Too many cooks committees in monetary policy helge berger and volker nitsch
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Too Many Cooks? Committees in Monetary Policy Helge Berger and Volker Nitsch. Discussion by Christopher Crowe, IMF Research Department* for Conference on Central Bank Communication, Decision-Making and Governance , Waterloo University April 28-29 2009.

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Too Many Cooks? Committees in Monetary Policy Helge Berger and Volker Nitsch

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Too Many Cooks? Committees in Monetary PolicyHelge Berger and Volker Nitsch

Discussion by Christopher Crowe, IMF Research Department* for Conference on Central Bank Communication, Decision-Making and Governance, Waterloo University April 28-29 2009

* Does not necessarily reflect the views of the IMF, its management or Executive Board.


Summary of the paper

  • Paper’s key contribution is a new dataset covering >30 countries for up to 40 years

    • De facto as well as de jure committee size for CB MPCs

    • Composition of MPC (industrial, regional, institutional background)

  • Principal Use of the Data: is there an optimal committee size for inflation control?


Main Results

  • U-shaped relationship for inflation: minimized at 8-10 committee members.

    • Similar U-shaped relationship for inflation volatility.

    • Inverse-U for output growth.

  • Higher MPC member turnover associated with lower inflation (opposite of result with governor turnover).

  • Composition of MPC (e.g. government representation) has little impact.


My comments

  • Very interesting paper on an important topic.

  • The dataset could be used to shed light on several interesting questions relating to committees, decision-making and central bank governance…

  • …but I’m not wholly convinced that the paper’s main question is the right one to ask with this data.

  • Plus a few other comments.


Are the main results convincing?

  • Why should committee size affect the level of inflation?

    • Committee too large: cannot communicate easily; subject to factionalism or defense of own interests.

    • Committee too small: cannot benefit from lower volatility of mean decision.

    • But why higher inflation rather than more volatile inflation or inflation that’s harder to predict?

    • Any plausible model of the inflation bias with committee size as argument? Or of output growth?

  • Omitted variable bias likely large compared to any genuine effect.

    • Easy to think of omitted variables:

      • “Institutions” (effectiveness of government sector)

      • Heterogeneity (has macro implications, might require large committee)

      • “Culture” (shapes views on decision-making and individual responsibility, also macro policy and outcomes).

      • Regressions have only a minimum set of reasonable controls.


What could be driving the results?

  • Inflation bias can be caused by inappropriate output gap target

    • E.g. because government is going for short run growth

    • CBI as remedy: devolve to conservative CB’er or one with appropriate objectives

  • If a government wanted to weaken CBI:

    • Have a small committee (less political cover for tough decisions; easier to replace with more compliant candidates)

    • Have a large committee (ineffective talking shop; agenda-setting by compliant governor/chairman).

    • i.e. committee of reasonable size more independent.

  • But committee size not ultimate causal factor.


What other questions are there?

  • Inflation and output volatility

    • (paper already looks at variance of inflation)

  • Inflation and output predictability (look at variance of forecast errors)

  • Combine with voting behavior (more limited sample):

    • Do larger committees vote differently (e.g. agenda-setting by chair?)

    • Do different types of MPC member vote differently? (e.g. Besley, Meads and Surico, 2007; Meade and Sheets, 2005).

  • MPC member turnover (some interesting results in the paper, I would give these greater prominence).


Some other comments

  • The baseline results could be made more convincing:

    • Cluster SE’s by country to capture country-specific patterns of serial correlation

    • Additional controls:

      • measures of governance

      • Political turnover measures

      • De jure CBI

      • Output gap rather than growth minus avg. growth

  • Use inflation tax transform π/(1+ π) to reduce impact of outliers

  • It would also be useful to have summary statistics for the main variables.


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