# The golden ratio and its meaning in the economy

Bert de Groot, Professor of Governance and Strategic Investment Policy at Erasmus School of Economics, recently appeared on Canadian podcast show Tech Insights to discuss his finding of the golden ratio in the interrelationship of economic subcycles. It took him ten years to find the golden ratio. Was he surprised, how did he find it and what should we take away from this finding?

## A surprising finding

In the podcast, De Groot tells that he was surprised to see the golden ratio appear in the economy: this is the first time that it has an application in the economy. Normally, the golden ratio would be seen in biology and astrology, systems which aren’t made by people. De Groot draws the following conclusion: it is time to think about a dynamic system of the economy, in which every submarket fits.

## Tools for analysis

To detect cycles, Fourier analysis is a very useful tool and at the core of De Groot’s analysis. The idea of the analysis is that a time series (a series of observations of a variable over a given period of time) can be decomposed into cosine waves. However, there is a problem. The analysis is not useful when the data shows irregular trends (non-stationarity). This is the case with lots of data, including the data of this research. De Groot uses a Generalized Autoregressive Conditional Heteroskedasticity (GARCH) model to account for this obstacle. This makes the data less irregular, still preserving the cyclic behaviour of the original data. After performing these two tests, De Groot uses an algorithm to figure out which cycles are prominent. Finally, a trend-cycle is estimated to describe the amplitudes and phases of the economic cycles.

## Results

The models confirm that the cycles that were found, strongly correlate with the time series data. Almost all the estimates turn out to be statistically significant at a level of 5%. The detected cycles from the sample can describe swings in GDP growth rates of up to 5 percentage points. The models can be useful to predict future turning points of an economy as well: by letting the model forecast a part of the data that is left out of the sample, but is readily available, it is possible to assess whether the model actually forecasts what happens (out-of sample estimates). “The results indicate that in each economy, between two and five cycles are present. Cycles with a length between 5–6 years and between 9–10 years appear most frequently. Finally, De Groot has made an interesting observation, which contradicts the current notion on subcycles: “A meta-analysis on the detected cycle lengths reveals that the ratio between the lengths of consecutive cycles often closely matches the golden ratio.”