Perceptions of Electoral Integrity, (PEI-8.0)

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Garnett, Holly Ann; James, Toby S.; MacGregor, Madison, 2022, "Perceptions of Electoral Integrity, (PEI-8.0)", https://doi.org/10.7910/DVN/YSNYXD, Harvard Dataverse, V1, UNF:6:lINJ6KG6BcEwGIXz7tM4Yg== [fileUNF]

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Description	This dataset by the Electoral Integrity Project evaluates the quality of elections held around the world. Based on a rolling survey collecting the views of election experts, this research provides independent and reliable evidence to compare whether countries meet international standards of electoral integrity. PEI-8.0 cumulative release covers 480 national parliamentary and presidential contests held worldwide in 169 countries from 1 July 2012 to 31 December 2021. For each contest, approximately 40 election experts receive an electronic invitation to fill the survey. The survey includes assessments from 4,591 election experts, with a mean response rate of 23%. The study collects 49 indicators to compare elections. These indicators are clustered to evaluate eleven stages in the electoral cycle as well as generating an overall summary Perception of Electoral Integrity (PEI) 100-point index and comparative ranking. The datasets are available for analysis at three levels: COUNTRY-level (169 observations); ELECTION-level (479 observations), and also EXPERT-level (4,590 observations). Each dataset can be downloaded in STATA, CSV, and EXCEL formats. (2022-05-19)
Subject	Social Sciences
Keyword	Elections, Perceptions of Electoral Integrity (PEI), Electoral Integrity Project, Electoral integrity, Electoral fraud, Voting behavior, Cross-national elections, Global, Comparative politics, Free and fair
Related Publication	Garnett, Holly Ann, Toby S. James, and Madison MacGregor. 2022. Electoral Integrity Global Report, 2019-2021.https://www.electoralintegrityproject.com/globalreport2019-2021
License/Data Use Agreement	Custom Dataset Terms

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	1 to 10 of 10 Files	Original Format Archival Format (.tab)
	PEI 8.0 Codebook.docx MS Word - 380.0 KB Published May 18, 2022 660 Downloads MD5: e4b2af3c15c8ac542f4e60566754c1f7 Codebook describing the PEI 8.0 data	Access File File Access Public Download Options MS Word Download Metadata Data File Citation Download EndNote XML Download RIS Download BibTeX
	PEI country-level data (PEI_8.0)-1.tab Tabular Data - 249.6 KB Published May 18, 2022 835 Downloads 202 Variables, 169 Observations UNF:6:iIQCv+uzXXjR/5jdhnKiSQ== PEI 8.0 data at the country level, STATA data format	Preview "PEI country-level data (PEI_8.0)-1.tab" Preview "PEI country-level data (PEI_8.0)-1.tab" Access File File Access Public Download Options Stata 14 Binary (Original File Format) Tab-Delimited RData Download Metadata DDI Codebook v2 Data File Citation Download EndNote XML Download RIS Download BibTeX Explore Options Data Explorer v2
	PEI country-level data (PEI_8.0).tab Tabular Data - 90.8 KB Published May 18, 2022 473 Downloads 202 Variables, 169 Observations UNF:6:+UZ6MYxMJbDS4ZaXlsCisA== PEI 8.0 data at the country level, in the .csv format	Preview "PEI country-level data (PEI_8.0).tab" Preview "PEI country-level data (PEI_8.0).tab" Access File File Access Public Download Options Comma Separated Values (Original File Format) Tab-Delimited RData Download Metadata DDI Codebook v2 Data File Citation Download EndNote XML Download RIS Download BibTeX Explore Options Data Explorer v2
	PEI country-level data (PEI_8.0).xlsx MS Excel Spreadsheet - 264.3 KB Published May 18, 2022 551 Downloads MD5: 4bba314a376f2f398713851d062dbe9d PEI 8.0 data at the country level, in .xlsx format	Access File File Access Public Download Options MS Excel Spreadsheet Download Metadata Data File Citation Download EndNote XML Download RIS Download BibTeX
	PEI election-level data (PEI_8.0)-1.tab Tabular Data - 573.0 KB Published May 18, 2022 411 Downloads 206 Variables, 479 Observations UNF:6:U4l9YBgdmHxxWVEoDTUXtg== PEI 8.0 data at the election level, in STATA data format	Preview "PEI election-level data (PEI_8.0)-1.tab" Preview "PEI election-level data (PEI_8.0)-1.tab" Access File File Access Public Download Options Stata 14 Binary (Original File Format) Tab-Delimited RData Download Metadata DDI Codebook v2 Data File Citation Download EndNote XML Download RIS Download BibTeX Explore Options Data Explorer v2
	PEI election-level data (PEI_8.0).tab Tabular Data - 221.0 KB Published May 18, 2022 406 Downloads 206 Variables, 479 Observations UNF:6:+nBEVHq6KqJyZc1fO7Rbqw== PEI 8.0 data at the election level, in the .csv format	Preview "PEI election-level data (PEI_8.0).tab" Preview "PEI election-level data (PEI_8.0).tab" Access File File Access Public Download Options Comma Separated Values (Original File Format) Tab-Delimited RData Download Metadata DDI Codebook v2 Data File Citation Download EndNote XML Download RIS Download BibTeX Explore Options Data Explorer v2
	PEI election-level data (PEI_8.0).xlsx MS Excel Spreadsheet - 655.6 KB Published May 18, 2022 456 Downloads MD5: 71a88478341c8ef3d3187662beb619c9 PEI 8.0 data at the election level, in .xlsx format	Access File File Access Public Download Options MS Excel Spreadsheet Download Metadata Data File Citation Download EndNote XML Download RIS Download BibTeX
	PEI expert-level data (PEI_8.0)-1.tab Tabular Data - 7.6 MB Published May 18, 2022 399 Downloads 198 Variables, 4590 Observations UNF:6:1oXmin8xbrYYo/xBnO4Zpw== PEI 8.0 data at the expert level, in the .csv format	Preview "PEI expert-level data (PEI_8.0)-1.tab" Preview "PEI expert-level data (PEI_8.0)-1.tab" Access File File Access Public Download Options Comma Separated Values (Original File Format) Tab-Delimited RData Download Metadata DDI Codebook v2 Data File Citation Download EndNote XML Download RIS Download BibTeX Explore Options Data Explorer v2
	PEI expert-level data (PEI_8.0).tab Tabular Data - 2.5 MB Published May 18, 2022 405 Downloads 198 Variables, 4590 Observations UNF:6:Sfnzg/z1YkmQA9DLNChMmw== PEI 8.0 data at the expert level, in STATA data format	Preview "PEI expert-level data (PEI_8.0).tab" Preview "PEI expert-level data (PEI_8.0).tab" Access File File Access Public Download Options Stata 14 Binary (Original File Format) Tab-Delimited RData Download Metadata DDI Codebook v2 Data File Citation Download EndNote XML Download RIS Download BibTeX Explore Options Data Explorer v2
	PEI expert-level data (PEI_8.0).xlsx MS Excel Spreadsheet - 5.4 MB Published May 18, 2022 406 Downloads MD5: e97400139b4f7011305d1f677fc1382e PEI 8.0 data at the expert level, in .xlsx format	Access File File Access Public Download Options MS Excel Spreadsheet Download Metadata Data File Citation Download EndNote XML Download RIS Download BibTeX

