RDP 2020-08: Start Spreading the News: News Sentiment and Economic Activity in Australia 1. News, Sentiment and the Economy

Well, all I know is what I read in the Papers (American humourist, Will Rogers, The New York Times, 30 September 1923)

The large and immediate effect of the COVID-19 pandemic on consumer confidence, business sentiment and economic activity has highlighted the need for policymakers to develop better real-time indicators of the economy and to deepen their understanding of the links between the news, sentiment and economic activity.

In the popular press and the business community, there is a belief that sentiment (or ‘confidence’) has an important causal role in explaining changes in economic activity. But applied research on the topic generally finds that economic activity explains sentiment rather than vice versa (Roberts and Simon 2001). Some research concludes that sentiment is important for both forecasting and explaining business cycles, while other papers argue that it contains important information but has little causal effect, and some suggest it has no value even in forecasting (Barsky and Sims 2012).

To investigate these issues in more depth we develop a new real-time indicator for the Australian economy based on text analysis of news articles. A ‘news sentiment index’ (NSI) is constructed that measures the net balance of positive and negative words used by journalists in news articles about the economy. This indicator can be used to track economic conditions on a daily basis (Shapiro, Sudhof and Wilson 2017; Larsen and Thorsrud 2018). This new economic indicator allows us to explore the role of sentiment in the Australian business cycle with much greater precision and along more dimensions than previous work.

First, we demonstrate that the NSI is an important addition to the suite of real-time indicators of the economy. The NSI complements other high-frequency economic indicators in its ability to ‘nowcast’ the economy. But the NSI is timelier than almost all other indicators because it can be updated on a daily basis. This gives it a clear advantage in being able to pick turning points in the economy, which is important from a policy perspective.

Second, we provide some evidence of a causal role for news sentiment in driving survey-based measures of sentiment and, to a lesser extent, economic activity more generally. Not only is the NSI a very timely indicator, but changes in news-based sentiment precede movements in survey-based sentiment measures. This may be because, in making decisions, consumers and business managers rely on high-frequency information that is broadcast through the news media. On top of this, the NSI can predict changes in business conditions in the near future over and above survey-based sentiment indicators and measures of current business conditions (based on both local projection models and vector autoregressions). To the extent that the news media captures a broad audience the information could be more representative than survey data provided by professional data suppliers (Thorsrud 2020). But arguing against a causal interpretation, we find that the size of the effect of news sentiment on economic activity is small. We also do not find that changes in news sentiment can explain broad indicators of business conditions, such as GDP growth. This suggests the NSI provides limited information content at a lower (quarterly) frequency.

Third, we show that it is important to disentangle sentiment and uncertainty when trying to explain short-term fluctuations in economic activity.[1] There is now a very large literature exploring the links between uncertainty and the business cycle (e.g. Bloom 2014; Moore 2017; Shapiro et al 2017). But few studies look at both sentiment and uncertainty within the same framework. Along with the NSI, we construct a related measure of news uncertainty. We show that changes in news sentiment have larger and more persistent correlations with measures of economic activity than changes in news uncertainty. This may be because news sentiment is a better indicator of current economic conditions than news uncertainty.

Fourth, we construct an indicator capturing sentiment in news specifically relevant to monetary policy. This news indicator predicts changes in the cash rate even after accounting for other important determinants of the cash rate, such as the RBA's forecasts for the economy. One potential explanation is that the news contains useful information about the risks to the economic outlook to which the RBA is responding when setting interest rates (e.g. Sharpe, Sinha and Hollrah 2017). Alternatively, it may be that the forecasts are biased in some way. Either way, the evidence suggests that changes in news sentiment do not cause changes in monetary policy, but that the relationship is due to an omitted variable.

Finally, we provide evidence that monetary policy causes changes in sentiment in ways consistent with standard models. We identify the causal effect of changes in interest rates on news sentiment by conducting an event study in the days before and after monetary policy announcements. Standard models would predict that lowering interest rates should boost the outlook for the economy and hence be associated with increases in sentiment (Nakamura and Steinsson 2018a). Prior to the COVID-19 pandemic though, there were numerous media reports that falling interest rates were causing weaker sentiment amongst business and consumers (Kirchner 2020b). In line with standard models, however, we find that increases (decreases) in interest rates are generally associated with weaker (stronger) news sentiment. This is consistent with the findings of earlier studies that rely on lower-frequency measures of sentiment, which also found that lower interest rates led to higher sentiment on average (Roberts and Simon 2001).

One limitation of our analysis is that we cannot clearly disentangle the effect of shocks to news (fundamentals) from those of sentiment or ‘animal spirits’ (non-fundamentals) on the economy. Future research may be able to separate these two shocks through different types of news articles.


Broadly speaking, ‘sentiment’ captures people's beliefs about the mean of the distribution of future economic outcomes (the first moment) while ‘uncertainty’ captures the variance of people's beliefs (the second moment) (Haddow et al 2013).[1] [1]