Too few people are aware that empirical results in economic policy debates are often only approximations of reality.

Too few people are aware that empirical results in economic policy debates are often only approximations of reality.

In my contribution I would like to talk about the importance of empirical results in economic policy debates. Often these results are viewed as “golden currency” and seemingly precise results are treated as facts. However, many of these results are based on assumptions and models and are, at best, approximations of reality. The economy today is probably not suffering from too few, but from too many numbers and statistics.

An example of how equality can be measured is the Gini coefficient, which measures income distribution. This fluctuates between 0 and 1 and shows whether income is distributed absolutely equally or absolutely unequally. However, the Gini coefficient is a construct with weaknesses and there are different ideas about equality.

It is important to realize that many important values ​​such as happiness, freedom or security are difficult to quantify due to their complexity. In addition, averages often say little about the actual range and suggest a level of precision that is not present. Rankings should be viewed with caution, especially when the gaps are small.

The financial markets and economic policy have developed too much trust in models and numbers. It would be better to be “approximately right” rather than precisely wrong. John Maynard Keynes' dictum “roughly right than precisely wrong” should be taken into account in order not to fall into the trap of believing in numbers.

The impact of these findings on the market and the financial industry is diverse. An excessive focus on numbers and statistics can lead to an incorrect assessment of the situation. Companies and investors should be aware that these data are only approximations of reality and may be subject to uncertainty. It is important to critically question models and numbers and take a holistic perspective.

According to a report by www.nzz.ch, it is necessary to recognize the advantages and disadvantages of quantitative data in economics. While numbers and statistics are important decision-making tools, they should be viewed with caution and humility. Focusing too much on this data can lead to a loss of the bigger picture and have long-term negative effects. Therefore, decision-makers in the financial industry should not base their assessments exclusively on quantitative data, but also take qualitative aspects into account.

Source: https://www.nzz.ch/meinung/kommentare/die-oekonomie-als-forschung-leidet-unter-zu-vielen-zahlen-ld.1391358