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      <title>Recent Content on Compumetrika </title>
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    <link>http://npalmer.github.io/index.xml/</link>
    <language>en-us</language>
    
    
    <updated>Thu, 16 Apr 2015 11:51:05 EDT</updated>
    
    <item>
      <title>Notebooks</title>
      <link>http://npalmer.github.io/pages/notebooks/</link>
      <pubDate>Thu, 16 Apr 2015 11:51:05 EDT</pubDate>
      
      <guid>http://npalmer.github.io/pages/notebooks/</guid>
      <description>&lt;p&gt;This is a simple collection of my &amp;ldquo;scratchwork notebooks&amp;rdquo; &amp;ndash; a place to store collections of useful information. The subject of these notebooks is far ranging &amp;ndash; some are simply reminders of useful tools while others are more fully fleshed-out research explorations. Below is a simple list of notebooks by topic.&lt;/p&gt;
</description>
    </item>
    
    <item>
      <title>Teaching</title>
      <link>http://npalmer.github.io/pages/teaching/</link>
      <pubDate>Wed, 15 Apr 2015 21:36:26 EDT</pubDate>
      
      <guid>http://npalmer.github.io/pages/teaching/</guid>
      <description>&lt;p&gt;This is my teaching page!&lt;/p&gt;
</description>
    </item>
    
    <item>
      <title>Interests</title>
      <link>http://npalmer.github.io/pages/interests/</link>
      <pubDate>Wed, 15 Apr 2015 21:35:38 EDT</pubDate>
      
      <guid>http://npalmer.github.io/pages/interests/</guid>
      <description>&lt;p&gt;This is my interests page!&lt;/p&gt;
</description>
    </item>
    
    <item>
      <title>About</title>
      <link>http://npalmer.github.io/pages/about/</link>
      <pubDate>Wed, 15 Apr 2015 21:34:49 EDT</pubDate>
      
      <guid>http://npalmer.github.io/pages/about/</guid>
      <description>

&lt;p&gt;I am a PhD candidate in the &lt;a href=&#34;http://www.css.gmu.edu/&#34;&gt;Department of Computational Social Science&lt;/a&gt; at George Mason University, specializing in simulation techniques applied to macroeconomics (learning &amp;amp; consumption behavior) and finance (leverage, liquidity, &amp;amp; contagion). &lt;a href=&#34;http://www.css.gmu.edu/?q=node/27&#34;&gt;Rob&lt;/a&gt; &lt;a href=&#34;http://en.wikipedia.org/wiki/Robert_Axtell&#34;&gt;Axtell&lt;/a&gt; &lt;a href=&#34;http://ideas.repec.org/e/pax2.html&#34;&gt;is&lt;/a&gt; my advisor and I am having a blast working on interesting projects with a lot of very bright people.&lt;/p&gt;

&lt;p&gt;Note to prospective CSS students:  If you are interested in pursuing economics or finance in the CSS program, please feel free to send me an email at &lt;a href=&#34;mailto:npalmer4@masonlive.gmu.edu&#34;&gt;npalmer4@masonlive.gmu.edu&lt;/a&gt;. I&amp;rsquo;m always happy to talk about the work we do and am happy to offer (often blunt) advice as you survey the PhD landscape.&lt;/p&gt;

&lt;h2 id=&#34;toc_0&#34;&gt;Research&lt;/h2&gt;

&lt;p&gt;My &lt;a href=&#34;/pages/research&#34;&gt;research page&lt;/a&gt; outlines my current publications and work in progress.&lt;/p&gt;

&lt;p&gt;My CV can be found &lt;a href=&#34;/pages/cv&#34;&gt;here&lt;/a&gt;.&lt;/p&gt;

&lt;h2 id=&#34;toc_1&#34;&gt;Notebooks&lt;/h2&gt;

&lt;p&gt;My &lt;a href=&#34;/pages/notebooks&#34;&gt;notebooks&lt;/a&gt; are a simple collection of ideas and resources, spanning a wide range to topics. These exist as a &amp;ldquo;scratchwork area&amp;rdquo; to store things I find useful.&lt;/p&gt;

&lt;h2 id=&#34;toc_2&#34;&gt;Teaching&lt;/h2&gt;

&lt;p&gt;I have enjoyed teaching computational supplements in [Econ 838]() and [CSS 739]().&lt;/p&gt;

