Much of economic theory is developed with one very simple guiding principle: People pursue goals. They may do so consciously or unconsciously. I think the following (thought) experiment demonstrates that human behavior is not entirely unpredictable, that in some cases there are some very simple principles that can explain a fair amount of behavior, and at the same time demonstrates why economic theory will almost never provide perfect predictions.
Consider how you typically go to work, to school, or to the university from your home. In fact, go to google maps and put in the address of your destination (work, school, or uni). Then click on “directions” and enter your home address. Choose your chosen mode of transport: walk, bike, drive, or possibly (if google maps covers this for you) public transport. Then, ideally, put in the time and day at which you usually make this trip.
I would like you to look at the route that google maps recommends to you, as well as the (I usually get two) alternative routes that google maps also suggests. Please note down the amount of time that google maps says that you will spend on this route. I would then like you to manually enter the route you actually typically take. Now write down the amount of time that google maps says that you will spend on your route.
Now answer the following questions: Is your chosen route a) the same as google maps’ suggested route? b) the same as one of google maps’ alternative suggestions? c) very similar to one of these routes? d) quite different from any of these routes?
I have one more question: How much longer does your actual route take (according to google maps) than the route suggested by google maps?
Ah yes, one last question: How many routes do you have at your disposal?
I have asked students these questions in my previous two classes and got very similar answers on both occasions. Here are the numbers from the first class. Of 244 responses, 45.5% (111) state that they chose exactly the route google recommends, 13.5% (33) state that they choose one of the two or so other routes google recommends, 27% (66) state that they choose a route very similar to the ones google recommends, and the remaining 13.9% (34) state that they choose quite a different route.
For the second question, of 216 responses, 22.2% (48) state that their own route is faster than the best google maps route, 48.6% (105) state that they require between 0 and 10% more time, 13.9% (30) require between 10 and 20% more time, 6% (13) require between 20 and 30% more time, and then the remaining few require more than 30% more time (2.3% state they need more than 100% more time).
For the last question, of 223 responses, 6.3% (14) say “one” route, 36.3% (81) say “a few”, 28.3% (63) say “some”, 19.3% (43) say “many”, and 9.9 (22) say “very many”.
Of course, the last question was rather vague and this vagueness allowed me to trick you a bit. In principle, you have of course an infinite number of possible routes to go from your home to work. You can go from your home in Graz to your Uni in Graz via Vienna. You can go all around the world, you can ziz-zag a lot, you can do loops, et cetera. Most people do none of this. According to my students’ responses, roughly 85% of them take a route that is at most 20% longer than the best route according to google.
So, given the infinite possibilities, it is pretty remarkable that google maps is able to “predict” 45% of all of students’ actual routes exactly and is able to predict the time it takes for the students to get from A to B mostly within at most a 20% error band. What is behind google maps’ “predictions”? It is the simple idea that people would like to get from A to B in as little time as possible. In fact, 22% of students had even claimed that they could beat google maps’ best time by taking an even better route.
What have we learned from this? One, people have goals and pursue these goals, sometimes maybe not even consciously. In the present context the students’ primary goal seems to have been to waste as little time as possible on their way to the university. Second, if an analyst understands the goals that people have, this analyst is able to predict human behavior reasonably well. Third, this prediction is not perfect. The reason for this may be at least two things: people have other goals as well (such as being safe on their way to work, or perhaps they care about the beauty or pollution level of their way to work), and people are not machines and they can make “mistakes” or have “whims” of the moment. All this also gives you a first idea about the accuracy of economic “laws”. Most of these are not precise “laws” as some of the laws of the natural sciences may be, but there are clear “patterns” of behavior or “regularities” that we can understand to a reasonable extent.
One of the consequences of the “fact” that most people try to minimize the loss of time is that whenever there are multiple queues for the same thing (such as cars in multiple lanes, or shoppers with their trollies at supermarket cashier points) typically all queues are roughly equally long. And if one queue is much shorter than another then there is typically a “technical” reason for this such as a very full supermarket trolley in one queue or one lane is also for turning left (with the possibility of delay if there is oncoming traffic).
This is split into two videos (In German):