Probabilistic weights from the past may be a fragile guide to the future. Weighting may be in vain. Strategies that simplify, or perhaps even ignore, statistical weights may be preferable. The simplest imaginable such scheme would be equal-weighting or “tallying”. Gigerenzer and Brighton (2009). 7 In complex environments, tallying strategies have been found to be superior to risk-weighted alternatives. Take avalanche prediction. Avalanches are difficult to predict, as they are drawn from a fat-tailed (Power Law) distribution. Yet simple tallying of a small number of avalanche indicators has been found capable of predicting over 90% of historical accidents. It has also been found to be superior to more complex decision methods (McCammon and Hägeli (2007)). A similar finding has emerged from studies of asset prices. They too are drawn from a fat-tailed distribution. When investing across N assets, the Merton-Markowitz portfolio strategy would weight by risk and return. A far simpler strategy would equally-weight all assets – a 1/N rule. In out-of-sample trials, the 1/N rule outperforms complex optimising alternatives, including Merton-Markowitz (DeMiguel et al (2007)). Indeed, Markowitz himself pursued a 1/N, rather than Markowitz, strategy when investing for retirement. (d)  Small samples and simple rules  The choice of optimal decision-making strategy depends importantly on the degree of uncertainty about the environment – in statistical terms, model uncertainty. A key factor determining that uncertainty is the length of the sample over which the model is estimated.
In these past 15 years, the Norwegian economy has been exposed to different types of shocks. The supply side has been influenced by increased labour immigration following EU enlargement in 2004. The legacies from the financial crisis have posed challenges that monetary policy has had to address. And not least, the Norwegian economy has had to contend with wide fluctuations in the terms of trade. Chart: Performance Inflation targeting has performed well over the past 15 years taken as a whole. When inflation targeting was introduced, inflation had already come down after years at an elevated level and has since been low and relatively stable. At the same time, monetary policy has helped to moderate fluctuations in the real economy. Flexible inflation targeting has functioned well. The monetary policy framework has provided sufficient flexibility to address the shocks that have hit the economy. LONG-TERM INTEREST RATES HAVE FALLEN Chart: International interest rates In recent years, monetary policy has faced a new challenge in many countries. The interest rate level that is consistent with balanced developments in the economy has fallen. This is reflected in the low level of global interest rates. The decline in real interest rates has been particularly marked over the past 15–20 years. In 2001, when inflation targeting in Norway was adopted, real long-term interest rates were around 3 percent. Now, the same interest rates are around zero. Chart: Forces driving the fall in the global real interest rate The causes of the decline in interest rates are complex.