{"id":8348,"date":"2016-04-07T09:46:43","date_gmt":"2016-04-07T09:46:43","guid":{"rendered":"http:\/\/revoscience.com\/en\/?p=8348"},"modified":"2016-04-07T09:46:43","modified_gmt":"2016-04-07T09:46:43","slug":"how-network-effects-hurt-economies","status":"publish","type":"post","link":"https:\/\/www.revoscience.com\/en\/how-network-effects-hurt-economies\/","title":{"rendered":"How network effects hurt economies"},"content":{"rendered":"

Study reveals how woes in one industry can harm others, too.<\/strong><\/em><\/span><\/p>\n

\"\u201cRelatively<\/a>
\u201cRelatively small shocks can become magnified and then become shocks you have to contend with [on a large scale],\u201d says MIT economist Daron Acemoglu.
Image: Christine Daniloff\/MIT<\/figcaption><\/figure>\n

CAMBRIDGE, Mass.<\/strong> —\u00a0When large-scale economic struggles hit a region, a country, or even a continent, the explanations tend to be big in nature as well.<\/span><\/p>\n

Macroeconomists \u2014 who study large economic phenomena \u2014 often look for sweeping explanations of what has gone wrong, such as declines in productivity, consumer demand, or investor confidence, or significant changes in monetary policy.<\/span><\/p>\n

But what if large-scale economic slumps can be traced to declines in relatively narrow industrial sectors? A newly published study co-authored by an MIT economist provides evidence that economic problems may often have smaller points of origin and then spread as part of a network effect.<\/span><\/p>\n

\u201cRelatively small shocks can become magnified and then become shocks you have to contend with [on a large scale],\u201d says MIT economist Daron Acemoglu, one of the authors of a paper detailing the research.<\/span><\/p>\n

The findings run counter to \u201creal business cycle theory,\u201d which became popular in the 1970s and holds that smaller, industry-specific effects tend to get swamped by larger, economy-wide trends.<\/span><\/p>\n

More precisely, Acemoglu and his colleagues have found cases where industry-specific problems lead to six-fold declines in production across the U.S. economy as a whole. For example, for every dollar of value-added growth lost in the manufacturing industries because of competition from China, six dollars of value-added growth were lost in the U.S. economy as a whole.<\/span><\/p>\n

[pullquote]One of the key findings of the study, which confirms and builds on existing theory, is that demand-side shocks spread almost exclusively \u201cupstream\u201d in economic networks, and supply-side shocks spread almost exclusively \u201cdownstream.\u201d\u00a0[\/pullquote]<\/p>\n

The researchers also examined four different types of economic shocks to the U.S. economy that occurred over the years 1991-2009, and quantified the extent to which those problems spread \u201cupstream\u201d or \u201cdownstream\u201d of the central industry in question \u2014 that is, whether the network effects more strongly hurt industrial suppliers or businesses that sell products and provide services to consumers.<\/span><\/p>\n

All told, the researchers state in the paper, \u201cOur results suggest that the transmission of various different types of shocks through economic networks and industry interlinkages could have first-order implications for the macroeconomy.\u201d<\/span><\/p>\n

The paper, \u201cNetworks and the Macroeconomy: An Empirical Exploration,\u201d is being published in the\u00a0NBER Macroeconomics Annual<\/em>, by the National Bureau of Economic Research. The co-authors are Acemoglu, the Elizabeth and James Killian Professor of Economics at MIT; Ufuk Akcigit, an economist at the University of Chicago; and William Kerr, a professor at Harvard Business School.<\/span><\/p>\n

Upstream or downstream<\/strong><\/span><\/p>\n

Acemoglu, Afcigit, and Kerr used manufacturing data from the National Bureau of Economic Analysis, and industry-specific data from the Bureau of Economic Analysis, to examine four economic shocks hitting the U.S. economy during that 1991-2009 period. Those were: the impact of export competition on U.S. manufacturing; changes in federal government spending, which affect areas such as defense manufacturing; changes in Total Factor Productivity; and variation in levels of patents coming from foreign industry.<\/span><\/p>\n

