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2024 Stata

Economics Virtual Symposium

7 November 2024

What is the Economics Virtual Symposium?

Join us for the 2024 Stata Economics Virtual Symposium, a meeting of econometric theory and applied research using Stata. The program consists of invited talks by top Stata users and researchers in economics, and the virtual platform allows you to experience this one-day event from wherever you are.


Presenters + abstracts

Enjoy insightful and informative presentations by these experienced Stata users in the field.

Christopher Frank Parmeter

Miami Herber Business School, University of Miami

Vincenzo Verardi

LouRIM-LSM at UC Louvain

Peter Hull

Brown University

Yiru Wang

University of Pittsburgh

Carolina Caetano

University of Georgia

Zhuan Pei

Cornell University

Alyssa Carlson

University of Missouri-Columbia

Agenda

All times Central Standard Time

8:30 a.m.

The Xistence of Inefficiency: Lasso + SFA

Christopher Frank Parmeter, Miami Herber Business School, University of Miami

View abstract

Abstract coming soon

9:30 a.m.

Efficient estimation of regression models with spillovers: flexible parametric and semi-parametric approaches

Vincenzo Verardi, LouRIM-LSM at UC Louvain, Belgium

Joint work with: Nicolas Debarsy, CNRS, Lille & Catherine Vermandele, ULB, Brussels

View abstract

Abstract coming soon

10:30 a.m.

Causal inference with formula instruments

Peter Hull, Brown University

View abstract

Many studies use instruments or treatments that combine a set of exogenous shocks with other predetermined variables via a known formula. Examples include shift-share instruments and measures of social or spatial spillovers. I review recent econometric tools for this setting that leverage the assignment process of the exogenous shocks and the structure of the formula for identification. I compare this design-based approach with conventional estimation strategies based on conditional unconfoundedness and contrast it with alternative strategies that leverage a model for unobservables.

11:30 a.m.

Parameter path estimation in unstable environments: The tvpreg command

Yiru Wang, University of Pittsburgh

View abstract

This article introduces a novel command, tvpreg, that implements the following path estimators: (i) the asymptotically weighted average risk minimizing path estimators by Müller and Petalas, 2010, Review of Economic Studies 77: 1508–1539; (ii) and the path estimators proposed in Inoue, Rossi, and Wang, 2024, Journal of Econometrics: 105726, namely, the time-varying parameter local projections, the time-varying parameter instrumental-variables estimator, and the version of the latter estimator robust to weak instruments.

12:30 p.m.

Lunch

1:30 p.m.

Bunching identification strategies

Carolina Caetano, University of Georgia

View abstract

This talk gives an overview of the existing strategies for identification of causal effects in models with endogeneity that leverage bunching in the treatment variable. It covers some of the most user-friendly estimators, some strategies for robustness analysis, and a light discussion of the most recent nonparametric methods for identification of local effects.

2:30 p.m.

Supercompliers

Zhuan Pei, Cornell University

View abstract

Abstract coming soon

3:30 p.m.

Heteroskedasticity and heterogeneity in sample-selection models

Alyssa Carlson, University of Missouri-Columbia

View abstract

This presentation provides a practical guide for Stata users on the consequences of heteroskedasticity and heterogeneity in sample-selection models and estimators. First, we review the consequences of heteroskedasticity in the outcome equation, highlighting when standard sample-selection estimators are and are not consistent and how to obtain valid inference using the gtsheckman command. Given the strong implications of heteroskedasticity, we propose three tests to determine if and what type of heteroskedasticity is present. Next we consider the case of heteroskedasticity in both the outcome and sample-selection equation, again utilizing the gtsheckman command to implement a general control function approach. Finally, we extend to the panel-data setting, where we show how the same methods introduced earlier provide consistent estimation of panel-data sample-selection models that incorporate individual heterogeneity in both the intercept and the slopes.

4:30 p.m.

Adjourn

Registration: Free

The symposium is conducted in real time and will not be recorded, so all registered users are encouraged to attend. Login information will be sent to registered users on 6 November. Seats are limited. Register now.