Abel, A. B., & Eberly, J. C. (1994). A unified model of investment under uncertainty. The American Economic Review, 84(5), 1369.
Arellano, C., Bai, Y., & Kehoe, P. (2010). Financial markets and fluctuations in uncertainty. Federal Reserve Bank of Minneapolis Working Paper.
Bolton, P., Schaller, H., & Wang, N. (2013). The marginal value of cash and corporate savings. Discussion paper, Columbia University Working Paper. 3.
Bloom, N., Bond, S., & Van Reenen, J. (2007). Uncertainty and investment dynamics. The review of economic studies, 74(2), 391–415.
Bloom, N., Floetotto, M., Jaimovich, N., Saporta-Eksten, I., & Terry, S. J. (2014). Really Uncertain Business Cycles. US Census Bureau, Center for Economic Studies.
Bernanke, B. S., & Gertler, M. (1989). Agency Costs, Net Worth, and Business Fluctuations. American Economic Review, 79(1), 14–31
Bernanke, B. S., Gertler, M., & Gilchrist, S. (1999). The financial accelerator in a quantitative business cycle framework. Handbook of macroeconomics, 1, 1341–1393.
Caldara, D., Fuentes-Albero, C., Gilchrist, S., & Zakrajsek, E. (2014). The macroeconomic impact of financial and uncertainty shocks. unpublished, Boston University.
Carriére-Swallow, Y., & Céspedes, L. F. (2013). The impact of uncertainty shocks in emerging economies. Journal of International Economics, 90(2), 316–325.
Chinn, M. D., & Ito, H. (2006). What matters for financial development? Capital controls, institutions, and interactions. Journal of Development Economics, 81(1), 163–192
Fazzari, S., Hubbard, R. G., & Petersen, B. C. (1987). Financing constraints and corporate investment (No. w2387). National Bureau of Economic Research.
Fazzari, S. M., Hubbard, R. G., & Petersen, B. C. (2000). Financing constraints and corporate investment: Response to Kaplan and Zingales (No. w5462). National Bureau of Economic Research.
Gelos, G. and A. Isgut (2002), “Irreversibilites in Fixed Capital Adjustment—Evidence from Mexican and Colombian Plant,” Economic Letters, Vol. 74, Issue 1 (December), 85–89.
Gilchrist, S., Sim, J. W., & Zakrajšek, E. (2014). Uncertainty, financial frictions, and investment dynamics (No. w20038). National Bureau of Economic Research.
Gürkaynak, R. S., Sack, B., & Wright, J. H. (2007). The US Treasury yield curve: 1961 to the present. Journal of Monetary Economics, 54(8), 2291–2304.
Hayashi, F. (1982). Tobin’s marginal q and average q: A neoclassical interpretation. Econometrica: Journal of the Econometric Society, 213–224.
Hennessy, C. A., Levy, A., & Whited, T. M. (2007). Testing Q theory with financing frictions. Journal of Financial Economics, 83(3), 691–717.
Kaplan, S. N., & Zingales, L. (1997). Do investment-cash flow sensitivities provide useful measures of financing constraints?. The Quarterly Journal of Economics, 169–215.
Kaplan, S. N., & Zingales, L. (2000). Investment-cash flow sensitivities are not valid measures of financing constraints (No. w7659). National Bureau of Economic Research.
Love, I. (2003). Financial development and financing constraints: International evidence from the structural investment model. Review of Financial studies, 16(3), 765–791.
Love, I., & Zicchino, L. (2006). Financial development and dynamic investment behavior: Evidence from panel VAR. The Quarterly Review of Economics and Finance, 46(2), 190 210.
Magud, N. E. (2008). On asymmetric business cycles and the effectiveness of counter-cyclical fiscal policies. Journal of Macroeconomics, 30(3), 885–905.
Magud, M. N. E., & Sosa, S. (2015). Investment in Emerging Markets We Are Not in Kansas Anymore… Or Are We? (No. 15-77). International Monetary Fund.
McLean, R. D., & Zhao, M. (2014). The business cycle, investor sentiment, and costly external finance. The Journal of Finance, 69(3), 1377–1409.
Merton, R. C. (1974). On the pricing of corporate debt: The risk structure of interest rates. The Journal of Finance, 29(2), 449–470.
Modigliani, F., & Miller, M. H. (1958). The cost of capital, corporation finance and the theory of investment. The American economic review, 261–297.
Sandri, D. and F. Valencia (2013). Financial Crises and Recapitalizations. Journal of Money, Credit, and Banking, vol. 45s (8), 59–86.
Townsend, R. M. (1979). Optimal contracts and competitive markets with costly state verification. Journal of Economic theory, 21(2), 265–293.
