Lectures PDFs of slides are best viewed in Adobe Acrobat, rather than in your browser.
Course Introduction / Review of Linear Regression and Simulation
Supplementary material: Students looking to brush up on matrix algebra may want to read through Kevin Quinn's matrix algebra review in pdf format. In conjunction with this lecture I discuss examples that can be found in slides on labor standards in Africa and intimate partner homicide in the US.
Introduction to R
Supplementary material: This lab comes with three example scripts. First, there is an R code and data for exploratory data analysis using histograms and boxplots. Next, there is an R code and data for a simple bivariate linear regression. Finally, there is an R code and data for a multiple regression example. Interested students can find detailed instructions for downloading, installing, and learning my recommended software for quantitative social science here. Focus on steps 1.1 and 1.3 for now, and then, optionally, step 1.2.
Time Series: Stochastic Processes
Supplementary material: The univariate time series simulation function for R mentioned in the lecture is available here; this function allows for deterministic trends, stationary and nonstationary ARMA processes, and additive or multiplicative seasonality. Also available is a simpler but less flexible R script showing simulation and diagnostics of stationary processes using built-in functions.
Models of Stationary Time Series
Models of Non-stationary Time Series
Basic Concepts for Panel Data
Supplementary material: For the curious, the R script used to construct the example plots in the first half of this lecture is here.
Panel Data Models with Many Time Periods
Supplementary material: Panel ARIMA and fixed effects models in R: example code and csv data for estimating and interpreting panel models with a large number of periods and a small number of cross-sectional units.
Panel Data Models with Few Time Periods
Supplementary material: Panel GMM models (Arellano-Bond/Blundell-Bond) in R: example code, helper functions, and csv data for estimating and interpreting panel models with a small number of periods and a large number of cross-sectional units. On Nickell bias: a script to plot the asymptotic results of Nickell (1981) as well as a helper file and two Monte Carlo scripts (large N / large β and large N / small β) to produce the finite sample results in the lecture slides.
Heteroskedasticity in Panel Data
In-Sample Simulation for Panel Data Models
Advanced Topic 1
Missing Data and Multiple Imputation for Panel Data
Advanced Topic 2
Panel Data with Binary Dependent Variables
Course Problem Set
Problems may be turned in at any time during the course