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Identifying the Effect of Persuasion

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  • Sung Jae Jun
  • Sokbae Lee

Abstract

We set up an econometric model of persuasion and study identification of key parameters under various scenarios of data availability. We find that a commonly used measure of persuasion does not estimate the persuasion rate of any population in general. We provide formal identification results, recommend several new parameters to estimate, and discuss their interpretation. Further, we propose methods for carrying out inference. We revisit the empirical literature on persuasion to show that the persuasive effect is highly heterogeneous. We also show that the existence of a continuous instrument opens up the possibility of point identification for the policy-relevant population.

Suggested Citation

  • Sung Jae Jun & Sokbae Lee, 2018. "Identifying the Effect of Persuasion," Papers 1812.02276, arXiv.org, revised Jan 2021.
    • Handle: RePEc:arx:papers:1812.02276
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    References listed on IDEAS

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    1. Ruben Enikolopov & Maria Petrova & Ekaterina Zhuravskaya, 2011. "Media and Political Persuasion: Evidence from Russia," American Economic Review, American Economic Association, vol. 101(7), pages 3253-3285, December.
    2. Alan S. Gerber & Dean Karlan & Daniel Bergan, 2009. "Does the Media Matter? A Field Experiment Measuring the Effect of Newspapers on Voting Behavior and Political Opinions," American Economic Journal: Applied Economics, American Economic Association, vol. 1(2), pages 35-52, April.
    3. Stefano Della Vigna & Ruben Enikolopov & Vera Mironova & Maria Petrova & Ekaterina Zhuravskaya, 2014. "Cross-Border Media and Nationalism: Evidence from Serbian Radio in Croatia," American Economic Journal: Applied Economics, American Economic Association, vol. 6(3), pages 103-132, July.
    4. Nguimkeu, Pierre & Denteh, Augustine & Tchernis, Rusty, 2019. "On the estimation of treatment effects with endogenous misreporting," Journal of Econometrics, Elsevier, vol. 208(2), pages 487-506.
    5. Rossella Calvi & Arthur Lewbel & Denni Tommasi, 2018. "LATE with Missing or Mismeasured Treatment," Boston College Working Papers in Economics 959, Boston College Department of Economics, revised 15 Mar 2021.
    6. Daniel Ackerberg & Xiaohong Chen & Jinyong Hahn & Zhipeng Liao, 2014. "Asymptotic Efficiency of Semiparametric Two-step GMM," Review of Economic Studies, Oxford University Press, vol. 81(3), pages 919-943.
    7. Craig E. Landry & Andreas Lange & John A. List & Michael K. Price & Nicholas G. Rupp, 2006. "Toward an Understanding of the Economics of Charity: Evidence from a Field Experiment," The Quarterly Journal of Economics, Oxford University Press, vol. 121(2), pages 747-782.
    8. Vittorio Bassi & Imran Rasul, 2017. "Persuasion: A Case Study of Papal Influences on Fertility-Related Beliefs and Behavior," American Economic Journal: Applied Economics, American Economic Association, vol. 9(4), pages 250-302, October.
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    Cited by:

    1. Sung Jae Jun & Sokbae Lee, 2020. "Causal Inference in Case-Control Studies," Papers 2004.08318, arXiv.org, revised Oct 2020.

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    More about this item

    JEL classification:

    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • D72 - Microeconomics - - Analysis of Collective Decision-Making - - - Political Processes: Rent-seeking, Lobbying, Elections, Legislatures, and Voting Behavior
    • L82 - Industrial Organization - - Industry Studies: Services - - - Entertainment; Media

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