RDP 2021-04: Monetary Policy, Equity Markets and the Information Effect 3. Literature Review
April 2021
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Previous work has considered the information effect from a theoretical perspective using a number of vantage points: central bank credibility (Barthélemy and Mengus 2018), central bank information (Ellingsen and Söderström 2001; Frankel and Kartik 2018), the central bank reaction function (Brassil 2019), uncertainty (Tang 2015), the presence of other economic shocks (Berkelmans 2011), the type of economic shock (Jia 2019), dispersed information (Melosi 2017) or heterogeneous beliefs among agents (Andrade et al 2019). Jointly these papers provide useful context on how the information effect could occur.
Though theory provides various plausible mechanisms for the information effect, Romer and Romer (2000) first provided empirical evidence of the central bank information effect. They show that the Federal Reserve's inflation forecasts are superior to private forecasters, and that this superior information could be inferred from the Federal Reserve's monetary policy decisions. However, Faust, Swanson and Wright (2004) find that this result is not robust to changes in the sample period and modifications in methodology.
More recent work on the information effect has directly estimated the effect of monetary policy surprises on revisions to professional forecasts. In the United States, it has been shown that a surprise monetary policy tightening can drive declines in unemployment rate forecasts (Campbell et al 2012) and increases in GDP forecasts (Nakamura and Steinsson 2018; Janson and Jia 2020). These results are consistent with the idea that monetary policy surprises contain information about the economy. The findings also suggest that the information effect could indeed be a powerful channel of monetary policy. However, Bauer and Swanson (2019) provide evidence that the results in these papers are confounded by economic news that affect both the central bank's policy response and private forecasts.
An alternative lens to view the information effect is through the equity market. Bauer and Swanson (2019) find little evidence that the information effect dominates the response of equity prices to monetary policy surprises for the United States. Their results are consistent with earlier work from Bernanke and Kuttner (2005). On the other hand, Cieslak and Schrimpf (2019) find evidence in the United States and Europe that the response of equity prices are consistent with the information effect for certain forms of central bank communication such as press conferences and minutes.
To reconcile the information effect with standard macroeconomic predictions of monetary policy, Jarocinski and Karadi (2020) attempt to disentangle the information component of monetary policy actions by combining high-frequency identification of monetary policy surprises with sign restrictions. Exploiting the fact that the predictions of the information effect are different from standard effects (Table 1), they show that decreases in interest rates driven by information indeed have a significant contractionary effect on equity prices and future GDP, while a pure increase in interest rates (not driven by information) has the opposite and standard effect.
This paper uses the approach taken in Bauer and Swanson (2019) by looking at the response of the Australian equity market to monetary policy surprises. I also complement this approach by examining forecasts of equity earnings. To my knowledge, this is the first attempt in evaluating the information effect of monetary policy using equity earnings forecasts.