synthetic-control

There are 29 repositories under synthetic-control topic.

  • OscarEngelbrektson/SyntheticControlMethods

    A Python package for causal inference using Synthetic Controls

    Language:Python16542148

  • station-10/awesome-marketing-machine-learning

    A curated list of awesome machine learning libraries for marketing, including media mix models, multi touch attribution, causal inference and more

    77209

  • MasaAsami/pysynthdid

    Synthetic difference in differences for Python

    Language:Jupyter Notebook613521

  • cykbennie/fbi

    Factor-Based Imputation for Missing Data

    Language:R522315

  • jeremylhour/pensynth

    A Penalized Synthetic Control Estimator for Disaggregated Data (JASA, 2021)

    Language:MATLAB326415

  • nppackages/scpi

    Prediction and inference procedures for synthetic control methods with multiple treated units and staggered adoption.

    Language:R292010
  • Causal-Inference-Using-Quasi-Experimental-Methods

    LeihuaYe/Causal-Inference-Using-Quasi-Experimental-Methods

    Causal Inference Using Quasi-Experimental Methods

    203010

  • danilofreire/homicides-sp-synth

    Replication materials for the paper "Evaluating the Effect of Homicide Prevention Strategies in São Paulo, Brazil: A Synthetic Control Approach" (2016)

    Language:TeX5203

  • jvpoulos/rnns-causal

    Replication code for "RNN-based counterfactual prediction, with an application to homestead policy and public schooling"

    Language:R5401

  • wxwx1993/wildfire_mitigation

    data repository for publicly available code and data of "Low-intensity fires mitigate the risk of catastrophic wildfires in California's forests"

    Language:R5200

  • JBris/synthetic-control-pymc

    Tutorials for the synthetic control method for causal inference using PyMC

    Language:Jupyter Notebook320
  • Synthetic_Control_Method

    Tahahaha7/Synthetic_Control_Method

    Comparative Case Studies using The Synthetic Control Method

    Language:Jupyter Notebook3201

  • cvas91/Cannabis_Legalization

    Prevalence of Cannabis Use Disorder Post Legalization – Uruguay Case Study (Synthetic Control Method)

    Language:Stata2100

  • justinjjlee/julia-SyntheticControl.jl

    julia implementation of Synthetic Control estimation

    Language:Julia2100

  • agoryuno/robust_control

    A PyTorch implementation of the "robust" synthetic control model

    Language:Python1200

  • alexanderthclark/Synthetic-Control-Simulation

    Using simulated data to understand synthetic control

    Language:Jupyter Notebook110

  • almagashi/Replication-and-Extension

    A replication of the paper "Democratization and Economic Output in Sub-Saharan Africa".

    Language:HTML1100

  • diodz/chile-middle-income-trap

    Source code to replicate the results of our article published in Revista de Historia Económica: Another case of the middle-income trap: Chile, 1900-1939

    Language:Python1002

  • jguerrae/Escape-Clauses_SynthControl

    This repository implements synthetic control methodology to estime the effect of active escape clauses on debt.

    Language:Jupyter Notebook1100

  • jvpoulos/homesteads

    Replication code for "State-Building through Public Land Disposal? An Application of Matrix Completion for Counterfactual Prediction"

    Language:R1401

  • kenki931128/synthx

    SynthX: A Python Library for Advanced Synthetic Control Analysis

    Language:Python11100

  • wenddymacro/SC

    Synthenic Control Method

    Language:Ruby1301

  • 15EkbergC/Synthetic-Control-for-Elon-Musk-Buying-Twitter

    Using the Synthetic Control method to effectively demonstrate the impact of Elon Musk purchasing Twitter on overall sentiment towards the company and on Twitter's stock price.

    Language:Jupyter Notebook0100

  • diloloan72/cs112

    My assignments and R projects for the CS112 course. Topics covered include Predictive and Causal Inference, Genetic and P-score Matching, Synthetic Control.

    Language:R00

  • diodz/disasters-economic-freedom

    Code for disasters projects, regressions and synthetic controls

    Language:Python0100

  • subhaskghosh/lockdown-paper

    The ongoing pandemic of coronavirus disease 2019-2020 (COVID-19) is caused by Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2). This pathogenic virus is able to spread asymptotically during its incubation stage through a vulnerable population. Given the state of healthcare, policymakers were urged to contain the spread of infection, minimize stress on the health systems and ensure public safety. Most effective tool that was at their disposal was to close non-essential business and issue a stay home order. In this paper we consider techniques to measure the effectiveness of stringency measures adopted by governments across the world. Analyzing effectiveness of control measures like lock-down allows us to understand whether the decisions made were optimal and resulted in a reduction of burden on the healthcare system. In specific we consider using a synthetic control to construct alternative scenarios and understand what would have been the effect on health if less stringent measures were adopted. We present analysis for The State of New York, United States, Italy and The Indian capital city Delhi and show how lock-down measures has helped and what the counterfactual scenarios would have been in comparison to the current state of affairs. We show that in The State of New York the number of deaths could have been 6 times higher, and in Italy, the number of deaths could have been 3 times higher by 26th of June, 2020.

    Language:Python0101

  • murattasdemir/synth_runner

    A tool to run a pool of synthetic controls, conduct inference, and produce visualizations.

    Language:Stata10

  • quarcs-lab/Tutorial-synthetic-control-methods-Felipe-thesis-chapter5

    This tutorial presents the analysis of the 5th chapter of my master thesis - "The Effect of Conditional Cash Transfer Policies on Crime: Evidence from a Synthetic Controls Framework" - Felipe Santos-Marquez

    Language:R103

  • sodascience/schools_synth_test

    Test code for disaggregated synthetic control with simulated data

    Language:R30