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539b-econometrics-

(Advanced) Applied Econometrics

advanced-did-isr

applied-methods-phd

Repo for Yale Applied Empirical Methods PHD Course

applied-microeconometrics

Course website for Ph.D. Applied Microeconometrics at the KDI School.

appliedeconometrics2021

Applied Econometrics 2021

are213

PhD Applied Econometrics class taught at UC Berkeley

arm-workshop-rsc2019

Materials for the rstudio::conf 2019 Advanced R Markdown workshop

bigdataclass

blogs-code

Code for blog posts.

caal-data-analysis

causal-inference-2

Causal Inference II Mixtape Session taught by Scott Cunningham

causal_inference

Causal Inference class notes

causality

class_slides

DSApps @ TAU 2020: Course Repo

course-materials

data-science-in-tidyverse

Materials for Data Science in the Tidyverse, a two-day workshop @ rstudio:conf(2019)

datasets

dataviz

Course materials for Kieran Healy's rstudio::conf 2020 data visualization workshop

deep-learning-for-causal-inference

Extensive tutorials for learning how to build deep learning models for causal inference (HTE) using selection on observables in Tensorflow 2.

descriptr

Generate descriptive statistics

ec524w20

Masters-level applied econometrics course—focusing on prediction—at the University of Oregon (EC424/524 during Winter quarter, 2020 Taught by Ed Rubin

econml

ALICE (Automated Learning and Intelligence for Causation and Economics) is a Microsoft Research project aimed at applying Artificial Intelligence concepts to economic decision making. One of its goals is to build a toolkit that combines state-of-the-art machine learning techniques with econometrics in order to bring automation to complex causal inference problems. To date, the ALICE Python SDK (econml) implements orthogonal machine learning algorithms such as the double machine learning work of Chernozhukov et al. This toolkit is designed to measure the causal effect of some treatment variable(s) t on an outcome variable y, controlling for a set of features x.

econometric_theory_slides

Slides for A Primer in Econometric Theory

econometrics

Econometrics lecture notes with examples using the Julia language

emlab-generation

EMlab/emlab-generation is a suite of Agent-Based Models of power generation, dealing with energy and carbon policy questions. There is focus on long-term developments.

empecon

Empirical Economics with R

energymarket

This repo contains script to aid in playing the SET3055 Energy Market Simulation game at TU Delft.

finalfit

Quickly create elegant regression results tables and plots when modelling in R

finbert

Financial Sentiment Analysis with BERT

forecasting

Time Series Forecasting Best Practices & Examples