Corruption Information and Vote Share: A Meta-Analysis and Lessons for Experimental Design
Debate persists on whether voters hold politicians accountable for corruption. Numerous experiments have examined whether informing voters about corrupt acts of politicians decreases their vote share. Meta-analysis demonstrates that corrupt candidates are punished by zero percentage points across fi...
Gespeichert in:
Veröffentlicht in: | The American political science review 2020-08, Vol.114 (3), p.761-774, Article 000305542000012 |
---|---|
1. Verfasser: | |
Format: | Artikel |
Sprache: | eng |
Schlagworte: | |
Online-Zugang: | Volltext |
Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
container_end_page | 774 |
---|---|
container_issue | 3 |
container_start_page | 761 |
container_title | The American political science review |
container_volume | 114 |
creator | INCERTI, TREVOR |
description | Debate persists on whether voters hold politicians accountable for corruption. Numerous experiments have examined whether informing voters about corrupt acts of politicians decreases their vote share. Meta-analysis demonstrates that corrupt candidates are punished by zero percentage points across field experiments, but approximately 32 points in survey experiments. I argue this discrepancy arises due to methodological differences. Small effects in field experiments may stem partially from weak treatments and noncompliance, and large effects in survey experiments are likely from social desirability bias and the lower and hypothetical nature of costs. Conjoint experiments introduce hypothetical costly trade-offs, but it may be best to interpret results in terms of realistic sets of characteristics rather than marginal effects of particular characteristics. These results suggest that survey experiments may provide point estimates that are not representative of real-world voting behavior. However, field experimental estimates may also not recover the “true” effects due to design decisions and limitations. |
doi_str_mv | 10.1017/S000305542000012X |
format | Article |
fullrecord | <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_crossref_primary_10_1017_S000305542000012X</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><cupid>10_1017_S000305542000012X</cupid><sourcerecordid>2428029087</sourcerecordid><originalsourceid>FETCH-LOGICAL-c534t-cadf05ab8f7d51523e929b5549d4f0af7e024adc905734283869e7a195412bd73</originalsourceid><addsrcrecordid>eNqNkE9Lw0AQxRdRsFY_gLeAR4nun2yT9VZi1ULFQ1XES9gkk5rS7sbdDdpv7yYtehDB0wy83xvePIROCb4gmMSXc4wxw5xH1C-Y0Jc9NCCcxSEXEdtHg04OO_0QHVm77CGcDNBrqo1pG1drFUxVpc1a9rtUZfCsHQTzN2ngKhgH9-BkOFZytbG17fUZWKuVDbwrmHw2YOo1KCdXwTXYeqGO0UElVxZOdnOInm4mj-ldOHu4nabjWVhwFrmwkGWFucyTKi454ZSBoCL3SUUZVVhWMWAaybIQmMcsoglLRgJiSQSPCM3LmA3R2fZuY_R7C9ZlS90aH9Rm1POYCpx0FNlShdHWGqiyxueVZpMRnHUVZr8q9J7zrecDcl3ZogZVwLfPQ5yzEU9EX6ank__Tae36olPdKuetbBdOrnNTlwv4-eHveF9m4JKV</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2428029087</pqid></control><display><type>article</type><title>Corruption Information and Vote Share: A Meta-Analysis and Lessons for Experimental Design</title><source>Worldwide Political Science Abstracts</source><source>JSTOR Archive Collection A-Z Listing</source><source>Web of Science - Social Sciences Citation Index – 2020<img src="https://exlibris-pub.s3.amazonaws.com/fromwos-v2.jpg" /></source><source>Cambridge University Press Journals Complete</source><creator>INCERTI, TREVOR</creator><creatorcontrib>INCERTI, TREVOR</creatorcontrib><description>Debate persists on whether voters hold politicians accountable for corruption. Numerous experiments have examined whether informing voters about corrupt acts of politicians decreases their vote share. Meta-analysis demonstrates that corrupt candidates are punished by zero percentage points across field experiments, but approximately 32 points in survey experiments. I argue this discrepancy arises due to methodological differences. Small effects in field experiments may stem partially from weak treatments and noncompliance, and large effects in survey experiments are likely from social desirability bias and the lower and hypothetical nature of costs. Conjoint experiments introduce hypothetical costly trade-offs, but it may be best to interpret results in terms of realistic sets of characteristics rather than marginal effects of particular characteristics. These results suggest that survey experiments may provide point estimates that are not representative of real-world voting behavior. However, field experimental estimates may also not recover the “true” effects due to design decisions and limitations.