Is 'behavioral economics' not related to behavior?

[ccgoal]

I would like to hear you guys' opinion on behavioral economics (BE). Though under the name of behavioral, I see little difference between BE and Neo-classical style in terms of the ability to solve complicated optimization problem of agents. (For example, say, in Laibson's hyperbolic discounting paper). I think this point is also emphasized in one of Rubinstein's working paper.

I guess one of the reasons it to get published in mainstram journals using such math. But other than that, do you think it's really necessary to use math like this just to describe the real behavior, which is simple and random in most cases (I think)?

[allinwonder]

Being related to behavior does not necessarily mean it cannot be math heavy.

Nowadays even psychology is math intensive. (although I doubt its necessity)

[Chicunomics]

In a lot of these behavioral models, the way they basically proceed is to identify (from experiments/the psychology literature) certain behavioral biases or anomalies that arise in decision making, and then formalize these into models of consumer choice. I guess it's just generally sticking within the broader methodology of economics which is to use mathematics as a tool to ensure that the logic is solid and that the conclusions are rigorous. So really, the focus as distinct from other fields is drawing on observed behavior to enrich models, rather than simply to describe what people do (which is I guess more the domain of other disciplines, i.e., psychology -- though apparently even that's going mathematical from the post above mine...!)

[economics]

yes, behavioral economics needs math.

it's not psychology - if it were psychology, we wouldn't necessarily need math to model behavior.

but it's behavioral economics - the goal of which is to *integrate* psychological insights into economic models. therefore, in order for BE to be successful within the economics literature, it must show how existing models can be twisted to incorporate psychological realities, which then lead to counterintuitive (from the neoclassical standpoint) implications and/or can explain empirical behavior that is at odds with neoclassical predictions.

you will see that the most successful behavioral stuff has been formulated in a way that fits existing models. the laibson things are one example, where you take an existing problem (dynamic optimization) and add some fun component (the beta) into the problem and can explain a lot of stuff.

the point in such models is not the explain psychology - we aren't psychologists. instead, the point is to incorporate some psychological patterns into our models. laibson doesn't claim to know why people are impatient - but he says they are in many cases, and he proposes to add the beta as a very crude approximination of this pattern. and in turns out that such an augmented model can have high explanatory power.

however, from a psychological standpoint, it's merely descriptive, and such models don't explain what's actually going on in people's brains. but that suffices for us. we don't model psychology, but we adapt our models in order to make some statements that take impatience into account. therefore, since bahavioral economics supplements economics with psychology, we need math to make it salient to economics...

my 2 cents.

[YoungEconomist]

Originally Posted by ccgoal

Is 'behavioral economics' not related to behavior?

In the words of David Henderson, "All economics is behavioral." He hates the term, since all economics is about behavior.

[allinwonder]

Originally Posted by economics

yes, behavioral economics needs math.

it's not psychology - if it were psychology, we wouldn't necessarily need math to model behavior.

but it's behavioral economics - the goal of which is to *integrate* psychological insights into economic models. therefore, in order for BE to be successful within the economics literature, it must show how existing models can be twisted to incorporate psychological realities, which then lead to counterintuitive (from the neoclassical standpoint) implications and/or can explain empirical behavior that is at odds with neoclassical predictions.

you will see that the most successful behavioral stuff has been formulated in a way that fits existing models. the laibson things are one example, where you take an existing problem (dynamic optimization) and add some fun component (the beta) into the problem and can explain a lot of stuff.

the point in such models is not the explain psychology - we aren't psychologists. instead, the point is to incorporate some psychological patterns into our models. laibson doesn't claim to know why people are impatient - but he says they are in many cases, and he proposes to add the beta as a very crude approximination of this pattern. and in turns out that such an augmented model can have high explanatory power.

however, from a psychological standpoint, it's merely descriptive, and such models don't explain what's actually going on in people's brains. but that suffices for us. we don't model psychology, but we adapt our models in order to make some statements that take impatience into account. therefore, since bahavioral economics supplements economics with psychology, we need math to make it salient to economics...

my 2 cents.

Also we need experiments to test its validity.

[nas-83]

Kahneman and Tversky were both psych PhDs...

[Golden Rule]

Originally Posted by economics

laibson doesn't claim to know why people are impatient

true, though he's working on it i.e. getting into neuroeconomics.

And behavioral economists would not agree with the OP that these deviations from rationality are purely random -- hence the title of Dan Ariely's book, "Predictably Irrational."

[ZomgRogged]

Behavioral economists are looking for answers to why people behave in ways neo classical theory would call irrational. They've made some nice strides in GT, predicting experimental results much better than Nash without totally throwing away standard GT.

[ccgoal]

Thanks, you guys! I can see people almost back up the validity of economic modelling since it indeed is the sign of economics.

Originally Posted by economics

yes, behavioral economics needs math.

it's not psychology - if it were psychology, we wouldn't necessarily need math to model behavior.

but it's behavioral economics - the goal of which is to *integrate* psychological insights into economic models. therefore, in order for BE to be successful within the economics literature, it must show how existing models can be twisted to incorporate psychological realities, which then lead to counterintuitive (from the neoclassical standpoint) implications and/or can explain empirical behavior that is at odds with neoclassical predictions.

you will see that the most successful behavioral stuff has been formulated in a way that fits existing models. the laibson things are one example, where you take an existing problem (dynamic optimization) and add some fun component (the beta) into the problem and can explain a lot of stuff.

the point in such models is not the explain psychology - we aren't psychologists. instead, the point is to incorporate some psychological patterns into our models. laibson doesn't claim to know why people are impatient - but he says they are in many cases, and he proposes to add the beta as a very crude approximination of this pattern. and in turns out that such an augmented model can have high explanatory power.

however, from a psychological standpoint, it's merely descriptive, and such models don't explain what's actually going on in people's brains. but that suffices for us. we don't model psychology, but we adapt our models in order to make some statements that take impatience into account. therefore, since bahavioral economics supplements economics with psychology, we need math to make it salient to economics...

my 2 cents.

However, I have one question that's been puzzling for a long time. Is there any research that shows the relationship between the (neo-classical) modelling and the actual behavior? By this I mean on the one hand we make our decisions in the real world almost doing no calculations (Bayes Rule, complicated probability and so on), while on the other hand, in economic models, each step is math intensed. Without such connection, how can the results of researches that build on these models with smart agents (even for many BE models as mentioned) be reliable? So far, I can only recall John List'
s paper on the comparison between Neoclassical and Prospect theory in the field showing that for experienced subjects neoclassical theory works well.