Citation Metadata

Persistent Identifier	doi:10.7910/DVN/YSNYXD
Publication Date	2022-05-18
Title	Perceptions of Electoral Integrity, (PEI-8.0)
Author	Royal Military College. Department of Political Science and Economics0000-0002-2119-4399 University of East Anglia. School of Politics, Philosophy, Language and Communication Studies0000-0002-5826-5461 Electoral Integrity Project0000-0002-4942-0474
Point of Contact	Use email button above to contact. Electoral Integrity Project
Description	This dataset by the Electoral Integrity Project evaluates the quality of elections held around the world. Based on a rolling survey collecting the views of election experts, this research provides independent and reliable evidence to compare whether countries meet international standards of electoral integrity. PEI-8.0 cumulative release covers 480 national parliamentary and presidential contests held worldwide in 169 countries from 1 July 2012 to 31 December 2021. For each contest, approximately 40 election experts receive an electronic invitation to fill the survey. The survey includes assessments from 4,591 election experts, with a mean response rate of 23%. The study collects 49 indicators to compare elections. These indicators are clustered to evaluate eleven stages in the electoral cycle as well as generating an overall summary Perception of Electoral Integrity (PEI) 100-point index and comparative ranking. The datasets are available for analysis at three levels: COUNTRY-level (169 observations); ELECTION-level (479 observations), and also EXPERT-level (4,590 observations). Each dataset can be downloaded in STATA, CSV, and EXCEL formats. (2022-05-19)
Subject	Social Sciences
Keyword	Elections Perceptions of Electoral Integrity (PEI) Electoral Integrity Project Electoral integrity Electoral fraud Voting behavior Cross-national elections Global Comparative politics Free and fair
Topic Classification	Elections Politics
Related Publication	Garnett, Holly Ann, Toby S. James, and Madison MacGregor. 2022. Electoral Integrity Global Report, 2019-2021. https://www.electoralintegrityproject.com/globalreport2019-2021
Language	English
Producer	Electoral Integrity Project (Royal Military College of Canada, University of East Anglia) (EIP) https://www.electoralintegrityproject.com/
Production Date	2022
Production Location	Kingston, Ontario, Canada
Contributor	Project Manager: MacGregor, Madison
Funding Information	Social Sciences and Humanities Research Council: 890-2020-0006
Distributor	Electoral Integrity Project (EIP) https://www.electoralintegrityproject.com/
Distribution Date	2022-05-19
Depositor	MacGregor, Madison
Deposit Date	2022-05-18
Time Period	Start Date: 2012-07-1; End Date: 2021-12-31
Date of Collection	Start Date: 2012-07-1; End Date: 2022-04-12
Data Type	survey data
Series	Perceptions of Electoral Integrity Index: The pilot study (PEI_1), first released in May 2013, covered 20 elections held from 1 July 2012 to 31 December 2012. The second release (PEI_2) was made publicly available in February 2014 and included all national elections held from 1 January to 31 December 2013. The midyear release (PEI_2.5) in August included all these earlier cases and expanded the comparison by adding elections occurring from 1 January 2014 to June 30, 2014. The third release of the dataset (PEI_3) included 2012 and 2013 cases and expanded the comparison by including all national elections held from January 1st to December 31st, 2014. In total PEI_3 included expert evaluations of 127 elections held in 107 countries. PEI_3.5 included the responses for 1,696 experts for 153 elections in 125 countries. PEI_4.0 gathered the opinion of 2,080 experts for 180 elections in 139 countries, which were updated in the mid-year release PEI_4.5 to 2,417 experts for 213 elections in 153 countries. PEI_5.0, released May 2017, included the assessment of 2,709 individual expert evaluations of 241 elections in 158 countries up until the end of 2016. The mid-year update, PEI_5.5, included 2,961 experts, 260 national elections, and 161 countries, covering until 30 June 2017. PEI_6.0, released in March 2018, included 3,253 experts, evaluating 285 national elections in 164 countries covering until 1 January 2018. The mid-year update, PEI_6.5, included 3,524 experts, 310 national elections, and 165 countries, covering until 30 June 2018. PEI_7.0, covers 3,821 experts evaluating 336 national elections in 166 countries, from 1 July 2012 to 31 December 2018 . The present data release adds to these results 730 experts evaluating 143 national elections in 115 countries, from February 3rd, 2019, to December 31st, 2021.
Software	STATA, Version: 17