</description><identifier>ISSN: 0003-0554</identifier><identifier>EISSN: 1537-5943</identifier><identifier>DOI: 10.1017/S000305542000012X</identifier><language>eng</language><publisher>New York, USA: Cambridge University Press</publisher><subject>Behavior Problems ; Behavioral Science Research ; Behavioral Sciences ; Bias ; Candidates ; Corruption ; Corruption in government ; Election results ; Elections ; Estimates ; Evidence ; Experiments ; Financial Audits ; Government & Law ; Laboratory Experiments ; Local elections ; Meta Analysis ; Noncompliance ; Partisanship ; Political campaigns ; Political Science ; Politicians ; Politics ; Polls & surveys ; Research design ; Research methodology ; Researchers ; Selection Criteria ; Social Bias ; Social desirability ; Social Sciences ; Voter behavior ; Voters ; Voting</subject><ispartof>The American political science review, 2020-08, Vol.114 (3), p.761-774, Article 000305542000012</ispartof><rights>American Political Science Association 2020</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>true</woscitedreferencessubscribed><woscitedreferencescount>52</woscitedreferencescount><woscitedreferencesoriginalsourcerecordid>wos000553658900010</woscitedreferencesoriginalsourcerecordid><citedby>FETCH-LOGICAL-c534t-cadf05ab8f7d51523e929b5549d4f0af7e024adc905734283869e7a195412bd73</citedby><cites>FETCH-LOGICAL-c534t-cadf05ab8f7d51523e929b5549d4f0af7e024adc905734283869e7a195412bd73</cites><orcidid>0000-0003-3317-3533</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://www.cambridge.org/core/product/identifier/S000305542000012X/type/journal_article$$EHTML$$P50$$Gcambridge$$H</linktohtml><link.rule.ids>164,315,781,785,12850,27929,27930,28254,55633</link.rule.ids></links><search><creatorcontrib>INCERTI, TREVOR</creatorcontrib><title>Corruption Information and Vote Share: A Meta-Analysis and Lessons for Experimental Design</title><title>The American political science review</title><addtitle>AM POLIT SCI REV</addtitle><addtitle>Am Polit Sci Rev</addtitle><description>Debate persists on whether voters hold politicians accountable for corruption. Numerous experiments have examined whether informing voters about corrupt acts of politicians decreases their vote share. Meta-analysis demonstrates that corrupt candidates are punished by zero percentage points across field experiments, but approximately 32 points in survey experiments. I argue this discrepancy arises due to methodological differences. Small effects in field experiments may stem partially from weak treatments and noncompliance, and large effects in survey experiments are likely from social desirability bias and the lower and hypothetical nature of costs. Conjoint experiments introduce hypothetical costly trade-offs, but it may be best to interpret results in terms of realistic sets of characteristics rather than marginal effects of particular characteristics. These results suggest that survey experiments may provide point estimates that are not representative of real-world voting behavior. However, field experimental estimates may also not recover the “true” effects due to design decisions and limitations.</description><subject>Behavior Problems</subject><subject>Behavioral Science Research</subject><subject>Behavioral Sciences</subject><subject>Bias</subject><subject>Candidates</subject><subject>Corruption</subject><subject>Corruption in government</subject><subject>Election results</subject><subject>Elections</subject><subject>Estimates</subject><subject>Evidence</subject><subject>Experiments</subject><subject>Financial Audits</subject><subject>Government & Law</subject><subject>Laboratory Experiments</subject><subject>Local elections</subject><subject>Meta Analysis</subject><subject>Noncompliance</subject><subject>Partisanship</subject><subject>Political campaigns</subject><subject>Political Science</subject><subject>Politicians</subject><subject>Politics</subject><subject>Polls & surveys</subject><subject>Research design</subject><subject>Research methodology</subject><subject>Researchers</subject><subject>Selection Criteria</subject><subject>Social Bias</subject><subject>Social desirability</subject><subject>Social Sciences</subject><subject>Voter behavior</subject><subject>Voters</subject><subject>Voting</subject><issn>0003-0554</issn><issn>1537-5943</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2020</creationdate><recordtype>article</recordtype><sourceid>ARHDP</sourceid><sourceid>7UB</sourceid><sourceid>8G5</sourceid><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><sourceid>GUQSH</sourceid><sourceid>M2O</sourceid><recordid>eNqNkE9Lw0AQxRdRsFY_gLeAR4nun2yT9VZi1ULFQ1XES9gkk5rS7sbdDdpv7yYtehDB0wy83xvePIROCb4gmMSXc4wxw5xH1C-Y0Jc9NCCcxSEXEdtHg04OO_0QHVm77CGcDNBrqo1pG1drFUxVpc1a9rtUZfCsHQTzN2ngKhgH9-BkOFZytbG17fUZWKuVDbwrmHw2YOo1KCdXwTXYeqGO0UElVxZOdnOInm4mj-ldOHu4nabjWVhwFrmwkGWFucyTKi454ZSBoCL3SUUZVVhWMWAaybIQmMcsoglLRgJiSQSPCM3LmA3R2fZuY_R7C9ZlS90aH9Rm1POYCpx0FNlShdHWGqiyxueVZpMRnHUVZr8q9J7zrecDcl3ZogZVwLfPQ5yzEU9EX6ank__Tae36olPdKuetbBdOrnNTlwv4-eHveF9m4JKV</recordid><startdate>20200801</startdate><enddate>20200801</enddate><creator>INCERTI, TREVOR</creator><general>Cambridge University Press</general><general>Cambridge Univ Press</general><scope>17B</scope><scope>ARHDP</scope><scope>BLEPL</scope><scope>DVR</scope><scope>EGQ</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>0-V</scope><scope>3V.