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So, inspired by Brian and the general spirit of end-of-year reflection, some thoughts on what I’ve read this year. According to my reference manager software, I’ve read 183 papers this year, which is somewhat overstated because many were read last year but are dated incorrectly, and a substantial portion of the list contains slides, lecture notes, or other documents not quite meriting the status of article.

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Inspired by the release of a new and quite clear explainer on the topic by Hahn, Kuersteiner, and Mazzocco (HKM) amid a growing trend of using microeconomic data to learn about macroeconomic or aggregate effects, I believe it’s a good time to write something about what microeconometricians and applied microeconomists ought to know about dealing with aggregate effects. Broadly, this refers to any time-dependent variability in a data-generating process that can’t be modeled is independent across individual observations.

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In an effort to get into the habit of writing down my thoughts, I am, ill-advisedly, experimenting with starting a blog. I expect to cover mainly topics in statistics, econometrics, machine learning, and numerical computation, with some chance of also entertaining thoughts on how these relate to macroeconomics. Actual macroeconomics will be kept to a minimum, as that topic attracts sufficient attention online already, except in the case that I lack the self-control to avoid arguing on the internet.

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Attention Conservation Notice: Over 5000 words about math that I don’t particularly understand, written mostly to clarify my thoughts. A reader familiar with the topic (roughly, spectral or harmonic theory on graphs and manifolds) will find little here new except possibly misconceptions, while a reader not familiar with the topic will find minimal motivation and poorly explained jargon. The ideal reader is a pedant or troll who can tell me why I’m wrong about everything.

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Posterior Samplers for Turing.jl /*! jQuery v1.11.3 | (c) 2005, 2015 jQuery Foundation, Inc. | jquery.org/license */ !function(a,b){"object"==typeof module&&"object"==typeof module.exports?module.exports=a.document?b(a,!0):function(a){if(!a.document)throw new Error("jQuery requires a window with a document");return b(a)}:b(a)}("undefined"!=typeof window?window:this,function(a,b){var c=[],d=c.slice,e=c.concat,f=c.push,g=c.indexOf,h={},i=h.toString,j=h.hasOwnProperty,k={},l="1.11.3",m=function(a,b){return new m.fn.init(a,b)},n=/^[\s\uFEFF\xA0]+|[\s\uFEFF\xA0]+$/g,o=/^-ms-/,p=/-([\da-z])/gi,q=function(a,b){return b.toUpperCase()};m.fn=m.prototype={jquery:l,constructor:m,selector:"",length:0,toArray:function(){return d.call(this)},get:function(a){return null!=a?0a?this[a+this.length]:this[a]:d.call(this)},pushStack:function(a){var b=m.merge(this.constructor(),a);return b.prevObject=this,b.context=this.context,b},each:function(a,b){return m.each(this,a,b)},map:function(a){return this.pushStack(m.map(this,function(b,c){return a.call(b,c,b)}))},slice:function(){return this.pushStack(d.apply(this,arguments))},first:function(){return this.eq(0)},last:function(){return this.eq(-1)},eq:function(a){var b=this.length,c=+a+(0a?b:0);return this.pushStack(c=0&&bc?[this[c]]:[])},end:function(){return this.prevObject||this.constructor(null)},push:f,sort:c.sort,splice:c.splice},m.extend=m.fn.extend=function(){var a,b,c,d,e,f,g=arguments[0]||{},h=1,i=arguments.length,j=!1;for("boolean"==typeof g&&(j=g,g=arguments[h]||{},h++),"object"==typeof g||m.isFunction(g)||(g={}),h===i&&(g=this,h--);ih;h++)if(null!=(e=arguments[h]))for(d in e)a=g[d],c=e[d],g!==c&&(j&&c&&(m.isPlainObject(c)||(b=m.isArray(c)))?(b?(b=!1,f=a&&m.isArray(a)?a:[]):f=a&&m.isPlainObject(a)?a:{},g[d]=m.extend(j,f,c)):void 0!==c&&(g[d]=c));return g},m.extend({expando:"jQuery"+(l+Math.random()).replace(/\D/g,""),isReady:!0,error:function(a){throw new Error(a)},noop:function(){},isFunction:function(a){return"function"===m.type(a)},isArray:Array.isArray||function(a){return"array"===m.type(a)},isWindow:function(a){return null!=a&&a==a.window},isNumeric:function(a){return!m.isArray(a)&&a-parseFloat(a)+1=0},isEmptyObject:function(a){var b;for(b in a)return!1;return!0},isPlainObject:function(a){var b;if(!a||"object"!==m.type(a)||a.nodeType||m.isWindow(a))return!1;try{if(a.constructor&&!j.call(a,"constructor")&&!j.call(a.constructor.prototype,"isPrototypeOf"))return!1}catch(c){return!1}if(k.ownLast)for(b in a)return j.call(a,b);for(b in a);return void 0===b||j.call(a,b)},type:function(a){return null==a?

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