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<!doctype html>
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<head>
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<title>Tyler Ransom by tyleransom</title>
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<body>
<div class="wrapper">
<header>
<h1>Tyler Ransom</h1>
<p>Associate Professor of Economics<br>University of Oklahoma</p>
<p>Research Fellow<br><a href="https://www.iza.org/person/24155/tyler-ransom">Institute for the Study of Labor (IZA)</a></p>
<p>Fellow<br><a href="https://glabor.org/user/tyleransom/">Global Labor Organization (GLO)</a></p>
<h3><a href="https://tyleransom.github.io/">Home</a></h3>
<h3><a href="https://tyleransom.github.io/research.html">Research</a></h3>
<h3><a href="https://tyleransom.github.io/research/CV.pdf">CV</a></h3>
<h3><a href="https://tyleransom.github.io/code.html">Code</a></h3>
<h3><a href="https://tyleransom.github.io/teaching.html">Teaching</a></h3>
<h3><a href="https://tyleransom.github.io/personal.html">Personal</a></h3>
<b>Social</b><br>
<div class="social-row">
<a href="mailto:[email protected]" class="author-social" target="_blank"><i class="fa fa-fw fa-envelope-square"></i> Email</a><br>
<a href="https://scholar.google.com/citations?user=eohlTTcAAAAJ&hl=en" target="_blank"><i class="ai ai-fw ai-google-scholar-square"></i> Scholar</a><br>
<a href="https://orcid.org/0000-0002-6910-0363"><i class="ai ai-fw ai-orcid-square"></i> ORCID</a><br>
<a href="http://ideas.repec.org/f/pra541.html"><i class="ai ai-fw ai-ideas-repec-square"></i> RePEc</a><br>
<a href="http://github.com/tyleransom"><i class="fa fa-fw fa-github-square"></i> GitHub</a><br>
<a href="http://twitter.com/tyleransom" class="author-social" target="_blank"><i class="fa fa-fw fa-twitter-square"></i> Twitter</a><br>
<a href="http://linkedin.com/in/tyleransom" class="author-social" target="_blank"><i class="fa fa-fw fa-linkedin-square"></i> LinkedIn</a><br>
<br>
</div>
<br>
<p><b>Contact:</b><br>Department of Economics<br>University of Oklahoma<br>322 CCD1, 308 Cate Center Drive<br>Norman, OK 73072</p>
<p><small>Hosted on GitHub Pages — Theme by <a href="https://github.com/orderedlist">orderedlist</a></small></p>
</header>
<section>
<h2><a id="computer-code" class="anchor" href="#computercode" aria-hidden="true"><span class="octicon octicon-link"></span></a>Computer Code</h2>
<h3>Julia</h3>
<ul>
<li><a href="https://raw.githack.com/OU-PhD-Econometrics/fall-2022/master/LectureNotes/00-JuliaTips/00slides.html#1">Introductory slides</a> that introduce <a href="http://julialang.org/">Julia</a> (outdated version <a href="https://tyleransom.github.io/research/JuliaPresentation.pdf">here</a>)</li>
<li><a href="https://github.com/tyleransom/Julia">My Github repository</a>, which introduces basic econometric models in <a href="http://julialang.org/">Julia</a>.</li>
<li><a href="https://github.com/tyleransom/EMalgorithmExample"><code>EM algorithm example</code></a>: Code to generate data and estimate simple versions of the EM algorithm for estimation of models with discrete type-specific unobserved heterogeneity.</li>
</ul>
<h3>Matlab</h3>
<ul>
<li><a href="http://www.mathworks.com/matlabcentral/fileexchange/41150-summarize"><code>summarize.m</code></a>: Mimics Stata's <code>summarize</code> command.</li>
<li><a href="http://www.mathworks.com/matlabcentral/fileexchange/47927-normalmle-m"><code>normalMLE.m</code></a>: Estimates normal linear regression with heteroskedastic errors by maximum likelihood.</li>
<li><a href="http://www.mathworks.com/matlabcentral/fileexchange/47284-apply-restrictions"><code>applyRestr.m</code></a>: Allows for easy parameter restrictions in optimization problems (co-writen with <a href="http://bschool.pepperdine.edu/about/people/faculty/jared-ashworth/">Jared Ashworth</a>).</li>
<li><a href="http://www.mathworks.com/matlabcentral/fileexchange/47389-conditional-logit"><code>clogit.m</code></a>: Estimates conditional logit regression by maximum likelihood (co-writen with <a href="http://bschool.pepperdine.edu/about/people/faculty/jared-ashworth/">Jared Ashworth</a>).</li>
<li><a href="https://www.mathworks.com/matlabcentral/fileexchange/68256-ordered-logit"><code>ologit.m</code></a>: Estimates the ordered logit model by maximum likelihood.</li>
<li><a href="https://www.mathworks.com/matlabcentral/fileexchange/68255-emalgorithmexample"><code>EM algorithm example</code></a>: Code to generate data and estimate simple versions of the EM algorithm for estimation of models with discrete type-specific unobserved heterogeneity.</li>
</ul>
<h3>LaTeX</h3>
<ul>
<li><a href="https://github.com/tyleransom/CapeTownBeamerTheme">Cape Town</a>: a Beamer slide theme for LaTeX presentations.</li>
<li><a href="https://github.com/tyleransom/beamer-poster-example">Poster</a>: a LaTeX poster example.</li>
<li><a href="https://github.com/tyleransom/jolebib/blob/master/jole.bst">jole.bst</a>: a BibTeX style file for formatting citations according to the style of the <i>Journal of Labor Economics</i>.</li>
<li><a href="https://tyleransom.github.io/research/CVtemplate.tex">CV template</a>: a template for producing a CV in LaTeX (<a href="https://tyleransom.github.io/research/CVtemplate.pdf">PDF output</a>)</li>
<li><a href="https://github.com/tyleransom/Journal-Reviewer-Template">Template for completing peer review</a>: a template for producing materials for requests to serve as a peer reviewer </li>
<li><a href="https://github.com/tyleransom/LaTeX-Multiple-Bibliographies">Minimal working example</a> of how to include multiple bibliographies in a LaTeX document </li>
</ul>
<hr>
<h2><a id="machine-learning" class="anchor" href="#machinelearning" aria-hidden="true"><span class="octicon octicon-link"></span></a>Machine Learning Resources</h2>
<ul>
<li><a href="https://tyleransom.github.io/research/IntroMachineLearning.pdf">Introduction to machine learning for social scientists</a>: Slides from a short presentation that outlines what machine learning is and how social scientists can benefit from using its methods.</li>
<li><a href="https://homes.cs.washington.edu/~pedrod/papers/cacm12.pdf">Practical tips for machine learning practitioners</a>, via Pedro Domingos.</li>
<li><a href="http://www.basicbooks.com/full-details?isbn=9780465065707">The Master Algorithm</a>, written by Pedro Domingos.</li>
</ul>
</section>
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