Dimensionality and Disagreement: Asymptotic Belief Divergence in Response to Common Information

Loh, Isaac; Phelan, Gregory

doi:10.1111/iere.12406

Cited by 12 publications

(9 citation statements)

References 31 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In this paper, I present a model of a more optimistic alternative: affective polarization driven by misunderstanding. I model inter-personal feelings by assuming they are based on cognitive beliefs, consistent with recent work from psychology 1 See Williams (2017) and Loh and Phelan (2017) for recent models and discussion of the disagreement literature, which I also discuss briefly in Section 2. See Babcock and Loewenstein (1997) for discussion of work on bargaining impasses.…”

Section: Introductionmentioning

confidence: 88%

“…An important similarity between our models is that different beliefs about one dimension (in my model, tastes or level of strategic thinking) is the cause of increasing disagreement on the other dimension (character). Papers on related identification problems (data that is lower dimensional than the true model) leading to persistent or growing disagreement include Acemoglu, Chernozhukov, and Yildiz (2016), Piketty (1995), Benoît and Dubra (2017), and Loh and Phelan (2017). These papers are quite distinct from mine in two ways: 1) they do not focus on cognitive bias as the root cause of disagreement;…”

Section: Additional Related Literaturementioning

confidence: 99%

See 1 more Smart Citation

Just a big misunderstanding? Bias and Bayesian affective polarization

Stone¹

2018

Preprint

View full text Add to dashboard Cite

I present a model of affective polarization---growth in hostility over time between two parties---via quasi-Bayesian inference. In the model, two agents repeatedly choose actions. Each choice is based on a balance of concerns for private interests and the social good. More weight is put on private interests when an agent's character is intrinsically more self-serving and when the other agent is believed to be more self-serving. Each agent Bayesian updates about the other's character, and dislikes the other more when she is perceived as more self-serving. I characterize the effects on growth in dislike of three biases: a prior bias against the other agent's character, the false consensus bias, and limited strategic thinking. Prior bias against the other's character remains constant or declines over time, and actions do not diverge. The other two biases cause actions to become more extreme over time and repeatedly be ``worse'' than expected, causing mutual growth in dislike, i.e., affective polarization. The magnitude of dislike can become arbitrarily large---even when both players are arbitrarily ``good'' (unselfish). The results imply that seemingly irrelevant cognitive biases can be an important cause of the devolution of relationships, in politics and beyond, and that subtlety and unawareness of bias can be key factors driving the degree of polarization.

show abstract

Section: Introductionmentioning

confidence: 88%

Section: Additional Related Literaturementioning

confidence: 99%

Just a big misunderstanding? Bias and Bayesian affective polarization

Stone¹

2018

Preprint

View full text Add to dashboard Cite

show abstract

“…An important similarity between our models is that different beliefs about one dimension (in my model, tastes or level of strategic thinking) is the cause of increasing disagreement on the other dimension (character). Papers on related identification problems (data that are lower dimensional than the true model) leading to persistent or growing disagreement include Acemoglu et al (2016), Piketty (1995), Benoît and Dubra (2019), and Loh and Phelan (2019). These papers are quite distinct from mine in two ways: (1) They do not focus on cognitive bias as the root cause of disagreement; (2) they do not address interpersonal feelings, or growing dislike in particular.…”

Section: Additional Related Literaturementioning

confidence: 99%

“…Papers on related identification problems (data that are lower dimensional than the true model) leading to persistent or growing disagreement include Acemoglu et al. (), Piketty (), Benoît and Dubra (), and Loh and Phelan (). These papers are quite distinct from mine in two ways: (1) They do not focus on cognitive bias as the root cause of disagreement; (2) they do not address interpersonal feelings, or growing dislike in particular.…”

Section: Additional Related Literaturementioning

confidence: 99%

Just a Big Misunderstanding? Bias and Bayesian Affective Polarization

Stone

2020

Int Economic Review

View full text Add to dashboard Cite

I present a model of affective polarization—growth in hostility over time between two parties—via quasi‐Bayesian inference. In the model, two agents repeatedly choose actions. Each choice is based on a balance of concerns for private interests and the social good. More weight is put on private interests when an agent's character is intrinsically more self‐serving and when the other agent is believed to be more self‐serving. Each agent Bayesian updates about the other's character, and dislikes the other more when she is perceived as more self‐serving. I characterize the effects on growth in dislike of three biases: a prior bias against the other agent's character, the false consensus bias, and limited strategic thinking. Prior bias against the other's character remains constant or declines over time, and actions do not diverge. The other two biases cause actions to become more extreme over time and repeatedly be “worse” than expected, causing mutual growth in dislike, that is, affective polarization. The magnitude of dislike can become arbitrarily large—even when both players are arbitrarily “good” (unselfish). The results imply that seemingly irrelevant cognitive biases can be an important cause of the devolution of relationships, in politics and beyond, and that subtlety and unawareness of bias can be key factors driving the degree of polarization.

show abstract

“…() show that two individuals can persistently polarize in a model in which agents are not fully rational. Loh and Phelan () provide conditions for when long run polarization can occur, and when it cannot, when individuals do not store the full distribution over the multidimensional state space but only the marginals over each dimension. All four of these papers can be interpreted as showing population polarization as well as pairwise polarization in nonstandard settings.…”

Section: Related Literaturementioning

confidence: 99%

Apparent Bias: What Does Attitude Polarization Show?

Benoı̂t

Dubra

2019

Int Economic Review

View full text Add to dashboard Cite

Many, though not all, experiments have found that exposing groups of subjects who disagree to the same evidence may cause their initial attitudes to strengthen and move further apart, or polarize. Some have concluded that findings of attitude polarization show that people process information in a biased manner so as to support their initial views. We argue that, on the contrary, polarization is often what we should expect to find in an unbiased Bayesian population, in the context of experiments that find polarization.

show abstract

Dimensionality and Disagreement: Asymptotic Belief Divergence in Response to Common Information

Cited by 12 publications

References 31 publications

Just a big misunderstanding? Bias and Bayesian affective polarization

Just a big misunderstanding? Bias and Bayesian affective polarization

Just a Big Misunderstanding? Bias and Bayesian Affective Polarization

Apparent Bias: What Does Attitude Polarization Show?

Contact Info

Product

Resources

About