Unveiling capital flow dynamics: Beyond the traditional business cycle

Economists traditionally view fluctuations in economic variables as either structural and long-term or cyclical and short-term. The analysis of economic activity distinguishes between potential output and business cycle fluctuations, while labor market economists often differentiate between natural and cyclical unemployment. Scholars analyze structural and cyclical factors separately, even within distinct disciplines like growth theory and business cycle analysis. Furthermore, this differentiation between short and long-term extends beyond output and employment to other macrofinancial variables.

Among these variables, capital flows stand out as critical, especially for Emerging Market and Developing Economies (EMDEs). For instance, in these countries capital outflows can generate significantly negative social costs by triggering sudden stops, which lead to currency depreciation, higher inflation, output contractions, and occasionally even financial crises (Ostry et al., 2012; Fernández et al., 2015). In line with this, Burger et al. (2022) introduce a measure of the natural level of capital flows and show that when observed flows are large and deviate significantly from this level, there is usually a subsequent sudden stop. Research on capital flows, just as with other macrofinancial variables, typically distinguishes only between short- and long-term fluctuations.

However, this differentiation has encountered significant challenges, as several variables exhibit also important medium-term fluctuations, including credit growth, asset prices, and even productivity and GDP growth. In the presence of financial frictions, credit supply and asset demand hinge on investors' beliefs about borrowers' default probabilities (Aikman et al., 2014). Since these expectations depend on the actions of others, small changes in fundamentals that prompt some investors to reassess their beliefs can cause most investors to follow suit, leading to larger and longer swings in credit growth and asset prices. For example, a small increase in economic growth within the traditional business cycle may prompt a large group of investors to revise default probabilities and extend more credit. This increase in credit supply can result in significant and persistent expansions in credit and asset prices that extend beyond the typical business cycle timeframe.

Similarly, productivity growth affects GDP not only in the long term, as traditionally believed, but also in the medium term. This occurs because the adoption of new technologies is driven by investment in R&D, which experiences boom and bust phases. Periods of high investment in R&D lead to accelerations in technology adoption, causing productivity to undergo extended periods of above-average and below-average growth. This phenomenon is reflected in "medium-term business cycles" in GDP and other variables (Comin and Gertler, 2006).

Medium-term oscillations are relevant for several variables, indicating that it is insufficient to restrict the analysis to only the short and long term. In this blog entry, we argue that it is the medium-term cycle, rather than the short-term cycle, of deviations in capital flows from their natural value, as defined by Burger et al. (2022) (the KF* gap), that explains their ability to predict sudden stops. We calculate short-term and medium-term deviations from the KF* gap for several EMDEs and conduct logit regressions to estimate their separate effects on the likelihood of a sudden stop over different timeframes. Following Burger et al. (2022) and Forbes and Warnock (2021), we control for global GDP growth, changes in global money supply and global monetary policy rates, the VIX index, oil prices, and local real GDP growth. In a recent, but still unpublished, working paper, we undertake the same exercise to also assess the effect on vulnerability to global shocks.  

The results show that the predictive powers of the KF* gap's components differ significantly (Figure 1). The business cycle component significantly anticipates sudden stops only at a six-quarter horizon. In contrast, the medium-term component anticipates them as early as one quarter ahead and remains significant for longer periods. When the business cycle component is two standard deviations above average, the probability of a sudden stop increases marginally from 5% to 10%. However, for the medium-term component, this probability rises dramatically from around 5% to between 25% and 53%. Therefore, KF* gaps cannot be regarded solely as reflective of business cycle dynamics; their medium-term fluctuations are essential for improved anticipation of sudden stops.

Figure 1. Marginal effect of KF* gap and its components on the probability of a sudden stop 

^{Notes: Effects on the probability of a sudden stop episode of a 1 pp increase in the ratio of the KF* gap.}

To conclude, it has always been acknowledged that within the traditional business cycle timeframe, monitoring short-run fluctuations of capital flows is important. Adding to this, Burger et al. (2022) show that capital flows can also be affected by long-term factors. The main message of our exercise is that medium-term oscillations in capital flows should also be monitored. These oscillations contain important information for the performance of the real sector and for the stability of the financial system.

References

David Aikman & Andrew G. Haldane & Benjamin D. Nelson, 2015. "Curbing the Credit Cycle." Economic Journal, Royal Economic Society, vol. 125(585).

Burger, John D., Francis E. Warnock, Veronica Cacdac Warnock. 2022. “A natural level of capital flows.” Journal of Monetary Economics 130: 1-16.

Comin, Diego, and Mark Gertler. 2006. “Medium-Term Business Cycles.” American Economic Review 96 (3): 523-51.

Fernández, Andrés, Alessandro Rebucci, Martín Uribe. 2015. “Are capital controls countercyclical.” Journal of Monetary Economics 76: 1-14.

Forbes, Kristin J., and Francis E. Warnock. 2021. “Capital flow waves—or ripples? Extreme capital flow movements since the crisis.” Journal of International Money and Finance 116: 2-24.

Ostry, Jonathan D., Atish R. Ghosh, Marcos Chamon, and Mahvash S. Qureshi. 2012. “Tools for managing financial-stability risks from capital flows.” Journal of International Economics 88 (2): 407-21. 

^{* The views represent only those of the authors and do not represent those of Banco de Mexico or of any of its members}