AAEC5126 Empirical Economics

Klaus Moeltner | Department of Agricultural and Applied Economics | Virginia Tech | phone: (540) 231-8249 | fax: (540) 231-7417 | e-mail: moeltner@vt.edu
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Welcome to our course web site for Spring 2014. New material will be added as we move along. Anything below the "In Progress" line is subject to change and edits.

Syllabus and General Announcements

  1. Syllabus (pdf)
  2. LaTeX material for syllabus (for your LaTEX practice, so you can see the underlying code)

    1. Main TeX file (tex)
    2. Bibilography (bib)
    3. Table with schedule(called by the main script) (tex)

Software Instructions

We will be using R as our statistical programming package and LaTeX for word processing. The Sweave package combines the two to create unified documents that contain - subject to your full control - programming code, statistical results, tables, figures, comments, equations, and discussion. I recommend the RStudio interface to run R and to compose your Sweave files.

For a smooth start, please follow these instructions for downloading and customizing these software components exactly.

  1. Folder environment

    1. Instructions (pdf)
    2. Instructions (tex)

  2. Installing and customizing LateX for Windows

    1. Instructions (pdf)
    2. Instructions (tex)
    3. testscript (tex),(pdf - the finished result if all goes well)

  3. Installing new packages in LaTeX

    1. Instructions (pdf)
    2. Instructions (tex)

  4. Installing and custimizing R

    1. Instructions (pdf)
    2. Instructions (tex)

  5. Installing and customizing RStudio

    1. Instructions (pdf)
    2. Instructions (tex)

  6. Installing and customizing Sweave
    Sweave is already part of the generic R distribution. However, make sure the following Sweave style file is always in your working folder (see below under "test run"). You can also find it in your R program folder under share/texmf/tex/latex. Here is the latest version: Sweave.sty

  7. A test run with Sweave

    This is testrun.rnw, a Sweave file created with RStudio. Proceed as follows:

    1. Create a "test" folder directly under your course folder and download the testrun.rnw file to that folder.
    2. Also, download the Sweave.sty style file posted above into your "test" folder.
    3. Then start RStudio. This should automatically start R as well and show it in the bottom left window.
    4. If you haven't already installed the R package "xtable" during your R installation, do it now. (See RStudio instructions above)
    5. In RStudio, open the "testrun.rnw" file, and follow the instructions at the top of the file. NOTE: It's prudent to always repeat the sweave 2-3 times (so all internal links go through).
      The finished product should look llike this: testrun.pdf

  8. How to convert Excel tables into LaTeX and insert them into a LaTeX document (probably not needed for this course, but useful)

    1. Instructions (pdf)
    2. Instructions (tex)
    3. Excel table (excel)

Course Content

Module 1: Classical Linear Regression and Least Squares

Overview of Estimation Frameworks and Estimators

CLRM and Least Squares

  • wage data (tab-delimited .txt)
  • fundraising (tab-delimited .txt)


Finite Sample Properties of the OLS Estimator


Module 2: Maximum Likelihood Estimation


Module 3: Asymptotic Properties, Inference, Hypothesis Testing

Recap: Asymptotic Theory

Hypothesis Testing, Model Selection, and Prediction in Least Squares and ML Estimation


Module 4: Instrumental Variables, Generalized Linear Regression

Omitted Variables, Instrumental Variables, and Two-Stage Least Squares


Generalized Least Squares, Robust Estimation, Heteroskedasticity


Generalized Least Squares and Serial Correlation


Module 5: Estimation of Treatment Effects


Estimation via Regression

  • Lecture Notes (pdf)(tex)
  • R material

Estimation via Propensity Score

Estimation via Matching

Balance in Matching

  • Simulated housing data example (pdf)(sweave)
  • Prep script to generate graphs for housing data example (sweave)
  • Main script to generate graphs for housing data example (pdf)(sweave)

  • Coastal flood zone presentation (pdf)
  • Mountain pine beetle paper (see e-mail)


Module 6: Introduction to Bayesian Econometrics

Bayesian Econometrics: Introduction


In progress


Normal Regression with Conjugate Priors

Normal Regression with Independent Priors

Posterior Predictive Densitites and p-Values, Highest Posterior Density Intervals







Problem Sets

  • PS1 (pdf)(sweave) - due Feb. 2, 2017
  • PS2 (pdf)(sweave) - due Feb. 21, 2017
  • PS3 (pdf)(sweave) - due Mar. 27, 2017 (Monday, my office)
  • PS4 (pdf) (no sweave) - due April 11
    • homeprice data (tab-delimited txt)
  • PS5 (pdf)(sweave) - due May 2
    • gasoline data (tab-delimited txt)

Exam Practice and Solutions

  • midterm spring 2011 with solutions (pdf) (tex)
  • midterm spring 2012 with solutions (pdf) (tex)
  • midterm spring 2013 with solutions (pdf) (tex)
  • midterm spring 2014 with solutions (pdf) (tex)
  • midterm spring 2015 with solutions (pdf) (tex)
  • midterm spring 2016 with solutions (pdf) (tex)
  • midterm spring 2017 with solutions (pdf) (tex)

  • final spring 2011 with solutions (pdf) (tex)
  • final spring 2012 with solutions (pdf) (tex)
  • final spring 2013 with solutions (pdf) (tex)
  • final spring 2014 with solutions (pdf) (tex)
  • final spring 2015 with solutions (pdf) (tex)
  • final spring 2016 with solutions (pdf) (tex)
  • final spring 2017 with solutions (pdf) (tex)