&lt;p&gt;My material for parametric and non-parametric statistics for Econ 838 is only available to students who have taken the course or obtained special permission from the instructor.&lt;/p&gt;

&lt;p&gt;My crash course in dynamic programming for [CSS 739]() can be found in the &lt;a href=&#34;/pages/notebooks&#34;&gt;notebooks&lt;/a&gt; section and on my github page.&lt;/p&gt;

&lt;h2 id=&#34;toc_3&#34;&gt;Blog&lt;/h2&gt;

&lt;p&gt;My blog (which is updated somewhat infrequently) can be found &lt;a href=&#34;/#blog&#34;&gt;here&lt;/a&gt;.&lt;/p&gt;

&lt;h2 id=&#34;toc_4&#34;&gt;Interests&lt;/h2&gt;

&lt;p&gt;Aside from &lt;a href=&#34;http://www.comp-econ.org/&#34;&gt;computational economics&lt;/a&gt; and &lt;a href=&#34;http://www.youtube.com/watch?v=c-sieJVR5TI&#34;&gt;agent-based&lt;/a&gt; &lt;a href=&#34;http://www2.econ.iastate.edu/tesfatsi/ace.htm&#34;&gt;modeling&lt;/a&gt;, I thoroughly enjoy being outdoors. As a native South Texan, I miss Tex-Mex and dance halls (not line dancing, although that can be fun &amp;ndash; I&amp;rsquo;m much more a fan of two-step, waltz, polka, and swing). I recently discovered that some activities I enjoyed in undergrad are nowadays described as &amp;ldquo;freerunning&amp;rdquo; or &amp;ldquo;&lt;a href=&#34;http://en.wikipedia.org/wiki/Parkour&#34;&gt;parkour&lt;/a&gt;.&amp;rdquo; I&amp;rsquo;m certainly not in shape enough for that now, but I&amp;rsquo;d love to get into it again someday&amp;hellip;&lt;/p&gt;

&lt;p&gt;On an academic note, I really enjoy &lt;a href=&#34;http://johnstachurski.net/lectures/index.html&#34;&gt;programming and computational approaches&lt;/a&gt;, and the &lt;a href=&#34;http://johnstachurski.net/personal/mathematics.html&#34;&gt;mathematics&lt;/a&gt; needed to understand and use computational models. How people learn and make decisions in uncertain situations is fascinating to me. People are much smarter than they are often given credit, I believe, and capturing their behavior in a highly complex and uncertain environments is a fascinating topic. Optimizing behavior may at times seem to vastly over-estimate an agent&amp;rsquo;s ability, but rule-of-thumb behavior may vastly underestimate an agent&amp;rsquo;s ability. I am most attracted to learning processes based on generalizations to dynamic programming. There is a tremendous literature in this area and I believe this approach is rigorous and an excellent framework for many aspects of learning.&lt;/p&gt;

&lt;p&gt;I strongly believe that agent-based modeling is simply the next step in computational economic modeling, incorporating insights from software engineering to construct models that &amp;ldquo;trace out&amp;rdquo; the effects of &amp;ldquo;well tested theory&amp;rdquo; (to use &lt;a href=&#34;http://www.aeaweb.org/articles.php?doi=10.1257/jep.10.1.69&#34;&gt;Kydland and Prescott&amp;rsquo;s&lt;/a&gt; terminology). The &amp;ldquo;black box&amp;rdquo; of agent-based modeling need not exist.&lt;/p&gt;