</scope><scope>7UB</scope><scope>7WY</scope><scope>7WZ</scope><scope>7XB</scope><scope>87Z</scope><scope>88B</scope><scope>88J</scope><scope>8BJ</scope><scope>8FK</scope><scope>8FL</scope><scope>8G5</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>ALSLI</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BEZIV</scope><scope>CCPQU</scope><scope>CJNVE</scope><scope>DPSOV</scope><scope>DWQXO</scope><scope>FQK</scope><scope>FRNLG</scope><scope>F~G</scope><scope>GNUQQ</scope><scope>GUQSH</scope><scope>JBE</scope><scope>K60</scope><scope>K6~</scope><scope>KC-</scope><scope>L.-</scope><scope>M0C</scope><scope>M0P</scope><scope>M2L</scope><scope>M2O</scope><scope>M2R</scope><scope>MBDVC</scope><scope>PQBIZ</scope><scope>PQBZA</scope><scope>PQEDU</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>Q9U</scope><orcidid>https://orcid.org/0000-0003-3317-3533</orcidid></search><sort><creationdate>20200801</creationdate><title>Corruption Information and Vote Share: A Meta-Analysis and Lessons for Experimental Design</title><author>INCERTI, TREVOR</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c534t-cadf05ab8f7d51523e929b5549d4f0af7e024adc905734283869e7a195412bd73</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2020</creationdate><topic>Behavior Problems</topic><topic>Behavioral Science Research</topic><topic>Behavioral Sciences</topic><topic>Bias</topic><topic>Candidates</topic><topic>Corruption</topic><topic>Corruption in government</topic><topic>Election results</topic><topic>Elections</topic><topic>Estimates</topic><topic>Evidence</topic><topic>Experiments</topic><topic>Financial Audits</topic><topic>Government & Law</topic><topic>Laboratory Experiments</topic><topic>Local elections</topic><topic>Meta Analysis</topic><topic>Noncompliance</topic><topic>Partisanship</topic><topic>Political campaigns</topic><topic>Political Science</topic><topic>Politicians</topic><topic>Politics</topic><topic>Polls & surveys</topic><topic>Research design</topic><topic>Research methodology</topic><topic>Researchers</topic><topic>Selection Criteria</topic><topic>Social Bias</topic><topic>Social desirability</topic><topic>Social Sciences</topic><topic>Voter behavior</topic><topic>Voters</topic><topic>Voting</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>INCERTI, TREVOR</creatorcontrib><collection>Web of Knowledge</collection><collection>Web of Science - Social Sciences Citation Index – 2020</collection><collection>Web of Science Core Collection</collection><collection>Social Sciences Citation Index</collection><collection>Web of Science Primary (SCIE, SSCI & AHCI)</collection><collection>CrossRef</collection><collection>ProQuest Social Sciences Premium Collection</collection><collection>ProQuest Central (Corporate)</collection><collection>Worldwide Political Science Abstracts</collection><collection>Access via ABI/INFORM (ProQuest)</collection><collection>ABI/INFORM Global (PDF only)</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>ABI/INFORM Global (Alumni Edition)</collection><collection>Education Database (Alumni Edition)</collection><collection>Social Science Database (Alumni Edition)</collection><collection>International Bibliography of the Social Sciences (IBSS)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>ABI/INFORM Collection (Alumni Edition)</collection><collection>Research Library (Alumni Edition)</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>Social Science Premium Collection</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>Business Premium Collection</collection><collection>ProQuest One Community College</collection><collection>Education Collection</collection><collection>Politics Collection</collection><collection>ProQuest Central Korea</collection><collection>International Bibliography of the Social Sciences</collection><collection>Business Premium Collection (Alumni)</collection><collection>ABI/INFORM Global (Corporate)</collection><collection>ProQuest Central Student</collection><collection>Research Library