Some Useful Links

In case links may die in the future, download all available pdf files as soon as possible.

Macroeconomics Lecture notes:

General Topics

Groth (Copenhagen): https://web.econ.ku.dk/okocg/VM/VM-general/Material/Chapters-VM.htm

Acemoglu (MIT) growth: https://www.theigc.org/wp-content/uploads/2016/06/acemoglu-2007.pdf

William (WashU Louis): https://www.albany.edu/~am755146/teaching/aeco601/Williamson%20notes.pdf

UC Irvine (concise & clear): http://keeganskeate.com/pdfs/macroeconomics.pdf

Krueger (Penn): https://perhuaman.files.wordpress.com/2014/06/macrotheory-dirk-krueger.pdf

Le-Van Cuong (Paris): https://sites.google.com/site/cafeseminaire/courses/4-some-macroeconomic-growth-models

Krusell (Yale): http://www.econ.yale.edu/smith/econ510a/book.pdf

DSGE:

Hnatkovska (UBC): https://www.theigc.org/wp-content/uploads/2015/09/ISI2_2015.pdf

Bibiie (Oxford): https://www.nuffield.ox.ac.uk/Users/Bilbiie/teaching_files/notes_oxford_final.pdf

Stata: https://blog.stata.com/2018/04/23/dynamic-stochastic-general-equilibrium-models-for-policy-analysis/

den Haan (lots of numerical treatment): http://econ.lse.ac.uk/staff/wdenhaan/notes.htm

RBC:

Wieland (UC San Diego): https://econweb.ucsd.edu/~gramey/210C/Wieland_210C_S18_Lecture_Notes.pdf

Carroll (JHU): https://www.econ2.jhu.edu/people/ccarroll/public/LectureNotes/DSGEModels/RBC-Prescott.pdf

other by his: https://www.econ2.jhu.edu/people/ccarroll/public/LectureNotes/

Solomon (Montreal): https://mpra.ub.uni-muenchen.de/70321/8/MPRA_paper_70321.pdf

New Keynesian:

Blanchard: https://ocw.mit.edu/courses/economics/14-452-macroeconomic-theory-ii-spring-2007/lecture-notes/slides08.pdf

Brugnolini: https://lucabrugnolini.github.io/teaching/LB_notes.pdf

Collection: https://sites.google.com/site/buchananhodgman/lecture-notes

Production network propagation shock:

Leontief: https://www.math.umd.edu/~immortal/MATH401/ch_leontief.pdf

Empirical: https://econweb.ucsd.edu/~vramey/research/Shocks_HOM_Ramey_published_corrected.pdf?mod=article_inline

Primer: https://vasco-m-carvalho.github.io/pdfs/ProductionNetworks.pdf

Acemoglu: https://economics.mit.edu/files/13466

(his slide): https://economics.mit.edu/files/9790

Altinoglu: https://www.sciencedirect.com/science/article/pii/S0304393218305610?casa_token=Q6sqxbvRCT4AAAAA:TPV29GjPUL1wOywlxzIQCc8OEH2pNTb-D8QmY49IXCqe-KASR5TMSpYgBC7ebLEgpTBRlYbRIQ

Whelan (Dublin) (undergrad): https://www.karlwhelan.com/Macro2/Whelan-Lecture-Notes.pdf

Sims (Notre Dame) (intermediate): https://www3.nd.edu/~esims1/gls_int_macro.pdf

Nymoen (Oslo) : (intro to dynamics) https://www.uio.no/studier/emner/sv/oekonomi/ECON4410/h08/undervisningsmateriale/h08_3410_120808.pdf

Math for Econs:

Dawnkins (Lamar) Calculus and Optimization: https://tutorial.math.lamar.edu/

Groth’s exercises (Copenhagen) https://www.economics.ku.dk/staff/vip/?pure=en%2Fpersons%2Fchristian-groth(bc3cc402-5f91-49e7-a653-860ed5ca1848)%2Fpublications.html&page=6

