资料:经济系博一课程和编程

I. 北美经济系博士一年级的训练应该都很标准,基本上是两学期上完六门三高(微观/宏观/计量 I&II)。第一年结束后是资格考,然后第二年才开始进入各类fields课程。此处列下一些当时整理的资料:

Micro

J. Levin’s Micro Notes

Macro

1.General Notes: Dirk Krueger’s Notes (2012) & Per Krusell’s Notes (2014)

2. Violante’s Heterogeneity in Macroeconomics (2014 Spring)

Econometrics

Hensen’s Econometrics Notes (2017)

II. 第一年之后可能会有用的工具:

Structural Model

1. Discrete Choice Methods with Simulation, by Kenneth Train

2. Practical Methods for Estimation of Dynamic Discrete Choice Models, by Arcidiacono and Ellickson

Big Data & ML

1. Matt Taddy’s Big Data Course

2.Thorsten Joachims’s Counterfactual Machine Learning

3. Benjamin Soltoff’s Computing for the Social Science

4. Econ-ML 

III. 还有一些编程的资料:

Python

1. Learn Python 3 the Hard Way

2. 廖雪峰的Python 3 教程

3. Python Data Science Handbook

R

1.  R in Action (Book)

2. Hadley Wickham’s R for Data Science

3. Hadley Wickham’s Advanced R  with a recommended Solutions

4. R Reference Card 2.0

5. Geocomputation with R

LaTeX

1. The Not So Short Introduction To LaTeX (Chinese Version, 2017)

2.Wikibooks: LaTeX or Presentation

3. John C Frain’s Applied LATEX for Economists, Social Scientists and Others (2014)

GIS

MIT GIS Workshop

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