&lt;p&gt;Ongoing research in areas such as &lt;a href=&#34;http://www.nber.org/papers/w17783&#34;&gt;boundedly rational dynamic programming&lt;/a&gt;, &lt;a href=&#34;http://www2.econ.iastate.edu/tesfatsi/aemind.htm&#34;&gt;Q-learning &amp;amp; related tools&lt;/a&gt;, and &lt;a href=&#34;http://ideas.repec.org/p/ore/uoecwp/2010-15.html&#34;&gt;N-Period-ahead learning&lt;/a&gt; are just a few examples of topics that interest me quite a bit. Another approach, of course, is to &amp;ldquo;mix&amp;rdquo; some optimal and non-optimal behavior, either in a single agent (as in Laibson et al.&amp;rsquo;s  &lt;a href=&#34;http://www.aeaweb.org/articles.php?doi=10.1257/jep.24.4.67&#34;&gt;Natural Expectations&lt;/a&gt;, which is begging to be combined with a Bayesian approach a la &lt;a href=&#34;http://www.pnas.org/content/104/22/9493.full&#34;&gt;fictive learning&lt;/a&gt; ) or in a population of agents (as in &lt;a href=&#34;http://www.frbsf.org/economics/economists/staff.php?klansing&#34;&gt;Lansing&lt;/a&gt;&amp;rsquo;s &lt;a href=&#34;https://editorialexpress.com/cgi-bin/conference/download.cgi?db_name=CEF2012&amp;amp;paper_id=329&#34;&gt;work&lt;/a&gt; and &lt;a href=&#34;http://www.wouterdenhaan.com/&#34;&gt;Wouter den Haan&lt;/a&gt;&amp;rsquo;s &lt;a href=&#34;http://www.wouterdenhaan.com/numerical/boundedrationalityslides.pdf&#34;&gt;work&lt;/a&gt;). Beyond these approaches, of course, are econometric and statistical learning approaches, game-theoretic approaches, and AI and evolutionary approaches. For me an ideal outcome of these processes is a modular learning and expectations-formation procedures that are well-understood both at the individual level as well as at the aggregate level, which may then be used in any number of large-scale simulations.&lt;/p&gt;

&lt;p&gt;At the end of the day, we want to discover the simplest, theoretically well-understood learning processes which closely match household and individual behavior. We want &amp;ldquo;econometric rationality&amp;rdquo; &amp;ndash; a convex combination of a few simple learning models which give us zero error in expectation when forecasting population behavior. I strongly suspect that the &amp;ldquo;true structural parameters&amp;rdquo; which fulfill the Lucas Critique will in fact be learning parameters as well as preference parameters.&lt;/p&gt;
</description>
    </item>
    
    <item>
      <title>Main</title>
      <link>http://npalmer.github.io/pages/main/</link>
      <pubDate>Wed, 15 Apr 2015 21:34:49 EDT</pubDate>
      
      <guid>http://npalmer.github.io/pages/main/</guid>
      <description>

&lt;h2 id=&#34;toc_0&#34;&gt;About&lt;/h2&gt;

&lt;p&gt;I am currently a PhD candidate in the &lt;a href=&#34;http://www.css.gmu.edu/&#34;&gt;Department of Computational Social Science&lt;/a&gt; at George Mason University, specializing in simulation techniques applied to macroeconomics (learning &amp;amp; consumption behavior) and finance (leverage, liquidity, &amp;amp; contagion). &lt;a href=&#34;http://www.css.gmu.edu/?q=node/27&#34;&gt;Rob&lt;/a&gt; &lt;a href=&#34;http://en.wikipedia.org/wiki/Robert_Axtell&#34;&gt;Axtell&lt;/a&gt; &lt;a href=&#34;http://ideas.repec.org/e/pax2.html&#34;&gt;is&lt;/a&gt; my advisor and I am having a blast working on interesting projects with a lot of very bright people.&lt;/p&gt;

&lt;p&gt;&lt;strong&gt;Note to prospective CSS students:&lt;/strong&gt;  If you are interested in pursuing economics or finance in the CSS program, please feel free to send me an email at &lt;a href=&#34;mailto:npalmer4@masonlive.gmu.edu&#34;&gt;npalmer4@masonlive.gmu.edu&lt;/a&gt;. I&amp;rsquo;m always happy to talk about the work we do and am happy to offer (often blunt) advise as you survey the PhD landscape.&lt;/p&gt;

&lt;h2 id=&#34;toc_1&#34;&gt;Research&lt;/h2&gt;

&lt;p&gt;My &lt;a href=&#34;/pages/research&#34;&gt;research page&lt;/a&gt; outlines my current publications and work in progress.&lt;/p&gt;

&lt;p&gt;My CV can be found &lt;a href=&#34;/pages/cv&#34;&gt;here&lt;/a&gt;.&lt;/p&gt;

&lt;h2 id=&#34;toc_2&#34;&gt;Notebooks&lt;/h2&gt;