Le-Van Cuong (Paris): https://sites.google.com/site/cafeseminaire/courses/maths-for-economists

Reshef (Virginia) / based on Alpha Chiang (1967)’s “Fundamental Methods of Mathematical Economics” http://www.parisschoolofeconomics.com/reshef-ariell/Econ509/Lectures509.pdf

Mitra (Cornell) / have problem sets and solutions https://pages.nyu.edu/debraj/TapanMitra/Lectures/LectureNotes2011.pdf

Quick tips/ summaries: http://faculty.bcitbusiness.ca/kevinw/5701/5701_Lecture_Notes-14-3.htm

List of well-known closed-form results in Economics (Zevelev, 2014): https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2354226

Youtube courses:

Principle of Macroeconomics (MSU): https://youtube.com/playlist?list=PLdLiRaajwSXRcJxAeIHjVGukaJZoJtkXz

Principle of Microeconomics (MIT): https://youtube.com/playlist?list=PL61533C166E8B0028

Econometrics (UO): https://youtube.com/playlist?list=PLD15D38DC7AA3B737

Development Econs (MIT): https://youtube.com/playlist?list=PLUl4u3cNGP63-t0r0aC3noJiIOmj33S_Q

Math for Econs (UCI): https://youtube.com/playlist?list=PLqOZ6FD_RQ7n8yvjW0DAxRAmou8EOzbpD

Single Variable Calculus (MIT): https://youtube.com/playlist?list=PL590CCC2BC5AF3BC1

Multivariable Calculus (MIT): https://youtube.com/playlist?list=PL4C4C8A7D06566F38

Highlights of Calculus (MIT): https://youtube.com/playlist?list=PLBE9407EA64E2C318

Differential Equations (MIT): https://youtube.com/playlist?list=PLUl4u3cNGP63oTpyxCMLKt_JmB0WtSZfG

Linear Algebra (MIT): https://youtube.com/playlist?list=PL49CF3715CB9EF31D

Convex Optimization (Stanford): https://youtube.com/playlist?list=PL3940DD956CDF0622

Probability (MIT): https://youtube.com/playlist?list=PLUl4u3cNGP60hI9ATjSFgLZpbNJ7myAg6

Optimization (CMU ML): https://www.youtube.com/playlist?list=PL7y-1rk2cCsDOv91McLOnV4kExFfTB7dU

Applied Probability (MIT): https://youtube.com/playlist?list=PLUl4u3cNGP61MdtwGTqZA0MreSaDybji8

Advanced Macro (Berlin): https://youtube.com/playlist?list=PLJZlW3ik4xixAhVnY0aaTrz72XCZsygEA

Teaching how to solve things:

Constantin Burgi (GWU): https://youtube.com/playlist?list=PLXbXFxCCVuUWgdvabVrFMjgXFaArAdDrF

David Jinkins (Copenhagen): https://www.youtube.com/channel/UCxWh3hcY6Jbnoza3WLCjMXA/videos

Thomas J Sargent: https://www.youtube.com/channel/UCA8WXlZURaLVgp_Foo3NUlg/featured

Understanding Math intuitively (3B1B): https://www.youtube.com/channel/UCYO_jab_esuFRV4b17AJtAw

LaTeX:

Beamer: https://www.overleaf.com/learn/latex/Beamer_Presentations

Tikz: https://sites.google.com/site/kochiuyu/Tikz

Cookbook: https://latex-cookbook.net/ https://ctan.org/topic/cooking

Templates: https://www.latextemplates.com/

Elsevier template: http://mirrors.ctan.org/macros/latex/contrib/els-cas-templates.zip

Guide: https://computers.tutsplus.com/tutorials/the-beginners-guide-to-using-tex-in-os-x--mac-45177

R/Python:

