Most empirical studies in macroeconomics approximate the deviations of aggregate economic variables (such as the GDP) from their trends with a normal distribution. Besides analytical convenience, such an approximation has been relatively successful in capturing some of the more salient features of the behaviour of aggregate variables in the US and other OECD countries.
Macroeconomic tail risks
A number of recent studies (see Fagiolo et al. 2008), however, have documented that the distributions of GDP growth rate in the US and many OECD countries do not follow the normal, or bell-shaped distribution. Large negative or positive growth rates are more common than the normal distribution would suggest. That is to say, the distributions exhibit significantly heavier ‘tails’ relative to that of the normal distribution. Using the normal distribution thus severely underpredicts the frequency of large economic downturns.
This divergence can be seen clearly in Figure 1. Panel (a) depicts the quantile-quantile plot of post-war US GDP growth rate (1947:QI to 2013:QIII) versus the normal distribution after removing the top and bottom 5% of data points. The close correspondence between this dataset and the normal distribution, shown as the dashed red line, suggests that once large deviations are excluded, the normal distribution is indeed a good candidate for approximating GDP fluctuations. Panel (b) shows the same quantile-quantile plot for the entire US post-war sample. It is easy to notice that this graph exhibits sizeable and systematic deviations from the normal line at both ends. Together, these plots suggest that even though the normal distribution does a fairly good job in approximating the nature of fluctuations during most of the sample, it severely underestimates the most consequential fact about business cycle fluctuations, namely, the frequency of large economic contractions.
Figure 1. The quantile-quantile plots of the post-war US GDP growth rate (1947:QI to 2013:QIII) vs. the standard normal distribution (dashed red line)
Note: The horizontal axis shows quantiles of the standard normal distribution; the vertical axis shows quantiles of the sample data.
Input-output linkages, micro shocks, and macro risks
In recent work (Acemoglu et al. 2014), we have argued that input-output linkages between different firms and sectors within the economy can play a first-order role in determining the depth and frequency of large economic downturns. Building on an earlier framework by Acemoglu et al. (2012), we show that if all firms take roughly symmetric roles as input-suppliers to one another (in what we call a ‘balanced’ economy), not only GDP fluctuations are normally distributed, but also large economic downturns are extremely unlikely. In other words, absent any amplification mechanisms or aggregate shocks, microeconomic firm-level shocks cannot result in macroeconomic tail risks. More interestingly, this result holds regardless of how these firm-level microeconomic shocks are distributed.
Our subsequent analyses, however, establish that the irrelevance of microeconomic shocks for generating macroeconomic tail risks would no longer hold if the economy is ‘unbalanced’, in the sense that some firms play a much more important role as input-suppliers than others. More specifically, we argue that:
The propagation of microeconomic shocks through input-output linkages can significantly increase the likelihood of large economic downturns.
The implications of our theoretical results can be summarised as follows:
- First, the frequency of large GDP contractions is highly sensitive to the nature of microeconomic shocks.
In particular, in an unbalanced economy, micro shocks with slightly thicker tails can lead to a significant increase in the likelihood of large economic downturns. This suggests that unbalanced input-output linkages can lead to the build-up of tail risks in the economy.
- Second, depending on the distribution of microeconomic shocks, the economy may exhibit significant macroeconomic tail risks even though aggregate fluctuations away from the tails can be well-approximated by a normal distribution.
This outcome is consistent with the pattern of US post-war GDP fluctuations documented in Figure 1.
This observation underscores the importance of studying the determinants of large recessions, as such macroeconomic tail risks may vary significantly even across economies that exhibit otherwise identical behaviour for moderate deviations.
- Finally, there is a trade-off between the normality of micro-level shocks and imbalances in the input-output linkages.
An economy with unbalanced input-output linkages subject to normal microeconomic shocks exhibits deep recessions as frequently as a balanced economy subject to heavy-tailed shocks.
Solving the ‘small shocks, large cycles puzzle’
In this sense, our results provide a novel solution to what Bernanke et al. (1996) refer to as the ‘small shocks, large cycles puzzle’ by arguing that the interaction between the underlying input-output structure of the economy and the shape of the distribution of microeconomic shocks is of first-order importance in determining the nature of aggregate fluctuations.
Understanding the underlying causes of large economic downturns such as the Great Depression has been one of the central questions in macroeconomics. Our results suggest that the frequency and depth of such downturns may depend on the interaction between microeconomic firm-level shocks and the nature of input-output linkages across different firms. This is due to the fact that the propagation of shocks over input-output linkages can lead to the concentration of tail risks in the economy. This observation highlights the importance of separately studying the determinants of large economic downturns, as such macroeconomic tail risks may vary significantly even across economies that exhibit otherwise identical behaviour for moderate deviations.
Acemoglu, D, V M Carvalho, A Ozdaglar, and Al Tahbaz-Salehi (2012), “The network origins of aggregate fluctuations”, Econometrica, 80, 1977–2016.
Acemoglu, D, A Ozdaglar, and A Tahbaz-Salehi (2014), “Microeconomic origins of macroeconomic tail risks”, NBER Working Paper No. 20865.
Bernanke, B, M Gertler, and S Gilchrist (1996), “The financial accelerator and the flight to quality”, The Review of Economics and Statistics, 78, 1–15.
Fagiolo, G, M Napoletano, and A Roventini (2008), “Are output growth-rate distributions fat-tailed? Some evidence from OECD countries”, Journal of Applied Econometrics, 23, 639–669.