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Aguiar, Mark, Manuel Amador, and Gita Gopinath(2009): “Investment Cycles and Sovereign Debt Overhang,” Review of Economic Studies, 76(1): 1-31
Example of demographic transition in OLG model
交易成本下的因子模型检验Replication code for Detzel, Novy-Marx, and Velikov (2022), Model Comparison with Transaction Costs.
R-package accompanying the paper "Dynamic Factor Model for Functional Time Series: Identification, Estimation, and Prediction"
Dynamic Factor Models for R
Unofficial PyTorch implementation of the CVPR'19 paper "Skeleton-Based Action Recognition with Directed Graph Neural Networks".
Keeping track of what is going on with the latest DiD innovations.
Difference in Differences with Multiple Periods and Variation in Treatment Timing
Two-stage Difference-in-Differences package following Gardner (2021)
Two-Stage Difference-in-Differences following Gardner (2021)
R-code to compare some staggered did methods
Event studies: robust and efficient estimation, testing, and plotting
Code snippets from DiD Reading Group meetings
Difference-in-differences Imputation-based Estimator proposed by Borusyak, Jaravel, and Spiess (2021)
Implement of DiGCN, NeurIPS-2020
Short course on dimension reduction for AMSI
Pricing and estimation algorithms for affine jump diffusion models for divergence contracts (see Schneider and Trojani, ``Divergence and the Price of Uncertainty'')
Contains data and documentation for paper: "Valuing Private Equity Investments Strip by Strip" with Arpit Gupta and Stijn Van Nieuwerburgh
Deep Learning Statistical Arbitrage
✨新版大连理工Beamer主题 ✨一份简约现代的beamer模板 / PPT杀手 / 学术范入门
Approximate Bayesian computation with deep learning. A deep neural network inference with an rejection criterion.
This folder contains the R codes of Monte Carlo Simulation and empirical analysis in the paper "Dynamic Network Quantile Model"
Doing Applied Economics Research Mixtape Track
Dynamic (Optimal) shrinkage of portfolios!
DoubleML - Double Machine Learning in R
Doubly Robust Difference-in-Differences Estimators
Replication codes for Afrouzi and Yang (2019): "Dynamic Rational Inattention and the Phillips Curve"
A declarative, efficient, and flexible JavaScript library for building user interfaces.
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
An Open Source Machine Learning Framework for Everyone
The Web framework for perfectionists with deadlines.
A PHP framework for web artisans
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
Some thing interesting about web. New door for the world.
A server is a program made to process requests and deliver data to clients.
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
Some thing interesting about visualization, use data art
Some thing interesting about game, make everyone happy.
We are working to build community through open source technology. NB: members must have two-factor auth.
Open source projects and samples from Microsoft.
Google ❤️ Open Source for everyone.
Alibaba Open Source for everyone
Data-Driven Documents codes.
China tencent open source team.