Springer Nature is making SARS-CoV-2 and COVID-19 research free. View research | View latest news | Sign up for updates

Do I Think BLS Data are BS? The Consequences of Conspiracy Theories

Abstract

While the willingness of people to believe unfounded and conspiratorial explanations of events is fascinating and troubling, few have addressed the broader impacts of the dissemination of conspiracy claims. We use survey experiments to assess whether realistic exposure to a conspiracy claim affects conspiracy beliefs and trust in government. These experiments yield interesting and potentially surprising results. We discover that respondents who are asked whether they believe in a conspiracy claim after reading a specific allegation actually report lower beliefs than those not exposed to the specific claim. Turning to trust in government, we find that exposure to a conspiracy claim has a potent negative effect on trust in government services and institutions including those unconnected to the allegations. Moreover, and consistent with our belief experiment, we find that first asking whether people believe in the conspiracy mitigates the negative trust effects. Combining these findings suggests that conspiracy exposure increases conspiracy beliefs and reduces trust, but that asking about beliefs prompts additional thinking about the claims which softens and/or reverses the exposure’s effect on beliefs and trust.

This is a preview of subscription content, log in to check access.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5

Notes

  1. 1.

    For example, we dropped “September” from the headline and article and replaced “July” and “August” with “the two previous months.”

  2. 2.

    Our participants were paid 75 cents, which is consistent with standard rates on MTurk. We restricted participation to those in American who had at least a 95 % approval rate on at least 50 HITs—which are surveys or tasks in mTurk’s lingo—and we dropped respondents from the second experiment who participated in the first by using their random MTurk ID numbers.

  3. 3.

    Because the article was unrelated to the BLS data, we included the following transitional preface to questions in this condition: “Speaking of numerical data, the government provides a lot of economic data of its own. For example, the Bureau of Labor Statistics reports monthly economic data”.

  4. 4.

    The liberal and young nature of MTurk demographics suggest some caution in extrapolating these results to the elderly and extremely conservative segments of the American population. However, if anything, we would expect the elderly and conservative to be even more sharply affected by our conspiracy exposure than the young and liberal; so, our results likely downplay the effect of conspiracy exposure as a consequence of our sample’s demographics. Moreover, while our sample skews young and liberal, we do have a sizable number of elderly and conservative respondents (indeed, we control for both age and partisanship in our models).

  5. 5.

    The full models, including results for all of the institutions including those for which we do not expect confidence effects can be found in the Supplementary material, Table A4. All results remain substantively the same when we calculate a series of individual OLS estimates; the seemingly unrelated regression equations simply provide more efficient estimates.

  6. 6.

    Ideally one could also investigate the independent effect of the rebuttal, but doing so may not have much substantive meaning and/or confuse participants since a rebuttal without the conspiracy claim it relates to does not make much sense. Rebuttals on their own only make sense when they refer to well known conspiracy claims. In such an instance, though, the rebuttal is likely serving the role of the conspiracy exposure by reminding people of the claim as well.

References

  1. Aaronovitch, D., & Langton, J. (2010). Voodoo histories: The role of the conspiracy theory in shaping modern history. New York: Wiley.

  2. Abramowitz, A. (2010). The disappearing center: Engaged citizens, polarization, and american democracy. New Haven: Yale University Press.

  3. Allport, F. H., & Lepkin, M. (1945). Wartime rumors of waste and special privilege: Why some people believe them. The Journal of Abnormal and Social Psychology, 40(1), 3.

  4. Ansolabehere, S., & Iyengar, S. (1997). Going negative. New York: Simon and Schuster.

  5. Banas, J. A., & Miller, G. (2013). Inducing resistance to conspiracy theory propaganda: Testing inoculation and metainoculation strategies. Human Communication Research, 39(2), 184–207.

  6. Barker, D. C., & Hansen, S. B. (2005). All things considered: Systematic cognitive processing and electoral decisionmaking. Journal of Politics, 67(2), 319–344.

  7. Bartels, L. M. (2005). Homer gets a tax cut: Inequality and public policy in the American mind. Perspectives on Politics, 3(01), 15–31.

  8. Berinsky, A.J. (2013). Rumors, truths, and reality: A study of political misinformation. Unpublished Working Paper (V3.1).

  9. Berinsky, A. J., Huber, G. A., & Lenz, G. S. (2012). Evaluating online labor markets for experimental research: Amazon.com’s mechanical turk. Political Analysis, 20(3), 351–368.

  10. Blair, G., & Imai, K. (2012). Statistical analysis of list experiments. Political Analysis, 20(1), 47–77.

  11. Brotherton, R., French, C. C., & Pickering, A. D. (2013). Measuring belief in conspiracy theories: The generic conspiracist beliefs scale. Frontiers in Psychology, 4, 279.

  12. Bullock, J.G. (2007). Experiments on Partisanship and Public Opinion: Party Cues, False Beliefs, and Bayesian Updating. Stanford University Dissertation.

  13. Bullock, J. G., Gerber, A.S., Hill, S.J., & Huber, G.A. (2013). Partisan bias in factual beliefs about politics. National Bureau of Economic Research Working Paper.

