<?xml version="1.0" encoding="UTF-8"?>
 <rdf:RDF xmlns="http://purl.org/rss/1.0/" xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#" xmlns:content="http://purl.org/rss/1.0/modules/content/" xmlns:taxo="http://purl.org/rss/1.0/modules/taxonomy/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:cc="http://web.resource.org/cc/" xmlns:syn="http://purl.org/rss/1.0/modules/syndication/" xmlns:admin="http://webns.net/mvcb/">
  <channel rdf:about="http://pinboard.in">
    <title>Pinboard (sechilds)</title>
    <link>https://pinboard.in/u:sechilds/public/</link>
    <description>recent bookmarks from sechilds</description>
    <items>
      <rdf:Seq>	<rdf:li rdf:resource="http://www.danielmsullivan.com/econtools/"/>
	<rdf:li rdf:resource="https://twitter.com/johngraves9/status/1006203757691064320"/>
	<rdf:li rdf:resource="http://personal.lse.ac.uk/YoungA/ConsistencyWithoutInference.pdf"/>
	<rdf:li rdf:resource="http://www.stata.com/meeting/chicago16/"/>
	<rdf:li rdf:resource="http://davegiles.blogspot.com/2011/08/beware-of-econometricians-bearing.html"/>
	<rdf:li rdf:resource="http://www.env-econ.net/2014/09/regression-economics-and-theory-crafting.html"/>
	<rdf:li rdf:resource="http://worthwhile.typepad.com/worthwhile_canadian_initi/2014/03/why-do-people-get-so-worked-about-linear-probability-models.html"/>
	<rdf:li rdf:resource="http://andrewgelman.com/2013/08/07/i-doubt-they-cheated/"/>
	<rdf:li rdf:resource="http://errorstatistics.com/2012/12/24/13-well-worn-criticisms-of-significance-tests-and-how-to-avoid-them/"/>
	<rdf:li rdf:resource="http://davegiles.blogspot.com/2012/10/dancing-with-econometricians.html"/>
	<rdf:li rdf:resource="http://www.econometricsbysimulation.com/2012/07/bootstrapped-draws-for-simulating.html"/>
	<rdf:li rdf:resource="http://real-estate-and-urban.blogspot.ca/2012/07/mark-thoma-reminds-me-of-something-art.html"/>
	<rdf:li rdf:resource="http://davegiles.blogspot.ca/2012/07/concentrating-or-profiling-likelihood.html"/>
	<rdf:li rdf:resource="http://www.econometricsbysimulation.com/2012/07/delta-method.html"/>
	<rdf:li rdf:resource="http://blogs.reuters.com/felix-salmon/2012/07/10/how-economists-get-tripped-up-by-statistics/"/>
	<rdf:li rdf:resource="http://davegiles.blogspot.com/2012/07/decline-and-fall-of-power-curve.html"/>
	<rdf:li rdf:resource="http://www.econometricsbysimulation.com/2012/06/generating-random-variables-drawn-from.html"/>
	<rdf:li rdf:resource="http://www.econometricsbysimulation.com/2012/05/value-added-modelling-stata-simulation.html"/>
	<rdf:li rdf:resource="http://www.econometricsbysimulation.com/2012/06/estimating-vams-value-added-methods.html"/>
	<rdf:li rdf:resource="http://www.econometricsbysimulation.com/"/>
	<rdf:li rdf:resource="http://economistsview.typepad.com/economistsview/2006/09/if_at_first_you.html"/>
	<rdf:li rdf:resource="http://www.env-econ.net/2012/06/whither-t-192.html"/>
	<rdf:li rdf:resource="http://stats.stackexchange.com/questions/24263/model-stability-in-cross-validation-of-regression-models?atw=1"/>
	<rdf:li rdf:resource="http://davegiles.blogspot.com/2012/06/another-gripe-about-linear-probability.html"/>
	<rdf:li rdf:resource="http://davegiles.blogspot.com/2012/05/complex-survey-data-in-econometrics.html"/>
	<rdf:li rdf:resource="http://davegiles.blogspot.com/2012/05/bayes-estimators-loss-functions-and-j-m.html"/>
	<rdf:li rdf:resource="http://davegiles.blogspot.ca/2012/04/bayesian-consumption-function.html"/>
	<rdf:li rdf:resource="http://socserv.mcmaster.ca/racine/ECO0301.pdf"/>
	<rdf:li rdf:resource="http://codeandculture.wordpress.com/2012/03/15/control-for-x/"/>
	<rdf:li rdf:resource="http://andrewgelman.com/2011/07/descriptive_sta/"/>
	<rdf:li rdf:resource="http://www.env-econ.net/2011/10/an-example-of-utility.html"/>
	<rdf:li rdf:resource="http://worthwhile.typepad.com/worthwhile_canadian_initi/2011/10/in-praise-of-cookbook-econometrics.html"/>
	<rdf:li rdf:resource="http://worthwhile.typepad.com/worthwhile_canadian_initi/2011/10/five-steps-to-cleaner-data.html"/>
	<rdf:li rdf:resource="http://www.nber.org/minicourse3.html"/>
	<rdf:li rdf:resource="http://www.npwrc.usgs.gov/resource/methods/statsig/stathyp.htm"/>
	<rdf:li rdf:resource="http://www.estat.us/id38.html"/>
	<rdf:li rdf:resource="http://www.stat.columbia.edu/~cook/movabletype/archives/2005/03/the_secret_weap.html"/>
      </rdf:Seq>
    </items>
  </channel><item rdf:about="http://www.danielmsullivan.com/econtools/">
    <title>Package overview — econtools 0.1 documentation</title>
    <dc:date>2018-09-02T15:05:02+00:00</dc:date>
    <link>http://www.danielmsullivan.com/econtools/</link>
    <dc:creator>sechilds</dc:creator><description><![CDATA[econtools is a Python package for
econometrics and data manipulation. Download or clone econtools here and run the setup.py script: Python 2.7 or 3 (tested with 2.7 and 3.6) Pandas and its dependencies (Numpy, etc.) Scipy and its dependencies Nose (if you want to run the tests) Built with Sphinx using a theme provided by Read the Docs .]]></description>
<dc:subject>Python econometrics economics</dc:subject>
<dc:identifier>https://pinboard.in/u:sechilds/b:73c4d9a8abb6/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:sechilds/t:Python"/>
	<rdf:li rdf:resource="https://pinboard.in/u:sechilds/t:econometrics"/>
	<rdf:li rdf:resource="https://pinboard.in/u:sechilds/t:economics"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="https://twitter.com/johngraves9/status/1006203757691064320">
    <title>John Graves on Twitter: I feel like every time I see a study applying machine learning in health Econ context, standard approaches (OLS, logit) do nearly if not equally as well. Is anyone writing the definitive article on the contexts/situations where ML</title>
    <dc:date>2018-06-13T11:41:15+00:00</dc:date>
    <link>https://twitter.com/johngraves9/status/1006203757691064320</link>
    <dc:creator>sechilds</dc:creator><description><![CDATA[@johngraves9: I feel like every time I see a study applying machine learning in health Econ context, standard approaches (OLS, logit) do nearly if not equally as well. Is anyone writing the definitive article on the contexts/situations where ML adds most value over well specified OLS/logit?


