RDP 2016-01: Measuring Economic Uncertainty and Its Effects 1. Introduction

Uncertainty has been a frequently cited reason for the weak global recovery from the financial crisis. This has been true for the United States, the European Union, and Australia (e.g. FOMC 2009; Balta, Valdés Fernández and Ruscher 2013; Kent 2014).

In this context, uncertainty refers to clarity, or lack thereof, about future economic activity. It incorporates both ‘risk’ and ‘Knightian uncertainty’. In the former, the probabilities of potential outcomes are known, but which outcome will occur is not. In the latter, neither the probabilities of outcomes nor the eventual outcome are known (Knight 1921; Cagliarini and Heath 2000). In practice, the two are difficult to disentangle, so I refer to a single concept of uncertainty that blends both in this paper.

Understanding economic uncertainty is difficult because it is not directly observable. In response, economists have developed a large and active literature that attempts to measure uncertainty and assess how heightened uncertainty affects the economy – both in theory and in practice.

In this paper I apply these techniques to Australia. To do so, I first review a number of commonly used proxies of uncertainty (Section 2). These proxies include: newspaper-based measures of uncertainty, like those created by Baker, Bloom and Davis (2015); finance-based measures, such as stock market volatility; and measures of disagreement among forecasters for key economic variables. Using some of these proxies, I construct a monthly index of economic uncertainty for Australia (Figure 5; Section 2.2).

I then use this index to document some stylised facts about uncertainty (Section 3). Uncertainty is estimated to be higher around some major geopolitical events, recessions, surprise changes in monetary policy, and federal elections. It also tends to increase more quickly than it decreases – spiking up rapidly around major events, and then fading more slowly. The index is also very persistent – periods of high or low uncertainty tend to last. Finally, both foreign and domestic factors appear to be relevant for uncertainty in Australia.

In Section 4, I use the index to assess how and why economic uncertainty might matter in Australia. There are reasons it should. First, under ‘real options’ theory, heightened uncertainty delays decisions that are costly to reverse (for instance, because of adjustment costs) because firms are better off waiting for uncertainty to subside before committing.^[1] Second, heightened uncertainty may induce households to increase their precautionary savings and, therefore, reduce their consumption (Kimball 1990; Carroll 1997). In the short run, these responses are likely to be contractionary (Basu and Bundick 2012; Leduc and Liu 2015).

The Australian evidence is consistent with these theories: heightened uncertainty is estimated to weigh on economic activity. In particular, I find that employment growth slows modestly following a one standard deviation uncertainty shock, consistent with the real options channel of uncertainty. Also consistent with the real options channel, machinery and equipment investment growth slows in response to an uncertainty shock. The household saving ratio increases somewhat following an uncertainty shock and remains persistently elevated. This response is consistent with the precautionary savings channel of uncertainty.

Footnote

Bloom (2009) presents a model of real options effects in the context of firm hiring and investment choices with adjustment costs. Other earlier contributions to the real options literature include Bernanke (1983) and Dixit and Pindyck (1994). [1]