  14. Bullock, Will, Imai, Kosuke, & Shapiro, Jacob N. (2011). Statistical analysis of endorsement experiments: Measuring support for militant groups in Pakistan. Political Analysis, 19(4), 363–384.

  15. Campbell, Angus, Converse, Philip E., Miller, Warren E., & Stokes, Donald E. (1980). The American voter. Chicago: University of Chicago Press.

  16. Center, Pew Research. (2013). January Survey, Trust in Government.

  17. Chong, D., & Druckman, J. N. (2007). Framing public opinion in competitive democracies. American Political Science Review, 101(04), 637–655.

  18. Citrin, J., & Muste, C. (1999). Trust in government. In J. P. Robinson, P. R. Shaver, & L. Wrightsman (Eds.), Measures of political attitudes. New York: Academic Press.

  19. Coady, D. (2006). Conspiracy theories: The philosophical debate. Hampshire: Ashgate Publishing Ltd.

  20. Cobb, M. D., Nyhan, B., & Reifler, J. (2013). Beliefs don’t always persevere: How political figures are punished when positive information about them is discredited. Political Psychology, 34, 307–326.

  21. Eagly, A. H., & Chaiken, S. (1993). The psychology of attitudes. Fort Worth: harcourt brace jovanovich college publishers.

  22. Ecker, U. K. H., Lewandowsky, S., Swire, B., & Chang, D. (2011). Correcting false information in memory: Manipulating the strength of misinformation encoding and its retraction. Psychonomic Bulletin & Review, 18(3), 570–578.

  23. Edwards, Kari, & Smith, Edward E. (1996). A disconfirmation bias in the evaluation of arguments. Journal of Personality and Social Psychology, 71(1), 5.

  24. Ellin, A. (2012). GOP Jobs report manipulation claims dismissed. www.ABCnews.com.

  25. Gingerich, D. W. (2010). Understanding off-the-books politics: Conducting inference on the determinants of sensitive behavior with randomized response surveys. Political Analysis, 18(3), 349–380.

  26. Green, D. P., Palmquist, B., & Schickler, E. (2004). Partisan hearts and minds: Political parties and the social identities of voters. New Haven: Yale University Press.

  27. Hardin, R. (1999). Democracy and trust. In M. E. Warren (Ed.), Do we want trust in government? (pp. 22–41). Cambridge: Cambridge University Press.

  28. Hibbing, J. R., & Theiss-Morse, E. (2002). Stealth democracy: Americans’ beliefs about how government should work. Cambridge: Cambridge University Press.

  29. Jolley, D., & Douglas, K. M. (2013). The social consequences of conspiracism: Exposure to conspiracy theories decreases intentions to engage in politics and to reduce one’s carbon footprint. The British Journal of Psychology, 105, 35–56.

  30. Keeley, B. L. (1999). Of conspiracy theories. The Journal of Philosophy, 96, 109–126.

  31. Kinder, D. R., & Sanders, L. M. (1996). Divided by color: Racial politics and democratic ideals. Chicago: University of Chicago Press.

  32. Kriner, D. L., & Howell, W. G. (2012). Congressional leadership of war opinion? Backlash effects and the polarization of public support for war. In L. C. Dodd & B. I. Oppenheimer (Eds.), Congress reconsidered (10th ed.). Washington, DC: CQ Press.

  33. Kuklinski, J. H., Cobb, M. D., & Gilens, M. (1997). Racial attitudes and the new south. Journal of Politics, 59, 323–349.

  34. Kuklinski, J. H., Quirk, P. J., Jerit, J., Schwieder, D., & Rich, R. F. (2003). Misinformation and the currency of democratic citizenship. Journal of Politics, 62(3), 790–816.

  35. Levi, M., & Stoker, L. (2000). Political trust and trustworthiness. Annual Review of Political Science, 3(1), 475–507.

  36. Lewandowsky, S., Oberauer, K., & Gignac, G. (2013). NASA faked the moon landing therefore (Climate) science is a hoax: An anatomy of the motivated rejection of science. Psychological Science, 5, 622–633.

  37. Lewandowsky, S., Ecker, U. K. H., Seifert, C. M., Schwarz, N., & Cook, J. (2012). Misinformation and its correction continued influence and successful debiasing. Psychological Science in the Public Interest, 13(3), 106–131.

  38. Lewandowsky, S., Werner, G. K., & Krueger, J. I. (2013). Misinformation, disinformation, and violent conflict: From Iraq and the “war on terror” to future threats to peace. American Psychologist, 68(7), 487.

  39. Long, J. S., & Freese, J. (2005). Regression models for categorical outcomes using stata (2nd ed.). College Station: Stata Press.

  40. Lord, C. G., Ross, L., & Lepper, M. R. (1979). Biased assimilation and attitude polarization: The effects of prior theories on subsequently considered evidence. Journal of Personality and Social Psychology, 37(11), 2098.

  41. McCarty, N. M., Keith, T., & Knoedler, J. T. (2006). Polarized America: The dance of ideology and unequal riches. Cambridge: MIT Press.

