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Does Political Representation Increase Participation? Evidence from Party Candidate Lotteries in Mexico

Published online by Cambridge University Press:  26 August 2022

MATHIAS POERTNER*
Affiliation:
London School of Economics and Political Science, United Kingdom
*
Mathias Poertner, Assistant Professor of Political Science, Department of Government, London School of Economics and Political Science, United Kingdom, M.Poertner@lse.ac.uk.
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Abstract

How does representation by politicians from specific communities influence these communities’ political participation? Analyzing a natural experiment from Mexico in which a party uses lotteries to select candidates for public office, this paper presents new insights into how representation shapes the political participation of underrepresented segments of society. I find that participation in subsequent elections is significantly higher among constituents who have been represented by randomly selected legislators with a similar social background who are part of local organizational networks (embedded representatives). Furthermore, I show that these represented constituents feel more empowered and that the party that provides this “grassroots” representation is rewarded with more support in the subsequent election. The findings highlight the importance of community embeddedness for political mobilization and have important implications for debates about democratic inclusion and representation.

Information

Type
Research Article
Creative Commons
Creative Common License - CCCreative Common License - BY
This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0), which permits unrestricted re-use, distribution and reproduction, provided the original article is properly cited.
Copyright
© The Author(s), 2022. Published by Cambridge University Press on behalf of the American Political Science Association
Figure 0

Figure 1. Constituents’ Educational BackgroundsNote: Using data for 2017 LAPOP survey respondents in the municipalities with candidates in lottery.

Figure 1

Figure 2. Educational Backgrounds of PR Deputies by PartyNote: Coded based on the information reported in the congressional biographies (LXIII Legislature; 2015–2018). The three MORENA deputies who were not selected through the lottery (“external” deputies) are omitted here due to their small number. See the SI for information on external PR candidates.

Figure 2

Figure 3. Constituents’ Occupational BackgroundsNote: Coded using data for 2017 LAPOP survey respondents in the municipalities with candidates in lottery.

Figure 3

Figure 4. Occupational Backgrounds of PR Deputies by PartyNote: Coded based on the information provided on the candidate registration forms (LXIII Legislature; 2015–2018). The three MORENA deputies who were not selected through the lottery (external deputies) are omitted here due to their small number. See the SI for information on external PR candidates.

Figure 4

Figure 5. Organizational Backgrounds of MORENA Lottery DeputiesNote: Coded based on the information reported in the congressional biographies (LXIII Legislature; 2015–2018).

Figure 5

Table 1. Overview of Electoral and Territorial Units in Mexico

Figure 6

Figure 6. Schematic Illustration of the Structure of the Party ListsNote: The gender of the first candidate is randomly chosen (gender 1); gender 2 refers to second gender.

Figure 7

Figure 7. One of the Receptacles during the 2015 Candidate LotteryNote: Picture by Jesús Villaseca, February 23, 2015.

Figure 8

Figure 8. Map of Municipalities with Lottery Candidates in 2015

Figure 9

Table 2. Balance Statistics for Municipalities

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Figure 9. Effect of Representation on Electoral ParticipationNote: Estimates of effect of representation on electoral participation using IPW, comparing electoral returns (in the 2018 election) from municipalities with a MORENA lottery candidate who was elected in 2015 (treatment) with those with a lottery candidate who was not elected (control). Standard errors are clustered by constituency and number of lottery candidates; p values are two-tailed.

Figure 11

Figure 10. Effect of Representation on MORENA Vote ShareNote: Estimates of effect of representation on electoral support for MORENA using IPW, comparing electoral returns (in the 2018 election) from municipalities with a MORENA lottery candidate who was elected in 2015 (treatment) with those with a lottery candidate who was not elected (control). The vote share for MORENA also includes votes for the PT and PES because they ran in an electoral alliance in many districts in 2018. Standard errors are clustered by constituency and number of lottery candidates; p values are two-tailed.

Figure 12

Table 3. Effect of Representation on Allocation of Federal Transfers (Per Capita)

Figure 13

Table 4. Effect of Representation on Satisfaction with Public Goods and Economic Situation

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Figure 11. Electoral Participation by Class Background of Lottery DeputyNote: Estimates of effect of representation on electoral participation using randomization inference (two-tailed p values, based on 50,000 simulations), comparing electoral returns (in the 2018 elections) from municipalities with a MORENA lottery deputy with a postsecondary education to those with a lottery deputy without a postsecondary education and those with a MORENA lottery candidate who was not elected.

Figure 15

Figure 12. Electoral Participation by Organizational Ties of Lottery DeputyNote: Estimates of effect of representation on electoral participation using randomization inference (two-tailed p values, based on 50,000 simulations), comparing electoral returns in the 2018 elections from municipalities with a MORENA lottery deputy with ties to societal organizations to municipalities with a lottery deputy without organizational ties and municipalities with a lottery candidate who was not elected.

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Table 5. Effect of Representation on Political Attitudes

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Table 6. Effect of Representation on Google Searches

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Figure 13. Marginal Effects of Representation on Electoral Participation by Poverty LevelNote: Marginal effects of interaction between representation treatment and size of income-vulnerable population (% of municipality population) using inverse probability weighting.

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