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Modeling Economies and Markets with NetLogo
Rob Axtell series and Leigh Tesfatsion
Conventional vs ABM approach to economics up to 53:52
2017 SFI conference with
- Rob Axtell : large model with economic data of all individuals and firms in the US for assisting decision making for policy makers
- Michael .. statistical analysis vs ethics on mortgage loans discrimination with Axtell response
Axtell on large scale agent models
Axtell large scale model on Nasdaq and finance in general
epidemic modeling
Leigh Tesfatsion website
Rob Axtell web
CoreEcon
EconTalk
future jobs
Sornette
Nigel Gilbert
财政发力 = **政府向央行发债借钱 + 这些钱可以用来做基建 + 福利开支 + 支持地方债务 + 但这些钱未来要还的(加重当前债务和未来的债务偿还压力)
降准放水 = 将银行里扣着防范挤兑的钱,也借出去 (让银行满负荷房贷运作,增加银行系统风险)
央行印钞 = 从空气中造币,钱多了,可以大幅购买资产,但直接导致贬值压力上升
每种放水方式都有弊端,但日美印钞的弊端较小,因为是储备货币,风险被转移给世界各国平摊
Their problems are hard and massive but well-defined with big data and specific objective metrics
Using ML and DL is to apply a more powerful weapon to solve the problems more efficiently and accurately
The problems are real-world, but usually very vague (even more real-world), you need to define the problem with rigor before exploring solutions
The problems can arise from everywhere from anything, it is more real-life oriented
you are allowed to use any tools and techniques to approach and solve them (use easy tools to train thinking process )
Great programming languages to build brilliant softwares
Great programming languages to processing and mining big data with clever algorithms
Agent based modelling approaches to study and research economics, banking and money, trade and so on
Mathematical modeling and ABM
- solve real world problem with simpler tools and languages (NetLogo, Extentions with python or R, Weka)
- time and energy focus on approaches, processes, defining and solving problems, rather than sharpening tools like Java, Python, Tensorflow and Pytorch
- Dynamics of Economies, markets, Money and Banking, Debt cycles, Trade wars are much more interesting and useful to policy making
- together with big real economic data, the model can be more realistic and dynamic to help policy makers
NetLogo, R, Weka are powerful enough to solve most of the problems probably
Learning to use them efficiently on real problems should be a demanding skill (also demand time and effort, and few people give to them)
why updating code and comments are not enough?
- model is complex, codeCommentCorrect != modelUnderstood
how to write the code from scratch?
- commonLanguageModelNaturallyIntuitively = scratch step 1
codeVerifyOneStepATime
- scratch step 2 : code up globals, breeds, properties and the setup
- scratch step 3 build the go procedure framework and two functions are missing.
- scratch step 4 : to wirte the most difficult function with detailed structure in common language
Natasha Wilkerson
这个科学节就是由STEMIE(STEM +发明+创业)联盟推动的NICEE
Dear EmbraceLife
Your project on housing markets is quite fascinating, I wonder if we can have a deeper discussion through an email? Do you have any email contacts that I can send?
Thanks!
Best
Peter
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