Central banks' voting contest

Charemza, Wojciech (2020): Central banks' voting contest.

Abstract

This paper compares how effective different voting algorithms are for the decisions taken by monetary policy councils. A voting activity index is proposed and computed as the ratio of the number of all possible decisions to the total number of different combinations of decisions available to a given composition of an MPC. The voting systems considered are these used by the US Federal Reserve Board and the central banks of the UK, Australia, Canada, Sweden and Poland. In the dynamic simulation model, which emulates voting decisions, the heterogeneous agents act upon individual forecast signals and optimise a Taylor-like decision function. The selection criterion is based on the simulated probability of staying within the bounds that define the inflationary target. The general conclusion is that the voting algorithm used by the Bank of Sweden is the best given the criteria applied, especially when inflation is initially outside the target bounds. It is observed that a decrease in inflation forecast uncertainty, which is inversely proportional to the correlation between the forecast signals delivered to members of the monetary policy board, makes the voting less effective.

• Item Type: MPRA Paper
• Language: English
• Keywords: voting algorithms, monetary policy, inflation targeting, forecast uncertainty
• Subjects: D - Microeconomics > D7 - Analysis of Collective Decision-Making > D72 - Political Processes: Rent-Seeking, Lobbying, Elections, Legislatures, and Voting Behavior; E - Macroeconomics and Monetary Economics > E4 - Money and Interest Rates; E - Macroeconomics and Monetary Economics > E4 - Money and Interest Rates > E47 - Forecasting and Simulation: Models and Applications; E - Macroeconomics and Monetary Economics > E5 - Monetary Policy, Central Banking, and the Supply of Money and Credit > E58 - Central Banks and Their Policies

References

Akram, F., G. Bärsden, and Ø. Eithreim (2006),’Monetary policy and asset prices. Respond or not?’, International Journal of Finance and Economics 1, 279–292.

Charemza, W., C. Díaz and S. Makarova (2019), ‘Quasi ex-ante inflation forecast uncertainty’, International Journal of Forecasting 35, 994-1007.

Charemza, W. and D. Ladley (2016), ‘Central banks’ forecasts and their bias: evidence, effects and explanation’, International Journal of Forecasting 32, 804–817.

Choi, D.B., T. M. Eisenbach, and T. Yorulmazer (2016), ‘Sooner or later: timing of monetary policy with heterogeneous risk-taking, American Economic Review: Papers & Proceedings, 106, 490–495.

Clements M.P. (2014.) ‘Forecast uncertainty – ex-ante and ex-post: US inflation and output growth’, Journal of Business and Economic Statistics 32, 206-216.

Dietrich, F. and C. List (2004), ‘A model of jury decisions where all jurors have the same evidence’, Knowledge, Rationality & Action, 142, 235-262.

Geraats, P. (2009), ‘Trends in monetary policy transparency’, International Finance 12, 235-268.

Gersbach, H. and V. Hahn (2009), ‘Flexible majority rules for central banks’, Journal of Money, Credit and Banking 41, 507-516.

Gersbach, H. and B. Pahl (2009), ‘Voting transparency in a monetary union’, Journal of Money, Credit and Banking 41, 831-853.

Giordani, P. and P. Söderlind (2003), ‘Inflation forecast uncertainty’, European Economic Review 47, 1037-1059.

Horváth, R. and J. Jonášová (2015), ‘Central banks' voting records, the financial crisis and future monetary policy’, European Journal of Political Economy 38, 229–243.

Horváth, R., K. Šmídková and J. Zápal (2016), ‘Voting in central banks: Theory versus stylized Facts’, B.E. Journal of Economic Analysis and Policy 20150227, 1-62,.

Lahiri, K. and X. Sheng (2010), ‘Measuring forecast uncertainty by disagreement: the missing link’, Journal of Applied Econometrics 25, 514-538.

Olivei, G. and S. Tenreyro (2007), ‘The timing of monetary policy shocks’, American Economic Review 97, 636-663.

Riboni, A. and F. Ruge-Murcia (2014), ‘Dissent in monetary policy decisions’, Journal of Monetary Economics 66, 137–154.

Sirchenko, A. (2011), ‘Policymakers’ votes and predictability of monetary policy’, EUI Working Papers, Department of Economics, ECO 2011/05.

Sosnowska, H. (2013), Analysis of voting method used in the European Central Bank’, Operation Research and Decisions 1, 75-86.