Prep</collection><collection>International Bibliography of the Social Sciences</collection><collection>ProQuest Business Collection (Alumni Edition)</collection><collection>ProQuest Business Collection</collection><collection>ProQuest Politics Collection</collection><collection>ABI/INFORM Professional Advanced</collection><collection>ABI/INFORM Global</collection><collection>Education Database</collection><collection>Political Science Database</collection><collection>Research Library</collection><collection>Social Science Database</collection><collection>Research Library (Corporate)</collection><collection>ProQuest One Business</collection><collection>ProQuest One Business (Alumni)</collection><collection>ProQuest One Education</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>ProQuest Central Basic</collection><jtitle>The American political science review</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>INCERTI, TREVOR</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Corruption Information and Vote Share: A Meta-Analysis and Lessons for Experimental Design</atitle><jtitle>The American political science review</jtitle><stitle>AM POLIT SCI REV</stitle><addtitle>Am Polit Sci Rev</addtitle><date>2020-08-01</date><risdate>2020</risdate><volume>114</volume><issue>3</issue><spage>761</spage><epage>774</epage><pages>761-774</pages><artnum>000305542000012</artnum><issn>0003-0554</issn><eissn>1537-5943</eissn><abstract>Debate persists on whether voters hold politicians accountable for corruption. Numerous experiments have examined whether informing voters about corrupt acts of politicians decreases their vote share. Meta-analysis demonstrates that corrupt candidates are punished by zero percentage points across field experiments, but approximately 32 points in survey experiments. I argue this discrepancy arises due to methodological differences. Small effects in field experiments may stem partially from weak treatments and noncompliance, and large effects in survey experiments are likely from social desirability bias and the lower and hypothetical nature of costs. Conjoint experiments introduce hypothetical costly trade-offs, but it may be best to interpret results in terms of realistic sets of characteristics rather than marginal effects of particular characteristics. These results suggest that survey experiments may provide point estimates that are not representative of real-world voting behavior. However, field experimental estimates may also not recover the “true” effects due to design decisions and limitations.</abstract><cop>New York, USA</cop><pub>Cambridge University Press</pub><doi>10.1017/S000305542000012X</doi><tpages>14</tpages><orcidid>https://orcid.org/0000-0003-3317-3533</orcidid></addata></record> |
fulltext | fulltext |
identifier | ISSN: 0003-0554 |
ispartof | The American political science review, 2020-08, Vol.114 (3), p.761-774, Article 000305542000012 |
issn | 0003-0554 1537-5943 |
language | eng |
recordid | cdi_crossref_primary_10_1017_S000305542000012X |
source | Worldwide Political Science Abstracts; JSTOR Archive Collection A-Z Listing; Web of Science - Social Sciences Citation Index – 2020<img src="https://exlibris-pub.s3.amazonaws.com/fromwos-v2.jpg" />; Cambridge University Press Journals Complete |
subjects | Behavior Problems Behavioral Science Research Behavioral Sciences Bias Candidates Corruption Corruption in government Election results Elections Estimates Evidence Experiments Financial Audits Government & Law Laboratory Experiments Local elections Meta Analysis Noncompliance Partisanship Political campaigns Political Science Politicians Politics Polls & surveys Research design Research methodology Researchers Selection Criteria Social Bias Social desirability Social Sciences Voter behavior Voters Voting |
title | Corruption Information and Vote Share: A Meta-Analysis and Lessons for Experimental Design |
url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2024-12-13T08%3A09%3A22IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_cross&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Corruption%20Information%20and%20Vote%20Share:%20A%20Meta-Analysis%20and%20Lessons%20for%20Experimental%20Design&rft.jtitle=The%20American%20political%20science%20review&rft.au=INCERTI,%20TREVOR&rft.date=2020-08-01&rft.volume=114&rft.issue=3&rft.spage=761&rft.epage=774&rft.pages=761-774&rft.artnum=000305542000012&rft.issn=0003-0554&rft.eissn=1537-5943&rft_id=info:doi/10.1017/S000305542000012X&rft_dat=%3Cproquest_cross%3E2428029087%3C/proquest_cross%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=2428029087&rft_id=info:pmid/&rft_cupid=10_1017_S000305542000012X&rfr_iscdi=true |