Now we are ready to talk about the main results and the [UNKNOWN]
and Robinson's paper on the effective property rights on economic
development.
Here in the table four titled IV, instrumental variables regressions,
they've got three panels.
A, B and C, and then eight or nine columns rather, one through nine,
down here in panel C it's title ordinary least squares, they say
in the notes the dependent variable and columns one through eight
is log GDP per ca-pita in 1995, so that's our outcome variable,
GDP per capita.
Over here these are the right hand side variables, or our explanatory
variables.
So here in the first column, labelled based sample, we've got a
coefficient of 0.52 on average protection against expropriation
risk, property rights.
So this
is just telling us the regression that we looked at from before,
that in the data there is a positive correlation between having
strong property rights and having high GDP.
It's not telling us the causal effect.
So they have included it here for comparisons to the actual causal
effects they show in panel A.
In panel B they show the first stage for average protection against
expropriation risk, and that's our measure of property rights, that's
our treatment variable.
So these are the first stage regression that we talked about
in earlier modules.
So here in the first column
they're showing the correlation between the instrument log European
settler mortality and the treatment variable.
Average protection against expropriation risk and we see that there
is a negative co efficient -0.61 and this in parentheses that's
the standard error
so we could use that to construct a confidence interval for this
point estimate of the co-efficient and we'd find that this is a
statistically significant estimate, it is not zero.
So we see that the relevance assumption holds in the data.
There is a co-relation between the instrument and the treatment.
So relevance holds now we are ready to see the main result
that's right here this first column in the first panel 0.94 so panel
A is labelled two stage least squares remember that's the key word for
instrumental variables analysis.
So here we're looking at the coefficient on average protection against
expropriation risk and that's 0.94, and this is our treatment variable,
and our outcome variable here is log GDP per capita that's what
it said in the note, so this is telling us the effect, the true
causal effect of our treatment on our outcome.
If we did a compensatable for this number using this standard
here in parenthesis, we'd see that this point estimate is statistically
significantly not zero, it's positive.
So we see that there is a true causal effect of property rights
on economic development, that's the main result in this paper this
number right here is computed using instrumental variables analysis.
Now all the rest of this columns are just doing different robustness
checks to make sure that this number isn't explained away by other
possible theories like maybe geography matters.
We talked about that in the regression module so they're going to
include variables like latitude and what continent you are on in
other specifications like over here and they are going to see that
the coefficient on the treatment variable is still positive and
statistically significant among all of their specifications.
So that's the main results in this paper they find that property
rights actually do have a colossal effect on economic development
by using instrumental variable analysis where their instruments
is log European settler mortality.
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