Applications of Econometrics

Overview 

Objective :

Discussion of several econometric methods (see the syllabus) and of their applications, notably through the replication of published results.

Structure :

Six classes of two hours. Each class will start with short presentations of methodological papers or of papers relying on a given method. Related exercises (using Stata) and issues raised by the practical implementation of the method will follow.

Each paper will be presented by a group of two students. You will choose the paper among the references listed below. Papers can be found here.

Tutorials will be sent in advance so that you can prepare them before the class.

Grading : The grade will be based on your partiticipation during the class (answers to tutorials, papers presentation) and on a guided research project.

Papers allocation: please fill in this document :

https://lite.framacalc.org/Presentations

Stata : the "cheat sheets" provide a nice recap of the main commands you will need.

Papers can be found here :

https://drive.google.com/drive/folders/11O1_lBp38s9VbLtKfnzMZf62qD9H9-E9

 

Part 1  Introduction, Diff-in-diff, Natural Experiment

Slides

References

Yi Chen, Ziying Fan, Xiaomin Gu, and Li-An Zhou, 2020, Arrival of Young Talent : the Sent Down Movement and Rural Education in China, American Economic Review

Gordon B. Dahl, Christina Felfe, Paul Frijters, & Helmut Rainer, 2022, Caught between Cultures: Unintended Consequences of Improving Opportunity for Immigrant Girls, Review of Economic Studies


Tutorial : during class : download data here. Replicate the first column of Table 1 (p 39). The life satisfaction variable is z_ls.

For next class : download questions here. 

Link


Part 2 : Regression Discontinuity Design

2.1 Sharp design (Class 2) 

Slides 

Simulations

2.2 Fuzzy design and kink design (Class 3)

Slides


Method :

David S. Lee & Thomas Lemieux, 2010. Regression Discontinuity Designs in Economics, Journal of Economic Literature, American Economic Association, vol. 48(2), pages 281-355, June -->Read p281 to p335

Cattaneo, Idrobo and Titiunik (2019): A Practical Introduction to Regression Discontinuity Designs: Foundations. Cambridge Elements: Quantitative and Computational Methods for Social Science, Cambridge University Press. -->Read p 40 to p50 and p88 to p107

Papers for Class 2

Per Pettersson-Lidbom, 2008, Do Parties Matter for Economic Outcomes? A Regression Discontinuity Approach. Journal of the European Economic Association 6(5): 1037-1056.

Andrew C. Eggers,  Anthony Fowler, Jens Hainmueller, Andrew B. Hall and James M. Snyder, 2015. On the Validity of the Regression Discontinuity Design for Estimating Electoral Effects:New Evidence from Over 40,000 Close Races, American Journal of Political Science, Vol. 59, No. 1 (January), pp. 259-274

Papers for Class 3

Sam Asher, Paul Novosad, 2020, Rural Roads and Local Economic Development, American Economic Review 110:3 

Landais, Camille. 2015, Assessing the Welfare Effects of Unemployment Benefits Using the Regression Kink Design, American Economic Journal: Economic Policy, 7 (4): 243-78. 


Additional references

- for ideas and suitable settings :

Andrew C. Eggers, Ronny Freier, Veronica Grembi and Tommaso Nannicini, 2018. Regression Discontinuity Designs Based on Population Thresholds: Pitfalls and Solutions, American Journal of Political Science,  vol. 62(1), pages 210-229, January.

- for practical implementation :

Guido Imbens & Karthik Kalyanaraman, 2012, Optimal Bandwith Choice, Review of Economic Studies

Justin McCrary, 2008, Manipulation of the running variable in the regression discontinuity design : A density test, Journal of Econometrics

Useful Stata commands

https://sites.google.com/site/rdpackages/home

https://eml.berkeley.edu/~jmccrary/DCdensity/

Tutorial :

questions : tutorial 2 - RDD

dataset : tutorial2.dta

dofile : tutorial2.do

For your information :

Source of original data:  https://www.aeaweb.org/articles?id=10.1257/app.20120387

dofile for creating tutorial2.dta : tutorial2_prep


Part 3 : Propensity Score Matching 

Slides

Tutorial 

Rajeev H. Dehejia and Sadek Wahba, 1999, Causal Effects in Nonexperimental Studies:Reevaluating the Evaluation of TrainingPrograms. Journal of the American Statistical Association 94(448): 1053-1062.

Toke Aidt and Raphaël Franck, 2015, Democratization Under the Threat of Revolution: Evidence From the Great Reform Act of1832. Econometrica, Volume: 83 Issue 2

David McKenzie, John Gibson and Steve Stillman, 2010. How Important Is Selection? Experimental vs. Non-experimental Measures of the Income Gains from Migration, Journal of the European Economic Association Volume: 8 Issue 4, ISSN: 1542-4766

additional references

Marco Caliendo and Sabine Kopeinig, 2008. Some Practical Guidance for the Implementation of Propensity Score Matching. Journal of Economic Surveys, 22 (1): 31-72.


Part 4 : Grouped patterns of heterogeneity, two-way fixed effects with heterogeneous treatment effects

Slides

Stéphane Bonhomme and Elena Manresa, 2015, Grouped Patterns of Heterogeneity in Panel Data, Econometrica

de Chaisemartin d'Haultfoeuille, forthcoming, Two-Way Fixed Effects and Differences-in-Differences with Heterogeneous Treatment Effects: A Survey  Econometrics Journal 

de Chaisemartin d'Haultfoeuille, 2020, Two-way fixed effects estimators with heterogeneous treatment effects, American Economic Review, vol. 110, no. 9,(pp. 2964-96). 


Online references

Scott Cunningham, Causal Inference : the Mixtape.

Impact Evaluation in Practice is a good read if you have a limited background in econometrics/maths and struggle to understand what the various methods do.

Abadie, Cattaneo, 2018, Econometric Methods for Program Evaluation, Annual Review of Economics

 Textbooks

Wooldridge, 2010, Econometric Analysis of Cross Section and Panel Data

Angrist and Pischke, Mostly Harmless Econometrics

Wooldrigde, Introductory Econometrics : a Modern Approach (also available in French : Introduction à l'Econométrie)

Papers' replication

The best way to learn how to apply econometric methods is to replicate existing papers. Papers published in top five journals usually provide you with their data and code. You will also find interesting material here:

http://replication.uni-goettingen.de/wiki/index.php/Main_Page


https://i4replication.org

https://dataverse.harvard.edu/

https://ejd.econ.mathematik.uni-ulm.de/