Teach yourself R: https://teacher.arawles.co.uk/

Cookbook R: https://rc2e.com/

R For DS: https://r4ds.had.co.nz/

DS at the command line: https://www.datascienceatthecommandline.com/1e/

Bayesian: http://camdavidsonpilon.github.io/Probabilistic-Programming-and-Bayesian-Methods-for-Hackers/

Think Python: https://greenteapress.com/thinkpython2/thinkpython2.pdf

Web scraping: https://yanfei.site/docs/dpsa/references/PyWebScrapingBook.pdf companion code: https://github.com/PacktPublishing/Python-Web-Scraping-Cookbook

Data wrangling: https://github.com/Jffrank/Books/blob/master/Python%20for%20Data%20Analysis.%20Data%20Wrangling%20with%20Pandas%2C%20NumPy%2C%20and%20IPython%20(2017%2C%20O%E2%80%99Reilly).pdf

Matlab: https://github.com/jousefm/Mega-Course-MATLAB

Computational Codes/ Models:

Numedig (Copenhagen): http://www.tjeconomics.com/numedig/

Dynare by Pfeifer: https://github.com/JohannesPfeifer/DSGE_mod

Quantecon: https://quantecon.org/

Stata Parameters Estimation: https://blog.stata.com/2017/07/11/estimating-the-parameters-of-dsge-models/#ref

Computational Econs: https://juejung.github.io/jdocs/Comp/html/index.html

PyEcons: https://github.com/davidrpugh/pyeconomics/wiki/OLG-Models

CompEcon: https://github.com/PaulFackler/CompEcon

(Python: https://github.com/randall-romero/CompEcon

Book: http://www.untag-smd.ac.id/files/Perpustakaan_Digital_1/FINANCE%20Applied%20Computational%20Economics%20And%20Finance.%5B2004.ISBN0262633094%5D.pdf)

Torres (Malaga) DSGE: https://vernonpress.com/file/740/d1714638ebf2bb09a94aa3d85778e822/1440333327.zip

IRIS Macro Toolbox: https://iris.igpmn.org/install/matlab/

De La Croix HP models: https://perso.uclouvain.be/david.delacroix/articles.html

R.Econ.Dyn. papers’ code: https://ideas.repec.org/s/red/ccodes.html

Cheatsheets:

(R)Markdown: https://rmarkdown.rstudio.com/lesson-15.HTML

LaTeX: https://wch.github.io/latexsheet/

Python: https://hakin9.org/python-cheat-sheet-for-hackers-and-developers/

Pandas: https://datacamp-community-prod.s3.amazonaws.com/dbed353d-2757-4617-8206-8767ab379ab3

Pandas2: https://www.slideshare.net/ACASH1011/pandas-cheat-sheet

Matplotlib: https://github.com/matplotlib/cheatsheets or https://storage.googleapis.com/kaggle-forum-message-attachments/994125/16813/Python_Matplotlib_Cheat_Sheet.pdf

(R) Wrangling: https://www.rstudio.com/wp-content/uploads/2015/02/data-wrangling-cheatsheet.pdf

Economics Writing:

Nikolov (Harvard): https://www.people.fas.harvard.edu/~pnikolov/resources/writingtips.pdf

Todo (Waseda): http://www.f.waseda.jp/yastodo/laboratory/TipstoWriteAThesis20141119.pdf

GPEM (TeX tutorial): https://www.econ.tohoku.ac.jp/english/files2020/GPEM_Latex.pdf

Impact factor: https://ideas.repec.org/top/top.journals.simple.html

Paper evaluation through the eyes of a referee: https://web2.econ.ku.dk/okocg/Forside/Evaluating%20a%20research%20article.pdf

Selected online courses:

