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Assessing the economic value of probabilistic forecasts in the presence of an inflation target

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Listed:
  • Christopher McDonald
  • Craig Thamotheram
  • Shaun P. Vahey
  • Elizabeth C. Wakerly

Abstract

We consider the fundamental issue of what makes a “good” probability forecast for a central bank operating within an inflation targeting framework. We provide two examples in which the candidate forecasts comfortably outperform those from benchmark specifications by conventional statistical metrics such as root mean squared prediction errors and average logarithmic scores. Our assessment of economic significance uses an explicit loss function that relates economic value to a forecast communication problem for an inflation targeting central bank. We analyse the Bank of England’s forecasts for inflation during the period in which the central bank operated within a strict inflation targeting framework in our first example. In our second example, we consider forecasts for inflation in New Zealand generated from vector autoregressions, when the central bank operated within a flexible inflation targeting framework. In both cases, the economic significance of the performance differential exhibits sensitivity to the parameters of the loss function and, for some values, the differentials are economically negligible.

Suggested Citation

  • Christopher McDonald & Craig Thamotheram & Shaun P. Vahey & Elizabeth C. Wakerly, 2016. "Assessing the economic value of probabilistic forecasts in the presence of an inflation target," CAMA Working Papers 2016-40, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
  • Handle: RePEc:een:camaaa:2016-40
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    34. repec:hal:journl:peer-00834423 is not listed on IDEAS
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    Keywords

    Forecasting inflation; Inflation targeting; Cost-loss ratio; Forecast evaluation; Monetary policy;

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