Monetary Policy Challenges Posed by Asset Price Booms Stephen G. Cecchetti Rosenberg Professor of Global Finance

2 Outline Risks Posed by Asset Price Booms Policy Options Current State of the U.S. Economy

3 “A central bank seeking to maximize its probability of achieving its goals is driven, I believe, to a risk-management approach to policy. By this I mean that policymakers need to consider not only the most likely future path for the economy but also the distribution of possible outcomes about that path.” Alan Greenspan, August 2003.

4 A Risk Management Approach Control the probability of catastrophes. Financial Institution: Reduce risk of substantial monetary loss. Primary objective of monetary policy: Make sure nothing really bad happens. For a Central Bank: Control output & price deviations from trend.

5 Asset Price Booms and Busts Concern is primarily over catastrophes Natural to study the tail outcomes Conditional on seeing equity or housing prices rise by X%, what is the worst that can happen in the next year, in two years, in three?

6 Risks Created by Bubbles Look at some data: Real Equity: 27 countries Real Housing:17 countries Deviations of GDP from full-sample HP-filter.

7 Risks Created by Bubbles: Some estimates Mean: Real equity prices 20% above trend 4 quarters later, output gap is Real housing prices 10% above trend 12 quarters later, output gap is quarters later, price gap is Volatility Real housing prices 10% above trend 12 quarters later, output gap volatility is +5%

8 Risks Created by Bubbles: Some estimates Worst Outcomes (expected loss in lowest quartile) Equity: 20% boom lowers output gap tail 12 quarters later by 0.85 Housing: 10% boom lowers output gap tail 12 quarters later by 0.59

9 Risks Created By Asset Booms Levels: Equity & Housing  Output & Prices rise 4Q Housing  Output & Price declines 8-12Q+ Volatility: No impact on price level volatility Housing booms increase GDP volatility Expected Tail Loss Increase the probability of BAD events!

10 Equity vs. Housing Equity is typically 50% of GDP Housing is closer to 100% of GDP Equity holding is concentrated Housing bubbles increase bad outcomes

11 Equity vs. Housing Should we care about equity at all? Median capitalization <40% of GDP Interquartile range is 18% to 70% of GDP. Housing wealth effect tends to be large. Should there be any aggregate housing wealth effect?

12 Policy Options 1.Lean against the bubble 2.React to changes in inflation forecasts 3.Lean against the bust 4.Include housing prices target index. 5.Look for regulatory solutions.

13 Are Interest Rates the Right Instrument? Interest rates affect output & prices with a lag. Lags mean reducing interest rates in anticipation of the bubble bursting. But lowering interest rates reduces the probability the bubble will burst. Is it really possible to get the time right?

14 Housing prices price indices? Is this the right thing to do? Central bank objective: Stabilize the price of lifetime consumption. Analysis suggests substantial weight. Acquisition cost approach seems justified. (Note: No such evidence for stock prices.)

15 Putting Home Sale Prices in the Core PCE Price Index : 3/4 percentage points higher!

16 Regulatory Solutions Prudential regulation ensures that financial intermediaries remain well capitalized What about households? Are there times when lenders should be forced to restrict housing finance?

17 Current State of the U.S. Economy Federal Reserve Actions Short Term Objectives Long Term Objectives What’s Next?

18 Federal Reserve’s Short-Term Objectives “Do financial institutions and markets have sufficient funds to carry out their daily business?” Ensure markets remain liquid “Do market determined risk spreads accurately reflect current uncertainties in economic fundamentals?” Encourage rational valuation of collateral

19 Federal Reserve’s Long-Term Objectives “Are current financial conditions appropriate to attain medium-term macroeconomic stabilization objectives?” Does the September rate cut jeopardize Medium term inflation objectives? Maximum sustainable growth?

20 Inflation: Trend is Falling

21 Real Growth: What is the trend?

Simple Taylor Rule: 2% What is neutral?

23 Structural Questions 1.Do policymakers have the tools for the job? What are the central bank’s instruments? Target overnight rate Lending rate Deposit rate Collateral in Open Market Operations Term in Lending Collateral in Lending What should be the extent of public disclosure?

24 Structural Questions 2.How can we mitigate information problems that plague financial arrangements? Collateral, Net Worth Ratings agencies Data collection and disclosure Exchange-trading and the Clearinghouse

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26 Supplementary Tables

27 Risks Created By Bubbles How do booms change the Mean & Volatility of output and price-level gaps? Mean: x it = a + b d it-k (  ) +  it x it = output or price-level gap d it-k (  ) = 1 if k periods earlier filtered asset price exceeded threshold  Volatility: (x it ) 2 = a’ + b’ d it-k (  ) +  it

10% housing price deviation  output gap average -1.42, 12 quarters later

10% housing price deviation  volatility of output gap rises by 5.28% 12 quarters later

32 Expected Lower Tail Loss Expected Value conditional on being lower tail x it = a + b 0 d it-k (  ) +b 1 tail(  ) it +b 3 d it-k (  )x tail(  ) it +  it x it = output or price-level gap d it-k (  ) = 1 if k periods earlier filtered asset price exceeded threshold tail(  ) it = 1 if x it is in the  -percent tail b 3 estimate of impact of asset price boom of size  on expected tail loss in lowest  -percent of the dist.

20% equity price deviation  ETL in lowest quartile of output gap rises by quarters later