Introduction to the course
What is econometrics?
- Estimating economic relationships
- Demand curve \(\log(Q_{t})= \alpha_0 + \alpha_1 P_t + \epsilon_t\)
- Production function \(Y_{it}=A_{it}K_{it}^{\alpha}L_{it}^{\beta}\)
- Testing economic theory
- Does adverse selection exists in insurance markets?
- Are consumers rational?
- Determine the effect of a given intervention (causal inference)
- What is the effect of increasing minimum wage on employment?
- Do mergers increase the output price?
- Does democracy cause economic growth? (a series of works by Acemoglu, Robinsohn, and their co-authors).
- Effects of going to private colleges on your future earnings.
- Note: Some questions may have underlying economic models, others may not.
- Describe the data (prediction/forecasting)
- How does the distribution of wage look like?
- Relationship between electricity consumption and temperature (possibly nonlinear).
- Related to machine learning (ML).
Why do we need to learn computation
- Conduct statistical and empirical analysis using your own data set
- Construct the data set
- Describe the data
- Run regression or estimate an economic object
- Make tables and figures that show the results of your analysis.
- Verify the econometric theory through numerical simulations.
- Ex. Asymptotic theory considers the case when the sample size is large enough (i.e., \(N \rightarrow \infty\))
- Law of large numbers, central limit theorem
- How well is the asymptotic approximation?
- Monte Carlo simulations
- We will learn both aspects in this course.
Why do we use R?
- Many alternatives: Stata, Matlab, Python, etc…
- Free software!!
- Stata and Matlab are expensive.
- Though you can use Matlab through the campus license from this April.
- Good balance between flexibility in programming and easy-to-use for econometric analysis
- Stata is easy to use for econometric analysis, but hard to write your own program.
- Matlab is the opposite.
- You can do everything with R, including data construction, regression analysis, and complicated structural estimation.
- Many users
- Popular in engineering.
- Many packages being developed (especially important for recently popular tools. )
- Note: Python seems also good, though I have not used it before.