]]></description>
<dc:subject>economics econometrics machine_learning</dc:subject>
<dc:identifier>https://pinboard.in/u:sechilds/b:54735057499f/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:sechilds/t:economics"/>
	<rdf:li rdf:resource="https://pinboard.in/u:sechilds/t:econometrics"/>
	<rdf:li rdf:resource="https://pinboard.in/u:sechilds/t:machine_learning"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="http://personal.lse.ac.uk/YoungA/ConsistencyWithoutInference.pdf">
    <title>http://personal.lse.ac.uk/YoungA/ConsistencyWithoutInference.pdf</title>
    <dc:date>2017-11-18T14:44:11+00:00</dc:date>
    <link>http://personal.lse.ac.uk/YoungA/ConsistencyWithoutInference.pdf</link>
    <dc:creator>sechilds</dc:creator><description><![CDATA[I use the bootstrap to study a comprehensive sample of 1400 instrumentalvariables regressions in 32 papers published in the journals of the American Economic Association. IV estimates are more often found to be falsely significant and more sensitive to outliers than OLS, while having a higher mean squared error around the IV population moment. There is little evidence that OLS estimates are substantively biased, while IV instruments often appear to be irrelevant. In addition, I find that established weak instrument pre-tests are largely uninformative and weak instrument robust methods generally perform no better or substantially worse than 2SLS.

