Towards an integrated macro-finance framework for monetary policy NBB Conference Brussels, 16 October Liquidity, inflation and asset prices in a time- varying framework for the euro-area Paper by C Baumeister, E Durinck and G Peersman Discussion by Kostas Tsatsaronis Bank for International Settlements 1

2 Overview Main question: Look at the dynamic links between liquidity (money) and other macro variables from a monetary policy perspective. How do prices and quantities react to money shocks? Do these reactions differ conditionally on the broader macro context ? Basic answers: Money does matter… …for inflation, output growth and real asset prices …in particular “narrow money” and credit …especially during a financial boom-bust cycle

3 General comments An central question in macro and very important for central bankers Rich implications for inputs to policy decision making Brings to bear useful techniques: Time-varying VAR analysis of responses within different macro context Provides a lot of food for further thought

4 The workhorse: VAR Endogenous variables: GDP growth Inflation Interest Rate Real asset price growth Liquidity growth Exogenous variables: Period dummies: great moderation post 1985 Equity volatility index (high-low split) Estimation: Three lags Choleski identification

5 Comment of Grumpy Old Discussant Why use the “synthetic” euro area data for such an investigation? The euro area did not exist but for six out of 35 years in the sample period Data artificially biased towards an average that may mean little for each individual economy Focus on financial and monetary variables while ignoring the flexibility of European exchange rates! Why not look at single countries, or Germany together with its close monetary allies?

6 Further comments on the VAR Asset price volatility: maybe deviation from trend? How important is the ordering of the first variables? Especially the interest rate and asset price growth Three lags may be an issue Evidence that some of the mechanisms of interest are long-fused Especially the “endogenous risk” component

7 Time-varying parameter VAR An interesting idea to capture more subtle shifts in mechanisms Results are a little puzzling: Recently a liquidity shock leads to stronger output and inflation response, despite the higher interest rate Evidence of a change in the nature of what “liquidity” proxies for? Maybe worth to look into the M1 vs M3-M1 split

8 Analysis conditional on “states” An interesting idea to uncover regularities similar to split-sample regression but more flexible akin to quartile regressions in some cases where the states refer to ranges for the LHS variable The use of estimated residuals as RHS variables could be problematic, but I am not a purist

9 Conditional results The effect of liquidity shocks on output, inflation and real asset prices is strengthened during asset price booms and busts The liquidity effects during business cycle upswings are not too pronounced except for property prices In high inflation regimes liquidity boosts nominal asset prices and real property prices

10 Conditional results (cont’d)  Policy should be concerned with the dynamics of asset markets in assessing the response to liquidity shocks  Could one interpret the asset price boom periods as supply-driven, and business cycle boom periods as demand driven episodes of increased liquidity and credit?  What do we know about the periods that combine characteristics?

11 Bottom line I like the paper because: It presents different facets of the interactions between money/credit and the macroeconomy It provides ground for more structured analysis of these channels I think that authors have to look deeper in: Explaining the patterns they have uncovered Making sure that the results are not influenced by the “synthetic” nature of the data used