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......@@ -715,4 +715,189 @@ Publisher: Nature Publishing Group},
publisher = {R Foundation for Statistical Computing},
author = {{R Core Team}},
year = {2020}
}
@misc{firke_janitor:_2021,
title = {janitor: {Simple} {Tools} for {Examining} and {Cleaning} {Dirty} {Data}},
copyright = {MIT + file LICENSE},
shorttitle = {janitor},
url = {https://CRAN.R-project.org/package=janitor},
abstract = {The main janitor functions can: perfectly format data.frame column names; provide quick counts of variable combinations (i.e., frequency tables and crosstabs); and isolate duplicate records. Other janitor functions nicely format the tabulation results. These tabulate-and-report functions approximate popular features of SPSS and Microsoft Excel. This package follows the principles of the "tidyverse" and works well with the pipe function \%{\textgreater}\%. janitor was built with beginning-to-intermediate R users in mind and is optimized for user-friendliness. Advanced R users can already do everything covered here, but with janitor they can do it faster and save their thinking for the fun stuff.},
urldate = {2021-02-01},
author = {Firke, Sam and Denney, Bill and Haid, Chris and Knight, Ryan and Grosser, Malte and Zadra, Jonathan},
month = jan,
year = {2021}
}
@misc{muller_here:_2020,
title = {here: {A} {Simpler} {Way} to {Find} {Your} {Files}},
copyright = {MIT + file LICENSE},
shorttitle = {here},
url = {https://CRAN.R-project.org/package=here},
abstract = {Constructs paths to your project's files. Declare the relative path of a file within your project with 'i\_am()'. Use the 'here()' function as a drop-in replacement for 'file.path()', it will always locate the files relative to your project root.},
urldate = {2021-02-01},
author = {Müller, Kirill and Bryan, Jennifer},
month = dec,
year = {2020},
keywords = {ReproducibleResearch}
}
@misc{piburn_wbstats:_2020,
title = {wbstats: {Programmatic} {Access} to {Data} and {Statistics} from the {World} {Bank} {API}},
copyright = {MIT + file LICENSE},
shorttitle = {wbstats},
url = {https://CRAN.R-project.org/package=wbstats},
abstract = {Search and download data from the World Bank Data API.},
urldate = {2021-02-01},
author = {Piburn, Jesse and UT-Battelle and LLC},
month = dec,
year = {2020},
keywords = {Econometrics}
}
@misc{buchta_isocodes:_2020,
title = {{ISOcodes}: {Selected} {ISO} {Codes}},
copyright = {GPL-2},
shorttitle = {{ISOcodes}},
url = {https://CRAN.R-project.org/package=ISOcodes},
abstract = {ISO language, territory, currency, script and character codes. Provides ISO 639 language codes, ISO 3166 territory codes, ISO 4217 currency codes, ISO 15924 script codes, and the ISO 8859 character codes as well as the UN M.49 area codes.},
urldate = {2021-02-01},
author = {Buchta, Christian and Hornik [aut, Kurt and cre},
month = dec,
year = {2020}
}
@misc{garnier_viridis:_2018,
title = {viridis: {Default} {Color} {Maps} from 'matplotlib'},
copyright = {MIT + file LICENSE},
shorttitle = {viridis},
url = {https://CRAN.R-project.org/package=viridis},
abstract = {Implementation of the 'viridis' - the default -, 'magma', 'plasma', 'inferno', and 'cividis' color maps for 'R'. 'viridis', 'magma', 'plasma', and 'inferno' are ported from 'matplotlib' {\textless}http://matplotlib.org/{\textgreater}, a popular plotting library for 'python'. 'cividis', was developed by Jamie R. Nuñez and Sean M. Colby. These color maps are designed in such a way that they will analytically be perfectly perceptually-uniform, both in regular form and also when converted to black-and-white. They are also designed to be perceived by readers with the most common form of color blindness (all color maps in this package) and color vision deficiency ('cividis' only).},
urldate = {2021-02-01},
author = {Garnier, Simon and Ross, Noam and Rudis, Bob and Sciaini, Marco and Scherer, Cédric},
month = mar,
year = {2018},
keywords = {Spatial}
}
@misc{rudis__[aut_hrbrthemes:_2020,
title = {hrbrthemes: {Additional} {Themes}, {Theme} {Components} and {Utilities} for 'ggplot2'},
copyright = {MIT + file LICENSE},
shorttitle = {hrbrthemes},
url = {https://CRAN.R-project.org/package=hrbrthemes},
