3/23/2023: Jordan Kemp

[GabeNicholson]

Comment below with a well-developed question or comment about the reading for this week's workshop.

If you would really like to ask your question in person, please place two exclamation points before your question to signal that you really want to ask it.

Please post your question by Tuesday of the coming week, at 11:59 PM. We will also ask you all to upvote questions that you think were particularly good. There may be prizes for top question-askers.

[AlexPrizzy]

Thanks for presenting this work, Jordan! I'm wondering how this can be applied practically in real world scenarios? Such as using this in designing educational institutions to maximize outcomes of students

[shenyc16]

Hi Jordan, thanks a lot for sharing this insightful work with us! It is inspiring to think about the importance of learning for economic growth and income inequality, and the potential benefits of policies that promote education and knowledge sharing. My question is, What are some potential limitations or assumptions of the agent-based model used in the paper? Thank you!

[Hongkai040]

Hi Dr. Kemp, Thank you so much for sharing your work! It's interesting! I'd like to know do you plan to validate the model with several empirical cases and how do you think about the rational part and non-rational part of human decision? It seems that BO in decision-making is inherently rational. However, people in a (large) group may also connect to each other through weak ties, which is less explained by rational theory. Would you consider such connections into future models?

[fiofiofiona]

Hi Jordan, thank you for sharing your work with us. While the paper has discussed some developments of models for realistic situations, I am curious about the challenges you would expect to face when implementing the model in real-world cases, which have yet to be addressed by the current framework.

[WonjeYun]

Hi Jordan, thank you for sharing your research with us. About your research, I was wondering if we could use transfer entropy instead of mutual information in calculating the growth from information. Since transfer entropy is the conditional mutual information on the history of the influenced variable, under the assumption that the individuals can get the past information history, would it represent a better model of the reality?

[yunshu3112]

Hi Jordan,

I enjoyed reading your research. I wonder how does technological growth or drastic technological revolution fits into this model? Thank you!

[zbchen0129]

Hi Jordan, Thanks for sharing your work. Your theory of population dynamics for learning agents that associates growth rates with information and addresses problems of inequality in heterogeneous populations is particularly intriguing. Could you provide some examples of how this theory can be applied in practice to mitigate inequality? I am also interested in learning about how it could be applied in different domains, such as ecology, economics, or sociology. Can you provide some examples of how this theory might be used to advance our understanding of these fields? Thanks!

[edelahayeUChicago]

Hi Jordan,

This is a really interesting model, and I'm looking forward to your presentation tomorrow. However, I feel you avoided many of the more common currents in the literature connecting inequality and growth (i.e. secular stagnation, or the role of land/monopolies in rent-seeking). Was there a reason for this or is this something you look to integrate further in the future.

Thanks, Elliot

[pranathiiyer]

Hi Jordan, thanks so much for sharing your work! Looks super interesting! You talk about a framework that will "lay the foundations for a unified general quantitative theory of social and biological phenomena such as the dynamics of cooperation". Do we need a general quantitative theory for such complex phenomena? How 'general' would these actually be considering any limitations and assumptions? Thanks!

[koichionogi]

Dear Jordan I concur that the sequential Bayesian inference is a useful approach to model how individuals make their optimal decisions path-dependent or history-dependent. I would like to ask a related question about science communication. Have you noticed that when you present your work to audiences from different disciplines, they tend to approach it from different angles based on their background? If this is the case, it could indicate that interdisciplinary programs and workshops are worthwhile investments. On the other hand, have you encountered instances where people's misunderstandings stem from differences in terminology or other meta-level points of disagreement, which may be linked to the extent of their disciplinary background?

[zyang39]

Hi Jordan, thanks for sharing your work. It is a pleasure to see it, though it is not easy to fully absorb it. I am curious about what kind of fundamental theory that we are in lack of? Thanks for your sharing again!

[YutaoHeOVO]

Hi Jordan,

Very interesting work. Only used stochastic calculus in asset pricing before and next think it can be used in the context of assessing inequality. Here are some follow-up questions:

1. The underlying stochastic process is set as Brownian motion. And I am thinking it might be better to set it as a Levy process with jumps (this can simulate the exogenous shocks I suppose). Even though this might lead to the result that there is no analytical solution, the numerical stuff can also give us some insights.

2. On the conditions for progressive population dynamics. An intuition is that suppose we think of the social mobility as some kind of diffusion behavior (which can be modelled by a diffusion equation). A directly result by Ito's Lemma is that it is negatively correlated to the volatility. And a direct result of progressive dynamic will increase the volatility (making the diffusion term stronger, increasing social mobility) and it will decrease growth rate. And this intuitive result seems to make this part of the discussion trivial.

3. Does it mean that this paper focuses more on the numerical result instead of explaining the mechanism driving the inequality? It seems that what matters here is the parameter calibration and the parameter we select will decide the dynamic. It seems that the calibration of the parameter and how it is determined is not the focus of the paper.

Best, Yutao

[Ry-Wu]

Hi professor Kemp, thank you for sharing your interesting work with us! I'm wondering if different forms of inequalities have been taken into account and if they affect the model differently.

[ddlee19]

I appreciate you sharing your work with me. From what I understand, you suggest a method for studying growth patterns in diverse groups that relies on agent decision-making in a noisy environment and includes several assumptions. I'm interested in learning more about how you plan to make it more applicable to real-world scenarios. Can you please provide additional details on your future research plans?

[JerryCG]

Dear Jordan, The human society is very much like a physics system but with a lot more uncertainty and dynamics. You introduce the random environments factor which can be really important to consider. Do you think the model you develop is sufficient enough to capture the essential problems? Any other randomness like ability to acquire information and grasp new things should be included? Best, Jerry Cheng

[Peihan12]

Hi professor Kemp, how does information theory play a role in the development of these models, and what insights does it provide into the dynamics of wealth and cooperation?

[linhui1020]

Hello Jordan, Thank you for sharing your work. I am curious about how environmental factors stimulate the cognitive change of actors, and further lead to the decision-making. And how this research finding could be practically used for solving social issues?

[xinyi030]

Hi Jordan,

Thanks for sharing your interesting work. How do you see your findings being applied in real-world policy-making to reduce inequality, and what challenges do you anticipate in implementing these ideas? Thanks again.