As noted, the network effect of manufacturing competition with China made the overall economic shock about six times as great as it was to manufacturing alone. (This research built on previously published work by economists David Autor of MIT, David Dorn of the University of Zurich, and Gordon Hanson of the University of California at San Diego, sometimes in collaboration with Acemoglu and MIT graduate student Brendan Price.)<\/span><\/p>\n

In studying changes in the levels of federal spending after 1992, the researchers found a network effect about three to five times as large as that on directly-affected firms alone.<\/span><\/p>\n

The decline in Total Factor Productivity constituted a smaller economic shock but one with a larger network effect, of more than 15 times the initial impact. In the case of increased foreign patenting (another way of looking at corporate productivity), the researchers found a network effect similar to that of Total Factor Productivity.<\/span><\/p>\n

The first two of these areas constitute demand-side shocks, affecting consumer demand for the products in question. The last two are supply-side shocks, affecting firms\u2019 ability to be good at what they do.<\/span><\/p>\n

To see why, Acemoglu suggests, consider an auto manufacturer, which has parts suppliers upstream and is linked with auto dealers, repair shops, and other businesses downstream.<\/span><\/p>\n

When auto demand drops, \u201cIt\u2019s the suppliers [upstream] that get affected,\u201d Acemoglu explains. \u201cYou\u2019re going to cut the production of autos, and you buy less of each of the inputs,\u201d or supplies.<\/span><\/p>\n

Now suppose the supply changes, perhaps due to an increase in manufacturing efficiency, which makes cars cheaper. In that case, Acemoglu adds, \u201cPeople who use auto as inputs will buy more of them\u201d \u2014 picture a delivery company \u2014 \u201cso that shock will get transmitted to the downstream industries.\u201d<\/span><\/p>\n

To be sure, it is widely understood that the auto industry, like almost every other industry, is situated within a larger economic network. Yet estimating the spillover effects of struggles within any given industry, in the quantitative form of the current study, is rarely done.<\/span><\/p>\n

\u201cGiven the importance of this, it\u2019s surprising how scant the evidence is,\u201d Acemoglu says.\u00a0\u00a0<\/span><\/p>\n

Multiplying our knowledge<\/strong><\/span><\/p>\n

This could have policy implications: Proponents of government investment, such as the so-called stimulus bill of 2009, the American Recovery and Reinvestment Act, have contended that government spending creates a \u201cmultiplier effect\u201d in terms of growth. Opponents of such legislation sometimes assert that government spending crowds out private investment and thus does not generate more growth than would otherwise occur. In theory, a more granular understanding of these network effects could help describe and define what a multiplier effect is, and in which industrial areas it may be the most pronounced.<\/span><\/p>\n

To be clear, Acemoglu adds, it is always hard to define precisely what the origins of a negative economic shock may be. Is it overseas competition, a lack of innovation, or other factors \u2014 some of which may indeed be economy-wide in nature? The more economists can identify such shocks, the better they can use the current paper\u2019s framework to trace their effects.<\/span><\/p>\n

\u201cThere are many things going on, and there is the possibility that a whole [economic] area has been hit by a negative shock,\u201d Acemoglu says. \u201cIt\u2019s hard to distinguish all of these channels. That\u2019s why you need systematic work.\u201d<\/span><\/p>\n","protected":false},"excerpt":{"rendered":"