&lt;p&gt;My &lt;a href=&#34;/pages/notebooks&#34;&gt;notebooks&lt;/a&gt; are a simple collection of ideas and resources, spanning a wide range to topics. These exist as a &amp;ldquo;scratchwork are&amp;rdquo; to store things I find useful.&lt;/p&gt;

&lt;h2 id=&#34;toc_3&#34;&gt;Teaching&lt;/h2&gt;

&lt;p&gt;I have enjoyed teaching computational supplements in [Econ 838]() and [CSS 739]().&lt;/p&gt;

&lt;p&gt;My material for parametric and non-parametric statistics for Econ 838 is only available to students who have taken the course or obtained special permission from the instructor.&lt;/p&gt;

&lt;p&gt;My crash course in dynamic programming for [CSS 739]() can be found in the &lt;a href=&#34;/pages/notebooks&#34;&gt;notebooks&lt;/a&gt; section and on my github page.&lt;/p&gt;

&lt;h2 id=&#34;toc_4&#34;&gt;Blog&lt;/h2&gt;

&lt;p&gt;My blog (which is extremely rarely updated) can be found &lt;a href=&#34;#/blog&#34;&gt;here&lt;/a&gt;.&lt;/p&gt;

&lt;h2 id=&#34;toc_5&#34;&gt;Interests&lt;/h2&gt;

&lt;p&gt;Aside from &lt;a href=&#34;http://www.comp-econ.org/&#34;&gt;computational economics&lt;/a&gt; and &lt;a href=&#34;http://www.youtube.com/watch?v=c-sieJVR5TI&#34;&gt;agent-based&lt;/a&gt; &lt;a href=&#34;http://www2.econ.iastate.edu/tesfatsi/ace.htm&#34;&gt;modeling&lt;/a&gt;, I thoroughly enjoy being outdoors. As a native South Texan, I miss Tex-Mex and dance halls (not line dancing, although that can be fun &amp;ndash; I&amp;rsquo;m much more a fan of two-step, waltz, polka, and swing). I recently discovered that some activities I enjoyed in undergrad are nowadays described as &amp;ldquo;freerunning&amp;rdquo; or &amp;ldquo;&lt;a href=&#34;http://en.wikipedia.org/wiki/Parkour&#34;&gt;parkour&lt;/a&gt;.&amp;rdquo; I&amp;rsquo;m certainly not in shape enough for that now, but I&amp;rsquo;d love to get into it again someday&amp;hellip;&lt;/p&gt;

&lt;p&gt;On an academic note, I really enjoy &lt;a href=&#34;http://johnstachurski.net/lectures/index.html&#34;&gt;programming and computational approaches&lt;/a&gt;, and the &lt;a href=&#34;http://johnstachurski.net/personal/mathematics.html&#34;&gt;mathematics&lt;/a&gt; needed to understand and use computational models. How people learn and make decisions in uncertain situations is fascinating to me. People are much smarter than they are often given credit, I believe, and capturing their behavior in a highly complex and uncertain environments is a fascinating topic. Optimizing behavior may at times seem to vastly over-estimate an agent&amp;rsquo;s ability, but rule-of-thumb behavior may vastly underestimate an agent&amp;rsquo;s ability. I am most attracted to learning processes based on generalizations to dynamic programming. There is a tremendous literature in this area and I believe.&lt;/p&gt;

&lt;p&gt;I strongly believe that agent-based modeling is simply the next step in computational economic modeling, incorporating insights from software engineering to construct models that &amp;ldquo;trace out&amp;rdquo; the effects of &amp;ldquo;well tested theory&amp;rdquo; (to use &lt;a href=&#34;http://www.aeaweb.org/articles.php?doi=10.1257/jep.10.1.69&#34;&gt;Kydland and Prescott&amp;rsquo;s&lt;/a&gt; terminology). The &amp;ldquo;black box&amp;rdquo; of agent-based modeling need not exist.&lt;/p&gt;