The authors thank Ravi Balakrishnan, Stephan Danninger, Greg Duffee, Jon Faust, Tryiggvi Gudmundson, Fei Hand, Dora Iakova, Alex Klemm, Peter Linder, Camelia Minoiu, Machiko Narita, Alejandro Werner, Jonathan Wright, and seminar participants at the IMF for comments and suggestions.
See for example Bloom (2009), Carriere-Swallow and Cespedes (2013), Caldara and others (2014), and Gilchrist and others (2014) for experiments on aggregate investment. See Gilchrist and others (2014) and Magud and Sosa (2015) for discussions on average investment.
See Bernanke and Gertler (1989), Bernanke, Gertler, and Gilchrist (1999), Gilchrist and Zakrajsek (2007), Arellano, Bai, and Kehoe (2012), Christiano, Motto, and Rostagno (2014), Caldara and others (2014), and Gilchrist and others (2014) for discussions of costly external financing; see McDonald and Siegel (1986), Dixit and Pindyck (1994), Abel and Eberly (1994), Bloom and others (2000, 2007, 2009, 2014) and Magud (2008) for discussions of the option value of wait-and-see. Gelos and Isgut (2001) document the impact of non-convex adjustment costs in emerging markets.
This can be the result of a wedge between the cost of internal and external finance that moves counter-cyclically with a firm’s networth, which could arise from the interaction between default risk and some financial friction. In a setting where default risk is endogenous, it can be shown (for instance using Townsend, 1979’s costly state verification) that this wedge can move in response to changes in risk-free interest rates (as in Bernanke, Gertler, and Gilchrist, 1999) and in response to increases in volatility (as in Sandri and Valencia, 2013; and Christiano, Motto, and Rostagno, 2014).
For the real option of waiting, the canonical literature mostly focuses on an inaction region along the demand/productivity dimension. Decamps and Villeneuve (2006) provides a similar theoretical foundation along the liquidity dimension.
Both terms, volatility and uncertainty, will be used interchangeably throughout the paper.
It is worth clarifying that we loosely use “shock” and “change” in these variables interchangeably. Strictly speaking, a shock should be the unexpected component of the change. Because part of the change can be expected, our results likely underestimate the impact of the unexpected component.
The intuition is that the two channels wane-and-wax in a negatively-correlated way. This leaves aggregate effects of uncertainty on investment similar across countries. Specifically, in a country with stronger fundamentals, the financing channel of uncertainty will be weaker as downside risks are lower. In this case the wait-and-see channel will be observed as firms are more capable of waiting–as they do not need to rush investments to generate operating revenues or building capital to use as collateral, if confronted with tighter financial constraints.
Before McLean and Zhao (2014), most of the literature treats this sensitivity to be time-invariant; they instead use U.S. data to show that such sensitivity varies over time with the business cycles. Our work further specifies that interest rates and uncertainty are two crucial determinants. Related work includes Baum and others (2009 and 2010) from which we depart by exploiting country heterogeneity among emerging market firms (as in Love and Zicchino, 2006; Love, 2003; and Magud and Sosa, 2015).
Here high vs. low means whether in a particular year the VIX is above or below the median.
One important consideration here is whether to use market or accounting leverage. We opt for accounting leverage as in Hennessy, Levy, and Whited (2007) because it is less affected by differing degrees of stock market liquidity among emerging markets.
Adopting net debt (leverage) is closer to various theoretical setups like Hennessy, Levy, and Whited (2007) or Gilchrist and others (2014), where cash stocks are treated as negative debt. In reality, we observe ubiquitously that firms hold cash and external debt at the same time, partially owing to leverage adjustment costs. Also, Bates and others (2009) argue that a precautionary motive for future riskiness is the most crucial reason for firms to hold cash. Therefore, we treat cash flows, rather than cash stocks, as a more reliable source of internal funds for investment. This is also more widely used in the existing literature. Another reason is that the use of cash flow brings us closer to the theoretical definition of the marginal propensity to invest since cash flow can be more plausibly treated as an stochastic variable than cash stocks.
Such a time-to-build effect of investment is also discussed in Bernanke, Gertler, and Gilchrist (1999).
Core accounting variables include: total asset, total (net) property, plant, and equipment, total common equity, cash stock, and capital expenditures. Such criteria are common in the existing literature; see, for example, Bolton, Chen, and Wang (2013) or McLean and Zhao (2014).
It is important to note that our model specification (2) passes the Sargan-Hansen endogeneity test for all right-hand-side firm-level variables when firm fixed effects are included, which implies support to treating them as exogenous. Results are available from the authors upon request.
Dropping also firms in the oil-&-gas sector does not affect our results; this is to rule out effects of changes in oil prices on investment.
Specifically we use the ratio of total private credit by deposit banks to GDP as a measure of financial depth. Our results are robust to using private credit from all financial institutions.
The detailed regression results are not reported but are available from the authors upon request.