abstract = {A compilation of extra 'ggplot2' themes, scales and utilities, including a spell check function for plot label fields and an overall emphasis on typography. A copy of the 'Google' font 'Roboto Condensed' {\textless}https://github.com/google/roboto/{\textgreater} is also included along with a copy of the 'IBM' 'Plex Sans' {\textless}https://github.com/IBM/type{\textgreater}, 'Titillium Web' {\textless}https://fonts.google.com/specimen/Titillium+Web{\textgreater}, and 'Public Sans' {\textless}https://github.com/uswds/public-sans/{\textgreater} fonts are also included to support their respective typography-oriented themes.},
urldate = {2021-02-01},
author = {Rudis [aut, Bob and cre and Kennedy, Patrick and Reiner, Philipp and support), Dan Wilson (Secondary axis and Adam, Xavier and Fonts), Google (Roboto Condensed \& Titillium Web and Font), IBM (Plex Sans and Font), Impallari Type (Public Sans and Barnett, Jacob and Leeper, Thomas J. and Meys, Joris},
month = mar,
year = {2020}
}
@misc{ram__[aut_wesanderson:_2018,
title = {wesanderson: {A} {Wes} {Anderson} {Palette} {Generator}},
copyright = {MIT + file LICENSE},
shorttitle = {wesanderson},
url = {https://CRAN.R-project.org/package=wesanderson},
abstract = {Palettes generated mostly from 'Wes Anderson' movies.},
urldate = {2021-02-01},
author = {Ram [aut, Karthik and cre and Wickham, Hadley and Richards, Clark and Baggett, Aaron},
month = apr,
year = {2018}
}
@misc{hester_glue:_2020,
title = {glue: {Interpreted} {String} {Literals}},
copyright = {MIT + file LICENSE},
shorttitle = {glue},
url = {https://CRAN.R-project.org/package=glue},
abstract = {An implementation of interpreted string literals, inspired by Python's Literal String Interpolation {\textless}https://www.python.org/dev/peps/pep-0498/{\textgreater} and Docstrings {\textless}https://www.python.org/dev/peps/pep-0257/{\textgreater} and Julia's Triple-Quoted String Literals {\textless}https://docs.julialang.org/en/v1.3/manual/strings/\#Triple-Quoted-String-Literals-1{\textgreater}.},
urldate = {2021-02-01},
author = {Hester, Jim},
month = aug,
year = {2020}
}
@misc{wilke_ggridges:_2021,
title = {ggridges: {Ridgeline} {Plots} in 'ggplot2'},
copyright = {GPL-2 {\textbar} file LICENSE},
shorttitle = {ggridges},
url = {https://CRAN.R-project.org/package=ggridges},
abstract = {Ridgeline plots provide a convenient way of visualizing changes in distributions over time or space. This package enables the creation of such plots in 'ggplot2'.},
urldate = {2021-02-01},
author = {Wilke, Claus O.},
month = jan,
year = {2021}
}
@misc{pedersen_patchwork:_2020,
title = {patchwork: {The} {Composer} of {Plots}},
copyright = {MIT + file LICENSE},
shorttitle = {patchwork},
url = {https://CRAN.R-project.org/package=patchwork},
abstract = {The 'ggplot2' package provides a strong API for sequentially building up a plot, but does not concern itself with composition of multiple plots. 'patchwork' is a package that expands the API to allow for arbitrarily complex composition of plots by, among others, providing mathematical operators for combining multiple plots. Other packages that try to address this need (but with a different approach) are 'gridExtra' and 'cowplot'.},
urldate = {2021-02-01},
author = {Pedersen, Thomas Lin},
month = dec,
year = {2020}
}
@misc{zhu__[aut_kableextra:_2020,
title = {{kableExtra}: {Construct} {Complex} {Table} with 'kable' and {Pipe} {Syntax}},
copyright = {MIT + file LICENSE},
shorttitle = {{kableExtra}},
url = {https://CRAN.R-project.org/package=kableExtra},
abstract = {Build complex HTML or 'LaTeX' tables using 'kable()' from 'knitr' and the piping syntax from 'magrittr'. Function 'kable()' is a light weight table generator coming from 'knitr'. This package simplifies the way to manipulate the HTML or 'LaTeX' codes generated by 'kable()' and allows users to construct complex tables and customize styles using a readable syntax.},
urldate = {2021-02-01},
author = {Zhu [aut, Hao and cre and Travison, Thomas and Tsai, Timothy and Beasley, Will and Xie, Yihui and Yu, GuangChuang and Laurent, Stéphane and Shepherd, Rob and Sidi, Yoni and Salzer, Brian and Gui, George and Fan, Yeliang and Murdoch, Duncan and Evans, Bill},
month = oct,
year = {2020}
}
@misc{wickham_readxl:_2019,
title = {readxl: {Read} {Excel} {Files}},
copyright = {GPL-3},
shorttitle = {readxl},
url = {https://CRAN.R-project.org/package=readxl},
