Lectures Click on lecture titles to view slides or the buttons to download them as PDFs. Topic 1 Course Introduction / Review of Linear Regression and Simulation Students looking to brush up on matrix algebra may want to read through Kevin Quinn’s matrix algebra review. Finally, in conjunction with these slides I discuss examples that can be found in slides on labor standards in Africa and intimate partner homicide in the US. Lab 1 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. Topic 2 Basic Concepts for Time Series: Trends, Lags, and Cycles 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. Topic 3 Models of Stationary Time Series Example code and csv data for estimating and interpreting ARMA models in R. Topic 4 Models of Non-stationary Time Series Example code for estimating and interpreting ARIMA and ECM models in R. You will also need these presidential approval data and this helper function for plotting counterfactual time series using R base graphics. Topic 5 For the curious, the R script used to construct the example plots in the first half of this lecture is here. Topic 6 Panel Data Models with Many Time Periods 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. Topic 7 Panel Data Models with Few Time Periods 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. Topic 8 Heteroskedasticity in Panel Data Topic 9 In-Sample Simulation for Panel Data Models Example code for simulating in-sample unit-by-unit from a panel data model. Uses the cigarette data and helper functions from Topic 7. Advanced Topic 1 Missing Data and Multiple Imputation for Panel Data Advanced Topic 2 Panel Data with Binary Dependent Variables Student Assignments Problems may be turned in at any time during the course Data for problems 1, 3, and 4 in comma-separated variable format. Data for problem 4. Data for problem 5. Data for Bonus Problem A. Data for Bonus Problems B and C. Data for Bonus Problem D. |

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