What is Econometrics?
and what will we be learning in ECON 4750?
What will we learn this semester?
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At a very high level, our goal for this semester is to develop skills related to using data to learn something
Two main course objectives:
Prediction
Causal inference
Prediction
Examples:
- credit risk / default probabilities
- product recommendation systems
- demand prediction
Tools:
- modern approaches to model selection
- machine learning
Causal Inference
Motivation: correlation is not causation
- pirates and global warming
- police and crime
- going to the doctor and illness
Running experiments is a a leading solution to this problem
- chemists can exogenously manipulate temperature on a Bunsen burner
- in medicine, it is common to randomly assign some patients to a new drug and others to a placebo
- some examples in economics: job trainging, conditional cash transfers, many in developing countries
Causal Inference
But experiments are often not feasible
- interest rates
- tax policy
- people’s education levels
- minimum wages
We will learn a number of tools/tricks for causal inference with observational data
We will also learn to be careful with our own causal claims and think carefully about others’ causal claims
- There may be (a large number of) cases where we have relevant data but still can’t fully understand causal relationships between our variables of interest
Tenor of the Course
We will have the dual goals of learning how to do prediction/causal inference/etc. and how it works
Along the way…
We will go in depth on a number of a related topics/tools
Statistical programming
Probability and statistics
Linear regression
These are the “language” we will be speaking this semester, and I aim for you to be experts (or at least very familiar) on all of these topics by the end of the semester.