Learning and Resources for Econometrics

Econometrics:

• 73-374 Econometrics II by Professor David Childers.
  • Creating nice tables in R: function stargazer() in library(stargazer).
  • IV regressions in R: Load library containing IV command ivreg() in library(AER).
  • Causal Graph in R: Libraries to create and analyze causal graphs library(dagitty) and library(ggdag).
• Metrics Notes by Professor Peter Hull.
  • Instrumental variable with Difference-in-Difference: DDIV/ Duflo, 2001/ Stata
  • DID

• RE vs FE

• Empirical IO

• Topics in Empirical IO - by Professor Kohei Kawaguchi (HKUST)

• IO Course

• Structual estimation and also ResEcon703

• Micro Data for Macro Models by Professor Thomas Winberry

& Also, additional great resource - NYU Bootcamp

& Excellent material from Professor Johnston

• AES Summer School 2019 - structural estimation and slides

• Dynamic Structual Model Summer School - ANU: amazing resources.

• Literature on Recent Advances in Applied Micro Methods

• Contract theory

• Empirical Method in IO

• Public Econ

• Empirical Corporate Finance - PHD Notes by Prof Todd A. Gormley

Data and Topics

• Private Equity and Venture Capital:
  • Amazing datasets in PE and VC by Professor Michael Ewens.
• Patents data: http://dvn.iq.harvard.edu/dvn/dv/patent . see paper “The role of human capital: Evidence from corporate innovation” by Liu, Mao and Tian (2023).

Other Nice Sources:

• A collection from Xuanli Zhu: Guide2EconRA

• Theory talk guidance: How to give an economic theory talk

• Macro Finance & 2023 / 2022 /

• Data Science for Econ

• Macro etc. by Prof Chris Edmond

Job Market

• [Job Market Advice from] Professor Kerry Y. Siani from MIT. (https://sites.google.com/view/kerryyangsiani/for-students)