[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-112944-en":3,"doc-seo-112944-105":29,"detail-sidebar-cat-0-en-105":90},{"code":4,"msg":5,"data":6},0,"success",{"doc_id":7,"user_id":8,"nickname":9,"user_avatar":10,"doc_module":4,"category_id":11,"category_name":12,"doc_title":13,"doc_description":14,"doc_content":15,"file_id":16,"file_url":17,"file_type":18,"file_size":19,"view_count":4,"is_deleted":4,"is_public":20,"is_downloadable":20,"audit_status":20,"page_count":21,"language":22,"language_code":23,"site_id":24,"html_lang":23,"table_of_contents":25,"faqs":26,"seo_title":13,"seo_description":14,"update_tm":27,"read_time":28},112944,687197207919,"Theodora","https://ap-avatar.wpscdn.com/avatar/a000253d6f5f7c60be?x-image-process=image/resize,m_fixed,w_180,h_180&k=1779446848396160552",8,"Research & Report","Do Poor Countries Really Need More IT?","Productivity gaps across countries are often linked to differences in technological capabilities, prompting this paper to examine whether adoption of information technologies shows systematic cross-country variation. Evidence indicates a positive correlation between IT use and income that weakens over time, yet endogeneity and complementary production factors can overstate true cross-country differences. The study introduces two calibration approaches to correct for this issue. After controlling for endogenous industrial composition differences, no systematic relationship remains between income and IT capabilities.","Pub lic Disclosure Authorized Pub lic Disclosure Authorized  \nThe World Bank Economic Review, 34(1), 2020, 48–62 doi: 10.1093/wber/lhy022 Article  \nDo Poor Countries Really Need More IT? Maya Eden and Paul Gaggl  \nAbstract  \nProductivity differences across countries are often attributed to differences in technological capabilities. This paper asks whether there are systematic cross-country differences in the adoption of information technologies (IT). We document a positive correlation between IT use and income, which weakens over time. However, given that IT use is an endogenous outcome of both technological capabilities and the abundance of complementary factors of production, it tends to over-state the degree of cross-country differences in technology. We propose two novel calibration approaches to address this problem. After accounting for endogenous differences in industrial composition, we find that there is no systematic relationship between income and IT capabilities.  \nJEL classification: O14, O33, O57, E22  \nKeywords: ICT adoption, industrial composition, ICT capital stocks  \nCross-country differences in income have been shown to be driven primarily by cross-country differences in total factor productivity (TFP), which is typically measured as the Solow residual (Caselli 2008): after accounting for cross-country differences in inputs, the remaining differences in output are attributed to productivity. While the Solow residual was traditionally interpreted as reflecting the level of a country’s technology, today it is widely understood that other country characteristics are included in this residual as well, such as the degree of misallocation (Hsieh and Klenow 2009) .  \nConsequently, new approaches are being developed for assessing the direct contribution of crosscountry differences in technology to differences in productivity. The dominant approach has been based on measuring cross-country differences in capital types that embody technology. For example, Comin and Hobijn (2010) and Comin and Mestieri (2017) track the abundance of 25 types of technology-intensive capital across countries, such as the ratio of phone lines to GDP. Comin and Mestieri (2017) find that the intensity with which countries use recently invented types of technology-intensive capital, such as computers, is positively correlated with income per capita. Their findings suggest that differences in technological capabilities remain an important source of cross-country variation in output.  \nMaya Eden (corresponding author) is an assistant professor of economics at Brandeis University, Waltham, MA. Her email address [is meden@brandeis.edu. Paul Gaggl](is meden@brandeis.edu. Paul Gaggl) is an associate professor of economics at the University of North Carolina, Charlotte, NC. His email address is [pgaggl@uncc.edu. This](pgaggl@uncc.edu. This) paper served as background work for the World Bank’s World Development Report 2016 “Digital Dividends.” It reflects the authors’ own views and not necessarily those of the World Bank, its Executive Directors, or the countries they represent. The authors thank Asad Zaman for helpful research assistance and Robert Inklaar for assistance with technical details in the Penn World Tables. The authors are further grateful for helpful comments by Uwe Deichmann, Bart Hobijn, Aart Kraay, Deepak Mishra, Indhira Santos, Marc Schiffbauer, and Luis Serven, as well as seminar participants at the Federal Reserve Bank of Atlanta and for generous financial support from a World Bank RSB grant. A supplementary online appendix is available with this article at The World Bank Economic Review website.  \n© The Author(s) 2019 . Published by Oxford University Press on behalf of the International Bank for Reconstruction and Development / THE WORLD BANK.  \nAll rights reserved. For permissions, please e-mail: [journals.permissions@oup.com](journals.permissions@oup.com)  \nDownloaded from [https://academic.oup.com/wber/article/34/1/48/5541741]","cbCaiqLpXAW3FUv2","https://ap.wps.com/l/cbCaiqLpXAW3FUv2","pdf",396987,1,15,"English","en",105,"# Abstract\n## Research question and empirical pattern\n## Endogeneity and complementary factors\n## Calibration approaches and key findings","[{\"question\":\"What question does the paper ask about information technologies?\",\"answer\":\"It investigates whether there are systematic differences across countries in the adoption of information technologies (IT).\"},{\"question\":\"What does the evidence show about IT use and income over time?\",\"answer\":\"The paper finds a positive correlation between IT use and income, but that correlation weakens over time.\"},{\"question\":\"How do the authors address the risk of overstating cross-country technology differences?\",\"answer\":\"They propose two calibration approaches to 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