Maybe you’ve heard the age-old question, “Which came first, the chicken or the egg?” Rarely when someone quotes this paradox are they talking about actual chickens. This metaphorical question is meant to make us question our assumptions about causality, or which event caused another. Some might argue that the egg came first, while others might believe that to be a case of reverse causation; there had to be a chicken to lay an egg, after all.
The following article explores reverse causality, also known as reverse causation, which refers to a situation in a cause-and-effect relationship where the effect is erroneously thought to be the cause. Explore some examples and effects of reverse causation below.
Reverse Causation Definition
As earlier described, reverse causation is the false belief that event A causes event B to happen when the truth is that the reverse is true. Reverse causation—which is sometimes called reverse causality—typically occurs because someone notices that two things share a causal relationship (think the chicken and the egg), but they don't understand the order of causation.
It challenges the conventional direction of causality and suggests that the dependent variable is causing changes in the independent variable, rather than the other way around.
People also frequently confuse causal relationships for things that are correlated.
Correlation is a statistical relationship where two things are linked and move in coordination with each other.
Fig. 1 - Correlation does not imply causation: The crowing rooster does not cause the sun to rise.
Two things that are correlated may appear to share a causal relationship because they are clearly linked, but there is another relevant adage here: “Correlation does not imply causation.” This means that just because two things are connected does not mean that one causes the other.
For example, someone might argue that statistics showing higher levels of opioid addiction in lower socioeconomic areas prove that poverty causes addiction. While this might make sense at first pass, there is no way to prove this because the reverse could just as easily be true; addiction might be a contributing factor to poverty.
Causation is the exclusive connection where something causes another to happen. Correlation is not the same thing; it is a relationship where two things simply share a commonality but are not connected by causation. Causation and correlation are regularly confused because the human mind likes to identify patterns and will see two things that are closely related as being dependent on one another.
Repeatable positive correlations are typically evidence of causal relationships, but it’s not always easy to tell which event is causing which.
A positive correlation is a relationship between two things that move in the same direction. That is to say, as one variable increases, so does the other; and as one variable decreases, so does the other.
The Effects of Reverse Causation
The assumption that one thing depends on another simply because they are connected is a logical fallacy.
A logical fallacy is a failure in reasoning which results in an unsound argument. Like a crack in the foundation of an idea, a logical fallacy can be either so small you don’t even notice or so large that it can’t be ignored. Either way, an argument can’t stand on an idea that contains a logical fallacy.
Reverse causation is an informal fallacy—meaning it doesn’t have to do with the format of the argument—of questionable cause. Another term for this is non causa pro causa, which means non-cause for cause in Latin.
Reverse causation has applications in economics, science, philosophy, and more. When and if you identify an argument with a logical fallacy, you should discredit the entire argument because it is not based on sound logic. This can mean serious implications, depending on the subject and scenario.
For example, statistics show that people struggling with depression also smoke cigarettes. A doctor could conclude that smoking cigarettes causes depression, and simply recommend the patient stop smoking instead of prescribing anti-depressants or other helpful treatments. This could easily be a case of reverse causation, though, as people with depression may be more likely to smoke as a way to cope with their symptoms.
Reverse Causality Bias
Reverse causality bias occurs when the direction of cause-and-effect is mistaken, leading to incorrect conclusions. This can be a major issue in observational studies and can lead to misconceptions about the relationships between variables. Researchers need to be aware of the possibility of reverse causality bias and employ appropriate statistical techniques or study designs, such as longitudinal studies, to mitigate its potential effects.
Reverse Causation Synonym
As previously mentioned, reverse causation is also known as reverse causality. There are a few other terms you can use to communicate reverse causation:
Fig. 2 - Order is important; the horse must go before the cart for the cart to function properly.
Reverse Causation Examples
A classic example of reverse causality is the relationship between health and wealth.
- It is generally accepted that wealth leads to better health due to access to better healthcare and living conditions. However, reverse causality suggests that good health can lead to increased wealth as healthier individuals are often more productive.
- Another example involves education and income. While it's commonly believed that more education leads to higher income, reverse causality would suggest that higher income enables more education due to increased access to educational resources.
People may also call reverse causation “cart before the horse bias” because reverse causation is essentially like putting the cart before the horse. In other words, the effect is confused for the cause, which is the exact opposite of a functional scenario.