MIT

  1. Intro to coding https://www.edx.org/course/introduction-to-computer-science-and-programming-7
  2. Python and data https://www.edx.org/course/introduction-to-computational-thinking-and-data-4
  3. Micro (Advanced Placement) https://www.edx.org/course/ap-microeconomics
  4. Macro (Advanced Placement) https://www.edx.org/course/ap-macroeconomics
  5. Prob. and Stats. https://ocw.mit.edu/courses/mathematics/18-05-introduction-to-probability-and-statistics-spring-2014/calendar/ or: https://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-041-probabilistic-systems-analysis-and-applied-probability-fall-2010/ (Video)
  6. Comp & DS https://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-0002-introduction-to-computational-thinking-and-data-science-fall-2016/
  7. Intermediate Macro:
 https://ocw.mit.edu/courses/economics/14-05-intermediate-macroeconomics-spring-2013/lecture-notes/
  8. Advanced Macro 1:
 https://ocw.mit.edu/courses/economics/14-461-advanced-macroeconomics-i-fall-2012/
  9. Advanced Macro 2:
 https://ocw.mit.edu/courses/economics/14-462-advanced-macroeconomics-ii-spring-2004/https://ocw.mit.edu/courses/economics/14-462-advanced-macroeconomics-ii-spring-2007/index.htm

IMF Courses:

  1. https://www.edx.org/course/financial-programming-and-policies-part-1-macroeco
  2. https://www.edx.org/course/financial-programming-and-policies-part-2-progra-2
  3. https://www.edx.org/course/compilation-basics-for-macroeconomic-statistics
  4. https://www.edx.org/course/public-sector-debt-statistics
  5. https://www.edx.org/course/financial-market-analysis
  6. https://www.edx.org/course/macroeconometric-forecasting-2
  7. https://www.edx.org/course/monetary-policy-analysis-and-forecasting

Essential for Econs:

  1. Optimization:
 https://agecon2.tamu.edu/people/faculty/woodward-richard/642/notes/default.htm
  2. Dynamic Programming:
 https://absalon.ku.dk/courses/25988/wiki
  3. Linear Algebra:
 https://ocw.mit.edu/courses/mathematics/18-06sc-linear-algebra-fall-2011/ax-b-and-the-four-subspaces/the-geometry-of-linear-equations/
  4. SIngle Variable Calculus: 
https://ocw.mit.edu/courses/mathematics/18-01sc-single-variable-calculus-fall-2010/
  5. Multi-variable Calculus: 
https://ocw.mit.edu/courses/mathematics/18-02sc-multivariable-calculus-fall-2010/
  6. Differential Equations:
 https://ocw.mit.edu/courses/mathematics/18-03sc-differential-equations-fall-2011/
  7. Development Economics (Macroeconomics): 
https://ocw.mit.edu/courses/economics/14-772-development-economics-macroeconomics-spring-2013/
  8. Econometrics with R-code:
 https://ocw.mit.edu/courses/economics/14-382-econometrics-spring-2017/
  9. Economic Growth:
 https://ocw.mit.edu/courses/economics/14-452-economic-growth-fall-2016/
  10. Time-series analysis with Matlab:
 https://ocw.mit.edu/courses/economics/14-384-time-series-analysis-fall-2013/index.htm
  11. Maxtrix method in Data Analysis:
 https://ocw.mit.edu/courses/mathematics/18-065-matrix-methods-in-data-analysis-signal-processing-and-machine-learning-spring-2018/
  12. Principles of Econs: https://online.stanford.edu/courses/sohs-yeconschool-principles-economics
  13. Convex Optimization: https://online.stanford.edu/courses/soe-yeecvx101-convex-optimization

Data Science:

  1. Harvard (R): 
https://www.edx.org/professional-certificate/harvardx-data-science
  2. IBM (SQL+Python)
: https://www.edx.org/professional-certificate/ibm-data-science

Tohoku University Data Science training (Intro to Python):

  1. Intro to Python: https://sites.google.com/view/gsis-ilo-skill-up-training/home

  2. Training Camp 1: https://sites.google.com/view/gsis-ilo-trainingcampi/home

  3. Linear Regression: https://sites.google.com/view/gsis-ilo-trainingcampi/lessons/lesson-v-supervised-learning/linear-regression?authuser=0

Written on January 10, 2023