abstract = {Import excel files into R. Supports '.xls' via the embedded 'libxls' C library {\textless}https://github.com/libxls/libxls{\textgreater} and '.xlsx' via the embedded 'RapidXML' C++ library {\textless}http://rapidxml.sourceforge.net{\textgreater}. Works on Windows, Mac and Linux without external dependencies.},
urldate = {2021-02-01},
author = {Wickham, Hadley and Bryan, Jennifer and attribution), RStudio (Copyright holder of all R. code {and} all C/C++ code without explicit copyright and code), Marcin Kalicinski (Author of included RapidXML and code), Komarov Valery (Author of included libxls and code), Christophe Leitienne (Author of included libxls and code), Bob Colbert (Author of included libxls and code), David Hoerl (Author of included libxls and code), Evan Miller (Author of included libxls},
month = mar,
year = {2019}
}
@misc{gohel_flextable:_2021,
title = {flextable: {Functions} for {Tabular} {Reporting}},
copyright = {GPL-3},
shorttitle = {flextable},
url = {https://CRAN.R-project.org/package=flextable},
abstract = {Create pretty tables for 'HTML', 'PDF', 'Microsoft Word' and 'Microsoft PowerPoint' documents from 'R Markdown'. Functions are provided to let users create tables, modify and format their content. It also extends package 'officer' that does not contain any feature for customized tabular reporting.},
urldate = {2021-02-01},
author = {Gohel, David and Fazilleau, Quentin and output), Maxim Nazarov (rmarkdown for docx and Robert, Titouan and footnotes), Michael Barrowman (inline and reference), Atsushi Yasumoto (support for bookdown cross and objects), Paul Julian (support for gam},
month = jan,
year = {2021},
keywords = {ReproducibleResearch}
}
@misc{south_rworldmap:_2016,
title = {rworldmap: {Mapping} {Global} {Data}},
copyright = {GPL-2 {\textbar} GPL-3 [expanded from: GPL (≥ 2)]},
shorttitle = {rworldmap},
url = {https://CRAN.R-project.org/package=rworldmap},
abstract = {Enables mapping of country level and gridded user datasets.},
urldate = {2021-02-01},
author = {South, Andy},
month = feb,
year = {2016},
keywords = {OfficialStatistics, Spatial}
}
@misc{arnold__<https://orcid.org/0000-0001-9953-3904>_ggthemes:_2021,
title = {ggthemes: {Extra} {Themes}, {Scales} and {Geoms} for 'ggplot2'},
copyright = {GPL-2},
shorttitle = {ggthemes},
url = {https://CRAN.R-project.org/package=ggthemes},
abstract = {Some extra themes, geoms, and scales for 'ggplot2'. Provides 'ggplot2' themes and scales that replicate the look of plots by Edward Tufte, Stephen Few, 'Fivethirtyeight', 'The Economist', 'Stata', 'Excel', and 'The Wall Street Journal', among others. Provides 'geoms' for Tufte's box plot and range frame.},
urldate = {2021-02-01},
author = {Arnold ({\textless}https://orcid.org/0000-0001-9953-3904{\textgreater}), Jeffrey B. and Daroczi, Gergely and Werth, Bo and Weitzner, Brian and Kunst, Joshua and Auguie, Baptise and Rudis, Bob and package.), Hadley Wickham (Code from the ggplot2 and package), Justin Talbot (Code from the labeling and London, Joshua},
month = jan,
year = {2021}
}
\ No newline at end of file
......@@ -83,7 +83,7 @@ The final demand expenditure, and thus the national footprint, is typically disa
2) HBS: European household budget survey from EUROSTAT, macro-data, from : https://ec.europa.eu/eurostat/web/household-budget-surveys/database [accessed on 22.05.2020] [@eurostat_database_nodate]
We discuss each of these in turn, including additional data inputs needed to complement the HBS. We then present our methodology for our results in the main paper, and data gaps and limitations. The final 'supplementary materials and methods' section presents an alternative methodology, and the final section of this supplementary information document presents supplementary results from the methodology used in the main paper and the alternative methodology.
We discuss each of these in turn, including additional data inputs needed to complement the HBS. We then present our methodology for our results in the main paper, and data gaps and limitations. The final 'supplementary materials and methods' section presents an alternative methodology, and the final section of this supplementary information document presents supplementary results from the methodology used in the main paper and the alternative methodology. The whole analysis was performed in RStudio [@r_core_team_r:_2020], using a variety of R packages [@wickham_welcome_2019 ].
## EXIOBASE
......
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