Brás Gonçalo Rodrigues
IN+, LARSyS, Center for Innovation, Technology and Policy Research, 'Instituto Superior Técnico', 'Universidade de Lisboa', Lisbon, Portugal.
Centre for Business and Economics Research (CeBER), Faculty of Economics, University of Coimbra, Coimbra, Portugal.
Data Brief. 2022 Dec 12;46:108818. doi: 10.1016/j.dib.2022.108818. eCollection 2023 Feb.
It is widely known that the Global Innovation Index reports are of unique value for research purposes. The aim of this work is to provide a panel data file with all pillars of the Global Innovation Index from 2011 until 2022, covering all available economies (149 in total) by income level. After the secondary data was gathered, it was reshaped in an exhaustive process that involved directly importing it from databases or manual insertion. Based on successive Global Innovation Index reports and World Bank data, this work attempts to provide a whole set of data on the incomes of world economies by using Gross Domestic Product per capita based on purchasing power parity (constant 2017 international $ and current international $) and Gross National Income per capita in current U.S. dollars (Atlas method). A descriptive analysis is also provided of data and inferences drawn based on the income differences between economies. The data compilation shared here has a singular relevance as it makes a large amount of structured information easier to access. Moreover, data from subsequent years or even from new entries of economies in the Global Innovation Index reports could be added to the data file. As a practical implication, this work should be considered a reliable tool for quantitative research directly or indirectly related with innovation topics (policies, ecosystems, technologies, programmes, among others), as it reduces the time-consuming process of gathering data.
众所周知，全球创新指数报告对于研究目的具有独特价值。这项工作的目的是提供一个面板数据文件，其中包含2011年至2022年全球创新指数的所有支柱，按收入水平涵盖所有可用经济体（总共149个）。收集二级数据后，在一个详尽的过程中对其进行了重塑，该过程涉及直接从数据库导入或手动插入。基于连续的全球创新指数报告和世界银行数据，这项工作试图通过使用基于购买力平价（2017年不变国际美元和当前国际美元）的人均国内生产总值以及以当前美元（阿特拉斯方法）计算的人均国民总收入，提供一套关于世界经济体收入的完整数据。还对基于经济体之间收入差异的数据和推断进行了描述性分析。这里共享的数据汇编具有独特的相关性，因为它使大量结构化信息更易于获取。此外，后续年份的数据，甚至全球创新指数报告中经济体的新条目数据都可以添加到数据文件中。作为一个实际影响，这项工作应被视为与创新主题（政策、生态系统、技术、项目等）直接或间接相关的定量研究的可靠工具，因为它减少了收集数据的耗时过程。
