the Fama and French (1992) 3-factor model, augmented with the momentum risk factor proposed by Carhart (1997). In the second step, we calculate the quarterly firm-specific standard deviation of daily idiosyncratic returns, according to...
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TL;DR: In this article, the American Finance Association Meeting, New York, December 1973, presented an abstract of a paper entitled "The Future of Finance: A Review of the State of the Art".
Abstract: Presented at the American Finance Association Meeting, New York, December 1973.(This abstract was borrowed from another version of this item.)
11,225 citations