[PDF]]]></description>
<dc:subject>econometrics</dc:subject>
<dc:identifier>https://pinboard.in/u:sechilds/b:1f3576a35a84/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:sechilds/t:econometrics"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="http://www.stata.com/meeting/chicago16/">
    <title>2016 Stata Conference Chicago | Stata</title>
    <dc:date>2016-07-21T17:49:43+00:00</dc:date>
    <link>http://www.stata.com/meeting/chicago16/</link>
    <dc:creator>sechilds</dc:creator><description><![CDATA[Looking forward to seeing everyone in #Chicago for #Stata2016! Registration is still open  ]]></description>
<dc:subject>Stata2016 Chicago DataScience Economics Econometrics</dc:subject>
<dc:source>https://twitter.com/</dc:source>
<dc:identifier>https://pinboard.in/u:sechilds/b:45e64b3cb11e/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:sechilds/t:Stata2016"/>
	<rdf:li rdf:resource="https://pinboard.in/u:sechilds/t:Chicago"/>
	<rdf:li rdf:resource="https://pinboard.in/u:sechilds/t:DataScience"/>
	<rdf:li rdf:resource="https://pinboard.in/u:sechilds/t:Economics"/>
	<rdf:li rdf:resource="https://pinboard.in/u:sechilds/t:Econometrics"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="http://davegiles.blogspot.com/2011/08/beware-of-econometricians-bearing.html">
    <title>Econometrics Beat: Dave Giles' Blog: Beware of Econometricians Bearing Spreadsheets</title>
    <dc:date>2014-10-09T09:28:46+00:00</dc:date>
    <link>http://davegiles.blogspot.com/2011/08/beware-of-econometricians-bearing.html</link>
    <dc:creator>sechilds</dc:creator><dc:subject>data econometrics</dc:subject>
<dc:source>https://instapaper.com/</dc:source>
<dc:identifier>https://pinboard.in/u:sechilds/b:7c1d58dfce40/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:sechilds/t:data"/>
	<rdf:li rdf:resource="https://pinboard.in/u:sechilds/t:econometrics"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="http://www.env-econ.net/2014/09/regression-economics-and-theory-crafting.html">
    <title>Environmental Economics: Regression, Economics and Theory-Crafting</title>
    <dc:date>2014-09-09T16:17:31+00:00</dc:date>
    <link>http://www.env-econ.net/2014/09/regression-economics-and-theory-crafting.html</link>
    <dc:creator>sechilds</dc:creator><description><![CDATA[I apologize ahead of time for the rant that's ahead.  The rant is motivated by daily interactions with my colleagues who mostly have PhD's in statistics,…]]></description>
<dc:subject>regression econometrics</dc:subject>
<dc:source>https://instapaper.com/</dc:source>
<dc:identifier>https://pinboard.in/u:sechilds/b:79cfc4e4dd0e/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:sechilds/t:regression"/>
	<rdf:li rdf:resource="https://pinboard.in/u:sechilds/t:econometrics"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="http://worthwhile.typepad.com/worthwhile_canadian_initi/2014/03/why-do-people-get-so-worked-about-linear-probability-models.html">
    <title>Why do beginner econometricians get worked up about the wrong things?</title>
    <dc:date>2014-03-23T12:32:30+00:00</dc:date>
    <link>http://worthwhile.typepad.com/worthwhile_canadian_initi/2014/03/why-do-people-get-so-worked-about-linear-probability-models.html</link>
    <dc:creator>sechilds</dc:creator><description><![CDATA[> Econometrics is a journey. Logit and probit are just one step on the path towards enlightenment. Once one arrives at probit, and can calculate marginal effects with ease, another challenge awaits - bootstrapped standard errors, perhaps, or correction for sample selection bias. The ultimate goal - identification of causal relationships - may never be achieved - but we journey down the path nonetheless.]]></description>
<dc:subject>econometrics</dc:subject>
<dc:source>https://pinboard.in/</dc:source>
<dc:identifier>https://pinboard.in/u:sechilds/b:490ad56a82b6/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:sechilds/t:econometrics"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="http://andrewgelman.com/2013/08/07/i-doubt-they-cheated/">
    <title>I doubt they cheated « Statistical Modeling, Causal Inference, and Social Science Statistical Modeling, Causal Inference, and Social Science</title>
    <dc:date>2013-08-08T09:33:00+00:00</dc:date>
    <link>http://andrewgelman.com/2013/08/07/i-doubt-they-cheated/</link>
    <dc:creator>sechilds</dc:creator><description><![CDATA[As we’ve discussed on this blog at other times, many methodologists (especially, but certainly not only, in economics) have a naive belief that they should be using unbiased estimates (not recognizing that, in practice, unbiasedness at one point the analysis is achieved at the expense of averaging over some other dimension such as time), and it would seem that, the higher degree the polynomial correction, the lower the bias. In which case the four additional degrees of freedom required to ramp up from a linear to a 5th-degree adjustment are a small price to pay if you have a large or even moderate sample size.

And in this case, sure, the cubic polynomial looks ridiculous, but a linear fit would be even worse (as the authors found using their model-fit statistics). I’m guessing that the authors were doing what they thought was right and proper by choosing the best-fitting of these polynomials.

What if the result had been statistically significant with linear adjustment but not with a higher-degree polynomial? What would the authors have done? Would they have presented the statistically significant linear result and stopped there? I have no idea. But, given my impression of how economists think about regression discontinuity analysis, my guess is that, given the data the authors did see, that they did not do a specification search; they just did what they thought was the most kosher analysis possible.

Why this is important

If Chen et al. had violated the rules of the game (in this case, not by faking or improperly discarding data but by trying analysis after analysis in a search for statistical significance), this would be a problem, but it’s a containable problem. The rules are (relatively clear), and you’re not supposed to break them.

But I think the problem is worse than that. I think Chen et al. did what, under current doctrine, they were supposed to do: find a discontinuity and adjust using a high-degree polynomial. When the recommended analysis has such problems of face validity, that’s a different problem entirely.

