Economists
often use graphs to advance an argument about how the economy works. In other
words, they use graphs to argue about how one set of events causes another set
of events. With a graphs like the demand curve, there is no doubt cause and
effect. Because we are varying price and holding all other variables constant,
we know that change in the price of novels cause change in the quantity Emma
demands. Remember however that our demand curve came from a hypothetical
example. When graphing data from the real world it is often more difficult to
establish how one variable affects another.
The first
problem is that it is difficult to hold everything else constant when measuring
how one variable affects another. If we are not able to hold variables
constant, we might decide that one variable on our graph is causing changes in
the other variable when actually those change are caused by a third omitted
variable not pictured on the graph. Even if we have identified the correct two
variables to look at we might run into a second problem reverse causality. In
other words, we might decide that A causes B when in fact B causes A. The
omitted-variable and reveres-causality traps us to proceed with caution when
using graph to draw conclusions causes and effects.
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