  42. McClosky, H., & Chong, D. (1985). Similarities and differences between left-wing and right-wing radicals. British Journal of Political Science, 15, 329–363.

  43. Mulligan, K., & Habel, P. (2013). The implications of fictional media for political beliefs. American Politics Research, 41(1), 122–146.

  44. Nyhan, B. (2012a). Enabling the jobs report conspiracy theory the consequences of careless coverage of friday’s unemployment numbers. Columbia Journalism Review.

  45. Nyhan, B. (2012b). Political knowledge does not guard against belief in conspiracy theories. You Gov: Model Politics.

  46. Nyhan, B. (2013). Boosting the Sandy Hook Truther Myth: The dangers of covering fringe misperceptions. Columbia Journalism Review.

  47. Nyhan, B., & Reifler, J. (2010). When corrections fail: The persistence of political misperceptions. Political Behavior, 32(2), 303–330.

  48. NYTimes. (2012). Editorial: Conspiracy world. New York: The New York Times.

  49. Presser, S., & Stinson, L. (1998). Data collection mode and social desirability bias in self-reported religious attendance. American Sociological Review, 63, 137–145.

  50. Putnam, R. D. (2001). Bowling alone: The collapse and revival of American community. New York: Simon & Schuster.

  51. Rahn, W. M. (2000). Affect as information: The role of public mood in political reasoning. In A. Lupia, M. D. McCubbins, & S. L. Popki (Eds.), Elements of reason: Cognition, choice, and the bounds of rationality (pp. 130–150). Cambridge: Cambridge University Press.

  52. Skurnik, I., Yoon, C., Park, D. C., & Schwarz, N. (2005). How warnings about false claims become recommendations. Journal of Consumer Research, 31(4), 713–724.

  53. Tesler, M. (2012). The spillover of Racialization into health care: How President Obama polarized public opinion by racial attitudes and race. American Journal of Political Science, 56(3), 690–704.

  54. Tesler, M., & Sears, D. O. (2010). Obama’s race: The 2008 election and the dream of a post-racial America. Chicago: University of Chicago Press.

  55. Uscinski, J. E., Klofstad, C., & Atkinson, M. (2014). Why do people believe in conspiracy theories? The role of informational cues and predispositions. Paper presented at Annual Meeting of American Political Science Association, Washington DC, August 29, 2014.

  56. Uscinski, J. E., & Parent, J. M. (2014). American conspiracy theories. New York: Oxford University Press.

  57. Zaller, J. R. (1992). The nature and origins of mass opinion. Cambridge: Cambridge University Press.

  58. Zaller, J., & Feldman, S. (1992). A simple theory of the survey response: Answering questions versus revealing preferences. American Journal of Political Science, 36, 579–616.

Download references

Acknowledgments

They would like to thank Adam Berinsky, Jennifer Hochschild, Doug Kriner, Brendan Nyhan, Dustin Tingley, seminar participants at Dartmouth College, and five anonymous reviewers for their helpful comments.

Author information

Correspondence to Katherine Levine Einstein.

Electronic supplementary material

Below is the link to the electronic supplementary material.

Supplementary material 1 (pdf 2451 KB)

Appendices

Appendix

Survey Question Wording

  • Conspiracy belief

    Do you think that recent monthly unemployment data from the Bureau of Labor Statistics are always calculated as accurately as possible or are they politically manipulated? (1) Calculated as accurately as possible (2) politically manipulated.

  • Confidence in Government

    Below is a list of institutions in American society. Please indicate how much confidence you have in each one. (1) Very confident (2) somewhat confident (3) not so confident (4) not confident at all.

  • Four Question Racial Resentment Index

    How strongly do you agree or disagree with the following statement? Irish, Italian, Jewish, and many other minorities overcame prejudice and worked their way up. Blacks should do some same without any special favors. (1) Strongly agree (2) agree (3) neither agree nor disagree (4) disagree (5) strongly disagree.

    How strongly do you agree or disagree with the following statement? Generations of slavery and discrimination have created conditions that make it difficult for blacks to work their way out of the lower class. Strongly agree (1) strongly agree (2) agree (3) neither agree nor disagree (4) disagree (5) strongly disagree.

    How strongly do you agree or disagree with the following statement? Over the past few years, blacks have gotten less than they deserve. Strongly agree (1) strongly agree (2) agree (3) neither agree nor disagree (4) disagree (5) strongly disagree.

    How strongly do you agree or disagree with the following statement? It’s really a matter of some people not trying hard enough; if blacks would only try harder they could be just as well off as whites. (1) Strongly agree (2) agree (3) neither agree nor disagree (4) disagree (5) strongly disagree .

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Einstein, K.L., Glick, D.M. Do I Think BLS Data are BS? The Consequences of Conspiracy Theories. Polit Behav 37, 679–701 (2015). https://doi.org/10.1007/s11109-014-9287-z

Download citation

Keywords

  • Conspiracy theories
  • Trust in government
  • Experiments
  • Misinformation