The Great Divide Between Cause and Effect

The Hutch Report

Cause and effect is the principle of causality, establishing one event or action as the direct result of another or where the cause is partly responsible for the effect, and the effect is partly dependent on the cause. 

We often look towards correlations in order to identify and resolve cause and effect relationships and there are so many. Is obesity (the effect) directly related to the consumption of fast food (the cause)? Or is obesity related to the fact that people with limited disposable income can only afford to eat at fast food establishments? Or is obesity the result of poor education that leads to poor paying jobs that result in limited disposable income which provokes people to choose affordable fast food outlets?

There is a further complication in that, “Correlation does not imply causation.” Just because two trends seem to fluctuate in tandem, doesn’t prove that they are meaningfully related to one another. As an example we can look at the correlation between the per capita consumption of chicken to total US crude oil imports.  

The Hutch ReportCorrelation is something which we think, when we have limited information at our disposal. So the less the information we have the more we are forced to observe correlations. Similarly the more information we have the more transparent things will become and the more we will be able to see the actual casual relationships. 

As humans, we generate and evaluate explanations in a very spontaneous manner. In fact, to do so is fundamental to our sense of understanding. We don’t like uncertainty and ambiguity. From an early age we respond to issues of uncertainty by spontaneously generating plausible explanations. In our rush for an explanation, we tend to produce fewer hypotheses and search less thoroughly for information. We are more likely to form judgments out of first impressions and fail to account enough for situational variables. This happens very often amongst economists and “may” explain why they are so often wrong in their conclusions. 

As an example, central banks believed that accommodative monetary policies would encourage banks to extend credit to borrowers. Available information regarding lending decisions pre- and post- negative interest rate policy (NIRP), however, indicates that banks did not increase their marginal propensity to lend. Instead, the suppression of rates on behalf of the central banks narrowed banks’ net interest margins and thereby discouraged credit expansion. Loan growth in Europe and Japan has remained weak and, despite the significant rally in global equity markets, bank stocks did not fare better after the arrival of NIRP. This example in itself is vastly over simplified as there are a number of issues that may have played a part in coming to this conclusion. 

So if this is really the case where we, as individuals, tend to jump to conclusions, spontaneously generate plausible explanations or find correlations where there are none, how can we be certain that our leaders, bankers, managers, the media etc, are not doing the same thing?

The general public is provided little to no insight into the detailed thought processes that go into many governmental decisions. How do we know our officials have considered all the angles and come to the best decision possible? All we are given is their decision and a political sound bite designed to provide the appearance of an explanation. We buy into these explanations because they provide us with a sense of certainty. 

If we look towards current events, we see that we are now experiencing an unprecedented level of income inequality in the country but what is the cause of this effect? It forces us to go back into a vicious cycle of thought where we once again are prone to jump to conclusions, explanations with limited information etc. 

To better understand the complexity of these issues you can try coming to your own conclusion with the use of the Five Whys technique. The five whys is an iterative interrogative technique used to explore the cause-and-effect relationships underlying a particular problem. As an example we have taken the recent riots and just brainstormed through the exercise. This doesn’t mean to say we have come to the proper conclusion or have exhausted all the whys, but you can see how finding causality can quickly become a complex issue. 

Effect: Riots

Why? – People are frustrated and are lashing out

Why? – They lack opportunities, equal opportunities and income / they are drowning in debt / injustice

Why? – Available jobs pay low salaries / expenses are increasing / fewer job opportunities / people living beyond their means / inequalities within the justice system

Why? – Increased productivity through technology has led to layoffs / poor levels of education

Why? – Management compensation is linked to increased shareholder value / Decrease costs and increase profits anyway possible / broken education system

If anything, this should persuade you to look deeper into our current state of affairs, question everything you hear and not to assume the explanations that you are being fed are anymore accurate than what you could conclude on your own. The divide between cause and effect is greater than you can imagine.