Josh Angrist: What's the Difference Between Economics and Data Science?

♪ [music] ♪

- [Narrator] What's the difference
between econometrics

and data science?

- [Josh] I would say that
the principal difference

is the approach
to the problem of prediction.

Data scientists are often concerned

with curve-fitting type
approaches to prediction.

So any model that fits
the data well will do.

If it's past experience, we might
be interested in using that

to extrapolate to the future.

A lot of the data science
agenda is tied

to somebody's marketing problems.

You're trying to figure out
who will buy something,

who will take some action.

Econometrics, in my view,

deals with kind of
a harder class of problems.

Econometricians are more concerned
with causal relationships.

In other words,
if we manipulate something,

say, health insurance
or monetary policy,

what's the world going to look like
in response to that change?

We don't take it for granted that
the past is a good guide to that

because we understand that variation
and variable is associated

with lots of potential
confounding variables --

we would say other things
that are moving

that also perhaps affect outcomes.

The simple observed relationship
there is often misleading

because there are factors
that are not well controlled,

and we have in mind
that there is a research design

that involves more
than curve fitting.

In fact, we're fairly indifferent
to curve fitting in economics.

I think we want to know,
for example, whether it matters

if you go to an expensive
private college --

does that change your life course
in the form of higher earnings?

That's not really
a curve-fitting question,

that's a causal question.

♪ [music] ♪

- [Narrator] Ready
to master econometrics?

Click here to embark
on an educational journey

with Josh Angrist,
aka Master Joshway.

Or, if you'd like to watch more
from this interview series,

click here.

♪ [music] ♪