vyassreenivas Goto Github PK

advanced-did

Advanced Differnce-in-Differences Mixtape Track

aom_web_scraping

A simple example of a Python script to scrape information of multiple websites - in this case of the names and affiliations of the participants to the Academy of Management Annual Meeting in 2014

bandits

This repo includes the code for running some of the seminal papers on organizational learning under uncertainty

causal-inference

Causal Inference Mixtape Sessions

causal-inference-1

Causal Inference 1 Mixtape Session taught by Scott Cunningham

causal-inference-2

Causal Inference II Mixtape Session taught by Scott Cunningham

causal-inference-3

Causal Inference 3 Mixtape Session taught by Scott Cunningham

causalbook

Replication code and downloadable example data sets for The Effect

causalityslides

Slides for the Seattle University Causal Inference Class

difference-in-differences

Difference-in-Differences

doing-applied-research

Doing Applied Economics Research Mixtape Track taught by Mark Anderson and Daniel Rees

econometricsslides

This is the repository for the slides used in the Seattle University Econometrics course

fahachapter8

Code Used for the Chapter 8 Lecture of the Course Foundations and Applications of Humanities Analytics, offered through the Santa Fe Institute's Complexity Explorer platform and funded by the National Endowment for the Humanities.

garbage_can_model

This is the recreation of the Cohen, March and Olsen (1972) Garbage Can Model or organizational decision making

instrumental-variables

Instrumental Variables Mixtape Track

machine-learning

Machine Learning and Causal Inference taught by Brigham Frandsen

march_1991_exploration_and_exploitation

This is a reproduction of the March 1991 computational model of exploration and exploitation in organizational learning. The code has been reproduced in R, using the information from the paper.

march_1991_original

This is a recreation of March's 1991 model of exploration and exploitation (in Python 3)

measuring-corporate-culture-using-machine-learning

Code Repository for MS20190155

mesa

Mesa is an open-source Python library for agent-based modeling, ideal for simulating complex systems and exploring emergent behaviors.

mesa-abm-tutorial

modsimpy

Text and supporting code for Modeling and Simulation in Python

nk

Description This repo includes the code for running some of the seminal papers on organizational learning under complexity

nk_model

Contains simple building blocks for NK modeling

regression-discontinuity

Regression Discontinuity Mixtape Track taught by Rocio Titiunik

respol_patents_code

https://github.com/jcgcarranza/respol_patents_code

ros-examples

Regression and other stories R examples

smj_code

synthetic-control-and-clustering

Synthetic-Control-and-Clustering taught by Alberto Abadie

text-analytics-with-python

Learn how to process, classify, cluster, summarize, understand syntax, semantics and sentiment of text data with the power of Python! This repository contains code and datasets used in my book, "Text Analytics with Python" published by Apress/Springer.