Macroprudential policy and central bank communication

1. Macroprudential policy and central bank communication Benjamin Born (Bonn U), Michael Ehrmann (ECB) and Marcel Fratzscher (ECB) Disclaimer: The views expressed here are solely the views of the presenter and do not necessarily reflect those of the ECB or the Eurosystem.

2. Motivation • Financial supervision and regulation at the forefront of the policy debate since the financial crisis • Central banks will play a major rolein macroprudential supervision • Example: European Systemic Risk Board (ESRB) hosted by the ECB

3. Motivation • Why assign macroprudential supervision to central banks? • Combining financial supervision with monetary policy tasks can lead to synergies, esp. via information gains (Borio 2009) • Financial stability objective clearly requires a lender of last resort of the central bank (Blinder 2010) • Focus on (short-run) price stability may ignore longer-term risks to price stability and financial stability (Feldstein 2010)

4. Motivation • But there are also risks involved • Conflicts among goals not excluded; e.g., need to tighten monetary policy vs. concerns about solvency of financial intermediaries (Goodhart & Shoenmaker 1995, De Grauwe &Gros 2009) • Asymmetric reputation risk: Failures in financial supervision typically attract a lot of media attention, successes much less so • Reputation loss could possibly adversely affect monetary policy conduct • Communication will be an important part of macroprudential policy

5. Our paper: Is communication a policy tool? • Exploits the fact that CBs have communicated about financial stability in the past, via FSRs and other forms • Important: we infer from a time without explicit macroprudential tasks! • Provides an empirical assessment of the effectiveness of central bank communication about financial stability • Effectiveness as in Blinder et al. (2008): “creating news” and “reducing noise” – impact on level and volatility • Unique dataset: 357 releases of Financial Stability Reports (FSRs) and 720 speeches and interviews by central bank governors • Broad country coverage: 36 countries from 1996-2009 • Analyzes the reaction of financial sector stocks to these communication events

6. Main findings • Frequency of speeches/interviews reacts to market conditions (in contrast to pre-scheduled FSRs) • FSRs have become less optimistic as of early 2006 • Communication about financial stability has important repercussions on financial sector stock prices • FSRs create news (long-lasting and sizeable effect on stock market returns) • FSRs reduce noise (reduce market volatility, particularly if containing optimistic assessment) • Speeches/interviews have little effect on returns and increase volatility

7. Literature • Central bank communication about financial stability has not yet received much attention in the academic literature. • Svensson (2003): FSRs as early warning • Cihak (2006,2007): on the content of FSRs • Oosterloo, de Haan, and Jong-A-Pin (2007): who publishes FSRs, for what motives, and with what content? • Allen, Francke, and Swinburne (2004): recommendations for the Riksbank’s FSR, i.e. some aspects of effectiveness • Triple role for CB communication (Blinder et al. 2008) • Enhance CB credibility • Improve effectiveness of policy • Accountability

8. Identifying the release date of communications • Financial Stability Reports • Main source: central bank websites and press offices • Complemented by news reports about FSR releases from Factiva • 357 FSRs in total • These determine our country sample (35 plus USA) and our time sample (January 1996 to September 2009) • Speeches and interviews • By central bank governors • Objective is to extract all relevant public statements that relate to financial stability from Factiva using name of governor plus keywords • 720 speeches/interviews in total

9. Stock market volatility and the occurrence of speeches and interviews Communication intensifies in times of financial turbulence

10. Measuring the content of communication • Employ the computerized textual-analysis software Diction 5.0 • Searches text for different semantic features using a corpus of several thousand words • Used, e.g., in Armesto et al. (2009, JMCB) to extract the information content of the Fed’s Beige Book • We are interested in two dimensions: • Optimism: information about current state and prospects of financial system • Activity: signals willingness and intentions to take corrective or supportive action

11. Measuring the content of communication • Advantages: • Software creates more mechanical and objective coding • Replicability of coding • Allows a consistent coding of long passages of text across a large number of communications • Drawback: • does not consider context of the text, cannot generate “tailor-made” coding for financial-stability communication

12. Measuring the content of communication • Compute scores • For each news report about a speech/interview • For each executive summary of an FSR • Transform the resulting scores into discrete variables (required for subsequent analysis): • +1: upper third of distribution • 0: middle third of distribution • -1: lower third of distribution • Alternative classification • Explain content of communication • Extract residuals, and sort these into a {-1,0,+1} indicator

13. Coding examples 28-01-1998: “U.K. BOE's George Confident Asia Contagion Can Be Avoided” “Governor of the Bank of England Eddie George said Wednesday he was 'reasonably confident' wider financial contagion from the Asia crisis could be avoided.” Source: Dow Jones International News Coded: Optimism =1, Activity =0 09-11-2000: “Korea markets unstable as worries linger-c.bank.” “South Korea's financial markets continue to show signs of instability as the second phase of financial restructuring progresses, the governor of the central Bank of Korea said on Thursday.” Source: Reuters News Coded: Optimism =-1, Activity =0 03-10-2008: “Bernanke: Fed to do all it can to combat crisis” “Federal Reserve Chairman Ben Bernanke said on Friday the U.S. central bank will do whatever it can to combat the credit crisis and help the economy.” Source: Reuters News Coded: Optimism =0, Activity =1