As the (sometimes) great Michael Kinsley once said, in a different context, “the scandal isn’t what’s illegal, the scandal is what’s legal.”]]></description>
<dc:subject>econometrics regression_discontinuity</dc:subject>
<dc:source>https://pinboard.in/</dc:source>
<dc:identifier>https://pinboard.in/u:sechilds/b:bbd4216d6857/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:sechilds/t:econometrics"/>
	<rdf:li rdf:resource="https://pinboard.in/u:sechilds/t:regression_discontinuity"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="http://errorstatistics.com/2012/12/24/13-well-worn-criticisms-of-significance-tests-and-how-to-avoid-them/">
    <title>13 well-worn criticisms of significance tests (and how to avoid them) « Error Statistics Philosophy</title>
    <dc:date>2012-12-24T23:28:35+00:00</dc:date>
    <link>http://errorstatistics.com/2012/12/24/13-well-worn-criticisms-of-significance-tests-and-how-to-avoid-them/</link>
    <dc:creator>sechilds</dc:creator><dc:subject>statistics statistics:philosophy econometrics</dc:subject>
<dc:source>https://instapaper.com/</dc:source>
<dc:identifier>https://pinboard.in/u:sechilds/b:6cdf16d92981/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:sechilds/t:statistics"/>
	<rdf:li rdf:resource="https://pinboard.in/u:sechilds/t:statistics:philosophy"/>
	<rdf:li rdf:resource="https://pinboard.in/u:sechilds/t:econometrics"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="http://davegiles.blogspot.com/2012/10/dancing-with-econometricians.html">
    <title>Econometrics Beat: Dave Giles' Blog: Dancing With the Econometricians</title>
    <dc:date>2012-10-07T18:54:23+00:00</dc:date>
    <link>http://davegiles.blogspot.com/2012/10/dancing-with-econometricians.html</link>
    <dc:creator>sechilds</dc:creator><description><![CDATA[This is often done in the context of a single structural equation, without a complete simultaneous equations model in sight. There's nothing wrong with this - but please don't refer to this as 2SLS! Unless Z = X, it's just an instrumental variables estimator, constructed in two steps.]]></description>
<dc:subject>econometrics</dc:subject>
<dc:source>https://instapaper.com/</dc:source>
<dc:identifier>https://pinboard.in/u:sechilds/b:280c7a90cfa2/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:sechilds/t:econometrics"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="http://www.econometricsbysimulation.com/2012/07/bootstrapped-draws-for-simulating.html">
    <title>Econometrics by Simulation: bootstrapped draws for simulating observations - merge method</title>
    <dc:date>2012-07-14T16:21:10+00:00</dc:date>
    <link>http://www.econometricsbysimulation.com/2012/07/bootstrapped-draws-for-simulating.html</link>
    <dc:creator>sechilds</dc:creator><dc:subject>econometrics statistics:bootstrap econometrics:simulation</dc:subject>
<dc:source>https://pinboard.in/</dc:source>
<dc:identifier>https://pinboard.in/u:sechilds/b:f00dcf6d7ee4/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:sechilds/t:econometrics"/>
	<rdf:li rdf:resource="https://pinboard.in/u:sechilds/t:statistics:bootstrap"/>
	<rdf:li rdf:resource="https://pinboard.in/u:sechilds/t:econometrics:simulation"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="http://real-estate-and-urban.blogspot.ca/2012/07/mark-thoma-reminds-me-of-something-art.html">
    <title>Richard's Real Estate and Urban Economics Blog: Mark Thoma reminds me of something Art Goldberger taught me: R-squared is over-rated</title>
    <dc:date>2012-07-12T12:26:16+00:00</dc:date>
    <link>http://real-estate-and-urban.blogspot.ca/2012/07/mark-thoma-reminds-me-of-something-art.html</link>
    <dc:creator>sechilds</dc:creator><description><![CDATA[The chief finding of the Soyer-Hogarth experiment is that the expert econometricians themselves—our best number crunchers—make better predictions when only graphical information—such as a scatter plot and theoretical linear regression line—is provided to them. Give them t-statistics and fits of R-squared for the same data and regression model and their forecasting ability declines. Give them only t-statistics and fits of R-squared and predictions fall from bad to worse.
It’s a finding that hits you between the eyes, or should. R-squared, the primary indicator of model fit, and t-statistic, the primary indicator of coefficient fit, are in the leading journals of economics - such as the AER, QJE, JPE, and RES - evidently doing more harm than good.
This reminds me of Art Goldberger's teaching in Econ 612.  After I took that class, he turned his class notes into a book.  From page 177:

From our perspective, R2 has a very modest role in regression analysis, being a measure of the goodness of fit of a sample of LS (least squares) linear regression in a body of data.  Nothing in the CR (classical regression) model requires R2 to be high.  Hence a high R2 is not evidence in favor of the model, and a low R2 is not evidence against it...

...In fact, the most important thing about R2 is that is is not important in the CR model.  The CR model is concerend with parameters in a population, not with the goodness of fit within the sample. 

I also remember Gary Chamberlain was not crazy about t-statistics--he said he didn't want to see any "damn stars" in our papers.  We should care more about confidence intervals than hypothesis tests. ]]></description>
<dc:subject>econometrics</dc:subject>
<dc:source>https://pinboard.in/</dc:source>
<dc:identifier>https://pinboard.in/u:sechilds/b:f484143ae47e/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:sechilds/t:econometrics"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="http://davegiles.blogspot.ca/2012/07/concentrating-or-profiling-likelihood.html">
    <title>Econometrics Beat: Dave Giles' Blog: Concentrating, or Profiling, the Likelihood Function</title>
    <dc:date>2012-07-11T01:46:05+00:00</dc:date>
    <link>http://davegiles.blogspot.ca/2012/07/concentrating-or-profiling-likelihood.html</link>
    <dc:creator>sechilds</dc:creator><dc:subject>econometrics</dc:subject>
<dc:source>https://instapaper.com/</dc:source>
<dc:identifier>https://pinboard.in/u:sechilds/b:88f5345c348a/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:sechilds/t:econometrics"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="http://www.econometricsbysimulation.com/2012/07/delta-method.html">
    <title>Econometrics by Simulation: The Delta Method</title>
    <dc:date>2012-07-10T19:39:13+00:00</dc:date>
    <link>http://www.econometricsbysimulation.com/2012/07/delta-method.html</link>
    <dc:creator>sechilds</dc:creator><dc:subject>econometrics econometrics:simulation</dc:subject>
<dc:source>https://pinboard.in/</dc:source>
<dc:identifier>https://pinboard.in/u:sechilds/b:625b1aa0d6b7/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:sechilds/t:econometrics"/>
	<rdf:li rdf:resource="https://pinboard.in/u:sechilds/t:econometrics:simulation"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="http://blogs.reuters.com/felix-salmon/2012/07/10/how-economists-get-tripped-up-by-statistics/">
    <title>How economists get tripped up by statistics | Felix Salmon</title>
    <dc:date>2012-07-10T19:39:08+00:00</dc:date>
    <link>http://blogs.reuters.com/felix-salmon/2012/07/10/how-economists-get-tripped-up-by-statistics/</link>
    <dc:creator>sechilds</dc:creator><dc:subject>econometrics statistics</dc:subject>
<dc:source>https://instapaper.com/</dc:source>
<dc:identifier>https://pinboard.in/u:sechilds/b:772d59856094/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:sechilds/t:econometrics"/>
	<rdf:li rdf:resource="https://pinboard.in/u:sechilds/t:statistics"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="http://davegiles.blogspot.com/2012/07/decline-and-fall-of-power-curve.html">
    <title>Decline and Fall of the Power Curve</title>
    <dc:date>2012-07-09T20:26:39+00:00</dc:date>
    <link>http://davegiles.blogspot.com/2012/07/decline-and-fall-of-power-curve.html</link>
    <dc:creator>sechilds</dc:creator><description><![CDATA[When we think of the power curve associated with some statistical test, we usually envisage a curve that looks something like (half or all of) an inverted Normal density. That is, the curve rises smoothly and monotonically from a height equal to the significance level of the test (say 1% or 5%), until eventually it reaches its maximum height of 100%.

