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ESTIMATE -- Early Summer Tutorial In Modern Applied Tools of Econometrics

Date of Appearance: 
Jan 21, 2013
Duration of the course: 
Jan 21, 2013 to Jun 2, 2013
Application Deadline: 
May 20, 2013

Course Details

Summer Schools

Course Fees

Not specified.

Location of Course

486 W. Circle Dr. 110 Marshall-Adams Hall
East Lansing, 48824
United States

ESTIMATE - Early Summer Tutorial in Modern Applied Tools of Econometrics
Presented by the Department of Economics at Michigan State University
-Jeffrey Wooldridge (
- Timothy Vogelsang (
May 31 – June 2, 2013
OBJECTIVES:  This is a short course in econometrics aimed at applied researchers wanting to use state-of-the-art econometrics in their empirical research.  The presentation will focus on understanding when various models and estimation methods are appropriate as well as how to conduct proper inference in a variety of settings.  The methods will be illustrated using several empirical examples using the econometrics package Stata.  It will be assumed that participants in ÊSTIMATE have an econometrics background comparable to a first-year PhD econometrics sequence.
1. Linear Panel Data Models with Microeconomic Data
        a. Random Effects, Fixed Effects, Differencing
        b. Correlated Random Effects
        c. Instrumental Variables
        d. Dynamic Models
2. Introduction to Regression with Time Series Data
        a. Basics of Time Series Regression in Stationary/Weak Dependent Settings
        b. Strict and Weak Exogeneity
        c. Time Trends
        d. Serial Correlation Robust Standard Errors (aka Newey-West)
        e. Fixed-b Asymptotics
3. Linear Panel Data Models with Many Time Periods
        a. Large-T Asymptotics
        b. Robust Inference: Clustering and Driscoll-Kraay Standard Errors      
        c. Link Between Individual/Time Period Dummies and Exogeneity Assumptions
        d. Perils of Two-Way Clustering in a Panel Setting
4. Nonlinear Panel Data Models with Microeconomic Data
        a. Fixed Effects, Conditional MLE, Correlated Random Effects
        b. Dynamic Models with Unobserved Heterogeneity
5. Control Function Methods for Handling Endogenous Explanatory Variables
        a. Linear Models with Random Slopes; Endogenous Switching
        b. Nonlinear Models; Limited Dependent Variables
        c. Combining Control Function and Correlated Random Effect Methods for Panel Data
REGISTRATION: For registration and additional information please visit  


  • Econometrics background comparable to a first-year PhD econometrics sequence.

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