&lt;p&gt;Ongoing research in areas such as &lt;a href=&#34;http://www.nber.org/papers/w17783&#34;&gt;boundedly rational dynamic programming&lt;/a&gt;, &lt;a href=&#34;http://www2.econ.iastate.edu/tesfatsi/aemind.htm&#34;&gt;Q-learning &amp;amp; related tools&lt;/a&gt;, and &lt;a href=&#34;http://ideas.repec.org/p/ore/uoecwp/2010-15.html&#34;&gt;N-Period-ahead learning&lt;/a&gt; are just a few examples of topics that interest me quite a bit. Another approach, of course, is to &amp;ldquo;mix&amp;rdquo; some optimal and non-optimal behavior, either in a single agent (as in Laibson et al.&amp;rsquo;s  &lt;a href=&#34;http://www.aeaweb.org/articles.php?doi=10.1257/jep.24.4.67&#34;&gt;Natural Expectations&lt;/a&gt;, which is begging to be combined with a Bayesian approach a la &lt;a href=&#34;http://www.pnas.org/content/104/22/9493.full&#34;&gt;fictive learning&lt;/a&gt; ) or in a population of agents (as in &lt;a href=&#34;http://www.frbsf.org/economics/economists/staff.php?klansing&#34;&gt;Lansing&lt;/a&gt;&amp;rsquo;s &lt;a href=&#34;https://editorialexpress.com/cgi-bin/conference/download.cgi?db_name=CEF2012&amp;amp;paper_id=329&#34;&gt;work&lt;/a&gt; and &lt;a href=&#34;http://www.wouterdenhaan.com/&#34;&gt;Wouter den Haan&lt;/a&gt;&amp;rsquo;s &lt;a href=&#34;http://www.wouterdenhaan.com/numerical/boundedrationalityslides.pdf&#34;&gt;work&lt;/a&gt;). Beyond these approaches, of course, are econometric and statistical learning approaches, game-theoretic approaches, and AI and evolutionary approaches. For me an ideal outcome of these processes is a modular learning and expectations-formation procedures that are well-understood both at the individual level as well as at the aggregate level, which may then be used in any number of large-scale simulations.&lt;/p&gt;

&lt;p&gt;At the end of the day, we want to discover the simplest, theoretically well-understood learning processes which closely match household and individual behavior. We want &amp;ldquo;econometric rationality&amp;rdquo; &amp;ndash; a convex combination of a few simple learning models which give us zero error in expectation when forecasting population behavior. I strongly suspect that the &amp;ldquo;true structural parameters&amp;rdquo; which fulfill the Lucas Critique will in fact be learning parameters as well as preference parameters.&lt;/p&gt;
</description>
    </item>
    
    <item>
      <title>Research</title>
      <link>http://npalmer.github.io/pages/research/</link>
      <pubDate>Wed, 15 Apr 2015 21:21:50 EDT</pubDate>
      
      <guid>http://npalmer.github.io/pages/research/</guid>
      <description>

&lt;p&gt;My research focuses on how to incorporate learning-to-optimize behavior from the dynamic programming literature into basic consumption-savings and portfolio decision problems (whether household, market maker, or other). In the past few decades the dynamic programming literature has expanded rapidly in the direction of &lt;em&gt;learning&lt;/em&gt; the solution to dynamic optimization problems from &lt;em&gt;streams of experience&lt;/em&gt;. For a particular stochastic optimization problem, streams of experience generated by the DGP replace full knowledge of the state-space. Instead of making sweeps over the state space to find the fixed point of a dynamic program (i.e. the optimal value and policy functions), a learning-to-optimize method takes streams of experience from a DGP to improve a policy and value function as the data arrives. Convergence often rests on the same monotoncity and contraction mapping properties which ensure that traditional dynamic programs converges. In this setting, optimization can occur &amp;ldquo;online,&amp;rdquo; as an agent experiences their problem. There are a number of ways to approximate portions of the solution method, which can make previously intractable problems tractable.&lt;/p&gt;

&lt;p&gt;New theoretical questions emerge from this framework, including the amount of learning time required to obtain an optimal solution from a given starting point, or, conversely, given a fixed time spent learning, the welfare cost of the policies found in that time. Additionally, the &amp;ldquo;exploitation/exploration&amp;rdquo; tradeoff is highlighted in this approach. There is always an opportunity cost to &amp;ldquo;exploring&amp;rdquo; a new policy when one doesn&amp;rsquo;t have full information: one may waste valuable time on a poor policy, when one could have simply exploited the best policy found thus far. Perhaps not surprisingly, learning from others can be a very important part of this process.&lt;/p&gt;

