datasets

Implementation of selected high-dimensional statistical and
econometric methods for estimation and inference. Efficient estimators and
uniformly valid confidence intervals for various low-dimensional causal/
structural parameters are provided which appear in high-dimensional
approximately sparse models. Including functions for fitting heteroscedastic
robust Lasso regressions with non-Gaussian errors and for instrumental variable
(IV) and treatment effect estimation in a high-dimensional setting. Moreover,
the methods enable valid post-selection inference and rely on a theoretically
grounded, data-driven choice of the penalty.
Chernozhukov, Hansen, Spindler (2016) <arXiv:1603.01700>.

Martin Spindler

High-Dimensional Metrics

Victor Chernozhukov

Christian Hansen

Philipp Bach

BLP function

<dl>
<dt>model.name</dt>
<dd>model name</dd><dt>model.id</dt>
<dd>model id</dd><dt>firm.id</dt>
<dd>firm id</dd><dt>cdid</dt>
<dd>cdid</dd><dt>id</dt>
<dd>id</dd><dt>price</dt>
<dd>log price</dd><dt>mpg</dt>
<dd>miles per gallon</dd><dt>mpd</dt>
<dd>miles per dollar</dd><dt>hpwt</dt>
<dd>horse power per weight</dd><dt>air</dt>
<dd>air conditioning (binary variable)</dd><dt>space</dt>
<dd>size of the car</dd><dt>share</dt>
<dd>market share</dd><dt>outshr</dt>
<dd>share s0</dd><dt>y</dt>
<dd>outcome variable defined as log(share) - log(outshr)</dd><dt>trend</dt>
<dd>time trend</dd>
</dl>

Format

BLP data set — BLP

<dl>
<dt>model.name</dt>
<dd>model name</dd>

<dt>model.id</dt>
<dd>model id</dd>

<dt>firm.id</dt>
<dd>firm id</dd>

<dt>cdid</dt>
<dd>cdid</dd>

<dt>id</dt>
<dd>id</dd>

<dt>price</dt>
<dd>log price</dd>

<dt>mpg</dt>
<dd>miles per gallon</dd>

<dt>mpd</dt>
<dd>miles per dollar</dd>

<dt>hpwt</dt>
<dd>horse power per weight</dd>

<dt>air</dt>
<dd>air conditioning (binary variable)</dd>

<dt>space</dt>
<dd>size of the car</dd>

<dt>share</dt>
<dd>market share</dd>

<dt>outshr</dt>
<dd>share s0</dd>

<dt>y</dt>
<dd>outcome variable defined as log(share) - log(outshr)</dd>

<dt>trend</dt>
<dd>time trend</dd>


</dl>

BLP: BLP data set

Description

Arguments

Format

Details

References

Examples