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    <title>Pinboard (dvse)</title>
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    <description>recent bookmarks from dvse</description>
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	<rdf:li rdf:resource="http://rsta.royalsocietypublishing.org/content/222/594-604/309.full.pdf"/>
	<rdf:li rdf:resource="http://economics.mit.edu/files/5326"/>
	<rdf:li rdf:resource="http://www.international.ucla.edu/media/files/Leamer_article.pdf"/>
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  </channel><item rdf:about="http://arxiv.org/abs/math-ph/0002049">
    <title>Classical and Quantum Probability</title>
    <dc:date>2012-08-11T15:25:00+00:00</dc:date>
    <link>http://arxiv.org/abs/math-ph/0002049</link>
    <dc:creator>dvse</dc:creator><description><![CDATA["We survey the development of probability from 1900, starting with Bachelier's theory of speculation. Fisher information appears in the theory of estimation. We touch on Brownian motion, and the Wiener integral. The Ito calculus, and its relation to to the heat equation, is mentioned. Quantum theory is introduced as a generalisation of probability, rather than of mechanics. The weakness of attempts to describe quantum theory in terms of hidden variables is explained, by a simple proof of Bell's inequality.
Quantum versions of the Langevin equation are discussed, and the theory of continuous tensor products is used to give a possible quantum version. The quantum stochastic calculus of Barnett, Wilde and the author, as well as that of Parthasarathy and Hudson, is introduced."]]></description>
<dc:subject>statistics foundations finance quantum_mechanics</dc:subject>
<dc:source>https://pinboard.in/</dc:source>
<dc:identifier>https://pinboard.in/u:dvse/b:1ba1cc2416ab/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:dvse/t:statistics"/>
	<rdf:li rdf:resource="https://pinboard.in/u:dvse/t:foundations"/>
	<rdf:li rdf:resource="https://pinboard.in/u:dvse/t:finance"/>
	<rdf:li rdf:resource="https://pinboard.in/u:dvse/t:quantum_mechanics"/>
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<item rdf:about="http://rsta.royalsocietypublishing.org/content/222/594-604/309.full.pdf">
    <title>On the mathematical foundations of theoretical statistics</title>
    <dc:date>2012-04-01T13:07:29+00:00</dc:date>
    <link>http://rsta.royalsocietypublishing.org/content/222/594-604/309.full.pdf</link>
    <dc:creator>dvse</dc:creator><description><![CDATA[R.A Fisher's classical paper outlining the maximum likelihood principle and the notions of sufficiency, efficiency and consistency.]]></description>
<dc:subject>statistics foundations estimation</dc:subject>
<dc:source>https://pinboard.in/</dc:source>
<dc:identifier>https://pinboard.in/u:dvse/b:4834fa210d16/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:dvse/t:statistics"/>
	<rdf:li rdf:resource="https://pinboard.in/u:dvse/t:foundations"/>
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<item rdf:about="http://economics.mit.edu/files/5326">
    <title>The Credibility Revolution in Empirical Economics: How Better Research Design Is Taking the Con out of Econometrics</title>
    <dc:date>2012-04-01T13:01:37+00:00</dc:date>
    <link>http://economics.mit.edu/files/5326</link>
    <dc:creator>dvse</dc:creator><description><![CDATA["Since Edward Leamer's memorable 1983 paper, "Let's Take the Con out of Econometrics," empirical microeconomics has experienced a credibility revolution. While Leamer's suggested remedy, sensitivity analysis, has played a role in this, we argue that the primary engine driving improvement has been a focus on the quality of empirical research designs. The advantages of a good research design are perhaps most easily apparent in research using random assignment. We begin with an overview of Leamer's 1983 critique and his proposed remedies. We then turn to the key factors we see contributing to improved empirical work, including the availability of more and better data, along with advances in theoretical econometric understanding, but especially the fact that research design has moved front and center in much of empirical micro. We offer a brief digression into macroeconomics and industrial organization, where progress -- by our lights -- is less dramatic, although there is work in both fields that we find encouraging. Finally, we discuss the view that the design pendulum has swung too far. Critics of design-driven studies argue that in pursuit of clean and credible research designs, researchers seek good answers instead of good questions. We briefly respond to this concern, which worries us little."

IV / natural experiment proponents revisiting Leamer's critique.]]></description>
<dc:subject>econometrics foundations estimation</dc:subject>
<dc:source>https://pinboard.in/</dc:source>
<dc:identifier>https://pinboard.in/u:dvse/b:b1a5ae558231/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:dvse/t:econometrics"/>
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<item rdf:about="http://www.international.ucla.edu/media/files/Leamer_article.pdf">
    <title>Let's take the Con out of Econometrics (Leamer)</title>
    <dc:date>2012-02-13T13:23:56+00:00</dc:date>
    <link>http://www.international.ucla.edu/media/files/Leamer_article.pdf</link>
    <dc:creator>dvse</dc:creator><description><![CDATA[What to do when "experiments" can not be controlled (not much, but indoctrination helps) - predates current IV methodology?]]></description>
<dc:subject>econometrics foundations statistics</dc:subject>
<dc:source>https://pinboard.in/</dc:source>
<dc:identifier>https://pinboard.in/u:dvse/b:ab99b9af5b7e/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:dvse/t:econometrics"/>
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<item rdf:about="http://projecteuclid.org/DPubS?service=UI&amp;version=1.0&amp;verb=Display&amp;handle=euclid.lnms/1249305323">
    <title>Huber: On the Non-Optimality of Optimal Procedures</title>
    <dc:date>2012-02-13T12:35:41+00:00</dc:date>
    <link>http://projecteuclid.org/DPubS?service=UI&amp;version=1.0&amp;verb=Display&amp;handle=euclid.lnms/1249305323</link>
    <dc:creator>dvse</dc:creator><description><![CDATA["This paper discusses some subtle, and largely overlooked, differences between conceptual and mathematical optimization goals in statistics, and illustrates them by examples."
]]></description>
<dc:subject>statistics robust_statistics optimization foundations via:mraginsky</dc:subject>
<dc:identifier>https://pinboard.in/u:dvse/b:710548abe3f2/</dc:identifier>
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