Interdisciplinary Economics: Economodeling
In this 36 week guided and interactive online high school course, students will use Python programming, Excel, and web scraping to get real time economic data to develop a predictive mathematical model of the global economy, using historical data available online and various regression models and economic relationships. Students will publish their findings periodically throughout the course in a blog to get public feedback on what they are learning. They will then convert that model into a user interface in the form of an app in order to make it available to those that have not participated in the modeling process. Through this, they will learn computer programming, mathematical modeling, data-based decision making, and technical communications and design. Please scroll down for more information and some samples of student work!
"And his master praised the unrighteous manager because he had acted shrewdly, for the sons of this age are more shrewd in relation to their own kind than the sons of light...He who is faithful in a very little thing is faithful also in much; and he who is unrighteous in a very little thing is unrighteous also in much. Therefore, if you have not been faithful in the use of unrighteous wealth, who will entrust true riches to you?" -- Luke 16:8, 10-11
Additional REsources required:
so, what's the story?
What if I continued to give you the following week’s edition of the paper every day for the next year? Could you make a million dollars?
This course started with a German stoplight, a joke, a book title, and a science fiction robot. Yes, I realize that this requires a little explanation.
There is an old joke about two men in the woods who encounter a bear. As one man bends down to put on running shoes, his companion points out that a man cannot outrun a bear, no matter the choice of footwear. The other man replies: “I don’t have to outrun the bear; I just have to outrun you!” This is how many economics decisions actually play out. If you are ahead of the crowd, you win!
As I was walking to work in Germany, a stoplight would direct pedestrian traffic across the street.
Over time, I learned the traffic light patterns, so I was able to actually start walking before the pedestrian light allowed it, much to the surprise and dismay of the Germans.
I realized that if this were us buying stocks, I would be rich because I had “outrun” them.
Robert Heinlein, in his book Friday, tells of an android whose job it is to find correlations between all of the events in the world in order to determine causation (and thus, prediction.)
This got me thinking about whether or not it was possible that seemingly unrelated events had a causative “butterfly effect.”
Another book that I read, If It’s Raining In Brazil, Buy Starbucks, moved my speculations out of the realm of science fiction. I realized that the ability to use unlikely indicators, combined with sound analysis and careful modesty, could actually help “outrun” all of the so-called experts who were trying to “outrun the bear.”
Thus was born Econopolicy.
- Predictive mathematical model of the global economy
- App/user interface to make the predictions accessible to others than just the modelers
- Scholarly economic article submitted to a journal for publication
- Regular economic blog (generally bi-weekly) about your discoveries that you are making from the regression analysis
- Ability to predict the global economy to a calculated level of uncertainty
- Ability to mathematically model various problems in life so as to find rational solutions
- Working knowledge of the scholarly publication process
- Ability to design a user interface/app to "translate" technical knowledge to an end user
- Ability to communicate technical information in writing to a broader adult audience
What careers will this course give me a leg up on?
- Broker - Average Salary: $67,310 (https://www.careeronestop.org)
- Hedge Fund Manager - Average Salary: $100,866 (www.payscale.com)
- Investment Banker - Average Salary: $139,451 (https://www.glassdoor.com)
- Personal Financial Planner - Average Salary: $90,530 (https://www.careeronestop.org)
- App Developer - Average Salary: $85,773 (https://www.indeed.com)
- Economics Professor - Average Salary: $95,770 (https://www.careeronestop.org)
- Retired and Living on Your Investment Income - Average Salary: "Sky's the Limit!"
General syllabus (Subject to change as needed)
- Course Start: 23 August 2021
- Week 1:
- Template setup
- Week 2:
- Python Familiarization
- Week 3:
- Market Sectors week 1 (gathering historical data on market sector indexes)
- Week 4:
- Market Sectors week 2 (calculating and analyzing regression correlation between ratios of market sectors data)
- Week 5:
- Market Sectors blog preparation and publication
- Week 6:
- Industries Week 1
- Week 7:
- Industries Week 2
- Week 8:
- Industries blog preparation and publication
- Week 9:
- First iteration of mathematical model write up
- Limits Bounding Analysis (LBA) #1
- Week 10:
- Commodities Week 1 (gather historical data and calculate regression relationships)
- Week 11:
- Commodities Week 2 (analyze regression relationships and publish blog)
- Week 12:
- Currencies Week 1
- Week 13: Thanksgiving Week
- Currencies Week 2
- Week 14:
- Other Economic Indicators (International) Week 1
- Week 15:
- Other Economic Indicators (International) Week 2
- Week 16:
- Looking at Uncertainty: Bayes' Theorem
- Christmas Break: 13 December 2021 - 2 January 2022
- Week 17:
- Government Bonds Week 1
- Week 18:
- Government Bonds Week 2
- Week 19:
- Shock Events Week 1
- Week 20:
- Shock Events Week 2
- Week 21:
- Other Economic Indicators (U.S. Reports, Sentiment Indicators, Cross Market Correlations) Week 1
- Week 22:
- Other Economic Indicators (U.S. Reports, Sentiment Indicators, Cross Market Correlations) Week 2
- Week 23:
- LBA on Model and Computer Program
- Week 24:
- Variable Deep-Dive Program Development I
- Week 25:
- Variable Deep-Dive Program Development II
- Blog Publication on a Study Variable of your Choice
- Week 26:
- Variable Deep-Dive Program Development III
- Week 27:
- Variable Deep-Dive Program Development (User Interface Development)
- Blog Publication on a study variable of your choice
- Week 28:
- Variable Deep-Dive Program Development (Integration with Larger MPM)
- Week 29:
- Variable Deep-Dive Program Development (Integration with Larger MPM and Report Usefulness Refinement)
- Research publication requirements for professional scholarly journals
- Blog publication on study variable of your choice
- LBA on Computer Program and Model
- Week 30:
- Companies (stocks and bonds) Week 1
- Marketing plan for blog
- Spring Break: 11 - 17 April 2022
- Week 31:
- Company Stocks and Bonds Week 2
- Write scholarly article on most interesting relationship that you discovered (extended deadline)
- Week 32:
- User interface refinement
- Report usefulness and readability refinement
- Week 33:
- Critique classmate's user interface
- Critique classmate's article
- (Social) Marketing for Blog
- Week 34:
- (Social) Marketing for Blog
- Revise article for publication
- Submit article for publication
- Week 35:
- Revise user interface
- Final LBA on model, article, and user interface
- Week 36:
- Socialize most interesting findings
- Journey of Learning Narrative (JOLN)
- Final mathematical model with user interface submitted
- Course End: 28 May 2022
Expected work load
- Typically one or more tasks that you must perform to move your project iteratively "down the road"
- One or more discussion questions from the teacher to answer
***All of this is designed to take you about 5 focused hours per week, which is less than you would have if you were attending class in a traditional school.
How can I write this course up on a high school transcript?
- As an Economics credit, given the breadth of coverage of the prediction model that the students are developing and the interrelationships that they have explored in the creation of their model, as well as the scholarly writing that they will submit as their article to a scholarly journal
- As an Applied Mathematics credit, given the extensive use of regression modeling and conditional probability that is built into the modeling process for calculating the predictions and the level of uncertainty associated with those predictions.
- As a Computer credit, given the different applications that the students will be both using and developing in order to create a user interface that is accessible and useful.
- As a Technical Writing credit, given the students' regular blog posts about their growing mathematical model.