14. Evolution of optimism over time: FSRs Tone of FSRs improves from 2000-2006 Q1, then drops

15. Financial market data • Daily frequency for two practical reasons • Financial market data with higher frequency not available for a large cross-section of countries over a relatively long horizon • Identification of release time of central bank communication within a day impossible • Choice of financial sector stock market indices: • Expect empirical effects of financial stability communication to be most easily detected here • Less traditional market impact measures (implied volatilities, expected default frequencies) not available over whole cross-section and time • All stock indices expressed in local currency • Robustness: complete stock indices

16. Event study methodology • Event: release of FSR or delivery of speech/interview • Questions: • Does an event affect stock markets in a causal way? • How persistent is the effect? • Ingredients: • benchmark model to compute expected returns in absence of an event • excess returns as difference between actual and expected returns • Statistical tests to determine whether the event has a significant effect on returns and standard deviations

17. Benchmark model • Based on Edmans et al. (2007) • Rit daily local currency return on financial sector stock market index • Rmtdaily US dollar return on Datastream’s global financial sector stock market index • Dtday of the week dummies • Based on Pojarliev and Levich (2007) • Tit-1trend in stock markets over 20 days prior to event (momentum) • Sit-1standard deviation of daily returns over 20 days prior to event • Mit-1“misalignment” on the day preceding the event: percentage deviation of stock index from its national average over entire sample • Estimated over non-event days ±60 days

18. or Excess returns • Hypothesis to be tested:

19. or Cumulated excess returns • Recursive computation of excess returns k days after event: • Hypothesis to be tested: • To test whether communications reduce noise

20. Predicted vs. actual evolution of cumulated stock market returns after communication • Expected cumulated returns close to zero • Markets move in direction of central bank view • FSR release on average moves equity markets by 2% over 10 weeks

21. Predicted vs. actual evolution of cumulated stock market returns after communication • Stock markets decline by less than predicted • But difference much smaller than for FSRs

22. Effectiveness of FSRs – Optimism dimension • Around 60% of FSRs lead to desired market reaction • Initial excess return: 0.32% on average • Cumulated excess returns of up to 2% after 50 days • Sizeable and economically meaningful effect • Some evidence that FSRs lead to lower stock market volatility

23. Effectiveness of speeches/interviews – Optimism dimension • Effect on returns much less systematic • Consistently increase stock market volatility

24. Robustness – sample splits for speeches/interviews • Stronger effectiveness w.r.t moving prices in crisis period, but volatility increases • It is mainly pessimistic elements that affect financial markets

25. Channels: Why are FSRs effective? • Coordination channel • Markets lack information about financial stability, or • Discrepancy in market views  FSR coordinates market views and actions, with persistent effect on asset prices • Signalling channel • FSRs provide information about future policy actions or future path of economy  FSR affects markets by signalling future policy action (though may not necessarily change expectations, i.e. may not imply “surprise”)

26. Channels: Why are FSRs effective? • Only very weak evidence for signalling channel • Optimistic FSRs are followed by interest rate increases • FSRs slightly more effective when accompanied by corresponding interest rate movements • Persistence speaks in favour of signalling channel

27. Conclusions • Communication about financial stability has important repercussions on financial sector stock prices • FSRs • Have become more pessimistic as of early 2006 • Significant, potentially long-lasting effect on stock market returns • FSRs tend to reduce market volatility, particularly if containing optimistic assessment • Speeches/Interviews • Very flexible tool • On average far less effective instrument • Increase market volatility, particularly if using active language • Communication effects are longer-lasting •  potential to change dynamics in financial markets

28. Policy implications • Communication by monetary authorities on financial stability issues can effectively influence financial markets • But: needs to be employed with care … • Importance of differentiating between communication tools and content when designing communication strategy on financial stability issues • Difficulty of designing successful communication strategy on financial stability

29. Robustness – sample splits for FSRs • Much of findings driven by pre-crisis period  crisis is different (how?) • Market return findings for EMEs and advanced economies similar; volatility findings driven by advanced economies • Similar to benchmark: importance of optimism in FSRs

30. Determinants of success • What determines whether communication event is effective in guiding markets? Potential characteristics: • Content of communication • Characteristics of central banks • External conditions at time of events • Define two binomial dependent variables • Defined as +1, if optimistic communication triggers positive excess returns, or if pessimistic communication triggers negative excess returns, and 0 otherwise • Defined as +1, if event lowers market volatility, and 0 otherwise • Run probit regressions

31. Determinants of success in reducing noise: FSRs • Optimistic reports have 21% higher probability of being effective than pessimistic ones • FSRs in advanced economies have 17% higher probability of calming markets • FSRs with accompanying news reports nearly 20% more likely to trigger volatility reduction • FSRs have 19% reduced success probability in calming markets during financial crisis • FSRs with an about 25% larger probability to calm markets when market volatility has increased • evidence for a co-ordination channel

32. Determinants of success in reducing noise: Speeches • Similar to the effects of FSRs • Main difference: effects in advanced economies are not different to those in emerging markets • Leaning against boom increases the probability for a volatility reduction by 20% compared to other pessimistic statements • Leaning against declining stock markets does not trigger reduced volatility compared to pessimistic statements

33. Determinants of success: Summary • Optimistic messages have potential to reduce noise, i.e. to dampen volatility in financial markets • Exceptions are optimistic speeches that try to lean against bearish stock market • Much harder to reduce noise, if stock markets are characterized by a lot of momentum • Speeches leaning against booming markets very effective in calming markets • Effectiveness also more easily achieved in presence of highly volatile stock markets • Central bank communication not always and everywhere equally effective • Current market characteristics need to be taken into account