EconResources

• It contains some useful resources in economics.

• Some resources are friendly with Mandarin-speaking users like me.

• The different fields can be found here

• The collections for codes and coding skills can be found here

• The collections for data and some replication codes can be found here

• Comments are welcome. jianqihuang02 [at] gmail [dot] com

Causal Inference and Econometrics

• Causal Inference: Scott.

• The Effect: An Introduction to Research Design and Causality: Containing R, Stata, and Python codes.

• Introduction to Econometrics with R

• Mixed Models with R

• Applied Empirical Methods https://github.com/paulgp/applied-methods-phd: designed for graduate students learning econometric methods using empirical research.

• STAT 286/GOV 203

• Introduction to Computational Finance and Financial Econometrics with R

• Statistical Tools for Causal Inference other useful resource given by writter is here

• Econometrics (Master in Econ, 1st year): Jean-Marc Robin(Science Po)

• Probability and Statistics (Master in Econ, 1st year): Jean-Marc Robin(Science Po)

• Applied Micro in Stata Workshop, RoME 2022

• 因果推断与工资分解方法：理论与应用

• Metric's Note

• Causal ML

• Advanced Statistical Methods for Observational Studies

• Statistical Tools for Causal Inference

Math and Statistics

• Statistical Inference via Data Science https://moderndive.com/

• Doing Bayesian Data Analysis https://bookdown.org/content/3686/

• STAT545:Data wrangling, exploration, and analysis with R

• https://www.statlearning.com/ The classic book: An Introduction to Statistical Learning.

• Statistics Inference: Data Analyst Handbook

• Statistical Inference via Data Science https://moderndive.com/ using R and tidyverse to do statistical inference.

• Bayesian Stats: using Julia to apply Bayesian Statistics.

• Lecture Notes for STAT 709: Mathematical Statistics

• Applied Nonparametric and Modern Statistics

• 应用随机过程：介绍随机过程的基本概念及鞅和在金融中的应用。

Data Science

• Julia Data Science

• Using Spatial Data with R: a quick introduction to spatial data with R.

• Spatial Data Science: Getting a deeper learning in Spatial Data Science.

• Computational and Inferential Thinking it is full of statistic methods to do data science.

• Python for Data Science

• Methods for Network Analysis

• Data Science for Economics and Finance

• https://socviz.co/index.html#preface Data Visualization

• https://tellingstorieswithdata.com/ Telling stories with data.

• Data Science at the Command Line

• Data Visualization with R

• Data Science for Economists: using R.

• Data Science for Economists and Other Animals introducing the core R usuage in Econ.

• Tidy Finance

• R as GIS for Economists

• Computational Economics for PhDs: using Julia in the field of economics is getting more and more popular. written by Florian Oswald.

• Introduction to Python for Econometrics, Statistics and Numerical Analysis

• Forecasting

• Introduction to Computational Finance and Financial Econometrics with R written by Eric Zivot

• 金融时间序列讲义

• Economic Networks THEORY AND COMPUTATION written by John Stachurski and Thomas J.Sargent.

Lectures

• Abhijit Banerjee and Esther Duflo’s online course at PSE https://www.parisschoolofeconomics.eu/en/news/from-may-24-to-june-4-watch-abhijit-banerjee-and-esther-duflo-s-online-course/#partie1

• Search and Matching in Macro and Finance Virtual Seminar Series https://sammf.com/

• Useful ML tools for empirical researchers https://www.nber.org/lecture/summer-institute-2018-meet-randomistas-useful-ml-tools-empirical-researchers Development Economics Masters Lecture by Esther Dulfo

• XMU has some lectures on Bilibili, like The Advanced Econometric, Introduction to Nonparametric Analysis in Time Series Econometrics.

Macroeconomics

• Macroeconomics (FDU) Zhiwei Xu

• Lectures in Recursive Economic Dynamics: Peter Galbács

• ECON 7300 Tools for Applied Macro I(Cornell, Sp2017)

• Advanced Macroeconomics I taught by Professor Gertler

• Notes on Macroeconomic Theory(pdf)

• Macro Theory

• Advanced Macroeconomics: Models with Heterogeneous Agents José Víctor Ríos Rull and Wei Cui

• Advanced macroeconomic analysis: JENNIFER LA'O(Columbia Business School)

• PhD Computational Methods Course Fatih Guvenen(UMN)

• Advanced Macro

• Overlapping-generations (OG) Model

Micro

• Econ 711 Fall 2021 - Dan Quint

• https://www.johnquah.com/lecture-slides.html

Econometrics and Time Series

• https://web.sas.upenn.edu/schorf/classes/ VAR estimation

• Forecasting: Principles and Practice: the classic book in time-series analysis.

• SVAR

• Graduate Macro Theory II taught by Eric Sims(University of Notre Dame)

• The Econometrics of Unobservables

• Hayashi Econometrics

• Mathematical Statistics

• Econometrics: First year graduate level econometrics notes with embedded examples using the Julia language.

Strcutural Estimation

• Structural Analysis of Discrete Data and Econometric Applications Textbook.

• DSE2019

Trade and IO

• Advanced Topics in Trade taught by ​Heiwai Tang

• Quantitative Dynamic Model taught by Daniel XU.

• Graduate Trade

• QUANTITATIVE INTERNATIONAL TRADE(pdf)

• Empirical Methods for Industrial Organization taught by Matthew Shum(Caltech).

• EIO

• Organizational Economics II taught by Daniel Barron(Northwestern).

Other Fields

• Dynamic Contracts

• Public Econ

• Dynamic Fiscal Policy in Political and International Economies:

• Urban Economics

• graduate-urban-economics

• Information Economics

• ORGANIZATIONAL ECONOMICS

• Environmental Economics

• Political Economy of Development: it is a online book built by Bookdown, has some great material in development field.

• Health Economics Teaching Materials Repository

• Resources in Personnel Economics

• Inequality

• Insurance

• Master EMI: Understanding economic fluctuations

• PDE for Finance

Research Guide

• Guidelines: Research Design & term paper draft

• Guidelines: Term paper

• https://gregmankiw.blogspot.com/search?q=advice: the research suggestions from Greg Mankiw.

• https://blogs.ubc.ca/khead/research/research-advice: collected research advice by Keith Head.

• https://sites.google.com/site/mounirkaradja/resources: Tips and resources for research.

• https://sites.google.com/view/kleintob/ph-d-students: Academic writing, communicating and many other things.

• https://sites.google.com/view/lingzhou/resources

• https://haluong.weebly.com/resources.html

• https://matt.might.net/articles/phd-school-in-pictures/

• https://christinecai.github.io/items/PublicGoods.html

• https://kidger.site/thoughts/just-know-stuff/

• Econ Job market advice

• A practical guide of the first years (for outsiders) from insiders

• https://www.ruidu.org/miscellaneous

• https://www.mariorafaelsilva.com/resources/

• Impactful Research https://truan.github.io/resources/

• Productivity and work habit https://www.patrickbaylis.com/posts/2022-02-09-productivity/2022-02-09-productivity?continueFlag=5b129f8aac804b43a5524c23d36869e8

• Resources on Computation: Compiled by Gabriel Mihalache

• Jason Blevins's Notes