# ... mindmap


It would be great to show a modern roadmap in econometrics starting 
from mathematic foundations (linear algebra, calculus, probability) to 
econometrics to computationally intensive data processing tasks. 
I've seen this being approached as [clusters of courses][hacla], 
Khan Academy has goals by subject, but I think there is more that 
can be done. 

[hacla]: https://www.quora.com/How-do-I-design-a-curriculum-to-teach-myself-statistics


## An (over)simplified view of econometrics curriculum


- linear algebra, calculus, probability and statistical inference 
- OLS (assumptions, violations, fixes + estimatore quality)
- limited depenedent variables + maximum likelihood
- intrumental variables 
- time series, state space representation
- panel data
- classifications
- systems of equations

## Key areas

- data structures (crosssection, time series, panel)
- inference methods 
   - model specification
   - estimation procedure
   - model evaluation 
- use cases 

## Additional topics

- simulation (Monte Carlo, bootstrap)
- transformations (PCA)

OLS Extensions:

- GMM
- 2,3 stage OLS
- quantile regressions 
- lasso, rigde

Estimation:

- maximum likelihood
- bayesian estimation
- mcmc (see reddit post)

Time series:

- time series, stationarity, unit root
- state space representation, Kalman filter
- fractional integration
- seasonal adjustment
- (vector) error correction model, VECM
- structural breaks 

## User profiles 


1. "Numerate biologists" - solve a domain problem in biology, psychology, social sciences
2. "Want to hit a 'Run' button" - quick results without thinking, typical of students
3. "I'm doing XYZ now!" - excited adopters, writing a piece on Medium full of acronyms 
4. "Sane econometrics" - appropriate methods with clear, accessible explaination, rare trait 
5. "Asymptotics" - publish evermore sophisticated articles to secure academic career 

Discussion
----------

[Undergraduate Econometrics Instruction: Through Our Classes, Darkly. NBER/IZA](https://www.nber.org/papers/w23144) and a criticism of [G1/G2 goals](https://fxdiebold.blogspot.com/2017/02/econometrics-angrist-and-pischke-are-at.html)