A newly published study co-authored by an MIT economist provides evidence that economic problems may often have smaller points of origin and then spread as part of a network effect.<\/p>\n","protected":false},"author":6,"featured_media":8349,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[34,28],"tags":[],"class_list":["post-8348","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-economics","category-techbiz"],"featured_image_urls":{"full":["https:\/\/www.revoscience.com\/en\/wp-content\/uploads\/2016\/04\/MIT-macroeconomy_0.jpg",639,426,false],"thumbnail":["https:\/\/www.revoscience.com\/en\/wp-content\/uploads\/2016\/04\/MIT-macroeconomy_0-150x150.jpg",150,150,true],"medium":["https:\/\/www.revoscience.com\/en\/wp-content\/uploads\/2016\/04\/MIT-macroeconomy_0-300x200.jpg",300,200,true],"medium_large":["https:\/\/www.revoscience.com\/en\/wp-content\/uploads\/2016\/04\/MIT-macroeconomy_0.jpg",639,426,false],"large":["https:\/\/www.revoscience.com\/en\/wp-content\/uploads\/2016\/04\/MIT-macroeconomy_0.jpg",639,426,false],"1536x1536":["https:\/\/www.revoscience.com\/en\/wp-content\/uploads\/2016\/04\/MIT-macroeconomy_0.jpg",639,426,false],"2048x2048":["https:\/\/www.revoscience.com\/en\/wp-content\/uploads\/2016\/04\/MIT-macroeconomy_0.jpg",639,426,false],"ultp_layout_landscape_large":["https:\/\/www.revoscience.com\/en\/wp-content\/uploads\/2016\/04\/MIT-macroeconomy_0.jpg",639,426,false],"ultp_layout_landscape":["https:\/\/www.revoscience.com\/en\/wp-content\/uploads\/2016\/04\/MIT-macroeconomy_0.jpg",639,426,false],"ultp_layout_portrait":["https:\/\/www.revoscience.com\/en\/wp-content\/uploads\/2016\/04\/MIT-macroeconomy_0.jpg",600,400,false],"ultp_layout_square":["https:\/\/www.revoscience.com\/en\/wp-content\/uploads\/2016\/04\/MIT-macroeconomy_0.jpg",600,400,false],"newspaper-x-single-post":["https:\/\/www.revoscience.com\/en\/wp-content\/uploads\/2016\/04\/MIT-macroeconomy_0.jpg",639,426,false],"newspaper-x-recent-post-big":["https:\/\/www.revoscience.com\/en\/wp-content\/uploads\/2016\/04\/MIT-macroeconomy_0.jpg",540,360,false],"newspaper-x-recent-post-list-image":["https:\/\/www.revoscience.com\/en\/wp-content\/uploads\/2016\/04\/MIT-macroeconomy_0.jpg",95,63,false],"web-stories-poster-portrait":["https:\/\/www.revoscience.com\/en\/wp-content\/uploads\/2016\/04\/MIT-macroeconomy_0.jpg",639,426,false],"web-stories-publisher-logo":["https:\/\/www.revoscience.com\/en\/wp-content\/uploads\/2016\/04\/MIT-macroeconomy_0.jpg",96,64,false],"web-stories-thumbnail":["https:\/\/www.revoscience.com\/en\/wp-content\/uploads\/2016\/04\/MIT-macroeconomy_0.jpg",150,100,false]},"author_info":{"info":["Amrita Tuladhar"]},"category_info":"Economics<\/a> Tech<\/a>","tag_info":"Tech","comment_count":"0","_links":{"self":[{"href":"https:\/\/www.revoscience.com\/en\/wp-json\/wp\/v2\/posts\/8348","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.revoscience.com\/en\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.revoscience.com\/en\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.revoscience.com\/en\/wp-json\/wp\/v2\/users\/6"}],"replies":[{"embeddable":true,"href":"https:\/\/www.revoscience.com\/en\/wp-json\/wp\/v2\/comments?post=8348"}],"version-history":[{"count":0,"href":"https:\/\/www.revoscience.com\/en\/wp-json\/wp\/v2\/posts\/8348\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.revoscience.com\/en\/wp-json\/wp\/v2\/media\/8349"}],"wp:attachment":[{"href":"https:\/\/www.revoscience.com\/en\/wp-json\/wp\/v2\/media?parent=8348"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.revoscience.com\/en\/wp-json\/wp\/v2\/categories?post=8348"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.revoscience.com\/en\/wp-json\/wp\/v2\/tags?post=8348"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}