Geospatial Metadata

Geographic Coverage	Albania Argentina Armenia Benin Bulgaria Canada Cape Verde Chile Cyprus Czech Republic Djibouti Ecuador Ethiopia Gambia Germany Iceland Iran, Islamic Republic of Iraq Israel Japan Kyrgyzstan Mexico Mongolia Morocco Netherlands Nicaragua Norway Peru Portugal Qatar Congo Russian Federation American Samoa Sao Tome and Principe Syrian Arab Republic Tonga Uganda Uzbekistan Viet Nam Zambia

Social Science and Humanities Metadata

Unit of Analysis	Expert survey - PEI asks experts to evaluate elections using 49 indicators, grouped into eleven categories reflecting the whole electoral cycle
Universe	Experts - an expert is defined in this survey as a political scientist (or social scientist in a related discipline such as law, sociology, economics, anthropology, mathematics, or statistics) who has published on (or who has other demonstrated knowledge of) the electoral process in a particular country. Specifically, demonstrated knowledge is defined by the following criteria: (1) membership of a relevant research group, professional network, or organized section of such a group; (2) existing publications on electoral or other country-specific topics in books, academic journals, or conference papers; and/or (3) employment at a university or college as a teacher. Around forty experts per country were contacted for each election, including both domestic and international experts. The domestic/international distinction was made based on institutional affiliation, citizenship, and country of residence.
Time Method	Respondents are contacted approximately one month after the date of a national election in their country of expertise. In the case of elections with several rounds (e.g. presidential elections with a run-off round), experts are contacted one month after the final round of the election. Three reminders are sent, each a week apart. Respondents completed the online questionnaire lasting approximately 15 minutes.
Collection Mode	e-mail
Cleaning Operations	1. Missing responses were addressed through multiple imputation. The imputation process was conducted in the following manner using Stata 14 at the expert unit of analysis. All ‘Don't Know’s and ‘Not Applicable’s were replaced by missing values. The data were then imputed using multiple imputation and chained equations by section. The other variables in a section were thus used in the imputation equation along with five fully observed expert background characteristics (sex, agegroup, supported, lived, leftrightscale). Twenty imputed values were then created for each variable taking 200 iterations after a 10 model burn-in. These values were collapsed to their mean value. In an identical manner used to generate PEIIndexp, the values for the 49 substantive variables were summed and standardized into a 0-100 point scale. For more detail on the multiple imputation procedure see Royston, Patrick. 2004. “Multiple imputation of missing values.” Stata Journal 4: 227–241 and Stata Multiple-Imputation Reference Manual: Release 13. College Station, TX: Stata Press, 137-164. Data users wishing to choose an alternative method of addressing missing data can access the expert-level dataset where raw data (not imputed) is available for expert responses to individual questions. Data users interested in the raw scores only can access them in all datasets using the ‘PEIIndexp’ variable or any of the subdimension variables not ended with an ‘I’. This may be appropriate in cases of low or no responses, according to the data user’s needs and methodological decisions; 2. cases with fewer than 2 survey responses were dropped from the dataset for release 8.0 so that any index scores were not relying only on one expert
Response Rate	Mean number of responses for each Elections - 2019 - 6,08; 2020 - 4,45; 2021 - 4,76

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