The following examples of reverse causality illustrate how easy it is to confuse causation in a situation where there is a connection between two things. Topics with an emotional element—such as politics, religion, or conversations involving children—are especially likely to result in reverse causation. This is because people become entrenched in a particular camp and can be so anxious to find any evidence to support their perspective that they might miss a logical fallacy in their argument.
Some statistics suggest that schools with smaller class sizes produce more "A" students. Many argue that is because smaller classes cause smarter students. However, after more research and a careful examination of the variables involved, this interpretation may be a mistake of reverse causation. It's possible that more parents with "A" students send their kids to schools with smaller class sizes.
While it's difficult to establish a definite causal connection on this topic—there are many variables to consider—it is definitely possible it is a simple case of reverse causation.
In the Middle Ages, people believed that lice caused you to be healthy because they were never found on sick people. We now understand that the reason lice were not present on sick people is because they are sensitive to even the slightest rise in temperature, and so lice did not like hosts with a fever.
Lice → healthy people
Sick people → inhospitable environment for lice
This is a true example of reverse causation. The truth about lice was the reverse of the common understanding of what lice do and how they affect human beings.
Children that play violent video games are more likely to act out violent behavior. So the belief may be that violent video games create violent behavior in children. But can we be sure the relationship is causal and not simply a correlation? Is it possible that children with violent tendencies prefer violent video games?
In this example, there is no measurable way to know for sure if the video games cause violent behavior or if the two are simply correlated. In this instance, it would be “easier” to blame violent video games for violence among children because parents could ban them from their homes, and even rally to ban them from the market. But it’s probable that there would not be a significant decrease in violent behavior. Remember, correlation does not imply causation.
Identifying Reverse Causality
There is no secret formula to test for reverse causation; identifying it is usually a matter of applying common sense and logic. For example, someone unfamiliar with windmills might see one spinning quickly, notice the wind blowing harder, and believe that the windmill is creating the wind. Logic would suggest that the opposite is true because the wind can be felt no matter how close you are to the windmill, so the windmill cannot be the source.Note: Subjective language. Please rephrase
There is no official way to test for reverse causality, but there are a few questions you can ask yourself to determine if it’s a possibility. If you believe that thunder (event A) causes lightning (event B), for example, ask yourself the following questions:
Is it possible that it can lightning (B) before you hear thunder (A)?
If the answer is yes, then it's potentially a case of reverse causation.
Can I definitively rule out the possibility that lightning (B) causes thunder (A)?
If the answer is yes, then it's not a case of reverse causation.
Do I find that changes in lightning (B) can happen before thunder (A) occurs?
If the answer is yes, then it's potentially a case of reverse causation.
Once you have answered these questions, you can either rule out reverse causation or identify it in the argument you’re considering.
Reverse Causality and Simultaneity
Simultaneity and reverse causality are two concepts that are so closely related that they can easily be confused.
Simultaneity is also known as confounding causation, or the Latin term cum hoc, ergo propter hoc, which means "with this, therefore because of this." All this means two things happen at the same time, which leads some to mistakenly believe one caused the other to happen.
Two events that share a simultaneous relationship may appear as an instance of reverse causation, or even regular causation, because of the way they are connected.
For example, the “Matthew effect” refers to the belief that intellects and professionals with higher status tend to receive more credit for their endeavors than those of lower status with the same achievements. More credit gains the higher-status intellect additional recognition and awards. As a result, the higher status becomes emphasized and creates a cycle of advantages from which the lower-status intellect is excluded.
In this instance, there is a self-feeding loop; more status generates more recognition, which generates more status.
The bottom line is that when two things appear to be connected, it is necessary to investigate further to determine the nature of their relationship rather than assume causation.
Reverse Causation - Key Takeaways
- Reverse causation is the false belief that event A causes event B to happen when the truth is that the reverse is true.
- People tend to mistake things that are correlated for things that share a causal connection.
- Reverse causation is an informal fallacy of questionable cause.
- Reverse causation is also called reverse causality, backward causation, or retrocaustion (causality).
- Simultaneity and reverse causality are two concepts that are so closely related that they can easily be confused.
- Simultaneity is when two things happen at the same time, which leads some to mistakenly believe one of them caused the other to happen.
Explanations 
Exams 
Magazine 