&lt;p&gt;The applications of this are multifaceted. Appropriate approximation techniques can allow previously intractable problems to be solved for their optimal solution - for example, models with highly heterogeneous agents. Alternatively, learning-to-optimize may provide a framework for bounded rationality itself, based on first principles.&lt;/p&gt;

&lt;p&gt;My research takes the latter approach. The goal is to find the simplest learning-to-optimize behavior which allows agents in large, complicated environments to none-the-less learn near-optimal policies in reasonable time. This is immediately applicable to any large agent-based model. Conversely, it may also suggest that even in a simpler setting, the transiton path to a long-term equilibrium may be very different from a purely rational-expectation baseline.&lt;/p&gt;

&lt;h2 id=&#34;toc_0&#34;&gt;Publications &amp;amp; Work in Progress&lt;/h2&gt;

&lt;ul&gt;
&lt;li&gt;Geanakoplos et al (2012), &amp;ldquo;Getting at Systemic Risk via an Agent-Based Model of the Housing Market.&amp;rdquo; &lt;em&gt;American Economic Review&lt;/em&gt;, 102(3): 53–58.

&lt;ul&gt;
&lt;li&gt;Efforts to address agent behavior in this highly complicated setting motivated my dissertation research.&lt;/li&gt;
&lt;li&gt;Paper &lt;a href=&#34;http://www.aeaweb.org/articles.php?doi=10.1257/aer.102.3.53&#34;&gt;here&lt;/a&gt;&lt;/li&gt;
&lt;li&gt;More in Peter Howitt&amp;rsquo;s Session 2 &lt;a href=&#34;http://bfi.uchicago.edu/events/macro-financial-modeling-meeting-spring-2013&#34;&gt;here&lt;/a&gt;; in particular, see the discussion by Sufi, Sims, Cochrane, Hansen, and others. Cochrane&amp;rsquo;s questions in particular are what I hope to address in my own research. (&lt;a href=&#34;https://web.archive.org/web/*/http://bfi.uchicago.edu/events/macro-financial-modeling-meeting-spring-2013&#34;&gt;Archived&lt;/a&gt;.)&lt;/li&gt;
&lt;li&gt;Rob Axtell discusses this model briefly near the end of &lt;a href=&#34;http://www.youtube.com/watch?v=c-sieJVR5TI&#34;&gt;this talk&lt;/a&gt;, around 12:40.&lt;/li&gt;
&lt;li&gt;Updated versions:

&lt;ul&gt;
&lt;li&gt;Slides, &lt;a href=&#34;https://www.bundesbank.de/Redaktion/EN/Downloads/Bundesbank/Research_Centre/Conferences/2014/2014_06_04_eltville_08_agent_based_model_of_housing_market_bubble_presentation.pdf?__blob=publicationFile&#34;&gt;2014&lt;/a&gt;&lt;/li&gt;
&lt;li&gt;Paper, &lt;a href=&#34;https://www.bundesbank.de/Redaktion/EN/Downloads/Bundesbank/Research_Centre/Conferences/2014/2014_06_05_eltville_10_axtell.pdf?__blob=publicationFile&#34;&gt;2014&lt;/a&gt;&lt;/li&gt;
&lt;/ul&gt;&lt;/li&gt;
&lt;/ul&gt;&lt;/li&gt;
&lt;/ul&gt;

&lt;hr /&gt;

&lt;ul&gt;
&lt;li&gt;My consumption research &lt;a href=&#34;http://editorialexpress.com/conference/CEF2012/program/CEF2012.html#31&#34;&gt;presented&lt;/a&gt; at &lt;a href=&#34;http://comp-econ.org/CEF_2012/index.htm&#34;&gt;CEF 2012&lt;/a&gt;.

&lt;ul&gt;
&lt;li&gt;Very preliminary version of the paper is &lt;a href=&#34;https://editorialexpress.com/cgi-bin/conference/download.cgi?db_name=CEF2012&amp;amp;paper_id=450&#34;&gt;linked here&lt;/a&gt;; an &lt;em&gt;&lt;strong&gt;extensively&lt;/strong&gt;&lt;/em&gt; updated version is in progress and will be out any day now&amp;hellip;&lt;/li&gt;
&lt;li&gt;CEF Slides can be found &lt;a href=&#34;https://docs.google.com/viewer?a=v&amp;amp;pid=sites&amp;amp;srcid=ZGVmYXVsdGRvbWFpbnxuYXRoYW5tcGFsbWVyfGd4OjEzNTYzNzExMTExMTAyMGE&#34;&gt;here&lt;/a&gt;.&lt;/li&gt;
&lt;/ul&gt;&lt;/li&gt;
&lt;/ul&gt;