The latter value reflects the fact that power is a probability.

But is this picture that invariably comes to mind - and that we see reproduced in all elementary econometrics and statistics texts - really the full story?

Actually - no!]]></description>
<dc:subject>econometrics statistics</dc:subject>
<dc:source>https://instapaper.com/</dc:source>
<dc:identifier>https://pinboard.in/u:sechilds/b:be56d4449d8e/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:sechilds/t:econometrics"/>
	<rdf:li rdf:resource="https://pinboard.in/u:sechilds/t:statistics"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="http://www.econometricsbysimulation.com/2012/06/generating-random-variables-drawn-from.html">
    <title>Econometrics by Simulation: Generating 'random' variables drawn from any distribution</title>
    <dc:date>2012-06-30T11:12:58+00:00</dc:date>
    <link>http://www.econometricsbysimulation.com/2012/06/generating-random-variables-drawn-from.html</link>
    <dc:creator>sechilds</dc:creator><dc:subject>econometrics Stata econometrics:simulation</dc:subject>
<dc:source>https://instapaper.com/</dc:source>
<dc:identifier>https://pinboard.in/u:sechilds/b:e65e042197e0/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:sechilds/t:econometrics"/>
	<rdf:li rdf:resource="https://pinboard.in/u:sechilds/t:Stata"/>
	<rdf:li rdf:resource="https://pinboard.in/u:sechilds/t:econometrics:simulation"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="http://www.econometricsbysimulation.com/2012/05/value-added-modelling-stata-simulation.html">
    <title>Econometrics by Simulation: Value-added modelling - Stata simulation - iPad example</title>
    <dc:date>2012-06-30T11:12:50+00:00</dc:date>
    <link>http://www.econometricsbysimulation.com/2012/05/value-added-modelling-stata-simulation.html</link>
    <dc:creator>sechilds</dc:creator><dc:subject>Stata econometrics</dc:subject>
<dc:source>https://instapaper.com/</dc:source>
<dc:identifier>https://pinboard.in/u:sechilds/b:a39bdb959a9f/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:sechilds/t:Stata"/>
	<rdf:li rdf:resource="https://pinboard.in/u:sechilds/t:econometrics"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="http://www.econometricsbysimulation.com/2012/06/estimating-vams-value-added-methods.html">
    <title>Econometrics by Simulation: Estimating VAMs Value Added Methods (models)</title>
    <dc:date>2012-06-30T11:12:35+00:00</dc:date>
    <link>http://www.econometricsbysimulation.com/2012/06/estimating-vams-value-added-methods.html</link>
    <dc:creator>sechilds</dc:creator><dc:subject>econometrics</dc:subject>
<dc:source>https://instapaper.com/</dc:source>
<dc:identifier>https://pinboard.in/u:sechilds/b:d3dacc9dc5b7/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:sechilds/t:econometrics"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="http://www.econometricsbysimulation.com/">
    <title>Econometrics by Simulation</title>
    <dc:date>2012-06-30T03:07:05+00:00</dc:date>
    <link>http://www.econometricsbysimulation.com/</link>
    <dc:creator>sechilds</dc:creator><dc:subject>econometrics Stata</dc:subject>
<dc:source>https://instapaper.com/</dc:source>
<dc:identifier>https://pinboard.in/u:sechilds/b:56316e12fb7b/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:sechilds/t:econometrics"/>
	<rdf:li rdf:resource="https://pinboard.in/u:sechilds/t:Stata"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="http://economistsview.typepad.com/economistsview/2006/09/if_at_first_you.html">
    <title>Economist's View: If At First You Don't Succeed, Run Another Regression</title>
    <dc:date>2012-06-28T19:26:09+00:00</dc:date>
    <link>http://economistsview.typepad.com/economistsview/2006/09/if_at_first_you.html</link>
    <dc:creator>sechilds</dc:creator><dc:subject>econometrics</dc:subject>
<dc:source>https://instapaper.com/</dc:source>
<dc:identifier>https://pinboard.in/u:sechilds/b:387212986147/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:sechilds/t:econometrics"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="http://www.env-econ.net/2012/06/whither-t-192.html">
    <title>Whither t = 1.92?</title>
    <dc:date>2012-06-28T19:16:22+00:00</dc:date>
    <link>http://www.env-econ.net/2012/06/whither-t-192.html</link>
    <dc:creator>sechilds</dc:creator><dc:subject>econometrics</dc:subject>
<dc:source>https://instapaper.com/</dc:source>
<dc:identifier>https://pinboard.in/u:sechilds/b:a8cd3492aaac/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:sechilds/t:econometrics"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="http://stats.stackexchange.com/questions/24263/model-stability-in-cross-validation-of-regression-models?atw=1">
    <title>Model stability in cross-validation of regression models - Cross Validated</title>
    <dc:date>2012-06-27T01:43:36+00:00</dc:date>
    <link>http://stats.stackexchange.com/questions/24263/model-stability-in-cross-validation-of-regression-models?atw=1</link>
    <dc:creator>sechilds</dc:creator><dc:subject>econometrics</dc:subject>
<dc:source>https://instapaper.com/</dc:source>
<dc:identifier>https://pinboard.in/u:sechilds/b:a13a2f5bd077/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:sechilds/t:econometrics"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="http://davegiles.blogspot.com/2012/06/another-gripe-about-linear-probability.html">
    <title>Another Gripe About the Linear Probability Model</title>
    <dc:date>2012-06-01T18:01:07+00:00</dc:date>
    <link>http://davegiles.blogspot.com/2012/06/another-gripe-about-linear-probability.html</link>
    <dc:creator>sechilds</dc:creator><dc:subject>econometrics</dc:subject>
<dc:source>https://instapaper.com/</dc:source>
