<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Paul Beaudry | Macro Paper Warehouse</title><link>https://macropaperwarehouse.com/authors/paul-beaudry/</link><description>Paul Beaudry</description><generator>Hugo -- gohugo.io</generator><language>en-us</language><atom:link href="https://macropaperwarehouse.com/authors/paul-beaudry/index.xml" rel="self" type="application/rss+xml"/><item><title>Stock Prices, News, and Economic Fluctuations</title><link>https://macropaperwarehouse.com/papers/stock-prices-news-and-economic-fluctuations/</link><guid>https://macropaperwarehouse.com/papers/stock-prices-news-and-economic-fluctuations/</guid><description>&lt;p&gt;This 2006 &lt;em&gt;American Economic Review&lt;/em&gt; paper (circulated as NBER Working Paper 10548, June 2004) develops a novel way to use the joint behavior of stock prices and measured total factor productivity (TFP) to discriminate between business-cycle theories, and in doing so coins the term &amp;ldquo;news shock&amp;rdquo; for what becomes one of the central concepts in the subsequent macroeconomics literature. The authors&amp;rsquo; method is to construct two different orthogonalized versions of the same reduced-form TFP/stock-price system &amp;ndash; one isolating the stock-price innovation that is contemporaneously uncorrelated with TFP, the other isolating the shock that drives TFP&amp;rsquo;s permanent (long-run) movements &amp;ndash; and to ask whether these two independently-derived shock series turn out to be the same disturbance. The paper shows this is a sharp test: in standard models where business cycles are driven by surprise (unanticipated) productivity shocks, the two series should be orthogonal to each other, but in a world where technological opportunities are first recognized and priced into the stock market and only later show up in measured productivity, the two series should be nearly identical. Using postwar U.S. data, the authors find the latter: the correlation between the two independently-identified shock series is consistently around 0.97-0.999 across many specifications, and when TFP is corrected for variable factor utilization (notably using the Basu-Fernald-Kimball measure), the shock identified this way causes an immediate boom in consumption, investment, and hours worked that precedes any actual rise in productivity by roughly three to four years &amp;ndash; a pattern the authors argue is &amp;ldquo;quite easily&amp;rdquo; explained by a model in which agents anticipate future technology and poorly explained by standard surprise-technology-shock models. The authors estimate this single shock accounts for roughly half of business-cycle fluctuations, and conclude that business-cycle theory needs models in which the recognition of future technological opportunities itself generates a current boom in spending and hours that precedes the productivity gains that eventually justify it.&lt;/p&gt;</description></item></channel></rss>