1.0Center for Economic and Policy Researchhttps://cepr.netadminhttps://cepr.net/author/admin/rich600338<blockquote class="wp-embedded-content"><a href="https://cepr.net/economists-use-fuzzy-graphs-to-challenge-data-on-the-human-cost-of-trump-sanctions-on-venezuela/">Economists Use “Fuzzy Graphs” to Challenge Data on the Human Cost of Trump Sanctions on Venezuela</a></blockquote> <script type='text/javascript'> <!--//--><![CDATA[//><!-- /*! This file is auto-generated */ !function(c,d){"use strict";var e=!1,n=!1;if(d.querySelector)if(c.addEventListener)e=!0;if(c.wp=c.wp||{},!c.wp.receiveEmbedMessage)if(c.wp.receiveEmbedMessage=function(e){var t=e.data;if(t)if(t.secret||t.message||t.value)if(!/[^a-zA-Z0-9]/.test(t.secret)){for(var r,a,i,s=d.querySelectorAll('iframe[data-secret="'+t.secret+'"]'),n=d.querySelectorAll('blockquote[data-secret="'+t.secret+'"]'),o=0;o<n.length;o++)n[o].style.display="none";for(o=0;o<s.length;o++)if(r=s[o],e.source===r.contentWindow){if(r.removeAttribute("style"),"height"===t.message){if(1e3<(i=parseInt(t.value,10)))i=1e3;else if(~~i<200)i=200;r.height=i}if("link"===t.message)if(a=d.createElement("a"),i=d.createElement("a"),a.href=r.getAttribute("src"),i.href=t.value,i.host===a.host)if(d.activeElement===r)c.top.location.href=t.value}}},e)c.addEventListener("message",c.wp.receiveEmbedMessage,!1),d.addEventListener("DOMContentLoaded",t,!1),c.addEventListener("load",t,!1);function t(){if(!n){n=!0;for(var e,t,r=-1!==navigator.appVersion.indexOf("MSIE 10"),a=!!navigator.userAgent.match(/Trident.*rv:11\./),i=d.querySelectorAll("iframe.wp-embedded-content"),s=0;s<i.length;s++){if(!(e=i[s]).getAttribute("data-secret"))t=Math.random().toString(36).substr(2,10),e.src+="#?secret="+t,e.setAttribute("data-secret",t);if(r||a)(t=e.cloneNode(!0)).removeAttribute("security"),e.parentNode.replaceChild(t,e)}}}}(window,document); //--><!]]> </script><iframe sandbox="allow-scripts" security="restricted" src="https://cepr.net/economists-use-fuzzy-graphs-to-challenge-data-on-the-human-cost-of-trump-sanctions-on-venezuela/embed/" width="600" height="338" title="“Economists Use “Fuzzy Graphs” to Challenge Data on the Human Cost of Trump Sanctions on Venezuela” — Center for Economic and Policy Research" frameborder="0" marginwidth="0" marginheight="0" scrolling="no" class="wp-embedded-content"></iframe>In our paper, “Sanctions as Collective Punishment: The Case of Venezuela,” we looked at some of the ways in which the sanctions on Venezuela imposed by the US government curtail access to essential and life-saving imports, and some of the data on impacts such as mortality. We concluded that US economic sanctions since August 2017 have likely caused a dire rise in mortality and a grave aggravation of Venezuela’s economic crisis. We concluded that the sanctions imposed since January will be much more devastating in terms of increased hunger and mortality, and of economic losses, than have the prior US executive orders and other economic sanctions. The fact that these sanctions cause extreme suffering and deaths should not be a matter of dispute. If you cut off access to medicines, medical equipment, imports needed to maintain water and sanitation infrastructure, and for spare parts, and you prevent an economy that is in a deep depression from recovering, a lot of people are going to suffer diseases and premature mortality. Economists Miguel Angel Santos and Ricardo Hausmann have challenged our claim that the sanctions dramatically worsened Venezuela’s crisis of oil production and exports, and therefore of the ability to finance food and medical imports. In what follows, we look at their arguments, which are based on easily identified 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