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Brás, G. (2023). Pillars of the Global Innovation Index by income level of economies: Longitudinal data (2011-2022) for researchers’ use. Data in Brief. 46

G. N. Brás,  "Pillars of the Global Innovation Index by income level of economies: Longitudinal data (2011-2022) for researchers’ use", in Data in Brief, vol. 46, 2023

@article{brás2023_1783048278742,
	author = "Brás, G.",
	title = "Pillars of the Global Innovation Index by income level of economies: Longitudinal data (2011-2022) for researchers’ use",
	journal = "Data in Brief",
	year = "2023",
	volume = "46",
	number = "",
	doi = "10.1016/j.dib.2022.108818",
	url = "https://www.sciencedirect.com/science/article/pii/S2352340922010216?via%3Dihub"
}

TY  - JOUR
TI  - Pillars of the Global Innovation Index by income level of economies: Longitudinal data (2011-2022) for researchers’ use
T2  - Data in Brief
VL  - 46
AU  - Brás, G.
PY  - 2023
SN  - 2352-3409
DO  - 10.1016/j.dib.2022.108818
UR  - https://www.sciencedirect.com/science/article/pii/S2352340922010216?via%3Dihub
AB  - 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.
ER  -