<dc:identifier>https://pinboard.in/u:sechilds/b:9d4d241ef86a/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:sechilds/t:econometrics"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="http://davegiles.blogspot.com/2012/05/complex-survey-data-in-econometrics.html">
    <title>Complex Survey Data in Econometrics</title>
    <dc:date>2012-05-18T22:17:33+00:00</dc:date>
    <link>http://davegiles.blogspot.com/2012/05/complex-survey-data-in-econometrics.html</link>
    <dc:creator>sechilds</dc:creator><dc:subject>econometrics econometrics:survey</dc:subject>
<dc:source>https://instapaper.com/</dc:source>
<dc:identifier>https://pinboard.in/u:sechilds/b:00c62ddbd571/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:sechilds/t:econometrics"/>
	<rdf:li rdf:resource="https://pinboard.in/u:sechilds/t:econometrics:survey"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="http://davegiles.blogspot.com/2012/05/bayes-estimators-loss-functions-and-j-m.html">
    <title>Bayes Estimators, Loss Functions, and J. M. Keynes</title>
    <dc:date>2012-05-11T23:55:35+00:00</dc:date>
    <link>http://davegiles.blogspot.com/2012/05/bayes-estimators-loss-functions-and-j-m.html</link>
    <dc:creator>sechilds</dc:creator><dc:subject>statistics:bayesian econometrics</dc:subject>
<dc:source>https://instapaper.com/</dc:source>
<dc:identifier>https://pinboard.in/u:sechilds/b:c8ee36798337/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:sechilds/t:statistics:bayesian"/>
	<rdf:li rdf:resource="https://pinboard.in/u:sechilds/t:econometrics"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="http://davegiles.blogspot.ca/2012/04/bayesian-consumption-function.html">
    <title>Econometrics Beat: Dave Giles' Blog: A Bayesian Consumption Function</title>
    <dc:date>2012-04-28T20:48:07+00:00</dc:date>
    <link>http://davegiles.blogspot.ca/2012/04/bayesian-consumption-function.html</link>
    <dc:creator>sechilds</dc:creator><dc:subject>econometrics statistics:bayesian</dc:subject>
<dc:source>https://instapaper.com/</dc:source>
<dc:identifier>https://pinboard.in/u:sechilds/b:339f0f2dbeb6/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:sechilds/t:econometrics"/>
	<rdf:li rdf:resource="https://pinboard.in/u:sechilds/t:statistics:bayesian"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="http://socserv.mcmaster.ca/racine/ECO0301.pdf">
    <title>Nonparametric Econometrics: A Primer</title>
    <dc:date>2012-03-20T18:30:24+00:00</dc:date>
    <link>http://socserv.mcmaster.ca/racine/ECO0301.pdf</link>
    <dc:creator>sechilds</dc:creator><description><![CDATA[This review is a primer for those who wish to familiarize themselves with nonparametric econometrics. Though the underlying theory for many of these methods can be daunting for some practitioners, this article will demonstrate how a range of nonparametric methods can in fact be deployed in a fairly straightforward manner. Rather than aiming for encyclopedic coverage of the field, we shall restrict attention to a set of touchstone topics while making liberal use of examples for illustrative purposes. We will emphasize settings in which the user may wish to model a dataset comprised of continuous, discrete, or categorical data (nominal or ordinal), or any combination thereof. We shall also consider recent developments in which some of the variables involved may in fact be irrelevant, which alters the behavior of the estimators and optimal bandwidths in a manner that deviates substantially from conventional approaches.]]></description>
<dc:subject>econometrics statistics statistics:nonparametric</dc:subject>
<dc:source>https://pinboard.in/</dc:source>
<dc:identifier>https://pinboard.in/u:sechilds/b:09913dae1515/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:sechilds/t:econometrics"/>
	<rdf:li rdf:resource="https://pinboard.in/u:sechilds/t:statistics"/>
	<rdf:li rdf:resource="https://pinboard.in/u:sechilds/t:statistics:nonparametric"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="http://codeandculture.wordpress.com/2012/03/15/control-for-x/">
    <title>Control for x</title>
    <dc:date>2012-03-15T18:51:02+00:00</dc:date>
    <link>http://codeandculture.wordpress.com/2012/03/15/control-for-x/</link>
    <dc:creator>sechilds</dc:creator><description><![CDATA[An extremely common estimation strategy, which Roland Fryer calls “name that residual,” is to throw controls at an effect then say whatever effect remains net of the controls is the effect. Typically as you introduce controls the effect goes down, but not all the way down to zero. Here’s an example using simulated data where we do a regression of y (continuous) on x (dummy) with and without control (continuous and negatively associated with x).]]></description>
<dc:subject>econometrics</dc:subject>
<dc:source>https://instapaper.com/</dc:source>
<dc:identifier>https://pinboard.in/u:sechilds/b:c291f10a77ef/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:sechilds/t:econometrics"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="http://andrewgelman.com/2011/07/descriptive_sta/">
    <title>Descriptive statistics, causal inference, and story time « Statistical Modeling, Causal Inference, and Social Science</title>
    <dc:date>2011-12-28T13:59:20+00:00</dc:date>
    <link>http://andrewgelman.com/2011/07/descriptive_sta/</link>
    <dc:creator>sechilds</dc:creator><description><![CDATA[But story time can’t be avoided. On one hand, there are real questions to be answered and real decisions to be made in development economics (and elsewhere), and researchers and policymakers can’t simply sit still and say they can’t do anything because the data aren’t fully persuasive. (Remember the first principle of decision analysis: Not making a decision is itself a decision.)

