Estimate Original | Michigan State University

Overview

Econometrics has long been a strength of the Economics Department at Michigan State University. ÊSTIMATE -- Early Summer Tutorial In Modern Applied Tools of Econometrics -- gives empirical practitioners, academic researchers, industry/government researchers/analysts, and graduate students, access to econometrics training usually reserved for students formally enrolled in Ph.D. programs at MSU. ÊSTIMATE is an intensive weekend workshop taught by world-class econometricians. ÊSTIMATE’s focus is modern econometric tools as used in practice. Participants learn methods and techniques to use immediately in their empirical research. ÊSTIMATE’s goal is to broaden and improve the practice of econometric methods throughout empirical research and data analysis in academics, industry and government.

Presentations focus on understanding when various models and estimation methods are appropriate as well as how to conduct proper inference in a variety of settings. Methods are illustrated with empirical examples using the econometrics software package Stata. Participants receive access to course/workshop materials including presentation slides, notes, data sets, and Stata .do files. Topics will include:

Linear Models with Cross-Sectional Data
Estimation of Causal Effects
Introduction to Regression with Time Series Data
Finite Populations, Stratified Sampling, and Cluster Sampling
Difference-in-Differences Estimation
Linear Panel Data Models with Microeconomic Data
Linear Panel Data Models with Many Time Periods
Instrumental Variables Methods with Panel Data
Nonlinear Models for Cross-Sectional Panel Data
Nonlinear Models for Panel Data

All are welcome to register for ÊSTIMATE. However, to fully benefit from the workshop, we recommend that participants have an econometrics background comparable to a first-year PhD econometrics sequence.

ÊSTIMATE Summer 2024

Instructors: Jeff Wooldridge (Michigan State University), Tim Vogelsang (Michigan State University)

Dates: June 7-9, 2024, 8:30 am to 5:30 pm, Eastern Daylight Time (EDT)

Bonus Stata Session: June 10, 8:30-12:30 EDT

Description: This course covers econometric methods that are commonly used in empirical research in a variety of data settings. The course begins with a review of ordinary least squares with cross-sectional data, with emphasis on the approximating properties of linear regression. Issues of inference in settings with finite populations and clustering will be covered. Properties of OLS and suitable inference methods for time series data are also covered on the first day. Several commonly used nonlinear models in causal inference – logit, probit, the fractional versions of these, and Poisson regression – round out the first day.

The second day begins with treatment effect estimation assuming either random or unconfounded assignment, using the methods covered on day one. Linear panel data models, from both the small-T and large-T perspectives, are also covered on day two. Pooled OLS, random effects, fixed effects, and first differencing are covered in some detail. These methods are applied to provide a modern treatment of difference-in-differences methods with panel data.

Day three covers instrumental variables estimation in both cross-sectional and panel data settings. In the latter case, we discuss how to combine fixed effects and differencing methods with instrumental variables. Nonlinear panel data models, with emphasis on binary, fractional, and nonnegative responses, are also covered on day three. The practically useful correlated random effects approach and the Poisson fixed effects estimator are the focus.

All methods will be illustrated using the software package Stata. The bonus session on Monday, June 10 shows how to use Stata for estimation in staggered difference-in-differences designs, including both linear and nonlinear models. Endogenous switching regressions to estimate treatment effects will be covered as time permits.

Participants will get the most of the course if they have had a first-year econometrics sequence at the advanced undergraduate or master’s levels – at the level of Wooldridge, Introductory Econometrics: A Modern Approach, 7e, Cengage, 2020. The Wooldridge book Econometric Analysis of Cross Section and Panel Data, 2e, MIT Press, 2010, covers much of the material but at a higher level than in the lectures.

The in-person/hybrid lectures and the Q&A sessions will be recorded and the recordings will be made available to participants.

Registration

Registration is open for ÊSTIMATE June 7-10, 2024. The workshop will be held in person with the option to attend virtually.

Course Fees

MSU students - $300 ($350 after May 15)
MSU faculty - $800 ($950 after May 15)
Non-MSU students and MSU Alumni - $600 ($700 after May 15)
General - $1,200 ($1,350 after May 15)

Group discounts are available when 5 or more people from the same organization register. For more information regarding this discount, please email estimate@econ.msu.edu.

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Course Schedule

Note: All times are in EDT.

ÊSTIMATE Frequently Asked Questions

For additional information, contact us:

ÊSTIMATE
Department of Economics
Michigan State University
486 W. Circle Dr. Room 110
East Lansing, MI 48824

Phone: (517) 355-7583
Email: estimate@econ.msu.edu

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