&lt;hr /&gt;

&lt;ul&gt;
&lt;li&gt;The Heterogeneous-Agent Computational toolKit (HACK) with Chris Carroll: an effort to bring together cutting-edge tools from research and software development to create a modular, extensible set of code libraries for the easy creation of highly-heterogeneous agent models. These are to include models in which some &amp;ldquo;alpha&amp;rdquo; fraction of truly rational agents are mixed in with (1-alpha) non-optimizing agents. A truly rational agent in this setting, of course, must anticipate the actions and outcomes of both the non-optimizing agents as well as the optimizing agents.

&lt;ul&gt;
&lt;li&gt;This is a particularly exciting project &amp;ndash; much more coming soon!&lt;/li&gt;
&lt;/ul&gt;&lt;/li&gt;
&lt;/ul&gt;
</description>
    </item>
    
    <item>
      <title>CV</title>
      <link>http://npalmer.github.io/pages/cv/</link>
      <pubDate>Wed, 15 Apr 2015 21:21:44 EDT</pubDate>
      
      <guid>http://npalmer.github.io/pages/cv/</guid>
      <description>&lt;p&gt;Please contact me at &lt;a href=&#34;mailto:npalmer4@masonlive.gmu.edu&#34;&gt;npalmer4@masonlive.gmu.edu&lt;/a&gt; for a recent copy of my CV.&lt;/p&gt;

&lt;p&gt;Updated CV coming soon.&lt;/p&gt;
</description>
    </item>
    
    <item>
      <title>test</title>
      <link>http://npalmer.github.io/research/test/</link>
      <pubDate>Wed, 15 Apr 2015 10:57:16 EDT</pubDate>
      
      <guid>http://npalmer.github.io/research/test/</guid>
      <description></description>
    </item>
    
    <item>
      <title>about</title>
      <link>http://npalmer.github.io/about/</link>
      <pubDate>Wed, 15 Apr 2015 10:54:27 EDT</pubDate>
      
      <guid>http://npalmer.github.io/about/</guid>
      <description>&lt;p&gt;This is an about page. Will see how this rolls out.&lt;/p&gt;
</description>
    </item>
    
    <item>
      <title>welcome</title>
      <link>http://npalmer.github.io/post/welcome/</link>
      <pubDate>Fri, 06 Mar 2015 17:42:25 EST</pubDate>
      
      <guid>http://npalmer.github.io/post/welcome/</guid>
      <description>&lt;p&gt;Welcome to my homepage - very much a work in progress! I am currently a PhD candidate in the &lt;a href=&#34;http://www.css.gmu.edu/&#34;&gt;Department of Computational Social Science&lt;/a&gt; at George Mason University, specializing in simulation techniques applied to consumption theory (learning and welfare), macroeconomics (expecations, dynamics and estimation), and macro-finance (leverage, liquidity, &amp;amp; contagion). &lt;a href=&#34;http://www.css.gmu.edu/?q=node/27&#34;&gt;Rob&lt;/a&gt; &lt;a href=&#34;http://en.wikipedia.org/wiki/Robert_Axtell&#34;&gt;Axtell&lt;/a&gt; &lt;a href=&#34;http://ideas.repec.org/e/pax2.html&#34;&gt;is&lt;/a&gt; my advisor and I am having a blast working on interesting projects with a lot of very bright people.&lt;/p&gt;

&lt;p&gt;Note to prospective CSS students:  If you are interested in pursuing economics or finance in the CSS program, please feel free to send me an email at &lt;a href=&#34;mailto:npalmer4@masonlive.gmu.edu&#34;&gt;npalmer4@masonlive.gmu.edu&lt;/a&gt;. I&amp;rsquo;m always happy to talk about the work we do and am happy to offer (often blunt) advise as you survey the PhD landscape.&lt;/p&gt;

&lt;p&gt;A similar offer stands for current economists and researchers &amp;ndash; feel free to drop me an email, I&amp;rsquo;m happy to chat.&lt;/p&gt;
</description>
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