From the other direction, once you have an interesting quantitative finding, of course you want to understand it, and it makes sense to use all your storytelling skills here. The challenge is to go back and forth between the storytelling and the data. You find some interesting result (perhaps an observational data summary, perhaps an analysis of an experiment or natural experiment), this motivates a story, which in turn suggests some new hypotheses to be studied. Yu-Sung and I were just talking about this today in regard to our article on public opinion about school vouchers.

The question is: How do quantitative analysis and story time fit into the big picture? Mike McGovern writes that he wishes Paul Collier had been more modest in his causal claims, presenting his quantitative findings as “intriguing and counterintuitive correlations” and frankly recognizing that exploration of these correlations requires real-world understanding, not just the rhetoric of hard-headed empiricism.

I agree completely with McGovern–and I endeavor to follow this sort of modesty in presenting the implications of my own applied work–and I think it’s a starting point for Coliier and others. Once they recognize that, indeed, they are in story time, they can think harder about the empirical implications of their stories.]]></description>
<dc:subject>econometrics statistics</dc:subject>
<dc:source>https://instapaper.com/</dc:source>
<dc:identifier>https://pinboard.in/u:sechilds/b:c72a5960b8af/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:sechilds/t:econometrics"/>
	<rdf:li rdf:resource="https://pinboard.in/u:sechilds/t:statistics"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="http://www.env-econ.net/2011/10/an-example-of-utility.html">
    <title>Maybe substitute &quot;time since I last had to open the SAS log file&quot; (for those economists over the age of, say, 44)</title>
    <dc:date>2011-10-13T13:32:13+00:00</dc:date>
    <link>http://www.env-econ.net/2011/10/an-example-of-utility.html</link>
    <dc:creator>sechilds</dc:creator><dc:subject>xkcd econometrics</dc:subject>
<dc:identifier>https://pinboard.in/u:sechilds/b:b9ce6c7a64d3/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:sechilds/t:xkcd"/>
	<rdf:li rdf:resource="https://pinboard.in/u:sechilds/t:econometrics"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="http://worthwhile.typepad.com/worthwhile_canadian_initi/2011/10/in-praise-of-cookbook-econometrics.html">
    <title>Worthwhile Canadian Initiative: In praise of cookbook econometrics</title>
    <dc:date>2011-10-07T11:27:54+00:00</dc:date>
    <link>http://worthwhile.typepad.com/worthwhile_canadian_initi/2011/10/in-praise-of-cookbook-econometrics.html</link>
    <dc:creator>sechilds</dc:creator><description><![CDATA[Cookbook econometrics has few fans.

I am one of them.

Cookbook econometrics provides clear algorithms for solving econometrics problems, without providing detailed explanations of why these algorithms work, or why specific steps in that algorithm are required.

For example, cookbook econometrics says "if you are trying to explain variable that can take on just two possible values, for example, smoker/non-smoker, use probit," but skips the formula for the inverse cumulative density function of the standard normal distribution, any discussion of how probit estimates are actually calculated, and proofs of the properties of the probit estimator.

David Giles sets out the case against cookbook methods in his blog:

My contention is that if you've been taken through the proof, and seen the assumptions "in action", you're more likely to pay proper attention to those assumptions being satisfied when you use the result, day to day, in your empirical work.

My position is the exact opposite: When you have struggled with empirical work, and seen econometrics "in action", you're more likely to pay proper attention to the proof, and understand the underlying assumptions. 

The difference stems from contrasting views about how people learn. His position appears to be that it is possible -- indeed desirable -- to grasp and understand abstract concepts before applying them and working with them. ]]></description>
<dc:subject>econometrics worthwhile_canadian_initiative</dc:subject>
<dc:source>https://pinboard.in/</dc:source>
<dc:identifier>https://pinboard.in/u:sechilds/b:11669f527ec4/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:sechilds/t:econometrics"/>
	<rdf:li rdf:resource="https://pinboard.in/u:sechilds/t:worthwhile_canadian_initiative"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="http://worthwhile.typepad.com/worthwhile_canadian_initi/2011/10/five-steps-to-cleaner-data.html">
    <title>Worthwhile Canadian Initiative: Nine steps to cleaner data</title>
    <dc:date>2011-10-06T09:29:31+00:00</dc:date>
    <link>http://worthwhile.typepad.com/worthwhile_canadian_initi/2011/10/five-steps-to-cleaner-data.html</link>
    <dc:creator>sechilds</dc:creator><description><![CDATA[Real world data is messy. Dirty. Untidy.

Before you can even think about using all of those pretty techniques you learned in econometrics class, you need to clean up the data.

Here is my nine step approach.]]></description>
<dc:subject>Stata econometrics worthwhile_canadian_initiative Stata:intro data:cleaning</dc:subject>
<dc:source>https://pinboard.in/</dc:source>
<dc:identifier>https://pinboard.in/u:sechilds/b:7f7d58cdc6f4/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:sechilds/t:Stata"/>
	<rdf:li rdf:resource="https://pinboard.in/u:sechilds/t:econometrics"/>
	<rdf:li rdf:resource="https://pinboard.in/u:sechilds/t:worthwhile_canadian_initiative"/>
	<rdf:li rdf:resource="https://pinboard.in/u:sechilds/t:Stata:intro"/>
	<rdf:li rdf:resource="https://pinboard.in/u:sechilds/t:data:cleaning"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="http://www.nber.org/minicourse3.html">
    <title>Whats New in Econometrics?</title>
    <dc:date>2009-02-28T18:32:45+00:00</dc:date>
    <link>http://www.nber.org/minicourse3.html</link>
    <dc:creator>sechilds</dc:creator><dc:subject>econometrics</dc:subject>
<dc:identifier>https://pinboard.in/u:sechilds/b:9ae08d01e6b6/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:sechilds/t:econometrics"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="http://www.npwrc.usgs.gov/resource/methods/statsig/stathyp.htm">
    <title>NPWRC :: Statistical Significance Testing</title>
    <dc:date>2008-05-24T18:50:23+00:00</dc:date>
    <link>http://www.npwrc.usgs.gov/resource/methods/statsig/stathyp.htm</link>
    <dc:creator>sechilds</dc:creator><description><![CDATA[Four basic steps constitute statistical hypothesis testing. First, one develops a null hypothesis about some phenomenon or parameter. This null hypothesis is generally the opposite of the research hypothesis, which is what the investigator truly believes]]></description>
<dc:subject>statistics econometrics</dc:subject>
<dc:identifier>https://pinboard.in/u:sechilds/b:bd79b2b5927a/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:sechilds/t:statistics"/>
	<rdf:li rdf:resource="https://pinboard.in/u:sechilds/t:econometrics"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="http://www.estat.us/id38.html">
    <title>Hierarchical Linear Model (HLM)</title>
    <dc:date>2008-04-24T18:13:30+00:00</dc:date>
    <link>http://www.estat.us/id38.html</link>
    <dc:creator>sechilds</dc:creator><description><![CDATA[A page of resources on hierarchical linear models.]]></description>
<dc:subject>statistics work econometrics</dc:subject>
<dc:identifier>https://pinboard.in/u:sechilds/b:ae5e698d0261/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:sechilds/t:statistics"/>
	<rdf:li rdf:resource="https://pinboard.in/u:sechilds/t:work"/>
	<rdf:li rdf:resource="https://pinboard.in/u:sechilds/t:econometrics"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="http://www.stat.columbia.edu/~cook/movabletype/archives/2005/03/the_secret_weap.html">
    <title>The secret weapon</title>
    <dc:date>2008-04-22T23:56:20+00:00</dc:date>
    <link>http://www.stat.columbia.edu/~cook/movabletype/archives/2005/03/the_secret_weap.html</link>
    <dc:creator>sechilds</dc:creator><description><![CDATA[An incredibly useful method is to fit a statistical model repeatedly on several different datasets and then display all these estimates together. For example, running a regression on data on each of 50 states (see here as discussed here), or running a reg]]></description>
<dc:subject>economics statistics econometrics</dc:subject>
<dc:identifier>https://pinboard.in/u:sechilds/b:0d6827d16848/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:sechilds/t:economics"/>
	<rdf:li rdf:resource="https://pinboard.in/u:sechilds/t:statistics"/>
	<rdf:li rdf:resource="https://pinboard.in/u:sechilds/t:econometrics"/>
</rdf:Bag></taxo:topics>
</item>
</rdf:RDF>